Botanically cowpea [Vigna unguiculata (L.) Walp.] belongs to the family Fabaceae, having chromosome no. 2n = 22. Cowpea is an annual herbaceous plant with alternate trifoliate leaves that have ovate-shaped leaflets and well-developed tap root system. It can be short and bushy or trailing type. Most of the wild variants of the cowpea are found in Central Africa, where it is likely to have originated. It has now spread to a large number of nations worldwide. The total harvested area of cowpea for its dry grains is estimated to cover over 15 million hectares worldwide, yielding around 9 million metric tons (Olorunwa et al., 2023; Laosatit et al., 2024). The growing recognition of the potential of cowpea as a climate-resilient crop highlights its role in enhancing food security and nutrition (Lonardi et al., 2019). Globally, dry grain production, harvested area and yield of cowpea have steadily increased over the past years (https://www.fao.org/faostat/en/; Accessed 2024/07/17). While production is widely distributed, the largest proportion (95.4%) of global dry grain cowpea is produced in Africa, particularly West Africa followed by Asia (2.9%) with the America (1.3%) and Europe (0.5%) recording smaller shares.             

This resilient legume thrives in water-limited and soil-deficient environments with its high protein content, low carbon footprint, short growth period and productivity in marginal areas aligning with Sustainable Development Goals (SDGs), namely SDGs 2, 3 and 13. In India, cowpea is a minor pulse crop grown primarily in arid and semi-arid plains, covering approximately 3.9 million hectares and yielding 2.21 million tonnes annually (Giridhar et al., 2020).
       
It is mostly grown in the semi-arid and arid regions of Punjab, Haryana, Delhi and Uttar Pradesh as well as in sizeable quantities in Rajasthan, Karnataka, Kerala, Tamil Nadu, Maharashtra, Gujarat, Odisha, West Bengal and other states. Cowpea is grown in tropics for its tender green pods and shelled immature seeds used as vegetable and dry seeds used as pulse. It is grown for immature pods and mature grains. The haulms are also fed to livestock. Cowpea is known as drought hardy nature, its wide and droopy leaves keep soils and soil moisture conserved due to shading effect. It is also known as black-eyed pea or southern pea etc. and has multiple uses like food, feed, forage, fodder, green manuring and vegetable (Saravaiya et al., 2014). According to Davis et al., (2000), the mature cowpea seed has 24.5% protein, 63.6% carbohydrates, 1.9% fat, 6.3% fibre, 0.00074% thiamine, 0.00042% riboflavin and 0.00281% niacin. Green leaves contain between 3 and 4% of protein, immature pods between 4 and 5% and mature seeds between 25 and 30%.
       
Several researchers have demonstrated considerable genotypic variability in cowpea for yield-related traits, physiological efficiency and adaptability across environments. Das et al., (2021) reported significant (p<0.01) variation among genotypes for pod yield (50-85 g plant^-1) and 100-seed weight (12-17 g) with heritability values exceeding 90%, indicating high genetic control over key yield traits. Similarly, Parmar et al. (2025) observed Genotypic and Phenotypic Coefficients of Variation (GCV = 8.7-21.5%; PCV = 10.1-23.8%), coupled with heritability up to 91% for yield and protein content, revealing substantial scope for selection of high-yielding genotypes. Singh et al., (2020) confirmed significant genotype × environment interactions (p<0.01) and identified genotypes GC-3 and RC-19 as stable across arid environments. Furthermore, Lata et al., (2024) demonstrated that under 80% PE (pre-emergence) irrigation, yields improved by 17-35% over sub- or full-irrigation regimes, with Swarna Mukut recording 12.6 t ha^-1 and highest water-use efficiency. A recent synthesis by Vaishna et al. (2025) highlighted broad genetic diversity (Nei’s distance 0.32-0.71) and yield potential of 0.8-2.5 t ha^-1 (grain) and 5-14 t ha^-1 (vegetable) types, underscoring the necessity of exploiting genotype variability for location-specific improvement. Collectively, these findings emphasize that identifying high-yielding and adaptable genotypes is crucial for optimizing productivity under diverse agro-ecological conditions.
       
In a traditional cropping system, there is a 90-day interval between the crops of rice and wheat. If a pulse crop like cowpea with a short lifetime, or one with a maturity period of fewer than 90 days, could be cultivated during this time period, the crop intensity of such systems might be boosted and also it is vital to establish the right agronomic manipulations for attaining higher yield when promising cultivars with higher yield potential are identified for a particular region. Similarly, in Varanasi region of Uttar Pradesh, it is necessary to assess the adaptation of promising cowpea types. For commercial cultivation, choosing a superior variety is essential and after evaluation, the best performing variety should be suggested to the farmers.

The present investigation was carried out at Agricultural Research Farm, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh during Kharif season of 2021 and 2022. The experiment was laid out in randomized block design (RBD) with three replications. Each replication consist of 10 varieties/genotypes viz. Pant lobia-1, Pant lobia-5, PGCP-28, PGCP-63, PGCP-68, PGCP-69 and PGCP-73 were collected from G.B. Pant University of Agriculture and Technology, Pantnagar and other three varieties viz., CP-6, CP-7 and Kashi Kanchan were collected from IIVR, Varanasi.  All the genotypes were randomized separately in each replication. The experimental field falls under sandy clay loam in texture and neutral in reaction with low in organic carbon and available Nitrogen and medium in available phosphorus and potassium. Before sowing, 20 kg N ha^-1, 60 kg P₂O₅  ha^-1 and 30 kg K₂O ha^-1 were applied as basal dose. Sowing was done on 13 August and 15 August 2022 with a row spacing of 45 cm and plant spacing of 10 cm, maintaining 1.5 m distance between replications and 1.0 m between plots. Two hand weeding were done to keep the plots weed free for uniform growth of plants. Pods after attaining maturity were harvested, dried under shade for 2-3 days and seeds were separated manually.
       
Five representative plants were tagged in each plot for recording various observations at 20, 40 days after sowing (DAS) and at harvest. Growth parameters recorded included plant height (cm), number of leaves/trifoliate leaves, number of branches and total dry weight (g plant^-1). Plant height was measured from the base to the tip of the main shoot; total dry weight was obtained by oven-drying plants at 70°C to constant weight. The number of nodules per plant was recorded at 40 DAS by carefully uprooting plants and washing roots under running water, while nodule dry weight (mg plant^-1) was determined after drying nodules at 70°C to constant weight. Days to 50% flowering were recorded as the number of days from sowing to when half the plants in a plot had at least one open flower. Yield attributes recorded included pod length (cm), number of pods per plant, number of seeds per pod and 100-seed weight (g). Pod length was measured using a ruler from five randomly selected pods, number of pods per plant and seeds per pod were counted manually and 100-seed weight was recorded using an electronic balance at 12% moisture. The yield parameters included biological yield (kg ha^-1), grain yield (kg ha^-1) and harvest index (%) was calculated using the formulae:

and adjusted to 12% moisture content. Harvest index (HI, %) was computed using the equation:

Protein content (%) in seeds was estimated from Nitrogen concentration determined by the Kjeldahl method (Moore et al., 2010) and calculated as:
 

Protein content (%) = Total nitrogen (%) × 6.25

 
All data recorded were subjected to statistical analysis using the standard procedure for Analysis of Variance (ANOVA) as described by Gomez and Gomez (1984). The significance of treatments was tested by “F” test at 5% level of probability and where significant, the treatment means were compared using the Critical Difference (CD) at 5% probability level. Standard error of mean (SEm ±) was computed in all cases. Data analysis was carried out using OPSTAT (HAU, Hisar) and verified using SPSS v26 to ensure accuracy and homogeneity of variances.

Impact of genotypes on growth parameters
Plant height
 
Significant differences were observed among all the varieties and genotypes for the selected growth parameters and are presented in Table 1. The average plant height at 20 DAS, genotype PGCP-28, recorded significantly maximum height (17.9 cm), which remained on a par with that of PGCP-68 and PGCP-63, respectively. At 40 DAS, maximum plant height was registered in genotype PGCP-68 (37.7 cm) over rest of the genotypes/varieties.    


       
Whereas, at harvest variety CP-7 remain at par PGCP-68, recorded significantly maximum plant height over rest of the genotypes/varieties. Significantly lowest plant height was observed in CP-6 (39.0 cm) over the rest of genotypes/varieties except for Pant lobia-5 and PGCP-69, respectively. The observed variation in plant height might be attributed to the inherent genetic potential of the genotypes, environmental adaptability and interaction effects as supported by earlier studies. Bisikwa et al. (2014) reported significant varietal differences in cowpea plant height, where elite variety IT82D-889 (32.31 cm) and MU-93 (erect) (32.31 cm) recorded taller plants compared to local varieties such as Ebelat (28.10 cm) and Ichirikukwai (27.89 cm). The study also revealed that plant height increased by 7.8% under higher rainfall conditions, demonstrating the influence of genotyp-environment interaction on growth. Similarly, Patil et al., (2015) recorded significant differences among 20 cowpea genotypes with plant height ranging from 34.95 cm to 57.78 cm (mean 44.83 cm). The tallest genotype was C-152 (57.78 cm), while PGCP-14 (34.95 cm) was the shortest, indicating wide genetic variability for plant stature among genotypes. The variation in plant height observed in the present study is therefore consistent with previous findings, affirming that genotype plays a decisive role in growth expression and plant architecture.
 
Trifoliate leaves per plant
 
The average number trifoliate leaves per plant at 20 and 40 DAS genotype PGCP-68 registered maximum value over rest of the genotypes/varieties, except at 40 DAS the differences for trifoliate leaves were found non-significant with CP-6, PGCP-28, CP-7 and Pant lobia-5, respectively (Table 1). Variation in number of trifoliate leaves is might be due to genetic constitution and also might be due to better adaptability to weather conditions. Hence, cowpea harvested maximum photosynthetically active radiation (PAR) through improved canopy in terms of assimilatory surface area. Ahmad et al. (2017) found that cowpea varieties like UPC-626 produced the maximum number of leaves at different growth stages and increased Phosphorus  application contributed to higher leaf counts, emphasizing the roles of genetics and nutrition; in their experiments, leaf number increases of up to 80.90 at 60 DAS and 75.22 at 90 DAS compared to the lowest-yielding check were observed. Kandel et al. (2019) similarly reported that varietal differences were significant regarding leaf production, specifically at later stages, with highest leaf counts recorded for some genotypes. These findings collectively demonstrate that the number of trifoliate leaves per plant in cowpea is markedly influenced by genotype and management, with higher leaf numbers enhancing photosynthetic area and ultimately supporting pod and grain yield.
 
Number of branches per plant
 
At 20 DAS, PGCP-68 being on a par with PGCP-28 recorded significantly maximum average number of branches per plant over rest of cowpea genotypes/varieties (Table 1). At 40 DAS and at harvest, PGCP-68 being on a par with CP-7, recorded significantly maximum average number of branches per plant over rest of cowpea genotypes/varieties. Variety Pant lobia-1, recorded lowest average number of branches per plant over rest of the cowpea genotypes/varieties, except for variety Pant lobia-5 and PGCP-69 at 40DAS whereas, at harvest genotype PGCP-69, variety Kashi Kanchan, variety Pant lobia-5 and genotype PGCP-73 observed non-significant the differences among themselves. This variation is might be due to genetic constitution and also might be due to better adaptability to weather conditions. Similar findings were also observed by the results of Ahmad et al., (2017), which demonstrated significant differences in number of branches per plant among cowpea varieties, with UPC-626 producing the highest number of branches (up to 26.34 at 60 DAS), which was attributed to both genetic variation and Phosphorus nutrition. Application of 80 kg P₂O₂ ha^-1 resulted in a significant increase in branching and UPC-626 recorded up to 5.94 branches per plant, outperforming other varieties. Similarly, Asati et al., (2018) reported that genotype Sel. N-1 produced a maximum of 11.25 branches per plant, significantly surpassing other genotypes, while the lowest count (8.83) was recorded for Pusa Komal. These findings support that genetic makeup and adaptability are key determinants of branch production in cowpea, correlating strongly with enhanced growth and yield attributes.
 
Total dry weight per plant
 
At 20 DAS, variety Pant lobia-5 and variety Kashi Kanchan remained at par with each other recorded significantly higher total average dry weight per plant than rest of cowpea genotypes/varieties (Table 1). While at 40 DAS and at harvest, genotypes PGCP-68 recorded significantly higher dry weight over rest of the genotypes/ varieties expect CP-7, PGCP-28 and CP-6 where, non-significant differences observed at harvest. The results are might be due to taller plants coupled with higher number of leaves and branches and higher number of pods at the time of harvest. This result is supported by Ahmad et al., (2017), who found that the cowpea variety UPC-626 accumulated the greatest dry matter (20.33 g at 60 DAS and 21.48 g at 90 DAS), attributed to its taller plants, greater leaf and branch numbers and higher Phosphorus nutrition improving biomass accumulation. Gereziher et al., (2018) likewise reported that Kenkety variety exhibited superior biomass production associated with higher pod and seed yields under moisture-stressed environments. These findings underscore that genetic constitution and vegetative vigour drive dry matter accumulation, which ultimately contributes to enhanced yield in cowpea.
       
The relationship between dry matter and grain yield among different cowpea varieties, displaying both parameters as bar graphs (Fig 1) for each genotype with an added linear regression trend line (y = 0.8073x + 13.32, R² = 0.2032). PGCP-68 stands out for having the highest dry matter and correspondingly high grain yield, while varieties such as Pant lobia-1 and CP-6 exhibit lower dry matter and grain yield values. Although the dotted trend line and the R² value indicate only a moderate positive correlation between dry matter accumulation and grain yield, the general pattern observed is that genotypes with greater biomass tend to achieve higher grain yields. This result suggests that improvement in total dry matter production may favourably impact grain yield in cowpea genotypes, though other physiological or genetic factors likely contribute to yield variability among varieties as evidenced by some genotypes deviating from the trend.


 
Number of nodules per plant and nodule dry weight
 
Average number of nodules per plant was recorded highest in genotype PGCP-69 (38.3), that remains at par with PGCP-68 (37.0), recorded significantly higher value than rest of the cowpea genotypes/varieties (Table 2). Average dry weight of nodules was observed highest in genotype PGCP-68, which remains significantly superior over rest of genotypes/varieties. The similar results also studied by Dangi et al., (2020), who reported significant genotypic differences in nodulation, with nodules per plant ranging from about 23 to 47, where genotypes with higher nodulation also showed superior growth and yield parameters due to better Nitrogen fixation.


 
Days to 50% flowering
 
Days to 50% flowering was varied statistically among the genotypes/varieties studied during the investigation. The lowest days for 50% flowering were recorded in the genotype CP-6 (36.00 days) which was at par with genotype CP-7 (Table 2). The genotype PGCP-68 recorded the highest days to 50% flowering (43.7 days), which was at par with Pant lobia-1 and Kashi Kanchan, respectively. This variation is influenced by intricate interactions of genetic and environmental factors such as temperature and photoperiod. Khanpara et al., (2016) observed a flowering range from 45.33 to 59.67 days among vegetable cowpea genotypes with significant genetic variability and heritability for flowering time, indicating its responsiveness to genetic control and breeding potential. Darai et al. (2023) reported days to 50% flowering between 49 and 68.5 days in seed-type cowpea genotypes, emphasizing the role of genetics and environment in modulating this trait under different agroecological conditions. Manohara et al., (2021) also documented a flowering range of 49 to 68.5 days under residual moisture conditions in rice-fallow areas, highlighting genetic variation among 23 genotypes and the significance of flowering time for adaptation in moisture-limited environments. These studies confirm that days to flowering is a complex trait shaped by genotypic differences and environmental interactions, supporting the observed variation in the present study.
 
Impact of genotypes on yield parameters
 
Number of pods per plant
 
The highest number of pods per plant was reported in genotype PGCP-68 (13.6) which remain at par with variety CP-7 (13.4) followed by genotype PGCP-28 (13.3) and varieties Pant lobia-5 (12.5) and CP-6 (11.9), respectively (Table 2). Whereas, PGCP-63 (6.07) recorded significantly lowest number of pods per plant. The findings of Parmar et al., (2025); Vaishna et al. (2025) and Kandel et al., (2019) support the observed differences in number of pods per plant in the studied cowpea genotypes. Parmar et al. (2025) highlighted significant genetic variability in seed yield and yield components across 31 cowpea genotypes, identifying specific lines and testers with high combining ability (CA) for traits such as seed yield, harvest index and protein content, which indirectly relate to pod development. Vaishna et al. (2025) reviewed the genetic diversity in cowpea and emphasized the importance of exploiting genotypic variation to improve yield and pod traits, underscoring the role of genetic diversity in enhancing crop productivity. Kandel et al. (2019) reported significant varietal differences in pod number per plant among cowpea genotypes evaluated in Nepal, with the highest pod numbers associated with superior yield and pod characteristics, confirming the influence of genetic factors on pod production. These studies corroborate that genetic traits regulating prolific flowering and pod development are fundamental in determining the number of pods per plant, aligning with the higher pod counts observed in genotypes PGCP-68, CP-7 and PGCP-28 in the present investigation.
 
Pod length
 
The average pod length was recorded highest in variety CP-6 (27.7 cm) over rest of genotypes/varieties evaluated (Table 2). Next in order to this, variety Kashi Kanchan which was remains on par with CP-7, recorded significantly higher pod length over rest of the remaining genotypes/varieties. Genotype PGCP-73 (14.7 cm), recorded significantly lowest pod length over the remaining genotypes/varieties except Pant lobia-1 and PGCP-63, respectively. The variation in pod length could be due to genotypic variations and influence of environment. Similar findings were also reported by Bhattarai et al., (2017) and observed the significant variation in pod length among different cowpea genotypes grown under upland conditions in western mid hills of Nepal. The genotype IT 86F-2062-5 recorded the longest pods measuring 21.00 cm, while IT 99K-573-2-1 had the shortest pods at 14.69 cm, indicating a wide genotypic influence on pod length. This variation was attributed to inherent genetic differences as well as environmental interactions. Similar to the present study, their findings showed that pod length varied considerably among genotypes, with genotypic characteristics playing a principal role in pod size determination. These results align with the observed highest pod length in variety CP-6 and next highest in Kashi Kanchan and CP-7, whereas PGCP-73 and some other genotypes recorded significantly shorter pods, indicating genetic and environmental effects on pod length.
 
Number of seeds per pod
 
Number of seeds per pod was recorded maximum in genotype PGCP-68 (14.8) than rest of cowpea genotypes except for variety CP-7 (13.3) and genotype PGCP-28 (13.1) where, the differences were observed non-significant among themselves (Table 2). Genotype PGCP-63 (8.2) remained on a par with that of PGCP-69 (8.5) and Pant lobia-1(10.0) recorded significantly lowest number of seeds per pod than rest of the cowpea genotypes/ varieties. The seed of cowpea genotypes/ varieties varied in seed coat colour and seed shape as shown in Plate 1. Similar results were also reported by Asati et al., (2018), reported that the cowpea genotype Sel. N-1 exhibited the highest number of seeds per pod (19.33), with significant variation among genotypes attributed to differences in genetic makeup and nutrient availability, confirming that seed count per pod is a heritable trait influenced by genotype selection. Dalorima et al. (2014) found improved varieties generally produced more seeds per pod (up to 15) with significant differences compared to local varieties, indicating that breeding and variety improvement can enhance seed set in cowpea. Dangi et al. (2020) highlighted significant differences in the number of seeds per pod among 13 cowpea genotypes under Prayagraj conditions, with seed counts ranging from approximately 9.85 to 16.13 seeds per pod, thus supporting the influence of genotypic variation on this yield component. This overall evidence confirms that number of seeds per pod in cowpea is strongly governed by genetic differences among varieties.


 
100-seed weight
 
Significantly maximum 100 seed weight was recorded in genotype PGCP-68 (19.2 g) than remaining cowpea genotypes/ varieties tested (Table 2). Significantly lowest 100 seed weight was registered in Pant lobia-1(12.3 g) than remaining cowpea genotypes/ varieties except for CP-6 (12.5 g) where, the differences for 100 seed weight were non-significant. Gereziher et al. (2018) found significant diversity in 100 seed weight among cowpea varieties tested in southern Tigray and Ethiopia, reporting mean values from 13.99 g to 14.62 g, with variety differences attributed to genetic makeup and ecological adaptation, although hundred seed weight was not statistically significant among the tested genotypes. Giridhar et al. (2020) reported that cowpea varieties differed significantly for 100 grain test weight, with Gomati recording the highest value (up to 53.2 g) and Kamini showing the lowest (50.6 g) and that wider plant spacing further enhanced 100 grain weight, highlighting the role of both genotype and agronomic management in maximizing seed size. These findings confirm that 100-seed weight in cowpea is strongly impacted by genetic traits and growing conditions, supporting the observed maximal seed weight in PGCP-68 and minimal values in Pant lobia-1 and CP-6.
 
Biological yield
 
Genotype PGCP-68 (3403 kg/ha) being on a par with that of variety Pant lobia-5 (3224 kg/ha) and genotype PGCP-69 (3355 kg/ha) recorded significantly highest value of biological yield than remaining cowpea genotypes/ varieties (Table 2). whereas, CP-6 (2886 kg/ha) recorded the lowest value. The findings are aligned with the studies of Giridhar et al. (2020) showed that plant spacing influenced cowpea biological yield with the widest spacing of 20 cm resulting in noticeably higher grain and stover yields due to reduced competition for light, moisture and nutrients, while the varieties did not significantly differ for biological yield attributes, indicating the impact of population density and agronomic management on biomass accumulation. Dangi et al. (2020) observed significant variability in biological yield among cowpea genotypes with the best-performing genotypes producing up to 4637 kg/ha, highlighting that biological yield is largely determined by genotypic potential for biomass and the expression of multiple growth and yield components. Manohara et al. (2021) reported high genetic variability in straw and seed yield among cowpea genotypes grown in rice-fallow conditions, emphasizing that straw yield and harvest index have a direct positive impact on seed yield and that selecting for higher biomass traits is beneficial for improving overall productivity under such environments. These findings together confirm that biological yield in cowpea is significantly affected by genotype, plant spacing and associated yield attributes.
 
Grain yield
 
Genotype PGCP-68 (1648 kg/ha) recorded significantly higher grain yield than remaining genotypes except for PGCP-69(1587 kg/ha), followed by Pant lobia-5 (1574 kg/ha) and Pant lobia-1(1568 kg/ha), respectively. Significantly lowest cowpea grain yield was registered with CP-6 (1259 kg/ha) than rest of the genotypes except for PGCP-63(1296 kg/ha), CP-7(1364 kg/ha) and PGCP-73 (1383 kg/ha), respectively. Darai et al. (2023) reported significant genotypic differences in grain yield among fourteen seed-type cowpea genotypes evaluated over two years with yields ranging from 934 kg/ha to 1449 kg/ha and the highest yields being directly associated with superior pod production, seed weight and plant height. Rout et al., (2023) similarly found significant variability in grain yield among fifteen varieties grown under Prayagraj conditions, where Booster Cowpea and Kashi Kanchan delivered the highest yield per plant and lower yields were linked to genotypes exhibiting fewer pods and seeds per plant. Both studies confirm that genetic constitution and yield attributes strongly influence grain yield potential, corroborating the present findings where PGCP-68, PGCP-69 and Pant lobia-5 exhibited superior performance, while CP-6 recorded the lowest yield due to limited expression of yield components.
 
Harvest index
 
Highest value of harvest index was obtained in Pant lobia-1 (51.8%) whereas, lowest value of harvest index was registered with CP-6 (43.6%) (Table 2).  Ahmad et al. (2017) reported a harvest index range of 40.2% to 51.4% among different cowpea cultivars, higher harvest index associated with varieties showing improved partitioning of assimilates towards grain yield, reflecting genotypic differences in efficiency of biomass utilization. Giridhar et al., (2020) observed harvest index values ranging from approximately 40% to 52% in cowpea varieties subjected to different plant densities, where varieties with higher grain yields had correspondingly higher harvest indices, indicating the importance of both genotype and agronomic management in improving harvest efficiency. Dangi et al., (2020) found significant variation in harvest index among cowpea genotypes grown under Prayagraj conditions with values from 41.5% to 53.3%, demonstrating the role of genetic variability in assimilate partitioning and yield potential. These findings support the present results showing the highest harvest index in Pant lobia-1 and lowest in CP-6, linked to differences in grain and biological yield among tested genotypes.
 
Impact of genotypes on quality parameters
 
Nitrogen content in grain
 
Highest value of nitrogen (N) content in grain registered in PGCP-68 (4.29%), whereas, lowest value of N content in grain was observed in CP-6 (3.70%) (Table 2). Nitrogen content in cowpea grain varies significantly among genotypes and is influenced by efficient nutrient uptake and utilization. Parmar et al. (2025) reported Nitrogen content ranging between 3.45% and 4.30% across diverse genotypes, highlighting genetic potential for improved N accumulation. Similarly, Kandel et al., (2019) observed Nitrogen content ranging from 3.5% to 4.3% linked to genotype and soil nutrient availability. Giridhar et al., (2020) also documented Nitrogen content variations linked to genotypic differences and agronomic factors, supporting the observed superior N content in PGCP-68 (4.29%) and lower content in CP-6 (3.70%) in this study.
 
Protein content in grain
 
Maximum protein content was registered in genotype PGCP-68 (26.8%) whereas, minimum value for protein content was noticed in CP-6 (23.1%) (Table 2). Protein content in cowpea grain is largely governed by genetic constitution and environmental interactions. Parmar et al., (2025) reported protein content variation from 22.5% to 27.0%, where genotypes exhibiting higher protein were linked with efficient Nitrogen assimilation capacities. Dangi et al., (2020) demonstrated genotypic variability for protein content (23%-27%) among cowpea genotypes, suggesting breeding potential for protein enhancement. Giridhar et al., (2020) confirmed these findings with protein content differences attributable to genetic and management factors. These results corroborate the higher protein content in PGCP-68 (26.8%) and lower in CP-6 (23.1%) recorded in the present study.

On the basis of above results, it can be concluded that the genotype PGCP-68 is superior to all other treatments on the basis of growth, yield and quality parameters. So, for commercial cultivation by the farmers of Varanasi region, cowpea genotype PGCP-68 is recommended. Future studies should focus on multi-location trials of promising genotypes like PGCP-68 to assess their stability across diverse agro-climatic zones. Integration with improved agronomic practices and stress tolerance screening could further enhance yield potential and adaptability. Additionally, exploring value-added traits like micronutrient content will strengthen cowpea’s role in sustainable cropping systems.

We are highly thankful to the Head of Department of Agronomy, Institute of Agricultural Sciences for providing technical guidance and technical facilities to conduct the experiments.

The authors declare that there is no conflict of interest regarding the publication of this manuscript.