Synergistic Effects of Nitrogen Fertilization and Row Spacing on Antioxidative Defense Mechanisms and Nitrogen Metabolism Dynamics During Reproductive Stages in Quinoa (Chenopodium quinoa Willd.)

Synergistic Effects of Nitrogen Fertilization and Row Spacing on Antioxidative Defense Mechanisms and Nitrogen Metabolism Dynamics During Reproductive Stages in Quinoa (Chenopodium quinoa Willd.) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Synergistic Effects of Nitrogen Fertilization and Row Spacing on Antioxidative Defense Mechanisms and Nitrogen Metabolism Dynamics During Reproductive Stages in Quinoa (Chenopodium quinoa Willd.) Yan Deng, Xiaojing Sun, Yadi Sun, Chenglei Deng, Sumera Anwar, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7125526/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Optimizing nitrogen (N) fertilization and row spacing is crucial for enhancing quinoa ( Chenopodium quinoa Willd.) yield and stress tolerance, particularly at critical reproductive stages. This two-year field study evaluated the interactive effects of three N rates (90, 120, and 150 kg/ha) and three row spacings (20, 40, and 60 cm) on N metabolism and antioxidative responses during reproductive growth. Key enzyme activity in N metabolism, including nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH), were measured across five growth stages alongside antioxidant enzymes (SOD, POD, and CAT). The combination of 150 kg/ha N and 40 cm row spacing significantly enhanced NR, GS, and GOGAT activities, particularly during the grain-filling stages, thereby improving N assimilation and translocation. Wider row spacing (60 cm) and higher N rates maximized GDH activity at flowering, which is crucial for mitigating oxidative stress. Antioxidant enzyme activities were highest during grain filling, with rates of 120 and 150 kg/ha at 40 cm spacing, resulting in reduced malondialdehyde (MDA) content and indicating lower oxidative damage. Grain yield was strongly correlated with GS, GOGAT, and SOD activities during late grain filling, resulting in a 2.22-fold increase under 150 kg/ha N and 60 cm spacing compared to lower N and row spacings. These findings underscore the importance of optimizing N rates and row spacing in enhancing N metabolism and antioxidative defense during reproductive stages, providing actionable insights for improving quinoa productivity in resource-limited environments. Chenopodium quinoa Growth stages GS/GOGAT Peroxidase Catalase Malondialdehyde Grain yield Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Quinoa ( Chenopodium quinoa Willd.) has gained considerable attention as a versatile and resilient pseudo-cereal crop due to its nutritional value and ability to thrive under adverse environmental conditions (Kumar et al., 2024 ). It is particularly high in protein, renowned for its content of all nine essential amino acids, making it a complete protein —a rarity among plant-based foods (Abou-Amer and Kamel, 2011 ; Präger et al., 2011; Wieme et al., 2020 ). Furthermore, it is naturally gluten-free, has a low glycemic index, and is abundant in essential minerals such as magnesium, phosphorus, and copper (Präger et al., 2011; Arneja et al., 2015 ). In recent years, China has emerged as a significant region for quinoa cultivation, particularly in arid and semi-arid areas such as Shanxi, Tibet, and Inner Mongolia. Quinoa's genetic variability enables it to adapt and grow under the most adverse environmental conditions, making it a valuable crop for cultivation in diverse climatic conditions, including low rainfall, poor soils, and temperature fluctuations (Li et al., 2024 ; Ren et al., 2024 ). This has led to its increasing popularity as a sustainable food source in China. However, optimizing its yield and improving agronomic practices remain key challenges. Continuous cropping typically results in the depletion of soil nutrients, necessitating proper fertilizer application (Cárdenas-Castillo et al., 2021 ; Deng et al., 2022; Li et al., 2024 ). Quinoa is recognized for its high nitrogen content, which makes nitrogen supply crucial for quinoa cultivation, as it directly affects photosynthesis, protein synthesis, and overall plant growth. Effective nitrogen fertilization strategies are crucial for maximizing grain yield and quality while minimizing environmental issues associated with excessive application. Research has highlighted the quinoa crop's ability to respond to N fertilization even at low rates (Cárdenas-Castillo et al., 2021 ). Adequate N supply enhances photosynthetic activity, biomass production, and grain development by regulating enzymatic and physiological activities in plants (Deng et al., 2023 ; Yang et al., 2024 ). However, excessive or insufficient nitrogen application can adversely affect plant metabolism and yield (Hoang et al., 2021 ). In the nitrogen-deficient soils of the Bolivian Altiplano, Cárdenas-Castillo et al. ( 2021 ) reported an increase in quinoa yield by nitrogen fertilizer up to 240 kg/ha, after which it plateaus and declines beyond 300 kg/ha of nitrogen. Nitrogen use efficiency decreases as N application increases (Almadini et al., 2019 ), highlighting the need for optimal fertilization rates to maximize yield while maintaining efficiency. Optimal N rates for quinoa typically range from 80 to 120 kg/ha, with variations depending on regional environmental factors, including soil fertility, water availability, and climate. Research in the Loess Plateau region indicates that an N rate of 120 kg/ha optimizes quinoa growth and yield, enhancing photosynthetic traits and reducing growth duration (Deng et al., 2024 ; Yang et al., 2024 ). Studies conducted under Mediterranean climatic conditions suggest that an N application of 150 kg/ha yields the highest grain yield and crude protein content for quinoa (Geren 2015 ). In northern African countries, quinoa is grown in marginal soils with limited fertility. Studies have found that 60–90 kg N/ha is sufficient to achieve satisfactory yields under rainfed conditions (Taaime et al., 2023 ). These studies highlight the need to optimize quinoa's nutrients under various agro-climatic conditions. Agricultural management practices, including sowing practices, row spacing, and planting density, play a crucial role in determining quinoa growth and yield (Yan et al., 2021 ). For instance, row spacing significantly affects resource competition, light interception, and nutrient availability among plants, ultimately influencing crop growth and grain yield. Previous studies have shown that narrow row spacing increases canopy closure, resulting in denser canopies and greater competition for light, water, and nutrients, which can restrict branching and reduce individual plant growth (Yan et al., 2021 ). Wider row spacing allows better light penetration, promotes lateral branching, and improves photosynthetic efficiency while reducing the risk of lodging (Zulkadir et al., 2021). It also enhances root expansion, nutrient uptake, and water use efficiency, particularly in resource-limited environments such as arid and semi-arid regions. However, increasing row spacing beyond the optimal range decreases yield per area because of fewer plants per unit area (Yan et al., 2021 ). A similar study in a Mediterranean climate found a yield reduction of quinoa with increasing row spacings from 26 to 80 cm (Asher et al., 2022 ). Yan et al. ( 2021 ) studied the effects of planting density and row spacing on quinoa yield in northern Shanxi Province and found that the optimal planting density of 9 × 10⁴ plants/ha, combined with a row spacing of 60 cm, significantly improved grain yield, photosynthetic traits, and lodging resistance. Combining optimal row spacing with appropriate N fertilizer and crop variety selection can further enhance productivity. Tailoring row spacing to environmental conditions and employing precision agriculture techniques can ensure efficient resource use and maximize quinoa yield across diverse growing regions. Apart from yield-related traits, nitrogen metabolism and antioxidant enzyme activities play a pivotal role in determining plant growth and stress tolerance (Grewal et al., 2022 ; Solali et al., 2022). Specifically, these metabolic activities influence yield during critical reproductive stages, including ear emergence, flowering, grain filling, and maturity (Vásquez et al., 2024 ; Yang et al., 2024 ). Nitrogen-metabolizing enzymes, including nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamic acid dehydrogenase (GDH), regulate nitrogen assimilation, translocation, and utilization in plants, directly impacting grain yield (Deng et al., 2023 ; Yang et al., 2024 ). Higher enzymatic activities during reproductive stages promote efficient N uptake and distribution, facilitating grain development and yield formation (Deng et al., 2023 ; Li et al., 2025 ). Concurrently, antioxidant enzymes such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) protect plant tissues from oxidative stress caused by reactive oxygen species (ROS) during critical growth stages (Rashid et al., 2022 ). Nutrient deficiency can lead to increased oxidative stress, particularly at the onset of the reproductive stage, when plants require substantial amounts of nutrients (Deng et al., 2022). Elevated antioxidant activities have been linked to improved stress tolerance, grain filling, and yield in cereal crops under various environmental and management conditions (Abbas et al., 2024 ). Despite quinoa's growing popularity in regions with challenging agroclimatic conditions, limited research exists on optimizing nitrogen fertilizer rates and row spacing to maximize yield and stress resilience. This knowledge gap is particularly evident in semi-arid environments, where resource limitations require efficient nutrient and space management. We hypothesize that nitrogen-metabolizing enzymes and antioxidant activities during key reproductive stages (ear emergence, flowering, early grain filling, late grain filling, and maturity) play a significant role in yield formation under varying N levels and row spacings. This study aims to (a) evaluate the effects of nitrogen application rates and row spacing on quinoa grain yield, (b) investigate changes in antioxidant enzyme activities (SOD, POD, and CAT) and nitrogen-metabolizing enzymes (NR, GS, GOGAT, and GDH) during reproductive growth stages, and (c) analyze the relationships between antioxidant and nitrogen-metabolizing enzyme activities and yield components to identify key factors influencing quinoa yield. By addressing these objectives, this study will provide valuable insights into optimizing nitrogen management and planting strategies for quinoa cultivation in China, ultimately contributing to improved productivity and sustainable agricultural practices. 2. Materials and methods 2.1 Overview of the test site The experiment was carried out from 2023 to 2024 at an experimental facility located in Jingle County, Xinzhou City, Shanxi Province, China (38°3′N, 111°9′E). This site, situated over 2,000 meters above sea level, experiences a temperate monsoon climate characterized by four distinct seasons, with warm to hot summers and significant temperature fluctuations between day and night. The region boasts more than 2,500 hours of sunshine annually and enjoys an average frost-free period of 120 to 135 days. In 2023 and 2024, the average annual temperatures were recorded at 8.06°C and 9.13°C, respectively. The average annual rainfall measured 505.3 mm and 510.9 mm, respectively, in these years. On May 29, 2023, the basic nutrient composition of the 0–20 cm soil layer was analyzed, revealing 7.87 g/kg of organic matter, 0.95 g/kg of total nitrogen, 132 mg/kg of available potassium, 21.31 mg/kg of available phosphorus, and a pH level of 8.09. A subsequent analysis on May 28, 2024, showed an increase in soil organic matter content to 7.56 g/kg, with total nitrogen at 0.87 g/kg, available potassium at 126.02 mg/kg, available phosphorus at 17.52 mg/kg, and a pH of 8.2. 2.2 Experimental Design The experiment employed a two-factor randomized complete block design with three blocks. There were three nitrogen application levels: N1 (90 kg/ha), N2 (120 kg/ha), and N3 (150 kg/ha), alongside three row spacings: 20 cm, 40 cm, and 60 cm, denoted as R1, R2, and R3. In total, nine treatments were replicated three times, yielding 27 plots overall. The quinoa variety used in this experiment was BL77, supplied by Shanxi Huaqing Quinoa Product Development Co., Ltd., China. BL77 is a relatively low N-tolerant variety with a high yield (Deng et al., 2023 ). Each plot measured 50 m² (5 m × 10 m), the planting density was 69,000 plants per hectare, and seeds were sown at a depth of 1–2 cm, with a 1 m aisle maintained between plots. Urea (N ≥ 46%) was used as a nitrogen fertilizer. The row spacing was established by marking the inside of the plot with a tape measure, while a uniform plant spacing of 40 cm was ensured across all plots. Throughout the entire growth period, no artificial irrigation was employed, relying solely on natural precipitation for moisture. Pest and disease management was conducted using pesticides, while manual labor was used for weeding, with other cultivation practices adhering to local agricultural conditions. Quinoa seeds were sown on flat ground following land preparation on June 1 in both 2023 and 2024, with harvests occurring on October 20, 2023, and October 25, 2024. 2.3 Sampling and measurement Quinoa leaves were sampled at different growth stages, i.e. , ear emergence stage, flowering stage, early grain filling stage, late grain filling stage, and maturity stage. 15 to 20 quinoa leaves were collected from each plot and immediately wrapped in aluminum foil, transferred to the lab, frozen in liquid nitrogen, and stored in a freezer at -80°C. 2.3.1 Antioxidant enzyme activities The biochemical kits, prepared by Beijing Solarbio Science & Technology Co., Ltd. (Beijing, China), were used to determine the enzyme activities in quinoa leaves. The activity of superoxide dismutase (SOD) was determined using the SOD activity assay kit (Catalog No.: BC0170) based on its ability to inhibit the formation of formazan dye at 560 nm, where one unit was defined as the amount of SOD required to inhibit 50% of superoxide radical production under the assay conditions, according to the manufacturer’s protocol. The activity of peroxidase (POD) was measured using the POD activity assay kit (Catalog No.: BC0090). The assay quantifies POD activity based on the enzyme's ability to catalyze the reaction of hydrogen peroxide (H₂O₂) with a chromogenic substrate, resulting in the production of a colored product. The absorbance was measured at 470 nm, and one unit of POD activity is defined as the amount of enzyme required to catalyze the oxidation of 1 µmol of substrate per minute under the assay conditions, following the manufacturer’s protocol. The activity of catalase (CAT) was determined using the CAT activity assay kit (Catalog No. BC0205) based on its ability to decompose H₂O₂ into water and oxygen. The decrease in H₂O₂ concentration was monitored spectrophotometrically at 240 nm. One unit of catalase activity is defined as the amount of enzyme required to decompose 1 µmol of H₂O₂ per second under the assay conditions. Results of SOD, POD, and CAT were expressed as units per gram of protein (U/g protein). 2.3.2 Malondialdehyde content The malondialdehyde (MDA) content was determined using the MDA content assay kit (Catalog No. BC0020). The assay is based on the reaction of MDA with thiobarbituric acid (TBA) to form a pink-colored MDA-TBA adduct, which was measured spectrophotometrically at 532 nm. Results were expressed as nmol per gram of protein (nmol/mg protein), following the protocol provided by the manufacturer. 2.3.3 Nitrogen assimilation enzymes The activity of nitrate reductase (NR) was measured using the NR activity assay kit (Catalog No. BC0080), which quantified NR activity based on its ability to catalyze the reduction of nitrate to nitrite. The nitrite produced reacts with a color reagent to form a colored compound, which was measured spectrophotometrically at 540 nm. One unit of NR activity corresponds to the amount of enzyme that reduces 1 µmol of nitrate per minute under the assay conditions. The activity of glutamine synthetase (GS) was determined using the GS activity assay kit (Catalog No. BC0915). This assay evaluates GS activity by monitoring its role in synthesizing glutamine from glutamic acid and ammonium with ATP and Mg²⁺. The resulting glutamine is converted into gamma-glutamyl hydroxamic acid, which reacts with iron under acidic conditions to produce a red complex measurable at 540 nm. One unit of GS activity corresponds to the synthesis of 1 µmol of gamma-glutamyl hydroxamic acid per minute. The activity of glutamate synthase (GOGAT) was determined using the GOGAT activity assay kit (Catalog No. BC0070) by measuring its ability to catalyze the formation of glutamate from glutamine and α-ketoglutarate. The reaction product was quantified spectrophotometrically at 340 nm, with one unit defined as the amount of GOGAT enzyme required to catalyze the conversion of 1 µmol of glutamine per minute under the assay conditions. The activity of glutamic acid dehydrogenase (GDH) was analyzed using the GDH activity assay kit (Catalog No. BC1460). GDH catalyzes the oxidative deamination of glutamic acid, producing α-ketoglutarate and ammonia, accompanied by the reduction of NAD⁺ or NADP⁺. The decrease in absorbance at 340 nm due to NAD(P)H formation was monitored to calculate GDH activity. One unit of GDH is defined as the enzyme required to catalyze the oxidation of 1 µmol of glutamic acid per minute under the specified conditions. 2.4 Determination of yield During the quinoa maturity period, 10 plants with uniform growth were randomly selected from each plot. The panicle length on the main stem (primary panicle length) was taken with a tape measure. The number of branches was calculated from the branches with spikes at the bottom. At the same time, the quinoa spikes were placed in a mesh bag, dried in the sun, threshed and stored, and then weighed using a JM-a 20002 electronic balance. The seed sample was used to evaluate the yield. 2.5 Statistical analysis Pearson correlation coefficients (𝑅) were calculated to evaluate the relationships between grain yield and physiological and biochemical indices (e.g., SOD, POD, CAT) across five growth stages. Correlations were visualized as a heatmap using Python's Seaborn library, with annotations indicating the strength and statistical significance of the correlations. 3. Results 3.1 Antioxidant enzyme activities Nitrogen application rates and row spacings significantly influenced the activity of superoxide dismutase (SOD) (Table S1). Increasing N rates from 90 to 120 kg/ha resulted in a rise in SOD activity across all growth stages (Fig. 1 ). However, when N rates were further increased to 150 kg/ha, the responses varied, showing either increased or decreased SOD activity. Across different growth stages, the highest SOD activity was observed during early grain filling, followed by late grain filling, while the lowest activity occurred at ear emergence. Wider row spacings enhanced SOD activity compared to narrower spacings, suggesting improved management of oxidative stress due to better resource availability. The combination of higher N rates (N3) and wider row spacing (R3) resulted in maximum SOD activity at the flowering stage, indicating an enhanced capacity to mitigate oxidative stress during this critical period. Peroxidase (POD) activity exhibited a similar trend across all growth stages, with notable peaks during the early grain-filling stage (Fig. 2 ). POD activity significantly increased with higher nitrogen application rates, indicating greater scavenging of hydrogen peroxide during periods of high metabolic activity. Wider row spacings also correlated with higher POD activity, likely due to reduced competition among plants. The highest values were recorded with the combination of N3 and R3, particularly during grain filling, reflecting the plant's increased need to scavenge hydrogen peroxide during high metabolic activity. Catalase (CAT) activity consistently increased with N rates across all growth stages, reaching its peak during the early grain-filling stage (Fig. 3 ). The pairing of N3 and R3 produced maximum CAT activity during era emergence, flowering and early grain filling period, underscoring the importance of optimized nitrogen and spacing for enhancing antioxidant defense mechanisms. CAT activity rose significantly, with N rates increasing from 90 to 120 kg/ha. However, when the N rate was further increased to 150 kg/ha, the response varied depending on row spacing and growth stage. At 60 cm row spacings, CAT activity consistently increased with higher N rates at all growth stages. In contrast, at 20- and 40-cm row spacings, increasing the N rate from 120 to 150 kg/ha did not result in an increase or decrease in CAT activity. At lower and medium N rates, a 40 cm row spacing exhibited higher CAT activity compared to 20 or 60 cm row spacing. Overall, plants grown in wider row spacings showed greater CAT activity than those in narrower spacings, indicating improved stress mitigation. 3.2 Malondialdehyde content Malondialdehyde (MDA) content, an indicator of lipid peroxidation and oxidative stress, decreased significantly with higher N rates (Fig. 4 ). The MDA content was highest at 90 kg/ha and lowest at 150 kg/ha. The main effects indicate that MDA was highest at the flowering stage and lowest at the maturity stage (Table S2). The interactive effect of N and row spacing showed that the highest MDA at the ear emergence and flowering stage was observed at 40 cm at 90 kg/ha (Fig. 4 ). While at early grain filling, late grain filling, and maturity, the MDA content was highest at 60 cm row spacing at 90 kg/ha. 3.3 Nitrogen metabolism enzyme activities The activities of all N metabolizing enzymes were significantly affected by the N rate, row spacing, stages, and their interactions (Table S2). The interactive effect of N rate and row spacing indicates that the nitrate reductase (NR) activity was highest at the ear emergence and flowering stages under the combination of N3 and R3 (Fig. 5 ). This combination provided the most favorable conditions for nitrate assimilation, particularly during early growth stages when nitrogen demand was highest. The lowest NR activity was observed at maturity, at 90 kg/ha, with row spacings of 20 and 60 cm. The maximum glutamine synthetase (GS) and glutamate synthase (GOGAT) activities were observed during late grain filling, followed by maturity (Table S2). Among N rates, the highest GS and GOGAT activities were at 150 kg/ha, and the lowest at 90 kg/ha. Among row spacings, 40 cm row spacings had higher GS and GOGAT activities than 20 and 60 cm. The combination of 120 kg N/ha or 150 kg N/ha with 40 cm row spacing resulted in the highest GS and GOGAT activities at late grain filling (Figs. 6 and 7 ). Glutamate dehydrogenase (GDH) activity was significantly highest at flowering, while it was lowest at the ear emergence stage. Among N rates, the highest GDH activity was at 150 kg/ha, and the lowest was at 90 kg/ha. The N and row spacing interaction showed that the combination of 150 kg N/ha and 60 cm row spacing demonstrated the highest GDH activity at the flowering stage (Fig. 8 ). The maximum GDH activities were observed at the flowering stage, and then decreased with the progression of the reproductive stage (Fig. 9 ). At 90 kg/ha and 120 kg/ha, the GDH activities were significantly highest at 40 cm, but at 150 kg/ha, the maximum GDH activity from flowering to maturity was observed at 60 cm. 3.4 Yield traits The N rate and row spacing significantly affected the number of branches, but their interaction was non-significant in both years (Table 1 ). Increasing the N rate to 120 and 150 kg/ha significantly increased the number of branches. Similarly, increasing the row spacing to 40 and 60 cm resulted in a higher number of branches compared to 20 cm row spacing. Table 1 The effect of the application of different N rates and row spacings on grain yield and yield-related traits of quinoa at the maturity stage. N rate (kg/ha) Row spacings (cm) Grain yield (kg/ha) Number of branches Primary panicle length (cm) 1000-grain weight (g) 2023 2024 2023 2024 2023 2024 2023 2024 90 20 2471.11 ± 56.9 e 1933.42 ± 64.4 g 16.77 ± 1.49 d 15.12 ± 0.35 f 37.52 ± 1.04 de 29.17 ± 0.68 e 4.70 ± 0.04 g 3.56 ± 0.07 e 40 3196.49 ± 22.0 d 2848.45 ± 92.2 e 18.87 ± 1.32 cd 18.24 ± 0.66 e 40.10 ± 0.18 cd 32.48 ± 0.52 cd 4.81 ± 0.03 ef 3.77 ± 0.09 d 60 2079.21 ± 70.9 f 2274.48 ± 82.0 f 18.17 ± 1.44 cd 19.43 ± 0.05 de 36.47 ± 1.55 e 31.48 ± 0.41 d 4.51 ± 0.01 h 3.63 ± 0.05 de 120 20 3809.15 ± 107.9 c 3613.62 ± 97.2 cd 20.53 ± 1.01 bc 19.74 ± 0.13 cd 43.23 ± 0.74 a − c 38.64 ± 1.03 b 5.26 ± 0.13 d 4.68 ± 0.08 ab 40 4480.99 ± 110.0 a 3973.48 ± 126.8 ab 23.02 ± 1.20 a 21.17 ± 0.86 b 46.26 ± 0.62 a 41.84 ± 0.01 a 5.57 ± 0.02 b 4.79 ± 0.07 a 60 3775.14 ± 64.2 c 3528.41 ± 86.4 d 23.43 ± 1.65 a 22.49 ± 0.16 a 41.36 ± 1.18 bc 39.12 ± 1.06 b 4.79 ± 0.03 f 4.57 ± 0.02 b 150 20 3353.20 ± 80.3 d 3024.25 ± 78.0 e 19.62 ± 1.84 c 19.32 ± 0.61 de 41.95 ± 1.29 bc 34.26 ± 0.99 c 4.88 ± 0.05 e 4.22 ± 0.07 c 40 4198.91 ± 97.2 b 3814.48 ± 99.3 bc 22.42 ± 0.87 ab 20.85 ± 0.69 bc 44.05 ± 2.38 ab 40.75 ± 1.02 ab 5.45 ± 0.06 c 4.71 ± 0.04 ab 60 4625.06 ± 70.6 a 4131.35 ± 113.1 a 22.58 ± 0.64 ab 21.87 ± 0.62 ab 45.78 ± 2.16 a 42.42 ± 1.85 a 5.88 ± 0.02 a 4.83 ± 0.10 a ANOVA ( F -value) N 2454.05*** 1179.1*** 54.3*** 212.8*** 89.38*** 480.4*** 1430.8*** 1112.0*** RS 493.37*** 245.2*** 19.65*** 150.9*** 16.01*** 108.7*** 283.13*** 66.4*** N x RS 271.81*** 75.8*** 0.68ns 5.91ns 9.95*** 27.2*** 571.99*** 40.4*** Each value is a mean of 3 replicates ± standard error, and letters indicate significant differences by Tukey HSD test. *, **, and *** indicate significance at 0.05, 0.01, and 0.001 probability levels, respectively. ns = non-significant. The interaction of N rate and row spacing significantly affected primary panicle length, 1000-grain weight, and grain yield. The primary panicle length was highest at the combination of 120 kg/ha and 40 cm row spacing in 2023 and 150 kg/ha with 60 cm row spacing in 2024, although both treatments were statistically similar. In contrast, the lowest panicle length was observed at 90 kg/ha at 60 cm (in 2023) and 20 cm (in 2024). This indicates that higher row spacing favors a higher N rate. The increase in the N rate from 90 kg/ha to 150 kg/ha resulted in increased grain weight and yield (Table 1 ). Increasing the row spacing from 20 to 40 cm increased these traits, and further increasing the row spacing to 60 cm then started to decrease. The highest grain weight and grain yield were achieved at 150 kg/ha at a depth of 60 cm. The lowest grain weight and grain yield were observed at 90 kg/ha with row spacings of 60 cm (in 2023) and 20 cm (in 2024). The grain weight at 150 kg/ha at 60 cm was 2.22-fold higher than at 90 kg/ha at 60 cm row spacing in 2023 and 26.3% higher than at 90 kg/ha at 20 cm row spacing in 2024. Similarly, the grain yield at 150 kg/ha at 60 cm was 2.22 times higher than at 90 kg/ha at 60 cm in 2023 and 2.13 times higher than at 90 kg/ha at 20 cm in 2024. 3.5 Correlation of yield with N metabolism and antioxidant enzymes Grain yield showed strong positive correlations with enzyme activities (SOD, POD, CAT, NR, GS, and GOGAT) across all growth stages, with the highest correlations observed at maturity (Fig. 9 ). MDA content was the only trait that exhibited negative correlations with yield. Particularly, MDA content at early grain filling, late grain filling, and maturity showed a significant negative correlation with yield. 4. Discussion 4.1 Effect of nitrogen rate and row spacing on antioxidant enzyme activities Various stresses at the initiation of the reproductive stage accelerate oxidative stress and early senescence. Senescence, in turn, alters the source-sink relationship and significantly reduces crop yield (Kong et al., 2017; Yue et al., 2021 ; Tang et al., 2024 ). Furthermore, continuous cropping (Yang et al., 2022) and nutrient or water deficiency are common factors under field conditions (Deng et al., 2023 ), which cause oxidative stress (Fischer et al., 2013 ; Yaqoob et al., 2019 ). The activity of antioxidant enzymes, such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), protects plants from oxidative stress caused by reactive oxygen species (ROS) (Liao et al., 2023 ; Lu et al., 2024). In the present study, the CAT, POD, and SOD activities peaked at the early grain-filling stages, followed by the late grain-filling stages, while being least at ear emergence. The higher activity of antioxidants during reproductive growth is linked with source remobilization and grain-filling processes. The grain-filling stage is metabolically intensive, often leading to increased ROS production. Potential reasons for increased antioxidant activity at early grain filling are that certain growth stages inherently exhibit higher antioxidant activities to support developmental transitions and ensure successful reproduction (Lu et al., 2024). Early grain filling involves rapid biosynthesis and nutrient translocation, increasing ROS production. Elevated activities of CAT, SOD, and POD during early grain filling may help mitigate oxidative stress associated with rapid cellular activities, thereby ensuring proper grain development. The malondialdehyde (MDA) content also peaked at the flowering and grain-filling stages, indicating the presence of oxidative stress. While many studies focus on stress-induced antioxidant responses, the upregulation of these enzymes during key developmental stages under optimal conditions is also crucial for maintaining cellular homeostasis (Kong et al., 2017; Zhao et al., 2025 ). CAT, SOD, and POD activities in quinoa leaves increased with the application of higher N levels. Enzyme activities at 120 and 150 kg/ha were significantly higher than those at 90 kg/ha at all growth stages. The higher antioxidant activities might be because adequate nitrogen fertilization enhances metabolic processes, potentially leading to increased ROS, which plants then compensate for by boosting antioxidant defenses to maintain redox balance. The appropriate N supply increased antioxidant enzyme activities (Ru et al., 2023 ; Lu et al., 2024), enhancing stress tolerance and potentially supporting grain development (Liao et al., 2023 ). The higher antioxidant enzyme activities at the early grain-filling stage under varying N levels align with findings in other crops, where antioxidant enzyme activities are influenced by nitrogen fertilization and developmental stages, improving plant resilience and metabolic functions (Lu et al., 2024; Zhao et al., 2025 ). For instance, research demonstrated that increasing N rates up to 200 kg/ha significantly elevated SOD and POD activities in maize, contributing to improved grain yield (Yue et al., 2021 ). Higher N application (180 kg/ha) increased CAT and SOD activities, enhancing nitrogen use efficiency and grain yield in rice (Wang et al., 2022 ). SOD and POD activity was highest during grain filling under 120 and 150 kg/ha N rates, coupled with wider row spacings. CAT activities peaked at flowering and early grain filling, particularly under 150 kg/ha N at 60 cm spacing. This indicates that the enhanced antioxidant activity under optimal N rates and spacing minimized oxidative stress during critical reproductive stages. Reduced MDA levels further confirmed the effectiveness of these antioxidant defenses in sustaining grain filling and yield. 4.2 Effect of nitrogen rate and row spacing on nitrogen metabolizing enzymes Quinoa grains are recognized for their high nitrogen content, which directly contributes to their protein-rich composition. On average, quinoa grains contain 15–20% protein by weight, equivalent to approximately 2.5–3.2% nitrogen content (Abou-Amer and Kamel, 2011 ; Wieme et al., 2020 ). Therefore, appropriate nitrogen is required for grain development. Studies indicate that nitrogen fertilization plays a crucial role in determining quinoa protein content, grain development, and yield (Thanapornpoonpong et al., 2008 ; Abou-Amer and Kamel, 2011 ; Geren, 2015 ; Almadini et al., 2019 ; Cárdenas-Castillo et al., 2021 ). Nitrogen-metabolizing enzymes play a fundamental role in nitrogen assimilation, translocation, and remobilization, processes essential for grain filling and yield development in quinoa. These enzymes include nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH), which act sequentially to convert absorbed nitrate into biologically available forms of nitrogen for metabolic functions (Sonali et al., 2024 ). The results showed that nitrogen fertilizer rates, row spacing, growth stages, and their interactions significantly affected the activity of these enzymes (Figs. 5 – 8 ; Table S2). NR catalyzes the first rate-limiting step in reducing nitrate (NO₃⁻) into nitrite (NO₂⁻). NR activity was highest during ear emergence and flowering, particularly under 150 kg/ha nitrogen (N3) at 60 cm row spacing (R3). The increased NR activity with increasing N application is attributed to the availability of nitrogen substrates and the plant’s metabolic demand for nitrogen assimilation and remobilization (Sonali et al., 2022; Sun et al., 2024). At later stages, NR activity declined or stabilized, with peaks observed at 120 kg/ha N during grain filling. This trend suggests that higher nitrogen supply during early reproductive stages supports nitrate assimilation, providing substrates for protein synthesis and tissue development (Sonali et al., 2022; Sun et al., 2024). As the plants progressed toward maturity, reliance on remobilized nitrogen reserves increased, reducing NR activity (Sonali et al., 2024 ). Following nitrate reduction, ammonium (NH₄⁺) is assimilated through the GS/GOGAT pathway, which drives the incorporation of ammonium into amino acids, ensuring nitrogen is readily available for grain filling (Li et al., 2025 ). The GS and GOGAT activities increased with higher N rates (90–120 kg/ha). However, their activities declined at 150 kg/ha or below, particularly in narrow (20 cm) and wide (60 cm) row spacings, during the late reproductive stages of growth. This decline may reflect enzyme saturation at excessive nitrogen levels, resulting in reduced efficiency as nitrogen availability exceeds plant demand. Glutamine and glutamate serve as nitrogen carriers in the phloem, transporting nitrogen from senescing leaves to developing grains. GS and GOGAT activities increase during early and late grain filling to facilitate the conversion of stored nitrogen compounds (proteins and amino acids) into mobile amino acids such as glutamine and asparagine for phloem loading and translocation to grains (Sonali et al., 2022). Their activities decline during maturity as remobilization slows and grains approach physiological maturity. In addition, GDH activity was highest during flowering, especially under 150 kg/ha N and 60 cm spacing, where it likely played a complementary role in recycling nitrogen from older tissues to support new growth and grain filling (Sonali et al., 2022). GDH’s involvement in deamination may have ensured nitrogen balance under high metabolic demand, particularly during senescence and stress recovery (Miranda-Apodaca et al., 2020 ; Sonali et al., 2022). Overall, NR, GS, and GDH activities peaked at flowering, while GOGAT activity peaked at late grain filling. The possible reason for the stage-specific trends in enzyme activities is that at flowering, N uptake and assimilation are dominant, resulting in high NR, GS, and GDH activities. On the other hand, at grain filling, N remobilization and reassimilation are dominant, resulting in high GOGAT activity (Liang et al., 2011 ). These differences in trends in enzyme activities highlight the dynamic nitrogen demands across reproductive stages (Hirel et al., 2007 ; Sonali et al., 2024 ). NR activity during ear emergence and flowering supported early nitrate reduction and reproductive growth, while the GS/GOGAT pathway promoted amino acid synthesis and remobilization during grain filling (Sun et al., 2024). GDH activity further complements nitrogen utilization by recycling nitrogen during late reproductive stages, sustaining grain development under conditions of high nitrogen demand. The interplay between nitrogen assimilation and remobilization was optimized at 120 kg/ha N, where enzyme activities supported greater nitrogen reserves in vegetative tissues and their efficient translocation to grains. This combination resulted in higher yield and grain quality, demonstrating the importance of balanced nitrogen management. Conversely, higher N rates (150 kg/ha) may have induced luxury consumption, reducing enzyme efficiency and resulting in diminished nitrogen use efficiency during later stages (Almadini et al., 2019 ). These findings emphasize the critical role of nitrogen-metabolizing enzymes in regulating nitrogen assimilation, recycling, and translocation during reproductive stages (Sun et al., 2024). The results also highlight the need for appropriate N rates and row spacing to activate metabolic pathways, improving nitrogen utilization efficiency, protein content, and grain yield in quinoa. 4.3 Yield and correlation with antioxidative and nutrient metabolism Grain yield and related traits, such as panicle length, 1000 grain weight, and number of branches, are key indicators of quinoa productivity (Yan et al., 2021 ; Deng et al., 2023 ). These traits are influenced by N rates and row spacing, which regulate resource availability, nutrient uptake, and plant growth dynamics. Our results demonstrated that yield components responded positively to increasing N rates from 90 to 120 kg/ha across all row spacings. However, further increasing the N rate to 150 kg/ha reduced yield at 20 cm and 40 cm spacing, while it continued to improve at 60 cm spacing, suggesting an interaction between N supply and spatial arrangements. Plants grown at 60 cm row spacing with 150 kg/ha N achieved 17.1% and 22.5% higher grain yields and 5.7% and 22.7% heavier grains, respectively, in 2023 and 2024, compared to 120 kg/ha, indicating that wider spacing mitigated interplant competition and supported higher nitrogen uptake and utilization. In contrast, narrower spacing (20 cm) at 150 kg/ha likely led to resource competition and lodging, resulting in reduced yield, as observed in previous studies (Yan et al., 2021 ). These findings underscore the importance of balancing N rates and row spacing to optimize nutrient efficiency and yield formation. The higher nitrogen demand observed at wider row spacing (60 cm) could be attributed to improved root expansion, which enables greater soil exploration and nutrient absorption. Wider spacing reduces competition for light, water, and nutrients, thereby supporting the efficiency of photosynthesis and protein synthesis, which are critical processes during grain filling (Ebrahimikia et al., 2021 ). Additionally, quinoa's plastic root architecture adapts to spatial availability, promoting deeper root penetration at wider spacing, which facilitates better nitrogen uptake and water absorption (Schulte auf’m Erley et al., 2005). Increased nitrogen availability further stimulates the activities of NR, GS, GOGAT, and GDH, accelerating nitrate assimilation and remobilization to grains (Kakabouki et al., 2018 ; Sun et al., 2024). Our results align with studies reporting 120 kg/ha N as optimal for enhancing yield without compromising nitrogen use efficiency. Schulte auf’m Erley et al. (2005) reported quinoa yields ranging from 1790 to 3495 kg/ha with an average nitrogen utilization efficiency of 22.2 kg grain per kg N, which did not decline at higher N rates. Similarly, Sun et al. (2024) demonstrated that applying 120 kg/ha nitrogen using slow-release fertilizers achieved 4525.8 kg/ha, highlighting the role of fertilizer formulations in improving N efficiency. Higher N rates (> 120 kg/ha), particularly at narrower spacing (20 cm), likely promoted luxury consumption, resulting in nitrogen retention in vegetative tissues instead of efficient remobilization to grains (Almadini et al., 2019 ; Cárdenas-Castillo et al., 2021 ). This pattern was also observed in amaranth and quinoa, where increased nitrogen supplies delayed flowering, extended the vegetative phase, and reduced the harvest index (Ebrahimikia et al., 2021 ). Our study revealed that yield improvement was closely associated with antioxidative enzyme activities (POD, SOD, and CAT) during early grain filling, particularly under higher N rates. Elevated SOD and CAT activity at this stage likely reduced oxidative damage, thereby supporting protein synthesis and cell expansion, which are critical for grain development. Similar findings in wheat and rice link higher antioxidant activity to reduced oxidative stress and better nitrogen assimilation under adequate fertilization (Yue et al., 2021 ; Liao et al., 2023 ; Xue et al., 2024). The high antioxidant activity observed during early grain filling can be attributed to the increased metabolic activity and ROS production associated with rapid nutrient translocation and grain filling (Kong et al., 2017). Optimum N rates likely induced higher respiration rates and energy demands, necessitating antioxidative defenses to protect cellular integrity during this metabolically active phase (Sun et al., 2024; Yan et al., 2021 ). Approximately 50–70% of the total nitrogen remobilized within the plant accumulates in the grains (Sun et al., 2024). Higher activities of NR, GS, and GOGAT during the flowering and grain-filling stages likely facilitated nitrogen assimilation and remobilization, improving yield and grain quality. Concurrently, antioxidant enzymes mitigated oxidative stress, preventing premature senescence and ensuring optimal grain filling (Zhao et al., 2007 ; Panda and Sarkar, 2013 ). While MDA levels (lipid peroxidation) showed a negative correlation with yield, reduced MDA under higher N levels indicates lower oxidative stress and higher metabolic stability, supporting nitrogen efficiency and grain development (Deng et al., 2023 ). These patterns emphasize the importance of maintaining a balanced nitrogen supply and optimal row spacing to sustain yield formation without inducing stress-related losses. Conclusion This study highlights the critical role of nitrogen fertilization rates and row spacing in optimizing grain yield, nitrogen metabolism, and antioxidative responses in quinoa during reproductive stages. The combination of 120 kg/ha nitrogen at 40 cm row spacing proved optimal for most traits, including panicle length, grain weight, and 1000 grain yield, performing significantly similar to the highest yield achieved with 150 kg/ha nitrogen at 60 cm spacing. The superior performance at 120 kg/ha and 40 cm spacing resulted from enhanced nitrogen assimilation and remobilization, supported by increased activities of nitrate reductase (NR), glutamine synthetase (GS), and glutamate synthase (GOGAT). Additionally, antioxidant enzymes (SOD, POD, and CAT) were highly active during early grain filling, mitigating oxidative stress and ensuring efficient nutrient translocation for grain development. While higher N rates (150 kg/ha) at wider spacing (60 cm) further improved yield, they may have promoted luxury consumption and reduced nitrogen use efficiency, making 120 kg/ha at 40 cm a more balanced and sustainable choice for enhancing yield and quality. Declarations Ethics approval and consent to participate All participants provided written informed consent prior to participation, ensuring they understood the purpose of the study, their rights, and confidentiality measures. Consent for publication All authors have given their consent for the publication of this manuscript. Availability of data and materials The materials used in this research and protocols, are available upon request. Competing interests The authors declare that they have no competing interests that could have influenced the results There are no financial, personal, or professional conflicts of interest related to this research. Funding This study was funded by multiple projects, The Shanxi Province Key Laboratory Construction Project (Z135050009017-1-14), The Central Government Guides the Local Science and Technology Development Fund Project (YDZJSX2024D042),The Key Projects of Key R&D Plan Shanxi Province (202102140601007), The Academician Workstation Project (TYYSZ201707), The National Major Talent Engineering Expert Workstation Project (TYSGJZDRCZJGZZ202104). The Central Government Guides Local Science and Technology Development Fund Project (YDZJSX2022A045) Authors' contributions Conceptualization: Yan Deng and Chuangyun Wang; Methodology: Yan Deng, Xiaojing Sun, Yadi Sun; Data Collection: Yan Deng, Jiaxing Gao; Data Analysis: Yan Zheng, Zeyun Guo; Writing – Original Draft: Yan Deng, Xiaojing Sun; Writing – Review & Editing: Sumera Anwar; Supervision: Chuangyun Wang and All authors read and approved the final manuscript. Acknowledgments The authors wish to thank all participants who generously contributed their time and insights to this study. We also acknowledge the support staff at Shanxi Agricultural University for their assistance with data collection logistics. Special thanks to colleagues who provided valuable feedback during manuscript preparation. References Abbas, G., Murtaza, B., Amjad, M., Saqib, M., Akram, M., Naeem, M.A., Shah, G.M., Raza, M., Ali, Q., and Ahmed, K., 2024. Heat stress resulting from late sowing impairs grain yield and quality of quinoa genotypes facing drought and salt stress under field conditions. Journal of Agronomy and Crop Science, 210(4), p.e12717. Abou-Amer, A.I. and Kamel, A.S., 2011. Growth, yield and nitrogen utilization efficiency of quinoa ( Chenopodium quinoa ) under different rates and methods of nitrogen fertilization. Egypt. J. Agron, 33(2), pp.155-166. Almadini, A.M., Badran, A.E. and Algosaibi, A.M., 2019. Evaluation of efficiency and response of quinoa plant to nitrogen fertilization levels. Middle East J. Appl. Sci, 9(4), pp.839-849. Arneja, I., Tanwar, B. and Chauhan, A., 2015. Nutritional composition and health benefits of golden grain of 21st Century, Quinoa ( Chenopodium quinoa Willd.): A review. Pakistan Journal of Nutrition, 14(12), p.1034. Asher, A., Dagan, R., Galili, S. and Rubinovich, L., 2022. Effect of row spacing on quinoa ( Chenopodium quinoa ) growth, yield, and grain quality under a Mediterranean climate. Agriculture, 12(9), p.1298. Cárdenas-Castillo, J.E., Delatorre-Herrera, J., Bascuñán-Godoy, L. and Rodriguez, J.P., 2021. Quinoa ( Chenopodium quinoa Wild.) seed yield and efficiency in soils deficient of nitrogen in the Bolivian altiplano: an analytical review. Plants, 10(11), p.2479. Deng, Y., Zhao, L., Anwar, S., Zhang, L.G., Shafiq, F., Guo, H.X., Qin, L.X., Wang, M.X. and Wang, C.Y., 2023. Phosphorus fertigation conferred lodging tolerance and improved grain quality in Chenopodium quinoa via enhanced root proliferation and stalk strength. Journal of Soil Science and Plant Nutrition, 22(4), pp.5099-5110. Deng, Y., Zheng, Y., Lu, J., Guo, Z., Sun, X., Zhao, L., Guo, H., Zhang, L. and Wang, C., 2024. Effects of Different N Fertilizer Doses on Phenology, Photosynthetic Fluorescence, and Yield of Quinoa. Agronomy, 14(5), p.914. Deng, Y., Sun, X., Zhang, Q., Anwar, S., Lu, J., Guo, H., Qin, L., Zhang, L. and Wang, C., 2023. Comprehensive evaluation and physiological response of quinoa genotypes to low nitrogen. Agronomy, 13(6), p.1597. Ebrahimikia, M., Jami Moeini, M., Marvi, H., Hasheminejhad, Y., and Ghasemzadeh Ganjehie, M., 2021. Agro-physiological response of quinoa ( Chenopodium quinoa Willd.) to the nitrogen application rate and split application method. Journal of Soil Science and Plant Nutrition, 21(4), pp.3437-3450. Fischer, S., Wilckens, R., Jara, J. and Aranda, M., 2013. Variation in antioxidant capacity of quinoa ( Chenopodium quinoa Will) subjected to drought stress. Industrial Crops and Products, 46, pp.341-349. Schulte auf’m Erley, G., Kaul, H.P., Kruse, M. and Aufhammer, W., 2005. Yield and nitrogen utilization efficiency of the pseudocereals amaranth, quinoa, and buckwheat under differing nitrogen fertilization. European Journal of Agronomy, 22(1), pp.95-100. Geren, H., 2015. Effects of different nitrogen levels on the grain yield and some yield components of quinoa ( Chenopodium quinoa Willd.) under Mediterranean climatic conditions. Turkish Journal of Field Crops, 20(1), pp.59-64. Grewal, S.K., Gill, R.K. and Chandora, R., 2022. Exploring the role of carbon and nitrogen metabolism in Chenopodium quinoa (Willd.) from the commencement of grain growth until maturity. Hirel, B., Le Gouis, J., Ney, B., & Gallais, A. (2007). The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches. Journal of Experimental Botany, 58(9), 2369-2387. Hoang, D.T., Anh, D.T.P., Nhan, L.H. and Long, N.V., 2021. Effects of nitrogen application on the growth and yield of quinoa under saline conditions in Northern Vietnam. Vietnam Journal of Agricultural Sciences, 4(1), pp.903-911. Kakabouki, I.P., Hela, D., Roussis, I., Papastylianou, P., Sestras, A.F. and Bilalis, D.J., 2018. Influence of fertilization and soil tillage on nitrogen uptake and utilization efficiency of quinoa crop ( Chenopodium quinoa Willd.). Journal of Soil Science and Plant Nutrition, 18(1), pp.220-235. Liang, C.G., Chen, L.P., Yan, W.A.N.G., Jia, L.I.U., Xu, G.L. and Tian, L.I., 2011. High temperature at grain-filling stage affects nitrogen metabolism enzyme activities in grains and grain nutritional quality in rice. Rice Science, 18(3), pp.210-216. Li, H., Wang, Y., Wang, J., Zhang, M., Liu, W., Li, X. and Lin, X., 2025. Improving Leaf GOGAT Activity After the Post-Silking Period Contributes to High Grain Yield with Reduced Nitrogen in N-Efficient Maize. Agronomy, 15(6), p.1379. Li, G., Ren, A., Anwar, S., Shi, L., Bai, W., Zhang, Y., and Gao, Z., 2024. Optimizing Soil Health and Sorghum Productivity through Crop Rotation with Quinoa. Life, 14(6), p.745. Kumar R, Bhardwaj, S., Sikarwar, M., Kumar, A., Singh, B.R., Gupta, M., Shukla, R. 2024. Innovative Food Applications of Quinoa: Exploring Novel Insights into its Nutritional Potential and Biological Activities. Journal of Food Composition and Analysis, 107133. https://doi.org/10.1016/j.jfca.2024.107133. Li, G., Ren, A., Anwar, S., Shi, L., Bai, W., Zhang, Y., and Gao, Z., 2024. Optimizing Soil Health and Sorghum Productivity through Crop Rotation with Quinoa. Life, 14(6), p.745. Miranda-Apodaca, J., Agirresarobe, A., Martínez-Goñi, X.S., Yoldi-Achalandabaso, A. and Pérez-López, U., 2020. N metabolism performance in Chenopodium quinoa subjected to drought or salt stress conditions. Plant Physiology and Biochemistry, 155, pp.725-734. Liao, G., Yang, Y., Xiao, W. and Mo, Z., 2023. Nitrogen modulates grain yield, nitrogen metabolism, and antioxidant response in different rice genotypes. Journal of Plant Growth Regulation, 42(4), pp.2103-2114. Rashid, N., Wahid, A., Ibrar, D., Irshad, S., Hasnain, Z., Al-Hashimi, A., Elshikh, M.S., Jacobsen, S.E., and Khan, S., 2022. Application of natural and synthetic growth promoters improves the productivity and quality of quinoa crop through enhanced photosynthetic and antioxidant activities. Plant Physiology and Biochemistry, 182, pp.1-10. Ren, A., Jiang, Z., Dai, J., Sun, M., Anwar, S., Tang, P., Wang, R., Ding, P., Li, L., Wu, X. and Gao, Z., 2024. Phenotypic Characterization and Yield Screening of Quinoa Germplasms in Diverse Low-Altitude Regions: A Preliminary Study. Agronomy, 14(7), p.1354. Ru, C., Wang, K., Hu, X., Chen, D., Wang, W. and Yang, H., 2023. Nitrogen modulates the effects of heat, drought, and combined stresses on photosynthesis, antioxidant capacity, cell osmoregulation, and grain yield in winter wheat. Journal of Plant Growth Regulation, 42(3), pp.1681-1703. Sonali, Grewal, S.K. and Gill, R.K., 2022. Insights into carbon and nitrogen metabolism and antioxidant potential during vegetative phase in quinoa ( Chenopodium quinoa Willd.). Protoplasma, 259(5), pp.1301-1319. Panda, D. and Sarkar, R.K., 2013. Natural leaf senescence: probed by chlorophyll fluorescence, CO 2 photosynthetic rate and antioxidant enzyme activities during grain filling in different rice cultivars. Physiology and Molecular Biology of Plants, 19, pp.43-51. Sonali, Grewal, S.K., Gill, R.K. and Chandora, R., 2024. Exploring the role of carbon and nitrogen metabolism in Chenopodium quinoa (Willd.) from the commencement of grain growth until maturity. Plant Growth Regulation, 103(1), pp.177-191. Taaime, N., El Mejahed, K., Choukr-Allah, R., Bouabid, R., Oukarroum, A. and El Gharous, M., 2023. Optimization of macronutrients for improved grain yield of quinoa ( Chenopodium quinoa Wild.) crop under semi-arid conditions of Morocco. Frontiers in Plant Science, 14, p.1146658. Thanapornpoonpong, S.N., Vearasilp, S., Pawelzik, E. and Gorinstein, S., 2008. Influence of various nitrogen applications on protein and amino acid profiles of amaranth and quinoa. Journal of Agricultural and Food Chemistry, 56(23), pp.11464-11470. Tang, P., Ren, A., Jiang, Z., Wang, R., Cui, K., Wu, X., Sun, M., Gao, Z. and Anwar, S., 2024. Evaluation of Quinoa Varieties for Adaptability and Yield Potential in Low Altitudes and Correlation with Agronomic Traits. Agronomy, 14(4), p.852. Vásquez, S.C., del Pozo, A., Castillo, D., Matus, I., Gómez-Pando, L., Zamudio-Ayala, D., Mignone, C.M., Bertero, H.D. and Calderini, D.F., 2024. The critical period for yield and grain protein determination in quinoa ( Chenopodium quinoa Willd.). Field Crops Research, 306, p.109207. Wang, W., Shen, C., Xu, Q., Zafar, S., Du, B. and Xing, D., 2022. Grain yield, nitrogen use efficiency and antioxidant enzymes of rice under different fertilizer inputs and planting density. Agronomy, 12(2), p.430. Wieme, R.A., Carpenter-Boggs, L.A., Crowder, D.W., Murphy, K.M. and Reganold, J.P., 2020. Agronomic and economic performance of organic forage, quinoa, and grain crop rotations in the Palouse region of the Pacific Northwest, USA. Agricultural Systems, 177, p.102709. Xue, N., Liu, J. and Anwar, S., 2019. Enhancing Soil Physicochemical Properties, Quinoa Yield, and Nutrients through Intercropping of Quinoa with Legumes. Polish Journal of Environmental Studies, 1-15. DOI: 10.15244/pjoes/191963. Yaqoob, H., Akram, N.A., Iftikhar, S., Ashraf, M., Khalid, N., Sadiq, M., Alyemeni, M.N., Wijaya, L., and Ahmad, P., 2019. Seed pretreatment and foliar application of proline regulate morphological, physio-biochemical processes and activity of antioxidant enzymes in plants of two cultivars of quinoa ( Chenopodium quinoa Willd.). Plants, 8(12), p.588. Yan, D., Juan-Ling, W., Anwar, S., Chuang-Yun, W., Li, Z., Li-Guang, Z., Hong-Xia, G., Li-Xia, Q., Hua, L., and Mei-Xia, W., 2021. Phenology, lodging and yield traits of Chenopodium quinoa under the effect of planting density and row spacings. Fresenius Environ. Bull, 30, 11757-11767. Yang, K., Liu, W.Y., Wang, W.T., Yang, F.R., Yang, C. and Wang, B.Q., 2021. Effects of continuous cropping on growth and physiological characteristics of quinoa. Acta Agriculturae Universitatis Jiangxiensis, 43 (2), 244-252 Yang, L., Yang, X., Zhou, X. and Yang, Y., 2024. Transcriptomic analysis of adaptive responses to nitrogen deficiency in quinoa. Applied Ecology and Environmental Research, 22(6), pp.5237-5253. Yue, K., Li, L., Xie, J., Fudjoe, S.K., Zhang, R., Luo, Z. and Anwar, S., 2021. Nitrogen supply affects grain yield by regulating antioxidant enzyme activity and photosynthetic capacity of maize plant in the loess plateau. Agronomy, 11(6), p.1094. Zhao, H., Dai, T., Jing, Q., Jiang, D. and Cao, W., 2007. Leaf senescence and grain filling affected by post-anthesis high temperatures in two different wheat cultivars. Plant Growth Regulation, 51, pp.149-158. Zhao, Y., Zhao, Y., Peng, Y., Sun, Y., Zhang, D., Zhang, C., Ran, X., Shen, Y., Liu, W., Ding, Y. and Tang, S., 2025. Nitrogen regulated reactive oxygen species metabolism of leaf and grain under elevated temperature during the grain-filling stage to stabilize rice substance accumulation. Environmental and Experimental Botany, 229, p.106037. Supplementary Tables Supplementary tables S1 and S2 are not available with this version. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 09 Jan, 2026 Reviews received at journal 10 Dec, 2025 Reviews received at journal 10 Dec, 2025 Reviewers agreed at journal 19 Nov, 2025 Reviewers agreed at journal 19 Nov, 2025 Reviews received at journal 27 Aug, 2025 Reviewers agreed at journal 28 Jul, 2025 Reviewers invited by journal 25 Jul, 2025 Editor invited by journal 23 Jul, 2025 Editor assigned by journal 23 Jul, 2025 Submission checks completed at journal 22 Jul, 2025 First submitted to journal 22 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7125526","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":491176530,"identity":"bbeaa55d-abd7-4c08-80c0-baea8897ac4f","order_by":0,"name":"Yan Deng","email":"","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Deng","suffix":""},{"id":491176533,"identity":"1ddc5507-2674-4ee0-98ac-39a6b6e24e33","order_by":1,"name":"Xiaojing Sun","email":"","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":false,"prefix":"","firstName":"Xiaojing","middleName":"","lastName":"Sun","suffix":""},{"id":491176535,"identity":"3294bc82-e9d9-4591-8114-20be9eb6d8e2","order_by":2,"name":"Yadi Sun","email":"","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":false,"prefix":"","firstName":"Yadi","middleName":"","lastName":"Sun","suffix":""},{"id":491176537,"identity":"4fc8fca1-94c2-4877-93c9-85c85a8505f9","order_by":3,"name":"Chenglei Deng","email":"","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":false,"prefix":"","firstName":"Chenglei","middleName":"","lastName":"Deng","suffix":""},{"id":491176539,"identity":"c72d864a-616e-47b8-9732-38dc2489e9a4","order_by":4,"name":"Sumera Anwar","email":"","orcid":"","institution":"Government College Women University Faisalabad","correspondingAuthor":false,"prefix":"","firstName":"Sumera","middleName":"","lastName":"Anwar","suffix":""},{"id":491176540,"identity":"ae3e2137-2e42-4413-8a6a-669ef30cd5d4","order_by":5,"name":"Jiaxing Gao","email":"","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":false,"prefix":"","firstName":"Jiaxing","middleName":"","lastName":"Gao","suffix":""},{"id":491176541,"identity":"de87adc6-56b4-4928-899a-c81da9ba489e","order_by":6,"name":"Yan Zheng","email":"","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Zheng","suffix":""},{"id":491176542,"identity":"a093e292-c04d-4b5d-91d1-4d28508d9c9a","order_by":7,"name":"Zeyun Guo","email":"","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":false,"prefix":"","firstName":"Zeyun","middleName":"","lastName":"Guo","suffix":""},{"id":491176543,"identity":"c3894f18-88c1-4434-9303-096f293b1c21","order_by":8,"name":"Chuangyun Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYNACNhsYgzj1jA0MbGmkazlMghaD42fMH/OUnbcHMgwYPpQdZuCf3UBAy5kcw2aec7cTZ/bkGDDOOHeYQeLOAfxazG7wGDbztt1O4GfIMWDmbTvMYCCRQJSWc/Zs/G8MmP+SoOUAY78E0BZGYrTYn0krnDnnXHLizBnPCg72nEvnkbhBQItk++ENH96U2dkbnE/e+OBHmbUc/wwCWhgYOAyYeKDMA0DMg0cpDLA/YPxBhLJRMApGwSgYwQAA0IpC5QCAGQYAAAAASUVORK5CYII=","orcid":"","institution":"College of Agriculture, Shanxi Agricultural University/ Key Laboratory of Sustainable Dryland Agriculture of Shanxi Province, Taiyuan","correspondingAuthor":true,"prefix":"","firstName":"Chuangyun","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-07-15 02:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7125526/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7125526/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87845488,"identity":"1b3016e0-4876-4b99-bff3-d99351898ba3","added_by":"auto","created_at":"2025-07-29 14:54:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":137196,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on the activity of superoxide dismutase (SOD) enzyme in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/0ec5fff04feec51cf4c223a7.png"},{"id":87845476,"identity":"9fb99b15-8c14-41cc-906b-1805a22b043c","added_by":"auto","created_at":"2025-07-29 14:54:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":135867,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on the activity of peroxidase (POD) enzyme in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, \u0026nbsp;and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/8854f426b894f80869a7cc38.png"},{"id":87845478,"identity":"4c4d5ca5-285c-4e8f-9064-47654b109ae5","added_by":"auto","created_at":"2025-07-29 14:54:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":140315,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on the activity of catalase (CAT) enzyme in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/fc5fe588fdd1a67cb10b832d.png"},{"id":87845494,"identity":"1c70e41b-b7a1-47e1-b9d0-52b33ef2126f","added_by":"auto","created_at":"2025-07-29 14:54:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":105618,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on malondialdehyde (MDA) content in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, \u0026nbsp;and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/f1bb4fdf0067825d12973e15.png"},{"id":87845740,"identity":"9cca19ca-3664-4d2a-9826-06cde20cee4e","added_by":"auto","created_at":"2025-07-29 15:02:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":111350,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on the activity of nitrate reductase (NR) enzyme in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/01d57de07a647d4dc83f5643.png"},{"id":87845749,"identity":"b255fa1c-8df0-4931-94e9-5b5a0de864f6","added_by":"auto","created_at":"2025-07-29 15:02:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":142589,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on the activity of glutamine synthetase (GS) enzyme in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/a0023dec117eb4395cdd26da.png"},{"id":87845742,"identity":"54615ec2-ddd2-4178-adec-b162cb48c96a","added_by":"auto","created_at":"2025-07-29 15:02:06","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":122029,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on the activity of glutamate synthase (GOGAT) enzyme in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/3272e397bcdd39142cc8b89f.png"},{"id":87845493,"identity":"f2b7a361-dd4a-48f0-b7f5-3810158dbd0e","added_by":"auto","created_at":"2025-07-29 14:54:08","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":124531,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the application of different N rates and row spacings on the activity of glutamate dehydrogenase (GDH) enzyme in the leaf of quinoa at the ear emergence, flowering, early grain filling, late grain filling, and maturity stages. Each value is a mean of 3 replicates ±standard error, averaged across two years, and letters indicate significant differences by Tukey HSD test.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/407edc91e0e8d69e92ce94c3.png"},{"id":87845469,"identity":"af2730b0-d9fe-48e5-a1cb-b80a1600d2b5","added_by":"auto","created_at":"2025-07-29 14:54:06","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":83006,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of correlation between grain yield and indices at different growth stages. ***, **, and ns indicate significance at 0.001, 0.01, and non-significant values.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/06695b3773228259c4636f9d.png"},{"id":87846678,"identity":"c8d523ed-909e-4001-945c-a6170f6801cd","added_by":"auto","created_at":"2025-07-29 15:10:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1947139,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7125526/v1/b7686576-a499-4807-9224-266fdd139efa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSynergistic Effects of Nitrogen Fertilization and Row Spacing on Antioxidative Defense Mechanisms and Nitrogen Metabolism Dynamics During Reproductive Stages in Quinoa (Chenopodium quinoa Willd.)\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eQuinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.) has gained considerable attention as a versatile and resilient pseudo-cereal crop due to its nutritional value and ability to thrive under adverse environmental conditions (Kumar et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It is particularly high in protein, renowned for its content of all nine essential amino acids, making it a complete protein \u0026mdash;a rarity among plant-based foods (Abou-Amer and Kamel, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Pr\u0026auml;ger et al., 2011; Wieme et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, it is naturally gluten-free, has a low glycemic index, and is abundant in essential minerals such as magnesium, phosphorus, and copper (Pr\u0026auml;ger et al., 2011; Arneja et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn recent years, China has emerged as a significant region for quinoa cultivation, particularly in arid and semi-arid areas such as Shanxi, Tibet, and Inner Mongolia. Quinoa's genetic variability enables it to adapt and grow under the most adverse environmental conditions, making it a valuable crop for cultivation in diverse climatic conditions, including low rainfall, poor soils, and temperature fluctuations (Li et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ren et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This has led to its increasing popularity as a sustainable food source in China.\u003c/p\u003e\u003cp\u003eHowever, optimizing its yield and improving agronomic practices remain key challenges. Continuous cropping typically results in the depletion of soil nutrients, necessitating proper fertilizer application (C\u0026aacute;rdenas-Castillo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Deng et al., 2022; Li et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Quinoa is recognized for its high nitrogen content, which makes nitrogen supply crucial for quinoa cultivation, as it directly affects photosynthesis, protein synthesis, and overall plant growth. Effective nitrogen fertilization strategies are crucial for maximizing grain yield and quality while minimizing environmental issues associated with excessive application. Research has highlighted the quinoa crop's ability to respond to N fertilization even at low rates (C\u0026aacute;rdenas-Castillo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Adequate N supply enhances photosynthetic activity, biomass production, and grain development by regulating enzymatic and physiological activities in plants (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, excessive or insufficient nitrogen application can adversely affect plant metabolism and yield (Hoang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In the nitrogen-deficient soils of the Bolivian Altiplano, C\u0026aacute;rdenas-Castillo et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported an increase in quinoa yield by nitrogen fertilizer up to 240 kg/ha, after which it plateaus and declines beyond 300 kg/ha of nitrogen. Nitrogen use efficiency decreases as N application increases (Almadini et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), highlighting the need for optimal fertilization rates to maximize yield while maintaining efficiency.\u003c/p\u003e\u003cp\u003eOptimal N rates for quinoa typically range from 80 to 120 kg/ha, with variations depending on regional environmental factors, including soil fertility, water availability, and climate. Research in the Loess Plateau region indicates that an N rate of 120 kg/ha optimizes quinoa growth and yield, enhancing photosynthetic traits and reducing growth duration (Deng et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Studies conducted under Mediterranean climatic conditions suggest that an N application of 150 kg/ha yields the highest grain yield and crude protein content for quinoa (Geren \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In northern African countries, quinoa is grown in marginal soils with limited fertility. Studies have found that 60\u0026ndash;90 kg N/ha is sufficient to achieve satisfactory yields under rainfed conditions (Taaime et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These studies highlight the need to optimize quinoa's nutrients under various agro-climatic conditions.\u003c/p\u003e\u003cp\u003eAgricultural management practices, including sowing practices, row spacing, and planting density, play a crucial role in determining quinoa growth and yield (Yan et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For instance, row spacing significantly affects resource competition, light interception, and nutrient availability among plants, ultimately influencing crop growth and grain yield. Previous studies have shown that narrow row spacing increases canopy closure, resulting in denser canopies and greater competition for light, water, and nutrients, which can restrict branching and reduce individual plant growth (Yan et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWider row spacing allows better light penetration, promotes lateral branching, and improves photosynthetic efficiency while reducing the risk of lodging (Zulkadir et al., 2021). It also enhances root expansion, nutrient uptake, and water use efficiency, particularly in resource-limited environments such as arid and semi-arid regions. However, increasing row spacing beyond the optimal range decreases yield per area because of fewer plants per unit area (Yan et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A similar study in a Mediterranean climate found a yield reduction of quinoa with increasing row spacings from 26 to 80 cm (Asher et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Yan et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) studied the effects of planting density and row spacing on quinoa yield in northern Shanxi Province and found that the optimal planting density of 9 \u0026times; 10⁴ plants/ha, combined with a row spacing of 60 cm, significantly improved grain yield, photosynthetic traits, and lodging resistance.\u003c/p\u003e\u003cp\u003eCombining optimal row spacing with appropriate N fertilizer and crop variety selection can further enhance productivity. Tailoring row spacing to environmental conditions and employing precision agriculture techniques can ensure efficient resource use and maximize quinoa yield across diverse growing regions.\u003c/p\u003e\u003cp\u003eApart from yield-related traits, nitrogen metabolism and antioxidant enzyme activities play a pivotal role in determining plant growth and stress tolerance (Grewal et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Solali et al., 2022). Specifically, these metabolic activities influence yield during critical reproductive stages, including ear emergence, flowering, grain filling, and maturity (V\u0026aacute;squez et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Nitrogen-metabolizing enzymes, including nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamic acid dehydrogenase (GDH), regulate nitrogen assimilation, translocation, and utilization in plants, directly impacting grain yield (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Higher enzymatic activities during reproductive stages promote efficient N uptake and distribution, facilitating grain development and yield formation (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConcurrently, antioxidant enzymes such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) protect plant tissues from oxidative stress caused by reactive oxygen species (ROS) during critical growth stages (Rashid et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nutrient deficiency can lead to increased oxidative stress, particularly at the onset of the reproductive stage, when plants require substantial amounts of nutrients (Deng et al., 2022). Elevated antioxidant activities have been linked to improved stress tolerance, grain filling, and yield in cereal crops under various environmental and management conditions (Abbas et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite quinoa's growing popularity in regions with challenging agroclimatic conditions, limited research exists on optimizing nitrogen fertilizer rates and row spacing to maximize yield and stress resilience. This knowledge gap is particularly evident in semi-arid environments, where resource limitations require efficient nutrient and space management. We hypothesize that nitrogen-metabolizing enzymes and antioxidant activities during key reproductive stages (ear emergence, flowering, early grain filling, late grain filling, and maturity) play a significant role in yield formation under varying N levels and row spacings. This study aims to (a) evaluate the effects of nitrogen application rates and row spacing on quinoa grain yield, (b) investigate changes in antioxidant enzyme activities (SOD, POD, and CAT) and nitrogen-metabolizing enzymes (NR, GS, GOGAT, and GDH) during reproductive growth stages, and (c) analyze the relationships between antioxidant and nitrogen-metabolizing enzyme activities and yield components to identify key factors influencing quinoa yield. By addressing these objectives, this study will provide valuable insights into optimizing nitrogen management and planting strategies for quinoa cultivation in China, ultimately contributing to improved productivity and sustainable agricultural practices.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Overview of the test site\u003c/h2\u003e\u003cp\u003eThe experiment was carried out from 2023 to 2024 at an experimental facility located in Jingle County, Xinzhou City, Shanxi Province, China (38\u0026deg;3\u0026prime;N, 111\u0026deg;9\u0026prime;E). This site, situated over 2,000 meters above sea level, experiences a temperate monsoon climate characterized by four distinct seasons, with warm to hot summers and significant temperature fluctuations between day and night. The region boasts more than 2,500 hours of sunshine annually and enjoys an average frost-free period of 120 to 135 days. In 2023 and 2024, the average annual temperatures were recorded at 8.06\u0026deg;C and 9.13\u0026deg;C, respectively. The average annual rainfall measured 505.3 mm and 510.9 mm, respectively, in these years.\u003c/p\u003e\u003cp\u003eOn May 29, 2023, the basic nutrient composition of the 0\u0026ndash;20 cm soil layer was analyzed, revealing 7.87 g/kg of organic matter, 0.95 g/kg of total nitrogen, 132 mg/kg of available potassium, 21.31 mg/kg of available phosphorus, and a pH level of 8.09. A subsequent analysis on May 28, 2024, showed an increase in soil organic matter content to 7.56 g/kg, with total nitrogen at 0.87 g/kg, available potassium at 126.02 mg/kg, available phosphorus at 17.52 mg/kg, and a pH of 8.2.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Experimental Design\u003c/h2\u003e\u003cp\u003eThe experiment employed a two-factor randomized complete block design with three blocks. There were three nitrogen application levels: N1 (90 kg/ha), N2 (120 kg/ha), and N3 (150 kg/ha), alongside three row spacings: 20 cm, 40 cm, and 60 cm, denoted as R1, R2, and R3. In total, nine treatments were replicated three times, yielding 27 plots overall. The quinoa variety used in this experiment was BL77, supplied by Shanxi Huaqing Quinoa Product Development Co., Ltd., China. BL77 is a relatively low N-tolerant variety with a high yield (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Each plot measured 50 m\u0026sup2; (5 m \u0026times; 10 m), the planting density was 69,000 plants per hectare, and seeds were sown at a depth of 1\u0026ndash;2 cm, with a 1 m aisle maintained between plots. Urea (N\u0026thinsp;\u0026ge;\u0026thinsp;46%) was used as a nitrogen fertilizer.\u003c/p\u003e\u003cp\u003eThe row spacing was established by marking the inside of the plot with a tape measure, while a uniform plant spacing of 40 cm was ensured across all plots. Throughout the entire growth period, no artificial irrigation was employed, relying solely on natural precipitation for moisture. Pest and disease management was conducted using pesticides, while manual labor was used for weeding, with other cultivation practices adhering to local agricultural conditions. Quinoa seeds were sown on flat ground following land preparation on June 1 in both 2023 and 2024, with harvests occurring on October 20, 2023, and October 25, 2024.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Sampling and measurement\u003c/h2\u003e\u003cp\u003eQuinoa leaves were sampled at different growth stages, \u003cem\u003ei.e.\u003c/em\u003e, ear emergence stage, flowering stage, early grain filling stage, late grain filling stage, and maturity stage. 15 to 20 quinoa leaves were collected from each plot and immediately wrapped in aluminum foil, transferred to the lab, frozen in liquid nitrogen, and stored in a freezer at -80\u0026deg;C.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 Antioxidant enzyme activities\u003c/h2\u003e\u003cp\u003eThe biochemical kits, prepared by Beijing Solarbio Science \u0026amp; Technology Co., Ltd. (Beijing, China), were used to determine the enzyme activities in quinoa leaves. The activity of superoxide dismutase (SOD) was determined using the SOD activity assay kit (Catalog No.: BC0170) based on its ability to inhibit the formation of formazan dye at 560 nm, where one unit was defined as the amount of SOD required to inhibit 50% of superoxide radical production under the assay conditions, according to the manufacturer\u0026rsquo;s protocol.\u003c/p\u003e\u003cp\u003eThe activity of peroxidase (POD) was measured using the POD activity assay kit (Catalog No.: BC0090). The assay quantifies POD activity based on the enzyme's ability to catalyze the reaction of hydrogen peroxide (H₂O₂) with a chromogenic substrate, resulting in the production of a colored product. The absorbance was measured at 470 nm, and one unit of POD activity is defined as the amount of enzyme required to catalyze the oxidation of 1 \u0026micro;mol of substrate per minute under the assay conditions, following the manufacturer\u0026rsquo;s protocol.\u003c/p\u003e\u003cp\u003eThe activity of catalase (CAT) was determined using the CAT activity assay kit (Catalog No. BC0205) based on its ability to decompose H₂O₂ into water and oxygen. The decrease in H₂O₂ concentration was monitored spectrophotometrically at 240 nm. One unit of catalase activity is defined as the amount of enzyme required to decompose 1 \u0026micro;mol of H₂O₂ per second under the assay conditions. Results of SOD, POD, and CAT were expressed as units per gram of protein (U/g protein).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2 Malondialdehyde content\u003c/h2\u003e\u003cp\u003eThe malondialdehyde (MDA) content was determined using the MDA content assay kit (Catalog No. BC0020). The assay is based on the reaction of MDA with thiobarbituric acid (TBA) to form a pink-colored MDA-TBA adduct, which was measured spectrophotometrically at 532 nm. Results were expressed as nmol per gram of protein (nmol/mg protein), following the protocol provided by the manufacturer.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.3.3 Nitrogen assimilation enzymes\u003c/h2\u003e\u003cp\u003eThe activity of nitrate reductase (NR) was measured using the NR activity assay kit (Catalog No. BC0080), which quantified NR activity based on its ability to catalyze the reduction of nitrate to nitrite. The nitrite produced reacts with a color reagent to form a colored compound, which was measured spectrophotometrically at 540 nm. One unit of NR activity corresponds to the amount of enzyme that reduces 1 \u0026micro;mol of nitrate per minute under the assay conditions.\u003c/p\u003e\u003cp\u003eThe activity of glutamine synthetase (GS) was determined using the GS activity assay kit (Catalog No. BC0915). This assay evaluates GS activity by monitoring its role in synthesizing glutamine from glutamic acid and ammonium with ATP and Mg\u0026sup2;⁺. The resulting glutamine is converted into gamma-glutamyl hydroxamic acid, which reacts with iron under acidic conditions to produce a red complex measurable at 540 nm. One unit of GS activity corresponds to the synthesis of 1 \u0026micro;mol of gamma-glutamyl hydroxamic acid per minute.\u003c/p\u003e\u003cp\u003eThe activity of glutamate synthase (GOGAT) was determined using the GOGAT activity assay kit (Catalog No. BC0070) by measuring its ability to catalyze the formation of glutamate from glutamine and α-ketoglutarate. The reaction product was quantified spectrophotometrically at 340 nm, with one unit defined as the amount of GOGAT enzyme required to catalyze the conversion of 1 \u0026micro;mol of glutamine per minute under the assay conditions.\u003c/p\u003e\u003cp\u003eThe activity of glutamic acid dehydrogenase (GDH) was analyzed using the GDH activity assay kit (Catalog No. BC1460). GDH catalyzes the oxidative deamination of glutamic acid, producing α-ketoglutarate and ammonia, accompanied by the reduction of NAD⁺ or NADP⁺. The decrease in absorbance at 340 nm due to NAD(P)H formation was monitored to calculate GDH activity. One unit of GDH is defined as the enzyme required to catalyze the oxidation of 1 \u0026micro;mol of glutamic acid per minute under the specified conditions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Determination of yield\u003c/h2\u003e\u003cp\u003eDuring the quinoa maturity period, 10 plants with uniform growth were randomly selected from each plot. The panicle length on the main stem (primary panicle length) was taken with a tape measure. The number of branches was calculated from the branches with spikes at the bottom. At the same time, the quinoa spikes were placed in a mesh bag, dried in the sun, threshed and stored, and then weighed using a JM-a 20002 electronic balance. The seed sample was used to evaluate the yield.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003ePearson correlation coefficients (\u0026#119877;) were calculated to evaluate the relationships between grain yield and physiological and biochemical indices (e.g., SOD, POD, CAT) across five growth stages. Correlations were visualized as a heatmap using Python's Seaborn library, with annotations indicating the strength and statistical significance of the correlations.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Antioxidant enzyme activities\u003c/h2\u003e\u003cp\u003eNitrogen application rates and row spacings significantly influenced the activity of superoxide dismutase (SOD) (Table S1). Increasing N rates from 90 to 120 kg/ha resulted in a rise in SOD activity across all growth stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, when N rates were further increased to 150 kg/ha, the responses varied, showing either increased or decreased SOD activity. Across different growth stages, the highest SOD activity was observed during early grain filling, followed by late grain filling, while the lowest activity occurred at ear emergence. Wider row spacings enhanced SOD activity compared to narrower spacings, suggesting improved management of oxidative stress due to better resource availability. The combination of higher N rates (N3) and wider row spacing (R3) resulted in maximum SOD activity at the flowering stage, indicating an enhanced capacity to mitigate oxidative stress during this critical period.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePeroxidase (POD) activity exhibited a similar trend across all growth stages, with notable peaks during the early grain-filling stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). POD activity significantly increased with higher nitrogen application rates, indicating greater scavenging of hydrogen peroxide during periods of high metabolic activity. Wider row spacings also correlated with higher POD activity, likely due to reduced competition among plants. The highest values were recorded with the combination of N3 and R3, particularly during grain filling, reflecting the plant's increased need to scavenge hydrogen peroxide during high metabolic activity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eCatalase (CAT) activity consistently increased with N rates across all growth stages, reaching its peak during the early grain-filling stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The pairing of N3 and R3 produced maximum CAT activity during era emergence, flowering and early grain filling period, underscoring the importance of optimized nitrogen and spacing for enhancing antioxidant defense mechanisms. CAT activity rose significantly, with N rates increasing from 90 to 120 kg/ha. However, when the N rate was further increased to 150 kg/ha, the response varied depending on row spacing and growth stage. At 60 cm row spacings, CAT activity consistently increased with higher N rates at all growth stages. In contrast, at 20- and 40-cm row spacings, increasing the N rate from 120 to 150 kg/ha did not result in an increase or decrease in CAT activity. At lower and medium N rates, a 40 cm row spacing exhibited higher CAT activity compared to 20 or 60 cm row spacing. Overall, plants grown in wider row spacings showed greater CAT activity than those in narrower spacings, indicating improved stress mitigation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Malondialdehyde content\u003c/h2\u003e\u003cp\u003eMalondialdehyde (MDA) content, an indicator of lipid peroxidation and oxidative stress, decreased significantly with higher N rates (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The MDA content was highest at 90 kg/ha and lowest at 150 kg/ha. The main effects indicate that MDA was highest at the flowering stage and lowest at the maturity stage (Table S2). The interactive effect of N and row spacing showed that the highest MDA at the ear emergence and flowering stage was observed at 40 cm at 90 kg/ha (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). While at early grain filling, late grain filling, and maturity, the MDA content was highest at 60 cm row spacing at 90 kg/ha.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Nitrogen metabolism enzyme activities\u003c/h2\u003e\u003cp\u003eThe activities of all N metabolizing enzymes were significantly affected by the N rate, row spacing, stages, and their interactions (Table S2). The interactive effect of N rate and row spacing indicates that the nitrate reductase (NR) activity was highest at the ear emergence and flowering stages under the combination of N3 and R3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This combination provided the most favorable conditions for nitrate assimilation, particularly during early growth stages when nitrogen demand was highest. The lowest NR activity was observed at maturity, at 90 kg/ha, with row spacings of 20 and 60 cm.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe maximum glutamine synthetase (GS) and glutamate synthase (GOGAT) activities were observed during late grain filling, followed by maturity (Table S2). Among N rates, the highest GS and GOGAT activities were at 150 kg/ha, and the lowest at 90 kg/ha. Among row spacings, 40 cm row spacings had higher GS and GOGAT activities than 20 and 60 cm. The combination of 120 kg N/ha or 150 kg N/ha with 40 cm row spacing resulted in the highest GS and GOGAT activities at late grain filling (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGlutamate dehydrogenase (GDH) activity was significantly highest at flowering, while it was lowest at the ear emergence stage. Among N rates, the highest GDH activity was at 150 kg/ha, and the lowest was at 90 kg/ha. The N and row spacing interaction showed that the combination of 150 kg N/ha and 60 cm row spacing demonstrated the highest GDH activity at the flowering stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe maximum GDH activities were observed at the flowering stage, and then decreased with the progression of the reproductive stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). At 90 kg/ha and 120 kg/ha, the GDH activities were significantly highest at 40 cm, but at 150 kg/ha, the maximum GDH activity from flowering to maturity was observed at 60 cm.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Yield traits\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe N rate and row spacing significantly affected the number of branches, but their interaction was non-significant in both years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Increasing the N rate to 120 and 150 kg/ha significantly increased the number of branches. Similarly, increasing the row spacing to 40 and 60 cm resulted in a higher number of branches compared to 20 cm row spacing.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe effect of the application of different N rates and row spacings on grain yield and yield-related traits of quinoa at the maturity stage.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eN rate (kg/ha)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRow spacings (cm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eGrain yield (kg/ha)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eNumber of branches\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003ePrimary panicle length (cm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e1000-grain weight (g)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2471.11\u0026thinsp;\u0026plusmn;\u0026thinsp;56.9\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1933.42\u0026thinsp;\u0026plusmn;\u0026thinsp;64.4\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e29.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3196.49\u0026thinsp;\u0026plusmn;\u0026thinsp;22.0\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2848.45\u0026thinsp;\u0026plusmn;\u0026thinsp;92.2\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e32.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eef\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2079.21\u0026thinsp;\u0026plusmn;\u0026thinsp;70.9\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2274.48\u0026thinsp;\u0026plusmn;\u0026thinsp;82.0\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e31.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3809.15\u0026thinsp;\u0026plusmn;\u0026thinsp;107.9\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3613.62\u0026thinsp;\u0026plusmn;\u0026thinsp;97.2\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e43.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;c\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e38.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4480.99\u0026thinsp;\u0026plusmn;\u0026thinsp;110.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3973.48\u0026thinsp;\u0026plusmn;\u0026thinsp;126.8\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e46.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e41.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3775.14\u0026thinsp;\u0026plusmn;\u0026thinsp;64.2\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3528.41\u0026thinsp;\u0026plusmn;\u0026thinsp;86.4\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e41.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e39.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3353.20\u0026thinsp;\u0026plusmn;\u0026thinsp;80.3\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3024.25\u0026thinsp;\u0026plusmn;\u0026thinsp;78.0\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e41.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e34.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4198.91\u0026thinsp;\u0026plusmn;\u0026thinsp;97.2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3814.48\u0026thinsp;\u0026plusmn;\u0026thinsp;99.3\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e44.05\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e40.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4625.06\u0026thinsp;\u0026plusmn;\u0026thinsp;70.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4131.35\u0026thinsp;\u0026plusmn;\u0026thinsp;113.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e45.78\u0026thinsp;\u0026plusmn;\u0026thinsp;2.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e42.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eANOVA (\u003cem\u003eF\u003c/em\u003e-value)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2454.05***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1179.1***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.3***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e212.8***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e89.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e480.4***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1430.8***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1112.0***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e493.37***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e245.2***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.65***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e150.9***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.01***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e108.7***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e283.13***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e66.4***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN x RS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e271.81***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75.8***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.68ns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.91ns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.95***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e27.2***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e571.99***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e40.4***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eEach value is a mean of 3 replicates\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error, and letters indicate significant differences by Tukey HSD test. *, **, and *** indicate significance at 0.05, 0.01, and 0.001 probability levels, respectively. ns\u0026thinsp;=\u0026thinsp;non-significant.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe interaction of N rate and row spacing significantly affected primary panicle length, 1000-grain weight, and grain yield. The primary panicle length was highest at the combination of 120 kg/ha and 40 cm row spacing in 2023 and 150 kg/ha with 60 cm row spacing in 2024, although both treatments were statistically similar. In contrast, the lowest panicle length was observed at 90 kg/ha at 60 cm (in 2023) and 20 cm (in 2024). This indicates that higher row spacing favors a higher N rate.\u003c/p\u003e\u003cp\u003eThe increase in the N rate from 90 kg/ha to 150 kg/ha resulted in increased grain weight and yield (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Increasing the row spacing from 20 to 40 cm increased these traits, and further increasing the row spacing to 60 cm then started to decrease. The highest grain weight and grain yield were achieved at 150 kg/ha at a depth of 60 cm. The lowest grain weight and grain yield were observed at 90 kg/ha with row spacings of 60 cm (in 2023) and 20 cm (in 2024). The grain weight at 150 kg/ha at 60 cm was 2.22-fold higher than at 90 kg/ha at 60 cm row spacing in 2023 and 26.3% higher than at 90 kg/ha at 20 cm row spacing in 2024. Similarly, the grain yield at 150 kg/ha at 60 cm was 2.22 times higher than at 90 kg/ha at 60 cm in 2023 and 2.13 times higher than at 90 kg/ha at 20 cm in 2024.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Correlation of yield with N metabolism and antioxidant enzymes\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eGrain yield showed strong positive correlations with enzyme activities (SOD, POD, CAT, NR, GS, and GOGAT) across all growth stages, with the highest correlations observed at maturity (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). MDA content was the only trait that exhibited negative correlations with yield. Particularly, MDA content at early grain filling, late grain filling, and maturity showed a significant negative correlation with yield.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Effect of nitrogen rate and row spacing on antioxidant enzyme activities\u003c/h2\u003e\u003cp\u003eVarious stresses at the initiation of the reproductive stage accelerate oxidative stress and early senescence. Senescence, in turn, alters the source-sink relationship and significantly reduces crop yield (Kong et al., 2017; Yue et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tang et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, continuous cropping (Yang et al., 2022) and nutrient or water deficiency are common factors under field conditions (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which cause oxidative stress (Fischer et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Yaqoob et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe activity of antioxidant enzymes, such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), protects plants from oxidative stress caused by reactive oxygen species (ROS) (Liao et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lu et al., 2024). In the present study, the CAT, POD, and SOD activities peaked at the early grain-filling stages, followed by the late grain-filling stages, while being least at ear emergence. The higher activity of antioxidants during reproductive growth is linked with source remobilization and grain-filling processes. The grain-filling stage is metabolically intensive, often leading to increased ROS production. Potential reasons for increased antioxidant activity at early grain filling are that certain growth stages inherently exhibit higher antioxidant activities to support developmental transitions and ensure successful reproduction (Lu et al., 2024). Early grain filling involves rapid biosynthesis and nutrient translocation, increasing ROS production. Elevated activities of CAT, SOD, and POD during early grain filling may help mitigate oxidative stress associated with rapid cellular activities, thereby ensuring proper grain development. The malondialdehyde (MDA) content also peaked at the flowering and grain-filling stages, indicating the presence of oxidative stress. While many studies focus on stress-induced antioxidant responses, the upregulation of these enzymes during key developmental stages under optimal conditions is also crucial for maintaining cellular homeostasis (Kong et al., 2017; Zhao et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCAT, SOD, and POD activities in quinoa leaves increased with the application of higher N levels. Enzyme activities at 120 and 150 kg/ha were significantly higher than those at 90 kg/ha at all growth stages. The higher antioxidant activities might be because adequate nitrogen fertilization enhances metabolic processes, potentially leading to increased ROS, which plants then compensate for by boosting antioxidant defenses to maintain redox balance. The appropriate N supply increased antioxidant enzyme activities (Ru et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lu et al., 2024), enhancing stress tolerance and potentially supporting grain development (Liao et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe higher antioxidant enzyme activities at the early grain-filling stage under varying N levels align with findings in other crops, where antioxidant enzyme activities are influenced by nitrogen fertilization and developmental stages, improving plant resilience and metabolic functions (Lu et al., 2024; Zhao et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). For instance, research demonstrated that increasing N rates up to 200 kg/ha significantly elevated SOD and POD activities in maize, contributing to improved grain yield (Yue et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Higher N application (180 kg/ha) increased CAT and SOD activities, enhancing nitrogen use efficiency and grain yield in rice (Wang et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSOD and POD activity was highest during grain filling under 120 and 150 kg/ha N rates, coupled with wider row spacings. CAT activities peaked at flowering and early grain filling, particularly under 150 kg/ha N at 60 cm spacing. This indicates that the enhanced antioxidant activity under optimal N rates and spacing minimized oxidative stress during critical reproductive stages. Reduced MDA levels further confirmed the effectiveness of these antioxidant defenses in sustaining grain filling and yield.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Effect of nitrogen rate and row spacing on nitrogen metabolizing enzymes\u003c/h2\u003e\u003cp\u003eQuinoa grains are recognized for their high nitrogen content, which directly contributes to their protein-rich composition. On average, quinoa grains contain 15\u0026ndash;20% protein by weight, equivalent to approximately 2.5\u0026ndash;3.2% nitrogen content (Abou-Amer and Kamel, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wieme et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, appropriate nitrogen is required for grain development. Studies indicate that nitrogen fertilization plays a crucial role in determining quinoa protein content, grain development, and yield (Thanapornpoonpong et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Abou-Amer and Kamel, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Geren, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Almadini et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; C\u0026aacute;rdenas-Castillo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNitrogen-metabolizing enzymes play a fundamental role in nitrogen assimilation, translocation, and remobilization, processes essential for grain filling and yield development in quinoa. These enzymes include nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH), which act sequentially to convert absorbed nitrate into biologically available forms of nitrogen for metabolic functions (Sonali et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results showed that nitrogen fertilizer rates, row spacing, growth stages, and their interactions significantly affected the activity of these enzymes (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e; Table S2). NR catalyzes the first rate-limiting step in reducing nitrate (NO₃⁻) into nitrite (NO₂⁻). NR activity was highest during ear emergence and flowering, particularly under 150 kg/ha nitrogen (N3) at 60 cm row spacing (R3). The increased NR activity with increasing N application is attributed to the availability of nitrogen substrates and the plant\u0026rsquo;s metabolic demand for nitrogen assimilation and remobilization (Sonali et al., 2022; Sun et al., 2024). At later stages, NR activity declined or stabilized, with peaks observed at 120 kg/ha N during grain filling. This trend suggests that higher nitrogen supply during early reproductive stages supports nitrate assimilation, providing substrates for protein synthesis and tissue development (Sonali et al., 2022; Sun et al., 2024). As the plants progressed toward maturity, reliance on remobilized nitrogen reserves increased, reducing NR activity (Sonali et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFollowing nitrate reduction, ammonium (NH₄⁺) is assimilated through the GS/GOGAT pathway, which drives the incorporation of ammonium into amino acids, ensuring nitrogen is readily available for grain filling (Li et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The GS and GOGAT activities increased with higher N rates (90\u0026ndash;120 kg/ha). However, their activities declined at 150 kg/ha or below, particularly in narrow (20 cm) and wide (60 cm) row spacings, during the late reproductive stages of growth. This decline may reflect enzyme saturation at excessive nitrogen levels, resulting in reduced efficiency as nitrogen availability exceeds plant demand.\u003c/p\u003e\u003cp\u003eGlutamine and glutamate serve as nitrogen carriers in the phloem, transporting nitrogen from senescing leaves to developing grains. GS and GOGAT activities increase during early and late grain filling to facilitate the conversion of stored nitrogen compounds (proteins and amino acids) into mobile amino acids such as glutamine and asparagine for phloem loading and translocation to grains (Sonali et al., 2022). Their activities decline during maturity as remobilization slows and grains approach physiological maturity.\u003c/p\u003e\u003cp\u003eIn addition, GDH activity was highest during flowering, especially under 150 kg/ha N and 60 cm spacing, where it likely played a complementary role in recycling nitrogen from older tissues to support new growth and grain filling (Sonali et al., 2022). GDH\u0026rsquo;s involvement in deamination may have ensured nitrogen balance under high metabolic demand, particularly during senescence and stress recovery (Miranda-Apodaca et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sonali et al., 2022).\u003c/p\u003e\u003cp\u003eOverall, NR, GS, and GDH activities peaked at flowering, while GOGAT activity peaked at late grain filling. The possible reason for the stage-specific trends in enzyme activities is that at flowering, N uptake and assimilation are dominant, resulting in high NR, GS, and GDH activities. On the other hand, at grain filling, N remobilization and reassimilation are dominant, resulting in high GOGAT activity (Liang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). These differences in trends in enzyme activities highlight the dynamic nitrogen demands across reproductive stages (Hirel et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sonali et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). NR activity during ear emergence and flowering supported early nitrate reduction and reproductive growth, while the GS/GOGAT pathway promoted amino acid synthesis and remobilization during grain filling (Sun et al., 2024). GDH activity further complements nitrogen utilization by recycling nitrogen during late reproductive stages, sustaining grain development under conditions of high nitrogen demand.\u003c/p\u003e\u003cp\u003eThe interplay between nitrogen assimilation and remobilization was optimized at 120 kg/ha N, where enzyme activities supported greater nitrogen reserves in vegetative tissues and their efficient translocation to grains. This combination resulted in higher yield and grain quality, demonstrating the importance of balanced nitrogen management. Conversely, higher N rates (150 kg/ha) may have induced luxury consumption, reducing enzyme efficiency and resulting in diminished nitrogen use efficiency during later stages (Almadini et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese findings emphasize the critical role of nitrogen-metabolizing enzymes in regulating nitrogen assimilation, recycling, and translocation during reproductive stages (Sun et al., 2024). The results also highlight the need for appropriate N rates and row spacing to activate metabolic pathways, improving nitrogen utilization efficiency, protein content, and grain yield in quinoa.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Yield and correlation with antioxidative and nutrient metabolism\u003c/h2\u003e\u003cp\u003eGrain yield and related traits, such as panicle length, 1000 grain weight, and number of branches, are key indicators of quinoa productivity (Yan et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These traits are influenced by N rates and row spacing, which regulate resource availability, nutrient uptake, and plant growth dynamics. Our results demonstrated that yield components responded positively to increasing N rates from 90 to 120 kg/ha across all row spacings. However, further increasing the N rate to 150 kg/ha reduced yield at 20 cm and 40 cm spacing, while it continued to improve at 60 cm spacing, suggesting an interaction between N supply and spatial arrangements.\u003c/p\u003e\u003cp\u003ePlants grown at 60 cm row spacing with 150 kg/ha N achieved 17.1% and 22.5% higher grain yields and 5.7% and 22.7% heavier grains, respectively, in 2023 and 2024, compared to 120 kg/ha, indicating that wider spacing mitigated interplant competition and supported higher nitrogen uptake and utilization. In contrast, narrower spacing (20 cm) at 150 kg/ha likely led to resource competition and lodging, resulting in reduced yield, as observed in previous studies (Yan et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These findings underscore the importance of balancing N rates and row spacing to optimize nutrient efficiency and yield formation.\u003c/p\u003e\u003cp\u003eThe higher nitrogen demand observed at wider row spacing (60 cm) could be attributed to improved root expansion, which enables greater soil exploration and nutrient absorption. Wider spacing reduces competition for light, water, and nutrients, thereby supporting the efficiency of photosynthesis and protein synthesis, which are critical processes during grain filling (Ebrahimikia et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, quinoa's plastic root architecture adapts to spatial availability, promoting deeper root penetration at wider spacing, which facilitates better nitrogen uptake and water absorption (Schulte auf\u0026rsquo;m Erley et al., 2005). Increased nitrogen availability further stimulates the activities of NR, GS, GOGAT, and GDH, accelerating nitrate assimilation and remobilization to grains (Kakabouki et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sun et al., 2024).\u003c/p\u003e\u003cp\u003eOur results align with studies reporting 120 kg/ha N as optimal for enhancing yield without compromising nitrogen use efficiency. Schulte auf\u0026rsquo;m Erley et al. (2005) reported quinoa yields ranging from 1790 to 3495 kg/ha with an average nitrogen utilization efficiency of 22.2 kg grain per kg N, which did not decline at higher N rates. Similarly, Sun et al. (2024) demonstrated that applying 120 kg/ha nitrogen using slow-release fertilizers achieved 4525.8 kg/ha, highlighting the role of fertilizer formulations in improving N efficiency.\u003c/p\u003e\u003cp\u003eHigher N rates (\u0026gt;\u0026thinsp;120 kg/ha), particularly at narrower spacing (20 cm), likely promoted luxury consumption, resulting in nitrogen retention in vegetative tissues instead of efficient remobilization to grains (Almadini et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; C\u0026aacute;rdenas-Castillo et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This pattern was also observed in amaranth and quinoa, where increased nitrogen supplies delayed flowering, extended the vegetative phase, and reduced the harvest index (Ebrahimikia et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Our study revealed that yield improvement was closely associated with antioxidative enzyme activities (POD, SOD, and CAT) during early grain filling, particularly under higher N rates. Elevated SOD and CAT activity at this stage likely reduced oxidative damage, thereby supporting protein synthesis and cell expansion, which are critical for grain development. Similar findings in wheat and rice link higher antioxidant activity to reduced oxidative stress and better nitrogen assimilation under adequate fertilization (Yue et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liao et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xue et al., 2024).\u003c/p\u003e\u003cp\u003eThe high antioxidant activity observed during early grain filling can be attributed to the increased metabolic activity and ROS production associated with rapid nutrient translocation and grain filling (Kong et al., 2017). Optimum N rates likely induced higher respiration rates and energy demands, necessitating antioxidative defenses to protect cellular integrity during this metabolically active phase (Sun et al., 2024; Yan et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eApproximately 50\u0026ndash;70% of the total nitrogen remobilized within the plant accumulates in the grains (Sun et al., 2024). Higher activities of NR, GS, and GOGAT during the flowering and grain-filling stages likely facilitated nitrogen assimilation and remobilization, improving yield and grain quality. Concurrently, antioxidant enzymes mitigated oxidative stress, preventing premature senescence and ensuring optimal grain filling (Zhao et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Panda and Sarkar, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). While MDA levels (lipid peroxidation) showed a negative correlation with yield, reduced MDA under higher N levels indicates lower oxidative stress and higher metabolic stability, supporting nitrogen efficiency and grain development (Deng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These patterns emphasize the importance of maintaining a balanced nitrogen supply and optimal row spacing to sustain yield formation without inducing stress-related losses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the critical role of nitrogen fertilization rates and row spacing in optimizing grain yield, nitrogen metabolism, and antioxidative responses in quinoa during reproductive stages. The combination of 120 kg/ha nitrogen at 40 cm row spacing proved optimal for most traits, including panicle length, grain weight, and 1000 grain yield, performing significantly similar to the highest yield achieved with 150 kg/ha nitrogen at 60 cm spacing. The superior performance at 120 kg/ha and 40 cm spacing resulted from enhanced nitrogen assimilation and remobilization, supported by increased activities of nitrate reductase (NR), glutamine synthetase (GS), and glutamate synthase (GOGAT). Additionally, antioxidant enzymes (SOD, POD, and CAT) were highly active during early grain filling, mitigating oxidative stress and ensuring efficient nutrient translocation for grain development. While higher N rates (150 kg/ha) at wider spacing (60 cm) further improved yield, they may have promoted luxury consumption and reduced nitrogen use efficiency, making 120 kg/ha at 40 cm a more balanced and sustainable choice for enhancing yield and quality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided written informed consent prior to participation, ensuring they understood the purpose of the study, their rights, and confidentiality measures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have given their consent for the publication of this manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe materials used in this research and protocols, are available upon request. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests that could have influenced the results\u003c/p\u003e\n\u003cp\u003eThere are no financial, personal, or professional conflicts of interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003erelated to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by multiple projects, The Shanxi Province Key Laboratory Construction Project (Z135050009017-1-14), The Central Government Guides the Local Science and Technology Development Fund Project (YDZJSX2024D042),The Key Projects of Key R\u0026amp;D Plan Shanxi Province (202102140601007), The Academician Workstation Project (TYYSZ201707), The National Major Talent Engineering Expert Workstation Project (TYSGJZDRCZJGZZ202104). The Central Government Guides Local Science and Technology Development Fund Project (YDZJSX2022A045)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Yan Deng and Chuangyun Wang; Methodology: Yan Deng, Xiaojing Sun, Yadi Sun; Data Collection: Yan Deng, Jiaxing Gao; Data Analysis: Yan Zheng, Zeyun Guo; Writing – Original Draft: Yan Deng, Xiaojing Sun; Writing – Review \u0026amp; Editing: Sumera Anwar; Supervision: Chuangyun Wang and All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank all participants who generously contributed their time and insights to this study. We also acknowledge the support staff at Shanxi Agricultural University for their assistance with data collection logistics. Special thanks to colleagues who provided valuable feedback during manuscript preparation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbbas, G., Murtaza, B., Amjad, M., Saqib, M., Akram, M., Naeem, M.A., Shah, G.M., Raza, M., Ali, Q., and Ahmed, K., 2024. Heat stress resulting from late sowing impairs grain yield and quality of quinoa genotypes facing drought and salt stress under field conditions. Journal of Agronomy and Crop Science, 210(4), p.e12717.\u003c/li\u003e\n \u003cli\u003eAbou-Amer, A.I. and Kamel, A.S., 2011. Growth, yield and nitrogen utilization efficiency of quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e) under different rates and methods of nitrogen fertilization. Egypt. J. Agron, 33(2), pp.155-166.\u003c/li\u003e\n \u003cli\u003eAlmadini, A.M., Badran, A.E. and Algosaibi, A.M., 2019. Evaluation of efficiency and response of quinoa plant to nitrogen fertilization levels. Middle East J. Appl. Sci, 9(4), pp.839-849.\u003c/li\u003e\n \u003cli\u003eArneja, I., Tanwar, B. and Chauhan, A., 2015. Nutritional composition and health benefits of golden grain of 21st Century, Quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.): A review. Pakistan Journal of Nutrition, 14(12), p.1034.\u003c/li\u003e\n \u003cli\u003eAsher, A., Dagan, R., Galili, S. and Rubinovich, L., 2022. Effect of row spacing on quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e) growth, yield, and grain quality under a Mediterranean climate. Agriculture, 12(9), p.1298.\u003c/li\u003e\n \u003cli\u003eC\u0026aacute;rdenas-Castillo, J.E., Delatorre-Herrera, J., Bascu\u0026ntilde;\u0026aacute;n-Godoy, L. and Rodriguez, J.P., 2021. Quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Wild.) seed yield and efficiency in soils deficient of nitrogen in the Bolivian altiplano: an analytical review. Plants, 10(11), p.2479.\u003c/li\u003e\n \u003cli\u003eDeng, Y., Zhao, L., Anwar, S., Zhang, L.G., Shafiq, F., Guo, H.X., Qin, L.X., Wang, M.X. and Wang, C.Y., 2023. Phosphorus fertigation conferred lodging tolerance and improved grain quality in Chenopodium quinoa via enhanced root proliferation and stalk strength. Journal of Soil Science and Plant Nutrition, 22(4), pp.5099-5110.\u003c/li\u003e\n \u003cli\u003eDeng, Y., Zheng, Y., Lu, J., Guo, Z., Sun, X., Zhao, L., Guo, H., Zhang, L. and Wang, C., 2024. Effects of Different N Fertilizer Doses on Phenology, Photosynthetic Fluorescence, and Yield of Quinoa. Agronomy, 14(5), p.914.\u003c/li\u003e\n \u003cli\u003eDeng, Y., Sun, X., Zhang, Q., Anwar, S., Lu, J., Guo, H., Qin, L., Zhang, L. and Wang, C., 2023. Comprehensive evaluation and physiological response of quinoa genotypes to low nitrogen. Agronomy, 13(6), p.1597.\u003c/li\u003e\n \u003cli\u003eEbrahimikia, M., Jami Moeini, M., Marvi, H., Hasheminejhad, Y., and Ghasemzadeh Ganjehie, M., 2021. Agro-physiological response of quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.) to the nitrogen application rate and split application method. Journal of Soil Science and Plant Nutrition, 21(4), pp.3437-3450.\u003c/li\u003e\n \u003cli\u003eFischer, S., Wilckens, R., Jara, J. and Aranda, M., 2013. Variation in antioxidant capacity of quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Will) subjected to drought stress. Industrial Crops and Products, 46, pp.341-349.\u003c/li\u003e\n \u003cli\u003eSchulte auf\u0026rsquo;m Erley, G., Kaul, H.P., Kruse, M. and Aufhammer, W., 2005. Yield and nitrogen utilization efficiency of the pseudocereals amaranth, quinoa, and buckwheat under differing nitrogen fertilization. European Journal of Agronomy, 22(1), pp.95-100.\u003c/li\u003e\n \u003cli\u003eGeren, H., 2015. Effects of different nitrogen levels on the grain yield and some yield components of quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.) under Mediterranean climatic conditions. Turkish Journal of Field Crops, 20(1), pp.59-64.\u003c/li\u003e\n \u003cli\u003eGrewal, S.K., Gill, R.K. and Chandora, R., 2022. Exploring the role of carbon and nitrogen metabolism in \u003cem\u003eChenopodium quinoa\u003c/em\u003e (Willd.) from the commencement of grain growth until maturity.\u003c/li\u003e\n \u003cli\u003eHirel, B., Le Gouis, J., Ney, B., \u0026amp; Gallais, A. (2007). The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches. Journal of Experimental Botany, 58(9), 2369-2387.\u003c/li\u003e\n \u003cli\u003eHoang, D.T., Anh, D.T.P., Nhan, L.H. and Long, N.V., 2021. Effects of nitrogen application on the growth and yield of quinoa under saline conditions in Northern Vietnam. Vietnam Journal of Agricultural Sciences, 4(1), pp.903-911.\u003c/li\u003e\n \u003cli\u003eKakabouki, I.P., Hela, D., Roussis, I., Papastylianou, P., Sestras, A.F. and Bilalis, D.J., 2018. Influence of fertilization and soil tillage on nitrogen uptake and utilization efficiency of quinoa crop (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.). Journal of Soil Science and Plant Nutrition, 18(1), pp.220-235.\u003c/li\u003e\n \u003cli\u003eLiang, C.G., Chen, L.P., Yan, W.A.N.G., Jia, L.I.U., Xu, G.L. and Tian, L.I., 2011. High temperature at grain-filling stage affects nitrogen metabolism enzyme activities in grains and grain nutritional quality in rice. Rice Science, 18(3), pp.210-216.\u003c/li\u003e\n \u003cli\u003eLi, H., Wang, Y., Wang, J., Zhang, M., Liu, W., Li, X. and Lin, X., 2025. Improving Leaf GOGAT Activity After the Post-Silking Period Contributes to High Grain Yield with Reduced Nitrogen in N-Efficient Maize. Agronomy, 15(6), p.1379.\u003c/li\u003e\n \u003cli\u003eLi, G., Ren, A., Anwar, S., Shi, L., Bai, W., Zhang, Y., and Gao, Z., 2024. Optimizing Soil Health and Sorghum Productivity through Crop Rotation with Quinoa. Life, 14(6), p.745.\u003c/li\u003e\n \u003cli\u003eKumar R, Bhardwaj, S., Sikarwar, M., Kumar, A., Singh, B.R., Gupta, M., Shukla, R. 2024. Innovative Food Applications of Quinoa: Exploring Novel Insights into its Nutritional Potential and Biological Activities. Journal of Food Composition and Analysis, 107133. https://doi.org/10.1016/j.jfca.2024.107133.\u003c/li\u003e\n \u003cli\u003eLi, G., Ren, A., Anwar, S., Shi, L., Bai, W., Zhang, Y., and Gao, Z., 2024. Optimizing Soil Health and Sorghum Productivity through Crop Rotation with Quinoa. Life, 14(6), p.745.\u003c/li\u003e\n \u003cli\u003eMiranda-Apodaca, J., Agirresarobe, A., Mart\u0026iacute;nez-Go\u0026ntilde;i, X.S., Yoldi-Achalandabaso, A. and P\u0026eacute;rez-L\u0026oacute;pez, U., 2020. N metabolism performance in Chenopodium quinoa subjected to drought or salt stress conditions. Plant Physiology and Biochemistry, 155, pp.725-734.\u003c/li\u003e\n \u003cli\u003eLiao, G., Yang, Y., Xiao, W. and Mo, Z., 2023. Nitrogen modulates grain yield, nitrogen metabolism, and antioxidant response in different rice genotypes. Journal of Plant Growth Regulation, 42(4), pp.2103-2114.\u003c/li\u003e\n \u003cli\u003eRashid, N., Wahid, A., Ibrar, D., Irshad, S., Hasnain, Z., Al-Hashimi, A., Elshikh, M.S., Jacobsen, S.E., and Khan, S., 2022. Application of natural and synthetic growth promoters improves the productivity and quality of quinoa crop through enhanced photosynthetic and antioxidant activities. Plant Physiology and Biochemistry, 182, pp.1-10.\u003c/li\u003e\n \u003cli\u003eRen, A., Jiang, Z., Dai, J., Sun, M., Anwar, S., Tang, P., Wang, R., Ding, P., Li, L., Wu, X. and Gao, Z., 2024. Phenotypic Characterization and Yield Screening of Quinoa Germplasms in Diverse Low-Altitude Regions: A Preliminary Study. Agronomy, 14(7), p.1354.\u003c/li\u003e\n \u003cli\u003eRu, C., Wang, K., Hu, X., Chen, D., Wang, W. and Yang, H., 2023. Nitrogen modulates the effects of heat, drought, and combined stresses on photosynthesis, antioxidant capacity, cell osmoregulation, and grain yield in winter wheat. Journal of Plant Growth Regulation, 42(3), pp.1681-1703.\u003c/li\u003e\n \u003cli\u003eSonali, Grewal, S.K. and Gill, R.K., 2022. Insights into carbon and nitrogen metabolism and antioxidant potential during vegetative phase in quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.). Protoplasma, 259(5), pp.1301-1319.\u003c/li\u003e\n \u003cli\u003ePanda, D. and Sarkar, R.K., 2013. Natural leaf senescence: probed by chlorophyll fluorescence, CO 2 photosynthetic rate and antioxidant enzyme activities during grain filling in different rice cultivars. Physiology and Molecular Biology of Plants, 19, pp.43-51.\u003c/li\u003e\n \u003cli\u003eSonali, Grewal, S.K., Gill, R.K. and Chandora, R., 2024. Exploring the role of carbon and nitrogen metabolism in \u003cem\u003eChenopodium quinoa\u003c/em\u003e (Willd.) from the commencement of grain growth until maturity. Plant Growth Regulation, 103(1), pp.177-191.\u003c/li\u003e\n \u003cli\u003eTaaime, N., El Mejahed, K., Choukr-Allah, R., Bouabid, R., Oukarroum, A. and El Gharous, M., 2023. Optimization of macronutrients for improved grain yield of quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Wild.) crop under semi-arid conditions of Morocco. Frontiers in Plant Science, 14, p.1146658.\u003c/li\u003e\n \u003cli\u003eThanapornpoonpong, S.N., Vearasilp, S., Pawelzik, E. and Gorinstein, S., 2008. Influence of various nitrogen applications on protein and amino acid profiles of amaranth and quinoa. Journal of Agricultural and Food Chemistry, 56(23), pp.11464-11470.\u003c/li\u003e\n \u003cli\u003eTang, P., Ren, A., Jiang, Z., Wang, R., Cui, K., Wu, X., Sun, M., Gao, Z. and Anwar, S., 2024. Evaluation of Quinoa Varieties for Adaptability and Yield Potential in Low Altitudes and Correlation with Agronomic Traits. Agronomy, 14(4), p.852.\u003c/li\u003e\n \u003cli\u003eV\u0026aacute;squez, S.C., del Pozo, A., Castillo, D., Matus, I., G\u0026oacute;mez-Pando, L., Zamudio-Ayala, D., Mignone, C.M., Bertero, H.D. and Calderini, D.F., 2024. The critical period for yield and grain protein determination in quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.). Field Crops Research, 306, p.109207.\u003c/li\u003e\n \u003cli\u003eWang, W., Shen, C., Xu, Q., Zafar, S., Du, B. and Xing, D., 2022. Grain yield, nitrogen use efficiency and antioxidant enzymes of rice under different fertilizer inputs and planting density. Agronomy, 12(2), p.430.\u003c/li\u003e\n \u003cli\u003eWieme, R.A., Carpenter-Boggs, L.A., Crowder, D.W., Murphy, K.M. and Reganold, J.P., 2020. Agronomic and economic performance of organic forage, quinoa, and grain crop rotations in the Palouse region of the Pacific Northwest, USA. Agricultural Systems, 177, p.102709.\u003c/li\u003e\n \u003cli\u003eXue, N., Liu, J. and Anwar, S., 2019. Enhancing Soil Physicochemical Properties, Quinoa Yield, and Nutrients through Intercropping of Quinoa with Legumes. Polish Journal of Environmental Studies, 1-15. DOI: 10.15244/pjoes/191963.\u003c/li\u003e\n \u003cli\u003eYaqoob, H., Akram, N.A., Iftikhar, S., Ashraf, M., Khalid, N., Sadiq, M., Alyemeni, M.N., Wijaya, L., and Ahmad, P., 2019. Seed pretreatment and foliar application of proline regulate morphological, physio-biochemical processes and activity of antioxidant enzymes in plants of two cultivars of quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.). Plants, 8(12), p.588.\u003c/li\u003e\n \u003cli\u003eYan, D., Juan-Ling, W., Anwar, S., Chuang-Yun, W., Li, Z., Li-Guang, Z., Hong-Xia, G., Li-Xia, Q., Hua, L., and Mei-Xia, W., 2021. Phenology, lodging and yield traits of Chenopodium quinoa under the effect of planting density and row spacings. Fresenius Environ. Bull, 30, 11757-11767.\u003c/li\u003e\n \u003cli\u003eYang, K., Liu, W.Y., Wang, W.T., Yang, F.R., Yang, C. and Wang, B.Q., 2021. Effects of continuous cropping on growth and physiological characteristics of quinoa. Acta Agriculturae Universitatis Jiangxiensis, 43 (2), 244-252\u003c/li\u003e\n \u003cli\u003eYang, L., Yang, X., Zhou, X. and Yang, Y., 2024. Transcriptomic analysis of adaptive responses to nitrogen deficiency in quinoa. Applied Ecology and Environmental Research, 22(6), pp.5237-5253.\u003c/li\u003e\n \u003cli\u003eYue, K., Li, L., Xie, J., Fudjoe, S.K., Zhang, R., Luo, Z. and Anwar, S., 2021. Nitrogen supply affects grain yield by regulating antioxidant enzyme activity and photosynthetic capacity of maize plant in the loess plateau. Agronomy, 11(6), p.1094.\u003c/li\u003e\n \u003cli\u003eZhao, H., Dai, T., Jing, Q., Jiang, D. and Cao, W., 2007. Leaf senescence and grain filling affected by post-anthesis high temperatures in two different wheat cultivars. Plant Growth Regulation, 51, pp.149-158.\u003c/li\u003e\n \u003cli\u003eZhao, Y., Zhao, Y., Peng, Y., Sun, Y., Zhang, D., Zhang, C., Ran, X., Shen, Y., Liu, W., Ding, Y. and Tang, S., 2025. Nitrogen regulated reactive oxygen species metabolism of leaf and grain under elevated temperature during the grain-filling stage to stabilize rice substance accumulation. Environmental and Experimental Botany, 229, p.106037.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplementary Tables","content":"\u003cp\u003eSupplementary tables S1 and S2 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chenopodium quinoa, Growth stages, GS/GOGAT, Peroxidase, Catalase, Malondialdehyde, Grain yield","lastPublishedDoi":"10.21203/rs.3.rs-7125526/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7125526/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOptimizing nitrogen (N) fertilization and row spacing is crucial for enhancing quinoa (\u003cem\u003eChenopodium quinoa\u003c/em\u003e Willd.) yield and stress tolerance, particularly at critical reproductive stages. This two-year field study evaluated the interactive effects of three N rates (90, 120, and 150 kg/ha) and three row spacings (20, 40, and 60 cm) on N metabolism and antioxidative responses during reproductive growth. Key enzyme activity in N metabolism, including nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH), were measured across five growth stages alongside antioxidant enzymes (SOD, POD, and CAT). The combination of 150 kg/ha N and 40 cm row spacing significantly enhanced NR, GS, and GOGAT activities, particularly during the grain-filling stages, thereby improving N assimilation and translocation. Wider row spacing (60 cm) and higher N rates maximized GDH activity at flowering, which is crucial for mitigating oxidative stress. Antioxidant enzyme activities were highest during grain filling, with rates of 120 and 150 kg/ha at 40 cm spacing, resulting in reduced malondialdehyde (MDA) content and indicating lower oxidative damage. Grain yield was strongly correlated with GS, GOGAT, and SOD activities during late grain filling, resulting in a 2.22-fold increase under 150 kg/ha N and 60 cm spacing compared to lower N and row spacings. These findings underscore the importance of optimizing N rates and row spacing in enhancing N metabolism and antioxidative defense during reproductive stages, providing actionable insights for improving quinoa productivity in resource-limited environments.\u003c/p\u003e","manuscriptTitle":"Synergistic Effects of Nitrogen Fertilization and Row Spacing on Antioxidative Defense Mechanisms and Nitrogen Metabolism Dynamics During Reproductive Stages in Quinoa (Chenopodium quinoa Willd.)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-29 14:53:37","doi":"10.21203/rs.3.rs-7125526/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-09T23:48:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-11T00:13:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-10T22:33:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210311390142022462270436979169793278938","date":"2025-11-19T23:30:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202116614017046891789247196428351160544","date":"2025-11-19T15:26:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-28T00:28:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286554709811229889719382283733589280487","date":"2025-07-28T11:27:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-25T17:46:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-23T09:13:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-23T09:01:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-22T05:37:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-07-22T05:34:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"76eea03b-d2bd-4aea-b93d-ff1bcec5df74","owner":[],"postedDate":"July 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-03T11:10:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-29 14:53:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7125526","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7125526","identity":"rs-7125526","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}