*Cucurbita* **Rootstocks Improve Salt Tolerance of Melon Scions by Inducing Physiological, Biochemical and Nutritional Responses**

### **Abdullah Ulas 1,\*, Alim Aydin 2, Firdes Ulas 3, Halit Yetisir <sup>3</sup> and Tanveer Fatima Miano 3,4**


Received: 15 September 2020; Accepted: 12 October 2020; Published: 14 October 2020

**Abstract:** A hydroponic experiment was conducted to assess whether grafting with *Cucurbita* rootstocks could improve the salt tolerance of melon scions and to determine the physiological, biochemical, and nutritional responses induced by the rootstocks under salt stress. Two melon (*Cucumis melo* L.) cultivars (Citirex and Altinbas) were grafted onto two commercial *Cucurbita* rootstocks (Kardosa and Nun9075). Plants were grown in aerated nutrient solution under deep water culture (DWC) at two electrical conductivity (EC) levels (control at 1.5 dS m−<sup>1</sup> and salt at 8.0 dS m<sup>−</sup>1). Hydroponic salt stress led to a significant reduction in shoot and root growths, leaf area, photosynthetic activity, and leaf chlorophyll and carotenoid contents of both grafted and nongrafted melons. Susceptible plants responded to salt stress by increasing leaf proline and malondialdehyde (MDA), ion leakage, and leaf Na<sup>+</sup> and Cl<sup>−</sup> contents. Statistically significant negative correlations existed between shoot dry biomass production and leaf proline (r = −0.89), leaf MDA (r = −0.85), leaf Na<sup>+</sup> (r = <sup>−</sup>0.90), and leaf (r = 0.63) and root (r = <sup>−</sup>0.90) ion leakages under salt stress. Nongrafted Citirex tended to be more sensitive to salt stress than Altinbas. The *Cucurbita* rootstocks (Nun9075 and Kardosa) significantly improved growth and biomass production of grafted melons (scions) by inducing physiological (high leaf area and photosynthesis), biochemical (low leaf proline and MDA), and nutritional (low leaf Na<sup>+</sup> and ion leakage and high K<sup>+</sup> and Ca++ contents) responses under salt stress. The highest growth performance was exhibited by the Citirex/Nun9075 and Citirex/Kardosa graft combinations. Both *Cucurbita* cultivars have high rootstock potential for melon, and their significant contributions to salt tolerance were closely associated with inducing physiological and biochemical responses of scions. These traits could be useful for the selection and breeding of salt-tolerant rootstocks for sustainable agriculture in the future.

**Keywords:** photosynthesis; chlorophyll; proline; ion leakage; susceptibility

### **1. Introduction**

Salinity is the one of the major environmental stress factors limiting crop growth and productivity in many arid and semiarid regions, in spite of the advanced management techniques developed in recent decades [1]. Worldwide, up to 20% of arable land and up to 50% in irrigated areas is detrimentally affected by salinity, while in Turkey almost 4 million hectares of land has salinity problems [2]. As long as the current situation in salinization remains, half of the presently cultivated agricultural land may be lost by 2050 [3]. Crops that are grown under excessively saline conditions usually exhibit shorter life cycles or limited plant growth and biomass yield [4]. Internal damages and metabolic disturbances [5], ion toxicity [6], water deficiency in older leaves and carbohydrate deficiency in younger leaves [7], and reductions in root growth, nutrient uptake [8], photosynthetic activity [9,10], and protein synthesis are some of the major problems exhibited by crops grown under salt stress conditions.

As a horticultural crop, melon (*Cucumis melo* L.) has economic significance in the world due to its intensive and wide cultivation particularly in arid and semiarid regions. Global melon production was almost 31.6 million tons (Mt) in 2018 [11], and the main producing countries were China (16 Mt), Turkey (1.8 Mt), Iran (1.6 Mt), and Egypt (1.06 Mt). As melon is an arid and semiarid region crop, several studies have focused on the salt stress problems of melon and have determined that melon is a salt-sensitive or moderately tolerant crop in terms of yield and fruit quality characteristics [12,13]. To improve the salt tolerance of melon for sustainable agriculture production, integrated management strategies that take into consideration improved soil and crop management practices are necessary. Moreover, another way to avoid or reduce salt stress impacts and hinder yield losses in melon production affected by salt stress in high-yielding susceptible cultivars (as scions) would be to graft them onto resistant genotypes (as rootstocks) capable of improving the salt tolerance of the scions. Some studies [7–9] have revealed that *Cucurbita* genotypes exhibit salt tolerance and may therefore be used as rootstocks to improve the growth and yield of some horticultural crops (i.e., cucumber and melon) under salt stress. Grafting onto suitable rootstocks is an important technique in the horticultural area for the suitable cultivation of some Cucurbitaceae and Solanaceae species in Japan, Korea, China, and some other Asian and European countries [14]. Previously, other studies [15–18] were carried out to determine the contribution of grafting to several abiotic stress tolerance mechanisms of many plant species. However, no comprehensive hydroponic studies were found in the literature with regard to the salinity problem of melon plants. Therefore, the aim of the present study was to evaluate whether grafting with hybrid *Cucurbita maxima* × *Cucurbita moschata* rootstocks could improve the salt tolerance of melon scions and to determine the physiological, biochemical, and nutritional responses induced by *Cucurbita* rootstocks under hydroponic salt stress.

### **2. Materials and Methods**

### *2.1. Plant Material, Treatments, and Experimental Design*

A hydroponic trial was set up using an aerated deep water culture (DWC) technique in a fully automated climate room in the Plant Physiology Laboratory of Erciyes University's Faculty of Agriculture, Department of Soil Science and Plant Nutrition, in Kayseri, Turkey. For the vegetation period, the room temperatures were maintained at 25/22 ◦C (day/night) with a relative humidity of 65–70%. The supplied photon flux in the growth chamber was almost 350 μmol m−<sup>2</sup> S−<sup>1</sup> with an intensity of 16/8 h (light/dark) photoperiod. As plant materials, two melon cultivars [Galia type (Citirex F1) and standard type (Kirkagac Manisa Altinbas)] were used as scions, while two commercial *Cucurbita* hybrid (*Cucurbita maxima* × *C. moschata*) cultivars (Kardosa and Nun9075) were used as rootstocks. Maintaining homogeneity among the germinated seedlings is very crucial in a hydroponic study. Therefore, melon seeds were sown 1 week earlier than rapidly growing *Cucurbita* hybrid rootstocks' seeds in multipots containing a mixture of peat (pH: 6.0–6.5) and perlite in a 2:1 (*v*/*v*) ratio for 2 weeks. When the seedlings reached the stage of three or four true leaves, the melon scions were grafted by using the cleft grafting technique onto the *Cucurbita* rootstocks. As control plants, the nongrafted melon varieties were used. For the healing and acclimatization process, the grafted plants were transferred to double-layered and shaded plastic growth boxes and placed in the growth chamber for 7 days. When the healing and acclimatization process was completed, the grafted and nongrafted control plants were removed from the growth medium of the multipots. The roots were washed without root damage, and the stem of each seedling was carefully covered with a thin sponge. After that, each seedling was placed onto the cover of 8 L plastic pots filled with nutrient solution (modified

Hoagland) in the fully automated climate chamber. The sufficiently dissolved oxygen (8.0 mg/L) in nutrient solution was supplied by using a continuously working air pump.

The trial was set up in a completely randomized block design (RBD) with four replicated blocks and two plants of each ungrafted cultivar and cultivar by rootstock combination in each block treated with one of two different electrical conductivity (EC) levels (control at 1.5 dS m−<sup>1</sup> and salt at 8.0 dS m<sup>−</sup>1). The salt stress was created by adding NaCl in nutrient solution. The salt application was done gradually in an increasing manner (2 dS/m per day) 5 days after transplanting. The total growth period of the plants from transplant into 8 L plastic pots to final harvest was 42 days after treatment (DAT). To prepare the nutrient solution for the hydroponic experiment, analytical grade (99% pure) chemicals with distilled water were used according to the Hoagland (modified) formulation. In the solution, 2000 μM nitrogen was supplied by using 75% calcium nitrate (Ca(NO3)2) and 25% ammonium sulfate ((NH4)2SO4) as the N sources. Moreover, the composition of the basic nutrient solution was as follows (μM): CaSO4 (1000), K2SO4 (500), MgSO4 (325), KH2PO4 (250), NaCl (50), H3BO3 (8.0), Fe-EDDHA (80), ZnSO4 (0.4), CuSO4 (0.4), MnSO4 (0.4), MoNa2O4 (0.4). All the nutrients were replaced to prior concentrations when the N concentration in the solution fell from 2.0 mM to below 1.0 mM. Daily nitrogen concentration was checked by nitrate test strips (Merck, Darmstadt, Germany) with the aid of a NitracheckTM reflectometer. Distilled water was added every 2 days to replenish the water lost to evaporation, and the solution was changed weekly.

### *2.2. Harvest, Shoot, and Root Dry Weight Measurements*

At the final harvest, the plants were separated into leaves, stems, and roots. To determine the dry biomass, plant tissues were dried in a forced-air oven at 70 ◦C for 72 h. They were then weighed on an electronic digital scale. The sum of aerial vegetative plant parts (leaves + stems) is equal to total shoot biomass. To calculate the shoot-to-root ratio, the sum of leaf and stem dry weights was divided by the total root dry weight.

### *2.3. Leaf Area and Photosynthetic Activity Measurements*

Prior to the harvest, nondestructive measurements of the leaf-level CO2 gas exchange (μmol CO2 m−<sup>2</sup> s<sup>−</sup>1) were performed using a portable photosynthesis system (LI-6400XT; LI-COR Inc., Lincoln, NE, USA). The leaf net photosynthesis measurement (photosynthetically active radiation (PAR) = 1000 μmol m−<sup>2</sup> s<sup>−</sup>1, CO2 at 400 μmol mol<sup>−</sup>1) was performed on the youngest fully expanded leaves, using four replicate leaves per treatment in the third and fifth weeks of the growth period. Leaf area of the plants was measured destructively during the harvesting process by using a portable leaf-area meter (LI-3100, LI-COR. Inc., Lincoln, NE, USA). Total leaf area was recorded as cm2.

### *2.4. Leaf Total Chlorophyll and Carotenoid Content Measurements*

A day before harvesting, 100 mg of fresh leaf samples from each replication of the two treatments was taken to measure the leaf total chlorophyll and carotenoid contents using UV–VIS spectroscopy. The samples were put into 15 mL capped containers where 10 mL of 95% (*v*/*v*) ethanol was added. Afterward, to allow for the extraction of the leaf pigments, the samples were held overnight in darkness at room temperature. Measurements were done using a spectrometer (UV/VS T80+, PG Instruments Limited, UK) at wavelengths of 470, 648.6, and 664.2 nm. Total chlorophyll (a-Total-Chlo) and total carotenoids (b-TC) were estimated from the spectrometric readings using the formulae described by Lichtenthaler [19]:


(Note: WL470, WL648.6, and WL664.2 refer to spectrometric readings at wavelengths 470, 648.6, and 664.2 nm, respectively).

### *2.5. Proline Contents and Lipid Peroxidation Measurements*

The proline contents were measured according to the method described by Bates et al. [20]. To homogenize the plant material, 3% aqueous sulfosalicylic acid was used. After centrifugation of the homogenate mixture at 10,000 rpm, the proline contents were determined in supernatant. To prepare the reaction mixture, 2 mL of acid ninhydrin and 2 mL of glacial acetic acid were used and then boiled at 100 ◦C for 1 h. Afterwards, the reaction was terminated in an ice bath. For the extraction of the reaction mixture, 4 mL of toluene was used, and then the absorbance was read at 520 nm. Membrane lipid peroxidation was characterized by the main product of lipid peroxidation, the malondialdehyde (MDA) concentration, which was determined according to the method described by Lutts et al. [21].

### *2.6. Leaf and Root Electrolyte Leakage Measurements*

Electrolyte leakage (EL) in leaves and roots was measured according to the method described by Lutts et al. [22]. The youngest fully expanded leaves were used for the EL measurements in between 1100 and 1500 h every 48 h with three replications per treatment. Leaf disks (1 cm2) were excised from young fully expanded leaves using a cork borer. To clean leaf surface contamination, samples were washed three times with distilled water. Afterwards, the samples were placed in individual stoppered vials containing 10 mL of distilled water.

EL determination in plant roots was done by taking fresh root tips (2 cm in length) from each treatment at the final harvest. The root samples containing 10 mL of distilled water were placed on a shaker (100 rpm) for 24 h at room temperature (25 ◦C) for incubation. After incubation, the first electrical conductivity (EC1) reading in the solution was performed. After a while, the same samples were placed in an autoclave at 120 ◦C for 20 min. After termination of the autoclave process, the samples were left at room temperature for cooling, and then the second electrical conductivity (EC2) reading was performed in the solution. The EL was expressed as EL = (EC1/EC2) × 100.

### *2.7. Mineral Analysis Measurements*

To determine mineral element composition, 0.5 g dried leaf tissues were used. Potassium (K+), calcium (Ca++), and sodium (Na+) contents were measured by dry ashing at 400 ◦C for 4.5 h. After that, the ash samples were dissolved in 5 mL of 20% (*v*/*v*) HCl, which was then filtered. The filtered solutions were then diluted with distilled water to a volume 50 mL. An amount of 10 mL was used for inductively coupled plasma atomic emission spectroscopy (ICP-AES) analysis. The ICP-AES results were converted into percentages (%) and parts per million (ppm). Chloride (Cl−) was determined by precipitation as AgCl and titration according to the method described by Johnson and Ulrich [23].

### *2.8. Statistical Analysis*

Statistical analysis of the data was performed using the PROC GLM procedure of the SAS Statistical Software (SAS for Windows 9.1, SAS Institute Inc., Cary, NC, USA). A two-factor analysis of variance was performed to study the effects of genotype or grafting combination and salt and their interactions on the variables analyzed. The levels of significance are represented at *p* < 0.05 (\*), *p* < 0.01 (\*\*), *p* < 0.001 (\*\*\*), or n.s. as not significant (*F*-test and Pearson correlation coefficients). Differences between the treatments were analyzed using Duncan's multiple range test (*p* < 0.05).

### **3. Results**

### *3.1. Results and Discussion*

### 3.1.1. Changes in Shoot and Root Biomass Productions and Partitioning

The results indicated that shoot and root dry matter and the shoot-to-root ratio of melon plants were affected significantly (*p* < 0.001) by salt, graft combination, and salt × graft combination interaction (Table 1). Irrespective of the graft combinations, shoot and root growths were affected detrimentally by hydroponic salt stress, and thus significant reductions were found in shoot (49.9%) and root (17.6%) dry matter and shoot-to-root ratio (45.8%) of melon plants under salt stress as compared with the control conditions. It is well-known that crop growth decreased with rising salinity level. Corroborative results were demonstrated in several studies conducted with melon [4,9], watermelon [24,25], cucumber [8], tomato [26], eggplant [27], and pepper [10] under salt stress. Our results clearly indicated that grafting with the *C. maxima* × *C. moschata* hybrid rootstocks had pronounced positive effects on the improvement of growth of melon scions under control and particularly salt stress conditions.

**Table 1.** Shoot and root dry weight and shoot-to-root ratio of melon graft combinations under control (1.5 dS m<sup>−</sup>1) and salt stress (8.0 dS m−1) conditions.


<sup>z</sup> Values denoted by different letters are significantly different between graft combinations within columns at *p* < 0.05. Significance of main and interaction effects *F* values: *p* < 0.05 (\*), *p* < 0.01 (\*\*), and *p* < 0.001 (\*\*\*).

Significant differences were found between the two melon cultivars and their graft combinations. Nongrafted Citirex showed significantly higher shoot dry matter than nongrafted Altinbas under control conditions, whereas both melon cultivars did not differ significantly in shoot dry matter under salt stress (Table 1). However, shoot dry matter reductions of Citirex (78.5% decline) tended to be more than those of Altinbas (59.2% decline) under salt stress. This might be due to root morphological differences between the two melon cultivars. Nongrafted Altinbas showed a significantly higher root dry matter than Citirex under salt stress (Table 1). Furthermore, Altinbas exhibited similar root dry matter as Nun9075 and Kardosa rootstocks under salt stress. These indicated that Altinbas has a vigorous root system compared with Citirex. The shoot dry matter of Citirex was increased by 288.8% in Citirex/Nun9075 and 257.7% in Citirex/Kardosa graft combinations, whereas the increase in the shoot dry matter of Altinbas was 130.1% in Altinbas/Nun9075 and 158.3% in Altinbas/Kardosa graft combinations under salt stress.

This was also shown by the significantly higher shoot-to-root ratios of Citirex/Nun9075 and Citirex/Kardosa graft combinations under salt stress. The graft combination Altinbas/Nun9075 and nongrafted Altinbas showed significantly lower shoot-to-root ratios in control and salt stress conditions. All the results clearly indicated that grafting with the *Cucurbita maxima* × *C. moschata* hybrid rootstocks significantly improved the salt tolerance of both melon (scions) cultivars. However, the contribution of both rootstocks to salt tolerance was much higher for Citirex (high sensitivity) than for Altinbas (less sensitivity). Grafted plants usually have strong and vigorous root systems [24], and thus, improved crop growth performance of grafted melons might be the result of more water and nutrient uptake that caused an increase in leaf area and photosynthetic activity of leaves under salt stress.

3.1.2. Changes in Leaf Area, Photosynthesis, Chlorophyll, and Carotenoid Contents

The results indicated that the leaf area, photosynthetic activity of leaves, total chlorophyll content, and carotenoid content of melon plants were affected significantly by salt and graft combination

(Table 2). An interaction between salt and graft combination was found only in the total leaf area and carotenoid content. Irrespective of the graft combinations, similar shoot and root biomass reductions under salt stress led to a significant decline in leaf area formation (49.1%), photosynthesis (9.1%), chlorophyll content (14.8%), and carotenoid content (20.4%) of melon plants. This also explains why the shoot and root dry biomass productions (Table 1) of both melon cultivars and their graft combinations were detrimentally affected by hydroponic salt stress, since crop biomass production and yield is strongly dependent on leaf area formation and leaf photosynthetic activity [28]. Our results also correspond to those from the study of Colla et al. [24], who found that salinity decreased the photosynthesis of grafted and nongrafted watermelon plants grown in a hydroponic system. Similar results were also demonstrated with grafted and nongrafted pepper plants under saline conditions [10].


**Table 2.** Leaf area, photosynthesis, chlorophyll content (a+b), and carotenoid content of melon graft combinations under control (1.5 dS m<sup>−</sup>1) and salt stress (8.0 dS m−1) conditions.

<sup>z</sup> Values denoted by different letters are significantly different between graft combinations within columns at *p* < 0.05. Significance of main and interaction effects *F* values: *p* < 0.05 (\*), *p* < 0.01 (\*\*), and *p* < 0.001 (\*\*\*), with n.s. meaning not significant.

That study showed that the photosynthetic activity of pepper leaves decreased as a result of the reduction in chlorophyll and carotenoid contents as salinity level increased in nutrient solution. Similar to our study, a substantial decline in the chlorophyll content of leaves was reported for several horticultural species, such as melon [5] and tomato [26], under salt stress conditions. Furthermore, significant variations existed between grafted and nongrafted melon plants regarding measured parameters at control and salt stress conditions (Table 2). The grafted melons produced 16.3% and 93.43% higher leaf area than the nongrafted melons under control and salt stress conditions, respectively. This clearly indicated that the rootstock contributions to leaf area development of scions (melon) were substantially higher under salt stress than under control conditions. As a result, the reduction in the total leaf area of nongrafted melons was 65.2%, whereas the reduction in grafted melons was only 42.2%. The grafted melons showed 11.7% higher photosynthetic activity than the nongrafted ones under salt stress. This might be due to higher chlorophyll (7.4%) and carotenoid contents (9.4%) of the grafted melons as compared with the nongrafted ones under salt stress. Our results corroborated those of a study that showed that the leaf area of nongrafted watermelon (cv. Tex) was significantly improved when it was grafted onto two commercial rootstocks, Macis [*Lagenaria siceraria* (Mol.) Standl.] and Ercole (*Cucurbita maxima* Duchesne × *Cucurbita moschata* Duchesne), under salt stress conditions [20].

In our study, significant genotypic variation existed regarding leaf area formation between the two nongrafted melon cultivars under salt stress. Under control conditions, Altinbas and Citirex had similar leaf areas, whereas significantly higher total leaf area was exhibited by Altinbas than Citirex under salt stress. This clearly indicated a significant genotype × salt interaction. The Altinbas total leaf area was reduced by 54.1% under salt stress, whereas the reduction in total leaf area of Citirex was 74.9%. As shown by shoot and root dry matter productions (Table 1), Altinbas can be characterized as a salt-tolerant cultivar due to maintaining high leaf area under salt stress as compared with the salt-sensitive cultivar Citirex (Table 2). On the other hand, the salt-sensitive cultivar Citirex exhibited significantly higher leaf area formation, photosynthetic activity, leaf chlorophyll content, and carotenoid content when it was grafted on Nun9075 and Kardosa rootstocks under salt stress. Although similar rootstock contributions to leaf area formation, photosynthesis, total leaf chlorophyll content, and carotenoid content were recorded with Altinbas/Nun9075 and Altinbas/Kardosa graft combinations under salt stress, the increases were lower than those in graft combinations with Citirex. These results clearly indicated that the two melon cultivars had contrasting salt tolerances (Citirex: sensitive, Altinbas: tolerant) and therefore responded significantly differently when they were grafted with both tolerant rootstocks.

### 3.1.3. Changes in Proline, Lipid Peroxidation, and Root and Leaf Ion Leakages

The proline content (Figure 1A), lipid peroxidation (MDA) (Figure 1B), and ion leakages in roots (Figure 1C) and leaves (Figure 1D) of melon plants were affected significantly (*p* < 0.001) by salt, graft combination, and salt × graft combination interaction. Regardless of the graft combination, salt stress led to a significant increase in proline (59.1%) and MDA (31.3%) contents and leaf (56.8%) and root (36.7%) ion leakages of salt-treated melons as compared with controls (Figure 1A–D). These are common responses of plants that usually exhibit tolerance strategies as shown in studies with melon [29], cucumber [30], pepper [10,31], and tomato [32]. However, there were significant differences between grafted and nongrafted melons regarding biochemical responses under both control and salt stress conditions (Figure 1A–D). Irrespective of the cultivars, grafted melons produced 24.4%, 2.9%, 0.53%, and 9.1% lower proline, MDA, leaf ion leakage, and root ion leakage, respectively, than nongrafted melon plants under control conditions. Similar contributions of rootstocks to the biochemical responses of melon plants were also observed under salt stress. However, the plants responded much more under salt stress, such that grafted melons produced 27.6%, 29.6%, 13.5%, and 13.2% lower proline, MDA, leaf ion leakage, and root ion leakage, respectively, than nongrafted melon plants. Our results clearly indicated that grafting with the *Cucurbita maxima* × *C. moschata* rootstocks had pronounced contributions to the biochemical responses of the scions (melon) under both control and salt stress conditions. Similar results were observed when the experiment was conducted using different Iranian melon landraces [29].

Nongrafted Altinbas showed significantly higher proline, MDA, and leaf ion leakage than Citirex under control conditions, whereas the root ion leakage of Altinbas was significantly lower than that of Citirex. Without salt stress, significantly lower root ion leakage could be the result of the vigorous root system of Altinbas (Table 1), which leads to its characterization as salt tolerant. However, under salt stress, opposite results were found between the two melon cultivars. Citirex showed significantly higher proline, slightly higher MDA, and significantly higher root ion leakage than Altinbas. This might be due to the sensitivity of the response of Citirex to salt stress. This was confirmed by the results, which revealed that Citirex had increased proline, MDA, leaf ion leakage, and root ion leakage by 231.6%, 80.3%, 91.6%, and 32.7%, respectively, whereas the increase in proline, MDA, leaf ion leakage, and root ion leakage of Altinbas was 97.3%, 43.6%, 58.2%, and 50.1%, respectively, under salt stress as compared with control conditions. Similarly, greater responses were exhibited by Citirex in shoot and root growth (Table 1), leaf area formation, photosynthesis, and photosynthetic pigment contents (Table 2) under salt stress.

**Figure 1.** Leaf proline (**A**), malondialdehyde (MDA) (**B**), leaf ion leakage (**C**), and root ion leakage (**D**) of melon graft combinations under control (1.5 dS m<sup>−</sup>1) and salt stress (8.0 dS m−1) conditions. Values denoted by different letters are significantly different between graft combinations within columns. Significance of main and interaction effects *F* values: *p* < 0.05 (\*), *p* < 0.01 (\*\*), and *p* < 0.001 (\*\*\*).

All of the results clearly indicated that Citirex is a salt-sensitive cultivar, whereas Altinbas is a salt-tolerant cultivar. Our results corroborate those from the study of Yasar et al. [27], who concluded that MDA content in leaf tissues of salt-tolerant eggplant genotypes was twofold lower than that of salt-sensitive eggplant genotypes under salt stress. Similar results were also demonstrated by the study of Lutts et al. [21], who elucidated that MDA content was lowest in salt-tolerant rice genotypes, whereas a salt-sensitive rice genotype exhibited the highest MDA content under salt stress.

Interestingly, irrespective of the cultivar, the proline, MDA, leaf ion leakage, and root ion leakage were significantly reduced when they were grafted with Nun9075 and Kardosa rootstocks under salt stress (Figure 1A–D). Although significant reductions existed when Altinbas was grafted onto both rootstocks, significantly lower proline, MDA, leaf ion leakage, and root ion leakage were exhibited only in Citirex/Nun9075 and Citirex/Kardosa graft combinations under salt stress. One of the indicators of tolerance to salt stress is low absolute or proportional ion leakages, which was demonstrated in studies conducted with rice [21], cucumber [30], pepper [31], tomato [32], and melon [29]. Our results again confirmed that grafting with tolerant *Cucurbita maxima* × *C. moschata* rootstocks had pronounced positive effects on the biochemical responses that contribute to the tolerance mechanisms of sensitive scions (melons) under salt stress.

### 3.1.4. Changes in Leaf Na+, Cl−, K+, and Ca++ Uptakes

The leaf Na+, Cl−, K+, and Ca++ uptakes of melon plants was significantly (*p* < 0.001) affected by salt, graft combination, and salt × graft combination interaction (Table 3). Irrespective of the graft combination, leaf Na<sup>+</sup> and Cl<sup>−</sup> concentrations of melon plants increased by 1137.5% and 1392.3%, respectively, under salt stress as compared with control conditions. It is well-known that Na<sup>+</sup> and Cl− uptakes of leaves increase with increasing salinity level. A study by Colla et al. [8] demonstrated that the Cl− concentration of cucumber leaves increased by 300% with salt application regardless of genotype. Similar increases in Na<sup>+</sup> and Cl<sup>−</sup> concentrations in leaves have been reported in melon [33], watermelon [25], and pumpkin [6] grown under salt stress. However, we observed significant differences between grafted and nongrafted melons regarding leaf Na<sup>+</sup> and Cl<sup>−</sup> uptakes under both control and salt stress conditions (Table 3).

**Table 3.** Leaf Na+, Cl−, K+, and Ca++ contents of melon graft combinations under control (1.5 dS m<sup>−</sup>1) and salt stress (8.0 dS m<sup>−</sup>1) conditions.


<sup>z</sup> Values denoted by different letters are significantly different between graft combinations within columns at *p* < 0.05. Significance of main and interaction effects *F* values: *p* < 0.05 (\*), *p* < 0.01 (\*\*), and *p* < 0.001 (\*\*\*).

Irrespective of the cultivars, grafted melons exhibited 58.1% and 19.8% lower Na<sup>+</sup> and Cl<sup>−</sup> uptakes, respectively, than nongrafted melon plants under control conditions. Similar contributions of rootstocks to Na<sup>+</sup> exclusion were observed, whereas an opposite response was observed in Cl<sup>−</sup> uptake in grafted plants under salt stress. Consequently, the grafted melons exhibited 52.1% lower Na<sup>+</sup> uptake than the nongrafted ones under salt stress. However, under the same conditions, the grafted plants showed the opposite, a higher Cl− uptake (28.7%) than that of the nongrafted melon plants. Excluding the toxic ion in roots and retaining salt in the root and not transporting it to shoots are known biochemical responses of salt-tolerant genotypes [34,35]. In agreement with this characterization, our results clearly confirmed that with the two tolerant *Cucurbita maxima* <sup>×</sup> *C. moschata* rootstocks, Na<sup>+</sup> uptake might be excluded by the roots, and thus the leaf Na<sup>+</sup> content of the scions (melon) was significantly reduced under salt stress. On the other hand, higher leaf Cl− uptake of the grafted plants than that of the nongrafted plants disagrees with the salt tolerance characterization studies of Acosta-Motos et al. [34] and Zhu and Bie [35]. However, the study of Colla et al. [33] reported that grafted melon plants had higher leaf Cl− contents than nongrafted ones under salt stress, which was corroborated by our results. In our study, this result might be due to maintenance of a higher leaf area and photosynthetic activity (Table 2) of the grafted melon plants as compared with the nongrafted ones under salt stress. Chloride can play an essential role in photosynthetic activity by controlling stomatal conductance [36] and osmoregulation [37]. Therefore, the increase in leaf area of the grafted melons with high chloride uptake may be a result of enhancement in cell division rates and cell extension [38].

Irrespective of the graft combination, the leaf K<sup>+</sup> concentration of the melon plants was reduced by 20.1%, whereas the leaf Ca++ concentration increased by 353.3% under salt stress as compared with that under control conditions. The reduction in leaf K<sup>+</sup> uptake under salt stress could be the result of high Na<sup>+</sup> uptake, which usually causes a disruption in ion activities [39] and a specific competition with K<sup>+</sup> for binding sites [40]. Moreover, highly significant differences were found between grafted and nongrafted melon plants regarding leaf Na+, K+, and Ca++ uptakes under salt stress. As compared with nongrafted melon cultivars, leaf Na<sup>+</sup> uptake was significantly reduced (52.1%), whereas leaf K<sup>+</sup> (75.1%) and Ca++ (123.2%) uptakes significantly increased in all graft combinations under salt stress. This indicates that the increase in leaf K<sup>+</sup> might be the result of indirect contributions of substantial Ca++ uptake of the grafted plants under salt stress. High Ca++ content can maintain membrane stability in roots and leaves by limiting the adverse effects of Na<sup>+</sup> ions on the membrane [41] and leads to decreased Na<sup>+</sup> uptake and increased K<sup>+</sup> uptake [42]. Yetisir and Uygur [43] reported that *Cucurbita* and *Lagenaria* rootstocks expressed mechanisms to avoid physiological damage caused by excessive accumulation of Na<sup>+</sup> ion in leaves and hence showed higher performance than watermelon under salinity stress. In agreement with this study, our results clearly indicated that grafting with two tolerant *Cucurbita maxima* <sup>×</sup> *C. moschata* rootstocks (Nun9075 and Kardosa) led to an increase in leaf K<sup>+</sup> and Ca++ ions and hence caused a decline in the leaf Na<sup>+</sup> ion of the two melon cultivars under salt stress. This might be a useful strategy for preserving membrane stability and maintaining K<sup>+</sup> balance for increasing the tolerance of plants to salt stress [44].

3.1.5. Correlation between Shoot and Root Growths and the other Parameters under Salt Stress

Irrespective of the graft combination, the correlation coefficients between shoot and root dry biomass productions, leaf area formation, and the other parameters of melon plants under salt stress conditions are shown in Table 4. Shoot dry weight and leaf area of salt stress plants were significantly negatively correlated with leaf proline, leaf MDA, leaf Na+, and leaf and root ion leakages. Similar negative correlations between root dry matters were recorded only with leaf MDA and root ion leakage.


**Table 4.** Irrespective of the graft combination, the correlation coefficients between shoot and root dry biomass productions, leaf area formation, and other parameters of melon plants under salt stress (8.0 dS m<sup>−</sup>1) condition.

<sup>z</sup> Levels of significance are represented by *p* < 0.05 (\*), *p* < 0.01 (\*\*), and *p* < 0.001 (\*\*\*) with n.s. meaning not significant (Pearson correlation coefficient, *n* = 18).

On the other hand, all physiological (leaf area, photosynthesis, and chlorophyll and carotenoid contents) and nutritional (leaf K, Ca, and Cl) parameters were significantly positively correlated with shoot dry weight and leaf area under salt stress. All of these results clearly indicated that salt tolerance was closely associated with high shoot biomass production with an extensive photosynthetically active leaf area formation, but conversely with substantially lower leaf proline, leaf MDA, leaf Na+, and leaf and root ion leakages. This might be due to common tolerance responses of grafted plants that were usually exhibited as salt tolerance strategies in studies carried out with rice [21], melon [29], cucumber [30], pepper [10,31], and tomato [32].

### **4. Conclusions**

One of the most prevalent abiotic stress factors, salinity usually has harmful effects on crop productive capacity by decreasing yield and quality, particularly in arid and semiarid regions of the world. To solve this problem, grafting with salt-tolerant rootstocks can be an effective management strategy for improving the salt tolerance of crop plants. In this short-term hydroponic experiment, two melon cultivars were grafted onto two different commercial *Cucurbita maxima* × *C. moschata* hybrid rootstocks to assess plant growth performance under control (1.5 dS m<sup>−</sup>1) and salt stress (8.0 dS m–1) conditions. Results indicated that the shoot and root growths of grafted and nongrafted melon plants were detrimentally affected by salt stress. Significant reductions were recorded in some agronomic and physiological plant responses under salt stress. On the other hand, susceptible plants responded to salt stress by increasing leaf proline and malondialdehyde (MDA), ion leakage, and leaf Na<sup>+</sup> and Cla− contents. As a result, significant negative correlations existed between shoot dry biomass production and leaf proline (r: <sup>−</sup>0.89 \*\*\*), leaf MDA (r: <sup>−</sup>0.85 \*\*\*), leaf Na<sup>+</sup> (r: <sup>−</sup>0.90 \*\*\*), leaf ion leakage (r: 0.63 \*), and root ion leakage (r: −0.90 \*\*\*) under salt stress. The two melon cultivars differed significantly in salt tolerance. Nongrafted Citirex tended to be more sensitive than Altinbas to salt stress. The *Cucurbita* rootstock genotypes (Nun9075 and Kardosa) significantly improved the growth and biomass production of the grafted melon scions by inducing physiological (high leaf area and photosynthesis), biochemical (low leaf proline and MDA), and nutritional (low leaf Na and ion leakages and high K<sup>+</sup> and Ca++) responses under salt stress. The highest plant growth performance was exhibited by Citirex/Nun9075 and Citirex/Kardosa graft combinations. All of these suggest that these *Cucurbita* cultivars have a high rootstock potential for melon, and their significant contributions to salt tolerance were closely associated with inducing beneficial plant physiological and biochemical responses of melon scions. Consequently, these traits could be useful for the selection and breeding of salt-tolerant rootstocks for sustainable agriculture in the future.

**Author Contributions:** Conceptualization, A.U. and H.Y.; methodology, A.U., A.A., and H.Y.; software, A.U. and H.Y.; validation, A.A., F.U., and T.F.M.; formal analysis, A.U. and H.Y.; investigation, A.U., A.A., F.U., T.F.M., and H.Y.; resources, A.U. and H.Y.; data curation, A.U. and H.Y; writing—original draft preparation, A.U., A.A., and F.U.; writing—review and editing, A.U., F.U., and H.Y.; visualization, A.A., F.U., and T.F.M.; supervision, H.Y.; project administration, A.U. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** We would like to thank all the staff members of the Plant Physiology Laboratory of Erciyes University, Turkey, for their technical support and for supplying all facilities during the experiments.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

### **References**


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## *Article* **The E**ff**ects of Gibberellic Acid and Emasculation Treatments on Seed and Fruit Production in the Prickly Pear (***Opuntia ficus-indica* **(L.) Mill.) cv. "Gialla"**

### **Lorenzo Marini 1,\*, Chiara Grassi 1, Pietro Fino 1, Alessandro Calamai 1, Alberto Masoni 1, Lorenzo Brilli <sup>2</sup> and Enrico Palchetti <sup>1</sup>**


Received: 26 June 2020; Accepted: 12 August 2020; Published: 17 August 2020

**Abstract:** Prickly pear (*Opuntia ficus-indica* (L.) Mill. 1768) is cultivated in several dry and semi-dry areas of the world to produce fresh fruit, bioenergy, cosmetics, medicine, and forage. One of the main production constraints is the presence of many seeds within the fruit, which can negatively influence both the fresh-fruit market price and industrial transformation processes. In this study, different gibberellic acid (GA3) concentrations were tested for their ability to produce well-formed and seedless fruits. Different application methods (injection and spraying) and concentrations of GA3 (0, 100, 200, 250, and 500 ppm) combined with floral-bud emasculation were applied to a commercial plantation in southern Italy to evaluate their effects on the weight, length, and diameter of the fruits, total seed number, hard-coated viable seed number, and seed weight per fruit. The results indicated that the application of 500 ppm GA3 sprayed on emasculated floral buds was the most effective method for reducing seed numbers of prickly pear fruits (−46.0%). The injection method resulted in a very low number of seeds (−50.7%) but produced unmarketable fruit. Observed trends suggest the need to investigate the impact of higher GA3 concentrations and the applicability of a maximum threshold. Further studies are needed to increase our understanding of the physiological effects of the gibberellic acid pathway through productive tissue in terms of organoleptic and fruit quality.

**Keywords:** cactus pear; GA3; injection application; spraying application; lignification

### **1. Introduction**

Prickly pear (*Opuntia ficus-indica* (L.) Mill.) is the most cultivated plant species in the Cactaceae family due to edible fruit production [1]. It is a bushy-shaped, xerophytic, and crassulacean acid metabolism (CAM) plant originating from dry areas of Mexico [2]. The annual global production of prickly pear is approximately 500,000 tons, and Italy supplies 12% of the total market, preceded by Mexico and followed by Israel [3,4]. According to the Food and Agriculture Organization (FAO), in the last few years, prickly pear cultivation has gained a considerable amount of interest in relation to coping with food security issues in mostly dry and semi-dry regions, such as in South America, Africa, and the Mediterranean basin, thanks to its high resistance to drought and the important nutritional compounds present in the fruits [2,5]. Despite numerous species of the *Opuntia* genus being mainly cultivated to produce fresh fruit, this cultivation can play a key role in other contexts, such as environmental defense, forage and bioenergy production, the medicine and cosmetics sectors, and human health [1,6–8]. For instance, in some tropical agroforestry systems, *Opuntia elatior* (Mill.) and *O. ficus-indica* are cultivated in association with other crops [9,10], as a productive living fence guarding against desertification [11,12]. In Africa and South America, the association of *Opuntia robusta* (J.C. Wendl) and *O. ficus-indica* var. *inermis* provide both living fences and livestock fodder [7,13]. Species such as *Opuntia maxima* (Mill.), *Opuntia heliabranoava* (Scheinvar), and *O. ficus-indica* are currently studied for biogas and fertilizer production, especially when associated with domestic plants in rural areas that are situated off of the energy grid [8,14–16]. *O. ficus-indica* has also been recently studied for medical and nutritional purposes since its juice has been found to show nutraceutical activities [17] and beneficial properties against specific types of cancer cells (bladder, ovarian, and leukemia) [18–20].

The *Opuntia ficus-indica* fruit is a false berry with an average weight of approximately 100–120 g, of which 2–10% is seeds and 60–70% is pulp [21]. *Opuntia ficus-indica* fruits present polyembrionatic seeds and 40–45% of them are aborted [22,23], while the remaining 60–55% are viable hard-coated seeds. This represents one of the main production challenges, which can influence the market price, because fruits with few or abortive seeds are more appreciated by consumers [24]. Abundant hard-coated seeds also complicate industrial processes, negatively impacting the transformation of fruit into such products as juice, nectars, jam, and food coloring [25–27], and potentially affecting consumer health by causing constipation [28–30]. However, whilst in other species such as citrus, the pulp development is not strictly linked with seed presence, in *Opuntia ficus-indica*, fruit pulp development depends on the funiculus of the seeds [31,32]. The funiculi are needed to produce a commercially acceptable pulp volume; however, a higher number of abortive seeds, characterized by their smaller size, would be more acceptable to consumers. The creation of hybrid types characterized by a good balance between these two latter aspects (i.e., high volume pulp—less number of seeds) would be feasible primarily through genetic breeding programs and agronomic techniques. The application of the first approach [31,33,34] is not economically viable and has resulted in poor fruit performance. By contrast, agronomic techniques, such as spring flushing or growth regulator treatments to inhibit seed growth, especially with auxin and/or gibberellins, may easily and more quickly provide well-formed and seedless fruits [2]. In the last decades, a few studies investigated the use of a phytoregulator on prickly pear [35–38]. For instance, Gil et al. [36] showed that the treatment of emasculated floral buds using gibberellic acid (GA3) at 200 ppm increased both the development of ovular tissue and the funiculus, but also the hard-coated abortive seeds. Barbera et al. [35] indicated that at least 200 ppm of GA3 injected into *Opuntia*'s stem (cladode) underneath the fruit was able to decrease the percentage of regular seeds. Mejía et al. [38], comparing the use of GA3 by injection and spray application at different maturation stages, indicated the best performances using a 100 ppm GA3 injection in pre- and postblooming. Kaaniche-Elloumi [23] also reported that the number and timing of GA3 applications can affect fruit and seed development.

In this study, we tested the application of two methods (injection and spraying) of gibberellic acid (GA3) on cactus prickly pear both at pre- and postblooming in order to obtain well-formed seedless fruits in emasculated flowers. Increased GA3 concentrations and floral-bud emasculation techniques were also applied to evaluate fruit weight, length, and diameter; and seed weight, the total number of seeds, and the number of hard-coated viable seeds per fruit.

### **2. Materials and Methods**

### *2.1. Study Area*

The experiments were conducted in the spring–summer of 2016 in a prickly pear orchard located in the Apulia region, southern Italy (41◦35 58" N, 15◦45 25" E). The soil is sub-alkaline and shallow, with a calcareous bedrock substrate [39]. The regional climate is typically Mediterranean, with dry summers and mild winters. Average yearly rainfall is approximately 400 mm, with the lowest precipitation occurring in July and August. Air temperature maximums occur in August and July (~30 ◦C) and the minimum in January and February (~3 ◦C). During the experiments, the recorded maximum daily temperature was 39.1 ◦C, while the lowest rainfall (21 mm) was observed in July [40].

The field experiment was a 4-hectare, 10-year-old orchard with a density of 2.000 plants/ha, characterized by globe-shaped growth and a north–south row-oriented axis. The orchard was under organic management, with no irrigation and a permanent grass cover between rows.

### *2.2. Experimental Design*

The experiment was conducted on *O. ficus-indica* cv. "Gialla", an Italian cultivar [41]. Combination treatments consisted of two randomized blocks to investigate both the effect of flower emasculation and the application of different concentrations of GA3. Floral buds (N◦ = 360) were treated and examined, considering five floral buds for each plant. Fifty percent of the floral buds were emasculated (EM), while the rest were left intact (IN). Emasculation was performed 24 h before the first gibberellic acid application, in the morning (6:00–8:30 a.m.), by cutting stamens with a scalpel and then isolating the flower buds with a non-woven fabric cover to prevent natural pollination [38]. Both EM and IN floral buds were then subdivided into two groups and exposed to the two different application methods of gibberellic acid (Berelex® 40SG—Sumitomo Chemical, Saint Didier au Mont d'Or, Lion, France (GA3)).

The GA3 was injected (INJ) or sprayed (SPY) on floral buds using 1 mL of GA3 solution in the following concentrations: for INJ, 0, 100, and 200 ppm; for SPY, 0, 250, and 500 ppm. Control floral buds were injected and/or sprayed with distilled water. The different dose regimes of INJ and SPY were selected because injection treatment is more efficient than spraying [38]. Doses will hereafter be indicated as control level (0 ppm for both INJ and SPY), low level (100 ppm for INJ and 250 ppm for SPY), and high level (200 ppm for INJ and 500 ppm for SPY). Following the methodology proposed by Mejía and Cantwell [38] and De La Barrera and Nobel [42], the GA3 was applied twice on each bud at two different times corresponding to different phenological stages: 1–2 days before blooming (i.e., floral-bud diameter of 1.3–1.5 cm), and 20 days after blooming. Other management options (i.e., irrigation and fertilization) were not applied during the experiment.

### *2.3. Fruit and Seed Analyses*

All fruits were harvested at the end of August when control fruits reached commercial maturity. At harvest time, fruit weight, diameter, and length were measured, and fruits were immediately stored in plastic bags at −20 ◦C. While frozen, each fruit was peeled and centrifuged (Girmi il Naturista mod. CE25 500W, Omegna, Italy) to separate pulp and seeds. Seeds were collected, washed with tap water, dried at 30 ◦C for 24 h, and then weighed, counted, and separated by seed type (hard-coated viable seeds or soft-coated aborted seeds) [38]. The fruit parameters considered were length, weight, and diameter, while the seed parameters considered were number, weight, and presence of viable seeds.

### *2.4. Statistical Analyses*

Analysis of variance (ANOVA) was carried out by applying a mixed model on a complete factorial design to evaluate both the effects of each factor and all interactions, considering the GA3 levels between INJ and SPY as equivalent. In the model, blocks were considered as random factors, while emasculation (EM/IN), application methods (INJ/SPY), and GA3 levels were considered as fixed factors. Data that did not fulfill ANOVA assumptions were square-root transformed before running the model. All the analyses were performed using SPSS v.25 software (IBM Corp., New York, NY, USA). Tukey's post-hoc test was also calculated with Bonferroni correction (*p* ≤ 0.05).

### **3. Results**

### *3.1. Fruits Characterization*

In general, the lowest average values for diameter, length, and weight were those of EM plants (Table 1). Considering the combined effect of only INJ/SPY and EM/IN (not GA3 level) on fruit diameter, the highest mean value was found in the IN+SPY group. No significant difference in diameter was found between IN+SPY and IN+INJ combined treatment (−3%), while lower diameters were detected

using the combined treatments EM+SPY (−16%) and EM+INJ (−18.5%). The GA3 levels somewhat affected the results. Higher diameters were found in IN+SPY under all GA3 levels and the IN+INJ control, while the lower values were found in the EM group control using both methods (i.e., INJ and SPY). However, the highest statistical significance was observed between control levels of emasculated fruits (INJ: 3.35 ± 0.33 cm, SPY: 3.29 ± 0.33 cm) and control levels of intact fruits (INJ: 4.95 ± 0.24 cm, SPY: 4.74 ± 0.32 cm).


**Table 1.** Effect of gibberellic acid (GA3) application treatments on fruit variables.

<sup>z</sup> EM: emasculated fruits; IN: intact fruits. Application methods were injection (INJ) and spraying (SPY). <sup>y</sup> The levels of GA3 were control, low levels (100 ppm and 250 ppm) and high levels (200 ppm and 500 ppm). <sup>x</sup> Different letters indicate significant differences using Tukey's post-hoc test with Bonferroni correction (*p* ≤ 0.05). Lower case letters (a–f) are for comparison of individual treatment means and upper case (A,B) are for main effect means.

Considering the combined effect of only INJ/SPY and EM/IN (without GA3 levels) on fruit length, the highest mean was found within the IN+SPY combined treatment, while the lowest was observed using EM+INJ. The application of GA3 resulted in statistically significant differences in fruit lengths between intact and emasculated fruits. Specifically, greater fruit lengths were found in the intact fruits under all GA3 levels and application methods. In contrast, low statistical significance was observed in emasculated fruits among all GA3 treatments and methods, and the only exception was for the highest level of the SPY method in line with the results of intact fruits.

Considering the combined effect of INJ/SPY and EM/IN (without GA3 level) on fruit weight, the highest mean was found using the IN+SPY combined treatment, while the lowest was observed using EM+INJ. No significant difference in weight was found between EM+INJ and IN+INJ combined treatment (−6%), while with respect to the remaining combinations (EM+SPY and EM+INJ), considerable weight differences were observed (−38% and −42%, respectively). The application of GA3 resulted in statistical significance between intact and emasculated fruits. The higher values were found using IN+SPY at all GA3 levels, with similar weights for all treatments, and in the IN+INJ control group. In contrast, the lowest values were found specifically for the control of the emasculated fruits using both INJ and SPY. The highest statistical significance was observed, indeed, between the control group of the IN+INJ and control group of EM+INJ combination treatment.

### *3.2. Fruit Defects*

At harvest time, 39% of total fruit displayed defects. These defects were defined as (Table 2, Figure 1) (a) lignification on pulp tissue; (b) lignification of ovular tissue; (c) recalcitrant fruits (i.e., fruits that have not reached maturity).


**Table 2.** Relative frequencies of harvested fruits and the related defects per combination treatment. Frequency is based on the observation of thirty floral buds per combination treatment.

**Figure 1.** Main defects of harvested fruits: (**a**) lignification on pulp tissue; (**b**) lignification of ovary tissue; (**c**) healthy fruits; (**d**) recalcitrant fruits and (**e**) its longitudinal section; (**f**) longitudinal section of floral bud. Scale bar = 2 cm.

Lignification on pulp tissue was only found in EM+INJ and IN+INJ combined treatments, while under EM+SPY and IN+SPY, this defect was not observed. Specifically, this defect was observed when GA3 treatments were applied. In particular, the highest and lowest defect percentages were found in the intact fruits using the injection method for low and the high GA3 levels, respectively.

Lignification of ovular tissue was observed in three of the four combined treatments, specifically EM+INJ, EM+SPY (10.10%), and IN+INJ. Only within the IN+SPY group was this defect not found. This defect was observed to a greater extent in the EM fruits, with the highest percentage observed within the control group of both the INJ (20.00%) and SPY methods. In contrast, in intact fruit, lignification of ovular tissue was observed only for the INJ method for the low GA3 level (6.70%).

Finally, recalcitrant fruits were found under EM+INJ, EM+SPY, and IN+INJ, while no defect was found using IN+SPY. Fruit recalcitrance was observed in the EM group, with the highest percentage observed in the control groups of both the injected and sprayed methods. The lignification of ovular tissue in IN fruits was observed only in the low GA3 group using the INJ method (13.30%).

The only group free of defects was IN+SPY under all GA3 levels. In contrast, the highest presence of defects was observed using the EM+INJ combined treatment, where only 15.70% of harvested fruits were healthy.

### *3.3. Seed Characterization*

In all groups, the EM flowers showed the lowest average values for all seed variables: the number of seeds was 83.83 ± 8, the number of hard seeds was 12.17 ± 2, and the weight of seeds was 0.16 ± 0.02 g (Table 3).


**Table 3.** Effect of GA3 application treatments on seed variables.

<sup>z</sup> EM: emasculated fruits; IN: intact fruits. Application methods were injection (INJ) and spraying (SPY). <sup>y</sup> The levels of GA3 were control, low levels (100 ppm and 250 ppm) and high levels (200 ppm and 500 ppm). <sup>x</sup> Different letters indicate significant differences using Tukey's post-hoc test with Bonferroni correction (*p* ≤ 0.05). Lower case letters (a–f) are for comparison of individual treatment means and upper case (A,B) are for main effect means.

Without considering the GA3 levels, the combination treatment IN+INJ showed the highest average number of seeds. Only a slight difference was found between IN+INJ and the IN+SPY combined treatment (−1.3%), while, on average, a considerably lower number of seeds was found with EM+SPY (−52%) and EM+INJ (−57.5%). The GA3 levels resulted in statistical significance between intact and emasculated fruits. Specifically, more seeds were found in the IN fruits under most GA3 levels and application methods, with the only exception being the low GA3 level using the INJ method. In contrast, low values were observed using EM fruits under all GA3 treatments and methods, particularly in the control groups.

Regardless of GA3 levels, the highest number of hard seeds per fruit was in the IN+SPY combined treatment. Few differences were observed between IN+SPY and IN+INJ (−13.3%), while large differences were found under EM+SPY (−94.1%) and EM+INJ (−92%) combined treatments. The GA3 levels resulted in statistical significance between intact and emasculated fruits. In particular, the highest level of significance was found in the control groups of both injection and sprayed methods.

Finally, the average highest seed weight per fruit, without considering GA3 levels, was within IN+SPY. The lower average weight of seeds per fruit was found using IN+INJ (−32%) with respect to IN+SPY, while large differences in seed weight were observed using EM+SPY (−93.5%) and EM+INJ (−91.7%). Similarly, the GA3 levels for the seed weight per fruit resulted in statistical significance between intact and emasculated fruits. In particular, the highest level of significance was found under the control of both the INJ and SPY methods.

### *3.4. ANOVA Results*

ANOVA assumptions showed that only the seed variables needed to be transformed. Afterwards, the statistical analysis showed the significant effects of fixed factors and their interactions on both fruit and seed variables (Table 4). Emasculation treatment significantly influenced each variable for both fruits and seeds. The combined treatment SPY/INJ influenced fruit size, seed weight, and viability, but not the number of seeds per fruit. GA3 levels strongly influenced all variables and only moderately impacted the seed number per fruit. Interaction between all factors (EM/IN × SPY/INJ × GA) revealed that there was a strong effect among factors for all the variables.



<sup>z</sup> "ns" means not significant (*p* ≥ 0.05); "\*" low significance (0.01 < *p* < 0.05); "\*\*" high significance (*p* ≤ 0.01). These results were obtained from data presented in Tables 1 and 3.

### **4. Discussion**

The use of different application methods and GA3 concentrations in prickly pears to obtain well-formed and seedless fruits in *O. ficus-indica* (L.) Mill. "Gialla" provided several curious results.

The objective of obtaining well-formed fruits with few seeds was only partially achieved in this study. More well-formed fruits were obtained from the IN rather than the EM treatment, but the IN treatment produced a higher seed content. This was also observed in the aforementioned study by Mejía and Cantwell [38], which found the emasculated fruits were generally smaller and had lower numbers of hard seeds (viable seeds) than the intact ones. This difference could be explained by the lack of stamens (emasculation), which contributed to the lack of or low development of the flower tissues. The external tissue of the anthers is the main gibberellin biosynthesis site, and thus the main regulating factor for the development of the remaining floral parts. This was deduced from Inglese et al. [37], who observed that *Opuntia ficus-indica* flowers with removed anthers show lower levels of endogenous gibberellin than pollinated ones. This behavior has been observed in other crops such as rice [43] and *Arabidopsis* [44].

The emasculated fruits showed a general decrease in all the analyzed variables (i.e., diameter, length, and weight) compared to the intact ones, regardless of the GA3 treatment applied. In the prickly pear, pulp development originates from the funiculus, which connects the seed to the ovular tissue, and thus seeds are needed for fruit development [32,38,45]. On this basis, if the development of the ovular tissue and funiculus was inhibited, the *Opuntia*'s fruit may have difficulty in developing properly [23]. Despite the plausibility of the hypothesis, the gibberellin transport mechanism in the developing organs of the flower—from the male part (stamen) to the female part (ovary tissue and funiculus)—is not currently fully understood [46,47].

Generally, it has been observed that treatment with GA3 may improve pulp development and reduce seed numbers in emasculated prickly pear fruits as a result of the replacement of endogenous gibberellins. This was also suggested by the fact that in *Opuntia ficus-indica*, the highest levels of GA3 in the flowers were found during blooming [37], and these, in turn, are responsible for the development of fruits and natural pollination [42]. This has also been observed in other plant species, i.e., the *Citrus* genus [48], where although gibberellic acid is not the only factor emulating the effects of natural pollination, the contribution of both pollination and exogenous GA3 application can improve fruit development.

However, the response of fruits and seeds to growth regulator treatments in this study depended on the specific application method. More specifically, while the spraying of GA3 (both low and high levels) generally enhanced the performance of all the analyzed variables of the treated fruits, the injection method showed the opposite pattern, especially for the intact fruits. One of the effects caused by gibberellic acid is control over the elongation of cellular tissues in plants [49–51]. Generally, the exogenous sprayed GA3 is able to spread through the elongation of cells in plant tissues, thus facilitating the absorption and avoiding the direct negative effect of gibberellic acid within the parenchyma tissue [42,52].

Whilst several studies have demonstrated that GA3 application can increase the presence of defects in *Arabidopsis*[44,53], *Coriadrum sativum* L. [54], *Oryza sativa* L. [46], *Zea mays* L. [52], and *Daucus carota* L. [55], to our knowledge, only a few studies have investigated the effects of GA3 on *Opuntia* [35,56]. In this study, the main defects were lignification of the ovular and pulp tissue, and the presence of recalcitrant fruits. Lignification on pulp tissue was observed in both EM and IN fruits, particularly in the INJ groups. Specifically, most pulp tissue lignification was found corresponding to the needle entry hole for the GA3 injection. This condition may have been caused by two different factors. First, the needle was not able to reach the ovary, thus spreading the GA3 solution into the pulp. It is also possible that the injected compounds returned to the entry hole. This was partially deduced by Nobel et al. [56], who observed that in *Opuntia ficus-indica* tissues, injected gibberellic acid likely came into contact with expanding parenchyma tissue, thus leading to an excessive accumulation of dry matter in the tissue around the needle entry hole. This has been confirmed in several studies [42,52], which proposed that the gibberellic acid in prickly pear fruits can cause a sink effect promoting dry matter accumulation in parenchyma tissue. This pattern was also indirectly supported by Jedidi Neji et al. [57], in which injection of gibberellic acid into the ovary of the *Opuntia* flower through the stigma and not the pulp did not result in lignification effects on the pulp tissue in fruits.

The lignification on ovular tissue, mostly recorded in EM fruits, was highest when the GA3 was sprayed rather than injected. Ortiz Hernandez et al. [58] reported a similar behavior in an *O. amyclaea* study: when the flowers were emasculated and treated with different growth regulators, the fruits showed ovarian tissue lignification. This result was likely driven by the flower emasculation rather than the method of GA3 application since the absence of stamens can cause a lack or little development of the remaining flower tissues. Gupta et al. [47] suggested that, generally, even a short-distance movement of GA3 from the stamen to the other floral organs and the pedicel may be sufficient for flower development.

Recalcitrant fruits were found mostly in EM fruits. The highest incidence was observed within the control groups for EM+INJ (80%) and EM+SPY (53%). This result was likely because emasculation does not allow for the development of full fruit maturity, thus creating smaller fruits. These findings are consistent with a similar study carried out by Kaaniche-Elloumi et al. [23], in which prickly pear emasculated fruit reached maturity after GA3 treatment. Besides, when comparing the IN control group fruits with the different GA3 treatments, an overall decrease in the number of seeds, the number of hard-coated seeds, and the weight of seeds was observed. This may confirm that exogenous GA3 on *Opuntia* can reduce the number of hard-coated seeds [35,36,38]. Furthermore, seed abortion could be related to the effect of GA3 on chromosomal DNA, which may lead to the incomplete development of the endosperm [57].

### **5. Conclusions**

Prickly pear cultivation is important in several dry and semi-dry areas of the world owing to its diverse uses (e.g., as fresh fruit, in bioenergy, cosmetics, and medicine production, and as forage). The results of GA3 application on fruits indicated that 500 ppm of GA3 sprayed on emasculated floral buds was the most effective technique for reducing the number of seeds within prickly pear fruits. The spraying of the GA3 (both low and high levels) enhanced the growth performance of all the analyzed variables of the treated fruits, while the injection method, though capable of reducing the

number of seeds, can increase the presence of defects, making the fruit unmarketable. The results suggested the need to further investigate the impact of higher GA3 concentrations on fruit production, and particularly, GA3 application methods, especially regarding industrial production. The GA3 spraying method would indeed be easier to apply in large-scale production than the injection method, whilst manual emasculation may be better replaced by chemical emasculation, which provides similar results. Given the scarcity of studies on prickly pear cultivation and the repercussions of its industrial processes, future studies should focus on these aspects by conducting experiments that directly address the application of these treatments in industrial-scale processes. Moreover, further studies should focus on the maximum thresholds of GA3 applicability and the physiological effects of the gibberellic acid pathway through productive tissue, thus elucidating the economic viability of this cultivation technique and the changes in fruit quality and organoleptic properties.

**Author Contributions:** Conceptualization, C.G. and E.P.; Formal analysis, L.M. and A.M.; Investigation, C.G. and P.F.; Methodology, C.G., P.F. and E.P.; Resources, E.P.; Writing—original draft, L.M.; Writing—review and editing, A.C., L.B. and E.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## **Water Use and Yield Responses of Chile Pepper Cultivars Irrigated with Brackish Groundwater and Reverse Osmosis Concentrate**

**Gurjinder S. Baath 1,\*, Manoj K. Shukla 2, Paul W. Bosland 2, Stephanie J. Walker 3, Rupinder K. Saini <sup>4</sup> and Randall Shaw <sup>5</sup>**


Received: 3 March 2020; Accepted: 20 April 2020; Published: 6 May 2020

**Abstract:** Freshwater availability is declining in most of semi-arid and arid regions across the world, including the southwestern United States. The use of marginal quality groundwater has been increasing for sustaining agriculture in these arid regions. Reverse Osmosis (RO) can treat brackish groundwater, but the possibility of using an RO concentrate for irrigation needs further exploration. This greenhouse study evaluates the water use and yield responses of five selected chile pepper (*Capsicum annuum* L.) cultivars irrigated with natural brackish groundwater and RO concentrate. The four saline water treatments used for irrigation were tap water with an electrical conductivity (EC) of 0.6 dS m−<sup>1</sup> (control), groundwater with EC 3 and 5 dS m<sup>−</sup>1, and an RO concentrate with EC 8 dS m<sup>−</sup>1. The evapotranspiration (ET) of all chile pepper cultivars decreased and the leaching fraction (LF) increased, particularly in the 5 dS m−<sup>1</sup> and 8 dS m−<sup>1</sup> irrigation treatments. Based on the water use efficiency (WUE) of the selected chile pepper cultivars, brackish water with an EC ≤ 3 dS/m could be used for irrigation in scarce freshwater areas while maintaining the appropriate LFs. A piecewise linear function resulted in a threshold soil electrical conductivity (ECe) ranging between 1.0–1.3 dS m−<sup>1</sup> for the tested chile pepper cultivars. Both piecewise linear and sigmoid non-linear functions suggested that the yield reductions in chile peppers irrigated with Ca2<sup>+</sup> rich brackish groundwater were less than those reported in studies using an NaCl-dominant saline solution. Further research is needed to understand the role of supplementary calcium in improving the salt tolerance of chile peppers.

**Keywords:** *Capsicum annuum*; salinity; evapotranspiration; leaching fraction; calcium

### **1. Introduction**

Freshwater is an integral resource for all ecological and social activities, including food and energy production, industrial growth, and human health. As freshwater resources are unevenly and irregularly distributed [1], many arid and semi-arid parts of the world are facing acute water shortages. Similar water shortages affect the southwestern United States due to low rainfall and high evapotranspiration [2]. As agriculture is the largest consumer of freshwater [3], the use of marginal quality water resources, including brackish groundwater, has been increasing [4,5]. About 75% of the groundwater aquifers in the southwestern United States have brackish water, with an electrical

conductivity (EC) of > 3 dS/m [6,7]. Additionally, the desalination of brackish groundwater through Reverse Osmosis (RO) produces potable, low saline water and high saline–sodic wastewater known as RO concentrate [7]. The application of desalinated water for irrigation can promote soil hydrological functions [8]. However, the disposal of RO concentrate from an inland desalination system can be problematic, and its sustainable management is a major environmental challenge that restricts the widespread application of RO for groundwater desalination. RO concentrate could serve as a potential source of irrigation for the production of salt-tolerant crops, along with brackish water available from natural saline aquifers [9,10], which will consequently encourage desalination through RO in freshwater scarce-areas.

Continued irrigation with brackish groundwater can lead to salt accumulation in soil which can lower yields, although plants differ extensively in their response to soil salinity. Most crop plants are glycophytes, which can be affected by even a moderate level of soil salinity [11]. Instead of accumulating salts, most glycophytes produce some chemicals (sugars and organic acids) to raise the concentration of constituents in the root cell. This process requires more energy, and thus their crop growth and yield are more susceptible to damage compared to halophytes [12]. Moreover, salt tolerance within the glycophytes group varies widely [13]. Sugarbeet (*Beta vulgaris* L.) and wheat (*Triticum aestivum* L.) are considered salt-tolerant; potato (*Solanum tuberosum* L.), sunflower (*Helianthus annuus* L.), maize (*Zea mays* L.), soybean (*Glycine max* L. Merrill.), and tomato (*Solanum lycopersicum* L.) are moderately salt-sensitive; and chickpea (*Cicer arietinum* L.) and lentil (*Lens culinaris* Medic.) are salt-sensitive [14].

Chile pepper (*Capsicum annuum* L.), also a glycophyte, is an important cash crop of the southwestern United States, cultivated over an area of 20,000 acres annually [15]. It is classified as moderately salt-sensitive, with a saturated soil paste extract EC (ECe) threshold value of 1.5 dS m−<sup>1</sup> [16]. Studies have also reported threshold values between an ECe of 0–2 dS/m for peppers [17,18]. To the best of our knowledge, most studies on peppers have used NaCl as the sole or the dominant salinizing agent [17–21]. However, Na+, Ca2<sup>+</sup>, and Mg2<sup>+</sup> are the dominant cations, and Cl<sup>−</sup>, SO4 <sup>2</sup><sup>−</sup>, and HCO3 − are the dominant anions in most groundwater across the world [22]. It has been suggested that the adoption of salinizing solutions with a single salt may result in ambiguous and erroneous interpretations about plant responses to salinity [23]. Only a few accounts are available involving the use of natural brackish groundwater for growing chile peppers [24]. Therefore, more research on the use of natural brackish groundwater and RO concentrate for irrigating chile pepper cultivars is needed.

The use of brackish groundwater often brings risks and obligations to an agricultural system. The application of insufficient water quantities causes a lowering of the osmotic potential of soil water, ultimately causing stress to the plants [25], whereas over-application is economically ineffectual and could exacerbate salinity problems, including groundwater contamination [26]. There is very limited information available on the evapotranspiration (ET) responses of the chile pepper to varying irrigation salinity. An understanding of water uptake by the chile pepper under contrasting saline water treatments would allow the exploration of irrigation scheduling protocols for regions utilizing brackish groundwater. Therefore, the objectives of this study were to (1) quantify the influences of brackish groundwater and RO concentrate irrigation on the leaching fraction and water use of five chile pepper cultivars; and (2) determine their yield responses to the resulting soil salinity.

### **2. Materials and Methods**

### *2.1. Experimental Set Up*

The study was conducted in a greenhouse located at the Fabian Garcia Science Center of New Mexico State University (NMSU), Las Cruces, New Mexico (32.2805◦ N latitude and 106.770◦ W longitude at an elevation of 1186 m above sea level), consistent with the potential of greenhouse chile pepper production in New Mexico [27] and the New Mexico Department of Agriculture regulation of no land application of water with an EC > 4 dS m<sup>−</sup>1. The chile pepper cultivars selected for this study were AZ1904 (Curry Chile and Seed, Pearce, AZ, USA), Paprika LB25 (Biad Chile, Leasburg, NM, USA), Paprika 3441 (Olam, Las Cruces, NM, USA), and two NMSU varieties: NuMex Joe E. Parker and NuMex Sandia Select. The natural brackish groundwater and RO concentrate provided by the Brackish Groundwater National Desalination Research Facility (BGRNDRF), Alamogordo, were used in the irrigation treatments (Table 1). Sandy loam soil (78.7% sand, 11% silt, and 10.3% clay) with an initial ECe of 0.87 dS/m was air-dried, crushed, and sieved through a 4 mm sieve. A soil mix was prepared by mixing soil, sand, and organic peat in the ratio 8:1:1 on a volume basis. The soil mix was sterilized in an oven at 80 ◦C for at least 30 min. The cylindrical pots used in the experiment were 0.14 m in diameter and 0.25 m in depth. The bottom of each pot was perforated and covered with cheesecloth and then gravels to allow free drainage. The soil packing was done in 5 cm depth increments to obtain a bulk density of 1.36 g/cm3. The average day and night temperatures recorded during the study period (148 days) were 31.8 ± 0.2 ◦C and 24.4 ± 0.1◦C.

**Table 1.** Mean (standard error) for chemical properties of the four saline water treatments over the growing period.


Tap water is the control; EC: electrical conductivity; RO conc.: reverse osmosis concentrate.

### *2.2. Saline Irrigation Treatments*

The four irrigation water treatments selected were tap water with the EC 0.6 dS m−1, brackish groundwater with the EC 3 and 5 dS m<sup>−</sup>1, and an RO concentrate with the EC 8 dS m−1. Before planting, the soil was washed three times with tap water to remove any pre-existing salts, and then the soil salinity was raised to the saline treatment level by irrigating twice with each of the saline water treatments. Four seeds of each chile pepper were sown in pots at a soil depth of 1–2 cm. After emergence, the seedlings were thinned, and only one vigorous seedling was retained in each pot. The irrigation water treatments were continuously applied at an interval of 3–4 days during the experiment period, based on the change in weights of some reference pots. The plants were fertigated using a water-soluble synthetic fertilizer (Miracle-Gro®; 15-30-15) at2gL−<sup>1</sup> every six weeks.

### *2.3. Data Collection*

The same amount of irrigation (I) was applied manually to each pot, and the deep percolation (D) was measured by collecting all the water coming out of the bottom of each pot. The ET was calculated using the following water balance equation:

$$\text{ET} = \text{P} + \text{I} - \text{D} - \text{R} - \Delta \text{S} \tag{1}$$

where ET is the actual crop evapotranspiration (cm), P is the precipitation (cm), I is the irrigation amount (cm), D is the deep percolation (cm), R is the runoff (cm), and ΔS is the change in soil water storage (cm). As the experiments were carried out in a greenhouse, the precipitation and runoff were zero. The change in soil water storage (ΔS) was determined from the difference in weights of the pots at planting and final harvest. The leaching fraction (LF) was calculated for every irrigation as the ratio of D and I. The pods were hand-harvested at the horticultural green mature stage, and the fresh pod weights were measured. The water use efficiency (WUE) was calculated as the ratio of the total yield to total crop ET.

At the end of the experiments, the top 10 cm layer of soil was collected from each pot and saturated soil paste extracts were prepared using composite samples and analyzed for their *ECe*, magnesium (Mg), calcium (Ca), and sodium (Na) ion concentrations [28]. The sodium adsorption ratio (*SAR*) was determined using the following equation:

$$SAR = \frac{[Na^{+}]}{\sqrt{\frac{([Ca^{2+}]/Mg^{2+}]}{2}}} \tag{2}$$

### *2.4. Salinity-Yield Response Equations*

The relative yield (*Yr*) was obtained as the ratio of actual total yield and maximum total yield for each cultivar. The relationship between the *ECe* at the end of the growing season and the relative yield was predicted using the piecewise linear function [16]:

$$Y\_r = 1 - b\left(EC\_t - a\right) \tag{3}$$

where *a* = the salinity threshold (dS m<sup>−</sup>1); *b* = the yield reduction, or slope (per dS m<sup>−</sup>1); and *ECe* = the EC of saturated soil extracts from the root zone (dS m<sup>−</sup>1).

Similarly, the relationships between the *Yr* and *ECe* of each cultivar were best-fitted with the sigmoid non-linear function [29]:

$$Y\_r = \frac{1}{\left(1 + \frac{c}{c \otimes 0}\right)^p} \tag{4}$$

where *Yr* = relative yield; *c* = the EC of saturated soil extracts from the root zone (dS m<sup>−</sup>1), *c*<sup>50</sup> = root zone *ECe* at which the yield had declined by 50% (dS m<sup>−</sup>1) and *p* is the exponential constant.

### *2.5. Statistical Analysis*

The cylindrical pots for the experiments were arranged in a completely randomized factorial design with eight replicates of each cultivar and a saline water treatment combination. A two-way analysis of variance (ANOVA) was used to identify the significant differences at alpha 5% applying general linear model procedure (PROC GLM) for ET, D, ΔS, and WUE [30]. The means were separated using the least significance difference (LSD) post hoc test at a 5% significance level (*p* ≤ 0.05). The relationships of the ECe with the concentrations of Mg, Ca, and Na ions and SAR were tested for linear, quadratic and exponential functions using Sigmaplot version 14 (Systat Software Inc., San Jose, CA, USA), and the best fit was selected based on regression statistics. The relative yield response to the ECe was best fitted to the piecewise linear and sigmoid non-linear functions using the 'nls2 package in R [31].

### **3. Results and Discussion**

### *3.1. Leaching Fraction over Growing Season*

The leaching fractions (LF) for AZ 1904, NuMex Joe E. Parker, NuMex Sandia Select, Paprika LB25, and Paprika 3441 over the growing season are shown in Figure 1a–e, respectively. For almost one month after planting, LFs were similar for cultivars grown using the four saline water treatments. Over time, variations in the LF appeared and became a function of the irrigation water salinity for all five cultivars. Among the four irrigation water treatments, the LFs for the 0.6 dS m−<sup>1</sup> (control) treatment were the least, while they were the most for the 8 dS m−<sup>1</sup> RO irrigation treatment throughout the growing season. The differences in LFs of between 0.6 dS m−<sup>1</sup> and 3 dS m−<sup>1</sup> were considerably smaller compared to the other two treatments in all five cultivars.

**Figure 1.** Effect of different saline water treatments on the leaching fractions of (**A**) AZ1904, (**B**) NuMex Joe E. Parker, (**C**) NuMex Sandia Select, (**D**) Paprika LB25, and (**E**) Paprika 3441 over the growing season.

The observed higher LFs under the saline treatments could be due to the self-adjusting nature of the plants under water and osmotic stresses. In response to saline irrigation water, the transpiration rate of chile pepper plants would have decreased due to the reduction in water potential caused by accumulated salts at the root zone [32]. Similar increases in LFs at a given irrigation rate occurred due to the reduction in transpiration rates for the bell pepper (*Capsicum annuum* L.) [33]. In the areas with a shallow water table, more deep percolation could cause secondary salinization [34]. Therefore, it is

advisable to explore irrigation scheduling protocols before the application of the concentrate in a field to maintain the soil and groundwater quality [7].

### *3.2. Water Balance*

A total irrigation of 106.3 cm was applied to each pot during the experiment period. The influence of irrigation water salinity on the total crop ET, ΔS and D are shown in Table 2. There was no significant interaction (*p* > 0.05) between the saline treatments and cultivars for D, ΔS, and ET, while the significant main effects of both the saline treatments and cultivars were observed. The total ET of five chiles showed a significant decrease (*p* ≤ 0.05) with increasing irrigation water salinity. The highest cumulative ET of the five cultivars was noted at 0.6 dS m−<sup>1</sup> (control), which was only 4% greater than 3 dS m<sup>−</sup>1; however, it was around 12% and 17% greater compared to the 5 dS m−<sup>1</sup> and 8 dS m−<sup>1</sup> treatments, respectively. The total deep percolation was inversely related to the total crop ET and significantly increased from 24% of the total irrigation amount in the 0.6 dS m−<sup>1</sup> (control) to 35% in the 8 dS m−<sup>1</sup> (RO concentrate).



† Values within each column followed by same letter(s) are not significantly different according to the least significance difference test (*p* ≤ 0.05). NS = non-significant at *p* ≤ 0.05. Irrigation amount applied was 103.6 cm for all of the treatments.

The reduction in ET with increasing water salinity could be attributed to retarded plant growth and a decrease in bioavailable water under saline soil conditions. The water uptake of plants, through apoplastic and symplastic pathways at roots, is largely regulated by the osmotic and matric potentials of the root zone [35]. Under saline soil conditions, the reduced osmotic potential affects the free energy of water and decreases the root water uptake by plants, which leads to a reduction in the plant growth and ET and thus an increase in leaching [36]. In addition, a salt crust formed at the top soil layer due to saline irrigation could reduce evaporation from the soil surface [37]. Therefore, the surface crusting (visual observations) could also have played some role in reducing the total ET of the chile pepper.

In contrast to the total ET, NuMex Sandia Select had the greatest D, while Paprika LB 25 and 3441 had the minimum among the five cultivars. The differences noticed in the cumulative ET among the cultivars could be attributed to natural variations in the growth of the cultivars. The overall change in soil water storage was small in all of the pots, but it decreased significantly across irrigation treatments from 1.56 cm in the 0.6 dS m−<sup>1</sup> to 1.34 cm in the 8 dS m−<sup>1</sup> irrigation water treatment.

### *3.3. Water Use E*ffi*ciency*

No significant interaction between the saline treatments and cultivars (*p* > 0.05) was observed for the WUE, while significant reductions (*p* ≤ 0.05) in the WUE were noted with the increasing salinity of the irrigation water (Figure 2A). The reduction in the WUE was only 9% in the 3 dS m−<sup>1</sup> compared to the control treatment, while it was 38% and 42% in the 5 and 8 dS m−<sup>1</sup> water treatments, respectively. The WUE is generally treated as an important physiological indicator of crops that are grown in water-scarce conditions. As the WUE of chile peppers irrigated with 3 dS/m was not much different from those irrigated with 0.6 dS/m, a slightly brackish groundwater (<3 dS m<sup>−</sup>1) might be considered for irrigating chile peppers if brackish groundwater is the only available source of irrigation, while simultaneously monitoring salts in the leachate water and soil. However, significant reductions can occur with a further increase in the salinity of the irrigation waters. A similar reduction in the WUE with an increased irrigation water salinity was reported in tomato [38,39]. The average WUE of the five chile pepper cultivars in this study was similar and was in agreement with results reported by Reina-Sanchez et al. (2005) for four tomato cultivars irrigated with saline water (Figure 2B) [40].

**Figure 2.** (**A**) Water use efficiency (WUE) of the chile pepper cultivars under four saline irrigation waters, and (**B**) the WUE of five chile pepper cultivars across saline irrigation waters. Bars with the same letters are not significantly different according to the least significance difference test at *p* ≤ 0.05.

### *3.4. Accumulation of Mg2*<sup>+</sup>*, Ca2*<sup>+</sup> *and Na*<sup>+</sup> *Cations in Soil*

There were no significant differences among the cultivars (*p* > 0.05) for the magnesium, calcium and sodium concentrations and the sodium adsorption ratios of saturated soil paste extracts (data not presented). Although all three Mg2<sup>+</sup>, Ca2<sup>+</sup>, and Na<sup>+</sup> cation concentrations increased significantly (*<sup>p</sup>* <sup>≤</sup> 0.05) with the ECe, different responses were noted, especially at ECe higher than 9 dS m−<sup>1</sup> (Figure 3A). A linear relationship of Mg2<sup>+</sup> concentration was obtained with the ECe, while the response of Na<sup>+</sup> and Ca2<sup>+</sup> was positive exponential and negative exponential, respectively. It was observed that the Na/Ca ratio of the soil paste extract increased from 1.13 in the 0.6 dS m−<sup>1</sup> to 1.87 in the 8 dS m−<sup>1</sup>

treatment. The reason could be the displacement of Ca2<sup>+</sup> by Na<sup>+</sup> and the subsequent Ca2<sup>+</sup> leaching under high Na<sup>+</sup> concentrations in soil [41]. The SAR increased linearly (*p* <sup>≤</sup> 0.05) with the increasing ECe (Figure 3B), which could be well explained by a greater increase in Na<sup>+</sup> than in Ca2<sup>+</sup> concentration under high salinity.

**Figure 3.** Relationships of (**A**) magnesium (Mg), calcium (Ca), and sodium (Na) ions buildup and (**B**) the sodium adsorption ratio (SAR) with the salinity level (ECe) of soil irrigated with brackish water and reverse osmosis concentrate.

### *3.5. Yield Responses to Root-Zone Salinity*

The relative yield responses of five chile pepper cultivars to the ECe were similar and considerably well explained by both piecewise linear and sigmoid non-linear functions; though the sigmoid function resulted in a slightly better fit for each of the five cultivars, as evident by their higher coefficient of determination (r2; 0.87–0.91) and lower residual sum of squares (RSS) values (Table 3). Likewise, the overall yield responses of chile pepper cultivars were slightly better explained by the sigmoid function compared to the piecewise function. The threshold value (*a*) estimated using the piecewise linear function ranged between 1.04–1.33 dS m<sup>−</sup>1, with Numex Joe E. Parker and Paprika LB25 having the lowest and greatest *a* value, respectively, among the cultivars. Whereas, both Paprika 3441 and NuMex Sandia Select resulted in threshold values (1.09 & 1.12 dS m−1) close to the observed value of 1.10 dS m−<sup>1</sup> for all the cultivars. The *a* values obtained in this study were lower than the earlier threshold values of 1.5–1.8 dS m−<sup>1</sup> suggested for the peppers [16,17,42]. Additionally, the determined

slope (*b*) values of 0.038–0.046 were also lower as compared to the earlier reported values of 0.14 [43] and 0.12 [42].


**Table 3.** Regression statistics for two response functions applied to yield responses of five chile pepper cultivars against soil salinity.

*a*: salinity (ECe) threshold; *b*: slope; *c50*: ECe at which yield is reduced by 50%; *p*: regression constant for sigmoid function.

The 50% yield reduction (*c50*) estimations from sigmoid non-linear functions were ranged between 10.75–13.55 dS m−1, which was in agreement with the range (12.15–14.21 dS m−1) predicted using piecewise linear equations for the chile pepper cultivars. The lowest *c50* (10.75 dS m<sup>−</sup>1) was noted for NuMex Sandia Select, while Paprika 3441 had the greatest *c50* of 13.55 dS m<sup>−</sup>1. The other three varieties showed similar yield reductions with an increase in soil salinity, and their *c50* values were ranged between 12.01–12.22 dS m<sup>−</sup>1. The observed *c50* values of all the chile peppers were much higher than the 6 dS m−<sup>1</sup> proposed for the peppers [42,44]. Furthermore, the constant *p* values ranging between 1.26–2.11 were comparatively lower than the value of 3.0 suggested for most of the crops, including peppers [45].

Lower yield reductions in chile peppers against the soil salinity compared to previous reports could be attributed to the calcium dominated brackish groundwater used in this study. The considerable amount of calcium in the natural saline irrigation treatments has been reported to ameliorate the salinity's impact on plants [46]. Calcium plays regulatory roles in the metabolism, water transport, and root hydraulic conductivity of plants under salt stress [47,48]. Moreover, high calcium levels can shield the cell membrane from detrimental salinity effects [49].

### **4. Conclusions**

This study evaluated the effects of natural brackish groundwater and RO concentrate irrigation on the water use, leaching fraction, and yield responses of chile pepper cultivars. Saline irrigation caused a reduction in the water uptake of the chile peppers and increased LFs, particularly in the 5 dS m−<sup>1</sup> and the 8 dS m<sup>−</sup>1. The WUE was not substantially different between 0.6 and 3 dS m−<sup>1</sup> but decreased significantly in the other two higher salinity treatments. Therefore, irrigating chile peppers with up to 3 dS m−<sup>1</sup> brackish water could be possible by maintaining appropriate leaching fractions to sustain chile pepper production in freshwater-scare areas, where brackish groundwater is the only available source of irrigation. The yield response curves showed that the yield reductions in the chile peppers irrigated with natural brackish water were lesser compared to those of NaCl-dominant solution studies. Low yield reductions could be related to significant Ca2<sup>+</sup> concentrations in the brackish groundwater and RO concentrate. However, there is further need to investigate the effects of different Na+/Ca2<sup>+</sup> concentrations on plant physiology, water transport, ion content and transport, growth, nutrition, and yields for improving the salt tolerance of chile peppers.

**Author Contributions:** Conceptualization, G.S.B. and M.K.S.; methodology, G.S.B., M.K.S., P.W.B., and S.J.W.; formal analysis, G.S.B. and R.K.S.; writing—original draft preparation, G.S.B.; writing—review and editing, M.K.S., R.K.S., P.W.B., S.J.W. and R.S.; visualization, G.S.B. and R.K.S.; supervision, M.K.S.; project administration, M.K.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was partially supported by the USDA National Institute of Food and Agriculture, Hatch project 1006850, and Nakayama Chair endowment.

**Acknowledgments:** Authors would like to acknowledge New Mexico State University Agricultural Experiment Station for the financial support through Graduate Research Award and Brackish Groundwater National Desalination Research Facility in Alamogordo, NM for providing the groundwater and RO concentrate. Authors thank Barbara Hunter and Jacob Pino for their assistance in analyzing soil and water samples.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

## **Alterations in the Chemical Composition of Spinach (***Spinacia oleracea* **L.) as Provoked by Season and Moderately Limited Water Supply in Open Field Cultivation**

### **Christine Schlering 1,2,\*,**†**, Jana Zinkernagel 2, Helmut Dietrich 1, Matthias Frisch <sup>3</sup> and Ralf Schweiggert <sup>1</sup>**


Received: 6 March 2020; Accepted: 7 April 2020; Published: 10 April 2020

**Abstract:** The current use and distribution of agricultural water resources is highly prone to effects of global climate change due to shifting precipitation patterns. The production of vegetable crops in open field cultivation often requires demanding water applications, being impaired in regions where climate change will increasingly evoke water scarcity. To date, increasingly occurring precipitation-free periods are already leading to moderate water deficits during plant growth, e.g., in southern Europe. Among all vegetable crops, leafy vegetables such as spinach (*Spinacia oleracea* L.) are particularly vulnerable to limited water supply, because leaf expansion is highly dependent on water availability. Besides biomass production, water limitation might also affect the valuable nutritional composition of the produce. Therefore, we investigated the impact of moderately reduced water supply on the chemical composition of spinach, cultivated in the open field in three consecutive years. Two different water supply treatments, full and reduced irrigation, were used in a randomized block design consisting of three sets of six plots each. In the reduced water supply treatment, the total amount of supplied water, including both irrigation and natural precipitation, amounted to 90%, 94% and 96% in 2015, 2016 and 2017, respectively, of the full, optimal water supply treatment. Spinach grown under limited water supply showed significantly higher fresh biomass-based contents of polyols (e.g., inositol, glycerol), ascorbic acid, potassium, nitrogen, phosphorous, zinc and manganese, as well as total flavonoids and carotenoids. Increased dry biomass-based levels were found for total inositol, zinc and manganese, as well as decreased levels for malic acid, fumaric acid, phosphate and chloride. Furthermore, we report a high seasonal variation of several minor phytochemicals, such as single flavonoids. Spinacetin derivatives, spinatoside-glucoside as well as a rather unusual hexuronylated methylenedioxy flavonoid showed highest amounts when grown under relatively low irradiation in autumn. Levels of patuletin derivatives tended to increase under high irradiation conditions during spring. In summary, the chemical composition of spinach was shown to be highly sensitive to moderately reduced water supply and seasonal variation, but the overall nutritional quality of fresh marketable spinach was only marginally affected when considering health-related constituents such as minerals, trace elements, flavonoids and carotenoids.

**Keywords:** vegetables; water deficit; climate change; polyols; minerals; flavonoids; carotenoids

### **1. Introduction**

The ongoing climate change as well as the associated side effects, such as rising temperatures and substantial shifts in precipitation patterns, may lead to less favorable conditions for the cultivation of the respective, currently grown crop plants. Future projections of precipitation indicate even more severe conditions for almost the entire European continent [1]. Changing climatic conditions do not only boost temperature and rainfall fluctuations, but also consequently influence soil evaporation and plant transpiration [2]. Adverse distributions of rainfall during the cultivation period are already likely to create short-term water deficiencies in horticultural crops, which lead to sub-optimal conditions for plant growth. These temporary stress-related conditions may induce complex interactions in plant metabolism, especially under heterogenic requirements in open-field cultivation, where a combination of different stress factors simultaneously occurs. The results in terms of physiological and biochemical responses can be very different as a function of growth stage, severity and duration of stress [3].

In addition, plant responses to stress are dependent on the tissue or organ affected by the stress [4]. The reaction of plants to drought consists of numerous coordinated processes to alleviate both cellular hyperosmolarity and ion disequilibria [5]. Plants respond to drought stress with physiological and biochemical changes, aiming at the retention of water against a high external osmotic pressure and the maintenance of photosynthetic activity, while stomatal opening is reduced to counteract water loss [5]. While severe drought stress often results in clearly unmarketable crops, mild and moderate limitations in water supply induce more subtle changes and have earlier been considered to even enhance the formation of health-promoting antioxidant constituents in leafy vegetables [6]. However, this effect is highly plant-specific. For instance, experiments with moderately induced drought stress towards the end of the cultivation period followed by re-watering did not lead to significant increases in the concentrations of antioxidant compounds such as carotenoids and tocopherols in spinach (*Spinacia oleracea* L.), but did increase the levels of the aforementioned compounds in rocket [7]. Therefore, smart irrigation strategies are already used in horticultural systems to reduce the consumed irrigation water and even improve harvest quality [8]. However, severe water deficits evoked by fewer precipitation events or scarcity of irrigation water can be hard to manage and thereby cause short-term stress events during plant development.

Leafy vegetables such as spinach are usually highly sensitive to water deficits, because transpiration is affected due to stomatal closure. Stomatal closure as well as leaf growth inhibition are among the earliest responses to drought, protecting the plants from extensive water loss [3]. Since the biological function of plant leaves, i.e., photosynthesis, requires their exposure to sunlight and air, they might be expected to most sensitively react to a number of stress factors. The sensitivity of the photosynthetic apparatus is the basis of chlorophyll fluorescence measurements for recognizing plant stress prior to other physiological and even macroscopically visible stress responses [9]. Among the latter, the total leaf area is determinative for biomass accumulation and crop yield and also represents a factor highly correlated with detrimental effects on crop growth under stressful conditions [10]. Mild environmental stress was shown to lead to a significant decrease in the yield of freshly harvested spinach due to diminution of the relative water content, which recovered to control values within three days after re-watering [7]. However, plant growth remained affected. Thus, attempts to enhance levels of health-promoting phytochemicals like antioxidants by manipulating environmental factors may be burdened by a drop in yield [7]. Water deficit inhibits plant growth by reducing water uptake into the expanding cells, and enzymatically alters the robustness and plastic properties of the cell wall [4]. A crop's need for water varies considerably among species, but water requirements for horticultural crops are generally high [11]. Especially in the case of leafy vegetables, constant amounts of available water are crucial [11].

Spinach is a leafy vegetable belonging to the long-day plants, which flower, or bolt, if the light period is as long as or longer than a 'critical day length' [11]. In northern regions, spinach is usually grown under short-day conditions in spring or fall in order to avoid bolting [11] and unfavorable textural alterations like fibrousness and stringiness. In brief, bolting renders spinach unmarketable. Similar to other leafy vegetables like lettuce or cabbage, spinach can tolerate lower light levels than fruiting vegetable crops [11]. Spinach is viewed as a vegetable with high nutritional quality [12], providing many health-promoting antioxidant constituents like carotenoids, flavonoids and other phenolic compounds [13], as well as considerable amounts of minerals, trace elements and vitamins, like vitamin C [14]. As compared to other flavonoid-rich vegetables such as Swiss chard (2.700 mg/kg fresh matter (FM) [15]) or red lettuce (1.400 mg/kg FM [16]), spinach showed similarly high contents of flavonoids (1.000 mg/kg FM [17]). Spinach is also known to accumulate high levels of rather undesired substances such as nitrate (547–3.350 mg/kg FM) and oxalate (2.309–10.108 mg/kg FM) [18]. With respect to its high nutritional quality, we studied how moderately reduced water supply might influence the chemical composition and, thus, the product quality of field-grown spinach. By evaluating this during three different cultivation years, this study also demonstrated the seasonal variability of the above-mentioned nutritionally relevant substances in spinach.

### **2. Materials and Methods**

### *2.1. Chemicals*

All reagents and solvents used were at least of analytical or HPLC quality, unless specified differently. Folin–Ciocalteu's phenol reagent and sodium carbonate were purchased from Merck (Darmstadt, Germany), L-(+)-ascorbic acid from Carl Roth (Karlsruhe, Germany), (+)-catechin-hydrate, *myo*-inositol (>99.5%, HPLC), anhydrous glycerol (≥99.5%) and *meso*-erythritol (≥99%) from Sigma Aldrich (Steinheim, Germany). Quercetin-4 -O-glucoside (spiraeoside), (all-*E*)-lutein and (all-*E*)-β-carotene were obtained from Extrasynthese (Genay Cedex, France). L-aspartic acid (Ph. Eur., USP) was received from AppliChem (Darmstadt, Germany).

### *2.2. Plant Material and Field Experimental Design*

Spinach cv. 'Silverwhale' seeds were purchased from Rijk ZwaanWelver (Welver, Deutschland) and were grown under open field conditions on a sandy loam at Geisenheim University, Germany (49◦59 N, 7◦58 E). The experimental field design has been reported earlier in detail by Schlering et al. [19]. In brief, one cultivation set per year was conducted in a plot installation between the years 2015 and 2017, resulting in three years, i.e., cultivation replicates, being grown as shown in Table 1. Each set consisted of six circular plots (marked by A, C, F, H, M and P) with an inner diameter of 11.9 m. Each plot was subdivided into four quarters (subplots) for the simultaneous cultivation of different vegetable crops with an annual crop rotation. Each subplot quarter was again divided into two further segments for the implementation of the different irrigation treatments following a randomized block design (cf. Schlering et al. [19]). The size of each segment was at least 6.5 m2, respectively. A third segment located outwardly was not harvested to avoid boundary effects but cultivation and irrigation took place as described in the next section. The irrigation levels of the subplots described below remained unchanged during the full experimental period, irrespective of the annual crop rotation.

**Table 1.** Cultivation and climate data of the spinach years during the different experimental periods. DAS: days after sowing. Irrigation (mm): Total irrigation amount including irrigation during initial stage. Total water amount (%) RWS: water amount (%) of the reduced variants including watering after sowing.


<sup>z</sup> Reference evapotranspiration (ETo) using grass and the FAO56 Penman–Monteith method. <sup>y</sup> Includes irrigation during the treatment period (6.2 L/m<sup>2</sup> x irrigation events) and the irrigation during initial growth stages.

### *2.3. Cultivation and Water Supply*

Spinach seeds were sown by a manual seed-drilling machine with row spacing of ca. 0.25 m and a sowing distance of ca. 0.013 m, corresponding to a sowing density of ca. 308 seeds per m2. Uniform fertilization with calcium ammonium nitrate was carried out according to commercial standard specifications for the cultivation of standard-quality spinach for the fresh food market (135 kg/N ha<sup>−</sup>1) based on mineralized N (NO3 −-N) in 0–30 cm soil depth.

Crop protection was applied equally to all plots, whereby application depended on the growing set, described as follows: Chemical and biological insecticides were used depending on pest occurrence. NeemAzal®-T/S (Trifolio-M GmbH, Lahnau, Germany) was used against leafminer flies (Agromyzidae) and Fastac ME (BASF-SE, Limburgerhof, Germany) was applied against aphids (Sternorrhyncha). Goldor®Bait (BASF, Ludwigshafen, Germany) had been brought into the soil before sowing once per cultivation set against wireworms (Elateridae). Weed control was done manually.

Water supply by drip irrigation was generally activated when the soil suction tension fell below −20 kPa at a 10 cm depth, as controlled by a tensiometer with an electronic pressure sensor (Tensio-Technik, Bambach, Geisenheim and Deutschland). During the initial growth stages, i.e., until the appearance of the seedlings, the soil moistures of both the well-watered control (CTR) and the reduced water supply (RWS) treatments were kept evenly moist by irrigation. Depending on the year, this period of identical water supply lasted for 19 days (2015), 20 days (2016) and 17 days (2017). Then, the well-irrigated CTR segments were provided 6.2 L/m2 per irrigation, whereas the RWS treatment was reduced to ca. 50% of that of the CTR treatment. Because of the natural precipitation, both the volume of irrigation water and also the ultimate total water volume varied strongly between years. As a result, the total water volume of the RWS was 90% (2015), 94% (2016) and 96% (2017) of that of the CTR treatments during the respective years (Table 1).

### *2.4. Harvest*

A total of 40 plants per segment was harvested randomly when most of the leaves were unfolded, representing the commercially targeted maturation stage for fresh-marketed spinach. To avoid border effects, outer rows were omitted from harvest. Specifically, harvest dates were 51, 44 and 39 days after

sowing years in 2015, 2016 and 2017, respectively (Table 1). After harvest, plants were cleaned twice manually with fresh tap water to remove adhered soil particles and roots were removed with a knife, before leaves were spun using a commercial salad spinner to remove remaining water. Subsequently, the fresh spinach leaves were frozen at −80 ◦C until further analyses.

### *2.5. Climatic Data*

Local climate data were supplied by the local weather station, which was located at 100 m distance from the experimental field site in Geisenheim. Climatic parameters for each cultivation period are summarized in Table 1, while detailed weather conditions can be obtained from Figures S1–S4 in the Supplementary Materials. Based on global irradiation and total water amount (Table 1), the three different growing periods were characterized and assigned as follows: 2015 (less irradiation, dry), 2016 (more irradiation, moist) and 2017 (more irradiation, dry). More precisely, the cultivation periods 2016 and 2017 were characterized by high global irradiation and evapotranspiration (Supplementary Figures S2 and S4), but relative air humidity was considerably lower during the vegetation period in 2016 (Supplementary Figure S3) and the temporal development of the temperature profiles were opposite between the cultivation periods. While the temperature constantly decreased in 2015, it increased substantially during the growth periods in 2016 and 2017. Altogether, temperature sum and mean air humidity did not differ strongly between years, whereas their profiles during plant growth varied strongly (Supplementary Figures S1–S4). In addition, the precipitation profiles were quite different between years (data not shown). While natural precipitation was relatively high during the first half of the growing period in 2015 and 2017, when additional irrigation was mainly initiated in the last two weeks of cultivation, the opposite was true for the cultivation set in 2016, when natural precipitation was very high in the second half of the cultivation period.

### *2.6. Sample Preparation*

For all analyses, except for the determination of ascorbic acid, 150–200 g frozen spinach leaves of each sample were lyophilized (BETA 2-8 LDplus, Martin Christ Gefriertrocknungsanlagen GmbH, Osterode am Harz, Germany) prior to grinding with a laboratory mill (IKA M 20; IKA-Werke, Staufen, Germany). Dry biomass content was determined gravimetrically using fresh and freeze-dried material. D-Glucose, D-fructose, titratable acidity, L-malic acid and fumaric acid, as well as inorganic anions like nitrate, phosphate, sulfate and chloride, were determined from aqueous extracts prepared from the lyophilized powder. For this purpose, an aliquot of 8–10 g of lyophilized plant material was thoroughly homogenized with 500 mL ultrapure water at room temperature and rigorously mixing for ca. 10 s using a stainless-steel food blender (setting 2, Waring Blender, Waring Commercial, Torrington, CT 06790, USA). After transferring the extract including solids into an 800 mL beaker using another 150 mL of added ultrapure water, extraction continued for 10 min under continuous magnetic stirring, followed by a single ultrasound-assisted extraction step in an ultrasound water bath for another 5 min. After centrifuging for 5 min at 4596× *g* to separate liquid and solid phases, the supernatants were collected, filtered and stored at −25 ◦C until analyses. Extraction procedures for all other target analytes are given below.

### *2.7. Chemical Analyses*

Unless otherwise noted, IFU-methods (International Fruit Juice Union, Paris, France) were used for determination of routine parameters in aqueous extracts, such as sugars, total acidity, organic acids and inorganic anions.

### 2.7.1. Sugars and Polyols

D-Glucose and D-fructose were determined spectrophotometrically using enzymatic kits (R-Biopharm, Darmstadt, Germany) and a Konelab 20 Xti analyzer (ThermoFisher, Dreieich, Germany).

Determination of polyols excluding the aforementioned sugars was carried out in duplicates as described by Schlering et al. [19]. Quantitation was carried out with linear external calibrations of *myo*-inositol, glycerol and erythritol.

### 2.7.2. Organic Acids

Titratable acidity, calculated as citric acid, was measured potentiometrically after titration to pH 8.1 with 0.3 M NaOH (Titroline alpha, Schott, Mainz, Germany). L-malic acid was determined spectrophotometrically using enzymatic kits (R-Biopharm, Darmstadt, Germany). Fumaric acid was determined by HPLC with UV detection and ascorbic acid by iodometric titration, as previously described [19].

### 2.7.3. Inorganic Anions

Nitrate, sulfate and phosphate were determined by ion chromatography and chloride by potentiometric titration with an AgCl-electrode, as described previously [19].

### 2.7.4. Total Carbon and Nitrogen

Elemental analyses of spinach samples for carbon and nitrogen were carried out in duplicate by the Dumas combustion method (Vario MAX CNS, Elementar Analysensysteme GmbH, Langenselbold, Germany), combusting 300 mg of lyophilized and powdered plant material at 950 ◦C. L-aspartic acid was used as a reference substance.

### 2.7.5. Minerals and Trace Elements

Minerals and trace elements were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES) (SPECTRO ARCOS, SPECTRO Analytical Instruments, Kleve, Germany) after Kjeldahl digestion with the Gerhardt Turbotherm rapid digestion unit (C. Gerhardt GmbH & Co. KG, Königswinter, Germany), as reported earlier [19].

### 2.7.6. Total Phenols

An aliquot of 500 mg of lyophilized powdered plant material was extracted twice with 12 mL of 70% aqueous methanol under ultrasonication for 30 min. After centrifuging for 10 min at 12,857× *g*, the combined supernatants were made up to 25 mL with extraction solvent and stored at −28 ◦C until spectrophotometric analyses with the Folin–Ciocalteu reagent. A linear (+)-catechin calibration was used as described previously [20].

### 2.7.7. Flavonoids

Flavonoids were extracted from lyophilized powdered material as described for total phenols (see above) in duplicates. Extracts were filtered through a 0.2 μm membrane using a polytetrafluoroethylene (PTFE) syringe filter (Macherey-Nagel, Düren, Germany), before extracts were analyzed with reversed-phase HPLC equipped with a photodiode array detector (RP-HPLC/PDA) with negative electrospray ionization mass spectrometry (ESI-MS) on an Accela/LXQ system (ThermoFisher, Dreieich, Germany). Chromatographic separation was achieved on a 150 × 2 mm, 3 mm C18 (2) Luna column (Phenomenex, Aschaffenburg, Germany) protected with a guard cartridge of the same material. Injection volume was 4 μL and elution conditions were the following: flow rate 250 mL/min at 40 ◦C, solvent A was water/formic acid (95:5, v/v), solvent B was methanol, 1 min isocratic conditions with 10% B, linear gradient from 10% to 55% B in 25 min, followed by washing with 100% B and re-equilibrating the column. MS scan range was set at m/z 250–1050 (negative mode). The MS settings were: ESI source voltage +4.5 kV, capillary voltage 32 V, capillary temperature 275 ◦C, collision energy for MS<sup>n</sup> experiments 30%. Flavonoids were identified by comparison of their retention times, UV/Vis and mass spectral data with those of authentic standards or published data [21,22]. Flavonoids were quantified

at 360 nm using an external spiraeoside standard (Extrasynthese, Lyon, France) in a linear range of 5–100 mg/L.

### 2.7.8. Carotenoids

An aliquot of 75 mg of lyophilized powdered spinach was combined with ca. 0.4 g of NaHCO3 in a glass tube prior to extraction with 4 mL of a mixture of n-hexane/acetone (2:3, v/v) using vortex stirring for 10 s. Then, the extracts were stored on ice in the dark for 10 min using an intermediate stirring step after 5 min. After centrifuging at 4596× *g* for 10 min at 4 ◦C, the supernatant was collected in 25 mL amber glass volumetric flasks previously flushed with N2. The remaining solids were extracted further four times and the obtained extracts were combined and then transferred quantitatively to amber round-bottomed flasks prior to evaporation to dryness under reduced pressure at 25 ◦C (Rotavopar R-210, Büchi, Switzerland). The dried extract was re-dissolved in HPLC solvent A (see below), transferred to a 10 mL volumetric flask, made up to 10 mL, and filtered through a 0.2 μm membrane filter (Chromafil O-20/25 PTFE syringe filter; Macherey-Nagel, Düren, Germany) into an HPLC vial. Carotenoids contained in the extract were separated with a HPLC-PDA system consisting of a Dionex P 680 HPLC pump, a Dionex STH 585 column oven and Dionex PDA-100 Photodiode Array Detector (Dionex/Thermo Fisher Scientific, Germany), which was mounted with a YMC Carotenoid (C30)-column (4.6 × 250 mm, 5 μm particle size, YMC, Kyoto, Japan) protected with a guard column of the same material. Column temperature was 20 ◦C. Solvent A was a quaternary mixture of methanol (MeOH), methyl *tert*-butyl ether (MTBE), water anda1M ammonium acetate solution (AAc) (MeOH/MTBE/H2O/AAc, 88:5:2:5, v/v/v/v) and solvent B a ternary mixture of MeOH/MTBE/AAc (20:78:2, v/v/v). A linear gradient from 0% to 85% B in 45 min followed by a linear gradient to 100% B in 5 min was applied, followed by an isocratic equilibration step with 100% B for 10 min. Flow rate was 1 mL/min. Total run time was 60 min. Injection volume was 20 μL. Compounds were identified by comparing their retention times and UV/Vis absorption spectra to those of authentic reference compounds ((all-*E*)-lutein, (all-*E*)-β-carotene) and literature (violaxanthin, neoxanthin, (*Z*)-isomers of β-carotene, Britton [23]). Carotenoids were quantified at 450 nm. An external linear calibration of authentic (all-*E*)-lutein was used for quantitation of violaxanthin, neoxanthin and (all-*E*)-lutein, while authentic (all-*E*)-β-carotene calibrations were used for quantitating (9*Z*)-β-carotene and (all-*E*)-β-carotene.

### *2.8. Statistical Analyses*

Analytical results were calculated based on both dry and fresh biomass (i) to enable evaluations regardless of different water contents in the plant material by dry biomass-related data and (ii) to assess the nutritional values of the harvested edible plant material by fresh biomass-related data. Data were analyzed by fitting a linear mixed-effect model using the lmer-function within the lme4-package [24] of the statistical software R [25] in RStudio [26]. The evaluation of the single years was based on a model which aimed at correcting for random plot-effects (Equation (1)), while the total dataset was evaluated with respect to the interaction of plot and year (Equation (2)):

$$\text{y} \sim \text{H}\_2\text{O} + \text{(1|plot)}\tag{1}$$

$$\text{by} \sim \text{H}\_2\text{O} + \text{(1|plot:year)}\tag{2}$$

Comparisons of means derived from different treatments were considered significantly different if *p* < 0.10. Pairwise comparison of least-squares means was carried out with lsmeans-package [27] to estimate fixed-effects of the treatment as well as random effects for the plot and season. Significances of random effects were calculated by the lmer test-package [28]. The results for the treatment (CTR: control, RWS: reduced) were evaluated on the basis of adjusted data generated from the model mentioned above. Principal Component Analysis (PCA) was carried out by using the R-packages FactoMineR [29] and factoextra [30]. Within PCA analysis, individual samples were visualized in a score plot, while corresponding chemical components were represented in a loading plot inside

a correlation circle presenting the relationship between the variables. To avoid an overweight of flavonoids and carotenoids by representation of individual components, only total amounts were considered for PCA.

### **3. Results and Discussion**

### *3.1. Evaluation of Years and Season*

According to the PCA of data that had been corrected for plot effects (Equation (1)), the three years derived from three consecutive growing years (2015, 2016 and 2017) were clearly differentiated by their chemical composition, highlighting the strong influence of the year on the product quality. Similar results were already shown for radish grown within the same experimental field site [19]. The first two principal components (PCs) accounted for 63.7% of the total variance considering dry biomass-related data (Figure 1) and for 65.6% considering fresh biomass-related data (data not shown). Similar year-to-year variations have been reported earlier for other vegetable crops [31,32]. While the two sets from 2015 and 2016 were clearly distinguishable over the first principal component (Dim1, Figure 1), the set from 2017 was additionally separated over the second principal component (Dim 2). The year 2015 was characterized by comparably low sunlight exposure (global irradiation: 453.5 MJ/m2) as compared to 2016 (799.9 MJ/m2) and 2017 (756.9 MJ/m2). Consequently, evapotranspiration was higher in 2016 (126.9 mm) and 2017 (126.6 mm) in contrast to 2015 (68.7 mm). The years 2016 and 2017 were different when considering the total water amount the plants received. In 2016, total water supply was higher (184 mm) than 2017 (113 mm), with the latter being similar to that in 2015 (104 mm, Table 1).

**Figure 1.** Principal Component Analysis (PCA) of the original, plot-adjusted dataset including all spinach years from 2015 (red circles), 2016 (green triangles) and 2017 (blue squares). Score plot represents the individual samples of each cultivation set (separated by color) and plot (marked by the letters A, C, F, H, M and P) based on dry biomass-related data.

### *3.2. E*ff*ects of Reduced Water Supply on the Chemical Composition of Spinach Biomass*

The PCA of the entire dataset adjusted by the interaction of plot and year (Equation (2)) revealed that well-irrigated spinach samples were mainly clustered in sectors with negative PC2, while those grown under mildly reduced water supply were mainly located in sectors with positive PC2 (Figure 2A). Most of the individuals were separated by the second principal component PC2 (Dim2), which, however, accounted for only 14.1% of the total variance. The first two principal components (Dim1 + Dim2) accounted for 38.7% of the total variance in the dataset. As shown in the corresponding loading plot (Figure 2B), the most important variables with high contribution to Dim2 were dry-matter-based contents in trace elements like manganese (Mn), zinc (Zn), iron (Fe), total phenols, flavonoids, polyols, as well as nitrate, nitrogen (N), potassium (K) and carotenoids. Dim1 was mainly influenced by contents of sugars (glucose, fructose), organic acids (malic acid, fumaric acid) and anions (chloride,

sulfate). Apart from these multivariate analyses, a univariate statistical evaluation shown in Table 2 was conducted to underpin the multivariate estimate. While CTR samples were characterized by higher contents of organic acids like malic and fumaric acid, as well as certain anions like chloride, phosphate and sulfate, the content of inositol and trace elements such as Zn and Mn as well as flavonoids was lower than in samples derived from RWS treatments (Table 2). However, the univariate results also pointed out that the levels of glucose, fructose, quantitatively abundant elements (K, N, P, Ca and Mg) and carotenoids remained widely unaffected by mild water reduction. Only in 2015, when the highest relevant water reduction was achieved, i.e., 10% less than the well-watered control, did some minerals and carotenoids show increased dry biomass-based contents in the RWS samples (Table 2). In our earlier study on red radish root tubers, the identical environmental conditions had not led to an increase in the corresponding levels [19]. In this study, leaves of spinach reacted to the identical water deficits by both the increase of polyols and the accumulation of certain trace elements such as Mn and Zn.

**Figure 2.** Multivariate evaluation by PCA (PC1 + PC2) of the total spinach dataset including all years (2015, 2016 and 2017) based on dry biomass-data. Score plot (**A**) represents all individual plot samples (marked by the letters A, C, F, H, M and P) classified according to the control (CTR, blue circles) and reduced water supply (RWS, red triangles). The corresponding loading plot (**B**) shows the related variables determined by the chemical analyses.

The distinction of both water supply treatments by PCA with fresh biomass-related data was significantly clearer (Figure 3A) than that based on dry biomass-related data (Figure 2A). With very few exceptions, fresh biomass-based data allowed for distinguishing both groups clearly over the first principal component (Dim1), explaining 28.8% of the total variance. Upon addition of the second principal component (Dim2), a share of 46.7% of the total variance was explained. In contrast to red radish root tubers grown under control and reduced water supply conditions [19], the fresh biomass-based discrimination of spinach from well-watered versus reduced water treatments was not mainly based on primary metabolites like polyols, total carbon and ascorbic acid, but also on secondary metabolites such as total phenols, flavonoids and carotenoids, as well as selected minerals and trace elements (Figure 3). In brief, fresh biomass-related contents of most of the targeted chemical components, especially those of polyols, minerals, trace elements and secondary metabolites such as flavonoids and carotenoids, were increased in spinach samples grown under reduced water supply. The univariate evaluation shown in Table 3 confirmed these results. The fresh biomass-based contents of all of the studied carotenoids, i.e., violaxanthin, lutein and ß-carotene, showed significant and rather uniform increases (Table 3, Supplementary Table S1).


*Horticulturae* **2020** , *6*, 25

**Table 2.** Influence of reduced water supply on the dry biomass

(DM)-related

 levels of constituents

 of spinach leaves from different years (2015, 2016 and 2017). Linear


#### *Horticulturae* **2020** , *6*, 25


**Table 3.** Influence of reduced water supply on the fresh biomass (FM)-related levels of constituents of spinach leaves from different years (2015, 2016 and

 2017).



**Figure 3.** Multivariate evaluation by PCA (PC1 + PC2) of the total spinach dataset including all years (2015, 2016 and 2017) based on fresh biomass-data. Score plot (**A**) represents all individual plot samples (marked by the letters A, C, F, H, M and P) classified according to the control (CTR, blue circles) and reduced water supply (RWS, red triangles). The corresponding loading plot (**B**) shows the related variables, i.e., contents of constituents as determined by the chemical analyses.

It is noteworthy that the ratio of individual carotenoids in chloroplast-containing plant tissues is rather constant due to their pivotal role in photosynthesis, commonly 20%–25% β-carotene, 40%–45% lutein, 10%–15% violaxanthin and 10%–15% neoxanthin [33]. Occasionally, the levels of xanthophyll cycle carotenoids, such as antheraxanthin, were reported to be increased upon exposure of the plant to abiotic stress [34]. Findings similar to those of our study were found earlier for antioxidant compounds such as carotenoids and tocopherols in rocket (*E. sativa* Mill. var. Golden line) in the case of moderate drought stress followed by re-watering at the end of the cultivation period [7]. However, the same experiment did not result in higher levels of such antioxidants in spinach [7]. Altogether, fresh biomass-based contents of many other constituents in spinach showed a significant increase, possibly being related to higher dry biomass content of reduced watered plants (Table 2), which was also shown for cabbage (*Brassica oleracea* L.) subjected to drought stress just during head development [35].

### *3.3. Sugars and Polyols*

The content of sugars such as glucose and fructose was hardly affected by moderate water reduction, but was characterized by high variations between the years irrespective of the water supply treatment. The dry biomass-related data emphasized that glucose was highest in 2016 (62.70–72.92 mg/g dry matter (DM)) in contrast to other years (50.92–59.55 mg/g DM), while fructose levels were highest in 2015 (43.35–43.59 mg/g DM) compared to 2016 (30.94–37.58 mg/g DM) and 2017 (27.70–29.41 mg/g DM, Table 2). As shown in Table 1, the 2015 set was characterized by comparably low irradiation (453.5 MJ/m2) in contrast to 2016 (799.9 MJ/m2) and 2017 (756.9 MJ/m2), but the growing period was considerably longer in 2015 (51 days) in contrast to 2016 (44 days) and 2017 (39 days). These conditions, typically occurring during late growing seasons in autumn, resulted in the highest levels of fructose in 2015, while high light intensities, which are known to increase soluble carbohydrates in spinach [36], led to the highest contents of glucose in 2016. While both tended to decrease with mild water reduction in 2016 (*p* = 0.1521 and *p* = 0.0721 respectively, Table 2), when global irradiation and evapotranspiration were high, values were unaffected or increased in 2015 and 2017 due to mild water reduction. These trends were found for both dry and fresh biomass-related data.

In general, contents of dry biomass were significantly higher in 2015 (8.54%–8.60%) compared to other years (5.40%–6.83%), which automatically leads to enhanced values in the fresh biomass-related results (Table 3). By analogy, the overall glucose and fructose levels were higher in 2015 (537–564 mg and 410–413 mg per 100 g FM, respectively) than in other sets (318–403 mg glucose and 171–208 mg fructose per 100 g FM) (Table 3) without significant differences between the treatments.

Analogous to glucose and fructose contents, inconsistent effects of mild water reduction were found regarding the content of polyols in spinach dry biomass. Interestingly, the levels of polyols, particularly those of *myo*-inositol and glycerol, were lowest in 2016, although glucose levels were highest. These findings were in contrast to those found for radish, which showed congruently high levels of glucose and polyols [19]. Total polyols were generally lowest in 2016 (3.87 mg/g DM), being significantly increased to 4.09 mg/g DM upon reduced water supply (*p* = 0.0302) (Table 2). In contrast, levels in 2015 were higher (5.91 mg/g DM), but no changes in concentration were observed upon reduced water supply, although total water reduction was highest (−10%). These findings indicated that factors other than water supply had overruled a potential, marginal effect of the water supply. In our earlier study on red radish, a water reduction of 15%–20% led to significant increases of polyols [19]. Probably, reduced photosynthesis and the associated lowered growth under comparably "low light" conditions in 2015 (daily mean global irradiation: 8.7 MJ/m2) have not influenced the assimilation and allocation of photosynthetic products as much as in 2016 and 2017, when plant growth was accelerated by higher levels of daily irradiation (17.8 and 18.9 MJ/m2, respectively). In this context, Quick et al. [37] has shown that the levels of soluble carbohydrates in leaves of two annual crops (*Lupinus albus* L. and *Helianthus annuus* L.) were maintained when exposed to water stress under field conditions, even though photosynthesis was strongly inhibited. Maintenance of soluble sugars probably occurs because partitioning was altered in water-stressed plants [37]. In brief, the accumulation of polyols in spinach leaves seemed to be more sensitive to moderately reduced water supply than that in radish root tubers, which only showed increased levels after more severe reductions in water supply (≥15% lower than full water supply), as described in Schlering et al. [19].

### *3.4. Organic Acids*

Organic acids' contents in spinach were inconsistently influenced by moderate water reduction, depending on the cultivation period (year). While dry biomass-based contents of ascorbic acid significantly increased in 2015, those of oxalic and fumaric acid decreased (Table 2). Differences in malic acid contents were insignificant comparing the treatments in 2015, but they were significantly reduced by RWS in 2016. Significant differences for malic acid were also found considering the entire dataset. Cutler and Rains [38] observed significantly increased accumulations of malic acid in leaves of cotton (*Gossypium hirsutum* L.) exposed to water stress, explained by osmotic adjustment and the importance of malate in turgor regulation of stomatal guard cells [38,39]. However, in our study on spinach, rather inconsistent changes in malic acid levels were observed, presumably because mild water reduction applied in this experiment had not been severe enough to cause sufficient stress to alter the plants' metabolism.

The significant increase of dry biomass-related ascorbic acid levels in spinach grown in 2015 (*p* = 0.0493) was in agreement with findings of Koyama et al. [6], who demonstrated an augmentation of ascorbic acid by lower water supply in hydroponically grown leafy vegetables such as lettuce and spinach. In contrast to our study, Koyama et al. [6] did not observe significant alterations in the water content. In our study, by analogy to polyols, ascorbic acid levels were highest in the relatively "low light, dry" cultivation set in 2015, both in dry and fresh biomass, possibly being related to lower global irradiation, which has previously been shown to enhance ascorbic acid contents in spinach [40]. The comparably high content of dry biomass in 2015 contributed to the increased fresh biomass-based levels of ascorbic acid (80.49–85.30 mg/100 g FM) as compared to other years (23.62–46.02 mg/100 g FM).

### *3.5. Inorganic Anions*

The dry biomass-related contents of anions such as phosphate (PO4 <sup>3</sup><sup>−</sup>) and sulfate (SO4 <sup>2</sup>−) were significantly decreased by RWS in 2015. By analogy, red radish root tubers studied within the same field experiment exhibited significant decreases of PO4 <sup>3</sup><sup>−</sup> upon similar water reduction, i.e., to 80% of full water supply [19]. Phosphate uptake into the roots might have been diminished under RWS [41], because its mobility depends on soil moisture [10]. On the other hand, the mineralization of organic

matter by microbial activity, responsible for the release of ions such as H2PO4 <sup>−</sup> and HPO4 <sup>2</sup><sup>−</sup> [11], might have been negatively affected due to water reduction. A significant decrease of dry biomass-related levels of SO4 <sup>2</sup><sup>−</sup> was measurable in 2015 (*p* = 0.0192), when total water reduction was highest compared to other years, but the contents of SO4 <sup>2</sup><sup>−</sup> (*p* = 0.0910) and chloride (Cl−) (*p* = 0.0692) were also reduced in 2016, when water reduction was lower (Table 2). When considering the overall dataset, a dry biomass-related decline of PO4 <sup>3</sup><sup>−</sup> (*p* = 0.0594) and Cl<sup>−</sup> (*p* = 0.0053) was observed in plants that had received slightly reduced water amounts, but the content of SO4 <sup>2</sup><sup>−</sup> also declined (*p* = 0.1151). In contrast, Abdel Rahman et al. [42] observed an accumulation of Cl− in grasses and legumes as a result of decreasing soil moisture.

In contrast to the above-mentioned anions, the influence of RWS on the dry biomass-related nitrate (NO3 <sup>−</sup>) levels in spinach was insignificant. However, an unexpected increase of NO3 − in fresh biomass-based levels upon limited water supply was observed in 2016 (*p* = 0.0238, Table 3). The opposite was found in previously reported studies of fresh biomass-related nitrate levels of lettuce (*Lactuca sativa*) [6] and carrots (*Daucus carota* L.) [43] exposed to drought stress. In principle, NO3 −-flux from roots to leaves is believed to generally decrease during drought stress [44], being accompanied by a reduced expression of the nitrate reductase enzyme [45]. This did not apparently occur in spinach grown under RWS in our study, since dry biomass-related levels did not differ between water supply treatments. It is noteworthy that there was also a strong impact of the cultivation year. NO3 − contents were substantially higher in the moist year 2016 (28.16–28.60 mg/g DM) compared to other comparably drier years 2015 and 2017 (7.73–12.98 mg/g DM), as shown in Table 2. Presumably due to frequent and high precipitation events towards the end of the cultivation period in 2016 (data not shown), a high absorption of NO3 <sup>−</sup> might have led to higher NO3 − levels. This hypothesis warrants further study. Nevertheless, in agreement with our study, a positive correlation was found between NO3 − and water contents in spinach [46]. Custi´ ´ c et al. [47] also observed increased NO3 − accumulation under warm and wet conditions in chicory (*Cichorium intybus*). It is known that NO3 − accumulation varies with the season [47] and is greatly affected by environmental factors [48]. Santamaria et al. [49] observed more than doubled NO3 − levels in rocket, accompanied by a decrease in dry biomass, when temperature increased from 10 to 20 ◦C. An inverse correlation of fresh biomass-based NO3 − and oxalate levels with those of dry biomass content was also confirmed by our results. Therefore, the markedly increased NO3 − levels in 2016 might have occurred due to high temperature (Supplementary Figure S1) and a simultaneously high water supply (data not shown) along with decreasing irradiation (Supplementary Figure S2) by the end of the cultivation period. It is well known that low irradiation promotes NO3 − accumulation in spinach [11,50].

### *3.6. Carbon*

The dry biomass-related content of total carbon (C) remained unaffected by RWS in spinach, as shown in Table 2. Fresh biomass-related levels were significantly higher in less irrigated plants (2.48 mg/g FM) in contrast to well-irrigated samples (2.20 mg/g FM) only in 2017, when, simultaneously, the dry biomass content also significantly increased, despite the comparably low water reduction (by 4%). Nevertheless, multivariate analysis supports the contribution of C to the separation of both groups in the PCA plot on a fresh biomass basis (Figure 3).

### *3.7. Nitrogen*

Dry biomass-related total nitrogen (N) was not affected, but fresh biomass-related data was significantly influenced by RWS when considering the data across all three years (Tables 2 and 3). For instance, dry biomass-related N levels remained unchanged in 2016 and 2017, irrespective of the water supply treatment (*p* = 0.7042 and 0.7088, respectively), but they only marginally increased from 50.92 to 51.64 mg/g DM in 2015 (*p* = 0.0682). Upon reduced water supply, fresh biomass-related N levels significantly increased from 176.2 to 202.6 mg/100 g FM in 2016 (*p* = 0.0065) and from 238.58 to 262.42 mg/100 g FM in 2017 (*p* = 0.0097). A similar increase from 273.99 to 291.73 mg/100 g FM

was found considering the whole dataset (*p* = 0.0013), but not when considering data of 2015 only (407.22 versus 410.14 mg/100 g FM for CTR and RWS respectively, Table 3). Multiple irrigation events in 2015 might have evoked drying–re-wetting conditions, which are known to increase soil-available N and, therefore, might have alleviated the negative effect of drought on reduced N mineralization [51].

In agreement with our fresh biomass-related data, dry biomass-related total N levels were highest in 2015 (50.92–51.64 mg/g DM) as compared to the other years (38.07–42.47 mg/g DM). These findings might be explained by the fact that, in 2015, spinach was cultivated in autumn and therefore harvested after a longer growth period (51 days) as compared to 2016 and 2017 (44 and 39 days, respectively), as caused by lower irradiation in 2015. The lowest N levels were found in 2016 when total water amount as well as irradiation sum and temperature sum were highest compared to other years (Table 1) and precipitation was more frequent just before harvest (data not shown). Different results were found earlier for red radish with highest contents of nitrogen under moist conditions [19].

### *3.8. Potassium*

Water supply limitation resulted in significantly increased levels of potassium (K+) in spinach dry biomass in 2015 only (Table 2), when water reduction was most pronounced. According to fresh biomass-related PCA analyses (Figure 3), where most of the minerals were contributing to the separation of the treatments, significantly higher levels of K<sup>+</sup> were found in spinach grown under reduced water conditions in 2015 and 2017 (Table 3). While dry biomass content of reduced watered spinach was significantly higher in 2017, which might explain the increase in K<sup>+</sup> based on fresh biomass, the dry biomass content did not differ in 2015 with reduced water supply. Anyway, the availability of K<sup>+</sup> from the soil was shown to decrease with declining soil water content due to decreasing mobility of K<sup>+</sup> [52]. Our results indicated that K<sup>+</sup> uptake, which is often reduced under drought conditions [53,54], was not significantly affected by moderate water reduction. The highest absolute K<sup>+</sup> levels in spinach were found in 2016 (85.60–87.88 mg/g DM) and 2017 (89.89–90.68 mg/g DM), when global irradiation and evapotranspiration rates were high and temperatures continuously increased during the cultivation period (Supplementary Figures S1, S2, S4).

### *3.9. Phosphorous*

In accordance with other macronutrients, dry biomass-related levels of phosphorous (P) were higher in less irrigated than in well-watered spinach in 2015 (*p* = 0.0596), but not in other years (Table 2). Similar to N, fresh biomass-related P levels were significantly increased in all years as well as in the overall dataset (*p* = 0.0004, Table 3), which probably can be traced back to higher contents of dry biomass in samples obtained from the reduced watered plants. This result was also visible in the PCA on fresh biomass-based data, where P clearly contributed to the differentiation of both treatments. In contrast, red radish root tubers grown within the same experimental field site revealed a significant decrease of P based on dry biomass, while fresh biomass-related data showed no effect [19]. In general, the fresh biomass-based P levels differed strongly between the cultivation set of 2015 (47.65–50.96 mg/g DM) and those of 2016 and 2017 (29.77–34.09 mg/g DM). One possible explanation might be the prolonged cultivation time in 2015 (51 days) and the associated high content of dry biomass (8.54%–8.60%) in contrast to other years (5.40%–6.83%). The shortened cultivation times in 2016 (44 days) and 2017 (39 days) might have resulted in lower absolute nutrient uptake from the soil.

### *3.10. Calcium*

Calcium (Ca2+) content of spinach was independent of the water supply. Generally, lower Ca2<sup>+</sup> levels were found in 2015 (10.85–11.69 mg/g DM) compared to the other years 2016 and 2017 (13.78–14.94 mg/g DM). This result is in contrast to those found for N, which displayed the highest levels in 2015. Since Ca2<sup>+</sup> is a readily available element for plant uptake from the soil, high Ca2<sup>+</sup> levels have earlier been suggested to be associated with high concentrations in the soil rather than with potential relationships with uptake efficiency or transpiration velocity of the plant [41,55]. In agreement with our findings, Sánchez-Rodríguez et al. [56] did not find any difference in the Ca2<sup>+</sup> accumulation of tomato leaves exposed to moderate drought stress, even though its uptake was significantly reduced. These findings are in further agreement with those from Hu and Schmidhalter [57], stating that Ca2<sup>+</sup> accumulation was much less sensitive to drought than that of K and phosphate. Basically, Ca2<sup>+</sup> has structural functions and acts as an important second messenger [58]. Since important plant functions are controlled by very small, but physiologically active pools of Ca2<sup>+</sup> within the cytoplasm [59], the observed insignificant effects of moderate water reduction on the Ca2<sup>+</sup> levels in spinach had been expected.

### *3.11. Magnesium*

The dry biomass-based content of magnesium (Mg2+) in spinach was significantly reduced by RWS in 2015, but not in 2016 and 2017. Thus, multivariate analysis by PCA did not show a strong contribution of Mg2<sup>+</sup> to the differentiation of both groups (Figure 2). The same result was found for fresh biomass-based analyses (Table 3). In agreement with our findings, effects of moderate water reduction had no effects on Mg2<sup>+</sup> levels in leaves of cherry tomatoes and were dependent on the cultivar [56]. In contrast, Pulupol et al. [60] found higher fresh biomass-based Mg2<sup>+</sup> levels in tomato fruits grown under deficit irrigation, while dry biomass-related amounts were influenced insignificantly. Also, radish cultivated under RWS within the same experiment exhibited no significant changes in fresh biomass-related Mg2<sup>+</sup> levels [19].

### *3.12. Micronutrients (Fe, Zn, Mn, Cu)*

Significant effects on the dry biomass-related contents of iron (Fe) and copper (Cu) were not observed in our study, irrespective of water supply and cultivation year. However, dry biomass-based zinc (Zn) and manganese (Mn) contents were significantly increased by limited water supply (Table 2). PCA analyses supported the contribution of these micronutrients to variant differentiation (Figure 2). Similar findings were evident during analyses of fresh biomass-related data (Table 3, Figure 3). In contrast, moderate water reduction resulted in significantly decreased contents of Mn in radish root tubers grown within the same field experiment [19]. By analogy, water deficit-conditions have been shown to lead to lower Mn levels in leaves of cherry tomatoes [56].

### *3.13. Phenolic Compounds*

In spinach dry biomass, total polyphenol content, including flavonoids, remained unchanged with RWS considering both the single datasets as well as the total dataset across all cultivation years. The levels of total flavonoids, as derived by summing up levels of individually quantitated flavonoids (Supplementary Tables S2 and S3), remained highly similar within a narrow range in all individual years (9.82–10.56 mg/g DM), while the amount of total polyphenol contents were marginally higher in 2016 (11.26–11.80 mg/g DM) and 2017 (11.38–11.42 mg/g DM) as compared to 2015 (10.09–10.31 mg/g DM).

In contrast to the quite stable dry biomass-related contents, fresh biomass-based contents displayed a much higher variability, particularly considering total flavonoids ranging from 54.45 to 86.93 mg/100 g FM. Fresh biomass-related levels of total flavonoids were significantly higher in reduced watered spinach than in well-watered spinach in 2017, which, however, was obviously based on significantly higher levels in dry biomass (Table 3). The levels found were in accordance with those of a previous study of Gil et al. [17], who found ca. 1000 mg/kg total flavonoids in fresh cut spinach. Because of generally higher contents of dry biomass in 2015, the fresh biomass-related levels of total flavonoids (86.52–86.93 mg/100 g FM) were substantially greater in 2015 as compared to those found in other years, reaching the lowest levels in 2016 (54.45–59.17 mg/100 g FM, Table 3). In accordance, strong seasonal variations in the levels of flavonoids such as quercetin and kaempferol were found in leafy vegetables such as lettuce (1.9–30 mg/kg quercetin) and endive (15–95 mg/kg kaempferol), based on fresh biomass-analyses [61]. Apart from fresh biomass-based variations, flavonoid levels in our study did not show any differences if compared on a dry biomass basis, even if there were strong differences

in the global irradiation levels during the cultivation periods (Table 1, Supplementary Figures S1–S4). A rather low dependence or even independence of flavonoid contents from climatic factors such as temperature and global irradiation were reported previously in kale (*Brassica oleracea* var. *sabellica*) by Schmidt et al. [62].

Focusing on flavonoids, Bergquist et al. [22] observed the highest concentrations in baby spinach at early growth stages accompanied by high variations as associated with different sowing times. Furthermore, Hertog et al. [61] showed quite strong seasonal variations in the flavonoid levels of leafy vegetables such as lettuce and endive, which were 3 to 5 times higher in summer than in other seasons. In our study, the highest amounts of flavonoids in spinach fresh biomass were found in 2015 (86.52–86.93 mg/g FM), when cultivation took place in autumn with relatively low global irradiation in contrast to other years which had been sown at springtime (54.45–73.40 mg/ FM).

For individual flavonoids, RWS did not induce any clear effect in spinach. Univariate analyses indicated a dry biomass-related increase of some minor patuletin-derivatives in 2015 as well as an increase in the levels of a few more abundant flavonoids in 2016 upon moderate water limitation (Supplementary Table S3). For example, levels of specific patuletin- and spinatoside-derivatives (e.g., compounds **3**, **5** and **11**, Supplementary Table S2) were partly increased by RWS in 2015 and 2016. Among the other flavonoid-derivatives, the content of spinatoside, which represented one of the most abundant flavonoid-compounds in spinach according to a comparison of our mass spectral data to those reported previously by Aritomi et al. [63], tended to increase by RWS in 2016 (*p* = 0.0677). Apart from that, the study of Bergquist et al. [22] demonstrated that flavonoid profiles of baby spinach were highly similar during all growth stages, although the relative amounts of the individual flavonoids were prone to changes. Similar results were found in our study when comparing the different years, with hardly any difference in total flavonoids years, but individual flavonoids varied widely (Supplementary Table S3). The contents of individual flavonoids were almost the same when grown during early 2016 and 2017, while the proportions were markedly different when grown in late 2015. While an apparent methylenedioxyflavone-glucuronide (5,3 ,4 -trihydroxy-3-methoxy-6:7-methylene-dioxyflavone-4 -β-D-glucuronide [21,22]) was the main flavonoid in 2016 and 2017 (30.0%–30.4%, Supplementary Table S4), the spinatoside accounted for the largest proportion in 2015 (20.2%–20.5%, Supplementary Table S4). A clear causal relationship between moderate limitations in water supply and changes in single or total flavonoids could not be established, which might indicate that the RWS effect on the levels of these compounds was rather low. Nevertheless, further studies in more controlled environments and, possibly, with more severe reductions in water supply, should be encouraged.

### *3.14. Carotenoids*

In general, (all-*E*)-lutein was the major carotenoid found in spinach, followed by β-carotene and violaxanthin, which is in accordance with what had been expected in photosynthetically active plant tissues [33]. Moderately reduced water supply did not show clear effects on the contents of total carotenoids in spinach when evaluating the dry biomass-related dataset (Table 2). There was a slight increase of β-carotene, (9*Z*)-β-carotene and total carotenoids in 2015, not reaching statistical significance. In contrast, fresh biomass-related levels of all carotenoids significantly increased with RWS in all three cultivation years (Table 3). In contrast to the lack of effect of water supply, a seasonal variation was observed. For instance, total carotenoid levels in spinach dry biomass were ca. two-fold higher in 2017 (7.22–7.25 mg/g DM) than in 2015 and 2016 (3.03–4.11 mg/g DM). The high level of global irradiation in 2017 (756.9 MJ/m2) had been expected to lead to comparably high levels of carotenoids, because increased radiation has been shown to enhance the accumulation of carotenoids in green vegetables [7]. This hypothesis would have explained the low carotenoid levels in 2015 with a global irradiation of 453.5 MJ/m2, but not the low carotenoid levels in 2016 (3.03–3.05 mg/g DM) which were characterized by a high global irradiation (799.9 MJ/m2). Carotenoid synthesis and accumulation must have been impacted by other, yet unknown, factors, such as the occurrence of multiple short-time drought events during the plant growth in 2016. By analogy to the levels of flavonoids, a clear effect of

moderate water limitation and season on the levels of carotenoids was not observed in our open filed cultivation experiment.

### **4. Conclusions**

In this study, the chemical composition of both dry and fresh biomass of spinach was shown to be strongly influenced by climatic conditions and/or water supply. The effects were highly dependent on the type of nutrient. Even moderately reduced water supply led to significant increases of dry biomass, which in turn often led to increased levels of numerous constituents and, thus, apparently enhanced the nutritional value of the vegetable product. For instance, fresh biomass-related levels of ascorbic acid, potassium, nitrogen, phosphorous as well as total flavonoids and carotenoids increased upon limiting water supply. Our results indicated that changes in levels of characteristic flavonoids might depend on seasonal variations, although further study is needed in this regard. Considering the composition of the dry biomass itself, we demonstrated that even mild water supply reductions led to significant increases of inositol, zinc and manganese levels, while malic acid, phosphate and chloride levels decreased. It is likely that such climate-related reductions in water supply will occur more frequently in the future, as is already occurring more and more due to the presumably accelerating climate change. In summary, our results indicate that the nutritional composition of spinach is sensitive to even moderately reduced water supply, but the overall quality of fresh spinach did not suffer regarding the levels of health-promoting constituents such as minerals, trace elements, flavonoids and carotenoids.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2311-7524/6/2/25/s1: Figure S1–S4: Daily mean weather conditions during the different spinach cultivation periods of 2015, 2016 and 2017: (1) Mean air temperature (◦C), (2) global irradiation sum (W/m2), (3) daily mean relative humidity (%) and (4) daily mean evapotranspiration (mm). DAS: Days after sowing. Figure S5: HPLC-DAD chromatogram of spinach flavonoids at 350 nm. Flavonoid peaks assigned by comparing retention times, UV/Vis-spectra and mass spectral data to those reported by literature as shown in Table S2. Table S1: Proportion of single carotenoids on the total amount of carotenoids in spinach fresh biomass from three years (2015, 2016 and 2017). CTR: Control treatment with full water supply, RWS: Reduced water supply treatment. Table S2: Peak assignment to flavonoid-compounds as detected in spinach from years 2015, 2016 and 2017 by comparing retention time (RT), UV/Vis-spectra and negative ion m/z and important MS/MS-fragments to the literature. An exemplary chromatogram is shown in Figure S5. Table S3: Influence of reduced water supply on the dry biomass (DM)-related levels of single flavonoid compounds in spinach leaves from three years (2015, 2016 and 2017). Linear mixed model, t-test, *p*-values: < 0.1, < 0.05 (\*), < 0.01 (\*\*) and < 0.001 (\*\*\*); CTR: Control treatment with full water supply, RWS: Reduced water supply treatment. Compound to peak number assignment is provided in Table S2. Table S4: Proportion of single flavonoids on the total amount of flavonoids in spinach dry biomass from three years (2015, 2016 and 2017). CTR: Control treatment with full water supply, RWS: Reduced water supply treatment. Compound to peak number assignment is provided in Table S2.

**Author Contributions:** Conceptualization, H.D. and J.Z.; methodology, C.S. and H.D.; software, M.F. and C.S.; formal analysis, C.S. and M.F.; investigation, C.S.; resources, H.D., R.S. and J.Z.; data curation, C.S.; writing—original draft preparation, C.S.; writing—review and editing, C.S., J.Z., H.D., M.F. and R.S.; visualization, C.S.; supervision, R.S., H.D., M.F. and J.Z.; project administration, H.D. and J.Z.; funding acquisition, H.D. and J.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the LOEWE excellence cluster FACE2FACE from the Hessian State Ministry of Higher Education, Research and Arts (Wiesbaden, Germany).

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **Container Type and Substrate A**ff**ect Root Zone Temperature and Growth of 'Green Giant' Arborvitae**

**Anthony L. Witcher 1,\*, Jeremy M. Pickens <sup>2</sup> and Eugene K. Blythe <sup>3</sup>**


Received: 20 December 2019; Accepted: 25 March 2020; Published: 7 April 2020

**Abstract:** Root zone temperature (RZT) in nursery containers commonly exceeds ambient temperature during the growing season, negatively impacting crop growth and quality. Black nursery containers absorb radiant heat resulting in excessive RZT, yet other types of containers and different substrates can moderate RZT. We conducted studies in Tennessee and Alabama to evaluate the effects of container type and substrate on RZT and growth of 'Green Giant' arborvitae (*Thuja standishii* × *plicata* 'Green Giant'). Trade gallon arborvitae were transplanted into black, white, or air pruning containers filled with pine bark (PB) or 4 PB: 1 peatmoss (v:v) (PB:PM). Plants grown in PB:PM were larger and had greater shoot and root biomass than plants grown in PB, likely due to increased volumetric water content. Plant growth response to container type varied by location, but white containers with PB:PM produced larger plants and greater biomass compared with the other container types. Root zone temperature was greatest in black containers and remained above 38 ◦C and 46 ◦C for 15% and 17% longer than white and air pruning containers, respectively. Utilizing light color containers in combination with substrates containing peatmoss can reduce RZT and increase substrate moisture content thus improving crop growth and quality.

**Keywords:** *Thuja standishii* × *plicata*; container production; nursery production; volumetric water content

### **1. Introduction**

Container-grown nursery crops are subjected to extended periods of root zone heat stress throughout the growing season, negatively impacting crop growth and quality. The deleterious effects of high root zone temperature (RZT) have been observed historically in commercial container production. Self and Ward [1] observed less root growth of loquat (*Eriobotrya japonica*) on the south side of black metal cans where substrate temperature was 10 ◦C to 15 ◦C greater than ambient temperature (30 ◦C). In nursery containers, maximum RZT can reach 54 ◦C which can damage crops even when exposed for short periods [2,3]. At RZTs above 46 ◦C, direct injury to plants including immediate root cell damage can occur even with an exposure time under 30 min. Indirect injury to plants can occur at RZTs above 38 ◦C, including interruption of physiological mechanisms which may not present visible signs of damage but lead to reduced growth [4,5].

Many factors contribute to high RZT in container production. Nursery containers have a high surface-to-volume ratio, allowing excessive heat to be absorbed by the container and exchanged between the substrate through conduction [4]. Root zone temperature will vary within the container, with greater temperatures occurring in the region with direct exposure to the sun which will change throughout the growing season [3,4].

Container color, composition, or porosity can also affect RZT and plant growth. Dark-colored containers absorb more solar radiation than light-colored containers leading to excessive heat buildup in the substrate. Containers with a more porous exterior facilitate evaporation from the substrate and reduce heat exchange between the container wall and the substrate [6,7]. Markham et al. [3] evaluated the growth of red maple (*Acer rubrum*) and redbud (*Cercis canadensis*) along with RZT in conventional black containers and white painted containers. They reported RZT was 7.7 ◦C greater in black containers compared with white containers and that red maple had 2.5 times greater root density in white containers. In the same study, they noted white containers had little effect on redbud growth suggesting sensitivity to supraoptimal RZT varies by plant species.

Another alternative to conventional containers is air pruning containers which are available from several manufacturers and are designed with circular openings or long open slots to prevent root circling and improve root branching. Arnold and McDonald [8] evaluated the growth of five tree species in air pruning and conventional black containers. Although results were species specific, plant height, trunk diameter, and root and shoot biomass were similar or improved in the air pruning container compared to the conventional container. In the same study, it was also reported RZT near the exterior edges was 5 ◦C cooler in the air pruning container.

Container substrate porosity and moisture content are also factors in the rate of heat buildup or dissipation. Substrates with low air-filled porosity may improve heat energy diffusion through the substrate due to the physical connectivity of substrate particles. Water is an effective thermal conductor; thus, heat builds up more slowly in substrates with greater water content and minimizing temperature fluctuations in the substrate [4]. Pine bark (PB) is the most widely used substrate for nursery crops in the eastern United States and can be used alone or in combination with other components such as peatmoss (PM) or sand [9,10]. Pine bark typically has a high proportion of drainable air space, whereas PM has greater water holding capacity. Nevertheless, PB physical properties can vary by region and source due to processing methods and aging which could affect crop growth [11]. The combination of PM with PB would increase substrate water holding capacity and possibly reduce RZT.

Plant species vary in response to RZT and duration of exposure. Eastern arborvitae (*Thuja occidentalis*) is sensitive to high RZT and performs best in the United States Department of Agriculture (USDA) plant hardiness zones two to seven where summer temperatures are more moderate [5,12]. In a similar species such as 'Green Giant' arborvitae (*Thuja standishii* × *plicata* 'Green Giant'), root temperature sensitivity has not been reported but it is more heat tolerant and adapted to various soil types and climates including areas with long durations of high summer temperatures [13].

Although the benefits of light-colored containers and air pruning containers have been well documented, commercial adoption of these products remains low. Substrates with increased water retention properties can improve crop growth, yet most nursery producers continue to use PB as the sole substrate component (personal observation). Previous research has focused on differences among container type or among substrates, but the combined effects of container type and substrate have not been reported. Determining which factors (container or substrate) or combination of factors have the greatest impact on crop growth could increase adoption of these practices.

The objective of this research was to evaluate the combined effects of container type and substrate on RZT and growth of 'Green Giant' arborvitae.

### **2. Materials and Methods**

Two separate studies were conducted concurrently at the Tennessee State University Otis L. Floyd Nursery Research Center, McMinnville, TN (USDA Plant Hardiness Zone 7a) and the Auburn University Ornamental Horticulture Research Center, Mobile, AL, USA (USDA Plant Hardiness Zone 8b). The studies were conducted at two locations due to potential differences in environmental conditions which may affect plant growth including temperature and rainfall. The average daily temperature in Tennessee (TN) ranged from 20.8 ◦C (September) to 26.7 ◦C (July) and ranged from

24 ◦C (May) to 27.3 ◦C (July) in Alabama (AL). Rainfall totaled 75.4 cm (TN) and 103.6 cm (AL) over the duration of each study.

Three different container types included black or white solid wall containers (11.3 L; PF1200; Nursery Supplies Inc., Kissimmee, FL, USA) and an air pruning container (10.5 L; #5 Rediroot; Nursery Source Inc., Boring, OR, USA). Two substrates were evaluated in combination with each container type (for a total of six treatments) and included PB and 4 PB: 1 peatmoss (v:v) (PB:PM). Pine bark was obtained from Morton's Horticultural Products (McMinnville, TN, USA) and from Longleaf Mulch (Semmes, AL, USA) for the TN and AL studies, respectively. Both substrates were amended (per 1 m3) with 5.9 kg 18N-2.6P-6.6K controlled-release fertilizer (18-6-8 Nutricote® Total Type 180; Florikan USA, Sarasota, FL, USA), 3.6 kg dolomitic limestone, and 0.9 kg micronutrient granules (Micromax; ICL Specialty Fertilizers, Summerville, SC, USA). Trade gallon (2.4 L) 'Green Giant' arborvitae were transplanted on 19 April 2017 (AL) or 27 April 2017 (TN) into each treatment with 12 replicates (for a total of 72 individual experimental units) and plants were arranged on a gravel container pad in a randomized complete block design. To provide maximum container surface area to sunlight, plants were spaced 0.9 m apart.

Separate irrigation zones were used for each treatment to monitor and adjust irrigation application rates. Plants were irrigated daily using a modified dribble ring (15.2 cm diameter; Dramm Corp., Manitowoc, WI) fitted with a pressure-compensating emitter (8 L h–1; Netafim USA, Fresno, CA). Irrigation application volume for each treatment was adjusted every two weeks to a target leaching fraction of 10% to 20%. Decagon 5TE (AL) and 5TM (TN) sensors and EM50 data loggers (Decagon Devices Inc., Pullman, WA) were used to measure and record RZT and volumetric water content (VWC; m3·m–3) every 15 min throughout both studies. Sensors (1 per container; n <sup>=</sup> 3) were positioned vertically approximately 4.3 cm from the south-facing container sidewall and placed midway between the substrate surface and bottom of the container. Plant height and diameter were measured at 0, 59, 138, and 166 days after planting (DAP) in AL and 0, 69, 95, 120, and 173 DAP in TN. Growth index was calculated [(height + width at widest point + perpendicular width) / 3] and increase in plant height and growth index was also reported (increase = final – initial). The studies were terminated at 166 (AL) and 173 (TN) DAP and plants were destructively harvested. Shoot dry weight (n = 12) and root dry weight (n = 4) were measured after samples were oven-dried at 70 ◦C for approximately 7 days. Substrate pH and electrical conductivity (EC) were recorded using the pour-through method [14] at 52, 97, 146, and 166 DAP (AL) and at 60, 95, and 120 DAP (TN). The percentage of time roots were exposed to temperatures above critical thresholds (38 ◦C and 46 ◦C) mentioned by Ingram et al. (2015) was calculated using the total number of data recordings during daylight hours. Substrate physical properties (n = 3) including air space, container capacity, total porosity, and bulk density were determined using porometer analysis [15].

Multi-factor data were analyzed with linear mixed models using the GLIMMIX procedure of SAS (Version 9.3; SAS Institute, Inc., Cary, NC, USA) by first testing for an interaction between treatment factors (container type and substrate). When there was an interaction between treatment factors, levels of container type were compared within each substrate. Porometer data were analyzed with linear models using the GLIMMIX procedure of SAS. *P*-values for all simultaneous comparisons were adjusted using the Tukey method to maintain an overall significance level of α = 0.05.

### **3. Results**

### *3.1. Plant Growth*

In the TN study, there was an interaction between container type and substrate for final plant height and height increase (Table 1). Both height and height increase were greatest for plants in the white container for PB:PM. White containers with PB:PM also produced plants with the greatest growth index (final and increase) (Table 2). Overall, plants grown in PB:PM produced more shoot and root dry weight (biomass) compared with plants grown in PB. White and black containers had similar shoot

and root dry weight in PB but shoot dry weight was greatest in white containers for PB:PM. In the white container, shoot dry weight and root dry weight were 56% and 68% greater, respectively, for PB:PM compared with PB. In PB, final growth index and increase were similar for plants in black and white containers. Regardless of substrate, however, plants were shortest in the air pruning container.


**Table 1.** Plant height and height increase (n = 12) of 'Green Giant' arborvitae grown in different types of containers and substrates in Tennessee and Alabama.

<sup>z</sup> Container type: Black and White—standard solid wall (11.3 L; PF1200; Nursery Supplies Inc., Kissimmee, FL, USA); Air—air pruning (10.5 L; #5 Rediroot; NurserySource Inc., Boring, OR, USA). <sup>y</sup> Substrate: Pine bark alone (PB) or combined (v:v) with peatmoss (PB:PM; 4 pine bark: 1 peatmoss). <sup>x</sup> DAP = days after planting. <sup>w</sup> Increase = final plant height—initial plant height. <sup>v</sup> When the interaction term in the model is not significant (*P* > 0.10), main effects means for levels within each treatment factor followed by the same lower-case letter are not significantly different using the Tukey method for multiple comparisons (α = 0.05). When the interaction term in the model is significant (*P* ≤ 0.10), simple effects means (treatment means for container grouped within substrate) followed by the same lower-case letter are not significantly different using the Tukey method for multiple comparisons (α = 0.05); otherwise, the treatment means are presented without letter groupings for informational purposes.

In the AL study after approximately two months of growth, plant height was similar between the two substrates and among the three types of containers (Table 1). At the end of the study, plant height was greater in PB:PM compared to PB and greatest in the white container (by over 18%). The plant height increase was also greatest in white containers and PB:PM. Plant growth index followed a similar trend with white containers and PB:PM producing larger plants throughout the study and the greatest growth index increase (Table 2). Although the white container with PB:PM tended to produce taller plants, shoot dry weight was similar among all container types in PB:PM and similar between black and white containers in PB. Container type did not have an effect on root dry weight, but root dry weight was 12% greater in PB:PM compared to PB.


and

*Horticulturae* **2020**

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### *3.2. Substrate Chemical and Physical Properties*

Substrate pH ranged from 5.3 to 6.4 (TN) and from 5.4 to 6.7 (AL) for all treatments in each study (data not shown), remaining within the recommended range of 4.5 to 6.5 [16] except at 52 DAP in AL. Substrate pH was only 0.3 units lower in PB:PM at 95 and 120 DAP in TN and the addition of PM had no effect on substrate pH in the AL study. Substrate EC varied among treatments in the TN study but no clear trend was observed (data not shown). Conversely, substrate and container type had no effect on substrate EC in the AL study except at 146 DAP with substrate EC being greatest in the black container.

Substrate container capacity increased 12% (TN) and 7% (AL) with the addition of PM compared to PB (Table 3). Substrate air space was greater for PB in the TN study, being reduced by 8% in PB:PM. Substrate air space was similar for substrates in the AL study, and air space was overall lower in PB from AL compared with TN.


**Table 3.** Physical properties (n = 3) of substrates for production of 'Green Giant' arborvitae in Tennessee and Alabama.

<sup>z</sup> Substrate: Pine bark alone (PB) or combined (v:v) with peatmoss (PB:PM; 4 pine bark: 1 peatmoss). <sup>y</sup> Data obtained using the North Carolina State University porometer method (Fonteno and Harden, 2010). <sup>x</sup> Means followed by the same letter within a location are not significantly different (α = 0.05).

### *3.3. Root Zone Temperature and Volumetric Water Content*

Substrate did not have an effect on the percentage of time at or above specific threshold temperatures (38 ◦C and 46 ◦C) in either study, but black containers produced the greatest RZT and remained above the critical thresholds far longer than the other container types (Table 4). In TN, RZT in the black container remained above 38◦ C for over 19% of the time which was 15% and 17% longer than white and air pruning containers, respectively. Although RZT in black containers only remained at or above 46 ◦C for 0.1% of the time, RZT in air pruning and white containers remained below 46◦ C throughout the study. In AL, there was an interaction between container type and substrate for a percentage of time at or above 38 ◦C. Root zone temperature in the black container remained above 38 ◦C for over 21% of the time (regardless of substrate), over 13% longer than the other container types. Root zone temperature in air pruning and white containers did not reach the 46 ◦C threshold but RZT in black containers remained at this threshold for nearly 2% of the time.

Volumetric water content was lowest in the air pruning container throughout most of the TN study (Table 5). Volumetric water content was similar for black and white containers in June and July, but black containers had the greatest VWC compared with the other container types in August and September. Substrate also affected VWC, with PB:PM maintaining greater VWC throughout the study. Similar trends were observed for VWC in the AL study, with VWC greater in black containers compared to the air pruning containers and VWC was also greater in PB:PM throughout the study (data not shown).


**Table 4.** Percent of time (n = 3) substrate temperature remained at or above critical thresholds (38 ◦C and 46 ◦C) during daylight hours for 'Green Giant' arborvitae grown in different types of containers and substrates in Tennessee and Alabama.

<sup>z</sup> Container type: Black and White—standard solid wall (11.3 L; PF1200; Nursery Supplies Inc., Kissimmee, FL); Air—air pruning (10.5 L; #5 Rediroot; NurserySource Inc., Boring, OR). <sup>y</sup> Substrate: Pine bark alone (PB) or combined (v:v) with peatmoss (PB:PM; 4 pine bark: 1 peatmoss). <sup>x</sup> When the interaction term in the model is not significant (*P* > 0.10), main effects means for levels within each treatment factor followed by the same lower-case letter are not significantly different using the Tukey method for multiple comparisons (α = 0.05). When the interaction term in the model is significant (*P* ≤ 0.10), simple effects means (treatment means for container grouped within substrate) followed by the same lower-case letter are not significantly different using the Tukey method for multiple comparisons (α = 0.05); otherwise, the treatment means are presented without letter groupings for informational purposes.

**Table 5.** Average daytime volumetric water content (n = 3) over a four-month period for 'Green Giant' arborvitae grown in different types of containers and substrates in Tennessee.


<sup>z</sup> Container type: Black and White—standard solid wall (11.3 L; PF1200; Nursery Supplies Inc., Kissimmee, FL, USA); Air—air pruning (10.5 L; #5 Rediroot; NurserySource Inc., Boring, OR, USA). <sup>y</sup> Substrate: Pine bark alone (PB) or combined (v:v) with peatmoss (PB:PM; 4 pine bark: 1 peatmoss). <sup>x</sup> When the interaction term in the model is not significant (*P* > 0.10), main effects means for levels within each treatment factor followed by the same lower-case letter are not significantly different using the Tukey method for multiple comparisons (α = 0.05). When the interaction term in the model is significant (*P* ≤ 0.10), simple effects means (treatment means for container grouped within substrate) followed by the same lower-case letter are not significantly different using the Tukey method for multiple comparisons (α = 0.05); otherwise, the treatment means are presented without letter groupings for informational purposes.

### **4. Discussion**

Overall, arborvitae grew taller and produced more biomass in white containers with PB:PM. Plants in air pruning containers were smaller than those grown in black or white containers (regardless of substrate), but more growth occurred when PB:PM was used. The air pruning and white containers provided a lower RZT for plants throughout both studies, minimizing heat-related stress which likely led to reduced plant growth in the black container. Maximum RZT (data not shown) was reduced from 5 ◦C to 8 ◦C in the air pruning and white containers. Root zone temperature in the black container reached 46 ◦C (TN) and 51 ◦C (AL), while RZT in the air pruning and white containers reached a maximum of 41 ◦C (TN) and 43 ◦C (AL). These results support previous research documenting increased growth in white containers due to the deleterious effects of supraoptimal RZT. Root zone temperatures can commonly exceed 54 ◦C in container-grown crops, but RZT near 38 ◦C can cause indirect injury to plants leading to reduced shoot and root growth, increased water stress, interruption of physiological mechanisms (photosynthesis and respiration, and increased susceptibility to pathogens [3,4,7]. In our study, fewer roots were observed on the south-facing side of the solid wall containers, regardless of container color, suggesting supraoptimal RZT prevents root growth and development near the container sidewall even in light color containers.

Although air pruning containers had lower RZT, plant growth and biomass were consistently lower than plants in white containers. These results contradict previous work by Arnold and McDonald [8] where tree growth of several tree species was similar or superior in the air pruning container compared to the black container. In the present study, black and white containers had a 7% larger volume than the air pruning container which could have attributed to some of the reduced plant growth observed in the air pruning container. The physical design of the air pruning container likely also contributed to the reduced growth. The air pruning container was designed with open slots, aligned longitudinally around the container side wall, to prevent root circling and improve root branching and growth. The slots increase aeration which prevents buildup of heat, resulting in moderated RZT closer to ambient conditions. In air pruning containers, a larger portion of substrate surface is exposed to the outside environment resulting in more rapid drying out due to increased evaporation through solar radiation and air flow. Arnold and McDonald [8] also noted the air pruning container moderated RZT and that plants in the air pruning container dried out sooner. In the present study, VWC was lowest in the air pruning container which limited the amount of plant-available water and likely led to the reduced plant growth. Irrigation volume was calculated based on leaching fraction and applied once daily, thus the substrate in air pruning containers dried more rapidly after irrigation compared with the solid wall containers and likely never reached container capacity. Overall, black and white containers received more irrigation volume (13% and 38%, respectively; data not shown) compared to the air pruning containers corresponding to the observed differences in arborvitae growth. Therefore, growers using air pruning containers should utilize more frequent (cyclic) irrigation to maximize VWC throughout the day and reduce water-related stress especially in substrates with high air-filled porosity and lower water holding capacity.

Peatmoss increased substrate container capacity by up to 12% compared to PB alone resulting in PB:PM having at least 7% greater VWC throughout both studies. On average, plants grown in PB:PM received 90% more irrigation volume compared PB. The combined benefits of greater water retention and irrigation volume corresponded to superior plant growth in PB:PM. Peatmoss has greater container capacity and easily available water compared to PB, likely due to a higher proportion of macropores and a lower proportion of fine particles in PB [17]. The PB and PM for each study were obtained from different sources which led to slight differences in physical properties for each study. Pine bark physical properties can vary due to a number of factors including source, age, and processing method [11]. Nevertheless, the addition of PM provided PB:PM with more plant-available water resulting in overall improved plant growth at both locations.

Peatmoss typically has a lower inherent pH compared to PB. It has been shown that increasing the percentage of PM in PB does not increase cation exchange capacity (and thus nutrient retention) on a volumetric basis [9,18]. Johnson et al. [18] reported an increase in soluble salt level with an increasing proportion of PM in PB substrates despite no increase in CEC. In our studies, PB:PM was composed of 20% PM but substrate pH was not negatively affected and differences in EC between substrates were not observed. However, EC was generally lower for PB:PM in both studies and a lack of significance might be due to sample variation and small sample size (n = 4).

Root zone temperature was not affected by substrate in the present studies, yet substrate porosity and VWC may contribute to the rate of heat buildup and dissipation in a substrate. Amoroso et al. [19] reported RZT was greater in substrates irrigated to 100% container capacity compared to 30% container capacity. In their study, the substrate was composed of 80% PM which typically has smaller particle size and lower air space compared to PB. Martin and Ingram [20] suggested substrates with lower pore space combined with greater VWC (25% to 40%) could dissipate heat more effectively. As a result, substrate temperature would increase at a slower rate and maintain a lower RZT overall. Although PB:PM had greater VWC, there was very little difference in substrate total porosity compared to PB alone which may have minimized thermal dissipation in this study. Plants were irrigated once daily at 12 pm, thus VWC may have been too low during the hottest portion of the day for heat to effectively dissipate. Applying irrigation multiple times throughout the afternoon would increase VWC over a longer period and possibly improve heat dissipation from the substrate.

All the arborvitae plants grown in these studies were marketable, but plants grown in PB:PM grew significantly larger and were visually superior in quality (Figure 1). Plants in PB:PM benefited from overall greater VWC and which remained higher throughout the day compared with PB. Peatmoss is more expensive than PB and requires additional equipment for mixing into the substrate, but the added benefits (water retention and availability) could result in higher quality crops that reach a finished size more quickly. For example, plants in PB:PM were on average larger (height and growth index) than plants in PB that had been grown for 30 additional days (data not shown).

**Figure 1.** Representative 'Green Giant' arborvitae plants 173 days after planting (in Tennessee) in 100% pine bark (three plants on left) and 4 pine bark: 1 peatmoss (v:v; three plants on right) in standard black, standard white, and air pruning containers (left to right within each substrate).

White containers provided lower RZT that likely reduced plant stress resulting in slightly larger and potentially healthier plants. White plastic containers are commercially available from a number of manufacturers in a variety of sizes (up to 11 or 19 L). Modern white containers are high quality and typically manufactured with co-extruded black (interior) and white (exterior) plastic to prevent light diffusion through the container which was a problem with earlier products. Plants grown in air pruning containers tend to have better branched and more vigorous root systems that can improve transplant establishment and subsequent crop quality, but to prevent drying out they will require more frequent irrigation and possibly higher application rates compared with crops in traditional black containers.

The impact of abiotic factors on crop growth has been well documented and developing methods for reducing root zone stress would improve root development, crop quality, and transplant success [21]. The interaction of factors such as container type, substrate, and moisture content must be considered when evaluating alternative production practices. Growers typically use a single substrate/container type for all the different crop species in production. Light-colored containers can effectively reduce RZT which may be especially important in temperature-sensitive species, but we found that using substrates with higher VWC had a greater effect on overall crop growth especially when used in white containers. Although 'Green Giant' arborvitae is highly adaptable to soil type and is considered a heat-tolerant plant, we demonstrated increased growth by modifying the substrate and container type. Growers should consider conducting small-scale evaluations to determine if a particular substrate/container combination works in their production system. When conducting small trials, growers should place each substrate/container combination in separate irrigation zones and adjust irrigation volume based on plant needs to ensure moisture is not a limiting factor.

**Author Contributions:** Conceptualization, A.L.W. and J.M.P.; methodology, A.L.W. and J.M.P.; formal analysis, A.L.W. and E.K.B.; investigation, A.L.W. and J.M.P.; writing—original draft preparation, A.L.W.; writing—review and editing, A.L.W., J.M.P., and E.K.B.; funding acquisition, A.L.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported the National Institute of Food and Agriculture (NIFA), United States Department of Agriculture (USDA) Evans-Allen grant, under award number TENX-1519-CCOCP.

**Acknowledgments:** The authors wish to thank Terry Kirby for assistance with data collection and project maintenance.

**Conflicts of Interest:** The authors declare no conflicts of interest.

### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

## **E**ff**ects of Non-Leguminous Cover Crops on Yield and Quality of Baby Corn (***Zea mays* **L.) Grown under Subtropical Conditions**

### **Atinderpal Singh 1, Sanjit K. Deb 1,\*, Sukhbir Singh 1, Parmodh Sharma <sup>2</sup> and Jasjit S. Kang <sup>3</sup>**


Received: 23 January 2020; Accepted: 13 March 2020; Published: 3 April 2020

**Abstract:** Effects of non-leguminous cover crops and their times of chopping on the yield and quality of no-till baby corn (*Zea mays* L.) were evaluated during two *kharif* seasons (May-August in 2014 and 2015) under subtropical climatic conditions of Punjab, India. The experiment was laid out in a split-plot design with four replications at Punjab Agricultural University's Research Farm. Three cover crops (pearl millet (*Pennisetum glaucum* L.), fodder maize (*Zea mays* L.), and sorghum (*Sorghum bicolor* L.)) and the control (no cover crop) were in the main plots and chopping time treatments (25, 35, 45 days after planting (DAP)) in the subplots. During both *kharif* seasons, the yield (cob and fodder yield) and dry matter accumulation of baby corn following cover crop treatments, especially pearl millet, were significantly (*p* ≤ 0.05) higher than the control, and improved with increments in chopping time from 25 to 45 DAP. The effect of cover crops on baby corn quality (i.e., protein, starch, total soluble solids, crude fiber, total solid, and sugar content) did not differ among treatments, while increasing increments in chopping time had a significant effect on the protein and sugar content of baby corn. The use of cover crops and increment in chopping time helped in enhancing topsoil quality, especially available nitrogen; yet, the effect of cover crops and their times of chopping on topsoil organic carbon, phosphorus, and potassium did not differ among treatments. During both seasons, there was no significant interaction between cover crop and time of chopping among treatments with respect to baby corn yield and quality, as well as topsoil quality parameters.

**Keywords:** baby corn; non-leguminous cover crops; chopping; baby corn yield; baby corn quality; *kharif* season

### **1. Introduction**

Maize (*Zea mays* L.), also called corn, is the third most important cereal crop in the world after rice and wheat as a source of calories and in terms of the value of production [1–3]. The importance of maize worldwide is driven by its multiple uses as human food, livestock feed, a variety of food and industrial products, and seed [4]. Maize is grown as a food crop (i.e., grain maize) in many tropical areas, particularly in Latin American, African, and Asian countries, including India. In 2014, India produced about 23.7 million tons of maize on 9.3 million ha [5]. The average maize yield in India was 2.56 t·ha−<sup>1</sup> during 2015–2016, less than one-quarter of that obtained in the United States of America (USA), and less than half of that obtained in China and Brazil [6].

As a C4 plant, maize has a higher grain yield potential than other major cereal grains (i.e., wheat and rice) [7]. Maize can be directly consumed as food at different stages of crop development, from baby corn to mature grain. Baby corn is the young, fresh, and finger-like ears of fully-grown standard cultivars, which are harvested immediately after the silks emerge (i.e., within 2 or 3 days of silk emergence) and before pollination and fertilization [8,9]. In general, except for the length of time from the establishment to harvest, baby corn cultivation practices are similar to those of maize cultivation. Baby corn has increasingly gained popularity as a valued vegetable throughout the world. In India, baby corn has also emerged as a potential remunerative crop, especially among progressive farmers.

Maize, a heavy user of nutrients, requires more nitrogen (N) compared to other mineral nutrients. Shivay et al. [10] reported that increasing N application rate significantly increased leaf area index, dry matter accumulation, and net assimilation rate at different growth stages of maize. Cover crops (leguminous or non-leguminous cover crops) or green manures (particularly leguminous green manures) have the potential to fully or partially replace inorganic N fertilizer, particularly for high N-requiring cereal crops such as maize, and thereby promote the use of sustainable production practices. Leguminous cover crops are commonly used to provide N for use by subsequent crops [11,12]. Leguminous crops contribute N through symbiotic dinitrogen (N2) fixation, reduce N fertilizer needs for subsequent crop, and increase soil N retention [13,14]. While leguminous cover crops are used as N sources to supplement or replace inorganic N fertilizer, non-leguminous cover crops have the potential to enhance soil organic matter by increasing biomass production and by scavenging nutrients, especially N leftover from previous crops [15]. Non-leguminous cover crops have been also reported to reduce nitrate leaching losses [16,17]. The use of legume-grass mixtures could combine the benefits of both, including N fixation, biomass production, and N scavenging [18,19].

The selection of cover crops for a given region requires, among others, knowledge of their growth potentials [20,21]. The major climatic variables affecting cover crop selection include temperature and rainfall [22]. Non-leguminous cover crops have become more important in tropical and subtropical areas, such as Punjab in India where crop residues in conventional systems are not enough to compensate for the loss of soil organic matter due to high rates of mineralization [23]. Additionally, the limited availability of farmyard manures could be overcome by using non-leguminous cover crops, especially in subtropical areas of Punjab by sowing them before *Kharif* baby corn (i.e., monsoon crop). In Punjab, these non-leguminous cover crops often include pearl millet (*Pennisetum glaucum* L.), fodder maize, and sorghum (*Sorghum bicolor* L.).

Cover crops could jump-start no-till, resulting in yield increases [3]. Hoorman et al. [3] reported that maize yields dropped slightly for the first five to seven years after switching to no-till because continuous conventional tillage oxidized the soil organic matter and soil productivity declined with time. However, long-term (i.e., seven to nine years), no-till practices improved soil health by getting microbes and soil fauna back into balance, restored nutrients lost by conventional tillage and increased organic matter levels, resulting in higher maize yields than conventionally tilled fields [3]. Hoorman et al. [3] suggested that cover crops could be an important part of a continuous no-till system for maintaining short-term as well as increasing long-term maize yields. The effects of leguminous cover crops on improved maize yield and enhanced soil N under no-till conditions have been repeatedly stressed in the literature [24–29]. Despite non-leguminous cover crops having beneficial effects on crop production, there remains a paucity of information about their effects on no-till maize or baby corn production, especially under subtropical conditions of Punjab, India.

In Punjab, planting *Kharif* non-leguminous cover crops has been often recommended in the second fortnight of April [30]. The benefits of non-leguminous cover crops as fodder crops could be obtained by cutting 50-day old crops before planting subsequent maize or baby corn crop [30]. Non-leguminous cover crops can be chopped before their flowering stages, and subsequent maize or baby corn crop can be planted under no-till conditions. The effects of leguminous cover crops such as sunn hemp (*Crotolaria juncea*), cowpea (*Vigna unguiculata*), and dhaincha (*Sesbania aculeata*) and their times of chopping on maize growth and yield have been evaluated in very few studies. Salaria [31] reported that the combination of leguminous cover crops (sunn hemp, cowpea, and dhaincha) and their times of chopping increased average maize grain yield by 15.3% over the control under subtropical climatic conditions. A significant interaction between leguminous cover crops and increment in chopping time indicated that chopping of cover crops at 45 days after planting (DAP) increased average maize grain yield by 12.9% and 24.6% over chopping at 35 DAP and 25 DAP, respectively [31]. Moreover, the manner in which leguminous cover crops have been used, various N levels as well as time of chopping, have improved available soil nitrogen (N), phosphorus (P), potassium (K) and organic carbon at harvest during a *kharif* no-till maize growing season [31]. In contrast, very little is known about the effects of non-leguminous cover crops and their times of chopping on the yield and quality of baby corn grown under tropical or subtropical climatic conditions. Therefore, the objective of this study was to evaluate the effects of non-leguminous cover crops (pearl millet, fodder maize, and sorghum) and increments in chopping time (25 DAP, 35 DAP, and 45 DAP) on the yield and quality of no-till baby corn during *kharif* seasons under the subtropical climatic conditions of Punjab, India.

### **2. Materials and Methods**

### *2.1. Experimental Site*

The field experiment was conducted at the Research Farm of the Department of Agronomy, Punjab Agricultural University, Ludhiana, India (latitude 30◦53 58.27" N, longitude 75◦47 50.26" E, at an altitude of 247 m above mean sea level) during two summer or *kharif* seasons (i.e., May–August in 2014 and 2015). The soil of the experimental field was sandy loam (coarse-loamy, calcareous, mixed, hyperthermic Typic Ustochrept) containing 3.3·g·kg−<sup>1</sup> organic carbon [32]. On average, within the 0–180 cm soil depths, soil pH, electrical conductivity (EC), soil water content at 30 kPa (i.e., soil water content at field capacity), and soil water content at 1500 kPa (i.e., soil water content at wilting point) were 8.0, 0.20·dS·cm<sup>−</sup>1, 13.23%, and 7.61%, respectively [32]. As reported by Kukal and Sidhu [32], the soil in the experimental field was generally low in content of KMnO4-extractable N (152·kg·ha<sup>−</sup>1), and medium in content of 0.5 N NaHCO3-extractable P (13.7·kg·ha<sup>−</sup>1) and available K (145·kg·ha<sup>−</sup>1).

### *2.2. Weather Conditions*

The experimental site was located in a region characterized by a subtropical, semi-arid climate with three distinct seasons: hot and dry summer (April–June) when *kharif* crops are grown, hot and humid monsoon (July–September), and cold winter (November–January) when *rabi* crops are grown. Weather data obtained from the meteorological observatory at Punjab Agricultural University, which was approximately 500 m from the experimental site, included maximum and minimum air temperatures, relative humidity, rainfall, and soil evaporation during two *kharif* seasons (2014–2015) (Figure 1). The weekly average maximum air temperature varied between 38.8 ◦C and 46.4 ◦C in 2014 (6 May–26 August) and between 38.9 ◦C and 48.2 ◦C in 2015 (6 May–26 August). The weekly average minimum air temperature ranged between 20.7 ◦C and 29.3 ◦C and 24.1 ◦C and 27.9 ◦C during 2014 and 2015, respectively. The weekly average relative humidity ranged from 43.9% to 84.4% in 2014 and from 29.6% to 81.1% in 2015. The experimental site received considerably less rainfall (161 mm) during the *kharif* season in 2014 compared to the *kharif* season in 2015 (197 mm). The weekly average soil evaporation rates varied from 24 mm to 80 mm and from 23.3 mm to 84 mm during 2014 and 2015, respectively.

**Figure 1.** Weekly average weather data observed at the experimental site during both *kharif* seasons (6 May–26 August in 2014 and 2015).

### *2.3. Experimental Design and Agronomic Practices*

The experimental field was divided into forty plots each 11 m × 3 m in size. All plots were subjected to no-till practices during both *kharif* seasons (2014–2015). The experiment was laid out in a split-plot randomized complete block design with four replications, which were comprised of three cover crops (i.e., non-leguminous pearl millet, fodder maize, and sorghum) and the control (no cover crop) in the main plots and cover crop chopping time treatments (i.e., 25 DAP, 35 DAP, and 45 DAP) in the sub-plots. All cover crops (pearl millet, fodder maize, and sorghum) were manually sown using the dibbling method on 5 May, 15 May, and 25 May during the *kharif* season in 2014, while all cover crops were sown on 9 May, 19 May, and 29 May during the *kharif* season in 2015. No fertilizers were applied to cover crops. The cover crops were chopped on 19 June in 2014 and on 22 June in 2015, corresponding to 25 DAP, 35 DAP, and 45 DAP at the time of chopping. The 25-, 35-, and 45-day old cover crops were chopped in situ using a chopper-cum-spreader and left uniformly on the soil surface. The chopper-cum-spreader used in this study was a tractor mounted flail type chopper, which was designed and developed by the Central Institute of Agricultural Engineering (CIAE), Bhopal, India [33]. The chopper cut cover crops above the ground level and chopped them into small pieces (i.e., 5–10 cm in length). The blades of the chopper were covered to prevent the spread of chopped cover crops from one plot to another. Baby corn was then planted on 19 June in 2014 and 22 June in 2015.

Baby corn (variety G-5414, Syngenta, India) was sown at a rate of 40·kg·ha−<sup>1</sup> by the dibbling method at a row × plant spacing of 30 cm × 20 cm recommended by Dhaliwal and Kular for baby corn [30]. The recommended doses of N, P and K were used at rate of 120·kg·N·ha−<sup>1</sup> as urea, 50·kg·P·ha−<sup>1</sup> as diammonium phosphate and 30·kg·K2O ha<sup>−</sup><sup>1</sup> as muriate of potash, respectively [30,34]. Half of the N and full doses of P and K were applied to baby corn as basal doses. The remaining dose of N was top-dressed at the knee-high stage of the baby corn. Prior to planting cover crops, pre-sowing flood irrigation was applied to all plots during both *kharif* seasons (2014–2015). Cover crops were sown when the soil water content was at field capacity in experimental plots. No post-sowing irrigation was applied to cover crops. As shown in Figure 1, a significant amount of rainfall during both seasons resulted in sufficient soil water content for cover crops. After chopping cover crops, all treatment plots

had sufficient soil water content for the emergence of baby corn. A first irrigation was applied to baby corn at 8 DAP during both seasons. Additional irrigations were applied at two critical growth stages of water stress [35], i.e., at the knee-high stage and at the tassel emergence and silking stage, respectively.

### *2.4. Harvest of Baby Corn and Yield*

To determine the dry matter accumulation, a plant sample of baby corn was collected at harvest from each treatment plot, sun-dried, and then oven-dried to a constant weight at 60 ◦C for 48–72 h. Generally, the dry matter accumulation provides an indicator of the growth and metabolic efficiency of the plant (i.e., an indicator of the crop yield) [31]. During both *kharif* seasons, baby corn cobs for each treatment plot was hand-harvested at two picking dates. The cobs were ready for first picking at 55 DAP when the silk length was about 2–4 cm. The second harvest was performed 5 days after the first harvest date. Baby corn can be marketed as green ears (with husk) and dehusked ears. All collected cobs, immediately after harvest, were dehusked by hand to remove their outer sheaths and weighed, and baby corn cob yield for each plot was recorded. After the completion of cob-picking, the crop was harvested, and green fodder (i.e., green stems and leaves of baby corn) yield for each plot was determined.

### *2.5. Quality Parameters of Baby Corn*

The protein content (%) of baby corn cobs from individual treatments was estimated by multiplying its N content by the factor 6.25 [36]. The N content (%) was determined using the Kjeldahl distillation method [37]. The total soluble solids (TSS) (%) was determined with a hand-held digital refractometer (Erma, Tokyo, Japan) following the procedure described by Nelson and Sommers [38]. The total sugar content (%) of baby corn was estimated using the modified Nelson-Somogyi method [39,40]. The measurement of total solids content or dry matter content (% in relation to sample weight) of a baby corn cob was made by placing the sample (15 g) in a hot air oven at a temperature of 70 ◦C for 16–18 h until a constant mass was obtained. The dried sample was cooled down to room temperature in a desiccator, and the total solids content was determined as the remaining weight of the sample after drying.

The starch content (%) of a baby corn cob sample (i.e., about 5 g sample) was determined using the colorimetric method [41]. After the sugars present in the sample were extracted until a quantitative test with anthrone gave no green color, the sample was cooled and mixed with perchloric acid, solubilized, filtered, and diluted. The diluted solution was mixed with anthrone reagent and boiled until the reaction was completed. The solution was then allowed to cool, and its absorbance was measured at 630 nm in a spectrophotometer. The concentration of starch was calculated from a standard curve. A standard curve was prepared using 0.5, 1.0, and 1.5 mL of starch standard solution in a 100 mL volumetric flask. A 5 mL solution from each sample was used to develop the standard curve, i.e., a plot of absorbance versus concentration.

The crude fiber content (%) of baby corn cob was determined using the method described by Ranganna [41] and Horwitz [42]. About 2 g of baby corn cob sample was placed into the crucible, dissolved in 200 mL of sulfuric acid (H2SO4) solution, and boiled for 30 min in a digestion flask with the condenser. The hydrolyzed mixture was filtered, and the residue was rinsed with hot water to remove acid from the filtrate in the crucible. The residue from acid digestion was washed again in the flask with 200 mL of sodium hydroxide (NaOH) solution and boiled for 30 min. The hydrolyzed sample was again filtered, and the residue was rinsed with hot water to ensure that the crucible was free of alkalinity. The residue in the crucible was oven-dried at 105 ◦C until a constant mass was attained. The crucible containing dry residue was weighed and placed in a muffle furnace at 550 ◦C for 5 h. The crucible with ash was cooled to room temperature in a desiccator and weighed. The crude fiber content of baby corn cob sample was then calculated as:

### Crude fiber content (%) = Weight of crucible with dry residue − Weight of crucible with ash Weight of sample taken <sup>×</sup> <sup>100</sup>

### *2.6. Soil Analysis*

Prior to planting cover crops in 2014, soil samples within the topsoil (0–20 cm soil depth) were collected from the experimental field to determine soil texture and soil chemical properties (Table 1). To determine soil chemical properties following cover crop treatments, soil samples (0–20 cm) were collected from all cover crop and control treatment plots immediately after harvesting baby corn in 2014 and 2015. The available soil nitrogen (N) was determined using the modified alkaline permanganate extraction method proposed by Subbaiah and Asija [43], the available soil phosphorus (P) using the sodium bicarbonate extraction method described by Olsen [44], and the available soil potassium (i.e., the ammonium acetate extractable K) using the method described by Merwin and Peech [45]. The chromic acid titration method [46] was used to determine the soil organic carbon.

**Table 1.** Selected soil chemical properties of the experimental field determined prior to planting non-leguminous cover crops during *kharif* season (May–August) in 2014.


<sup>β</sup> According to USDA (United States Department of Agriculture) classification.

### *2.7. Statistical Analysis*

The analysis of variance (ANOVA) was performed using the General Linear Model (GLM) procedure of SAS software version 9.4 (SAS Institute, Cary, NC, USA). The appropriate error term was used to evaluate each factor and interaction. The main plot factors (cover crops) and sub-plot factors (times of chopping) were considered as fixed variables, and the data in 2014 and 2015 was considered as random variables. Differences among treatment means were compared using Fisher's protected least significance difference (LSD) test. Statistical significance was evaluated at *p* ≤ 0.05.

### **3. Results and Discussion**

### *3.1. Cover Crop E*ff*ects on Dry Matter Accumulation and Cob Yield of Baby Corn*

The dry matter content of baby corn following non-leguminous cover crop treatments (pearl millet, fodder maize, and sorghum) was determined at harvest. The combination of cover crops and different times of chopping (25 DAP, 35 DAP, and 45 DAP) resulted in a higher amount of dry matter accumulation of baby corn compared to the control (no cover crop treatment) in 2014 and 2015 (Table 2). Similar enhanced dry matter content following cover crops and their times of chopping under no-till maize production was also reported by Salaria [31]. However, Salaria [31] evaluated leguminous cover crops (e.g., sunnhemp, cowpea, and dhaincha) and different N levels for their effects on dry matter yield of maize grown under subtropical climatic conditions.


**Table 2.** Effects of cover crops and their times of chopping (at different days after planting (DAP)) on the dry matter of baby corn, the cob yield of baby corn, and

#### *Horticulturae* **2020** , *6*, 21

the

On average, the dry matter of baby corn in 2014 and 2015 (4.34 t·ha−<sup>1</sup> and 4.40 t·ha<sup>−</sup>1, respectively) was significantly (*p* ≤ 0.05) higher following pearl millet cover crop treatment than following sorghum cover crop and control treatments. However, the dry matter of baby corn following fodder maize cover crop was similar to that observed following pearl millet cover crop in both years. In a review study, Dar et al. [47] reported that the dry matter yield of baby corn grown in India varied from 6.0 to 8.0 t·ha−<sup>1</sup> during *rabi* and late-*rabi* seasons and from 8.0 to 9.0 t·ha−<sup>1</sup> during *kharif* and summer seasons. The higher dry matter yield of baby corn reported by different studies was mainly influenced by various agronomic practices including closer crop geometries (i.e., closer row spacing) and higher rates of N application [47]. Eltelib et al. [48] observed that the dry matter yield of maize ranged from 3.7 to 12.2 t·ha−<sup>1</sup> based on the amount of fertilizer application especially different levels of N application.

The maximum cob yield of baby corn was observed following pearl millet cover crop treatment in both years (Table 2). The cob yield of baby corn (1.45 t·ha−<sup>1</sup> and 1.50 t·ha−<sup>1</sup> in 2014 and 2015, respectively) was significantly (*p* ≤ 0.05) higher following pearl millet than no cover crop (i.e., control) and sorghum cover crop. The cob yield of baby corn following fodder maize cover crop was statistically similar to the cob yield observed following pearl millet cover crop treatment in both years. On average, pearl millet cover crop treatment resulted in a relatively higher amount of green fodder yield of 20.52 t·ha−<sup>1</sup> and 20.56 t·ha−<sup>1</sup> in 2014 and 2015, respectively (Table 2). The green fodder yield of baby corn following sorghum was slightly lower than that of the control treatment in both years. However, the fodder yield of baby corn in both years was not significantly different between all cover crops and the control. Although information pertinent to the effect of non-leguminous and leguminous cover crops on cob and fodder yields of baby corn grown under subtropical climatic conditions is very limited, comparable results have been reported by several studies. For instance, as reported by Dar et al. [47], the yield of baby corn or sweet corn grown in India generally varied from 1.2 to 12.7 t·ha−1, while the fodder yield of baby corn (sum of green fodder yield and dry fodder yield) ranged from 4.12 to 27.0 t·ha<sup>−</sup>1. Baby corn intercropped with fodder legumes, such as maize, cowpea, clusterbean (*Cyamopsis tetragonoloba* L.), and pillipesara (*Phaseolus trilobus* L.), has been reported to produce 28.6 to 50.5 t·ha−<sup>1</sup> green fodder and 5.1 to 8.8 t·ha−<sup>1</sup> dry fodder yield of baby corn during *rabi* season [49]. The higher baby corn and fodder yield data reported in previous studies [47,49] were primarily attributed to high rates of N application, plant densities, and planting patterns.

In situ chopping of cover crops at 25 DAP, 35 DAP, and 45 DAP was likely to provide a large quantity of cover crop biomass, which could improve soil physical properties such as soil water retention and soil temperature. Cover crop residues could also provide additional nutrients for better growth responses of the subsequent crop [50]. Accordingly, compared to the control, the relatively higher dry matter accumulation of baby corn observed following all cover crop treatments was most likely due to the improved soil conditions. During both years, pearl millet cover crop was growing faster than sorghum and fodder maize. The relatively fast-growing deep root system of pearl millet [51,52] might scavenge more nutrients, resulting in more biomass production and dry matter accumulation of baby corn following this non-leguminous cover crop treatment (Table 2). The use of pearl millet as a cover crop to enhance biomass production and nutrients for subsequent crops has been reported in different studies (e.g., [53–56]). Schonbeck and Morse [53] reported that pearl millet cover crop could produce biomass from 7.0 to 12 t·ha<sup>−</sup>1. Pearl millet cover crop has been also reported to improve N use efficiency by a succeeding maize crop [54], provide 60–80% of the potassium nutrient needed for the subsequent crop [55], and improve soil organic matter and inhibit soil-borne diseases [56].

Overall, chopping of cover crops at 45 DAP showed a significant (*p* ≤ 0.05) effect on the dry matter accumulation of baby corn cob and green fodder yield of baby corn in both years (Table 2). The amount of dry matter accumulated in baby corn after chopping cover crops at 45 DAP (i.e., an average yield of 4.40 t·ha−<sup>1</sup> and 4.43 t·ha−<sup>1</sup> in 2014 and 2015, respectively) was significantly higher than the dry matter accumulation after chopping at 25 DAP and 35 DAP. Similarly, the average cob yield of baby corn observed after chopping cover crops at 45 DAP (i.e., 1.40 t·ha−<sup>1</sup> and 1.41 t·ha−<sup>1</sup> in 2014 and 2015, respectively) was significantly higher than those observed after chopping at 25 DAP and 35 DAP. The

average green fodder yield of baby corn observed after chopping at 45 DAP (i.e., 20.31 t·ha−<sup>1</sup> and t·ha−<sup>1</sup> in 2014 and 2015, respectively) was slightly higher than those observed after chopping at 25 DAP and 35 DAP. However, the fodder yield of baby corn in both years was not significantly different among time of chopping treatments. Overall, the results suggested that chopping all non-leguminous cover crops, particularly pearl millet, at 45 DAP could enhance dry mass accumulation and cob and fodder yield of succeeding *kharif* baby corn under no-till practices. Another aspect to be noted in Table 2 is that during both *kharif* seasons, the interaction of cover crops and their times of chopping on the dry matter accumulation and cob and fodder yield were not significant among treatments.

### *3.2. Cover Crop E*ff*ects on Baby Corn Quality Parameters*

### 3.2.1. Protein Content

The protein content of baby corn cob following non-leguminous cover crop treatments in 2014 and 2015 is presented in Table 3, suggesting that the average protein content of baby corn following cover crop treatments was slightly higher than that of no cover crop (i.e., control) treatment. On average, the higher amount of protein content of baby corn cob (12.15% and 12.26% in 2014 and 2015, respectively) was observed following pearl millet cover crop treatment. The reason might be attributed to the maximum amount of cover crop dry matter produced by pearl millet treatment that resulted in a higher amount of N available for use by subsequent baby corn, contributing to higher N uptake by baby corn. However, in both years, there was no statistically significant (*p* ≤ 0.05) difference in the protein content of baby corn cob between all cover crops and the control. To the best of our knowledge, very little is known about the effect of non-leguminous cover crops on the protein content of baby corn; however, similar results of the protein content in baby corn intercropped with leguminous crops were reported by several studies. For instance, Kumar and Venkateswarlu [49] reported that the protein content of baby corn intercropped with fodder legumes (e.g., maize, cowpea, clusterbean, and pillipesara) varied from 7.01% to 8.73% during *rabi* season. The protein content of baby corn was significantly influenced by plant densities and fertilization practices, especially high rates of inorganic N levels in different studies (e.g., [57,58]). Hooda and Kawatra [59] reported that the protein content of baby corn (17.9%) was similar or slightly higher than vegetables like cabbage, bitter gourd, eggplant, French beans, and spinach. Comparable results (i.e., protein content varied between 10.3% and 12.96%) were also reported for sweet corn and maize [60,61]. The protein content of forage maize has been reported to vary from 3.67% to 9.06% under different levels of N application [48].

The average protein content of baby corn cob after chopping cover crops at 45 DAP was significantly (*p* ≤ 0.05) higher than the protein content obtained after chopping at 25 DAP (Table 3). The protein content of baby corn cob was not significantly different after chopping cover crops at 35 DAP and 45 DAP. On average, the maximum protein content (12.60% and 12.68% in 2014 and 2015, respectively) was observed after chopping cover crops at 45 DAP. As mentioned earlier, the higher protein content of baby corn could be explained by the higher dry matter of cover crops and resulting higher amount of N associated with increment in chopping time from 25 DAP to 45 DAP. There was no interaction of cover crops and their times of chopping on the protein content of baby corn cob among treatments (Table 3).


**Table 3.** Effects of cover crops and their times of chopping (at different days after planting (DAP)) on the protein content, the starch content, and the crude fiber

176

#### *Horticulturae* **2020** , *6*, 21

### 3.2.2. Starch Content

The starch content of baby corn cob, as shown in Table 3, was not significantly (*p* ≤ 0.05) different between all cover crops and the control in both years. On average, the maximum starch content (2.41% in both years) was observed following pearl millet cover crop treatment. There is a paucity of quantitative information on the starch content of baby corn following non-leguminous cover crop treatments. Nevertheless, evaluation of nutritional compositions of baby corn or sweet corn in several studies reported different starch content values for baby corn. For instance, Hooda and Kawatra [59] reported a starch content value of 15.6% for baby corn. Ugur and Maden [62] suggested that sweet corn would contain 10% to 11% starch. Generally, the average starch content of baby corn decreased with increment in chopping time from 25 DAP to 45 DAP. On average, the maximum starch content of baby corn (2.41% and 2.42% in 2014 and 2015, respectively) was observed after chopping cover crops at 25 DAP. As shown in Table 3, there was no interaction of cover crops and their times of chopping on the starch content of baby corn cob in both years.

### 3.2.3. Crude Fiber Content

The average crude fiber content of baby corn cob varied between 2.40% and 2.41% among cover crop and control treatments in both years (Table 3). The average crude fiber content was not significantly (*p* ≤ 0.05) different between all cover crops and the control. A slightly lower amount of crude fiber was observed following pearl millet cover crop and no cover crop (control) treatments compared to fodder maize and sorghum cover crop treatments. The lower crude fiber content of baby corn in this study might be explained by the higher protein content of baby corn (Table 3), which generally decreased the deposition of lignin and cellulose [62]. Nutritional evaluation of baby corn for crude fiber content has yielded contrasting results in different studies. For instance, similar results of lower crude fiber contents of baby corn (4.53–5.89%) were reported by several studies (e.g., [57,59,63]). Shobha et al. [64] evaluated the quality of eleven maize genotypes at baby corn and grain maturity stages and observed lower crude fiber contents ranging from 1.96% to 2.40% among maize genotypes. In contrast, Kumar and Venkateswarlu [49] reported higher crude fiber content of baby corn (i.e., 23.76–25.71%) intercropped with fodder legumes (e.g., maize, cowpea, clusterbean, and pillipesara). Eltelib et al. [48] also reported that the crude fiber content of maize varied between 21.13% and 22.1%. The higher crude fiber contents of baby corn or maize in their studies were significantly influenced by high rates of N application.

The crude fiber content of baby corn cob was not significantly (*p* ≤ 0.05) different after chopping cover crops at 25 DAP, 35 DAP, and 45 DAP in both years (Table 3). On average, the minimum amount of crude fiber content in baby corn cob (i.e., 2.10% in both years) was observed after chopping cover crops at 45 DAP. There was no statistically significant interaction between cover crops and their times of chopping among treatments with respect to the crude fiber content of baby corn cob.

### 3.2.4. Total Soluble Solids and Total Solid Content

There was no statistically significant (*p* ≤ 0.05) difference in the total soluble solids (TSS) content of baby corn cob between all cover crops and the control in both years (Table 4). On average, the maximum amount of TSS (8.88 ◦Brix and 8.89 ◦Brix in 2014 and 2015, respectively) was observed following pearl millet cover crop treatment. Information about the effect of non-leguminous cover crops on the TSS content of baby corn is still limited; however, similar TSS values were reported by several studies that evaluated nutritional composition of baby corn. For instance, Joshi and Chilwal [58] reported that the TSS of baby corn varied from 8.1 to 9.5 ◦Brix. However, Khan et al. [65] found relatively higher TSS values in sweet corn cob ranging from 14.31 to 16.56 ◦Brix, which were attributed to agronomic practices associated with transplanting dates and higher N levels. Ugur and Maden [62] reported that average TSS values in sweet corn varied from 8.52 to 20.64 ◦Brix with the progression of the cultivation period among different sweet corn varieties. In contrast, Shobha et al. [64] observed relatively lower TSS content values of maize at the baby corn stage, ranging from 5.06 to 5.86 ◦Brix among different maize genotypes.

**Table 4.** Effects of cover crops and their times of chopping (at different days after planting (DAP)) on the total soluble solids (TSS), the total solid content, and the sugar content of baby corn cob during both *kharif* seasons (May–August in 2014 and 2015).


<sup>z</sup> Treatment means in columns for cover crops or rows for DAP across cover crops followed by the same letter are not significantly different. <sup>y</sup> NS: non-significant interaction at *p* ≤ 0.05.

The TSS content of baby corn cob was not significantly (*p* ≤ 0.05) different among the time of chopping treatments, i.e., after chopping cover crops at 25 DAP, 35 DAP, and 45 DAP in both years. The average amount of TSS was increased with increment in chopping time from 25 DAP to 45 DAP. For example, in 2014, the highest amount of TSS (8.90 Brix) was observed after chopping cover crops at 45 DAP, followed by chopping at 35 DAP (8.77 Brix), and the TSS was the lowest after chopping cover crops at 25 DAP (Table 4). There was no statistically significant interaction between cover crops and their times of chopping among treatments with respect to the TSS of baby corn cob.

As shown in Table 4, there was no statistically significant (*p* ≤ 0.05) difference in the total solid content (i.e., dry matter content) of baby corn cob between all cover crops and the control in both years. To the best of our knowledge, there is almost no information on total solids content or dry matter content of baby corn cob following leguminous or non-leguminous cover crops. On average, the maximum total solids content of baby corn cob (15.16% and 14.97% in 2014 and 2015, respectively) was observed following pearl millet treatment, followed by no cover crop (control) treatment (15.04% and 14.95% in 2014 and 2015, respectively). The total solids content of baby corn cob was not significantly different among the time of chopping treatments, i.e., after chopping cover crops at 25 DAP, 35 DAP, and 45 DAP. The total solids content of baby corn observed after chopping cover crops at each time was statistically similar, with the highest amount after chopping cover crops at 45 DAP in both years. There was no interaction of cover crops and their times of chopping on the total solids content of baby corn among treatments (Table 4).

### 3.2.5. Sugar Content

Similar to the starch content of baby corn, there was no statistically significant (*p* ≤ 0.05) difference in the sugar content of baby corn cob between all cover crops and the control in both years (Table 4). On average, the maximum sugar content of baby corn cob (7.1% and 7.3% in 2014 and 2015, respectively) was observed following pearl millet treatment. Like other baby corn quality parameters discussed earlier, evaluation of nutritional composition of baby corn or sweet corn in several studies reported

different total sugar content values for baby corn. Shobha et al. [64] evaluated the total sugar content among different maize genotypes at the baby corn stage and reported that the total sugar content ranged from 0.40% to 0.89%. The total sugar content of baby corn has been also reported to vary from 0.002% to 2.3% (e.g., [57,61]). Prajwal Kumar et al. [63] reported relatively lower total sugar content of baby corn, ranging from 0.021% to 0.025%. In contrast, Rosli and Anis [66] reported that baby corn contained a significantly higher total sugar content of 10.7–21.48%.

In both years, the average sugar content of baby corn cob increased with increment in chopping time from 25 DAP to 45 DAP (Table 4). Notably, on average, the sugar content of baby corn after chopping cover crops at 45 DAP was significantly (*p* ≤ 0.05) higher than the sugar content observed after chopping cover crops at 25 DAP and 35 DAP. There was no interaction of cover crop treatments and their times of chopping on the sugar content of baby corn among treatments (Table 4).

### *3.3. Cover Crop E*ff*ects on Soil Quality Parameters*

### 3.3.1. Soil Organic Carbon

The amount of soil organic carbon content in different treatment plots in the topsoil (0–20 cm), presented in Table 5, was determined after the harvest of baby corn in both years. All cover crop treatments resulted in slightly higher average soil organic carbon content (i.e., ranging from 0.32% to 0.35% during 2014–2015) compared to the control (i.e., ranging from 0.31% to 0.32% during 2014–2015) (Table 5). Sharma et al. [67] suggested that although cover crops were highly decomposable, increased soil organic matter following cover crops was only confined to the topsoil (0–20 cm). However, in this study, there was no statistically significant (*p* ≤ 0.05) difference in soil organic carbon content between all cover crops and the control in both years. Among only cover crop treatments, the soil organic carbon content was slightly higher following pearl millet and sorghum treatments than that observed following fodder maize treatment. The enhanced organic carbon content in the topsoil (0–20 cm) following non-leguminous cover crops (i.e., pearl millet, fodder maize, and sorghum) was most likely due to increased biomass or dry matter accumulation produced by these cover crop treatments under no-till practices [15,68,69]. It is worth noting that the soil organic carbon content is a good indicator of soil quality [38,70].


**Table 5.** Effects of cover crops and their times of chopping (at different days after planting (DAP)) on the organic carbon content in soil at harvest during both *kharif* seasons (May–August in 2014 and 2015).

<sup>z</sup> Treatment means in columns for cover crops or rows for DAP across cover crops followed by the same letter are not significantly different. <sup>y</sup> NS: non-significant interaction at *p* ≤ 0.05.

Generally, improved soil organic carbon following various cover crop treatments have been reported in numerous studies (e.g., [13,50,67,71,72]). Sainju et al. [68] reported that a non-leguminous cover crop (rye) was better than legumes (hairy vetch and crimson clover) in increasing soil organic carbon. Several studies observed that the use of both leguminous and non-leguminous cover crops and conservation tillage practices increased soil organic carbon content under maize production systems (e.g., [69,73]). On average, the soil organic carbon after chopping cover crops at 45 DAP was significantly (*p* ≤ 0.05) higher than the soil organic carbon observed after chopping cover crops at 25 DAP and 35 DAP in both years (Table 5). In both years, there was no statistically significant interaction between cover crops and their times of chopping among treatments with respect to the soil organic carbon.

### 3.3.2. Available Soil Nitrogen

The amount of available soil nitrogen (N) in different treatment plots in the topsoil (0–20 cm), which was determined after the harvest of baby corn in both years, is presented in Table 5. The use of pearl millet, fodder maize, and sorghum cover crops improved available topsoil N content at harvest in 2014 and 2015 (Table 6) compared to N values observed at the beginning of this study (Table 1).

On average, all cover crop treatments generally resulted in significantly (*p* ≤ 0.05) higher available soil N as compared to the control (Table 6). Sharma et al. [67] also reported that most of the changes in soil chemical properties (e.g., soil N) following cover crops appeared to be confined in the topsoil (0–20 cm). Among cover crop treatments, the amount of available soil N following pearl millet (196.7 kg·ha−<sup>1</sup> and 196.4 t·ha−<sup>1</sup> in 2014 and 2015, respectively) was significantly higher than the available soil N observed following fodder maize and sorghum cover crops.

The enhanced soil N content following various cover crops have been observed in numerous studies (e.g., [67,68,72]). Substantial changes in soil total N content were primarily due to long-term use of cover crops, which increased total soil N through additions of fixed N or prevention of N losses (e.g., [67,74]). The evaluation of the effects of leguminous and non-leguminous cover crops on soil N has yielded contrasting results in different studies for different crops. For instance, Kuo et al. [20] observed that leguminous cover crops, particularly hairy vetch, were more effective than non-leguminous cover crops (i.e., rye and annual ryegrass) in increasing soil inorganic N levels. In contrast, Sainju et al. [68] suggested that a non-leguminous cover crop (rye) was much more effective than legumes (hairy vetch and crimson clover) in increasing N availability in the soil.

Compared to legumes, the use of non-leguminous cover crops has been reported to reduce the loss of nitrate through leaching [16,17,75–77]. McCracken et al. [16] observed that a non-leguminous cover crop (rye) was much more effective than a leguminous cover crop (hairy vetch) in reducing nitrate leaching. A direct evaluation of the efficacy of non-leguminous cover crops in scavenging N was not examined in this study; however, the non-leguminous cover crop has been recognized for its potential as a scavenger of soil N [15,78]. Moreover, all non-leguminous cover crops, particularly pearl millet, were more likely to reduce nitrate leaching. Overall, as shown in Table 6, the contribution from non-leguminous cover crops to N availability in the topsoil (0–20 cm) suggested that inorganic fertilizer nutrients could be reduced in *kharif* no-till baby corn production.

In both years, the average amount of available soil N was increased with an increase in the time of chopping of cover crops from 25 DAP to 45 DAP (Table 6). On average, the available soil N after chopping cover crops at 45 DAP was significantly (*p* ≤ 0.05) higher than the soil N observed after chopping cover crops at 25 DAP. However, the available soil N was not significantly different among increment in chopping time treatments 35 DAP and 45 DAP in both the years. There was no interaction of cover crops and their times of chopping on the available soil N among treatments.


#### *Horticulturae* **2020** , *6*, 21

### 3.3.3. Available Soil Phosphorus

The amount of available soil phosphorus (P) at different treatment plots in the topsoil (0–20 cm), which was determined after the harvest of baby corn in both years, is presented in Table 6. There was no statistically significant (*p* ≤ 0.05) difference in the average available soil P between all cover crops and the control in 2014 and 2015. The average available soil P among all cover crop and control treatments ranged from 21.2 to 23.2 kg·ha−<sup>1</sup> during 2014–2015. The use of cover crop treatments did not markedly increase available topsoil P content at harvest (Table 6) compared to *p* values observed at the beginning of this study (Table 1). Several studies showed that soil P content could be conserved or maintained and/or enhanced (primarily in the topsoil) by various cover crop species [67,79]. Cover crops could also accumulate P near the soil surface due to the deposition of crop residue [67]. However, cover crops have been shown to have relatively little effect on soil P availability, even though cover crops increased crop dry matter accumulation and recycled a large amount of P to the soil surface [80]. Cover crops could improve P uptake of succeeding crops by converting unavailable native P and residual fertilizer P to chemical forms that are more available to succeeding crops, resulting in lower soil P concentrations [67].

In both years, the average amount of available soil P was increased with an increase in the time of chopping of cover crops from 25 DAP to 45 DAP (Table 6). On average, the available soil P after chopping cover crops at 45 DAP (23.9 kg·ha−<sup>1</sup> in both years) was significantly (*p* <sup>≤</sup> 0.05) higher than the soil P observed after chopping cover crops at 25 and 35 DAP. As shown in Table 6, there was no statistically significant interaction between cover crops and their times of chopping among treatments with respect to the available soil P.

### 3.3.4. Available Soil Potassium

As shown in Table 6, the amount of available soil potassium (K) in the topsoil (0–20 cm), which was determined after the harvest of baby corn in both years, was not significantly (*p* ≤ 0.05) different between all cover crops and the control. The average available soil K among all cover crop and control treatments ranged from 158.1 to 163.9 kg·ha−<sup>1</sup> during 2014–2015. The amount of available soil K following pearl millet treatment was higher than the available soil K observed following sorghum and fodder maize cover crops, and no cover crop (i.e., control), particularly in 2015 *kharif* season when the amount of available soil K following pearl millet cover crop was significantly higher than following sorghum, fodder maize, and control treatments. In both years, the average amount of available soil K was increased with increment in chopping time from 25 DAP to 45 DAP. On average, the available soil K after chopping cover crops at 45 DAP (164.0 kg·ha−<sup>1</sup> and 165.4 kg·ha−<sup>1</sup> in 2014 and 2015, respectively) was significantly higher than after chopping cover crops at 25 DAP and 35 DAP. Similar to the available soil N and P content, there was no interaction of cover crops and their times of chopping on the available soil K among treatments in both years. The use of cover crops treatments did not markedly increase topsoil K content at harvest (Table 6) compared to K values observed at the beginning of this study (Table 1). The enhanced soil K content following various cover crops have been observed in several studies (e.g., [81,82]). Studies also suggested that cover crops could accumulate K at the soil surface due to deposition of crop residue and lack of surface-applied fertilizers [81,82]. However, the succeeding crop in its growing season could take up soil K at a much higher rate than the addition of K by cover crops, resulting in lower soil K concentrations [82].

### **4. Conclusions**

Effects of three non-leguminous cover crops (pearl millet, fodder maize, and sorghum) and their times of chopping on the yield and quality of no-till baby corn were evaluated during two *kharif* seasons (during 2014–2015) under subtropical climatic conditions of Punjab, India. During both *kharif* seasons, the yield (cob and green fodder yield) and dry matter accumulation of baby corn following cover crop treatments were significantly higher than the control (no cover crop) and improved with increment in chopping time from 25 DAP to 45 DAP. Among cover crop treatments, the yield (cob and green fodder yield) and dry matter accumulation of baby corn following pearl millet cover crop were significantly higher compared to fodder maize and sorghum cover crop and control treatments. Chopping of cover crops at 45 DAP showed significantly higher yield and dry matter accumulation of baby corn over chopping at 25 DAP and 35 DAP. The effect of cover crops on baby corn quality parameters (i.e., protein, starch, crude fiber, total soluble solids (TSS), total solid, and sugar content) was not significant among treatments during both *kharif* seasons, while increment in chopping time (from 25 DAP to 45 DAP) had a significant effect on the protein and sugar content of baby corn cob. The use of cover crops and increment in chopping time generally helped in enhancing topsoil quality at harvest, especially available soil N. However, the effect of cover crops and their times of chopping on other topsoil quality parameters (i.e., organic carbon content, and available soil P and K) did not differ among treatments. During both *kharif* seasons, there was no significant interaction between cover crops and their times of chopping among treatments with respect to baby corn yield and quality as well as topsoil quality parameters. Based on the results during two *kharif* seasons, it is suggested that non-leguminous cover crops and their times of chopping evaluated in this study could be used for sustainable maize crop production system to improve baby corn growth and yield, baby corn quality, and topsoil quality. However, long-term evaluation of these non-leguminous cover crops and increment in chopping time on *kharif* baby corn yield and quality, as well as soil quality under subtropical climatic conditions, is needed.

**Author Contributions:** A.S. and J.S.K. conceived and designed the experiments. Funding acquisition and project administration were performed by J.S.K., A.S., and J.S.K. performed the experiments and collected the data. A.S., J.S.K., and S.K.D. analyzed the data. S.S. and P.S. provided technical assistance when the data was analyzed. S.K.D. and A.S. wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** We are grateful to the Department of Agronomy, Punjab Agricultural University (PAU), Ludhiana for providing field and laboratory facilities for the experiment. We gratefully acknowledge the funding support from the "Farm Fresh Foods" (Ladhowal, Punjab) to carry out this research during 2014–2015. We are also thankful to graduate students and technical staff of the Department of Agronomy, PAU, for their assistance during the field experiment. The constructive comments from three anonymous reviewers have improved this manuscript and are greatly appreciated.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **E**ff**ect of Stand Reduction at Di**ff**erent Growth Stages on Yield of Paprika-Type Chile Pepper**

### **Israel Joukhadar \* and Stephanie Walker**

Extension Plant Sciences, New Mexico State University, P.O. Box 30003, MSC 3AE, Las Cruces, NM 88003, USA; swalker@nmsu.edu

**\*** Correspondence: icalsoya@nmsu.edu

Received: 16 December 2019; Accepted: 24 February 2020; Published: 5 March 2020

**Abstract:** Paprika-type chile (*Capsicum annuum* L.) crops are susceptible to plant population losses through pest activity, disease, and extreme weather events such as hail storms. This study was conducted to determine the influence of intensity and timing of plant population reductions on the final harvested yield of paprika-type chile so that informed decisions can be made regarding continuing or ending a damaged field. Two trials, one per year, were conducted in southern New Mexico. 'LB-25', a standard commercial cultivar, was direct seeded on 29 March 2016 and 4 April 2017. Plants were thinned at three different growth stages; early seedling, first bloom, and peak bloom. Plants were thinned to four levels at each phenological stage; 0% stand reduction (control; ~200,000 plants/ha), 60% stand reduction (~82,000 plants/ha), 70% stand reduction (~60,000 plants/ha), and 80% stand reduction (~41,000 plant/ha). In both years, the main effects of stand reduction had a significant impact on harvested yield, emphasizing the percentage of stand reduction has more of an impact on yield than timing in paprika-type red chile. Consistently, an 80% stand reduction in paprika-type chile significantly reduced fresh red chile yield by 26% to 38%.

**Keywords:** *Capsicum annuum*; heat units; plant population density; hail damage

### **1. Introduction**

Crop hail damage can cause considerable economic loss during the growing season [1]. Physical crop injury can be divided into two main categories; defoliation and stand reduction [2]. Many researchers have simulated stand reduction in crops such as cotton (*Gossypium hirsutum* L.), corn (*Zea mays* L.), soybeans (*Glycine max* L.), and wheat (*Triticum aestivum* L.) by cutting and removing a specific number of plants from the field [2–4]. Conversely, for many vegetable crops including paprika-type chile, little to no research of a similar type has been conducted [1].

Paprika-type red chile (*Capsicum annuum* L.) is a specialty crop important in the southwest region of the United States with a total of 5382 ha of red chile harvested in New Mexico, Arizona, and Texas in 2016 [5,6]. Stand reductions due to pests and extreme weather events have been identified as threats to chile farmers in both Arizona and New Mexico. In response to these threats, the United States Department of Agriculture Risk Management Agency has started pilot programs to insure chile crops [7]. For example, in 2016, there were 136 hail events in New Mexico, 29 hail events in Arizona, and over 500 hail events in Texas [8], causing both defoliation and stand reduction damage to crops. To adequately insure and provide coverage for losses in chile, both farmers and insurance companies must have information on how chile yield changes due to stand reduction caused by pests or extreme weather events at different growth stages.

In the southwest US, New Mexico-type green and red chile are the two most prominent chile products. New Mexico-type red chile is harvested when fruit are at a mature red stage and are partially dried on the plant [9]. Paprika-type chile is a subset of red chile distinctive for fruit exhibiting very low heat level and high carotenoid content [10]. Carotenoids are extracted and used as a natural dye in a variety of food and cosmetic products [11]. Paprika-type chile is also ground into powder and used as a spice [12]. New Mexico is the only state in the southwest to categorize chile production, and in 2016, the highest harvested category of chile was paprika-type chile at 1416 ha [13]. Paprika-type chile was selected for this study due to its importance, not only in the southwest, but to the food industry all over the world. Throughout the world, red paprika-type chile is used as a culinary spice and the extracted pigments of paprika-type red chile are used a natural food colorant in many food products.

All of the previously reported research on the effect of plant population losses in paprika-type chile has been done at one growth stage, leaving a gap in the knowledge about responses during different growth stages. As Cavero et al. [14] found, paprika yield increased as plant density increased from 13,333 to 200,000 plants per hectare when the plants were thinned during the ten to twelve leaves growth stage. Although this illustrated that there is an impact on paprika-type red chile when plant populations change, how they respond to such changes over the season has not been explored. On the other hand, a paprika-type chile field with a high plant population density of 322,335 plants per hectare experienced a 60% yield reduction [10]. It has been reported that removing plants from fields with high plant populations at specific growth stages can be beneficial due to reduction in competition for light [15]. Pariossien and Flynn [10] reported the best planting density for paprika-type red chile to be 98,800 plants per hectare.

In other crops such as soybeans, when plant populations were reduced at the early growth stage, there were no significant changes in seed yield, but when stand reduction occurred in the later growth stage seed yield was decreased [2]. Similar results were found when sunflowers (*Helianthus annuus* L.) underwent stand reduction at early and late growth stages. Sunflower stand losses of 25% during later growth stages significantly reduced yield, while no reductions in yield occurred when stand losses of 25% occurred at an early growth stage [16]. Many crops can compensate for stand reduction losses early in the season.

The goal of this study was to understand how a simulation of population losses by stand reduction at different growth stages affected the yield of paprika-type red chile. Obtaining this knowledge will give farmers more insight into their yield expectations after a stand reduction event caused by pests and/or extreme weather events at any growth stage. The specific objectives were to determine how four levels of stand reduction simulating hail damage at three growth stages affect the yield components. Our hypothesis was that paprika-type red chile, an indeterminate crop, would recover from stand reduction early in the growing season.

### **2. Materials and Methods**

Field experiments were conducted during 2016 and 2017 at the New Mexico State University Leyendecker Plant Science Research Center in La Mesa, NM, USA [ LPSRC (lat. 32.16◦ N; long. 106.46◦ W; elevation 1186 m)]. The soil at LPSRC was a Glendale clay loam [17]. Fertilization during both years consisted of total nitrogen (Helena Chemicals, Collierville, TN, USA) at 168.1 kg·ha−<sup>1</sup> and total phosphorus at 112.1 kg·ha<sup>−</sup>1. All phosphorus and a quarter of the nitrogen were broadcast preplant as ammonium phosphate and the remaining nitrogen was delivered throughout the season in the irrigation water as urea and ammonium nitrate.

### *2.1. Field Cultivation*

The field was plowed, disced, laser-leveled, and listed before planting. 'LB-25' (Biad Chili Co., Leasburg, NM, USA), a common commercial paprika-type red chile cultivar, was planted at a rate of 5.6 kg·ha−<sup>1</sup> on 29 March 2016 and 4 April 2017 with metalaxyl fungicide (Ridomil Gold; Syngenta, Greensboro, NC, USA) at 146 mL·ha−<sup>1</sup> banded into the planting bed during the direct seeding of the 'LB-25'. A two-way factorial treatment structure in a randomized complete block design with four replications for a total of 48 plots was used. The first factor, stand reduction, had four levels, and the second factor, growth stage, had three levels, and each were combined and randomized in the field

plot. Each plot consisted of three rows, with a total area of 13.8 m<sup>2</sup> (3.0 m between row spacing <sup>×</sup> 4.6 m length). The field was 662.24 m2 (13.8 m2 <sup>×</sup> 48 plots) surrounded by one row (north and south) or plot (east and west) borders of paprika-type red chile plants. All plots were hand-weeded weekly each season. The field was furrow irrigated once every 10–14 days and irrigation ended on 16 September 2016 and 1 September 2017 when the crop was at a mature red growth stage.

### *2.2. Stand Reduction*

At three different growth stages, plants were thinned to four levels of stand reduction. When plants were thinned, two plants were left in a clump [18] at different spacing intervals to achieve desired plant counts per plot. When describing stand reduction treatments, a row is one of the three rows within a plot with an area of 4.6 m2 (1.0 m <sup>×</sup> 4.6 m). Each of the three rows in a plot were thinned to one of the specified treatments. The four stand reductions treatments were: control with no thinning and ~64 plants per row, 60% stand reduction with 35.7-cm spacing and ~25 plants per row, 70% stand reduction with 45.7-cm spacing and ~19 plants per row, and 80% stand reduction with 66.0-cm spacing and ~13 plants per row. The densities achieved in 2016 for each stand reduction level were 209,974 plants·ha−<sup>1</sup> (control, no thinning), 82,021 plants·ha−<sup>1</sup> (60% stand reduction), 62,336 plants·ha−<sup>1</sup> (70% stand reduction), and 42,651 plants·ha−<sup>1</sup> (80% stand reduction). The densities achieved in 2017 for each stand reduction level were 200,131 plants·ha−<sup>1</sup> (control, no thinning), 82,021 plants·ha−<sup>1</sup> (60% stand reduction), 59,055 plants·ha−<sup>1</sup> (70% stand reduction), and 39,370 plants·ha−<sup>1</sup> (80% stand reduction).

### *2.3. Growth Stages*

Stand reduction treatments occurred at pre-determined growth stages based on heat units accumulated after planting (HUAP). HUAP values were calculated using the method described by Brown [19] and Silvertooth et al. [20] (Tables 1 and 2) using 12 ◦C as the base temperature. Using heat unit systems in a phenology model for crops relates plant growth to local weather and climate conditions [19] and take into account day to day changes in temperature [20]. Daily weather data such as maximum temperatures, minimum temperatures, mean temperatures, and precipitation were collected from the LPSRC weather station, La Mesa, NM, USA [21,22] (Tables 1 and 2).





<sup>z</sup> Precipitation and temperature collected from LPSRC Weather Station, La Mesa, NM (2016). <sup>y</sup> Total weekly calculated heat units accumulated after planting; GDD (Growing Degree Days based on Fahrenheit scale) = mean daily temperature ◦F-32 ◦F; for paprika-type red chile with a base temperature of 55 ◦F, if maximum temperature exceeds 86 ◦F then maximum temperature is set at 86 ◦F in DDF equation; if minimum temperature is below 55 ◦F then minimum temperature set at 55 ◦F in DDF equation; HUAP = cumulative DDF. 32 ◦F = 0 ◦C. <sup>w</sup> Mean temperatures, total precipitation during growing season, total heat units accumulated during growing season.


**Table 2.** Growing season (4 April–17 October 2017) weather data z: weekly total precipitation, daily maximum, minimum, mean temperatures, and calculated heat units accumulated after planting.

<sup>z</sup> Precipitation and temperature collected from LPSRC Weather Station, La Mesa, NM (2017). <sup>y</sup> Total weekly calculated heat units accumulated after planting; GDD (Growing Degree Days based on Fahrenheit scale) = mean daily temperature ◦F-32 ◦F; for paprika-type red chile with a base temperature of 55 ◦F, if maximum temperature exceeds 86 ◦F then maximum temperature is set at 86 ◦F in DDF equation; if minimum temperature is below 55 ◦F then minimum temperature set at 55 ◦F in DDF equation; HUAP = cumulative DDF. 32 ◦F = 0 ◦C. <sup>w</sup> Mean temperatures, total precipitation during growing season, total heat units accumulated during growing season.

The targeted growth stages for the stand reduction treatments were early seedling stage at 700 HUAP, first bloom at 1400 HUAP, and peak bloom at 2000 HUAP [20]. Although HUAP values were used to determine phenological growth stages, we observed that early seedling stage was characterized by the plants having about 30 true leaves, 60–70 days after planting. First bloom was when anthesis began on each plant and peak bloom when more than 60% anthesis was observed. Due to inclement weather and scheduling constraints, stand reduction events did not occur at the exact targeted number of HUAPs for each growth stage. The actual HUAPs and dates for each stand reduction event in 2016 were: early seedling stage on 1 June 2016 at 623 HUAP, first bloom on 27 June 2016 at 1268 HUAP, and peak bloom on 19 July 2016 at 1849 HUAP. The actual HUAPs and dates for each stand reduction event in 2017 were: early seedling stage on 31 May 2017 at 717 HUAP, first bloom on 26 June 2017 at 1398 HUAP, and peak bloom on 17 July 2017 at 1894 HUAP.

### *2.4. Harvest*

The plots were harvested on 17 October 2016 at 3598 HUAP and on 25 October 2017 at 3629 HUAP. The harvested sample area was 3.1 m2 (3.04 m <sup>×</sup> 1.01 m) taken from the middle section of the middle row of each plot. In 2017, due to labor constraints, the sample size was reduced to 1.5 m2 (1.52 m <sup>×</sup> 1.01 m). All fruit within a sample area was hand-harvested into plastic bags and then removed from the field for sorting.

### *2.5. Yield Data Collection*

Harvested material was sorted into the following categories: (1) fresh red yield, (2) fresh green yield, (3) unmarketable yield, (4) immature yield. Fruit classified as red were fruits with more than 50% red color. Fruit classified as green were fruits with more than 50% green color. Fruit classified as unmarketable yield were fruits with blemishes and/or discoloration from disease covering over 40% of the fruit. Immature fruit were fruits under 7.6-cm and had a malleable pericarp. Immature yield was nominal, so data were not included in this report. All of the sorted material was weighed (SVI-100E; Sartorius Stedim North America, Bohemia, NY, USA). Fresh red yield was put in a drier at 54.4 ◦C until fruit were completely dehydrated and then weighed for a dry red yield. In 2016, red yield subsamples in the drier were overcome with mold and had to be discarded.

### *2.6. Data Analysis*

Additionally, this study was designed to measure and compare the interaction of stand reduction and growth stage on various yield components. Analysis was conducted on each year separately due to environmental variation between the years. Response variables analyzed in 2016 and 2017 were: fresh red yield, green yield, unmarketable yield, and plant counts. Additionally, dry red yield was analyzed in 2017, but not in 2016 due to the mold growth noted above. Response variable data were analyzed by analysis of variance (ANOVA) using SAS (version 9.4; SAS Institute, Cary, NC, USA). Tukey's significant difference test (*p* ≤ 0.05) was used to separate means when interactions between stand reduction level and growth stage were significant. When interactions were not significant, ANOVA was conducted on the main effects of stand reduction levels. If statistically significant differences were detected in the main effects, then Tukey's significant difference test (*p* ≤ 0.05) was used to separate means.

### **3. Results**

### *3.1. Weather Di*ff*erences*

There were two major differences in weather patterns between the 2016 and 2017 growing seasons. First, 2017 had an overall higher average minimum temperature for the entire season. In 2016, the season average minimum temperature was 13.7 ◦C, 0.5 ◦C cooler than in 2017. The higher minimum temperatures 2017 increased the growth rate of the plants, so they matured at a faster rate. Due to this, the 2017 season was 28 weeks long and the 2016 season was 30 weeks long. Second, 2017 had 5.2 cm more total precipitation during the growing season. Much of the precipitation recorded in 2017

occurred in the month of July 2017; it fell at a fast rate, leaving the field with standing water for over a week from 17 July through 24 July 2017.

### *3.2. Yield Components*

Growth stage by stand reduction interactions were not statistically significant for all of the yield components measured in 2016 and 2017 (Tables 3 and 4). So significant stand reduction main effects were evaluated. In 2016, stand reduction had a significant impact on fresh red fruit yield and plant counts (Table 3). The 0%, 60%, and 70% stand reduction plots had on average 36% more fresh red fruit yield than the 80% stand reduction plots (Figure 1A). As expected, the 0% stand reduction plots had over two and a half times more plants than the 80% and 70% stand reduction plots (Figure 1B). In 2017, stand reduction had an effect on fresh red fruit yield, dry red fruit yield, and plant counts (Table 4). The 60% stand reduction plots in 2017 had 45% more fresh red yield than the 0%, 70%, and 80% stand reduction plots (Figure 2A). The 60% stand reduction plots also had 83% more dry red yield than the 80% stand reduction plots (Figure 2B). When evaluating the plant counts, the 0% stand reduction plots had over four times the number of plants as the 80% stand reduction plots (Figure 2C).

**Table 3.** Yield and plant counts of paprika-type red chile with four stand reduction levels at three growth stages harvested on 25 October 2016.


<sup>z</sup> Percent of plant population reduced from standard population of ~200,000 plants per hectare. <sup>y</sup> Growth stage characterized by heat units accumulated after planting (HUAP) during stand reduction events for 2016; early seedling = 623 HUAP, first bloom = 1268 HUAP, peak bloom = 1849 HUAP. <sup>x</sup> All chile yields were harvested in kg per 3.1 m2; reported in tons per hectare. Fresh red yield were fruits at the mature red stage; means of n = 4. <sup>w</sup> Green yield were fruits with more than 50% green color; means of n = 4. <sup>v</sup> Unmarketable yield were fruits with more than 40% disease caused discoloration and/or blemishes; means of n = 4. <sup>u</sup> Number of counted plants in each row per plot; means off n = 4. <sup>t</sup> NS, \*\*\* Nonsignificant or significant at *p* ≤ 0.001, respectively.


**Table 4.** Yield and plant counts of paprika-type red chile with four stand reduction levels three growth stages harvested on 17 October 2017.

<sup>z</sup> Percent of plant population reduced from standard population of ~200,000 plants per hectare. <sup>y</sup> Growth stage characterized by heat units accumulated after planting (HUAP) during stand reduction events for 2017; early seedling= 717 HUAP, first bloom = 1398 HUAP, peak bloom = 1894 HUAP. <sup>x</sup> All chile yields were harvested in kg per 3.1 m2; reported in tons per hectare. <sup>w</sup> Weight of dehydrated fresh red fruit yield, means of n = 4. <sup>v</sup> Green yield were fruits with more than 50% green color; means of n = 4. <sup>u</sup> Unmarketable yield were fruits with more than 40% disease caused discoloration and/or blemishes; means of n= 4. <sup>t</sup> Number of counted plants in each row per plot; means off n = 4. <sup>s</sup> NS, \*, \*\*\* Nonsignificant or significant at *p* ≤ 0.05, or 0.001, respectively.

**Figure 1.** Stand reduction effects on fresh red yield (**A**) and plant counts (**B**) of paprika-type chile in 2016. Mean values of yield component measurements ± SE; all values are means of n = 12. Means separated by Tukey's test, *p* ≤ 0.05. Means with common letter do not differ significantly. Yield reported in tons per hectare.

**Figure 2.** Stand reduction effects on the fresh red yield (**A**), dry red yield (**B**), and plant counts (**C**) of paprika-type chile in 2017. Mean values of yield component measurements ± SE; all values are means of n = 12. Means separated by Tukey's test, *p* ≤ 0.05. Means with common letter do not differ significantly. Yield reported in tons per hectare.

### **4. Discussion**

We found that the timing of stand reductions for paprika-type chile did not impact marketable red yields at the end of the season. Studies conducted in soybeans and sunflowers showed that yield was significantly impacted by the growth stage during which a stand reduction occurs. When sunflower plant populations were reduced in early growth stages they were able to recover yield, but stand losses in later growth stages resulted in yield reductions [16]. Similar results were found in soybeans when stand losses occurred in the early growth stages and yield was not affected due to plant compensation [2]. Yet, we found paprika-type chile yield was not affected by the growth stage during which stand reduction occurred. This could be due to our methodology of thinning the plots to clumps of 2 to 3 plants [18]. This standard practice, long employed by red chile growers in New Mexico, may provide protection from yield losses by increasing interplant competition. Interplant competition

driven by clumped plants may increase vigorous plant growth earlier in the season [9] producing robust plants by midseason that are able to compensate for plants lost. Additionally, we may not have decreased plant populations at optimal growth stages to have an impact on yield components. Our 70% and 80% stand reduction plots did not have statistically different plant counts in either 2016 or 2017; perhaps a 90% stand reduction plot was necessary.

In 2017, our control plots with 0% stand reduction had less fresh and dry red yields. Reports have shown that chile grown in dense populations will yield less due to a decrease in plant light reception [10,23]. Our lower yields in 2017 may suggest that some thinning might be necessary to ensure each plant has access to light and enough space to adequately grow.

Traditionally, when evaluating how crops respond to stand reductions due to pest and/or extreme weather damage, two variables are taken into consideration: growth stage and extent of crop loss [16,24,25]. Our yield components were not significantly affected by the growth stage during the stand reduction event. The percentage of stand losses had a greater impact on the fresh red yield and dry red yield of paprika-type chile. According to our results, percentage of crop loss is a better predictor of end of season crop loss than the growth stage during which the stand reduction occurs. Therefore, insurance adjusters and farmers can estimate paprika-type chile crop losses based on percentage of stand losses instead of growth stage. Fresh red yield will be significantly reduced by 26% to 38% when plant populations are reduced by 80%. Cavero et al. [14] had comparable yield loss results, indicating paprika-type chile has some capacity to recover and compensate for stand reduction losses. This has been observed in other indeterminate crops such as lentils (*Lens culinaris* L.) that can compensate for stand reduction caused by hail damage anytime during the season [26]. Our data shows that a farmer could lose up to 70% of their paprika-type chile stand (a remaining plant population of at least 60,000 plants per hectare) due to hail damage and experience minimal to no impact on their yields.

**Author Contributions:** I.J., conception or design of the work, and the acquisition, analysis, or interpretation of data for the work, wrote initial draft of manuscript, and completed edits. S.W., conception or design of the work, co-authored initial draft of manuscript, and completed edits. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no additional funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


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