Grain yield is a quantitatively inherited trait in groundnut (Arachis hypogea L.) and subject to genotype by environment interactions. Groundnut varieties show wide variation in grain yield across different agro-ecologies. The objectives of this study were to evaluate Valencia groundnut genotypes for yield stability and classify environments to devise appropriate breeding strategies. Seventeen multi-location trials were conducted in six countries, viz., Malawi, Tanzania, Uganda, Zimbabwe, Mozambique and Zambia, from 2013 to 2016. The experiments were laid out following a resolvable incomplete block design, with two replications at each location (hereafter referred to as ‘environments’) using 14 test lines and two standard checks. The additive main effects and multiplicative interaction (AMMI) analysis was conducted. Variation attributable to environments, genotypes and genotype × environment interaction for grain yield was highly significant (P<0.001). Genotype, environment and genotype × environment interactions accounted for 7%, 53 % and 40% of the total sum of squares respectively. Superior-performing genotypes possessing high to moderate adaptability and stability levels included ICGV-SM 0154, ICGV-SM 07539, ICGV-SM 07536, ICGV-SM 7501, ICGV-SM 99568 and ICGV SM 07520. Nachingwea 2013 in Tanzania, Nakabango 2014 in Uganda and Chitedze 2015 in Malawi were the most representative and discriminative environments. Considering the implications of interactions for Valencia groundnut breeding in East and Southern Africa we propose that different varieties should be targeted for production in different environments and at the same time used for breeding in specific environments.
Background Agri-innovations are mostly delivered to farmers through private and public sector-led institutions around the world, with various degrees of success in Malawi. These distribution systems, on the other hand, do not meet everyone's production and productivity needs, particularly those of smallholder farmers. Alternative gap-filling systems are therefore required. Over the course of 7 years, we performed two studies in Malawi to assess the efficiency of integrated farmer led agri-innovation delivery mechanisms, in order to advise programming and delivery improvements. The first study looked at the impact of farmer-led technology delivery on agricultural output and productivity. It was split into two phases: learning (2010–2015) and scaling-out (2016–2019). The second study looked at how smallholder farmers changed their behaviour, after receiving instruction during the scaling-out phase. A farmer-led social network, community seed banks, was used as the research platform. Results The number of farmers who had access to improved seed increased by 35-fold from 2.4% in the baseline year. Groundnut, the major study crop, had a 1.8-fold increase in productivity. In sorghum, and common bean, the difference in grain yield between beneficiaries and control populations was 19% and 30%, respectively. The lowest aflatoxin contamination was found in groundnut grain samples from trained farmers, showing that learning had occurred, with three training sessions sufficient for initiating and sustaining adoption of agri-innovations. Conclusions Many developing country economies have limited investments in agricultural extension and advisory services, and as well as inefficient agri-input delivery systems, limiting access to science solutions needed to boost productivity. The farmer-led technology and knowledge dissemination systems examined in this research, are appropriate for a variety farming contexts, especially for crops underinvested by private sector, and where public extension and advisory services are poorly funded.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.