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Proceeding Paper

Plant Density as the Main Driver of Quinoa Growth and Yield Under Andean Conditions †

by
Santiago C. Vásquez
1,2,*,
Marlene Molina-Müller
1,2,
Manuel Armijos
1,
Johana Pucha
1,
Santiago Erazo-Hurtado
1,
Fernando Granja
1,2,
Mirian Capa-Morocho
1,2,
Camilo Mestanza-Uquillas
3 and
Wagner Oviedo-Castillo
1
1
Agronomy Department, Faculty of Agricultural Sciences and Renewable Natural Resources, National University of Loja, Guillermo Falconí University Campus, Loja 110103, Ecuador
2
Research Group in Ecophysiology and Agricultural Production (AgroPHYS), National University of Loja, Guillermo Falconí University Campus, Loja 110103, Ecuador
3
Carrera Agropecuaria, Facultad de Ciencias Pecuarias y Biológicas, Universidad Estatal de Quevedo, Quevedo 120509, Ecuador
*
Author to whom correspondence should be addressed.
†
Presented at the 5th International Electronic Conference on Agronomy (IECAG 2025), 15–18 December 2025; Available online: https://sciforum.net/event/IECAG2025.
Biol. Life Sci. Forum 2026, 57(1), 9; https://doi.org/10.3390/blsf2026057009
Published: 13 April 2026
(This article belongs to the Proceedings of The 5th International Electronic Conference on Agronomy (IECAG 2025))
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Abstract

Quinoa is a highly nutritious Andean crop with considerable yield potential that remains underexploited in southern Ecuador. This study evaluated the effects of planting method (row seeding, hill seeding, and transplanting) and plant density (8–20 plants m−2) on quinoa growth and yield under Andean highland conditions. A factorial field experiment was conducted using a randomized complete block design with three replicates. Plant density significantly affected grain yield, increasing from 4.4 to 4.8 t ha−1 at 8 plants m−2 to a maximum of 6.97 t ha−1 at 20 plants m−2. This increase was mainly driven by a higher grain number per unit area, while thousand-grain weight remained stable across treatments. In contrast, the planting method and its interaction with plant density had no significant effect on yield or yield components. Grain yield showed a strong positive relationship with above-ground biomass, indicating that biomass accumulation was the main driver of yield variation. These results demonstrate that plant density is the primary agronomic factor controlling quinoa productivity under Andean conditions. Optimizing plant density to 15–20 plants m−2 is recommended as a simple and cost-effective management strategy to maximize grain yield, regardless of planting method.

1. Introduction

Quinoa (Chenopodium quinoa Willd.) has emerged as one of the most strategic crops for sustainable agriculture due to its exceptional nutritional quality and broad environmental adaptability [1,2]. Its grains contain high-quality protein (12–18%), a balanced amino acid profile, and significant levels of minerals and bioactive compounds, positioning quinoa as a key crop for food security under climate change scenarios [3]. Moreover, its tolerance to drought, salinity, and low temperatures makes it particularly suitable for marginal environments of the Andean highlands [4,5].
Despite these advantages, quinoa productivity in Ecuador rarely exceeds 1.5 t ha−1 under farmers’ conditions [6,7,8], whereas experimental trials and improved management systems have demonstrated yield potentials exceeding 7 t ha−1 [9]. This pronounced yield gap highlights the predominant role of agronomic constraints—rather than genetic limitations—and is mainly associated with suboptimal crop management practices, limited locally validated recommendations, and inefficient use of available resources.
Among agronomic factors, plant density is one of the most influential determinants of grain yield because it directly regulates canopy architecture, radiation interception, biomass accumulation, and sink formation [10,11,12,13]. According to crop physiological theory, grain yield is the product of grain number per unit area and grain weight, with grain number typically being the most plastic component under varying environmental and management conditions [14]. In quinoa, several studies have demonstrated that increasing plant density enhances leaf area index and radiation capture, leading to greater biomass production and grain number per unit area [15]. However, excessive density may intensify intra-specific competition and reduce individual plant performance [16].
For example, density ranges between 10 and 25 plants m−2 have been reported as optimal, depending on genotype and environmental conditions [17]. In northwestern Argentina, genotype-dependent responses showed that yield increases were mainly explained by improvements in grain number rather than thousand-grain weight [18]. Similarly, physiological studies have demonstrated that radiation-use efficiency and canopy development strongly determine quinoa productivity under temperate environments [15]. However, these responses are highly environment-specific, and their extrapolation to equatorial Andean systems may not be appropriate due to differences in the radiation regime, temperature amplitude, and soil fertility.
In addition to plant density, the planting method can influence spatial distribution, early vigor, and stand uniformity [17]. Direct seeding often results in heterogeneous emergence, which may alter competitive hierarchies within the canopy [19,20]. Transplanting, on the other hand, may improve early biomass accumulation and reduce initial establishment stress, potentially modifying the crop’s critical period for grain number determination [21]. Although transplant-based systems have shown yield advantages in peri-urban production systems of North America [22], their effectiveness under Andean highland conditions remains poorly documented.
From a theoretical perspective, plant density modifies source–sink relationships by altering both canopy photosynthetic capacity (source strength) and the number of reproductive structures (sink size) [23,24]. If density primarily enhances yield through increased biomass production, a positive relationship between above-ground biomass and grain yield should be expected. Conversely, if compensatory mechanisms dominate, yield components may remain relatively stable across plant densities.
In Southern Ecuador, information integrating plant density and planting method under Andean highland conditions remains scarce. Most agronomic recommendations are extrapolated from other countries without considering local factors such as altitude, radiation intensity, and soil characteristics. Consequently, farmers often adopt empirical plant densities that may not optimize resource capture or yield formation.
Therefore, this study aimed to evaluate the independent and interactive effects of plant density and planting method on quinoa growth and yield under Andean highland conditions in southern Ecuador. We hypothesized that:
(i) Increasing plant density would enhance grain yield primarily through an increase in grain number per unit area rather than grain weight; (ii) Planting method would have a secondary effect compared with plant density; and (iii) grain yield variation would be positively associated with above-ground biomass, supporting a source-driven yield formation mechanism.

2. Materials and Methods

2.1. Treatments and Experimental Design

The experiment was conducted using the quinoa variety Tunkahuan, a genotype adapted to the inter-Andean conditions of Ecuador. The experiment was established following a factorial arrangement of treatments in a randomized complete block design with three replicates. Two experimental factors were evaluated: plant density (PD) and planting method (PM). Four plant densities were tested: 8, 10, 15, and 20 plants m−2. These densities were combined with three planting methods: continuous row sowing, hill seeding, and transplanting, resulting in twelve treatment combinations (4 × 3 factorial design). Each experimental plot measured 6 m2, with rows spaced 0.5 m apart. Treatments were randomly assigned within each block to minimize the effects of spatial variability across the experimental field.

2.2. Data Collection

Above-ground biomass was measured at physiological maturity, defined as the stage when approximately 90% of the panicles had reached full maturity and grain moisture had substantially decreased. Plants were harvested from a 1 m linear section of the central rows in each plot to avoid border effects. Biomass samples were oven-dried at 65 °C until constant weight to determine total dry biomass. Grain yield and yield components were determined at harvest. Grain samples were cleaned and oven-dried at 65 °C until constant weight to obtain dry-grain weight. Grain yield was expressed on a hectare basis by extrapolating the dry-grain weight obtained from the harvested area of each plot. Thousand-grain weight (TGW) was determined by counting and weighing a subsample of 1000 grains from each plot.

2.3. Statistical Analysis

Data were analyzed using a two-way analysis of variance to evaluate the main effects of plant density (PD), planting method (PM), and their interaction (PD × PM). When significant effects were detected (p ≤ 0.05), treatment means were compared using Tukey’s honestly significant difference (HSD) test. In addition, linear regression analysis was performed to evaluate the relationship between above-ground biomass and grain yield. All statistical analyses were performed using the software InfoStat (version 2008).

3. Results

3.1. Main Effects

Plant density significantly affected several yield-related traits in quinoa. Grain number per unit area increased progressively with increasing plant density (p < 0.0001), indicating that higher plant populations enhanced the number of grains produced per surface unit (Table 1; Figure 1). Similarly, grain yield was significantly influenced by plant density (p = 0.0006), with the highest yields obtained at 20 plants m−2. Yield increased from approximately 4.4–4.8 t ha−1 at the lowest density (8 plants m−2) to values close to 7 t ha−1 at 20 plants m−2. This increase was mainly associated with the greater grain number per unit area rather than changes in grain size. Above-ground biomass also showed a strong response to plant density (p < 0.0001), increasing markedly with increasing plant population (Figure 2).
Planting method did not significantly affect thousand-grain weight, grain number per unit area, or grain yield (p > 0.05) (Table 1). Nevertheless, slight differences in grain yield were observed among planting methods, with row seeding and hill seeding showing a tendency toward higher grain yield compared with transplanting at higher plant densities (Figure 1). Overall, the absence of statistically significant differences indicates that the planting method had a limited influence on quinoa productivity under the conditions of this study.

3.2. Interaction Between Plant Density and Planting Method

The interaction between planting method and plant density (PM × PD) was not significant for any of the evaluated variables (p > 0.05), indicating that the response of quinoa grain yield to plant density was consistent across planting methods (Table 1). This result indicates that plant density did not influence grain yield, regardless of the planting method. Therefore, increasing plant density improved quinoa productivity regardless of whether crops were established through row seeding, hill seeding, or transplanting.

3.3. Relationship Between Grain Yield and Above-Ground Biomass

A significant positive linear relationship was observed between above-ground biomass and grain yield (Figure 2). This relationship indicates that treatments with greater biomass accumulation tended to produce higher grain yields, highlighting the importance of vegetative growth in determining final grain yield.

4. Discussion

The present study demonstrates that plant density is the primary agronomic factor determining quinoa productivity under Andean conditions in southern Ecuador. Increasing plant density significantly improved grain yield, mainly through an increase in grain number per unit area, while thousand-grain weight remained relatively stable. This response pattern indicates that grain yield formation in quinoa was predominantly regulated by sink size (grain number) rather than grain size, a mechanism widely reported in grain crops [18,25,26,27].
The increase in grain number with higher plant density likely resulted from improved canopy development and greater radiation interception during the reproductive period. In crops such as quinoa, grain number is highly sensitive to the amount of assimilates available during the critical period for grain yield determination [3]. Therefore, denser canopies may enhance biomass accumulation and provide a larger assimilate supply for reproductive development [15,28]. Similar responses have been reported in quinoa grown in Argentina and other environments, where grain yield increases under higher plant populations were mainly associated with improvements in grain number rather than grain weight [18].
The absence of significant effects of plant density on thousand-grain weight suggests that grain size is a relatively conservative trait in quinoa [3,25]. This stability has been previously documented and indicates that quinoa compensates for yield variations primarily through changes in grain number [29]. Such compensation mechanisms are common in grain crops, where grain weight tends to be less plastic than grain number under varying management conditions [26,30,31].
Although the planting method did not significantly influence yield or its components, slight trends toward higher grain yield under row seeding and hill seeding were observed at higher plant densities. These differences may be related to improved spatial distribution and stand establishment, which can influence early canopy closure and light interception [13]. However, under the environmental conditions of this study, these effects were relatively small compared with the strong influence exerted by plant density.
The strong positive relationship observed between above-ground biomass and grain yield reinforces the importance of vegetative growth in determining quinoa productivity. Greater biomass accumulation likely enhanced the crop’s photosynthetic capacity and assimilate availability for grain filling [24]. Similar biomass–yield relationships have been reported in quinoa and other grain crops, highlighting the importance of canopy development and radiation capture as key drivers of grain yield formation [32].
However, it is important to note that the results obtained in this study may be specific to the environmental and soil conditions of the experimental site in southern Ecuador. Under different climatic conditions or soil types, the optimal planting method and plant density may vary. In addition, this experiment was conducted using a single quinoa variety (Tunkahuan), and optimal plant densities may differ among varieties due to differences in plant architecture, growth habit, and yield potential. Therefore, further research across diverse environments and genotypes is necessary to validate and refine these agronomic recommendations.

5. Conclusions

Plant density was the main factor determining quinoa productivity under Andean highland conditions, whereas planting method had no significant effect on yield or its components. Increasing plant density from 8 to 20 plants m−2 significantly enhanced grain yield, mainly through an increase in grain number per unit area, while thousand-grain weight remained stable. The strong positive relationship between above-ground biomass and grain yield indicates that yield improvement was primarily driven by greater biomass accumulation and canopy development.
From an agronomic perspective, plant densities between 15 and 20 plants m−2 are recommended to maximize quinoa yield under the studied conditions, as they optimize radiation capture and biomass production without negatively affecting grain weight. These findings highlight plant density optimization as a practical, low-cost strategy to improve quinoa productivity in Andean production systems. Further research should evaluate these responses across different genotypes and environments to validate the consistency of these findings under broader production conditions.

Author Contributions

Conceptualization, S.C.V. and M.M.-M.; methodology, S.C.V. and M.M.-M.; software, S.C.V., S.E.-H. and W.O.-C.; formal analysis, S.C.V.; investigation, S.C.V., M.M.-M., J.P., M.A., F.G. and M.C.-M. data curation, W.O.-C., S.E.-H. and C.M.-U.; writing—original draft preparation, S.C.V.; writing—review and editing, S.C.V. and M.M.-M.; visualization, S.C.V., M.M.-M. and C.M.-U.; supervision, S.C.V.; project administration, S.C.V.; funding acquisition, S.C.V. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by Project 06-DI-FARNR-2023, funded by the Research Directorate of the National University of Loja, Ecuador.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. The raw data supporting the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors thank Beatriz Guerrero León (Bromatology Laboratory) and Lucía Quichimbo (Plant Physiology Laboratory) at the National University of Loja (UNL) for their assistance in processing plant material. We also acknowledge the staff of the “La Argelia” Experimental Station (UNL) for their technical support during the field phase. The authors further thank the Agronomy Department and the Research Directorate of UNL for providing the infrastructure and institutional support for this study. We are also grateful to the anonymous reviewers for their constructive comments, which improved the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
TGWThousand-grain weight
PMPlanting Method
PDPlant Density

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Blsf 57 00009 g001
Figure 1. Effects of sowing method and plant density on grain yield (A), thousand-grain weight (B), and grain number (C) in quinoa. Values represent means of three replicates ± standard error.
Figure 1. Effects of sowing method and plant density on grain yield (A), thousand-grain weight (B), and grain number (C) in quinoa. Values represent means of three replicates ± standard error.
Blsf 57 00009 g001
Blsf 57 00009 g002
Figure 2. Relationship between grain yield and above-ground biomass under different plant densities and sowing methods. Blue, green, red, and yellow symbols represent plant densities of 8, 10, 15, and 20 plants m−2, respectively. Circular, square, and triangular symbols indicate sowing methods: Row seeding, transplanting, and hill planting, respectively. The solid line represents the fitted linear regression.
Figure 2. Relationship between grain yield and above-ground biomass under different plant densities and sowing methods. Blue, green, red, and yellow symbols represent plant densities of 8, 10, 15, and 20 plants m−2, respectively. Circular, square, and triangular symbols indicate sowing methods: Row seeding, transplanting, and hill planting, respectively. The solid line represents the fitted linear regression.
Blsf 57 00009 g002
Table 1. Effect of Planting Method (PM) and Plant Density (PD) on Grain Yield, Thousand-Grain Weight (TGW), Grain Number, and Above-ground Biomass (AGB). p-values for each crop trait and source of variation are shown.
Table 1. Effect of Planting Method (PM) and Plant Density (PD) on Grain Yield, Thousand-Grain Weight (TGW), Grain Number, and Above-ground Biomass (AGB). p-values for each crop trait and source of variation are shown.
Source of VariationGrain YieldTGWGrain NumberAGB
Plant Methodnsnsnsns
Plant Density***ns******
PM × PDnsnsnsns
ANOVA significance levels: *** p < 0.001; ns = not significant (p > 0.05). PM × PD = Interaction between Planting Method and Plant Density.
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MDPI and ACS Style

Vásquez, S.C.; Molina-Müller, M.; Armijos, M.; Pucha, J.; Erazo-Hurtado, S.; Granja, F.; Capa-Morocho, M.; Mestanza-Uquillas, C.; Oviedo-Castillo, W. Plant Density as the Main Driver of Quinoa Growth and Yield Under Andean Conditions. Biol. Life Sci. Forum 2026, 57, 9. https://doi.org/10.3390/blsf2026057009

AMA Style

Vásquez SC, Molina-Müller M, Armijos M, Pucha J, Erazo-Hurtado S, Granja F, Capa-Morocho M, Mestanza-Uquillas C, Oviedo-Castillo W. Plant Density as the Main Driver of Quinoa Growth and Yield Under Andean Conditions. Biology and Life Sciences Forum. 2026; 57(1):9. https://doi.org/10.3390/blsf2026057009

Chicago/Turabian Style

Vásquez, Santiago C., Marlene Molina-Müller, Manuel Armijos, Johana Pucha, Santiago Erazo-Hurtado, Fernando Granja, Mirian Capa-Morocho, Camilo Mestanza-Uquillas, and Wagner Oviedo-Castillo. 2026. "Plant Density as the Main Driver of Quinoa Growth and Yield Under Andean Conditions" Biology and Life Sciences Forum 57, no. 1: 9. https://doi.org/10.3390/blsf2026057009

APA Style

Vásquez, S. C., Molina-Müller, M., Armijos, M., Pucha, J., Erazo-Hurtado, S., Granja, F., Capa-Morocho, M., Mestanza-Uquillas, C., & Oviedo-Castillo, W. (2026). Plant Density as the Main Driver of Quinoa Growth and Yield Under Andean Conditions. Biology and Life Sciences Forum, 57(1), 9. https://doi.org/10.3390/blsf2026057009

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