Genotype by environment interaction and grain yield stability of drought tolerant cowpea landraces in Ethiopia

Abstract

Cowpea is one of the most important indigenous food and forage legumes in Africa. It serves as a primary source of protein for poor farmers in drought-prone areas of Ethiopia. The crop is used as a source of food, and insurance crop during the dry season. Cowpea is adaptable to a wide range of climatic conditions. Despite this, the productivity of the crop is generally low due to lack of stable and drought tolerant varieties. In this study, 25 cowpea genotypes were evaluated in ve environments using a triple lattice design during the 2017 and 2018 main cropping seasons. The objectives of this study were to estimate the magnitude of genotype by environment interaction (GEI) and grain yield stability of selected drought tolerant cowpea genotypes across different environments. The additive main effect and multiplicative interaction (AMMI) model indicated the contribution of environment, genotype and GEI as 63.98 6%, 2.66% and 16.30% of the total variation for grain yield, respectively. The magnitudes of the GEI sum of squares were 6.12 times that of the genotypes for grain yield. The IPCA1, IPCA2 and IPCA3 were all signi cant and explained 45.47%, 28.05% and 16.59% of the GEI variation, respectively. The results from AMMI, cultivar superior measure (Pi), genotype plus genotype-by-environment (GGE) biplot yield stability index (YSI), and AMMI stability value (ASV) analyses identi ed NLLP-CPC-07-145-21, NLLP-CPC-103-B and NLLP_CPC-07-54 as stable and high yielding genotypes across environments. Thus, these genotypes should be recommended for release for production for drought prone areas. NLLP-CPC-07-143, Kanketi and CP-EXTERETIS were the least stable. The AMMI1 biplot showed that Jinka was a high potential and favorable environment while Babile was an unfavorable environment for cowpea production.GGE biplots help visualize and compare the distance between each genotype and the ideal genotype located at the center of the concentric circle (Yan and Rajcan 2002). The ideal genotypes, based on proximity to the center of the concentric circle of the GGE biplot were ACC-216-747 and NLLP-CPC-07-145-21, with high yield and stability (Figure 2). In addition, NLLP-CPC-07-10 was located on the next homocentric circle and might be considered as a desirable genotype. In principle, the ideal genotype should have the longest vector, highest mean performance and with zero GEI, and/or it should perform consistently in all environments. Because of the genetic background or nature of the traits (yield) and level of expression, the ideal genotype does not always exist in reality. Therefore, such like genotypes the breeders can be used as a reference for genotype for further study. Genotypes which were high yielding but were not stable across environments could be recommended for a particular environment. Yan & Rajcan (2002) and Yan et al. (2007) speci ed that the environments with long vectors (PC1 scores) and relatively small angles or absolute with the AEC abscissa are valuable for greater discriminatory capacity (in terms of the geno...

Breeding of Vegetable Cowpea for Nutrition and Climate Resilience in Sub-Saharan Africa: Progress, Opportunities, and Challenges

“…Understanding the variation among cowpea genotypes for leaf shape and size could potentially assist breeders in improving the crop for drought tolerance and yield. Previous studies [134] have shown that drought tolerance is associated with small leaf size, while other studies have reported that leaf shape and size are associated with photosynthesis rate and capacity. It has also been reported that leaf shape is not affected by geographic region [135], while other studies [136] have reported the opposite.…”

“…Several studies have focused on investigating genotype × environment (G × E) interactions and the change in the ranking of cowpea genotypes for seed grain in Egypt [100], Brazil [133], Ethiopia [134], Zimbabwe [135], and South Africa [136][137][138]. Fewer studies [97] have focused on G × E for cowpea yield and nutritional values.…”

Modeling covariance structures for genetic and non‐genetic effects in cowpea multi‐environment trials

“…In cowpea, edaphoclimatic variables such as minimum temperature, solar radiation, rainfall, wind speed, length of crop growth cycle, and altitude can affect the performance of genotypes in different environments (Oliveira et al., 2020). Bear in mind that 100‐grain weight is a quantitative trait, so it is expected that the greatest variation in this trait is due to the environmental effects (Mekonnen et al., 2022).…”

Breeding implications of nodulation performance and root structure under natural inoculation for soil fertility enhancement and sustainable cowpea production

“…Cowpea as a dryland legume crop has significant contribution to food and nutritional security in tropical and sub-tropical regions of the world, including in sub-Saharan Africa (SSA) (Dube and Fanadzo, 2013;Mekonnen et al, 2022b). Cowpea often is called "the poor man's meat" as it is a significant and cheap source of protein, minerals, and vitamins for the rural poor who have limited access to protein from animal sources such as meat and fish in SSA communities (Dube and Fanadzo, 2013).…”

“…Cowpea often is called "the poor man's meat" as it is a significant and cheap source of protein, minerals, and vitamins for the rural poor who have limited access to protein from animal sources such as meat and fish in SSA communities (Dube and Fanadzo, 2013). It has the ability to grow under harsh environmental conditions where other major crops fail (Timko and Singh, 2008) and is a climate-resilient smart legume crop for food security, especially in SSA (Mekonnen et al, 2022b).…”