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Cropping systems effect on the agronomic performance of neglected legumes under rainfed conditions

Jul 2026 · Frontiers in Sustainable Food Systems · 0 citations · 28 references

Abstract

Cropping systems are critical in modifying micro-environments, improving land-use efficiency, and enhancing crop adaptability to marginal conditions. However, the interaction between cropping systems and the performance of neglected legumes under rainfed conditions remains poorly understood. This study evaluated the effects of cropping systems on the agronomic performance of neglected legumes in rainfed environments. Field trials were conducted over two consecutive summer growing seasons (November 2022-January 2023 and November 2023-January 2024) using a split-plot randomized complete block design with three replications. Phenological traits (emergence, flowering, podding and senescence), yield components (pods per plant, pod mass, seeds per pod, 100-seed weight and grain yield), and land equivalent ratio (LER) were recorded and analyzed using GenStat ® and principal component analysis. Results revealed significant effects of cropping system, cultivar, season, and their interactions ( P ≤ 0.05). Intercropping enhanced early emergence and accelerated reproductive development in legumes Bambara groundnut, cowpea, and common bean, while pigeon pea showed reduced establishment under sole cropping. Pod and seed production, pod mass, 100-seed weight, and grain yield increased under intercropping. Cowpea and Bambara groundnut exhibited stable responses across seasons, whereas common bean and pigeon pea showed variability, highlighting the importance of genotype and species-specific compatibility with intercrop designs. LER consistently exceeded 1.0 under intercropping, indicating superior land-use efficiency. These findings demonstrate the potential of intercropping to enhance the productivity and resilience of neglected legumes in smallholder rainfed systems. Strategic selection of species with complementary phenology and growth dynamics is essential for maximizing interspecific interactions and system performance.

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