Current IssueEditorial BoardOnline First ArticlesArchive
Current IssueEditorial BoardOnline First ArticlesArchive

Short Communication

Quinoa (Chenopodium quinoa Willd.) Growth Dynamics and Yield under Varied Geometry and Fertility Levels

P
Pratiksha Raj1
A
Arunima Paliwal2,*
https://orcid.org/0009-0001-9953-8497
R
Ravisankar Dubey1
A
Aditya Raj Bisht3
A
Ajay Kumar4
G
Gargi Goswami5
S
Shalini6
1Department of Seed Science and Technology, College of Agriculture, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur-208 002, Uttar Pradesh, India.
2Department of Agronomy, College of Hill Agriculture, Chirbatiya, Veer Chandra Singh GarhwaliUttarakhand University of Horticulture and Forestry, Camp at Ranichauri-249 199, Uttarakhand, India.
3College of Forestry, Veer Chandra Singh Garhwali Uttarakhand University of Horticulture and Forestry, Ranichauri-249 199, Uttarakhand, India.
4Department of Agronomy, ICAR- National Institute of Seed Science and Technology, Mau-275 103, Uttar Pradesh, India.
5Department of Natural Resource Management, College of Horticulture, Veer Chandra Singh Garhwali Uttarakhand University of Horticulture and Forestry, Bharsar-246 123, Uttarakhand, India.
6Department of Agronomy, Krishi Vigyan Kendra, Hamirpur, Banda University of, Agriculture and Technology, Banda-210 505, Uttar Pradesh, India.

  • Submitted28-10-2025|

  • Accepted05-02-2026|

  • First Online 23-02-2026|

  • doi 10.18805/BKAP895

ABSTRACT

Background: The investigation was conducted to study the effect of various agronomic factors viz., geometry and fertility levels on growth dynamics and yield of quinoa (Chenopodium quinoa Willd.), often referred to as superfood and also called “the mother grain”.

Methods: The investigation was conducted in kharif 2022, with genotype “EC507742” at mid-hill region of Uttarakhand, India comprising of two factors viz., geometry (S): S1- 20 cm × 10 cm, S2- 30 cm × 10 cm and S3- 40 cm × 10 cm as main plots and fertility levels (F): F1- Control, F2- 75% NPKS, F3- 100% NPKS and F4- 125% NPKS as sub plots with total of 12 treatment combinations that were evaluated in split plot design with three replications and analysed using OPSTAT with figures from SAS (proc glm).

Result: The 30 cm × 10 cm spacing was found effective in field conditions compared to other crop geometries, indicating to be more suited for quinoa cultivation under 100% NPKS fertilizer application which produced best growth dynamics, yield characteristics and yield for quinoa. The interaction between the 30 cm × 10 cm spacing and 100% NPKS fertilizer was significant in recording the highest growth dynamics and yield. Analysis indicates that quinoa responds very well to fertilizer dose of 100% NPKS at an optimum spacing of 30 cm × 10 cm.

INTRODUCTION

Quinoa (Chenopodium quinoa) is a remarkable, resilient and versatile crop with deep historical roots dating back over 5,000 years. Indigenous to the Andean region of South America, it was cultivated by ancients and revered sacred status as the “mother grain”. Today, quinoa has trans-formed from a traditional dietary staple into much sought-after superfood, embraced by health-conscious individuals worldwide. One of quinoa’s most compelling attributes is its exceptional nutritional content as it is gluten-free and contains all nine essential amino acids, making it a complete protein vital for human well-being. Additionally, it is rich in dietary fibre, vitamins, minerals and antioxidants, making it a powerhouse of nutrition addressing malnutrition concerns besides promoting overall health and vitality. The rising global demand for quinoa has created significant economic opportunities for farmers and exporters in quinoa cultivating regions. As consumers recognize its nutritional benefits, the crop’s market value continues to grow, becoming a vital income source for small-scale farmers. This economic advancement empowers local communities in developing areas.
       
Fertility level can play a crucial role in enhancing seed quality of quinoa, which directly enhances the plant growth and development, besides increasing seed yield and better seed quality. Proper nutrient application also influences the nutritional composition of quinoa seeds. The research by Miranda et al. (2012) found that increasing nitrogen levels boosts seed protein content, while higher fertility levels can increase the concentration of essential minerals. However, excessive fertilization should be avoided, as it can compromise seed quality. The overuse of fertilizers, combined with inefficient resource management, deteriorate soil health and pose environmental risks (Yadav et al., 2024). In addition to fertility, plant geometry is a key agronomic factor for improving crop yields (Cha et al., 2016). The lack of proper crop geometry in the broadcasting method results in poor plant distribution, difficulties in intercultural operations, inefficient use of soil moisture and nutrients and higher competition among plants (Kumbhar et al., 2026). Quinoa is sensitive to afferent spacing, fertilizer types and application rate. However, optimal plant density ensures efficient resource utilization like water, nutrients and sunlight resulting in better plant growth and develop-ment, higher seed production and enhanced nutrient accu-mulation in seeds. Plant geometry can affect the competition for resources among individual plants, which lead to a decrease in stress and promoting more consistent seed yield. 
               
To maximize quinoa yields, farmers must adopt an integrated approach that carefully balances fertility manage-ment, plant geometry, irrigation and pest control. Optimal spacing and nutrient application ensure uniform seed development and improved germination rates, while adequate nutrient availability contributes to a high germination rate. Moreover, genetic factors and environ-mental conditions also significantly influence seed quality. By understanding these interconnected factors, farmers can enhance their production systems to achieve higher yields. Sustainable farming practices are essential to maintain quinoa’s nutritional value while preserving ecosystem health. Considering these critical aspects, this study was conceived to determine the ideal cropping geometry and fertility levels for optimizing quinoa growth, yield characteristics and productivity in the mid-hill regions of Uttarakhand, India.  

MATERIALS AND METHODS

A field experiment was conducted in kharif 2022 at Research and Extension Centre, Gaja, College of Forestry, Ranichauri (Tehri Garhwal), located in latitude 30o16’17’’N, longitude 78o25’21’’E at an altitude of 1700-1760 m above sea level in the chilly temperature. The experiment was laid out in spilt plot design with three replications having three different crop geometries (S1: 20 cm ×  10 cm, S2: 30 cm × 10 cm and S3: 40 cm × 10 cm) in main plot and four fertility levels (F1: Control, F2: 75% NPKS, F3: 100% NPKS and F4: 125% NPKS) in sub plot under tropical to subtropical zone of Uttarakhand. The mean maximum and minimum temperature, rainfall, relative humidity at morning and afternoon, wind speed and bright sunshine was 24.2oC, 13.1oC, 7.7 mm, 87.1%, 76.7%, 4.0 kmph and 6.0 hr/day, respectively during the crop growing period (Fig 1).

Fig 1: Weekly meteorological data during crop season (26 May to 30 September, 2022).


               
The experimental soil was silty clay loam in texture, medium in availability of nitrogen (242 kg/ha) and phosphorus (22 kg/ha), higher in available potassium (404 kg/ha) and organic carbon (0.75%) with slightly acidic pH (6.1). The genotype “EC507742” was used for the experiment, sown on 26 May 2022. The crop was applied with recommended dose of fertilizer i.e., 40:20:20:20 NPKS in the form of urea, NPK (12:32:16) and Bentonite S, respectively. Entire dose of NPK and S was applied as basal through placement in the furrows made with hand hoes 5 cm away from seed rows and at a depth of 2 cm below the seed zone as per the treatments. Thinning after one irrigation was done to facilitate uniform germination of the crop at 25 days after sowing (DAS). Two hand weedings were done manually at 30 and 60 DAS to keep the crop free from weeds. During the seed formation stage, sucking pest was noticed and was controlled by spraying imidacloprid @ 0.2 ml l-1 of water.  Anthracnose was observed after heavy rainfall in crop and was controlled by mancozeb @ 2 g l-1 of water. Growth dynamics, yield attributes and yield from random selected five plants from each net plot was recorded and the mean value was worked out. The crop was harvested on 02 September 2022. The experimental data obtained during the course of investigation was analysed by using split plot design (SPD) with OPSTAT Programme designed and development by O.P. Sheoran, Computer Programmer at CCS HAU, Hisar, India and figure from SAS (proc glm).

RESULTS AND DISCUSSION

Growth dynamics
 
Plant population growth rate
 
Plant population growth rate of quinoa was significantly influenced by geometry and fertility levels at different stages of crop growth i.e. 30-60 DAS, 60-90 DAS and 90 DAS-harvest (Table 1). Among different geometries, significantly higher plant population growth rate was attained in S2 than other geometry. Among different fertility levels, plant population growth rate was statistically more in F3 being at par with F4 at 30-60 DAS, F4 which was at par with F3 at 60-90 DAS and significantly highest in F4 at 90 DAS-harvest. Plant population growth rate showed significant variations in interaction effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS, 60-90 DAS and 90 DAS-harvest as per tukey grouping. The plant population growth rate was significantly more in S2F3 among all the interactions between geometries with different fertility levels that was at par with S2F4 and S1F4 as per tukey grouping at 30-60 DAS (Fig 2) and at 60-90 DAS along with S2F2 (Fig 3). However, at 90 DAS-harvest significantly higher plant population growth rate was found in S2F4 being at par with S2F3, S1F4 and S2F2 as per tukey grouping (Fig 4). This significant increase might be potentially attributable to favourable conditions such as ample sunlight, moisture and accessible nutrients which are conducive to promoting rapid plant propagation, a finding corroborated by Parameswari et al., (2003). The wider spacing between plants resulted in improved growth parameters, primarily because it minimized the competition among plants for crucial resources such as space, light, moisture and nutrients, are indispensable for their optimal growth and development. This observation concurs with the findings of Sarkar and Malik (2004). A marked increase in plant height at close spacing might be attributed to higher plant population density which might have resulted in less plant canopy area and more vertical growth by producing weak and tall plants due to competition for space, light, nutrients and moisture compared to those at wider spacing (Shrikanth et al., 2008). Attar et al. (2013) also reported increased plant height with narrow spacing. Nutrients are crucial elements of proteins, nucleotides, chlorophyll and enzymes and hence facilitate numerous metabolic processes in plants, resulting in increased output (Sharma et al., 2023).

Table 1: Effect of geometry and fertility levels on growth dynamics of quinoa.



Fig 2: Plant population growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.



Fig 3: Plant population growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.



Fig 4: Plant population growth rate at 90 DAS-harvest as per Tukey grouping of geometry and fertility levels.


 
Crop growth rate
 
Crop growth rate of quinoa was not significantly influenced by geometry while it was significantly influenced by fertility levels at different stages of crop growth i.e. 30-60 DAS and 60-90 DAS except 90 DAS-harvest. Among different geometries, higher crop growth rate was attained in S2 followed by S1 and S3 at 30-60 DAS and S1 followed by S2 and S3 at 60-90 DAS and at 90 DAS-harvest. Among different fertility levels, crop growth rate was significantly higher in F4 at 30-60 DAS and at 60-90 DAS that was statistically at par with F2 at 30-60 DAS. However, it was higher in F4 followed by F2, F3 and F1 at 90 DAS-harvest (Table 1).
       
Crop growth rate showed significant variations in interactive effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS and 60-90 DAS except 90 DAS-harvest as per tukey grouping. The crop growth rate was obtained statistically highest in S2F4 among all the interactions between geometries with different fertility levels which was at par with S3F2 and S1F4 as per tukey grouping at 30-60 DAS (Fig 5).

Fig 5: Crop growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.


       
At 60-90 DAS, it was statistically higher in S3F2 being at par with S2F4 and S1F4 (Fig 6). However, at 90 DAS-harvest, there was non-significant variations in interactive effect on crop growth rate were observed among geometries with different fertility levels (Table 1).

Fig 6: Crop growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.


       
The reduced plant height was observed in closer spacing that can be attributed to increased competition among plants for essential resources such as nutrients and light. In contrast, wider spacing decreases this competition, leading to increased plant height. These findings are in line with the research conducted by Rishi and Galwey (1991) but contradict the findings of Smitha et al. (2011). Additionally, it was noted that plant height exhibited a progressive increase with higher NPK levels, with the combination of the highest NPK levels resulting in the greatest plant height. The greater plant height can be ascribed to the abundant availability of nitrogen and phosphorus, facilitating improved photosynthesis and overall vigour. Phosphorous is an essential nutrient both as a part of several key plant structure compounds and also as a catalyst in conversion of numerous key biochemical reactions in plant like photosynthesis, respiration, cell elongation, cell division, activation of Amino acid for synthesis of protein and carbohydrate metabolism, also helps in formation of energy rich phosphate bonds, phospholipids and development of root system and nodulation which contributed to increase in general health and vigour of plant. Phosphorous also important for its role in capturing and converting sun’s energy into useful plant compounds. Phosphorous also associated with different metabolic activities that leads to better translocation of nutrients that leads to better expression of characters like increased stem strength, increased stalk and stimulated root development. With wider row spacing helped in reducing inter and intra plant competition thus helped in efficient utilization of solar radiation, nutrients and water which leads plants to better filling of available space by initiating branches. The study was in close conformity with Shukla et al. (2017). These observations are consistent with the results reported by Balliu et al. (2007), Abdelaziz et al. (2008) and Yasuor et al., (2013).
 
Leaves per plant growth rate
 
Leaves per plant growth rate of quinoa were significantly influenced by geometry and fertility levels at different stages of crop growth i.e. 30-60 DAS and 60-90 DAS. Among different geometry the leaves per plant growth rate were significantly highest in S2 at different stages of crop growth. Among different fertility levels, leaves per plant growth rate were significantly higher in F3 that was at par with F4 and vice-versa at various crop growth stages (Table 1). Leaves per plant growth rate showed significant variations in interactive effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS and 60-90 DAS as per tukey grouping. The significantly superior leaves per plant growth rate was found in S2F3 among all the interactions between geometries with different fertility levels which was at par with S2F4 at 30-60 DAS (Fig 7). At 60-90 DAS, it was statistically higher in S1F4 being at par with S2F3, S2F4 and S2F2 (Fig 8). The results obtained are likely due to the augmented level of fertilizer, which stimulates the synthesis of chlorophyll and fosters vegetative growth, resulting in an increase in the number of leaves and branches in the plants. These findings are in corroboration with the results reported by Kumar and Sudhavani (2004).

Fig 7: Leaves per plant growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.



Fig 8: Leaves per plant growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.


 
Branches per plant growth rate
 
Branches per plant growth rate of quinoa were significantly influenced by geometry and fertility levels at different stages of crop growth i.e. 30-60 DAS and 60-90 DAS. Among different geometry, significantly higher branches per plant growth rate were attained in S2 at different stages of crop growth. Among different fertility levels, branches per plant growth rate were significantly higher in F3 which was statistically at par with F4 at different crop growth stages (Table 1). Branches per plant growth rate showed significant variations in interaction effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS and 60-90 DAS as per tukey grouping. The significantly higher branches per plant growth rate was found in S2F3 among all the interactions between geometries with different fertility levels which was at par with S1F4, S2F4 and S2F2 as per tukey grouping at 30-60 DAS (Fig 9). At 60-90 DAS, it was statistically higher in S2F3 being at par with S2F4, S1F4, S2F2 and S1F3 (Fig 10).

Fig 9: Branches per plant growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.



Fig 10: Branches per plant growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.


       
In closely spaced crops, the intense competition for light, space, moisture and nutrients leads to reduced branching and a lower leaf count. These conclusions align with the findings reported by Yeboah et al. (2014). More number of branches/plant at 100% RDF may be due to the availability of optimum phosphorous content which may have attributed to the fact that phosphorus helped in producing a higher nodulation count, which resulted in higher nitrogen fixation which led to the production of more branches for higher photosynthetic ability (Ndor, 2012).
 
Yield attributes and yield
 
Panicle fresh weight (g)
 
Panicle fresh weight of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, significantly higher panicle fresh weight was attained in S2. Among different fertility levels, panicle fresh weight was significantly higher in F4 being at par with F3 (Table 2). Significant variations in interactive effect on panicle fresh weight were observed among geometries with different fertility levels as per tukey grouping. The significantly higher panicle fresh weight was recorded in S2F3 which was statistically at par with S2F4 and S1F4 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 11). This could possibly be attributed to the availability of nutrients to the plants and the improved uptake of elements, especially nitrogen, resulting from the application of fertilizers. Consequently, plants exhibited enhanced nutrient absorption, leading to growth and an increase in the yield attributes and yield.

Table 2: Effect of geometry and fertility levels on yield attributes and yield of quinoa.



Fig 11: Panicle fresh weight of quinoa as per Tukey grouping of geometry and fertility levels.


       
The application of phosphorus may have led to an accumulation of carbohydrates, which were subsequently mobilized to the reproductive parts of the plants. The significance of potassium, a highly mobile nutrient in plants, should not be overlooked, as it plays a vital role in the elongation and division of young tissues and contributes to maintaining turgor pressure. Moreover, it improves both the quality and yield of the plants. These findings are consistent with the research conducted by Nath et al. (2008) in ajwain and Mehta et al. (2011) in fennel.
 
Number of fingers
 
Number of fingers of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, significantly higher number of fingers was significantly attained in S2. Among different fertility levels, number of fingers was significantly higher in F3 which was found equal to F4 (Table 2). Significant variations in interactive effect on number of fingers were observed among geometries with different fertility levels with significantly higher in S2F3 among all the interactions between geometries with different fertility levels being at par with S2F4 as per tukey grouping (Fig 12). These findings are consistent with the research conducted by Nath et al. (2008) in ajwain and Mehta et al. (2011) in fennel.

Fig 12: Number of fingers of quinoa as per Tukey grouping of geometry and fertility levels.


 
Finger length (cm)
 
Finger length of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, higher finger length was significantly attained in S2. Among different fertility levels, finger length was significantly higher in F3 (Table 2).
       
Significant variations in interactive effect on finger length were observed among geometries with different fertility levels with significantly higher in S2F3 which was statistically at par with S2F4 and S1F3 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 13). This was might be due to the application of phosphorus may have led to an accumulation of carbohydrates, which were subsequently mobilized to the reproductive parts of the plants. Potassium plays a vital role in the elongation and division of young tissues and contributes to maintaining turgor pressure.

Fig 13: Finger length of quinoa as per Tukey grouping of geometry and fertility levels.


 
Test weight (g)
 
Test weight of quinoa was non-significantly influenced by geometry, while it was significantly influenced by fertility levels. Among different geometry, higher test weight was attained in S2 followed by S1 and S3. Among different fertility levels, test weight was significantly higher in F3 which was found equal to F4 being statistically at par with F2. Non-significant variations in interaction effect on test weight were observed among geometries with different fertility levels (Table 2). Increase in weight of 100 seeds with spacing might be due to better availability of nutrients and less competition between plants for nutrients, water and sunlight which may have enhanced photosynthetic activities and resulted in more weight of 100 seeds.
 
Seed yield (kg/ha)
 
Seed yield of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, higher seed yield was attained in S2 which was significantly equal to S3. Among different fertility levels, seed yield was significantly higher in F3 which was statistically at par with F4 (Table 2).
       
Significant variations in interactive effect on seed yield were observed among geometries with different fertility levels as per tukey grouping. The significantly higher seed yield was found S2F3 which was statistically at par with S2F4 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 14). The maximum yield attributes under widest spacing may be owing to maximum increase in the growth parameters (height, branches, leaves, stem diameter and plant spread) which means adequate photosynthates production and greater partitioning of metabolites and nutrients towards the reproductive organs. This eventually happened because of reduced competition between widely spaced plants for space, light, nutrients and moisture. These favourable conditions increased the growth parameters up to maximum extents. These results are in close agreement with those Bajpai et al., 2004; Singh et al., 2005; Ram et al., 2013 and Loria et al., 2022. The application of an increased fertilizer dosage resulted in enhanced growth and yield-related traits, leading to seed yield, crop residue and biological yield. These consistent outcomes correspond to the findings of Okeleye and Okelana (1997).

Fig 14: Seed yield of quinoa as per Tukey grouping of geometry and fertility levels.


       
The lowest values of plant growth parameters were recorded in control with narrower spacing. This might be due to the fact that non-availability of nutrient at early growth period reduced the plant growth significantly.
 
Biological yield (kg/ha)
 
Biological yield of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, higher biological yield was attained in S2. Among different fertility levels, biological yield was significantly higher in F4 which was statistically at par with F3 (Table 2).
               
Significant variations in interactive effect on biological yield were observed among geometries with different fertility levels as per tukey grouping. The significantly higher biological yield was found S2F4 which was statistically at par with S2F3 and S1F4 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 15). The enhanced reproductive growth allowed for an expanded gap between plants, facilitating enhanced sun exposure and increased nourishment. These outcomes correspond to the findings of Patel et al. (2008).

Fig 15: Biological yield of quinoa as per Tukey grouping of geometry and fertility levels.

CONCLUSION

Based on the experimental findings it can be concluded from the investigation that under mid-hills of Uttarakhand, optimal plant geometry of 30 cm × 10 cm with balanced fertilization of 100% NPKS is highly efficient and can be preferred for maximum growth and yield of quinoa. 

ACKNOWLEDGEMENT

The authors are thankful to the facilities provided by All India Coordinated Research Network- Potential Crops and the institutional support provided by the College of Forestry, V.C.S.G. Uttarakhand University of Horticulture and Forestry, Ranichauri, Tehri Garhwal, Uttarakhand, for the successful conduct of the research.
 
Authors’ contributions
 
Pratiksha Raj: Data curation, Formal analysis, Writing-original draft, Investigation. Arunima Paliwal: Supervision, Methodology, Resources, Validation, Writing-review and editing. Ravishankar Dubey and Aditya Raj Bisht: Data curation, Writing-original draft. Ajay Kumar: Methodology, Resources, Data curation, Writing-review and editing. Gargi Goswami: Methodology, Writing-review and editing. Shalini: Validation, Writing-review and editing.
 
Funding
 
Not funded.
 
Research content
 
Research content of this manuscript is original and has not been published or communicated elsewhere.
 
Ethical approval
 
Not applicable.
 
Data availability
 
All data generated and analysed are included in the research article.
 
Consent to publish
 
 All authors agree to publish research article in Agricultural Science Digest.

CONFLICT OF INTEREST

On behalf of all authors, the corresponding author states that there is no conflict of interest.

REFERENCES


  1. Abdelaziz, M.E., Ahmed, A.H.H., Bekhid, R.S. and Pokluda, R. (2008). Response of growth patterns in sweet pepper to different NPK levels. Acta Universitatis Agriculture Silvicultural Madelaine Brunensis. 56(1): 241-244. 

  2. Attar, A.V., Patil, B.T., Bhalekar, M.N. and Sinde, K.G. (2013). Effect of spacing and fertilizers levels on growth, yield and quality of garden pea (Pisum sativum L.) cv. Phule Priya. Bioinfolet. 10(4B): 1240-1242.

  3. Bajpai, V.P., Khan, A.A., Kumar. S., Singh, P. and Singh, C.B. (2004). Effect of spacing and sowing dates on growth and seed quality of okra (Abelmoschus esculentus). Farm Sci. 113(2): 116-117.

  4. Balliu, A., Bani, A. and Sulce, S. (2007). Nitrogen effects on the relative growth rate and its components of pepper (C. annuum) and eggplant (Solanum melongena) seedlings. Acta Universitatis Agriculture Silviculture Madeliene Brunensis. 56(1): 241-244. 

  5. Cha, M.K., Jeon, Y.A., Son, J.E. and Cho, Y.Y. (2016). Development of planting-density growth harvest (PGH) charts for quinoa (Chenopodium quinoa Willd.) and sow thistle (Ixeris dentata Nakai) grown hydroponically in closed-type plant production systems. Hort. Environ. Biotechnol. 57(3): 213-218. 

  6. Kumbhar, N.M., Thombare, P.D., Gholkar, M.D. and Wani A.G. (2026). Energy indices, productivity and profitability of rainfed chickpea (Cicer arietinum L.) influenced by crop geometry and nutrient management practices. Agricultural Reviews. 47(1): 122-130. doi: 10.18805/ag.R-2731.

  7. Kumar, R.K. and Sudhavani, V. (2004). Effect of plant densities and phosphorus levels on the growth and yield of vegetable cowpea. Department of Horticulture, College of Horticulture, Venkataramannagudem. 534: 101.

  8. Loria, K., Kumari, M., Sood, Y., Vikas, Lalita, Rani, S. and Himangini. (2022). Effect of seed rate and seed spacing on yield attributes of chickpea. Agricultural Science Digest. doi: 10. 18805/ag.D-5565.

  9. Mehta, R.S., Anwer, M.M. and Aishwath, O.P. (2011). Growth and yield of fennel (Foeniculum vulgare Mill.) as influenced by irrigation, nutrient levels and crop geometry. Journal of Spices and Aromatic Crop. 20(2): 77-80. 

  10. Miranda, M., Vega-Gálvez, A., Quispe-Fuentes, I., Rodríguez, M.J., Maureira, H. and Martínez, E.A. (2012). Nutritional aspects of six quinoa (Chenopodium quinoa Willd.) ecotypes from three geographical areas of Chile. Chilean J. of Agri. Res.  72(2): 175. 

  11. Nath, P., Jaiswal, R.C., Verma, R.B. and Yadav, G.C. (2008). Effect of date of sowing, nitrogen levels and spacing on growth and yield of ajwain (Trichyspermum ammi L.). Journal Spices Aromatic Crops. 17(1): 1-4. 

  12. Ndor, E., Dauda, N.S., Abimuku, E.O., Azagaku, D.E. and Anzaku, H. (2012). Effect of phosphorus fertilizer and spacing on growth, nodulation count and yield of cowpea [Vigna unguiculata (L) Walp] in southern Guinea savanna agroecological zone, Nigeria. Asian Journal of Agricultural Sciences. 4(4): 254-57.

  13. Okeleye, K.A. and Okelana, M.A.O. (1997). Effect of phosphorus fertilization on nodulation, growth and yield of cowpea (Vigna unguiculata) varieties. Indian Journal of Agriculture Science. 67(1): 10-12. 

  14. Parameswari, K., Vanangamudi, K. and Kavitha, S. (2003). Effect of spacing on hybrid seed yield of pigeon pea hybrid COPH2. Journal Madras Agriculture. 90: 691-696. 

  15. Patel, B.S., Patel, J.C. and Sadaria, S.G. (2008). Response of blond psyllium (Plantago ovata) to irrigation and phosphorus. Indian Journal of Agronomy. 4: 311-314. 

  16. Ram, Harischand, Khan, Mohd, Meraj and Singh, P.K. (2013). Effect of spacing and cultivars on growth and yield of okra (Abelmoschus esculentus L.). The Asian Journal of Horticulture. 8(2): 507-511.

  17. Rishi, J. and Galwey, N.W. (1991). Effect of sowing date and sowing rate on plant development and grain yield in a temperate environment. J. of Agri. Sci. 117: 325-332. 

  18. Sarkar, R.K. and Malik, G.C. (2004). Effect of method of planting and crop geometry on productivity of rainfed upland cotton grown low land rice fallows. Indian Journal of Agronomy. 49(4): 278-281. 

  19. Singh, J.P., Pandey, I.P., Shukla, I.N., Gautam, R.K.S. and Pandey, S.B. (2005). Effect of nitrogen, phosphorus and spacing on flowering, fruiting and yield of okra. Ann. Soil Res. 7(1): 85- 86.

  20. Smitha, P.A., Alagundagi, S.C., Mansur, C.P., Kubsaad, V.S., Hosamani, S.V. and Megeri, S.N. (2011). Effect of row spacing and seed rate on growth, fodder productivity and economics of amaranth genotypes. Karnataka Journal of Agriculture Science. 24(5): 651-653. 

  21. Shukla, R.D., Singh, A., Verma, S., Singh, A.K., Dubey, D. and Kumar, S. (2017). Effect of crop geometry and phosphorus levels on growth and productivity of chickpea (Cicer arietinum L.). Journal of Pharmacognosy and Phytochemistry. 6(5): 659-661.

  22. Shrikanth, A.S., Channaveerswami, S., Tirakannanavar, C.P. and Hosamani, R.M. (2008). Effect of spacings and fertilizer levels on crop growth and seed yield in lablab bean (Lablab purpureus L.). Karnataka Journal of Agricultural Sciences. 21: 440-443.

  23. Sharma, M., Shilpa, Kaur, M., Sharma, A.K. and Sharma, P. (2023). Influence of different organic manures, biofertilizers and inorganic nutrients on performance of pea (Pisum sativum L.) in north-western Himalayas. Journal of Plant Nutrition. 46: 600-617.

  24. Yadav, S.L., Debnath, S., Singh, Y., Singh, S.K., Devi, Y.B., Ghosh, A., Ram, A., Kumar, S. and Arunachalam, A. (2024). Influence of varied nutrient management strategies on yield,nutrient absorption and grain protein content in chickpea (Cicer arietinum L.). Indian Journal of Agricultural Research. 59(7): 1119-1125. doi: 10.18805/IJARe.A-6255.

  25. Yasuor, H., Gal, A. Ben, Yermiyahu, U., Yannai, E. Beit and Cohen, S. (2013). Nitrogen management of greenhouse pepper production: Agronomic, Nutritional and environmental implications. Horticulture Science. 48(10): 1241-1249.

  26. Yeboah, S., Dangquah, E. Owusu, Lamptey, J.N.L., Mochiah, M.B., Lamptey, S., Oteng- Darko, P., Adama, I., Appiah-Kubi, Z. and Agyeman, K. (2014). Influence of planting methods and density on performance of chia and its suitability as an oilseed plant. Agriculture Science. 2(4): 14-26. 
Published In
Bhartiya Krishi Anusandhan Patrika
Article Metrics
Metrics Icon
0
Views
0
Citations
Reviewed By
Share Article
Download Article
In this Article
    Contact us
    Follow us

    Short Communication

    Quinoa (Chenopodium quinoa Willd.) Growth Dynamics and Yield under Varied Geometry and Fertility Levels

    P
    Pratiksha Raj1
    A
    Arunima Paliwal2,*
    https://orcid.org/0009-0001-9953-8497
    R
    Ravisankar Dubey1
    A
    Aditya Raj Bisht3
    A
    Ajay Kumar4
    G
    Gargi Goswami5
    S
    Shalini6
    1Department of Seed Science and Technology, College of Agriculture, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur-208 002, Uttar Pradesh, India.
    2Department of Agronomy, College of Hill Agriculture, Chirbatiya, Veer Chandra Singh GarhwaliUttarakhand University of Horticulture and Forestry, Camp at Ranichauri-249 199, Uttarakhand, India.
    3College of Forestry, Veer Chandra Singh Garhwali Uttarakhand University of Horticulture and Forestry, Ranichauri-249 199, Uttarakhand, India.
    4Department of Agronomy, ICAR- National Institute of Seed Science and Technology, Mau-275 103, Uttar Pradesh, India.
    5Department of Natural Resource Management, College of Horticulture, Veer Chandra Singh Garhwali Uttarakhand University of Horticulture and Forestry, Bharsar-246 123, Uttarakhand, India.
    6Department of Agronomy, Krishi Vigyan Kendra, Hamirpur, Banda University of, Agriculture and Technology, Banda-210 505, Uttar Pradesh, India.

    • Submitted28-10-2025|

    • Accepted05-02-2026|

    • First Online 23-02-2026|

    • doi 10.18805/BKAP895

    ABSTRACT

    Background: The investigation was conducted to study the effect of various agronomic factors viz., geometry and fertility levels on growth dynamics and yield of quinoa (Chenopodium quinoa Willd.), often referred to as superfood and also called “the mother grain”.

    Methods: The investigation was conducted in kharif 2022, with genotype “EC507742” at mid-hill region of Uttarakhand, India comprising of two factors viz., geometry (S): S1- 20 cm × 10 cm, S2- 30 cm × 10 cm and S3- 40 cm × 10 cm as main plots and fertility levels (F): F1- Control, F2- 75% NPKS, F3- 100% NPKS and F4- 125% NPKS as sub plots with total of 12 treatment combinations that were evaluated in split plot design with three replications and analysed using OPSTAT with figures from SAS (proc glm).

    Result: The 30 cm × 10 cm spacing was found effective in field conditions compared to other crop geometries, indicating to be more suited for quinoa cultivation under 100% NPKS fertilizer application which produced best growth dynamics, yield characteristics and yield for quinoa. The interaction between the 30 cm × 10 cm spacing and 100% NPKS fertilizer was significant in recording the highest growth dynamics and yield. Analysis indicates that quinoa responds very well to fertilizer dose of 100% NPKS at an optimum spacing of 30 cm × 10 cm.

    INTRODUCTION

    Quinoa (Chenopodium quinoa) is a remarkable, resilient and versatile crop with deep historical roots dating back over 5,000 years. Indigenous to the Andean region of South America, it was cultivated by ancients and revered sacred status as the “mother grain”. Today, quinoa has trans-formed from a traditional dietary staple into much sought-after superfood, embraced by health-conscious individuals worldwide. One of quinoa’s most compelling attributes is its exceptional nutritional content as it is gluten-free and contains all nine essential amino acids, making it a complete protein vital for human well-being. Additionally, it is rich in dietary fibre, vitamins, minerals and antioxidants, making it a powerhouse of nutrition addressing malnutrition concerns besides promoting overall health and vitality. The rising global demand for quinoa has created significant economic opportunities for farmers and exporters in quinoa cultivating regions. As consumers recognize its nutritional benefits, the crop’s market value continues to grow, becoming a vital income source for small-scale farmers. This economic advancement empowers local communities in developing areas.
           
    Fertility level can play a crucial role in enhancing seed quality of quinoa, which directly enhances the plant growth and development, besides increasing seed yield and better seed quality. Proper nutrient application also influences the nutritional composition of quinoa seeds. The research by Miranda et al. (2012) found that increasing nitrogen levels boosts seed protein content, while higher fertility levels can increase the concentration of essential minerals. However, excessive fertilization should be avoided, as it can compromise seed quality. The overuse of fertilizers, combined with inefficient resource management, deteriorate soil health and pose environmental risks (Yadav et al., 2024). In addition to fertility, plant geometry is a key agronomic factor for improving crop yields (Cha et al., 2016). The lack of proper crop geometry in the broadcasting method results in poor plant distribution, difficulties in intercultural operations, inefficient use of soil moisture and nutrients and higher competition among plants (Kumbhar et al., 2026). Quinoa is sensitive to afferent spacing, fertilizer types and application rate. However, optimal plant density ensures efficient resource utilization like water, nutrients and sunlight resulting in better plant growth and develop-ment, higher seed production and enhanced nutrient accu-mulation in seeds. Plant geometry can affect the competition for resources among individual plants, which lead to a decrease in stress and promoting more consistent seed yield. 
                   
    To maximize quinoa yields, farmers must adopt an integrated approach that carefully balances fertility manage-ment, plant geometry, irrigation and pest control. Optimal spacing and nutrient application ensure uniform seed development and improved germination rates, while adequate nutrient availability contributes to a high germination rate. Moreover, genetic factors and environ-mental conditions also significantly influence seed quality. By understanding these interconnected factors, farmers can enhance their production systems to achieve higher yields. Sustainable farming practices are essential to maintain quinoa’s nutritional value while preserving ecosystem health. Considering these critical aspects, this study was conceived to determine the ideal cropping geometry and fertility levels for optimizing quinoa growth, yield characteristics and productivity in the mid-hill regions of Uttarakhand, India.  

    MATERIALS AND METHODS

    A field experiment was conducted in kharif 2022 at Research and Extension Centre, Gaja, College of Forestry, Ranichauri (Tehri Garhwal), located in latitude 30o16’17’’N, longitude 78o25’21’’E at an altitude of 1700-1760 m above sea level in the chilly temperature. The experiment was laid out in spilt plot design with three replications having three different crop geometries (S1: 20 cm ×  10 cm, S2: 30 cm × 10 cm and S3: 40 cm × 10 cm) in main plot and four fertility levels (F1: Control, F2: 75% NPKS, F3: 100% NPKS and F4: 125% NPKS) in sub plot under tropical to subtropical zone of Uttarakhand. The mean maximum and minimum temperature, rainfall, relative humidity at morning and afternoon, wind speed and bright sunshine was 24.2oC, 13.1oC, 7.7 mm, 87.1%, 76.7%, 4.0 kmph and 6.0 hr/day, respectively during the crop growing period (Fig 1).

    Fig 1: Weekly meteorological data during crop season (26 May to 30 September, 2022).


                   
    The experimental soil was silty clay loam in texture, medium in availability of nitrogen (242 kg/ha) and phosphorus (22 kg/ha), higher in available potassium (404 kg/ha) and organic carbon (0.75%) with slightly acidic pH (6.1). The genotype “EC507742” was used for the experiment, sown on 26 May 2022. The crop was applied with recommended dose of fertilizer i.e., 40:20:20:20 NPKS in the form of urea, NPK (12:32:16) and Bentonite S, respectively. Entire dose of NPK and S was applied as basal through placement in the furrows made with hand hoes 5 cm away from seed rows and at a depth of 2 cm below the seed zone as per the treatments. Thinning after one irrigation was done to facilitate uniform germination of the crop at 25 days after sowing (DAS). Two hand weedings were done manually at 30 and 60 DAS to keep the crop free from weeds. During the seed formation stage, sucking pest was noticed and was controlled by spraying imidacloprid @ 0.2 ml l-1 of water.  Anthracnose was observed after heavy rainfall in crop and was controlled by mancozeb @ 2 g l-1 of water. Growth dynamics, yield attributes and yield from random selected five plants from each net plot was recorded and the mean value was worked out. The crop was harvested on 02 September 2022. The experimental data obtained during the course of investigation was analysed by using split plot design (SPD) with OPSTAT Programme designed and development by O.P. Sheoran, Computer Programmer at CCS HAU, Hisar, India and figure from SAS (proc glm).

    RESULTS AND DISCUSSION

    Growth dynamics
     
    Plant population growth rate
     
    Plant population growth rate of quinoa was significantly influenced by geometry and fertility levels at different stages of crop growth i.e. 30-60 DAS, 60-90 DAS and 90 DAS-harvest (Table 1). Among different geometries, significantly higher plant population growth rate was attained in S2 than other geometry. Among different fertility levels, plant population growth rate was statistically more in F3 being at par with F4 at 30-60 DAS, F4 which was at par with F3 at 60-90 DAS and significantly highest in F4 at 90 DAS-harvest. Plant population growth rate showed significant variations in interaction effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS, 60-90 DAS and 90 DAS-harvest as per tukey grouping. The plant population growth rate was significantly more in S2F3 among all the interactions between geometries with different fertility levels that was at par with S2F4 and S1F4 as per tukey grouping at 30-60 DAS (Fig 2) and at 60-90 DAS along with S2F2 (Fig 3). However, at 90 DAS-harvest significantly higher plant population growth rate was found in S2F4 being at par with S2F3, S1F4 and S2F2 as per tukey grouping (Fig 4). This significant increase might be potentially attributable to favourable conditions such as ample sunlight, moisture and accessible nutrients which are conducive to promoting rapid plant propagation, a finding corroborated by Parameswari et al., (2003). The wider spacing between plants resulted in improved growth parameters, primarily because it minimized the competition among plants for crucial resources such as space, light, moisture and nutrients, are indispensable for their optimal growth and development. This observation concurs with the findings of Sarkar and Malik (2004). A marked increase in plant height at close spacing might be attributed to higher plant population density which might have resulted in less plant canopy area and more vertical growth by producing weak and tall plants due to competition for space, light, nutrients and moisture compared to those at wider spacing (Shrikanth et al., 2008). Attar et al. (2013) also reported increased plant height with narrow spacing. Nutrients are crucial elements of proteins, nucleotides, chlorophyll and enzymes and hence facilitate numerous metabolic processes in plants, resulting in increased output (Sharma et al., 2023).

    Table 1: Effect of geometry and fertility levels on growth dynamics of quinoa.



    Fig 2: Plant population growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.



    Fig 3: Plant population growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.



    Fig 4: Plant population growth rate at 90 DAS-harvest as per Tukey grouping of geometry and fertility levels.


     
    Crop growth rate
     
    Crop growth rate of quinoa was not significantly influenced by geometry while it was significantly influenced by fertility levels at different stages of crop growth i.e. 30-60 DAS and 60-90 DAS except 90 DAS-harvest. Among different geometries, higher crop growth rate was attained in S2 followed by S1 and S3 at 30-60 DAS and S1 followed by S2 and S3 at 60-90 DAS and at 90 DAS-harvest. Among different fertility levels, crop growth rate was significantly higher in F4 at 30-60 DAS and at 60-90 DAS that was statistically at par with F2 at 30-60 DAS. However, it was higher in F4 followed by F2, F3 and F1 at 90 DAS-harvest (Table 1).
           
    Crop growth rate showed significant variations in interactive effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS and 60-90 DAS except 90 DAS-harvest as per tukey grouping. The crop growth rate was obtained statistically highest in S2F4 among all the interactions between geometries with different fertility levels which was at par with S3F2 and S1F4 as per tukey grouping at 30-60 DAS (Fig 5).

    Fig 5: Crop growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.


           
    At 60-90 DAS, it was statistically higher in S3F2 being at par with S2F4 and S1F4 (Fig 6). However, at 90 DAS-harvest, there was non-significant variations in interactive effect on crop growth rate were observed among geometries with different fertility levels (Table 1).

    Fig 6: Crop growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.


           
    The reduced plant height was observed in closer spacing that can be attributed to increased competition among plants for essential resources such as nutrients and light. In contrast, wider spacing decreases this competition, leading to increased plant height. These findings are in line with the research conducted by Rishi and Galwey (1991) but contradict the findings of Smitha et al. (2011). Additionally, it was noted that plant height exhibited a progressive increase with higher NPK levels, with the combination of the highest NPK levels resulting in the greatest plant height. The greater plant height can be ascribed to the abundant availability of nitrogen and phosphorus, facilitating improved photosynthesis and overall vigour. Phosphorous is an essential nutrient both as a part of several key plant structure compounds and also as a catalyst in conversion of numerous key biochemical reactions in plant like photosynthesis, respiration, cell elongation, cell division, activation of Amino acid for synthesis of protein and carbohydrate metabolism, also helps in formation of energy rich phosphate bonds, phospholipids and development of root system and nodulation which contributed to increase in general health and vigour of plant. Phosphorous also important for its role in capturing and converting sun’s energy into useful plant compounds. Phosphorous also associated with different metabolic activities that leads to better translocation of nutrients that leads to better expression of characters like increased stem strength, increased stalk and stimulated root development. With wider row spacing helped in reducing inter and intra plant competition thus helped in efficient utilization of solar radiation, nutrients and water which leads plants to better filling of available space by initiating branches. The study was in close conformity with Shukla et al. (2017). These observations are consistent with the results reported by Balliu et al. (2007), Abdelaziz et al. (2008) and Yasuor et al., (2013).
     
    Leaves per plant growth rate
     
    Leaves per plant growth rate of quinoa were significantly influenced by geometry and fertility levels at different stages of crop growth i.e. 30-60 DAS and 60-90 DAS. Among different geometry the leaves per plant growth rate were significantly highest in S2 at different stages of crop growth. Among different fertility levels, leaves per plant growth rate were significantly higher in F3 that was at par with F4 and vice-versa at various crop growth stages (Table 1). Leaves per plant growth rate showed significant variations in interactive effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS and 60-90 DAS as per tukey grouping. The significantly superior leaves per plant growth rate was found in S2F3 among all the interactions between geometries with different fertility levels which was at par with S2F4 at 30-60 DAS (Fig 7). At 60-90 DAS, it was statistically higher in S1F4 being at par with S2F3, S2F4 and S2F2 (Fig 8). The results obtained are likely due to the augmented level of fertilizer, which stimulates the synthesis of chlorophyll and fosters vegetative growth, resulting in an increase in the number of leaves and branches in the plants. These findings are in corroboration with the results reported by Kumar and Sudhavani (2004).

    Fig 7: Leaves per plant growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.



    Fig 8: Leaves per plant growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.


     
    Branches per plant growth rate
     
    Branches per plant growth rate of quinoa were significantly influenced by geometry and fertility levels at different stages of crop growth i.e. 30-60 DAS and 60-90 DAS. Among different geometry, significantly higher branches per plant growth rate were attained in S2 at different stages of crop growth. Among different fertility levels, branches per plant growth rate were significantly higher in F3 which was statistically at par with F4 at different crop growth stages (Table 1). Branches per plant growth rate showed significant variations in interaction effect among geometries with different fertility levels at various stages of crop growth i.e. 30-60 DAS and 60-90 DAS as per tukey grouping. The significantly higher branches per plant growth rate was found in S2F3 among all the interactions between geometries with different fertility levels which was at par with S1F4, S2F4 and S2F2 as per tukey grouping at 30-60 DAS (Fig 9). At 60-90 DAS, it was statistically higher in S2F3 being at par with S2F4, S1F4, S2F2 and S1F3 (Fig 10).

    Fig 9: Branches per plant growth rate at 30-60 DAS as per Tukey grouping of geometry and fertility levels.



    Fig 10: Branches per plant growth rate at 60-90 DAS as per Tukey grouping of geometry and fertility levels.


           
    In closely spaced crops, the intense competition for light, space, moisture and nutrients leads to reduced branching and a lower leaf count. These conclusions align with the findings reported by Yeboah et al. (2014). More number of branches/plant at 100% RDF may be due to the availability of optimum phosphorous content which may have attributed to the fact that phosphorus helped in producing a higher nodulation count, which resulted in higher nitrogen fixation which led to the production of more branches for higher photosynthetic ability (Ndor, 2012).
     
    Yield attributes and yield
     
    Panicle fresh weight (g)
     
    Panicle fresh weight of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, significantly higher panicle fresh weight was attained in S2. Among different fertility levels, panicle fresh weight was significantly higher in F4 being at par with F3 (Table 2). Significant variations in interactive effect on panicle fresh weight were observed among geometries with different fertility levels as per tukey grouping. The significantly higher panicle fresh weight was recorded in S2F3 which was statistically at par with S2F4 and S1F4 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 11). This could possibly be attributed to the availability of nutrients to the plants and the improved uptake of elements, especially nitrogen, resulting from the application of fertilizers. Consequently, plants exhibited enhanced nutrient absorption, leading to growth and an increase in the yield attributes and yield.

    Table 2: Effect of geometry and fertility levels on yield attributes and yield of quinoa.



    Fig 11: Panicle fresh weight of quinoa as per Tukey grouping of geometry and fertility levels.


           
    The application of phosphorus may have led to an accumulation of carbohydrates, which were subsequently mobilized to the reproductive parts of the plants. The significance of potassium, a highly mobile nutrient in plants, should not be overlooked, as it plays a vital role in the elongation and division of young tissues and contributes to maintaining turgor pressure. Moreover, it improves both the quality and yield of the plants. These findings are consistent with the research conducted by Nath et al. (2008) in ajwain and Mehta et al. (2011) in fennel.
     
    Number of fingers
     
    Number of fingers of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, significantly higher number of fingers was significantly attained in S2. Among different fertility levels, number of fingers was significantly higher in F3 which was found equal to F4 (Table 2). Significant variations in interactive effect on number of fingers were observed among geometries with different fertility levels with significantly higher in S2F3 among all the interactions between geometries with different fertility levels being at par with S2F4 as per tukey grouping (Fig 12). These findings are consistent with the research conducted by Nath et al. (2008) in ajwain and Mehta et al. (2011) in fennel.

    Fig 12: Number of fingers of quinoa as per Tukey grouping of geometry and fertility levels.


     
    Finger length (cm)
     
    Finger length of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, higher finger length was significantly attained in S2. Among different fertility levels, finger length was significantly higher in F3 (Table 2).
           
    Significant variations in interactive effect on finger length were observed among geometries with different fertility levels with significantly higher in S2F3 which was statistically at par with S2F4 and S1F3 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 13). This was might be due to the application of phosphorus may have led to an accumulation of carbohydrates, which were subsequently mobilized to the reproductive parts of the plants. Potassium plays a vital role in the elongation and division of young tissues and contributes to maintaining turgor pressure.

    Fig 13: Finger length of quinoa as per Tukey grouping of geometry and fertility levels.


     
    Test weight (g)
     
    Test weight of quinoa was non-significantly influenced by geometry, while it was significantly influenced by fertility levels. Among different geometry, higher test weight was attained in S2 followed by S1 and S3. Among different fertility levels, test weight was significantly higher in F3 which was found equal to F4 being statistically at par with F2. Non-significant variations in interaction effect on test weight were observed among geometries with different fertility levels (Table 2). Increase in weight of 100 seeds with spacing might be due to better availability of nutrients and less competition between plants for nutrients, water and sunlight which may have enhanced photosynthetic activities and resulted in more weight of 100 seeds.
     
    Seed yield (kg/ha)
     
    Seed yield of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, higher seed yield was attained in S2 which was significantly equal to S3. Among different fertility levels, seed yield was significantly higher in F3 which was statistically at par with F4 (Table 2).
           
    Significant variations in interactive effect on seed yield were observed among geometries with different fertility levels as per tukey grouping. The significantly higher seed yield was found S2F3 which was statistically at par with S2F4 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 14). The maximum yield attributes under widest spacing may be owing to maximum increase in the growth parameters (height, branches, leaves, stem diameter and plant spread) which means adequate photosynthates production and greater partitioning of metabolites and nutrients towards the reproductive organs. This eventually happened because of reduced competition between widely spaced plants for space, light, nutrients and moisture. These favourable conditions increased the growth parameters up to maximum extents. These results are in close agreement with those Bajpai et al., 2004; Singh et al., 2005; Ram et al., 2013 and Loria et al., 2022. The application of an increased fertilizer dosage resulted in enhanced growth and yield-related traits, leading to seed yield, crop residue and biological yield. These consistent outcomes correspond to the findings of Okeleye and Okelana (1997).

    Fig 14: Seed yield of quinoa as per Tukey grouping of geometry and fertility levels.


           
    The lowest values of plant growth parameters were recorded in control with narrower spacing. This might be due to the fact that non-availability of nutrient at early growth period reduced the plant growth significantly.
     
    Biological yield (kg/ha)
     
    Biological yield of quinoa was significantly influenced by geometry and fertility levels. Among different geometry, higher biological yield was attained in S2. Among different fertility levels, biological yield was significantly higher in F4 which was statistically at par with F3 (Table 2).
                   
    Significant variations in interactive effect on biological yield were observed among geometries with different fertility levels as per tukey grouping. The significantly higher biological yield was found S2F4 which was statistically at par with S2F3 and S1F4 among all the interactions between geometries with different fertility levels as per tukey grouping (Fig 15). The enhanced reproductive growth allowed for an expanded gap between plants, facilitating enhanced sun exposure and increased nourishment. These outcomes correspond to the findings of Patel et al. (2008).

    Fig 15: Biological yield of quinoa as per Tukey grouping of geometry and fertility levels.

    CONCLUSION

    Based on the experimental findings it can be concluded from the investigation that under mid-hills of Uttarakhand, optimal plant geometry of 30 cm × 10 cm with balanced fertilization of 100% NPKS is highly efficient and can be preferred for maximum growth and yield of quinoa. 

    ACKNOWLEDGEMENT

    The authors are thankful to the facilities provided by All India Coordinated Research Network- Potential Crops and the institutional support provided by the College of Forestry, V.C.S.G. Uttarakhand University of Horticulture and Forestry, Ranichauri, Tehri Garhwal, Uttarakhand, for the successful conduct of the research.
     
    Authors’ contributions
     
    Pratiksha Raj: Data curation, Formal analysis, Writing-original draft, Investigation. Arunima Paliwal: Supervision, Methodology, Resources, Validation, Writing-review and editing. Ravishankar Dubey and Aditya Raj Bisht: Data curation, Writing-original draft. Ajay Kumar: Methodology, Resources, Data curation, Writing-review and editing. Gargi Goswami: Methodology, Writing-review and editing. Shalini: Validation, Writing-review and editing.
     
    Funding
     
    Not funded.
     
    Research content
     
    Research content of this manuscript is original and has not been published or communicated elsewhere.
     
    Ethical approval
     
    Not applicable.
     
    Data availability
     
    All data generated and analysed are included in the research article.
     
    Consent to publish
     
     All authors agree to publish research article in Agricultural Science Digest.

    CONFLICT OF INTEREST

    On behalf of all authors, the corresponding author states that there is no conflict of interest.

    REFERENCES


    1. Abdelaziz, M.E., Ahmed, A.H.H., Bekhid, R.S. and Pokluda, R. (2008). Response of growth patterns in sweet pepper to different NPK levels. Acta Universitatis Agriculture Silvicultural Madelaine Brunensis. 56(1): 241-244. 

    2. Attar, A.V., Patil, B.T., Bhalekar, M.N. and Sinde, K.G. (2013). Effect of spacing and fertilizers levels on growth, yield and quality of garden pea (Pisum sativum L.) cv. Phule Priya. Bioinfolet. 10(4B): 1240-1242.

    3. Bajpai, V.P., Khan, A.A., Kumar. S., Singh, P. and Singh, C.B. (2004). Effect of spacing and sowing dates on growth and seed quality of okra (Abelmoschus esculentus). Farm Sci. 113(2): 116-117.

    4. Balliu, A., Bani, A. and Sulce, S. (2007). Nitrogen effects on the relative growth rate and its components of pepper (C. annuum) and eggplant (Solanum melongena) seedlings. Acta Universitatis Agriculture Silviculture Madeliene Brunensis. 56(1): 241-244. 

    5. Cha, M.K., Jeon, Y.A., Son, J.E. and Cho, Y.Y. (2016). Development of planting-density growth harvest (PGH) charts for quinoa (Chenopodium quinoa Willd.) and sow thistle (Ixeris dentata Nakai) grown hydroponically in closed-type plant production systems. Hort. Environ. Biotechnol. 57(3): 213-218. 

    6. Kumbhar, N.M., Thombare, P.D., Gholkar, M.D. and Wani A.G. (2026). Energy indices, productivity and profitability of rainfed chickpea (Cicer arietinum L.) influenced by crop geometry and nutrient management practices. Agricultural Reviews. 47(1): 122-130. doi: 10.18805/ag.R-2731.

    7. Kumar, R.K. and Sudhavani, V. (2004). Effect of plant densities and phosphorus levels on the growth and yield of vegetable cowpea. Department of Horticulture, College of Horticulture, Venkataramannagudem. 534: 101.

    8. Loria, K., Kumari, M., Sood, Y., Vikas, Lalita, Rani, S. and Himangini. (2022). Effect of seed rate and seed spacing on yield attributes of chickpea. Agricultural Science Digest. doi: 10. 18805/ag.D-5565.

    9. Mehta, R.S., Anwer, M.M. and Aishwath, O.P. (2011). Growth and yield of fennel (Foeniculum vulgare Mill.) as influenced by irrigation, nutrient levels and crop geometry. Journal of Spices and Aromatic Crop. 20(2): 77-80. 

    10. Miranda, M., Vega-Gálvez, A., Quispe-Fuentes, I., Rodríguez, M.J., Maureira, H. and Martínez, E.A. (2012). Nutritional aspects of six quinoa (Chenopodium quinoa Willd.) ecotypes from three geographical areas of Chile. Chilean J. of Agri. Res.  72(2): 175. 

    11. Nath, P., Jaiswal, R.C., Verma, R.B. and Yadav, G.C. (2008). Effect of date of sowing, nitrogen levels and spacing on growth and yield of ajwain (Trichyspermum ammi L.). Journal Spices Aromatic Crops. 17(1): 1-4. 

    12. Ndor, E., Dauda, N.S., Abimuku, E.O., Azagaku, D.E. and Anzaku, H. (2012). Effect of phosphorus fertilizer and spacing on growth, nodulation count and yield of cowpea [Vigna unguiculata (L) Walp] in southern Guinea savanna agroecological zone, Nigeria. Asian Journal of Agricultural Sciences. 4(4): 254-57.

    13. Okeleye, K.A. and Okelana, M.A.O. (1997). Effect of phosphorus fertilization on nodulation, growth and yield of cowpea (Vigna unguiculata) varieties. Indian Journal of Agriculture Science. 67(1): 10-12. 

    14. Parameswari, K., Vanangamudi, K. and Kavitha, S. (2003). Effect of spacing on hybrid seed yield of pigeon pea hybrid COPH2. Journal Madras Agriculture. 90: 691-696. 

    15. Patel, B.S., Patel, J.C. and Sadaria, S.G. (2008). Response of blond psyllium (Plantago ovata) to irrigation and phosphorus. Indian Journal of Agronomy. 4: 311-314. 

    16. Ram, Harischand, Khan, Mohd, Meraj and Singh, P.K. (2013). Effect of spacing and cultivars on growth and yield of okra (Abelmoschus esculentus L.). The Asian Journal of Horticulture. 8(2): 507-511.

    17. Rishi, J. and Galwey, N.W. (1991). Effect of sowing date and sowing rate on plant development and grain yield in a temperate environment. J. of Agri. Sci. 117: 325-332. 

    18. Sarkar, R.K. and Malik, G.C. (2004). Effect of method of planting and crop geometry on productivity of rainfed upland cotton grown low land rice fallows. Indian Journal of Agronomy. 49(4): 278-281. 

    19. Singh, J.P., Pandey, I.P., Shukla, I.N., Gautam, R.K.S. and Pandey, S.B. (2005). Effect of nitrogen, phosphorus and spacing on flowering, fruiting and yield of okra. Ann. Soil Res. 7(1): 85- 86.

    20. Smitha, P.A., Alagundagi, S.C., Mansur, C.P., Kubsaad, V.S., Hosamani, S.V. and Megeri, S.N. (2011). Effect of row spacing and seed rate on growth, fodder productivity and economics of amaranth genotypes. Karnataka Journal of Agriculture Science. 24(5): 651-653. 

    21. Shukla, R.D., Singh, A., Verma, S., Singh, A.K., Dubey, D. and Kumar, S. (2017). Effect of crop geometry and phosphorus levels on growth and productivity of chickpea (Cicer arietinum L.). Journal of Pharmacognosy and Phytochemistry. 6(5): 659-661.

    22. Shrikanth, A.S., Channaveerswami, S., Tirakannanavar, C.P. and Hosamani, R.M. (2008). Effect of spacings and fertilizer levels on crop growth and seed yield in lablab bean (Lablab purpureus L.). Karnataka Journal of Agricultural Sciences. 21: 440-443.

    23. Sharma, M., Shilpa, Kaur, M., Sharma, A.K. and Sharma, P. (2023). Influence of different organic manures, biofertilizers and inorganic nutrients on performance of pea (Pisum sativum L.) in north-western Himalayas. Journal of Plant Nutrition. 46: 600-617.

    24. Yadav, S.L., Debnath, S., Singh, Y., Singh, S.K., Devi, Y.B., Ghosh, A., Ram, A., Kumar, S. and Arunachalam, A. (2024). Influence of varied nutrient management strategies on yield,nutrient absorption and grain protein content in chickpea (Cicer arietinum L.). Indian Journal of Agricultural Research. 59(7): 1119-1125. doi: 10.18805/IJARe.A-6255.

    25. Yasuor, H., Gal, A. Ben, Yermiyahu, U., Yannai, E. Beit and Cohen, S. (2013). Nitrogen management of greenhouse pepper production: Agronomic, Nutritional and environmental implications. Horticulture Science. 48(10): 1241-1249.

    26. Yeboah, S., Dangquah, E. Owusu, Lamptey, J.N.L., Mochiah, M.B., Lamptey, S., Oteng- Darko, P., Adama, I., Appiah-Kubi, Z. and Agyeman, K. (2014). Influence of planting methods and density on performance of chia and its suitability as an oilseed plant. Agriculture Science. 2(4): 14-26. 
    In this Article
      Contact us
      Follow us
      Published In
      Bhartiya Krishi Anusandhan Patrika

      Editorial Board

      View all (0)