Open AccessGenotype by Environment Interaction of Cotton Genotypes for Seed Cotton Yield in Zambia
Author(s) -
Martin Simasiku,
D Lungu,
Langa Tembo
Publication year - 2020
Publication title -
asian journal of research in crop science
Language(s) - English
Resource type - Journals
ISSN - 2581-7167
DOI - 10.9734/ajrcs/2020/v5i230092
Subject(s) - biplot , genotype , gene–environment interaction , ammi , hectare , biology , crop , grain yield , yield (engineering) , microbiology and biotechnology , backcrossing , agronomy , genetics , ecology , agriculture , gene , materials science , metallurgy
Cotton (Gossypium hirsutum L.) is an important cash crop in Zambia. The national seed cotton yield (SCY) per hectare ranges from 200-500 kg/ ha as compared to the potential of up to 2500 kg/ ha. Understanding the specific performance of several genotypes across different environments is an option, which may maximize specific genotypic performance. In addition, the performance of specific environments if known concerning specific and mean genotypic performance may guide the breeding approaches to these environments. This study therefore investigated the presence of SCY mega-production environments in Zambia and delineated the environments and identified the ideal test environment capable of discriminating yield differences among genotypes. Thirty (30) genotypes, were planted following a 6 x 5 lattice design with three replications in seven environments of Zambia. Additive main effects and multiplicative interaction (AMMI) model and genotype plus genotype by environment (GGE) biplot were used to explore the genotype by genotypic environmental interaction (GEI). Three mega environments (M1, M2 and M3) were identified. Genotype G27, G26 and G28 were the best performing genotypes in M1, M2 and M3 with overall mean SCY of 1416, 1320 and 960 kg/ ha respectively. Among the locations, Masumba was identified as an ideal test environment with mean SCY of 1249 kg/ ha. Therefore, testing seed cotton genotypic yield and selecting desirable genotypes in Masumba may be sufficient for evaluation.