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Article

Effect of Row Spacing on Quinoa (Chenopodium quinoa) Growth, Yield, and Grain Quality under a Mediterranean Climate

1
Northern Agriculture R&D, MIGAL—Galilee Research Institute, Kiryat Shmona P.O. Box 831, Israel
2
The Volcani Center, Institute of Plant Sciences, Agricultural Research Organization, Rishon LeZion P.O. Box 15159, Israel
*
Author to whom correspondence should be addressed.
Agriculture 2022, 12(9), 1298; https://doi.org/10.3390/agriculture12091298
Submission received: 31 July 2022 / Revised: 16 August 2022 / Accepted: 22 August 2022 / Published: 24 August 2022
(This article belongs to the Section Crop Production)

Abstract

:
Quinoa (Chenopodium quinoa Willd., Amaranthaceae) is an environmental stress-resilient crop of increasing global importance. Sowing density is a critical factor in the quinoa cultivation protocol. We evaluated the row-spacing effect on quinoa growth, yield, and grain quality under Mediterranean conditions. We hypothesized that lower row spacing would reduce quinoa stem diameter and increase yield but may reduce grain quality. Two quinoa accessions were sown in northern Israel with 16, 26, or 80 cm between rows during two consecutive years, in November and January each year. Plant density at harvest ranged from 22 to 260 plants m−2. Plant height and stem diameter ranged from 77 to 126 and 6.3 to 10.5 cm, respectively. Hay, grain, and straw yield ranged from 2259 to 17,979, 1604 to 4266, and 1212 to 3660 kg DM ha−1, respectively. Grain protein content (PC) ranged from 5.2 to 14.2 and thousand grain weight (TGW) from 2033 to 3446 mg. Plant density, hay, grain, and straw yield were negatively correlated to row spacing. Stem diameter was positively correlated to row spacing, while there were no correlations between this parameter and plant height, grain PC, or TGW. Results indicated that 16 cm between rows may be optimal, as this produced the greatest yields with no effect on grain quality. However, as it may result in plant lodging, 26 cm row spacing should also be considered. The effects of additional management-related parameters on quinoa production should be examined.

1. Introduction

Quinoa (Chenopodium quinoa Willd., Amaranthaceae) is an environmental stress-resilient crop plant native to the South American Andean Plateau [1]. The plant is well-known for its dry seeds (grains), which are consumed as a pseudo-cereal grain [2]. Quinoa grains are commonly used for human consumption and are considered the most edible part of the quinoa plant. The grains are recognized as ‘functional food’. They are rich in high-quality proteins, lipids, and carbohydrates, are gluten-free, and have an extraordinary balance of all essential amino acids [3,4,5,6]. Quinoa grains are also rich in micronutrients, such as vitamins and minerals, and contain bioactive compounds that exhibit antioxidant properties [7,8]. In light of these nutritional advantages for human consumption, the United Nations Food and Agriculture Organization (FAO) has recognized quinoa as significant in world food security and declared 2013 as the International Year of Quinoa (www.fao.org). Due to its remarkable nutritional value, market development, research, and promotion, the quinoa plant has gained global importance [1,9]. It is also important to note that climate change is expected to result in increasing frequency of extreme heat waves, especially under a Mediterranean climate, which may have negative impacts on global food production [10,11]. As quinoa has an exceptional tolerance to abiotic stresses and is highly nutritious, it can be an essential crop for food security [3]. Thanks to its high levels of genetic diversity, quinoa can grow in diverse agro-ecological regions and in recent years, it has been cultivated in many countries outside the Andean region [2,9,12,13].
Besides the use of quinoa grains for human consumption, other parts of the plant have also been examined for their use as forage for livestock feed. Several studies have reported that quinoa hay is of high quality, as it combines high protein content (PC) with a high level of digestibility [14,15,16]. For example, Ramos and Cruz [15] reported that quinoa’s aerial parts at 18.9% dry matter (DM) contained 26.3% crude fiber and 23.8% crude protein. Thus, they suggested that quinoa hay can improve livestock feed quality. Darwinkel [17] showed that ensiled quinoa may be used as a valuable forage for dairy farms, resulting in high milk yield and quality. Another study showed quinoa hay CP content and DM digestibility of 13–22% and 63–69%, respectively, both at desired feed levels [18]. In addition, quinoa contains bitter saponin compounds, which may reduce ruminal methane production [19] because they inhibit ruminal fungal and bacterial species and limit the H2 availability for rumen methanogenesis [20,21]. Thus, using quinoa for cattle feed may also reduce methane production. One of the consequences of the worldwide expansion of quinoa cultivation is the residual straw left as waste in the fields after grain harvest. Using quinoa straw for animal feed may overcome this problem [22,23,24].
In a previous study, conducted over two consecutive years in northern Israel, we investigated the potential of quinoa cultivation as a dual-purpose crop for grain production and livestock fodder [22]. We suggested that high quinoa hay biomass and quality, as well as high grain yield, offer strong prospects for quinoa cultivation in Israel and other regions with a semi-arid climate. We further suggested a novel whole-use approach using quinoa residual straw for cattle feed. However, grain-quality parameters such as grain PC and grain size, which are important marketing parameters [25,26], were not examined.
The main producers of quinoa grains are Bolivia and Peru. The harvested quinoa area in 2020 stood at 115,973 and 67,638 ha and the average grain yield at 605 and 1480 kg ha−1, in Bolivia and Peru, respectively (www.fao.org, accessed on 15 August 2022). In the past decade, quinoa cultivation has been introduced to more than 95 countries [12]. Thus, for additional farmers to adopt this underutilized crop, further agro-technical studies must be conducted to introduce quinoa cultivation and improve its growth and yield [27]. Sowing density is a critical factor in the success of commercial cultivation of quinoa, as well as other commercial field crops [28]. There is no strict protocol for row spacing in quinoa and in the last few years, studies have examined the effects of this parameter in quinoa with varying results [25,28,29,30,31]. We therefore evaluated the row-spacing effect on various parameters of quinoa growth, yield, and grain quality under Mediterranean conditions. As quinoa can be produced for both food and feed [22], we examined parameters relevant to both purposes. In our previous study, quinoa was grown at an inter-row spacing of 26 cm. In this study, we examined inter-row spacings of 16, 26, and 80 cm, corresponding to an equal distribution of 6, 4, and 2 sowing lines on a single flowerbed. This study hypothesized that lower row spacing would reduce quinoa stem diameter and increase yield, but higher row spacing would improve overall grain quality.

2. Materials and Methods

2.1. Experimental Site

The experiments were conducted from November 2018 to May 2020 in northern Israel [22] (at the Avnei-Eitan research farm, altitude 375 masl, 32°81′64″ N 35°76′28″ E). The experimental site soil is of basaltic origin composed of 60% clay, 35% silt, and 5% sand with pH = 7.6. The climate is Mediterranean, with a long-term annual average rainfall of 500–550 mm, mostly distributed between October to June. Most of the total precipitation during the experimental season of 2018 to 2019 occurred before March 2019, and air temperature ranged from 2.3 °C in January to 37.1 °C in June. Total precipitation during the growing season of 2019 to 2020 was very similar, but more than 60% of the rain occurred in December 2019 and January 2020. During this season, air temperature ranged from 0.4 °C in February to 40.9 °C in May (Table 1).

2.2. Plant Material and Experimental Design

Two commercial quinoa accessions were used in the experiments: ‘Mint Vanilla’ (accession 3) and accession 4E were obtained from ‘Wild Garden Seed’ (Philomath, OR, USA) and ‘Equinom’ Ltd. (Givat Brenner, Israel), respectively. Both accessions had a germination rate of approximately 95%. In all experiments, flowerbeds were prepared after cultivation and rolling. Seeds were sown into two, four, or six rows (80, 26, or 16 cm between rows, respectively) at an intra-row density of 40–50 seeds m−1 using a manual seeder. Quinoa accessions were sown into four 32 m2 (20 m long × 1.6 m wide) plots (repeats) in mid-November 2018 and 2019 and mid-January 2019 and 2020. Plots were randomized on each sowing date. A single irrigation using sprinklers at a rate of 100 m3 ha−1 was applied only in plots that did not receive rain within three days after sowing. All plots were manually weeded once during cultivation. The plots were fertilized by ~150 kg nitrogen ha−1 as urea (46%N).

2.3. Plant Measurements

To determine plant height and stem diameter, plants were measured after reaching maximum height, ~150 and ~110 days after sowing in November and January, respectively. Stem diameter was measured using a manual caliper. At least 10 plants were selected randomly and measured for each plot (repeat). To determine actual plant density at harvest, plants were counted in a representative 1 m2 area in each plot. The means of each treatment were calculated from the means of each plot.

2.4. Determination of Hay, Grain, and Straw Yield

When the plants reached 28–32% DM, representative samples of 1 m2 from each plot were hand-harvested ~5 cm above the ground and weighed for hay green yield. To determine hay %DM, representative samples were collected and weighed before and after drying at 60 °C for 48 h. Hay DM yield was calculated as hay green yield × hay %DM. To determine the grain yield of each plot, ripened mature plants were harvested and threshed using an experimental-scale combine. After that, the straw left in the field was collected by hand and weighed to determine straw yield.

2.5. Grain Quality Analyses

Grain PC was determined at the field service laboratory in Neve Yaar, Israel, using the Kjeldahl method [32]. To determine thousand grain weight (TGW), 300 grains of each sample were manually counted and weighed. Then the 300 grains’ weight (mg) was multiplied by 3.33 to achieve TGW.

2.6. Statistical Analysis

Results were subjected to one-way analysis of variance (ANOVA) followed by Tukey’s HSD test using JMP software version 11.0.0 (SAS Institute, Cary, NC, USA). Results were also subjected to a two-tailed Pearson correlation matrix using the ‘corrplot’ package in RStudio (Boston, MA, USA), in R programming language.

3. Results

3.1. Plant Density

In plots sown in November 2018, plant density at harvest (plant density) ranged from 22 to 255 plants m−2 (Table 2, Figure S1). For accession 3, plots with different row spacings had significantly (p < 0.05) different plant densities. However, for accession 4E, there were no differences (p > 0.05) between plant densities of plots sown at 26 and 80 cm between rows. In plots sown in November 2019, plant density ranged from 40 to 260 plants m−2 (Table 3, Figure S1). For both accessions, plots with different row spacings had significantly (p < 0.05) different plant densities. In plots sown in January 2019, plant density ranged from 35 to 259 plants m−2 (Table 4, Figure S1). However, differences in plant density between plots with different row spacings were less obvious. For accession 3, there were no differences (p > 0.05) between plots sown at 16 and 26 cm between rows. For accession 4E, there were no differences (p > 0.05) between the different treatments. In plots sown in January 2020, plant density ranged from 80 to 246 plants m−2 (Table 5, Figure S1). For both accessions, plant density was significantly greater (p < 0.05) in plots that were sown with 16 cm between rows compared to plots that were sown with 80 cm between rows. F-test analysis showed that on all sowing dates except January 2020, accession had a significant effect on plant density. In addition, row spacing had a significant effect on plant density on all sowing dates (Table 2, Table 3, Table 4 and Table 5).

3.2. Plant Height

In plots sown in November 2018, maximum plant height ranged from 78 to 87 cm and was very similar to that of plots sown in November 2019 (77–91 cm; Table 2 and Table 3, Figure S1). In plots sown in January 2019 and January 2020, maximum plant height ranged from 90 to 106 cm and 111 to 126 cm, respectively (Table 4 and Table 5, Figure S1). There were no significant differences (p > 0.05) in maximum plant height between the different accessions sown in the different row spacings on any one sowing date. F-test analysis showed that accession did not have a significant effect on plant height. This was also the case with row spacing, except for the November 2019 sowing date (Table 2, Table 3, Table 4 and Table 5).

3.3. Stem Diameter

In plots sown in November 2018, the maximum stem diameter ranged from 6.4 to 10.5 mm (Table 2, Figure S1). In both accessions, stem diameter was significantly greater (p < 0.05) in plants that were sown at 80 cm between rows compared to plants that were sown at 16 cm between rows. The maximum stem diameter in plots sown in November 2019 was very similar to that of the previous year (6.8–10.3 mm; Table 3, Figure S1). For accession 4E, stem diameter was significantly greater (p < 0.05) in plants that were sown at 80 cm between rows compared to plants that were sown at 26 or 16 cm between rows. For accession 3, stem diameter was only significantly greater (p < 0.05) in plants that were sown at 80 cm between rows compared to 16 cm. In plots sown in January 2019 and January 2020, maximum stem diameter ranged from 7.8 to 9.4 mm and 6.3 to 8.4 mm, respectively (Table 4 and Table 5, Figure S1). There were no differences (p > 0.05) between maximum stem diameters in the different treatments on either sowing date. F-test analysis showed that accession did not have a significant effect on stem diameter, except on the November 2019 sowing date. Row spacing had a significant effect on this parameter only for the November 2018 and November 2019 sowing dates (Table 2, Table 3, Table 4 and Table 5).

3.4. Hay Yield

In plots sown in November 2018, hay DM yield ranged from 2306 to 9037 kg DM ha−1 (Table 2, Figure S2). For both accessions, hay DM yield was significantly greater (p < 0.05) in plots sown at 16 or 26 cm between rows compared to 80 cm between rows. Hay DM yield in plots sown in November 2019 ranged from 5149 to 11,100 kg DM ha−1 (Table 3, Figure S2). On this sowing date as well, hay DM yield was significantly greater (p < 0.05) in plots that were sown at 16 or 26 cm between rows compared to 80 cm, but only for accession 3. For accession 4E, there was no difference (p > 0.05) in hay DM yield between the different treatments. In plots sown in January 2019 and 2020, hay DM yield ranged from 5574 to 13,586 kg DM ha−1 and 6773 to 17,979, respectively (Table 4 and Table 5, Figure S2). Similar to the results from the November sowing dates, hay DM yield in quinoa sown in January was significantly lower (p < 0.05) in plots that were sown at 80 cm between rows compared to those sown at 16 or 26 cm between rows. Moreover, there were no differences (p > 0.05) in hay DM yield between plots sown at 16 or 26 cm between rows for any of the experiments during 2018–2020. Furthermore, there were no differences (p > 0.05) in hay DM yield between accessions for plots sown at similar spacing in any of the experiments. F-test analysis showed that accession did not have a significant effect on hay yield, except on the November 2018 sowing date. Row spacing had a significant effect on this parameter on all sowing dates (Table 2, Table 3, Table 4 and Table 5).

3.5. Grain Yield

In plots sown in November 2018, grain yield ranged from 1958 to 4266 kg ha−1 (Table 2, Figure S2). For accession 3, grain yield was only significantly greater (p < 0.05) in plots sown at 26 cm between rows compared to 80 cm between rows. For accession 4E, grain yield was only significantly greater (p < 0.05) in plots sown at 16 cm between rows compared to 80 cm between rows. In plots sown in November 2019, grain yield ranged from 1827 to 3501 kg ha−1 (Table 3, Figure S2). There were no differences (p > 0.05) in grain yield between the three row spacings for either accession. However, grain yield for accession 4E sown at 16 or 26 cm between rows was significantly greater (p < 0.05) than that for plots of accession 3 sown at 80 cm between rows. In plots sown in January 2019 and 2020, grain yield ranged from 1604 to 3635 kg ha−1 and 1704 to 3299 kg ha−1, respectively (Table 4 and Table 5, Figure S2). For January 2019, in both accessions, grain yield was significantly lower (p < 0.05) in plots sown at 80 cm between rows compared to plots sown at 16 or 26 cm between rows. For January 2020, in both accessions, grain yield was only significantly lower (p < 0.05) in plots that were sown at 80 cm compared to 16 cm between rows. F-test analysis showed a significant effect of accession on grain yield only on the November 2019 and January 2020 sowing dates. Row spacing had a significant effect on this parameter on all sowing dates (Table 2, Table 3, Table 4 and Table 5).

3.6. Straw Yield

In plots sown in November 2018, quinoa straw yield ranged from 1275 to 3214 kg DM ha−1 (Table 2, Figure S2). For both accessions, the straw yield was significantly greater (p < 0.05) in plots that were sown at 16 cm between rows compared to 80 cm between rows. For accession 3, straw yield did not differ significantly (p < 0.05) in plots sown at 16 and 26 cm between rows. For accession 4E, straw yield did not differ (p > 0.05) in plots sown at 26 cm compared to 80 cm between rows. In plots sown in November 2019, straw yield ranged from 1398 to 3205 kg DM ha−1 (Table 3, Figure S2). For both accessions, the straw yield was significantly greater (p < 0.05) in plots sown at 16 or 26 cm between rows compared to 80 cm between rows. In plots sown in January 2019 and 2020, the straw yield ranged from 1212 to 3660 kg DM ha−1 and 1496 to 3187 kg DM ha−1, respectively (Table 4 and Table 5, Figure S2). In plots sown in January 2019, for both accessions, the straw yield was only significantly greater (p < 0.05) in plots sown at 16 cm between rows compared to 80 cm between rows. In contrast, in plots sown in January 2020, there was no difference (p > 0.05) in straw yield between the different treatments for each accession. Moreover, there were no differences (p > 0.05) in straw yield of plots sown at similar spacings in any of the experiments for either accession. F-test analysis showed that accession only had a significant effect on straw yield on the November 2019 and January 2020 sowing dates. Row spacing had a significant effect on this parameter on all sowing dates (Table 2, Table 3, Table 4 and Table 5).

3.7. Grain PC

In plots sown in November 2018 and 2019, grain PC ranged from 11.7 to 14.2% and 9.9 to 14.1%, respectively. No differences (p > 0.05) were observed between the different treatments (Table 2, Table 3 and Figure S3). In plots sown in January 2019, grain PC ranged from only 5.2 to 6.1% (Table 4, Figure S3). Grain PC in accession 4E sown at 26 cm between rows was only significantly greater (p < 0.05) than that of accession 3 sown with a similar row spacing. In plots sown in January 2020, grain PC ranged from 7.2 to 12.6% (Table 5, Figure S3). Grain PC was significantly greater (p < 0.05) in accession 4E sown at 80 cm between rows than in accession 3 plots sown at 16 or 26 cm between rows. F-test analysis showed that accession had a significant effect on grain PC on all sowing dates except November 2018. It also showed an inconsistent effect of row spacing on grain PC, with a significant effect on this parameter only on the November 2018 and January 2020 sowing dates (Table 2, Table 3, Table 4 and Table 5).

3.8. TGW

In plots sown in November 2018, TGW ranged from 3099 to 3446 mg, with no difference (p > 0.05) between the different treatments (Table 2, Figure S3). In plots sown in November 2019, TGW ranged from 2768 to 3312 mg (Table 3, Figure S3). Only TGW for accession 3 sown at 80 cm between rows was significantly greater (p < 0.05) than that of all plots of accession 4E. In plots sown in January 2019, quinoa TGW ranged between only 2324 and 2592 mg (Table 4, Figure S3). Only TGW for accession 3 sown at 26 cm between rows was significantly greater (p < 0.05) than that for accession 4E sown at 26 or 80 cm between rows. In plots sown in January 2020, TGW ranged from 2033 to 2588 mg (Table 5, Figure S3). TGW was significantly lower (p < 0.05) for accession 4E sown at 80 cm between rows compared to all plots of accession 3. F-test analysis showed a significant effect of accession on TGW on all sowing dates except November 2019. Row spacing did not influence this parameter on any sowing date except January 2019 (Table 2, Table 3, Table 4 and Table 5).

3.9. Correlations between Traits

Of the 36 correlation coefficients evaluated, 24 exhibited significant values (p < 0.05; Figure 1a,b). Row spacing was negatively correlated to plant density, hay yield, grain yield, and straw yield. It was only positively correlated to stem diameter, and no correlations were found between this parameter and plant height or grain-quality parameters (Figure 1a). The opposite trend was found for the correlations with plant density, which was positively correlated to hay, grain, and straw yield, and negatively correlated to stem diameter (Figure 1a). Hay yield was positively correlated to grain yield, straw yield, and plant height, and negatively correlated to stem diameter, PC, and TGW. Grain yield was positively correlated to straw yield, and negatively correlated to plant height and stem diameter. Straw yield was negatively correlated to stem diameter and TGW. Plant height was negatively correlated to PC and TGW. Stem diameter was positively correlated to TGW, as was PC (Figure 1a).

4. Discussion

Our previous study showed considerable potential for cultivating quinoa in Israel, as well as other Mediterranean regions during the winter [22]. To study the effect of row spacing on growth, yield, and grain quality, quinoa plots from the two highest-yielding accessions in that previous study were sown with different row spacings on two winter dates, over two consecutive years.

4.1. Effect of Row Spacing on Yield Parameters

All of the yield parameters were negatively correlated to row spacing, and positively correlated to plant density (Figure 1). However, in most cases, there were no significant differences in yield parameters between the 16 and 26 cm row-spacing treatments, whereas the 80 cm row-spacing treatment differed significantly from the 16 cm one (Table 2, Table 3, Table 4, Table 5, Figure S2). These results have an important applied aspect for commercial growers as the use of fewer seeds per unit area might reduce crop costs. However, as the stems become thicker, the quality of forage plants decreases, and the 16 cm row spacing might be the most beneficial for producing high-quality quinoa hay and straw for animal feed [33]. This notion should be examined in future studies.
Other studies have shown an increase in quinoa grain yield with lower row spacing. For example, Sief et al. [30] obtained the highest quinoa grain yield with 20 cm inter-row spacing, compared to 30 or 40 cm. Yet another study showed that 30 cm row-spacing treatment produces higher quinoa grain yield than 40 and 50 cm row-spacing treatments [34]. In contrast, a study conducted in Brazil, showed no change in quinoa grain yield with increasing plant density [28]. However, the maximum examined plant density was only 70 plant m−2, which might explain the difference from our results. It was also reported that plots with 25 or 12.5 cm row spacing give a lower yield than plots with a row spacing of 50 cm [35]. This might be explained by the fact that only plots with the highest row density were hoed for weeding purposes, thus reducing competition with weeds for resources. It should be noted that while grain yield per unit area can increase with increasing plant density, grain yield per plant may be decreased. Wang et al. [36] suggested that the reduction in quinoa grain yield per plant is due to competition for nutrients and light among individuals under high-density planting.
Although there is not much evidence of the effect of row spacing on quinoa hay or straw yield, in other plant species, increased yields have been shown with lower row spacing. For example, planting at 15 or 30 cm row spacing produced more intermediate wheatgrass hay and straw than 61 cm row spacing [37]. Another study showed that the forage yield of Hungarian vetch (Vicia pannonica Crantz) was significantly higher at 17.5 cm compared to 35 cm row spacing [38]. Notably, in our study, grain yield was positively correlated to straw yield. This may be beneficial to growers, as the residual straw following mechanical threshing for grain-production purposes may be used as animal feed, thereby increasing crop income [23,24].
There were no significant differences in hay, grain, or straw yield between the two accessions sown in the same row spacing (Table 2, Table 3, Table 4 and Table 5, Figure S2). Similar results were obtained in another study carried out in the same experimental location [22]. However, hay yield in accession 3 was generally higher than in accession 4E. An opposite trend was found in grain yield, as it was usually higher with accession 4E than in accession 3. Therefore, accession 3 is more suitable for cultivation in the experimental location when considering quinoa for hay production, while accession 4E is more suitable for cultivation when considering quinoa for grain production.

4.2. Effect of Row Spacing on Grain-Quality Parameters

Additional commercially important parameters are related to grain quality. In this study, grain PC was not correlated to either row spacing or plant density (Figure 1). Different results were found in a study carried out in Egypt, where grain PC was significantly higher in quinoa plants grown under low plant density compared to high plant density [31]. In another study, grain PC gradually increased with widening interspaces between rows, from 20 to 40 cm [30]. In contrast, in a different study conducted in Turkey, different row spacings of 20, 40, or 60 cm did not affect quinoa grain PC [39]. As already noted, the different results may be attributed to differences in quinoa genotype, environmental conditions, or management practices. Our results also showed that TGW was not correlated to row spacing. Additional studies support this notion, reporting no change in quinoa TGW under different row spacings or plant densities [28,30,36].
In most cases, there were no significant differences in PC between the two accessions sown in the same row spacing (Table 2, Table 3, Table 4, Table 5, Figure S3). However, PC in accession 4E was generally higher than in accession 3. An opposite trend was found in the TGW parameter, as it was usually higher with accession 3 than in accession 4E. Therefore, accession 4E is more suitable for cultivation in the experimental location when considering PC as the primary quality parameter. However, when TGW is considered the primary quality parameter, accession 3 may perform better than accession 4E.

4.3. Effect of Row Spacing on Plant Growth Parameters

Plant density was negatively correlated to row spacing (Figure 1). This is not surprising, as fewer seeds per unit area were sown in plots with higher row spacing compared to lower row spacing. Indeed, it had been reported that increasing sowing rate increases quinoa plant population density [29]. It should be noted that in a few cases in the current study, there were no differences in plant density between the different row-spacing treatments (Table 4, Figure S1). This might be attributed to the abortion of seedling development due to biotic or abiotic stress conditions [40,41]. Stem diameter was negatively correlated to row spacing and positively correlated to plant density (Figure 1). This aligns with our research hypothesis, as higher plant density may lead to higher competition for sunlight and nutrients, resulting in lower stem diameter. Spehar and Rocha [28] also indicated that low population density in commercial quinoa plots increases stem diameter. Other studies have shown similar results, where corn and alfalfa stem diameter increased significantly with increasing within-row spacing and decreasing plant density [42,43]. It is important to note that stem diameter may have an inverse relationship with lodging, thus validating the importance of appropriate between-row spacing during commercial quinoa cultivation [42,44]. In contrast to stem diameter, there was no effect of either row spacing or plant density on plant height (Table 2, Table 3, Table 4 and Table 5, Figure 1 and Figure S1). Plant height might be expected to increase with plant density due to a shade-avoidance response [45,46]; nevertheless, a previous study on quinoa showed that this parameter is barely influenced by within-row sowing rate [29]. In another study, quinoa plant height and plant density were negatively correlated. The differences between the effects of row spacing and plant density on plant height in the different studies may be attributed to the range of these parameters examined in each study. It might also be attributed to other factors, such as genotype, environment, and management practices [47].

5. Conclusions

The results from this study indicate that row spacing has significant effects on quinoa yield parameters and therefore should be considered before commercial cultivation. The collected data confirm our hypothesis that lower row spacing reduces quinoa stem diameter and increases crop-yield parameters. However, lower row spacing did not improve overall grain quality. The results from this study suggest that 16 cm between rows might be the optimal row spacing, because it resulted in the greatest hay, grain, and straw yields, and did not negatively affect grain quality. However, because low row spacing resulted in low stem diameter, in some accessions this may cause plant lodging. In these cases, 26 cm row spacing should also be considered. As noted in Section 4, these conclusions are also supported by additional studies conducted worldwide. With the global expansion of quinoa cultivation, growing protocols should be established to help growers adopt this underutilized crop. These protocols should be adjusted to genotype, environment, management, and growing purposes (i.e., leaf and grain for human consumption, or hay and straw for animal feed). Therefore, additional studies should be conducted to examine the effects of lower and higher row spacings, as well as the effects of inter-row spacing on various quinoa parameters.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture12091298/s1, Figure S1: Effect of row spacing on growth parameters, Figure S2: Effect of row spacing on yield parameters, Figure S3: Effect of row spacing on grain quality parameters.

Author Contributions

Conceptualization, A.A. and L.R.; Formal analysis, A.A., S.G. and L.R.; Funding acquisition, A.A., S.G. and L.R.; Investigation, A.A. and L.R.; Methodology, A.A., R.D. and L.R.; Project administration, L.R.; Supervision, L.R.; Validation, A.A. and L.R.; Writing—original draft, A.A., S.G. and L.R.; Writing—review and editing, A.A., S.G. and L.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Israeli Ministry of Agriculture and Rural Development, grant no. 21-01-0018.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors wish to thank the Avnei-Eitan research team for the effort that they invested in this study, Yaron Lugasi for his assistance in the field measurements, and Shaul Graph and Itzik Abarbanel for their enlightening remarks.

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

  1. Bazile, D.; Bertero, H.D.; Nieto, C. State of the Art Report on Quinoa around the World—International Year of Quinoa 2013; FAO & CIRAD: Rome, Italy, 2015. [Google Scholar]
  2. Alandia, G.; Rodriguez, J.P.; Jacobsen, S.E.; Bazile, D.; Condori, B. Global Expansion of Quinoa and Challenges for the Andean Region. Glob. Food Secur. 2020, 26, 100429. [Google Scholar] [CrossRef]
  3. Jaikishun, S.; Li, W.; Yang, Z.; Song, S. Quinoa: In Perspective of Global Challenges. Agronomy 2019, 9, 176. [Google Scholar] [CrossRef]
  4. Navruz-Varli, S.; Sanlier, N. Nutritional and Health Benefits of Quinoa (Chenopodium Quinoa Willd.). J. Cereal Sci. 2016, 69, 371–376. [Google Scholar] [CrossRef]
  5. Ceyhun Sezgin, A.; Sanlier, N. A New Generation Plant for the Conventional Cuisine: Quinoa (Chenopodium Quinoa Willd.). Trends Food Sci. Technol. 2019, 86, 51–58. [Google Scholar] [CrossRef]
  6. Yeşil, S.; Levent, H. The Influence of Fermented Buckwheat, Quinoa and Amaranth Flour on Gluten-Free Bread Quality. LWT 2022, 160, 113301. [Google Scholar] [CrossRef]
  7. Aloisi, I.; Parrotta, L.; Ruiz, K.B.; Landi, C.; Bini, L.; Cai, G.; Biondi, S.; del Duca, S. New Insight into Quinoa Seed Quality under Salinity: Changes in Proteomic and Amino Acid Profiles, Phenolic Content, and Antioxidant Activity of Protein Extracts. Front. Plant Sci. 2016, 7, 656. [Google Scholar] [CrossRef]
  8. Brend, Y.; Galili, L.; Badani, H.; Hovav, R.; Galili, S. Total Phenolic Content and Antioxidant Activity of Red and Yellow Quinoa (Chenopodium Quinoa Willd.) Seeds as Affected by Baking and Cooking Conditions. Food Nutr. Sci. 2012, 3, 1150–1155. [Google Scholar] [CrossRef]
  9. De Ron, A.M.; Sparvoli, F.; Pueyo, J.J.; Bazile, D. Editorial: Protein Crops: Food and Feed for the Future. Front. Plant Sci. 2017, 8, 6–9. [Google Scholar] [CrossRef]
  10. Zandalinas, S.I.; Fritschi, F.B.; Mittler, R. Global Warming, Climate Change, and Environmental Pollution: Recipe for a Multifactorial Stress Combination Disaster. Trends Plant Sci. 2021, 26, 588–599. [Google Scholar] [CrossRef]
  11. Alon, E.; Shapira, O.; Azoulay-Shemer, T.; Rubinovich, L. Shading Nets Reduce Canopy Temperature and Improve Photosynthetic Performance in ‘Pinkerton’ Avocado Trees during Extreme Heat Events. Agronomy 2022, 12, 1360. [Google Scholar] [CrossRef]
  12. Bazile, D.; Jacobsen, S.-E.; Verniau, A. The Global Expansion of Quinoa: Trends and Limits. Front. Plant Sci. 2016, 7, 622. [Google Scholar] [CrossRef]
  13. Bazile, D.; Pulvento, C.; Verniau, A.; Al-Nusairi, M.S.; Ba, D.; Breidy, J.; Hassan, L.; Mohammed, M.I.; Mambetov, O.; Otambekova, M.; et al. Worldwide Evaluations of Quinoa: Preliminary Results from Post International Year of Quinoa FAO Projects in Nine Countries. Front. Plant Sci. 2016, 7, 850. [Google Scholar] [CrossRef]
  14. Peiretti, P.G.; Gai, F.; Tassone, S. Fatty Acid Profile and Nutritive Value of Quinoa (Chenopodium Quinoa Willd.) Seeds and Plants at Different Growth Stages. Anim. Feed Sci. Technol. 2013, 183, 56–61. [Google Scholar] [CrossRef]
  15. Ramos, N.; Cruz, A.M. Evaluation of Seven Seasonal Crops for Forage Production during the Dry Season in Cuba. Cuba. J. Agric. Sci. 2002, 36, 271–276. [Google Scholar]
  16. Ebeid, H.M.; Kholif, A.E.; El-Bordeny, N.; Chrenkova, M.; Mlynekova, Z.; Hansen, H.H. Nutritive Value of Quinoa (Chenopodium Quinoa) as a Feed for Ruminants: In Sacco Degradability and in Vitro Gas Production. Environ. Sci. Pollut. Res. 2022, 29, 35241–35252. [Google Scholar] [CrossRef]
  17. Darwinkel, A. Understanding the Quinoa Crop: Guidelines for Growing in Temperate Regions of N.W. Europe; EC: Brussels, Belgium, 1997. [Google Scholar]
  18. Van Schooten, H.; van Schooten, H.; Pinxterhuis, I. Quinoa as an Alternative Forage Crop in Organic Dairy Farming. Available online: https://www.wur.nl/nl/landingspagina-redacteuren/nl/onderzoek-resultaten/onderzoeksinstituten/livestock-research/show-wlr/handboek-kwantitatieve-informatie-veehouderij-kwin.htm (accessed on 28 June 2022).
  19. Tamminga, S.; Bannink, A.; Dijkstra, J.; Zom, R. Feeding Strategies to Reduce Methane Loss in Cattle; Animal Sciences Group: Wageningen, The Netherlands, 2007. [Google Scholar]
  20. Patra, A.K.; Saxena, J. The Effect and Mode of Action of Saponins on the Microbial Populations and Fermentation in the Rumen and Ruminant Production. Nutr. Res. Rev. 2009, 22, 204–219. [Google Scholar] [CrossRef]
  21. Bodas, R.; López, S.; Fernández, M.; García-González, R.; Rodríguez, A.B.; Wallace, R.J.; González, J.S. In Vitro Screening of the Potential of Numerous Plant Species as Antimethanogenic Feed Additives for Ruminants. Anim. Feed Sci. Technol. 2008, 145, 245–258. [Google Scholar] [CrossRef]
  22. Asher, A.; Galili, S.; Whitney, T.; Rubinovich, L. The Potential of Quinoa (Chenopodium Quinoa) Cultivation in Israel as a Dual-Purpose Crop for Grain Production and Livestock Feed. Sci. Hortic. 2020, 272, 109534. [Google Scholar] [CrossRef]
  23. Matías, J.; Cruz, V.; Reguera, M. Heat Stress Impact on Yield and Composition of Quinoa Straw under Mediterranean Field Conditions. Plants 2021, 10, 955. [Google Scholar] [CrossRef]
  24. Filik, G. Biodegradability of Quinoa Stalks: The Potential of Quinoa Stalks as a Forage Source or as Biomass for Energy Production. Fuel 2020, 266, 117064. [Google Scholar] [CrossRef]
  25. Eisa, S.S.; El-Samad, E.H.A.; Hussin, S.A.; Ali, E.A.; Ebrahim, M.; González, J.A.; Ordano, M.; Erazzú, L.E.; El-Bordeny, N.E.; Abdel-Ati, A.A. Quinoa in Egypt—Plant Density Effects on Seed Yield and Nutritional Quality in Marginal Regions. Middle East J. Appl. Sci. 2018, 8, 515–522. [Google Scholar]
  26. Bertero, H.D.; de La Vega, A.J.; Correa, G.; Jacobsen, S.E.; Mujica, A. Genotype and Genotype-by-Environment Interaction Effects for Grain Yield and Grain Size of Quinoa (Chenopodium Quinoa Willd.) as Revealed by Pattern Analysis of International Multi-Environment Trials. Field Crops Res. 2004, 89, 299–318. [Google Scholar] [CrossRef]
  27. Sellami, M.H.; Pulvento, C.; Lavini, A. Agronomic Practices and Performances of Quinoa under Field Conditions: A Systematic Review. Plants 2021, 10, 72. [Google Scholar] [CrossRef] [PubMed]
  28. Spehar, C.R.; da Rocha, J.E.S. Effect of Sowing Density on Plant Growth and Development of Quinoa, Genotype 4.5, in the Brazilian Savannah Highlands. Biosci. J. 2009, 25, 53–58. [Google Scholar]
  29. Risi, J.; Galwey, N.W. Effects of Sowing Date and Sowing Rate on Plant Development and Grain Yield of Quinoa (Chenopodium Quinoa) in a Temperate Environment. J. Agric. Sci. 1991, 117, 325–332. [Google Scholar] [CrossRef]
  30. Sief, A.S.; El-Deepah, H.R.A.; Kamel, A.S.M.; Ibrahim, J.F. Effect of Various Inter and Intra Spaces on the Yield and Quality of Quinoa (Chenopodium Quinoa Willd.). J. Plant Prod. Mansoura Univ. 2015, 6, 371–383. [Google Scholar] [CrossRef]
  31. Van Minh, N.; Hoang, D.T.; van Loc, N.; Long, N.V. Effects of Plant Density on Growth, Yield and Seed Quality of Quinoa Genotypes under Rain-Fed Conditions on Red Basalt Soil Regions. Aust. J. Crop Sci. 2020, 14, 1977–1982. [Google Scholar] [CrossRef]
  32. Baird, R.; Eaton, A.; Rice, E. (Eds.) 4500-Norg NITROGEN (ORGANIC). In Standard Methods for the Examination of Water and Wastewater; American Public Health Association: Washington, DC, USA, 2017; p. 498. [Google Scholar]
  33. Volenec, J.J.; Cherney, J.H.; Johnson, K.D. Yield Components, Plant Morphology, and Forage Quality of Alfalfa as Influenced by Plant Population. Crop Sci. 1987, 47907, 321–326. [Google Scholar] [CrossRef]
  34. Prommarak, S. Response of Quinoa to Emergence Test and Row Spacing in Chiang Mai-Lumphun Valley Lowland Area. Khon Kaen Agric. J. 2014, 42, 8–14. [Google Scholar]
  35. Jacobsen, S.E.; Stølen, O.; Jørgensen, I. Cultivation of Quinoa (Chenopodium Quinoa) under Temperate Climatic Conditions in Denmark. J. Agric. Sci. 1994, 122, 47–52. [Google Scholar] [CrossRef]
  36. Wang, N.; Wang, F.; Shock, C.C.; Meng, C.; Qiao, L. Effects of Management Practices on Quinoa Growth, Seed Yield, and Quality. Agronomy 2020, 10, 445. [Google Scholar] [CrossRef]
  37. Hunter, M.C.; Sheaffer, C.C.; Culman, S.W.; Lazarus, W.F.; Jungers, J.M. Effects of Defoliation and Row Spacing on Intermediate Wheatgrass II: Forage Yield and Economics. Agron. J. 2020, 112, 1862–1880. [Google Scholar] [CrossRef]
  38. Albayrak, S.; Türk, M.; Yüksel, O. Effect of Row Spacing and Seeding Rate on Hungarian Vetch Yield and Quality. Turk. J. Field Crops 2011, 16, 54–58. [Google Scholar]
  39. Zulkadir, G.; Çiftçi, S.; Selenay Gökçe, M.; Karaburu, E.; Bozdağ, E.; İdikut, L. The Effect of Row Distances on Quinoa Yield and Yield Components in The Effect of Row Distances on Quinoa Yield and Yield Components in the Late Planting Period. Int. J. Res. Publ. Rev. 2020, 1, 37–42. [Google Scholar]
  40. Bellalou, A.; Daklo-Keren, M.; Abu Aklin, W.; Sokolskaya, R.; Rubinovich, L.; Asher, A.; Galili, S. Germination of Chenopodium Quinoa Cv. ‘Mint Vanilla’ Seeds under Different Abiotic Stress Conditions. Seed Sci. Technol. 2022, 50, 41–45. [Google Scholar] [CrossRef]
  41. Bellalou, A.; Daklo-Keren, M.; Abu-Aklin, W.; Sadan, G.; Sokolskia, R.; Rubinovich, L.; Asher, A.; Londner, A.; Amir-Segev, O.; Farber, A.; et al. Influence of Sowing Date of Quinoa Mother Plants on Seed Germination (in Hebrew). Nir Vatelem 2020, 1–7. [Google Scholar]
  42. Zhang, T.; Wang, X.; Han, J.; Wang, Y.; Mao, P.; Majerus, M. Effects of Between-Row and within-Row Spacing on Alfalfa Seed Yields. Crop Sci. 2008, 48, 794–803. [Google Scholar] [CrossRef] [Green Version]
  43. Turgut, I.; Duman, A.; Bilgili, U.; Acikgoz Authorsõ, E. Alternate Row Spacing and Plant Density Effects on Forage and Dry Matter Yield of Corn Hybrids (Zea Mays L.). J. Agron. Crop Sci. 2005, 191, 146–151. [Google Scholar] [CrossRef]
  44. Sher, A.; Khan, A.; Ashraf, U.; Liu, H.H.; Li, J.C. Characterization of the Effect of Increased Plant Density on Canopy Morphology and Stalk Lodging Risk. Front. Plant Sci. 2018, 9, 1047. [Google Scholar] [CrossRef]
  45. Ruberti, I.; Sessa, G.; Ciolfi, A.; Possenti, M.; Carabelli, M.; Morelli, G. Plant Adaptation to Dynamically Changing Environment: The Shade Avoidance Response. Biotechnol. Adv. 2012, 30, 1047–1058. [Google Scholar] [CrossRef]
  46. Roig-Villanova, I.; Paulišić, S.; Martinez-Garcia, J.F. Shade Avoidance and Neighbor Detection. Methods Mol. Biol. 2019, 2026, 157–168. [Google Scholar] [CrossRef]
  47. Schwalbert, R.; Amado, T.J.C.; Horbe, T.A.N.; Stefanello, L.O.; Assefa, Y.; Prasad, P.V.V.; Rice, C.W.; Ciampitti, I.A. Corn Yield Response to Plant Density and Nitrogen: Spatial Models and Yield Distribution. Agron. J. 2018, 110, 970–982. [Google Scholar] [CrossRef]
Figure 1. Pearson’s correlation coefficients among plant density, growth, yield, and grain-quality parameters of quinoa. Blue and red colors represent positive and negative correlations, respectively. (a) Pearson’s correlation values. (b) Significance of Pearson’s correlation values (* p < 0.05, ** p < 0.01, *** p < 0.001). Colors reflect correlation values between every two variables. Each value represents measurements from 96 plots for all three different row spacings during the years of the experiment (four sowing dates).
Figure 1. Pearson’s correlation coefficients among plant density, growth, yield, and grain-quality parameters of quinoa. Blue and red colors represent positive and negative correlations, respectively. (a) Pearson’s correlation values. (b) Significance of Pearson’s correlation values (* p < 0.05, ** p < 0.01, *** p < 0.001). Colors reflect correlation values between every two variables. Each value represents measurements from 96 plots for all three different row spacings during the years of the experiment (four sowing dates).
Agriculture 12 01298 g001
Table 1. Monthly precipitation and temperatures at the Avnei-Eitan research farm (northern Israel, altitude 375 masl, 32°81′64″ N 35°76′28″ E) during 2018–2019 and 2019–2020 growing seasons (Israeli Meteorological Services).
Table 1. Monthly precipitation and temperatures at the Avnei-Eitan research farm (northern Israel, altitude 375 masl, 32°81′64″ N 35°76′28″ E) during 2018–2019 and 2019–2020 growing seasons (Israeli Meteorological Services).
2018 to 20192019 to 2020
MonthRainfall (mm)Min. Temp (°C)Max. Temp (°C)Rainfall (mm)Min. Temp (°C)Max. Temp (°C)
October11.17.834.17.413.337.3
November30.08.429.514.23.330.6
December140.34.920.5207.43.922.6
January182.02.320.0220.71.017.1
February156.13.122.493.00.420.1
March106.03.523.680.94.526.2
April40.15.830.744.56.030.1
May0.47.341.029.88.240.9
June0.113.437.10.011.734.0
Total665.7 697.9
Table 2. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in November 2018. Results are presented as mean value ± standard error.
Table 2. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in November 2018. Results are presented as mean value ± standard error.
Row Spacing (cm)AccessionPlant Density at Harvest (Plant m−2)Plant Height (cm)Stem
Diameter (mm)
Hay Yield (kg DM ha−1)Grain Yield (kg ha−1)Straw Yield (kg DM ha−1)Grain Protein Content (%)Thousand Grain Weight (mg)
163255 ± 20 a78 ± 26.4 ± 0.1 c9037 ± 946 a3191 ± 239 ab3070 ± 254 a13.3 ± 0.33099 ± 68
4E198 ± 12 b77 ± 37.0 ± 0.3 c7035 ± 634 ab4266 ± 470 a3214 ± 348 a14.2 ± 0.53111 ± 86
263131 ± 8 c81 ± 48.8 ± 0.4 b6914 ± 669 ab3656 ± 280 a2756 ± 207 ab12.6 ± 0.53350 ± 83
4E61 ± 2 d77 ± 49.1 ± 0.5 ab5458 ± 377 b3270 ± 312 ab1831 ± 205 bc12.8 ± 0.73328 ± 101
80342 ± 3 d81 ± 39.4 ± 0.4 ab2259 ± 75 c1980 ± 106 b1287 ± 109 c11.7 ± 0.93294 ± 76
4E22 ± 3 d87 ± 210.5 ± 0.5 a2306 ± 239 c1958 ± 259 b1275 ± 194 c12.1 ± 0.53446 ± 204
F-testAccession***nsns*nsnsnsns
Row spacing***ns*************ns
Different lowercase letters in a column indicate significant difference (Tukey HSD, p < 0.05). F-test: significant at * p < 0.05, *** p < 0.001, not significant (ns).
Table 3. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in November 2019. Results are presented as mean value ± standard error.
Table 3. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in November 2019. Results are presented as mean value ± standard error.
Row Spacing (cm)AccessionPlant Density at Harvest (Plant m−2)Plant Height (cm)Stem
Diameter (mm)
Hay Yield (kg DM ha−1)Grain Yield (kg ha1)Straw Yield (kg DM ha−1)Grain Protein Content (%)Thousand Grain Weight (mg)
163260 ± 24 a77 ± 46.8 ± 0.2 c11,100 ± 1212 a2973 ± 425 ab2640 ± 425 ab10.3 ± 1.13103 ± 86 ab
4E190 ± 21 b81 ± 27.4 ± 0.2 bc10,361 ± 1090 abc3501 ± 250 a3205 ± 110 a11.9 ± 0.82775 ± 46 b
263165 ± 10 bc86 ± 48.2 ± 0.4 bc10,710 ± 1820 ab2431 ± 442 ab2634 ± 239 ab9.9 ± 0.33064 ± 82 ab
4E116 ± 4 cd86 ± 48.2 ± 0.5 bc9233 ± 1390 abc3249 ± 90 a3020 ± 92 a14.1 ± 1.72839 ± 46 b
80357 ± 4 de86 ± 38.5 ± 0.4 b5149 ± 256 c1827 ± 128 b1398 ± 129 c11.9 ± 1.13312 ± 137 a
4E40 ± 4 e91 ± 110.3 ± 0.4 a5670 ± 524 bc2383 ± 111 ab1979 ± 99 bc14.1 ± 1.52768 ± 79 b
F-testAccession**ns**ns*******
Row
spacing
***************nsns
Different lowercase letters in a column indicate significant difference (Tukey HSD, p < 0.05). F-test: significant at * p < 0.05, ** p < 0.01, *** p < 0.001, not significant (ns).
Table 4. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in January 2019. Results are presented as mean value ± standard error.
Table 4. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in January 2019. Results are presented as mean value ± standard error.
Row Spacing (cm)AccessionPlant Density at Harvest (Plant m−2)Plant Height (cm)Stem
Diameter (mm)
Hay Yield (kg DM ha−1)Grain Yield (kg ha−1)Straw Yield (kg DM ha−1)Grain Protein Content (%)Thousand Grain Weight (mg)
163259 ± 14 a96 ± 77.8 ± 0.313,586 ± 1208 a3635 ± 142 a3597 ± 645 a5.3 ± 0.1 ab2418 ± 26 abc
4E103 ± 27 b97 ± 38.7 ± 0.111,804 ± 1071 ab3575 ± 135 a3197 ± 387 ab5.4 ± 0.1 ab2324 ± 30 c
263185 ± 29 a98 ± 108.1 ± 0.612,007 ± 2083 ab3309 ± 229 a3660 ± 511 a5.2 ± 0.1 b2592 ± 18 a
4E87 ± 9 b90 ± 107.8 ± 0.89250 ± 876 abc3412 ± 379 a2491 ± 429 abc6.1 ± 0.1 a2355 ± 67 bc
80359 ± 8 b106 ± 118.6 ± 0.76616 ± 784 bc1604 ± 156 b1594 ± 136 bc5.5 ± 0.4 ab2586 ± 36 ab
4E35 ± 7 b99 ± 69.4 ± 0.45574 ± 769 c1719 ± 95 b1212 ± 180 c6 ± 0.3 ab2493 ± 78 abc
F-testAccession***nsnsnsnsns***
Row
spacing
***nsns*********ns*
Different lowercase letters in a column indicate significant difference (Tukey HSD, p < 0.05). F-test: significant at * p < 0.05, ** p < 0.01, *** p < 0.001, not significant (ns).
Table 5. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in January 2020. Results are presented as mean value ± standard error.
Table 5. Row spacing, plant density at harvest, yields, growth, and grain-quality parameters of quinoa accessions 3 and 4E sown in January 2020. Results are presented as mean value ± standard error.
Row Spacing (cm)AccessionPlant Density at Harvest (Plant m−2)Plant Height (cm)Stem
Diameter (mm)
Hay Yield (kg DM ha−1)Grain Yield (kg ha−1)Straw Yield (kg DM ha−1)Grain Protein Content (%)Thousand Grain Weight (mg)
163238 ± 34 a111 ± 86.6 ± 0.617,979 ± 1488 a3088 ± 388 ab2369 ± 501 ab8.2 ± 1.1 b2553 ± 54 a
4E256 ± 30 a113 ± 46.7 ± 0.414,011 ± 1334 a3299 ± 203 a3187 ± 315 a9.7 ± 0.7 ab2313 ± 147 ab
263165 ± 37 ab112 ± 106.3 ± 0.714,731 ± 1368 a2437 ± 56 abc2022 ± 360 ab7.2 ± 0.6 b2530 ± 55 a
4E154 ± 7 ab116 ± 97.1 ± 0.413,514 ± 1800 a2987 ± 283 ab2864 ± 244 ab9.8 ± 0.7 ab2224 ± 129 ab
80350 ± 6 b123 ± 57.6 ± 0.36773 ± 655 b1704 ± 68 c1496 ± 159 b10.6 ± 0.4 ab2588 ± 61 a
4E57 ± 8 b126 ± 58.4 ± 0.97651 ± 388 b2195 ± 179 bc2106 ± 97 ab12.6 ± 1.3 a2033 ± 67 b
F-testAccessionnsnsnsns******
Row
spacing
***nsns********ns
Different lowercase letters in a column indicate significant difference (Tukey HSD, p < 0.05). F-test: significant at * p < 0.05, *** p < 0.001, not significant (ns).
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Asher, A.; Dagan, R.; Galili, S.; Rubinovich, L. Effect of Row Spacing on Quinoa (Chenopodium quinoa) Growth, Yield, and Grain Quality under a Mediterranean Climate. Agriculture 2022, 12, 1298. https://doi.org/10.3390/agriculture12091298

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Asher A, Dagan R, Galili S, Rubinovich L. Effect of Row Spacing on Quinoa (Chenopodium quinoa) Growth, Yield, and Grain Quality under a Mediterranean Climate. Agriculture. 2022; 12(9):1298. https://doi.org/10.3390/agriculture12091298

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Asher, Aviv, Reut Dagan, Shmuel Galili, and Lior Rubinovich. 2022. "Effect of Row Spacing on Quinoa (Chenopodium quinoa) Growth, Yield, and Grain Quality under a Mediterranean Climate" Agriculture 12, no. 9: 1298. https://doi.org/10.3390/agriculture12091298

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