**Physiological and Biochemical Responses to Salt Stress in Cultivated Eggplant (***Solanum melongena* **L.) and in** *S. insanum* **L., a Close Wild Relative**

**Marco Brenes 1,2, Andrea Solana 1, Monica Boscaiu 3, Ana Fita 1, Oscar Vicente 1, Ángeles Calatayud 4, Jaime Prohens <sup>1</sup> and Mariola Plazas 1,\***


Received: 31 March 2020; Accepted: 17 April 2020; Published: 4 May 2020

**Abstract:** Eggplant (*Solanum melongena*) has been described as moderately sensitive to salinity. We characterised the responses to salt stress of eggplant and *S. insanum*, its putative wild ancestor. Young plants of two accessions of both species were watered for 25 days with an irrigation solution containing NaCl at concentrations of 0 (control), 50, 100, 200, and 300 mM. Plant growth, photosynthetic activity, concentrations of photosynthetic pigments, K+, Na+, and Cl<sup>−</sup> ions, proline, total soluble sugars, malondialdehyde, total phenolics, and total flavonoids, as well as superoxide dismutase, catalase, and glutathione reductase specific activities, were quantified. Salt stress-induced reduction of growth was greater in *S. melongena* than in *S. insanum.* The photosynthetic activity decreased in both species, except for substomatal CO2 concentration (Ci) in *S. insanum*, although the photosynthetic pigments were not degraded in the presence of NaCl. The levels of Na<sup>+</sup> and Cl<sup>−</sup> increased in roots and leaves with increasing NaCl doses, but leaf K<sup>+</sup> concentrations were maintained, indicating a relative stress tolerance in the two accessions, which also did not seem to suffer a remarkable degree of salt-induced oxidative stress. Our results suggest that the higher salt tolerance of *S. insanum* mostly lies in its ability to accumulate higher concentrations of proline and, to a lesser extent, Na<sup>+</sup> and Cl−. The results obtained indicate that *S. insanum* is a good candidate for improving salt tolerance in eggplant through breeding and introgression programmes.

**Keywords:** eggplant; wild relative; vegetative growth; photosynthesis; ion homeostasis; osmolytes; oxidative stress

#### **1. Introduction**

Soil salinity affects over 1000 million ha of land throughout the world [1,2], and it continuously increases worldwide, affecting large areas of arable land [3]. The effects of soil salinity on plants vary depending on weather conditions, light intensity, soil characteristics, and species or taxonomic groups [4], but most crops are glycophytes and, therefore, are not able to grow on saline soils. Generally, growth of glycophytes is completely inhibited at salt concentrations in soil equivalent to 100–200 mM NaCl, eventually resulting in the death of the plant [5].

Eggplant (*Solanum melongena* L.) is one of the most popular vegetable crops throughout the world and, especially in Southeast Asia [6], and is moderately sensitive to salinity [7]. Eggplant fruits have a low calories content and contain high concentrations of phenolic acids, beneficial for human health [8,9]. Eggplant is cultivated on more than 1.86 million hectares and its annual production is over 54 million tonnes [6]. *Solanum melongena* can be crossed with a wide range of wild relatives from the primary, secondary, and tertiary genepools [10], and backcrossing to *S. melongena* of the interspecific hybrids for introgression breeding can result in the incorporation of traits from wild species into the eggplant genepool and in the broadening of the genetic basis of the crop [11–13]. Therefore, identifying sources of variation for tolerance to salinity among eggplant wild relatives, some of which grow in harsh environments, including areas prone to salinity [14], can contribute to breeding eggplant for higher tolerance to salinity. One of the most promising species for introgression breeding in eggplant is *S. insanum* L., which is the wild ancestor of eggplant and grows in a wide range of soil conditions [15]. Interspecific hybrids between *S. melongena* and *S. insanum* as well as backcrosses of the hybrids to *S. melongena*, are easily obtained and are highly fertile [10,11,16], which facilitates the transfer of traits from *S. insanum* to *S. melongena*.

To our knowledge, the responses of *S. insanum* under conditions of salt stress have not yet been studied. Data on physiological and biochemical traits under stressful conditions could be used as selection criteria for possible breeding programmes [17]. This study aims to determine the level of tolerance to salinity of *S. insanum*, comparing it to *S. melongena* by analysing the variation of growth traits, photosynthesis, and biochemical responses associated with tolerance to salinity, such as levels of ions accumulated in different tissues, osmolytes, and antioxidants. The results will provide relevant information on *S. insanum* as a possible source of variation of tolerance to salinity, for eggplant breeding.

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

#### *2.1. Plant Material and Experimental Layout*

The plant material used was provided by the Institute for the Conservation and Improvement of Valencian Agrodiversity (COMAV-UPV). *Solanum melongena* accession MEL1 originates from Ivory Coast, and *S. insanum* INS2 from Sri Lanka. *Solanum melongena* MEL1 was chosen as this accession is of particular interest for breeding as it has an excellent fruit set and shows a high degree of success in interspecific hybridisation [10,11]. Seeds were germinated following a shortened version of a protocol developed by Ranil et al. [18]. Briefly, seeds were soaked first for 24 h in water and for an additional 24 h in a 500 ppm solution of gibberellic acid (GA3), and then placed in Petri dishes on filter paper moistened with a solution of 1000 ppm KNO3 and subjected to a heat shock treatment at 37 ◦C for 24 h. The Petri dishes were transferred to a growth chamber under conditions of 16 h light/8 h darkness at 25 ◦C until germination was completed. Once germinated, seedlings were placed in seedbeds and kept under the same conditions of light and temperature for two weeks. Seedlings homogenous in size were selected and transplanted to small pots and, subsequently, to 1.3 L pots with 500 g of Huminsubstrat N3 (Klasmann-Deilmann, Geeste, Germany) commercial substrate. The plants were transferred to a greenhouse with benches and controlled temperature (maximum of 30 ◦C and minimum of 15 ◦C) for acclimatisation for 20 days, and when plants developed 6–8 fully expanded leaves, the stress treatments were started. Five plants of each species, each one corresponding to a biological replica, were irrigated every four days with 1.25 L of NaCl solutions (final concentrations: 50, 100, 200, and 300 mM NaCl dissolved in deionised water) or deionised water for the control plants, for 25 days, and several non-destructive growth parameters were measured in all plants (stem length, stem diameter, and number of leaves). Runoff water after irrigation was allowed to freely drain. Measurements for physiological, biochemical, and ion content parameters were based on one technical replicate.

#### *2.2. Electrical Conductivity of the Substrate*

Electrical conductivity of the substrate was measured in a 1:5 suspension (EC1:5). At the end of the treatments, after removing the plants from the pots, the remaining substrate was dried in an oven at 65 ◦C for four days and a soil/water (1:5) suspension was prepared in deionised water and stirred for 1 h at 600 rpm and 21 ◦C. EC was measured with a Crison Conductivity-meter 522 (Crison Instruments SA, Barcelona, Spain) and expressed in dS m<sup>−</sup>1.

#### *2.3. Gaseous Exchange*

At the end of the stress period (25 days), the CO2 assimilation rate (AN, μmol CO2 m−<sup>2</sup> s−1), stomatal conductance to water vapor (gs, mol H2O m−<sup>2</sup> s−1), substomatal CO2 concentration (Ci, μmol CO2 mol−<sup>1</sup> air), and transpiration rate (E, mmol H2O m−<sup>2</sup> s−1) were measured in one of the fully developed leaves of each plant using a portable LI-COR 6400 infrared gas analyser (Li-Cor Inc., Lincoln, NE, USA).

#### *2.4. Evaluation of Growth Parameters*

To assess the effect of salt stress on the two species, several growth parameters were analysed at the end of the treatments: fresh weight of roots (RFW), stems (SFW), and leaves (LFW); length of roots (RL) and stems (SL); stem diameter (SD); and area of the largest leaf (LA). Stem elongation (SE), stem thickening (ST), and increase in the number of leaves (Lno) were calculated as the difference between the final and initial values of stem length, stem diameter, and number of leaves, respectively, in the same plant. The water content of roots (RWC), stems (SWC), and leaves (LWC) was determined by weighing a part of fresh material, drying it for four days at 60 ◦C, and weighing it again; the humidity percentage was calculated with the following formula: [(Fresh weight − Dry weight)/Fresh weight] \* 100.

#### *2.5. Ion Quantification*

Contents of potassium (K+), sodium (Na+), and chloride (Cl−) were determined in roots and leaves. Samples of 50 mg of ground dry plant material in 15 mL of deionised water were heated at 95 ◦C for one hour, followed by cooling on ice and filtration through a 0.45 μm nylon filter [19]. The Na<sup>+</sup> and K<sup>+</sup> content was quantified with a PFP7 flame photometer (Jenway Inc., Burlington, VT, USA), and the Cl− content was determined using a chlorimeter (Sherwood, model 926, Cambridge, UK).

#### *2.6. Quantification of Photosynthetic Pigments*

The content of chlorophyll a (Chl a), chlorophyll b (Chl b), and carotenoids (Caro) was determined using the methodology described by Lichtenthaler and Wellburn [20]. Pigments were extracted from 50 mg fresh plant material using 10 mL of ice-cold 80% acetone (v/v), and the extracts were diluted 10 times using the same solvent. The absorbance was measured at 470, 645, and 663 nm (A470, A645, and A663, respectively), and the following formulas were used to calculate the different pigments:

$$\text{Chl a } (\text{\(\mu g mL}^{-1}) = 12.21 \times \text{A}\_{663} - 2.81 \times \text{A}\_{646} \tag{1}$$

$$\text{Chl} \,\text{b} \,\text{ } (\mu\text{g } \text{mL}^{\pm 1}) = 20.13 \times \text{A}\_{646} - 5.03 \times \text{A}\_{663} \tag{2}$$

$$\text{Caro (\mu g mL}^{-1}) = (1000 \times \text{A}\_{470} - 3.27 \times \text{[Chl a]} - 104 \times \text{[Chl b]}) / 227 \tag{3}$$

#### *2.7. Quantification of Osmolytes*

The quantification of free proline (Pro) was carried out following the acetic acid-ninhydrin method [21]. An aqueous solution (2 mL) of 3% (w/v) sulfosalicylic acid was added to 50 mg freshly ground plant material (from each biological replica). One volume of extract was mixed with one

volume of ninhydrin acid and one volume of glacial acetic acid, and then the mix was placed in a water bath at 95 ◦C for one hour, and subsequently cooled for 10 min on ice and extracted with toluene. The absorbance of the organic phase was determined at 520 nm using toluene as the blank.

Total soluble sugars (TSSs) were measured according to the methodology described in [22]. Fresh leaf material (50 mg) was ground and mixed with 3 mL of 80% (v/v) methanol on a rocker shaker for 24 h, and the extract was recovered by centrifugation; concentrated sulfuric acid and 5% phenol were added to the supernatant and the absorbance was measured at 490 nm. TSS contents were expressed as 'mg equivalent of glucose' per g dry weight (DW).

#### *2.8. Measurement of Malondialdehyde (MDA) and Antioxidant Compounds*

MDA, total phenolic compounds (TPCs), and total flavonoids (TFs) were measured in plant extracts prepared from 50 mg ground fresh leaf material using 80% (v/v) methanol. For MDA quantification, extracts were mixed with 0.5% thiobarbituric acid (TBA) prepared in 20% trichloroacetic acid (TCA), or with 20% TCA without TBA for the controls, and then incubated at 95◦C for 20 min, cooled on ice, and centrifuged at 12,000× *g* for 10 min at 4 ◦C [23]. The absorbance of the supernatants was measured at 532 nm. The non-specific absorbance at 600 and 440 nm was subtracted, and MDA concentration was determined using the equations included in [23], based on the extinction coefficient of the MDA-TBA adduct at 532 nm. The concentration of MDA was expressed as nmol g−<sup>1</sup> DW.

TPCs were measured using the Folin–Ciocalteu reagent [24]. Methanol extracts were mixed with Na2CO3 and the reagent and, after 90 min of incubation in the dark, the absorbance was measured at 765 nm. A standard reaction was performed in parallel using known amounts of gallic acid (GA), and TPC contents were reported as equivalents of GA (mg eq. GA g−<sup>1</sup> DW).

Total flavonoids (TFs) were quantified according to the method described by Zhisen et al. [25], based on the nitration of aromatic rings containing a catechol group. Methanol extracts of each sample were reacted with NaNO2 and AlCl3 under alkaline conditions, and the absorbance at 510 nm was measured. The concentration of TFs was expressed as equivalents of catechin, used as the standard (mg eq. C g−<sup>1</sup> DW).

#### *2.9. Antioxidant Enzyme Activities*

The activities of superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR) were measured in crude protein extracts prepared from frozen (−70 ◦C) leaf material, as previously described [26]. Enzyme activities in the extracts were expressed as 'specific activities', in units per mg of protein.

SOD activity in the protein extracts was determined as described by Beyer and Fridovich [27], following the inhibition of nitroblue tetrazolium (NBT) photoreduction by measuring the absorbance of the sample at 560 nm. The reaction mixtures contained riboflavin as the source of superoxide radicals. One SOD unit was defined as the amount of enzyme causing 50% inhibition of NBT photoreduction under the assay conditions.

CAT activity was measured by the decrease in absorbance at 240 nm, which accompanies the consumption of H2O2 added to protein extracts [28]. One CAT unit was defined as the amount of enzyme that will decompose one mmol of H2O2 per minute at 25 ◦C.

The protocol of Conell and Mullet [29] was used for the GR assays, following the oxidation of NADPH (the cofactor in the GR-catalysed reduction of oxidised glutathione (GSSG)) by the decrease in absorbance at 340 nm. One GR unit was defined as the amount of enzyme that will oxidise one mmol of NADPH per minute at 25 ◦C.

#### *2.10. Statistical Analysis*

Data were analysed using the software Statgraphics Centurion v. XVI (Statpoint Technologies Inc., Warrenton, VA, USA). The significance of the differences between treatments (for each species), between species (for each treatment) and their interaction were evaluated through a two-factorial analysis

of variance (ANOVA) for traits related to plant growth, photosynthetic pigments, photosynthesis parameters, osmolytes, MDA, and antioxidants. For ion accumulation, an additional factor (organ) was included and a three-way factor analysis of variance (ANOVA) (treatment, species, and organ) was performed. Post-hoc comparisons were made using the Tukey Honestly Significant Difference (HSD) test at *p* < 0.05 for the effects of treatment within species (and combinations of species and organ in the case of ions). All the parameters measured in plants of the control and salt stress treatments were subjected to multivariate analysis through a principal component analysis (PCA).

#### **3. Results**

#### *3.1. Substrate Electrical Conductivity*

Electrical conductivity of the substrate increased in parallel to the concentration of NaCl, applied in a similar manner in both species, as indicated by the analysis of variance, which detected significant differences only between treatments, but not between the two species. EC reached the highest levels at the end of the treatments (19.19 dS m−<sup>1</sup> for *S. melongena* and 23.66 dS m−<sup>1</sup> for S*. insanum*) in the pots watered with 300 mM NaCl (Figure 1).

**Figure 1.** Electrical conductivity (EC1:5) of the pot substrates after 25 days of treatment with the indicated NaCl concentrations, in *Solanum melongena* (blue) and *S. insanum* (red). Same letters indicate homogeneous groups between combinations of treatments for EC according to the Tukey test (*p* < 0.05, *n* = 5).

#### *3.2. Analysis of Morphological and Photosynthetic Parameters*

Salt stress inhibited the growth of the two species, in a concentration-dependent manner. Several growth parameters were determined in control and salt-stressed plants, at the end of the treatments, and a two-way ANOVA was performed, considering the effect of treatment, species, and their interaction (Table 1). The effect of 'species' was significant for most of the parameters, except root length (RL), some stem traits [stem elongation (SE), thickening (ST), fresh weight (SFW), water content (SWC)], total fresh weight (TFW), and chlorophyll a (Chl a). The effect of 'treatment' was significant for all traits analysed, except water content of roots (RWC), stems (SWC), and leaves (LWC), as well chlorophylls a and b (Chl a and Chl b). The interaction of the two factors was significant only for stem elongation (SE), the increase in leaf number (Lno), leaf fresh weight (LFW), and the area of the largest leaf (Table 1).

**Table 1.** Two-way analysis of variance (ANOVA) of species, treatment, and their interactions, for the indicated parameters. Numbers shown represent percentages of the sum of squares (SS).



**Table 1.** *Cont.*

<sup>a</sup> \*\*\*, \*\*, and \* indicate significant at *p* < 0.001, *p* < 0.01, and *p* < 0.05, respectively.

At the root level, the effect of salt was more pronounced in *S. melongena*, as root length (RL) and root fresh weight (RFW) did not vary significantly in *S. insanum* (Table 2). In both species, the water content of the roots increased with salinity. Growth of the stems was affected by salinity, but the water content was maintained stable in both species. Regarding the analysed leaf parameters, all showed a significant decrease in salt-treated plants of *S. melongena*, whereas in S*. insanum*, their variation was not significant, except for the increase in the number of leaves (Lno). When considering the total fresh weight (TFW), the reduction was significant only in the cultivated eggplant, but not in the wild species, in which, at the lowest concentration applied, TFW even increased, although the variation was not statistically significant in relation to the control. In both species, the water content of the leaves (LWC) did not vary significantly with the treatments (Table 2). Moreover, the variation between treatments of Chl a and Chl b was non-significant, whereas carotenoids decreased only in *S. insanum*. Stomatal conductance (gs), internal concentration of CO2 (Ci), and transpiration (E) decreased in *S. melongena*, but not in *S. insanum*; photosynthesis rate (AN), on the other hand, showed a significant reduction in both species (Table 2).


**Table 2.** Growth responses and photosynthetic parameters in *Solanum melongena* (MEL) and *S. insanum* (INS) after 25 days of treatment with the indicated NaCl concentrations.


**Table 2.** *Cont.*

Mean ± SE values are shown (*n* = 5). Same letters within each row (lowercase for *S. melongena* and capital letters for *S. insanum*) indicate homogeneous groups between treatments for each species, according to the Tukey HSD test (*p* < 0.05). Abbreviations: root length (RL; cm), root fresh weight (RFW; g), root water content (RWC; %), stem elongation (SE; cm), stem thickening (ST; mm), stem fresh weight (SFW; g), stem water content (SWC, %), increase in the number of leaves (Lno), area of the largest leaf (LA; cm2), leaf fresh weight (LFW; g), leaf water content (LWC; %), total fresh weight (TFW; g), chlorophyll a (Chl a; mg g−<sup>1</sup> dry weight (DW)), chlorophyll b (Chl b; mg g−<sup>1</sup> DW), carotenoids (Caro; mg g−<sup>1</sup> DW), photosynthestic rate (AN; μmol CO2 m−<sup>2</sup> s<sup>−</sup>1), stomatal conductance (gs; mol H2O m−<sup>2</sup> s<sup>−</sup>1), internal concentration of CO2 (Ci; μmol CO2 mol−<sup>1</sup> air), and transpiration rate (E; mmol H2O m<sup>−</sup><sup>2</sup> s<sup>−</sup>1).

For an easier estimation of the pattern of variation of growth parameters in the two species, the variation of fresh weight and water content in the roots, stems, and leaves of the plants subjected to the salt treatments is shown in Figure 2, as percentages of the values measured in the corresponding non-stressed controls. In general, both fresh weight (FW) and water content (WC) showed a relatively smaller reduction in *S. insanum* than in *S. melongena*, at least in roots and leaves, and more pronounced at the highest salt concentration tested (Figure 2).

**Figure 2.** Reduction of fresh weight (FW) (**a**) and water content (WC) (**b**) in roots (MELr and INSr), stems (MELs and INSs), and leaves (MELl and INSl) of *Solanum melongena* (MEL; blue lines) and *S. insanum* (INS; red lines) plants after 25 days of salt treatments at the indicated NaCl concentrations. Values are shown as percentages of the corresponding controls (0 mM NaCl).

#### *3.3. Ion Accumulation*

To analyse the changes in ion contents in the plants, in response to the salt treatments, a multifactorial ANOVA was performed, considering the effect of the treatment, species, organs of the plants (roots vs. leaves), and their interactions (Table 3). In the case of Na<sup>+</sup> and Cl<sup>−</sup> contents and the K+/Na<sup>+</sup> ratio, the main effect was that of the treatment, which was highly significant for all traits, whereas the 'species' factor was significant only for Cl<sup>−</sup> and K+. The effect of the 'organ' variable was significant for Cl−, K+, and the K+/Na<sup>+</sup> ratio, but it was by far the greatest contributor to the sums of squares for K+, as leaves of both species contain considerably higher concentrations of K<sup>+</sup> than the roots. Some significant double and triple interactions were detected, for example, between 'treatment' and 'species' or between 'treatment' and 'organ' for Na<sup>+</sup> and Cl−, but their contribution to the sums of squares was generally low (below 3.5%), except for the interaction between 'treatment' and 'organ' for the K+/Na<sup>+</sup> ratio (Table 3).

**Table 3.** Factorial analysis of variance (ANOVA) considering the effect of treatment (A), species (B), organ (C), and their interactions (A <sup>×</sup> B; A <sup>×</sup> C; B <sup>×</sup> C; A <sup>×</sup> <sup>B</sup> <sup>×</sup> C) on ions (Na+, Cl−, K+) contents and the K+/Na<sup>+</sup> ratio, in *Solanum melongena* and *S. insanum*. Numbers represent percentages of sum of squares (SS).


<sup>a</sup> \*\*\*, \*\*, and \* indicate significant at *p* < 0.001, *p* < 0.01, and *p* < 0.05, respectively.

In both species, Na<sup>+</sup> and Cl<sup>−</sup> concentrations increased in parallel to the increase in external salinity, in the roots and the leaves of the plants (Figure 3a,b). The pattern of variation was similar in the two species, as were, in general, the contents of both ions in roots and leaves for each NaCl concentration tested, except that *S. insanum* accumulated higher levels of Na<sup>+</sup> and Cl<sup>−</sup> in leaves than in roots at high salinity (200–300 mM NaCl). On the contrary, K<sup>+</sup> levels remained generally steady in response to the salt treatments, in roots and leaves of the two species, and in all cases, significantly higher in the leaves (Figure 3c). The salt-induced increase in Na<sup>+</sup> concentrations, accompanied by no significant changes of K<sup>+</sup> contents, led to a significant decrease of the K+/Na<sup>+</sup> ratio in both species, especially in the leaves, where the initial values in the controls were higher than in roots (Figure 3d).

**Figure 3.** *Cont.*

**Figure 3.** Na<sup>+</sup> (**a**), Cl<sup>−</sup> (**b**), and K<sup>+</sup> (**c**) contents and K+/Na<sup>+</sup> ratio (**d**) in roots (MELr and INSr) and leaves (MELl and INSl) in *Solanum melongena* (blue) and *S. insanum* (red), after 25 days of treatments with the indicated NaCl concentrations. Mean ± SE values are shown (*n* = 5). Same letters (lowercase for roots, or uppercase for leaves) indicate homogeneous groups between combinations of treatments, according to the Tukey HSD test (*p* < 0.05).

#### *3.4. Osmolytes, MDA, and Antioxidants*

A two-way ANOVA was performed to analyse the effects of the variables 'treatment' and 'species', as well as their interaction, on different biochemical parameters related to the general responses of plants to salt stress (Table 4). This analysis revealed a strong effect of 'treatment', but also a significant effect of 'species' and their interaction for proline. In the case of TSS, however, only the 'species' factor and its interaction with 'treatment' were significant. MDA showed a significant variation according to the treatment and the species; for total phenolic compounds (TPCs), the two factors and their interaction were significant, although the strongest contribution to the sums of squares was that of 'species'. For total flavonoids (TFs), the only significant effect was owing to the treatment. Regarding the antioxidant enzymatic activities, the two factors, treatment and species, as well as their interaction, were significant for SOD, whereas only the species effect was significant for CA, and no significant factor was detected for GR. It is remarkable that, for all biochemical compounds analysed, except proline, and for the three enzymatic activities, the percentage of the sum of square of residuals was the most important contributor to the sums of squares, indicating a high influence of uncontrolled residual variation (Table 4).

**Table 4.** Two-way analysis of variance (ANOVA) of treatment, species, and their interactions for the parameters considered. Numbers represent percentages of sum of squares (SS) at the 5% confidence level. Abbreviations: proline (Pro), total soluble sugars (TSSs), malondialdehyde (MDA), total phenolic compounds (TPCs), total flavonoids (TFs), superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR).


<sup>a</sup> \*\*\*, \*\*, and \* indicate significant at *p* < 0.001, *p* < 0.01, and *p* < 0.05, respectively.

Leaf proline (Pro) levels increased significantly in the two species in response to the salt stress treatments. In *S. melongena*, Pro contents were lower than in *S. insanum* at all tested salinities, reaching a peak in the presence of 200 mM NaCl, and decreasing at 300 mM NaCl. In *S. insanum*, Pro increased gradually in parallel to the external NaCl concentration, reaching levels about 10-fold higher than in the control at 300 mM NaCl (Figure 4a). Contrary to Pro, total soluble sugars (TSSs) in leaves showed a slight increase in salt-treated *S. melongena* plants, but the difference with the control was significant only in the presence of 200 mM NaCl. Average TSS contents were substantially higher in *S. insanum* than in *S. melongena* plants, in the control and at low salinity, to decrease at higher NaCl concentrations; however, the differences with the non-stressed controls were non-significant (Figure 4b).

**Figure 4.** Proline (Pro) (**a**) and total soluble sugars (TSSs) (**b**) contents in *Solanum melongena* (blue) and *S. insanum* (red) after 25 days of treatments with the indicated NaCl concentrations. Mean ± SE values are shown (*n* = 5). Same letters (lowercase for *S. melongena* and capital for *S. insanum*) indicate homogeneous groups between combinations of treatments, according to the Tukey HSD test (*p* < 0.05).

Malondialdehyde (MDA) is regarded as a reliable marker of oxidative stress, as it is a product of peroxidation of unsaturated fatty acids, indicating damage to cell membranes by 'reactive oxygen species' (ROS) in plants and animals [30]. However, its levels did not increase in salt-treated plants as compared with the controls, neither in *S. melongena* nor in *S. insanum*; on the contrary, leaf MDA contents slightly decreased in response to increasing salinity in plants of the two species (Table 5). A similar decreasing trend was observed for the mean values of the analysed antioxidant compounds, TPC and TF, although the differences with the non-stressed controls were not statistically significant in *S. melongena* (Table 5). Moreover, no significant salt-induced differences in specific activity could be detected in the assays of the antioxidant enzymes, SOD, CAT, and GR. When comparing the two species, higher MDA, TPC, and TF contents and higher specific enzyme activities were generally observed in *S. insanum*, at each external salt concentration tested (Table 5).

**Table 5.** Malondialdehyde (MDA), total phenolic compounds (TPCs), total flavonoids (TFs), and activity of the antioxidant enzymes: superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR) in *S. melongena* (MEL) and *S. insanum* (INS) after 25 days of treatment with the indicated NaCl concentrations.



**Table 5.** *Cont.*

Units: MDA (nmol g−<sup>1</sup> DW), TPC (mg eq. GA g−<sup>1</sup> DW), TF (mg eq. C g−<sup>1</sup> DW), and enzymatic activity (U g−<sup>1</sup> protein). Mean ± SE values are shown (*n* = 5). Same letters within each row (lowercase for *S. melongena* and capital letters for *S. insanum*) indicate homogeneous groups between treatments for each species according to the Tukey HSD test (*p* < 0.05).

#### *3.5. Principal Component Analysis*

A principal component analysis (PCA) was performed, including all analysed traits in all individuals (Figure 5). Eight components with an Eigenvalue greater than one were identified, which overall explained 82.6% of the total variability; the first and second principal components accounted for 33.0% and 15.4% of the total variation, respectively. The first principal component displays positive correlations with growth parameters of stem (SE, ST, and SFW) and leaves (LA, LFW, and Lno), as well as with total fresh weight (TFW); carotenoids (Caro); photosynthetic parameters (AN, Ci, E, gs); K in leaves (Kl); the ratio K/Na in roots (K/Nar) and leaves (K/Nal); as well as MDA, TP, and TF contents. On the other hand, this first PC is negatively correlated with the levels of Na<sup>+</sup> and Cl<sup>−</sup> in roots and leaves (Nar, Nal, Clr, Cll), and with Pro and root water content (RWC). The second component displays strong positive correlations with Pro, some photosynthesis parameters (AN, E, gs), TSS, and CAT and SOD activities, whereas it is negatively correlated with root water content (RWC), leaf traits (LA, LFW, Lno), chlorophylls a and b (Chl a and Chl b), and K<sup>+</sup> contents in roots (Kr) and leaves (Kl) (Figure 5a).

**Figure 5.** Loading plot (**a**) and scatterplot (**b**) of the principal component analysis (PCA) including all the analysed traits in *Solanum melongena* and *S. incanum* plants subjected for 25 days to salt treatments. The first (PC1; X-axis) and second (PC2; Y-axis) principal components accounted for 33.0% and 15.4% of the total variation, respectively. Abbreviations in the loading plot (**a**) are as follows: root length (RL), root fresh weight (RFW), root water content (RWC), stem elongation (SE), stem thickening (ST), stem fresh weight (SFW), stem water content (SWC), leaf number increment (Lno), maximal leaf area (LA), leaf fresh weight (LFW), leaf water content (LWC), total fresh weight (TFW), chlorophyll a (Chla), chlorophyll b (Chlb), carotenoids (Caro), photosynthetic rate (AN), internal concentration of CO2 (Ci), transpiration (E), stomatal conductance (gs), sodium in roots (Nar), sodium in leaves (Nal), potassium in roots (Kr), potassium in leaves (Kl), chloride in roots (Clr), chloride in leaves (Cll), ratio potassium/sodium in roots (K/Nar), ratio potassium/sodium in leaves (K/Nal), proline (Pro), total soluble sugars (TSS), malondialdehyde (MDA), total phenolic compounds (TPC), total flavonoids (TF), superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR). Plants of *S. melongena* and of *S. insanum* are represented in blue and red, respectively, in the scatter plot (**b**). Salt treatments are represented by different symbols: 0 (-), 50 (•), 100 (), 200 (¡), and 300 (×) mM NaCl.

The 50 individuals analysed were dispersed onto the two axis of the PCA scatterplot (Figure 5b), indicating a clear separation of the applied treatments along the first principal component (X-axis), and of the two species along the second principal component (Y-axis). Plants subjected to the different salt treatments are distributed along the X-axis, from higher positive values (non-stressed controls), to higher negative values (300 mM NaCl), with almost no overlapping of the different treatments, except for the 200 and 300 mM NaCl in *S. melongena*. Samples from moderate salinity treatments (50–100 mM NaCl for *S. melongena* and 100–200 mM NaCl for *S. insanum*) are located in the scatterplot in intermediate positions, closer to '0 in the X-axis. This pattern of distribution validates the homogeneity of responses within each treatment in the two species. Regarding the second principal component, except for one sample per species, *S. insanum* samples are located in the positive part of the Y-axis, whereas *S. melongena* samples have negative values for this component.

#### **4. Discussion and Conclusions**

Eggplant is a glycophyte and, as such, responds to increased salinity by a reduction in growth parameters and yield, being generally considered as moderately sensitive (or moderately resistant) to salt stress [7,17,31,32], as other cultivated species of the same genus [33]. However, this crop is characterised by a large variation of phenotypical, biochemical, and physiological traits, which is related to differences between cultivars in their responses to biotic [34] or abiotic stresses, including drought and salinity [35–37]. Therefore, the use of more stress-tolerant cultivars of eggplants on marginal lands or on salinised soils is a realistic challenge for the future, considering that global warming is generating an increased rate of secondary salinisation [38]. Soils are considered as saline when their EC (in a soil saturated paste) is above 4 dS m<sup>−</sup>1; this electric conductivity corresponds to approximately 40 mM NaCl, generating an osmotic pressure of 0.2 MPa, which significantly reduces the yield of most crops [39]. These values cannot be directly compared with our results as we measured the substrate EC in soil/water (1:5) suspensions (EC1:5), not in saturated soil pastes. Nevertheless, in our experiments, all concentrations of NaCl applied were higher than 40 mM, ranging from 50 to 300 mM NaCl. After 25 days of treatments, the salinity of the substrate in pots exposed to the higher concentrations of salt was clearly beyond that normally occurring on salinised soils. All plants survived the salt treatments, but, as expected, growth of stressed plants was reduced in comparison with those from the control treatments in the two investigated species, *S. melongena*, the cultivated eggplant, and its wild relative *S. insanum*.

The analysis of several growth parameters indicated that, in general, the degree of salt-induced growth inhibition was relatively lower in *S. insanum* than in *S. melongena*. One of the most reliable growth variables, when ranking stress tolerance in different cultivars or related species, is the variation of fresh weight (FW) of the plants [36,40,41]. The analysis of this parameter clearly indicated a better tolerance to high salinity in *S. insanum* as the FW of all vegetative organs (roots, stems, and leaves) showed a lesser reduction than in *S. melongena* in the presence of 200 mM and, especially, 300 mM NaCl. Under the 50 mM and 100 mM NaCl treatments, RFW and LFW even slightly increased in the wild species, indicating that these low concentrations have an inhibitory effect only on stem growth. A smaller increase, also non-significant, was registered under 50 mM NaCl for the leaf area (LA) and total fresh weight (TFW) in this species. The highest concentration of 300 mM was not lethal, as all individuals survived until the end of the experiment, but its effect was considerably stronger on *S. melongena*, as shown by a 60% reduction of the total fresh weight (TFW) as compared with only a 30% reduction in *S. insanum*. Special attention is required for the analysis of the root growth parameters because, apparently, all salt treatments stimulated root growth in *S. insanum*. On the contrary, although lower salt concentrations had a positive effect of root growth in *S. melongen*a, under the 300 mM NaCl treatment, root length (RL) and root fresh weight (RFW) were significantly reduced. Therefore, the development of more vigorous roots under salt stress represents an important adaptative trait in *S. insanum.* The water content (WC) of vegetative organs, particularly leaves, is another useful indicator of the relative salt tolerance of related taxa. The more tolerant species or cultivars are usually

resistant to salt-induced leaf dehydration, or at least the degree of water loss is lower than in the more sensitive ones [42,43]. Indeed, this has also been observed comparing different eggplant cultivars, with those more stress-tolerant showing higher leaf water contents under salt stress conditions [37]. It is worth mentioning that the specific eggplant cultivar used in the present work, MEL1, although more sensitive to salt stress than *S. insanum* INS2, is nevertheless quite tolerant to salinity, at least much more than other common crops such as *Phaseolus* cultivars [42]; all plants survived the salt treatments, even at 300 mM NaCl, and a significant growth inhibition was only observed at the highest salinities tested.

Salt stress reduces photosynthesis, which is one of the major reasons for growth inhibition [44,45]. One of the first effects of abiotic stress is the closure of stomata, which helps in reducing the water loss, but also limits the intake of CO2. Therefore, in C3 plants (like the two species studied here), C assimilation decreases in such conditions [46]. The photosynthetic rate may also decrease owing to the degradation of chlorophylls or the inhibition of photosynthetic enzymes caused by toxic ions. The photosynthesis rate (AN) decreased in the two species, but only in plants treated with the highest NaCl concentrations, not at lower salinities, as has been reported in different eggplant cultivars [47]. The internal concentration of CO2 (Ci) and the transpiration (E) were reduced in *S. melongena* plants in response to the salt treatments, which is associated with a decrease in stomatal conductance (gs); this has also been observed in other cultivars of eggplant [48,49]. In *S. insanum*, however, salt stress did not induce any significant change in the above-mentioned photosynthetic parameters. On the other hand, in both species, chlorophylls a and b levels remained constant, for the control and all salt treatments, contrary to previous reports in eggplant [48,50]. The maintenance of a high assimilation rate in *S. insanum* may rely on its better developed root system, which allowed a higher water uptake under stressful conditions and a lower need for a restriction in transpiration (E), reflected in a higher stomatal conductance (gs) and internal concentration of CO2 (C). Taken together, these results point to a slightly higher salt tolerance of *S. insanum* INS2, as compared with *S. melongena* MEL1.

Regarding ion accumulation, a significant increase in Na<sup>+</sup> and Cl<sup>−</sup> contents was registered in parallel to increasing external salinity, at 100 mM and higher NaCl concentrations, both in roots and leaves and in plants of the two species; similar results have been previously reported in different eggplant cultivars [7,48,49]. Glycophytes typically respond to salt stress trying to limit the accumulation of toxic ions in the leaves, either reducing their absorption by the roots or blocking their transport to the aerial parts of the plant [50]; these mechanisms are effective only at low or moderate salinities, and once a certain threshold—dependent on the tolerance of each specific genotype—is exceeded, Na<sup>+</sup> and Cl<sup>−</sup> concentrations increase in the leaves. In our experiments, no inhibition of Na<sup>+</sup> or Cl<sup>−</sup> transport from roots to leaves was observed because, generally, their concentration in roots was not higher than in leaves. In *S. melongena*, the concentration of the two ions was practically identical in roots and leaves, at each salinity level (except for Na<sup>+</sup> at 100 mM NaCl). Interestingly, in *S. insanum* plants treated with 200 or 300 mM NaCl, Na<sup>+</sup> concentrations in leaves were substantially higher than in roots, and the same pattern was observed for Cl− at 100 mM and higher NaCl concentrations. This suggests that, in this species, high salinity activates the transport of these ions from roots to leaves, where they could contribute to cellular osmotic balance as inorganic osmolytes. This is not a common behaviour of glycophytes like eggplant, but represents one of the most relevant mechanisms of salt tolerance in dicotyledonous halophytes [51,52], which could also be operative in *S. insanum*, contributing to its relative higher tolerance, enhanced also by a more developed root system that allows a higher ion uptake.

Potassium homeostasis is also critical for salt tolerance, which includes as a key mechanism the intracellular retention of K<sup>+</sup> in the presence of high external salinities [53,54], as this cation is essential in plant metabolism. An increase in Na<sup>+</sup> concentration is generally accompanied by a decrease of K+, as both cations compete for the same membrane transport proteins [55]. Furthermore, high Na<sup>+</sup> levels produce a depolarisation of the plasma membrane, which induces K+-efflux from cells by activating voltage-dependent outward rectifying channels [56,57]. Many reports indicated a reduction of K<sup>+</sup> in conditions of salt stress in eggplant, as expected [32,48,49]. In our experiments, however, no significant

changes in root or leaf K<sup>+</sup> concentrations were observed in response to the salt treatments. Maintenance of constant K<sup>+</sup> levels, despite the increase in Na<sup>+</sup> concentrations, probably also contributes to salt tolerance, in this case, in both tested genotypes, *S. melongena* MEL1 and *S. insanum* INS2. Further studies will be required to elucidate the specific ion transporters involved in these regulatory mechanisms.

Another general response to salt stress is the synthesis of Pro, one the commonest osmolytes in plants, which, besides osmotic adjustment, plays an important role in ROS detoxification and maintenance of membrane integrity under stress [58,59]. Pro accumulation may be simply a biomarker of the level of stress affecting a plant, reaching higher concentrations in the more stressed individuals, as has been shown in some comparative studies on related genotypes [42]. On the contrary, Pro can be directly involved in the mechanisms of tolerance to stress, so that higher contents correlate with higher tolerance [40]. Comparative analyses of different eggplant cultivars have provided mixed results; in some cases, the more stress-tolerant genotypes accumulated higher Pro concentrations [35,36,60], but in other studies, higher levels were found in the more sensitive ones [32]. Our results clearly showed higher Pro levels in *S. insanum* than in *S. melongena* in all experimental conditions, but especially in the presence of the highest salinity tested, 300 mM NaCl, thus correlating with the relative salt tolerance of the two investigated species.

Although soluble sugars play a role in osmoregulation under stress conditions in many plant species [61], their levels did not vary significantly in response to the salt treatments in *S. insanum*, and were similar in the two species at high salinities. Therefore, TSS contents do not correlate with the degree of salt tolerance, and probably do not play any relevant role in the responses to salt stress of the two species studied here.

Mechanisms of salt tolerance based mostly on the accumulation of Pro, for osmotic adjustment and as 'osmoprotector'—with the possible contribution of Na<sup>+</sup> and Cl<sup>−</sup> as inorganic osmolytes in the case of *S. insanum*—appear to be efficient enough to avoid the generation of oxidative stress under the specific conditions used in our experiments. A common effect of high salinity, as well as other abiotic stresses, is the increase in the concentration of ROS, leading to secondary oxidative stress [62]. That did not occur in the present work, as shown by the determination of MDA contents, which did not increase in response to the salt treatments. Consequently, the activation of antioxidant systems, enzymatic and non-enzymatic, was also not detected, as the plants did not need to counteract any salt-induced oxidative stress. Generally, this behaviour is not observed in glycophytes, but has been reported for many halophytes [26,63].

In conclusion, our results from plant growth, photosynthetic parameters, and biochemical stress markers measurements indicate that *S. insanum* displays greater tolerance to moderate salt stress than *S. melongena*, mostly because of its ability to accumulate higher concentrations of Pro and, to a lesser extent, Na<sup>+</sup> and Cl<sup>−</sup> in the leaves, especially at high external salinities. Given that *S. insanum* and *S. melongena* are fully cross-compatible [10,16], and introgression breeding from *S. insanum* into *S. melongena* is relatively easy [11], we suggest that *S. insanum* can contribute to the development of *S. melongena* cultivars with increased salt tolerance. It remains to be evaluated if *S. insanum* could also be useful as a rootstock for eggplant under conditions of salinity. Therefore, the use of *S. insanum* in eggplant breeding and rootstock development may make an effective contribution to extending cultivation of eggplant in cultivated lands that are affected, or will be in the future, by soil salinity.

**Author Contributions:** Conceptualization, O.V. and J.P.; Data curation, M.B. (Marco Brenes) and M.B. (Monica Boscaiu); Formal analysis, J.P.; Funding acquisition, O.V. and J.P.; Investigation, M.P.; Methodology, M.B. (Marco Brenes) and A.S.; Project administration, O.V.; Resources, O.V. and J.P.; Software, M.B. (Monica Boscaiu); Supervision, M.P.; Validation, A.F. and A.C.; Visualization, M.B. (Monica Boscaiu) and M.P.; Writing—original draft, M.B. (Monica Boscaiu) and J.P.; Writing—review & editing, A.F., O.V., A.C., and M.P. All authors have read and agreed to the published version of the manuscript

**Funding:** This work was undertaken as part of the initiative "Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives", which is supported by the Government of Norway and managed by the Global Crop Diversity Trust. For further information, see the project website: http://cwrdiversity.org/. Funding was also received from Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación and Fondo Europeo de Desarrollo Regional (grant RTI-2018-094592-B-100 from MCIU/AEI/FEDER, UE), European

Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 677379 (Linking genetic resources, genomes, and phenotypes of Solanaceous crops; G2P-SOL) and Vicerrectorado de Investigación, Innovación y Transferencia de la Universitat Politècnica de València (Ayuda a Primeros Proyectos de Investigación; PAID-06-18). Mariola Plazas is grateful to Generalitat Valenciana and Fondo Social Europeo for a post-doctoral grant (APOSTD/2018/014). Marco Brenes is indebted to the Faculty of Biology of the Costa Rica Institute of Technology for partially supporting his stay in Valencia ("Fondo Solidario y Desarrollo Estudiantil").

**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**


© 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* **Main Root Adaptations in Pepper Germplasm (***Capsicum* **spp.) to Phosphorus Low-Input Conditions**

**Leandro Pereira-Dias 1, Daniel Gil-Villar 1, Vincente Castell-Zeising 2, Ana Quiñones 3, Ángeles Calatayud 3, Adrián Rodríguez-Burruezo <sup>1</sup> and Ana Fita 1,\***


Received: 27 March 2020; Accepted: 19 April 2020; Published: 1 May 2020

**Abstract:** Agriculture will face many challenges regarding food security and sustainability. Improving phosphorus use efficiency is of paramount importance to face the needs of a growing population while decreasing the toll on the environment. Pepper (*Capsicum* spp.) is widely cultivated around the world; hence, any breakthrough in this field would have a major impact in agricultural systems. Herein, the response to phosphorus low-input conditions is reported for 25 pepper accessions regarding phosphorus use efficiency, biomass and root traits. Results suggest a differential response from different plant organs to phosphorus starvation. Roots presented the lowest phosphorus levels, possibly due to mobilizations towards above-ground organs. Accessions showed a wide range of variability regarding efficiency parameters, offering the possibility of selecting materials for different inputs. Accessions bol\_144 and fra\_DLL showed an interesting phosphorus efficiency ratio under low-input conditions, whereas mex\_scm and sp\_piq showed high phosphorus uptake efficiency and mex\_pas and sp\_bola the highest values for phosphorus use efficiency. Phosphorus low-input conditions favored root instead of aerial growth, enabling increases of root total length, proportion of root length dedicated to fine roots and root specific length while decreasing roots' average diameter. Positive correlation was found between fine roots and phosphorus efficiency parameters, reinforcing the importance of this adaptation to biomass yield under low-input conditions. This work provides relevant first insights into pepper's response to phosphorus low-input conditions.

**Keywords:** *Capsicum annuum*; root structure; root hairs; phosphorus use efficiency; P-starvation; abiotic stress; macrominerals; nutrient; breeding

#### **1. Introduction**

Agriculture will face many challenges in the next generations, especially those related to food security and agricultural sustainability [1,2]. On one hand, intensive agriculture has a significant impact on the environment, contributing to soil erosion, soil salinization, eutrophication and contamination of water bodies, and biodiversity reduction [3,4]. On the other hand, agricultural systems need to be improved in order to cope with requirements of an increasing population as well as the impact of climate change consequences [1,5].

In both cases, one of the most critical resources involved is phosphorus (P), an inorganic mineral with a major role within the physiochemical processes of plants [6,7]. Since almost 40% of the world's arable land lacks of P or the soil properties to make it available for crops, P absence is a major constraint to food production all around the world [8–10]. Until now, application of P-enriched fertilizers has been the main strategy to face its deficiency in soils despite the severe contaminants emissions associated to its production [3,9,11]. In addition, only 15 to 40% of the added P is taken up by crops [3,9,12], while the remaining ends up being washed down through the soil, contributing to eutrophication of water bodies [13,14]. Furthermore, as costs of extraction increase and rock-phosphate reserves decline, P is becoming an extremely expensive resource that is already unaffordable in many regions of the globe [10]. As demand for P-enriched fertilizers is going to increase in the next decades, the control for P supply will be a source of conflicts [7,9]. Therefore, there is a need for P low-input adapted varieties.

The response to P-starvation conditions has been studied for a few model organisms and some economically important crops, such as soybean, maize, sunflower, brassica or melon over the last decades [15–19]. As a result, researchers have linked several root traits to a greater performance under low P conditions [20]. Thus, morphological changes, such as the increment of number of root hairs and higher root branching [15,18,21], as well as physiological changes, such as cellular structure alteration, enhanced phosphatases enzyme activity and organic acids production and root P transporters enhanced expression [12,16,22,23], are adaptations expressed under P-starvation conditions. The exploitation of these plant adaptations could have a remarkable impact on the reduction of chemical fertilizers inputs in agricultural systems [12,24].

Peppers (*Capsicum* spp.) are one of the most relevant vegetables, grown in almost all temperate and tropical regions of the world [25]. Food and Agriculture Organization of the United Nations (FAO) last available data estimates around 40 <sup>×</sup> 106 t of pepper produced each year [26]. Therefore, improving pepper for its uptake and use of P would significantly reduce the need for P-fertilizer applications [3,12]. Notwithstanding, the development of improved *Capsicum* varieties for P low-input conditions is a challenging goal and is conditioned by both the availability of genetic variability within *Capsicum* and the understanding of the mechanisms underlying the response. Regarding the first point, *Capsicum* spp., particularly *Capsicum annuum* L., is remarkably diverse, as well as adapted to a wide range of environments and, therefore, tolerant to several abiotic stresses [27–30]. However, pepper fundamentals regarding this subject have never been studied. Hence, we believe that an exhaustive characterization of pepper germplasm for its responses under P low-input conditions is of paramount importance in order to recognize the variability within the genus, to enhance our understanding regarding the responses activated under such conditions and, finally, to link those responses to the genomic regions controlling them. Herein, the characterization of the main root adaptations of pepper accessions to low P conditions was established as a main goal, as a first step towards the identification of elite individuals for future pepper breeding programs.

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

#### *2.1. Germplasm*

A collection of 25 pepper accessions, encompassing 22 *Capsicum annuum*, two *Capsicum chinense* and one *Capsicum frutescens* accessions, comprising a wide range of variability for fruit shape, fruit pungency, fruit color, biotic resistances and adaptation to the environments, was studied herein [31] (Table 1). The considered collection belongs to the Instituto Universitario de Conservación y Mejora de la Agrodiversidad Valenciana (COMAV) Germplasm Bank (Universitat Politècnica de València, Spain) and to the COMAV *Capsicum* breeding group, and was selected based on previous experiments, where an interesting performance and diversity for several relevant root and P uptake traits was observed [32].





#### *2.2. Germination and Cultivation Conditions*

Seeds were surface sterilized with a 30% NaClO solution (v:v) for five minutes, followed by rinsing with steril deionized water, and transfered to individual Petri dishes containing a wet layer of cotton under a filter paper disk. Two drops of 2% Tetramethylthiuram disulphide solution were added to each Petri dish to prevent fungal proliferation. Petri dishes were kept under germination chamber conditions until two-cotyledon stage. Seedlings were then transferred to seedling trays filled with Neuhaus N3 substrate (Klasmann-Dellmann GmbH, Geeste, Germany), kept under heated nursery conditions until the five leaves stage and, finally, transplanted to the greenhouse.

The experiment was carried out in two years. In the first year (from now on Trial 1), 12 accessions were trialed and the five most interesting genotypes were re-trialed in the second year (from now on Trial 2), against 13 new accessions (Table 1). In both trial years, plants were grown for 60 days under a mesh greenhouse, during the spring-summer cycle, on COMAV experimental fields (Universitat Politècnica de València Vera Campus GPS coordinates: 39◦28 56.33" N; 0◦20 10.88" W). Transplant was carried out in June and the experiment was finished in August. Nine (Trial 1) and six (Trial 2) plants, per accession and treatment, were grown in 15 L plastic pots filled with substrate made by mixing a part of soil with a part of sand (1:1) and arranged into a completely randomized design with six rows. Pots were spaced 1.2 m between rows and 0.40 m inside rows, while a drip irrigation system provided water and nutrient solutions to cover the plants' water and nutritional requirements. Individual plants were trained with vertical strings, according to standard local practices for pepper. Plants were not pruned during the experiment in order to avoid interference with biomass yield. Likewise, phytosanitary treatments against whiteflies, spider mites, aphids and caterpillars were applied accordingly to population levels.

Plants were subjected to two treatments. On one hand, control treatment was applied using a standard solution providing all elements (Table S1). On the other hand, stress treatment (from now on NoP) was applied using similar solution to the control treatment except for P carrying ions, which were removed from the formulation of the solution (Table S1).

#### *2.3. Sample Preparation*

After the 60 days period plants were harvested for processing. Shoot and fruits were processed separately in order to assess effects of P deprivation on both tissues. Each tissue was put into individual paper bags and dried at 70 ◦C, until constant weight was achieved, in a Raypa ID-150 oven (R. Espinar S.L., Barcelona, Spain). At this point, shoot (SW, g) and fruit (FW, g) dry weights were determined, and those tissues were ground into a thin powder, using a domestic Taurus coffee grinder (Taurus Group, Oliana, Spain), for later mineral content analysis. Furthermore, all plants' roots were separated from substrate by gently washing them with running tap water and processed separately from other tissues [33]. This was done by hand, one root at a time (Figure 1).

For Trial 1 (*n* = 9), root hairs (Ø < 0.5 mm) were separated from lateral roots (Ø > 0.5 mm) and dried at 70 ◦C in order to obtain root hairs dry weight (RHW, g) (Figure 1). It is important to note that what is referred here as root hairs does not correctly translate to the root anatomical definition of root hairs; instead, it includes root hairs and some fine tertiary and lower order roots. However, herein it is useful to differentiate between the evaluated root parts. In the same way, lateral roots are mainly secondary roots; however, as can be seen in the picture Figure 1C, they can also include a portion of tertiary roots, as it was impossible to separate all in such a large amount of samples. Lateral roots were scanned, using an Epson Expression 1640XL G650C scanner (Seiko Epson Corp., Suwa, Japan), and resulting images were analyzed by WinRIZHOTM Pro 2.3 software (Regent Instruments Inc., Québec, QC, Canada). Lateral root total length (LRL, m), lateral root average diameter (LRAD, mm) and total length of lateral roots with diameter under (LRL<1mm, m) and above (LRL>1mm, m) 1 mm were determined based on said images for each plant included in the experiment. Finally, scanned lateral roots were dried in order to obtain lateral roots dry weight (LRW, g) and ground for mineral content determination (Figure 1). From those measurements, several parameters were calculated

in order to better characterize plants' performance. Hence, for trial 1, total root dry weight (RW, g) was determined as the sum of RHW and LRW and, therefore, total biomass dry weight (BW, g) was calculated as the sum of RW, SW and FW. In addition, root to shoot weight ratio (R/S) was calculated by dividing RW by SW; the percentage of root dry weight devoted to root hairs (RHW%) was calculated by the division of RHW by RW. Furthermore, the proportion of root length devoted to fine lateral roots (PLFR, %) was defined as the ratio between LRL<1mm and LRL. Finally, lateral root specific length (LRSL, m/g) was calculated by dividing LRL by LRW.

For Trial 2 (*n* = 6), roots were entirely scanned (Figure 1). In order to fully capture a root's morphometrics, individual roots were properly spread over several transparent acetate sheets (Figure 1) and analyzed by WinRIZHOTM Pro 2.3 software (Regent Instruments Inc., Canada). Root total length (RTL, m), total root average diameter (TAD, mm) and total length of roots with diameters under (RL<1mm, m) and above (RL>1mm, m) 1 mm, were determined for each plant. Finally, the scanned roots were dried until constant weight was achieved and ground to a powder as in Trial 1. Root hairs dry weight (RHW, g), lateral roots dry weight (LRW, g), total root dry weight (RW, g), total biomass dry weight (BW, g), root to shoot ratio (R/S), percentage of root dry weight devoted to root hairs (RHW%) and root specific length (RSL, m/g) were determined as in Trial 1. Finally, the proportion of root length devoted to fine lateral roots was determined, that is, including root hairs and roots below 1 mm (PFR, %), as the ratio between RL<1mm and RTL.

**Figure 1.** Illustration of the roots along the scanning process (from a representative sample). Individual root systems were separated from the soil with running tap water and taken to the laboratory to be scanned and dried. In Trial 1, whole roots (**A**) were separated into (**B**) root hairs (Ø < 0.5 mm) and (**C**) lateral roots (Ø > 0.5 mm). Root hairs (**B**) were only weighed while lateral roots (**C**) were scanned and weighed. In Trial 2, whole roots (**A**) were also separated into root hairs (**B**) and lateral roots (**C**) and both were scanned and weighed.

#### *2.4. Tissue Mineral Concentration Assessment*

Before mineral content determination, samples were mineralized [34]. Thus, 2 g of powdered plant tissue were calcined for 2 h in a muffle at 450 ◦C. Ashes resulting from mineralization were let to cool down, weighted and then hydrated with 2 mL of distilled water followed by addition of 2 mL of concentrated HCl (Scharlau, Valencia, Spain). At this point, the solution was heated on a hot plate, until first fumes appeared, and then filtered with Whatman filter paper (Sigma-Aldrich, St. Louis, MI, USA). Finally, distilled water was added in order to make up to 100 mL volume [34].

In Trial 1 (*n* = 4), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sodium (Na) and sulfur (S) concentration (g 100 g−<sup>1</sup> DW) in different plant tissues (root, shoot and fruits, [Mineral]Tissue) was determined by Inductively Coupled Plasma-Atomic Emission Spectrometry (ICP-AES; iCAp-AES 6000, Thermo Scientific, Cambridge UK). Samples were digested for 24 h by adding 10 mL 65% HNO3 solution (Panreac Quimica S.A.U., Barcelona, Spain) to 0.5 g dried material, in a 25 mL open vessel. Digested samples were then boiled at 120 ◦C for 10 min followed by another 25 min at 170 ◦C. Finally, samples were cooled, 2 mL of 70% HClO4 was added (Panreac Quimica S.A.U., Barcelona, Spain) and were then heated at 200 ◦C for 40 min. At this point, samples were transferred to a flask and volume was brought up to 25 mL with distilled water.

For Trial 2 (*n* = 6), leaves' P-concentration ([P]Shoot) was determined by colorimetric reaction (MAPA, 1994). This method is based on absorbance measurement at 430 nm of each sample in acid solution and on the presence of vanadium (V5<sup>+</sup>) and molybdenum (Mo6<sup>+</sup>) ions. Under these conditions, phosphoric acid forms a phosphomolybvanadate complex that gives yellow coloration. Hence, 5 mL of mineralized solution were pipetted into a new 25 mL volumetric flask, followed by the addition of 5 mL of nitro-vanado-molybdic reagent. Volume was then brought up to 25 mL with distilled water. Prior to mineral concentration determination, a standard curve was constructed with standards 0, 2, 4, 6, 8, 10 and 12 μg of P mL−<sup>1</sup> prepared from an initial solution of 20 μg of P mL<sup>−</sup>1. Sample P concentration was determined using a 6305 model UV/V spectrophotometer (Jenway, Gransmore Green, England, UK) at 430 nm against a standard curve.

#### *2.5. Phosphorus Uptake and Use E*ffi*ciency Parameters*

In order to better characterize treatment effect on accessions performance, several widely-used P uptake and P use efficiency parameters (PUE) were calculated based on previous works [18,21] (Table 2).

**Table 2.** P uptake and P use efficiency (PUE) parameters used in this experiment and corresponding abbreviation, formula and expressed units. Dry weight (DW), total biomass dry weight biomass weight (BW).


<sup>1</sup> P concentration ([P]), Dry weight (DW), total biomass dry weight (BW) <sup>2</sup> Note that for Trial 2 only [P]shoot was measured, therefore PTP was obtained as [P]shoot × BW; <sup>3</sup> Note that [P] in Trial 1 is the weighted average [P] among different tissues, whereas in Trial 2 [P] = [P]shoot.

#### *2.6. Statistical Analysis*

Two-way factorial analysis of variance (ANOVA) was performed using individual plant values in order to assess accession and treatment effects and interaction significance [35]. In addition, Student-Newman-Keuls post-hoc multiple range test (*p* < 0.05) was used to detect significant differences among accession means for all evaluated traits. Finally, trait differences between treatments (μ*NoP*-μ*Control*) were used to perform multivariate Principal Component Analysis (PCA) using Euclidean pairwise distances. In addition, traits variation (%) between control and NoP conditions was calculated as μ*NoP*−μ*Control* μ*Control* × 100%. All statistical analysis were performed using Statgraphics Centurion XVII (StatPoint Technologies, Warrenton, VA, USA) and plotted using R package ggplot2 [36,37].

#### **3. Results**

#### *3.1. General Treatment E*ff*ect on P and Other Minerals Concentrations for Trial 1*

P concentration ([P]) in plant tissues is an important indicator of both treatment effectiveness and accession's capability to make the most with the available resources. In Trial 1 (*n* = 4), plants cultivated under NoP conditions showed significantly lower [P] compared to control plants. This behavior was statistically significant for all three sampled tissues (Table S2). For [P]Roots, there was a reduction from 0.56 g P 100 g−<sup>1</sup> DW, when cultivated under control conditions, to 0.10 g P 100 g−<sup>1</sup> DW (−81.76%) when cultivated under NoP conditions (Table S2). For [P]Shoot, values decreased from 0.18 g 100 g<sup>−</sup><sup>1</sup> DW to 0.12 g P 100 g−<sup>1</sup> DW (−29.31%) for control and NoP conditions, respectively; this the organ is less affected by the treatment (Table S2). Finally, fruit P levels dropped from 0.26 g P 100 g−<sup>1</sup> DW, when irrigated with control solution, to 0.17 g P 100 g−<sup>1</sup> DW (−35.18%) when NoP solution treatment was applied (Table S2).

Concentration of other macrominerals was determined in order to assess possible deficiencies induced by the applied treatments. Regarding that, significant differences between treatments were observed, particularly for K and Mg, probably due to the differences in the nutrient solutions and as a result of plant ionic adjustments. Despite that, mineral concentrations were within the normal range for pepper (Table S2) [6,38].

#### *3.2. Treatment E*ff*ect on P Accumulation and E*ffi*ciency Parameters for Trial 1 by Accessions*

Accessions were significantly affected by the NoP treatment, but not all to the same extent, as shown by the two-way ANOVA (Table S3) and the accession mean values for the evaluated traits (Table S4). For example, [P]Root dropped as much as 91.62% and 90.53% for bol\_037 and sp\_cwr accessions, respectively, while for bol\_144 the reduction was considerably lower (74.12%) (Table 3). Regarding [P]Shoot, the most affected accessions were sp\_piq (−45.26%) and sp\_cwr (−45.03%), while some accessions experienced no statistically significant reduction of their shoot P concentration, e.g., bol\_037, bol\_144, eq\_973, mex\_pas, sp\_bola and sp\_cat (Table 3 and Table S4). Finally, for [P]Fruit, only sp\_bola showed no statistical difference between both treatments, whereas the remaining accessions represented significant reductions of around 35% (Table 3).

In terms of P tissue accumulation, significant differences were found among accessions. Thus, despite P-deficient plants had on average 86.16% less accumulated P in the root (RootP) than control plants, 56.12% less P in the shoots (ShootP), and 34.32% less in fruits (FruitP), some genotypes, such as bol\_144 or eq\_973, increased the amount of fruit accumulated P (although this was not statistically significant). Overall, plant total P (PTP) was reduced by 63.30%; however, several genotypes experienced no statistically significant reduction of this trait, e.g., bol\_037, bol\_144\_eq\_973 and sp\_bola, while others, like sp\_mel, were highly affected (Table 3 and Table S4).

Furthermore, in order to evaluate how efficient genotypes were under these conditions parameters of physiological P use efficiency (PPUE), P efficiency ratio (PER), P uptake efficiency (PUpE) and P utilization efficiency (PUtE), were calculated [18,21]. Overall, PPUE was on average 36.26% higher under NoP conditions (Table 3). However, accessions' behavior for this parameter was extremely variable and significant differences between treatments were only found for two accessions, mu\_esp (41.31%) and sp\_cwr (97.53%) (Table 3 and Table S4). On the other hand, PER's behavior was more consistent and NoP treatment produced a generalized increase, averaging at 87.64% (Table 3). In this

case, only two accessions showed no significant differences, bol\_144 and sp\_bola (Table 3 and Table S4). Interestingly, the best performers in terms of increasing PER from control to NoP conditions were California type accessions (sp\_cat, sp\_mel and sp\_cwr) and *Capsicum chinense* accession eq\_973.

In addition, an interesting amount of variability was observed for P uptake efficiency (PUpE) and P utilization efficiency (PUtE) parameters (Figure 2). PUpE refers to the increase of internal P when it is available in the environment, whereas PUtE measures the ability of a genotype to increase its biomass per unit of internal P. Both measures always compare two conditions differing in P levels. PUpE averaged 96.56 mg P for the whole collection, where accessions mex\_scm (128.77 mg P), mu\_esp (144.43 mg P), sp\_cat (130.06 mg P), sp\_piq (124.53 mg P) and usa\_chi (108.70 mg P) showed the highest values of the experiment (Figure 2). PUtE values ranged from 29.77 g DW g−<sup>1</sup> P (bol\_144) to 404.95 g DW g−<sup>1</sup> P (mex\_pas) and averaged 186.55 g DW g−<sup>1</sup> P. Accessions mex\_pas (404.95 g DW g−<sup>1</sup> P), usa\_chi (316.77 g DW g−<sup>1</sup> P) and sp\_bola (273.16 g DW g−<sup>1</sup> P) presented the most interesting results (Figure 2).

**Figure 2.** (**A**) Average PUpE (P Uptake Efficiency) and PUtE (P Utilisation Efficiency) values for the 12 accessions (*n* = 4) studied in Trial 1. (**B**) The black dashed line represents the average value for the whole collection for both PUpE (96.56 mg P) and PUtE (186.55 g DW g−<sup>1</sup> P) parameters.

#### *3.3. Treatment E*ff*ect on Root and Shoot Biomass and Morphometrics for Trial 1 by Accessions*

P is a major factor controlling root structure and architecture [20]. Hence, in order to understand the possible effects on plant morphology, root structure and architecture resulting from lack of P, we compared several biomass and root traits.

Thus, roots dry weight (RW) showed a significant generalized decrease (−24.52%) when genotypes were cultivated under NoP conditions compared to control plants (Table 3, Tables S3 and S4). This weight difference was more evident in lateral roots (LRW), which, on average, weighed 26.07% less, while root hairs (RHW) weight was 18.34% lower than under control conditions. Notwithstanding, the greatest weight difference was observed for shoot dry weight (SW), −36.04% under NoP conditions (Table 3, Table S3 and Table S4). Despite that, taking a closer look at the treatment effect on biomass by accession, it is observed that only three accessions reduced it significantly in all organs: mex\_pas, mu\_esp and usa\_chi. The rest of the accessions also reduced their biomass but not so systematically (Table 3 and Table S4). Interestingly, accession mex\_scm, presented similar RW and SW under both treatments, while presenting the heaviest root system and shoot within the collection under NoP conditions (Table S4). Finally, root to shoot ratio (R/S) was positively affected under NoP treatment. This parameter increased by 20.94%, on average, although only usa\_chi showed statistically significant differences between treatments (+22.73%) (Table 3), apparently achieved by reducing a shoot's weight instead of increasing a root's weight (Table S4).



101

dry weight (SW), total biomass dry weight (BW), root to shoot ratio (R/S), lateral root total length (LRL), lateral root average diameter (LRAD), percentage of root dry weight devoted to

root hairs (RHW%), proportion of root length devoted to fine lateral roots (PLFR) and lateral root specific length (LRSL). \* Indicates significant differences between treatments for that

accession and trait.

Regarding root morphology traits, treatment and accession effects showed significant influence over most traits, except for the percentage of root dry weight devoted to root hairs (RHW%), for which significant differences between treatments were not detected (Table S3), despite there being differences among accessions. In addition, for lateral root specific length (LRSL), there was a significant accession per treatment interaction (Table S3). The significant effects of the NoP conditions on pepper's roots where to increase: the lateral root length (LRL), by 16.65%, the proportion of root length devoted to fine lateral roots (PLFR), by 4.88%, and the lateral root specific length (LRSL), by 67.08%, and to decrease the root average diameter by 6.29%.

Regardless of the general treatment effect, there were significantly different responses among genotypes (Table 3 and Table S4). It is worth to mention the significant increase of percentage of root length devoted to fine lateral roots (PLFR) and lateral root specific length (LRSL) observed in mu\_esp and sp\_bola (Table 3), with mu\_esp having the higher absolute values for these traits of the whole collection under NoP conditions. Another interesting response was presented by accession bol\_144, which outperformed the other genotypes for reducing its roots average diameter (21.81%) and increase PLFR and LRSL under the NoP treatment.

#### *3.4. Principal Components Analysis for Trial 1*

Principal components analysis (PCA) was pursued in order to determine possible correlations between the response of the different measured traits to different inputs of P (% of increase or decrease, as in Table 3), trying to demonstrate how accessions differed in terms of response to different P levels. The first two principal components (PC) explained in combination 59.79% of the total variability (Figure 3A). Response in terms of total biomass dry weight (BW), physiological P use efficiency (PPUE), fruit total P content (FruitP), total shoot dry weight (SW), plant total P content (PTP), P efficiency ratio (PER) and root hairs dry weight (RHW), and values for P uptake efficiency (PUpE) and P utilization efficiency (PUtE) were the traits that contributed the most to the positive component of PC1, which explained 36.96% of the total variation. Response of lateral root average diameter (LRAD) and root total P content (RootP) were negatively correlated to PC1 (Figure 3A). Therefore, accessions plotted in the extreme right of the graph (Figure 3B), such as usa\_chi, mu\_esp, mex\_pas and sp\_piq, have in common that they have a great reduction in biomass when passing from control to NoP, and have good PUpE and PUtE. In other words, those are accessions that react very positively to any P addition to the soil but probably will not be appropriate to cultivate on poor soils (Figure 3B). At the same time, accession plotted at the upper most left part of the graph (Figure 3B), such as bol\_144 and eq\_973, are grouped for having high reductions in the total amount of P in the roots with a high reduction in the diameter of the roots (LRAD) as adaptation to low P, while having little difference in biomass under the two assayed conditions. In addition, PC2 explained 22.83% of variability with the response of lateral root dry weight (LRW), lateral root average diameter (LRAD), root dry weight (RW) and P utilization efficiency (PUtE) being the traits that contributed the most to it. Conversely, shoot P concentration ([P]Shoot), fruit P concentration ([P]Fruit) and shoot total P content (ShootP) were negatively correlated with PC2 (Figure 3A). Hence, accession located in the top part of the graph, such as mex\_pas and sp\_bola (Figure 3B), change the allocation of root resources, reducing the lateral root weight and diameter in situation of P restriction, maintaining the P level status of the shoots. On the contrary, the accessions located on the lower part of the graph such as mex\_scm stand out by changing the level of P of the shoots and fruits ([P]Shoot, [P]Fruit, and ShootP) as a strategy to adapt to the low P conditions without modifying the lateral root morphology or size (Figure 3A). Interestingly, there was a cluster of parameters, such as the response in terms of [P]Root, R/S and LRSL, indicating correlations among them.

**Figure 3.** Principal Component Analysis (PCA) for the first two components based on trait differences between treatments for Trial 1. (**A**) Correlation between traits and the first two principal components. (**B**) Distribution of accessions based on studied traits. P tissue concentration traits [P]Tissue, P tissue total content traits RootP, ShootP, FruitP, plant total P content (PTP) trait, efficiency parameters PPUE (physiological P use efficiency), PER (P efficiency ratio), PUpE (P uptake efficiency) and PUtE (P utilization efficiency) and morphometric traits RW (root dry weight), LRW (lateral root dry weight), RHW (root hairs dry weight), SW (shoot dry weight), BW (total biomass dry weight), R/S (root to shoot ratio), LRL (lateral root length), LRAD (lateral root average diameter), RHW% (root hairs dry weight %), PLFR (proportion of length dedicated to fine roots) and LRSL (lateral root specific length) were considered.

Bearing these results, the second trial was designed. In it, five accessions from Trial 1 (mu\_esp, mex\_pas, sp\_bola, sp\_piq and mex\_scm) were re-trialed and used as a comparison standard against 13 new *C. annuum* accessions. These genotypes were selected based on their above average P uptake efficiency (PUpE) and P utilization efficiency (PUtE) scores and differential behavior against the lack of P. Note that an insufficient number of seeds to re-trial sp\_cat and sp\_mel, and the poor germination of usa\_chi dictated their exclusion of Trial 2. The second trial was focused on checking the diversity within the germplasm belonging to *Capsicum annuum* species; for that reason, bol\_144 and eq\_973 were not selected, despite their interesting features. In this case, only P from the shoots was analyzed by a colorimetric protocol as a faster general measure of the P status of the plant, instead of a multi-elemental analysis by tissue. In addition, root hairs weight clustered together with P efficiency parameters was analyzed, and it was demonstrated that the lateral roots increase their length and reduce their diameter; thus, it was decided to analyze the root hairs' behavior as well. Both lateral and hair roots were scanned and analyzed (Figure 1).

#### *3.5. Treatment E*ff*ect on P Accumulation and E*ffi*ciency Parameters for Trial 2 by Accessions*

As in Trial 1, ANOVA showed that accession and treatment effects significantly affected P-related traits (Table S5). Interestingly, for physiological P use efficiency (PPUE) the accession effect was more important than treatment (Table S5). Remarkably, accession per treatment interaction was significant for a plant's total P content (PTP), PPUE and P efficiency ratio (PER) (Table S5). Accessions' individual variation between treatments are shown in Table 4 as μ*NoP*−μ*Control* μ*Control* × 100% negative then indicating lower values under NoPtraits. To consult the accessions' mean values per treatment, please refer to Table S6.

In Trial 2 (*n* = 6), all accessions but two showed significant differences between treatments for shoot P concentration ([P]Shoot), plant total P content (PTP) and P efficiency ratio (PER) showing an average reduction of −31.5% and −66.17%, and an increase of 49.26%, respectively (Table 4). Accessions mex\_096D and sp\_piq stood out for their substantial [P]Shoot reduction and high PER value. In addition, accession sp\_piq showed a significant reduction of its PTP level (−86.93%), which, along with mex\_scm (−84.16%) and usa\_sandia (−87.88%), represented the highest reductions of the whole collection (Table 4). Contrarily, sp\_lam and sp\_lobo showed no differences between treatments regarding PTP (Table 4 and Table S6). In the case of PPUE, NoP treatment presented an average reduction of 24.98%; however, significant differences were only detected for six accessions and with extremely erratic behavior within the collection; some accessions showed a reduction up to 72.75% (mex\_scm), while others showed increases up to 45.04% (usa\_jap).

Regarding P uptake efficiency (PUpE), average value was 298 mg P, ranging from 63 mg P (sp\_lobo) to 796 mg P (usa\_sandia). Accessions presenting above the average mean values were mex\_096D, mex\_103B, mex\_ng, usa\_conq and the re-trialed mex\_scm and sp\_piq (Figure 4). Contrarily to what happened in Trial 1, mu\_esp was above the average for PUpE in this trial. Finally, average P utilization efficiency (PUtE) was 110 g DW g−<sup>1</sup> P, while the minimum observed value was 43 g DW g−<sup>1</sup> P (sp\_lam) and the maximum was 183 g DW g−<sup>1</sup> P (mex\_pas). Like in Trial 1, accessions mex\_pas (183 g DW g−<sup>1</sup> P) and sp\_bola (147 g DW g−<sup>1</sup> P) presented the best performance for this parameter (Figure 4).

**Figure 4.** (**A**) Average P uptake efficiency (PUpE) and P utilization efficiency (PUtE) values for the 12 accessions studied in Trial 2 (*n* = 6). (**B**) Black dashed line represents average value for the whole collection for both PUpE (298 mg P) and PUtE (110 g DW g−<sup>1</sup> P) parameters.

#### *3.6. Treatment E*ff*ect on Root and Shoot Biomass and Morphometrics for Trial 2 by Accessions*

In trial 2 (*n* = 6), multi-factorial ANOVA detected significant accession and treatment effects as well as the accession per treatment interaction for all biomass traits except root to shoot ratio (R/S) (Table S5). As expected, the effect of the NoP treatment led to lower dry weight accumulation of all sampled organs. This time, the most affected organs were the roots (RW, −52.96%) and root hairs (RHW, −59.10%) (Table 4). The genotypes usa\_sandia, mex\_scm and sp\_piq showed the highest biomass reduction when passing from control to NoP. On the contrary, fra\_DLL, sp\_lam, sp\_lobo and usa\_jap showed no statistical differences between treatments, although it is important to note that fra\_DLL, sp\_lobo, and sp\_lam displayed the smallest plants within the collection for both treatments, which could explain their results. Accession usa\_jap, on the other hand, showed medium-sized plants (Table S6).


**Table 4.** Accession behavior given by di fferences (%) between the control and NoP conditions for Trial 2. Twenty di fferent P accumulation and e fficiency, biomass

105

 P concentration ([P]Shoot), plant total P content (PTP), physiological P use e fficiency (PPUE), P e fficiency ratio (PER), total root dry weight (RW), lateral root dry weight root hairs dry weight (RHW), shoot dry weight (SW), total biomass dry weight (BW), root to shoot ratio (R/S), root total length (RTL), total root average diameter (TRAD), percentageroot dry weight devoted to root hairs (RHW%), proportion of root length devoted to fine roots (PFR) and root specific length (RSL). \* Indicates significant differences between treatmentsfor that accession and trait.

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#### *Agronomy* **2020**, *10*, 637

All root parameters were significantly affected by the accession effect, while only a percentage of root hairs (RHW%), proportion of root length devoted to fine roots (PFR) and root specific length (RSL) were significantly affected by the treatment. For root total length (RTL), accession usa\_numex (−39.33%) was the only genotype that significantly reduced its root length, while the general population tendency was to increase it (Table 4). Accessions mex\_103B (−7.53%), mex\_ng (−13.30%) and mu\_esp (−8.37%) significantly decreased their total average diameter under NoP conditions (Table 4) in accordance with the population general trend (−1.91%). Likewise, the percentage of root dry weight devoted to root hairs (RHW%) was 14.03% lower under P-stress conditions, with accessions mex\_096D (−19.79%), sp\_11814 (−21.27%), sp\_bola (−26.14%) and sp\_piq (−21.96%) being the significantly affected ones (Table 4). Contrarily, the proportion of root length devoted to fine roots (PFR) showed a slight increase under NoP (3.33%), compared to control conditions, although only four accessions were significantly affected. Thus, accessions mex\_103B (5.91%), mex\_ng (9.79%), mu\_esp (6.53%) and sp\_lobo (8.97%) significantly increased this parameter under NoP conditions (Table 4). Ultimately, root specific length (RSL) was, on average, 138.71% higher under NoP conditions. Most accessions were significantly affected by the treatment; mu\_esp (293.57%) and sp\_11814 (282.31%) were the accessions with a higher increase for root specific length (Table 4).

#### *3.7. Principal Components Analysis for Trial 2*

The first two PCs explained 63.84% of total variation for Trial 2 (Figure 5). PC1 explained 47.48% of the total variation and was defined by the response of total biomass dry weight (BW), shoot dry weight (SW), physiological P use efficiency (PPUE), plant total P content (PTP), root dry weight (RW), root hair dry weight (RHW) and absolute values for P uptake efficiency (PUpE), while the traits that most contributed negatively were the response of the root to shoot ratio (R/S) and root specific length (RSL) (Figure 5A). PC2 on the other hand explained 16.36% of total variability and was positively correlated with response of shoot P concentration ([P]Shoot), proportion of root length devoted to fine lateral roots (PFR) and root total length (RTL), while being negatively correlated with the total root average diameter (TAD) and P efficiency ratio (PER) (Figure 5A).

Based on those results, accessions located at the right side of the graph (usa\_sandia, mex\_ng, sp\_piq, usa\_conq, mex\_scm and mex\_103B), presented an important biomass reduction under NoP conditions and, at the same time, interesting PUpE and PUtE values and an increase at the R/S and RSL level when in NoP, indicating that these are good candidates for high input conditions due to their excellent response to the addition of P through fertilization (Table 4 and Figure 5B). On that matter, usa\_sandia stood out for its impressive PUpE values and high increase of R/S and high increase of RSL (Figure 4B). On the opposite side, sp\_lam, fra\_DLL and usa\_jap accessions were located, with negative values of R/S and relative low increase of RSL (Figure 5B) and poor values for PUpE and PUtE. From this group, usa\_jap and fra\_DLL had good values of biomass under NoP (Table S6). Altogether, this indicates that they perform well under NoP conditions but do not improve with additional units of P. Furthermore, in the upper part of the graph, accessions usa\_numex and mex\_096D were characterized by decreasing the P concentration in the shoot ([P]Shoot), and thus, increasing PER, and having higher root's total length (RTL), proportion of length dedicated to fine roots (PFR) and root diameter (TAD) in the control than in NoP conditions (Table 4 and Figure 5B). Finally, on the bottom part of the plot, accessions mu\_esp, mex\_pas, sp\_11814 and sp\_bola were positively correlated with changes in TAD and PER and high values of PUtE, indicating a tendency to reduce their roots' average diameter while maintaining the shoot [P] concentration (Table 4 and Figure 5B).

**Figure 5.** PCA based on trait increments between treatments for the Trial 2 experiment. (**A**) Correlation between traits and the first two principal components. (**B**) Distribution of accessions based on the studied traits. P tissue concentration traits [P]Shoot, P total plant content (PTP) trait, efficiency parameters PPUE (physiological P use efficiency), PER (P efficiency ratio), PUpE (P uptake efficiency) and PUtE (P utilization efficiency) and morphometric traits RW (root dry weight), LRW (lateral root dry weight), RHW (root hairs dry weight), SW (shoot dry weight), BW (total biomass dry weight), R/S (root to shoot ratio), RTL (root total length), TAD (root total average diameter), RHW% (root hairs dry weight %), PFR (proportion of length dedicated to fine roots) and RSL (root specific length) were considered.

#### **4. Discussion**

#### *4.1. Peppers Change Their Mineral Homeostasis and re-Allocate Their P Reserves to Adjust to Low-P Conditions*

A comparison of P (root, shoot and fruit in Trial 1 and just shoot in Trial 2) concentrations provided relevant information on the impact of the different levels of P on pepper. There is evidence to suggest that pepper plant organs require P in different amounts, and the minimum levels are drastically different between tissues. Regarding that, roots presented the highest drop of P concentrations between treatments, indicating that they are able to mobilize P in order to benefit above-ground biomass. This response has been described in other crops, in which physiological and morphological changes, such as changes in root porosity and aerenchyma proportion, have been reported as mechanisms for reducing both the metabolic expenses and P requirements of the root system, while maintaining the foraging ability [15,22,39]. Interestingly, there were also differences among genotypes on P-tissue allocation, which opens the door to breeding materials with minimal P levels in the fruits and less need for fertilization without hampering production. For instance, some authors believe that we consume more P than required for a healthy diet, and often in the form of phytate, which is not fully absorbed by the human digestive system [40,41].

Homeostatic processes by which plants take up, transport and store nutrients are not independent, and therefore, the absence or excess of some elements can affect how the rest are processed, as was observed herein [6,38,39]. However, despite some significant differences between treatments for other macro minerals and tissue combinations, the values observed for this experiment are within the normal range, and therefore, no deficiency or excess was detected apart from P [6,42].

#### *4.2. P E*ffi*ciency Parameters Measure Di*ff*erent Aspects of the Plant Response*

The use of parameters to describe a plant's mineral uptake and use efficiency is a widely adopted practice in this scientific field [18,21]. Thus, physiological P use efficiency (PPUE) provides information on how productive a genotype may be, based on its tissues P concentration under a specific treatment; hence, high values indicate higher efficiency transforming absorbed P into biomass. Under these conditions, accessions mex\_pas (control) and bol\_144 (NoP) presented the highest PPUE for Trial 1, whereas in Trial 2, usa\_sandia and fra\_DLL presented the highest values for control and NoP, respectively. These results indicate a differential response, making these accessions interesting candidates for different P-fertilizers input conditions (e.g., high and low). Interestingly, the general response of increasing PPUE from control to NoP was not observed for trial 2. It is important to point out that although it is the same parameter, it was calculated in a different way depending on the trial. For Trial 1, concentration of P was a mean of all plant tissues whereas for Trial 2 it was extrapolated from shoot only, which may have caused a behavior distortion. P efficiency ratio (PER), on the other hand, relates the amount of yielded biomass with the amount of accumulated P in the plant; thus, high values indicate a higher ability to generate biomass with less P. Thus, bol\_144 (Trial 1) and fra\_DLL (Trial 2) are extremely efficient genotypes, especially under low-input conditions. These results indicate an interesting ability to use every unit of absorbed P and convert it into biomass and suggest that aptitude should be used in low-input systems.

Regarding P uptake efficiency (PUpE), accessions mex\_scm and sp\_piq showed an above average performance in both trails, although in the Trial 2 both usa\_conq and usa\_sandia showed higher values. This indicates that these accessions responded well to fertilization and were able to take up high amounts of P when it is present. In terms of P utilization efficiency (PUtE), accessions mex\_pas and sp\_bola showed the highest values in both trials, indicating that they are able to use the absorbed P into biomass generation more efficiently than the rest of the accessions. Furthermore, genetic variation regarding P acquisition and use efficiency has been widely reported in soybean, maize, sunflower, brassica and melon [15,18,21,43,44]. However, to our knowledge, this is the first work that provides such information for pepper germplasm. Herein, a wide range of variability is reported regarding P efficiency parameters, as well as several combinations among them, offering numerous possibilities for breeding for improved P uptake and P use efficiency parameters (PUE). Several authors have reported independence between uptake and use efficiency, which enables the improvement of both as well as selecting materials with different purposes (e.g., high- and low-input environments) [12,18,21,44]. These results seem to point towards that idea, since both parameters were located separately in both trials' PCA.

#### *4.3. Modifications at Root Level*

Many species promote root instead of aerial growth in order to enhance foraging capability [15,17,21]. In this experiment, a loss of root mass was observed under NoP conditions; however, this reduction was lower than that of the aerial part. This resulted in an increased root to shoot ratio under NoP conditions compared to control plants. The results indicate that, apart from lower biomass accumulation and redistribution of it, there are important modifications, particularly at root level, that help the plant to cope with P-stress. This was also observed in previous works with other crops for P-starvation conditions [20].

Morphological adaptations to low P concentrations in the soil aim at enhancing P acquisition by enabling exploitation of a greater soil volume, as well as enhancing P uptake without significantly increasing metabolic costs [17,18,45,46]. This is achieved mainly by the stimulation of root hairs [15,18,45], by halting secondary growth of the root and promoting primary growth and elongation [46] or increasing porosity and aerenchyma in roots [22]. Herein, lateral root length (LRL), but not total root length (RTL), increased under NoP conditions. It seems that lateral root elongation was a key response of the plant to reach possible P patches in the soil. This response has been described as an adaptive response to low P in *Phaseolus vulgaris* [46]. Other parameters, such as the lateral root specific length (LRSL), root specific length (RSL), percentage of fine roots (PFR) and percentage of fine lateral roots (PFLR), were higher under NoP, whereas the LRAD was lower. Therefore, pepper genotypes react to low P by producing thinner and lighter roots (with less carbon cost), which is in concordance with the literature [15,18,45,47]. On that regard, bol\_144 (Trial 1) and mex\_ng (Trial 2) stood out for their significant reduction of root average diameter while increasing the proportion of length dedicated to thinner roots under NoP conditions. In addition, accessions such as mu\_esp and sp\_bola showed a significant stimulation of their root specific length and proportion of length dedicated to thinner roots under the NoP conditions, despite presenting a lower root weight than under control conditions.

Although the percentage of root hair weight (RHW%) decreased in Trial 2, and was not significantly different in Trial 1, it must be pointed out that this measure includes fine roots and not specifically root hairs; therefore, it must be investigated if root hairs are modified in pepper under contrasting P conditions. Analyzing roots is a difficult task, and specific protocols must be set up to increase accuracy of root traits' study. The differences regarding root scanning and the analysis procedure between trials indicate that the first methodology (scanning just lateral roots) was more effective in finding root responses, since scanning all the fine roots has technical limitations.

#### *4.4. A Wide Range of Responses to Breed E*ffi*cient Genotypes*

Despite the general responses of pepper to low P described in the previous section, there was a wide range of responses depending on the accession studied. PCA's projection showed a widely differentiated behavior among accessions, creating several accession clusters depending on their overall response to NoP. For example, sp\_piq, mex\_scm, usa\_sandia, usa\_conquistador and mex\_ng showed high PUpE values associated with increases in root to shoot ratio and root specific length. Sp\_bola, mex\_pas and mu\_esp were associated with high PUtE values, no changes in their concentration of P in the shoots, reduction of the root diameter and an increase of percentage of fine roots and root total length. On the other hand, there were accessions that were poorly responsive to the changes in P levels, such as bol\_37 and eq\_973, or sp\_lam, fra\_DLL or usa\_jap. Results indicated that some accessions were more suited to grow under low input conditions (bol\_144, eq\_973 and usa\_jap) and others were highly responsive to increasing amounts of P available in the soil (sp\_piq, sp\_pas and mu\_esp). It was also observed that P uptake efficiency and P utilization efficiency seem to be controlled independently, and here, this is demonstrated by the positioning of both parameters in opposite quadrants of the PCAs' second component, and accessions with contrasting levels.

On that matter, the availability of diversity is of paramount importance for crop breeding, enabling the combination of several favorable traits or behaviors in a single genotype, which in return can be a more effective solution than to have those traits in separate genotypes. For example, Miguel et al. [48] demonstrated, in common bean, that combining shallow basal roots and long root hairs yielded a larger effect regarding P acquisition than their additive effects separately. Breeding for efficient genotypes needs an accurate definition of the target to be improved; this is not the same as improving the ability to grow under low inputs than reacting favorably to P addition. Defining the best ideotype to each condition and the combination of different adaptation opens the possibility to breed towards different goals [12,18,21,44].

#### **5. Conclusions**

Herein, a diverse collection of 25 pepper accessions has been characterized for their behavior under P low-input conditions. A considerable amount of diversity has been reported for the response to phosphorus low-input conditions for several phosphorus uptake and use efficiency parameters, and root and biomass traits. Evidence suggests that P low-input conditions play an important role in the plant's tissues allocation for this mineral and that different organs show different critical levels of phosphorus. In addition, the responses of this collection indicate the existence of genetic diversity, which may be used in breeding programs to generate materials with different applications. Accessions bol\_144 and fra\_DLL showed promising results for low-input conditions, whereas mex\_scm, sp\_piq, usa\_conq and usa\_sandia were on the opposite spectrum and are probably best used under high-input conditions due to their uptake efficiency. In addition, mex\_pas and sp\_bola showed the best results regarding P use efficiency. Finally, P low-input conditions proved to be an important factor controlling root morphology. Under these conditions, roots presented longer and thinner roots. These traits correlated to a higher efficiency and biomass accumulation under P-starving conditions. This work provides relevant first insights into pepper's response to phosphorus low-input conditions. More works are needed in order to dissect the mechanisms controlling the response, and consequently, to be introgressed into new materials.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2073-4395/10/5/637/s1, Table S1: Ion concentrations for irrigation water, Control and NoP solutions used in both Trial 1 and Trial 2. Table S2: Effect of Control and NoP treatments on P, K, Ca, Mg, Na and S (g/100g DW) concentrations for root, shoot and fruit tissues for Trial 1. Overall mean values, standard deviation and *p*-value for each plant tissue and treatment are provided. Table S3: Trial 1 multi-factor ANOVA's mean square values of accession and treatment effects, their interaction, and error for P concentration traits [P]Root, [P]Shoot, [P]Fruit, P content traits RootP (g P), ShootP (g P), FruitP (g P), PTP (mg P), P efficiency parameters PPUE (g2 DW g−<sup>1</sup> P) and PER (g DW g−<sup>1</sup> P) and for morphometric traits RW (g), LRW (g), RHW(g), SW (g), BW (g), R/S, LRL (m), LRAD (mm), RHW% (%), PLFR (%) and LRSL (m/g). Table S4: Trial 1 mean values and standard deviation for P accumulation and efficiency traits and parameters, and biomass and root traits and parameters. Table S5: Trial 2 multi-factor ANOVA's mean square values of accession (A) and treatment (T) effects, their interaction and error (E) for P concentration trait [P]Shoot, P content trait PTP (mg P), for efficiency parameters PPUE (g2 DW g−<sup>1</sup> P) and PER (g DW g−<sup>1</sup> P) and for morphometric traits RW (g), LRW (g), RHW (g), SW (g), BW (g), R/S, RTL (m), TAD (mm), RHW%, PFR (%) and RSL (m/g). Table S6: Trial 2 mean values and standard deviation for P accumulation and efficiency traits and parameters, and biomass and root traits and parameters.

**Author Contributions:** Conceptualization, methodology and validation: A.F., Á.C. and A.R.-B.; Data curation: L.P.-D. and D.G.-V.; Formal analysis and investigation: L.P.-D., D.G.-V., V.C.-Z. and A.Q.; Resources, funding acquisition and project administration: A.F. and Á.C.; Writing–original draft: L.P.-D. and A.F.; Writing—review and editing: L.P.-D., D.G.-V., V.C.-Z., A.Q., Á.C., A.R.-B. and A.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by FEDER-Funds and INIA, grant number RTA2013-00022-C02-02. The APC was self-funded.

**Acknowledgments:** Authors thank seed providers included in Table 1, such as P.W. Bosland, François Jourdan and the different Regulatory Boards of the PDOs and GPIs included in this study. Additionally, we want to thank Jose J. Luna for his advice on Mexican peppers.

**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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