Understanding the underlying factors of soybean yield variation from field-managed interventions in northern Nigeria: Meta-regression approaches
2025
Muhammad Rabiu Kabiru | Mohamed Hafidi | Jibrin Mohammed Jibrin | Martin Jemo
Soybean (Glycine max, L.) is an important grain legume cultivated in northern Nigeria for human food, animal fodders and as a source of income. However, yield is often low and unpredictable, and our understanding of the factors explaining yield variability is limited. We examine the factors influencing soybean yield variability from field-managed interventions. A search using Web of Science, Google Scholar, and Scopus extracted studies on Rhizobia (Rh) inoculated and phosphorus (P) fertilizer or Rh × P combination treatments across three agroecological zones (AEZs): Sudan Savanna (SS), Northern Guinea Savanna (NGS), and Southern Guinea Savanna (SGS). The yield responses to management interventions and across AEZs were analyzed using effect size. Meta-regression models were used to fit yield change with various soil properties such as exchangeable potassium (K), nitrogen (N), and organic carbon (OC). The yield change was higher (39.1 ± 4.0 %) for the Rh × P combination than the Rh or P application. The NGS exhibited a lower yield change (23.1 ± 0.15 %) compared to SS (38.0 ± 0.2 %) and SGS (39.0 ± 0.2 %). The model identified a minimum soil exchangeable-K concentration of 0.54 cmol (+) kg−1 to increase yield under Rh and Rh × P treatments, while a minimum soil-N content of 1.50 g. kg−1 increased yield for the Rh and Rh × P interventions. The required OC content for significant yield responses ranged from 6 to 9 g kg−1 under the SGS agroecology. We discuss the impacts of soil OC and N levels on soybean yield variations, aiming to advance sustainable farming practices among smallholder farmers in Nigeria.
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