Abstract
Stability in performance is important for determining adaptation and recommendation of pre-commercial crop varieties. This study was conducted with the following objectives: i) to determine stability of grain yield for 55 quality protein maize (QPM) single cross hybrids generated from 14 inbred lines ii) to determine the pattern of grouping of QPM hybrids and test environments based on grain yield response. The test hybrids were generated during the second season of 2015 and evaluated in three agro-ecological zones during the first season of 2016. Two checks were used: Longe 5D, a popular QPM hybrid and a top cross of Longe 5D with CML511. Additive main effects and multiplicative interaction (AMMI) and genotype and genotype by environment interaction (GGE) analyses were used to assess the stability of the hybrids. Results showed highly significant differences between genotypes, environments and GEI. The first principal component axis (IPCAI) was significant (p < 0.01) and accounted for 61.5% of the interaction effect. Both (IPCAI) and IPCAII) cumulatively contributed to entire degrees of freedom available for interaction component. Hybrid QPMSC-29 had the highest grain yield across environments. The AMMI biplot clearly depicted the genotypes on the bases of their adaptation patterns. Hybrids QPMSC-43, QPMSC-12, QPMSC-18 and QPMSC-29 were found to be more stable and responsive to favorable environments. Among them QPMSC-18 was more stable across locations. The AMMI biplot successfully identified 2 mega-environments as Namulonge and Bulindi in the first mega-environment with QPMSC-29 as the winning genotype and Masaka as the second mega-environment with QPMSC-10 as the winning genotypes. Hybrid, QPMSC-46 was an ideal genotype with above average score for grain yield. The single cross hybrids QPMSC-29, QPMSC-18 and QPMSC-10 were identified as stable yielder across environments in addition to higher yield. These hybrids can be recommended for all the three locations, for cultivation.
Highlights
Maize (Zea mays L.) is an important food, feed and cash crop in east and southern Africa (ESA) grown predominantly by small-scale farmers
Data of the analysis of variance showed that grain yield was influenced by the environments of testing, genotypes and their interactions (Table 2)
The AMMI analysis of variance of grain yield of the fifty five genotypes tested in three environments showed that 71.65% of the total sum of squares was attributable to genotypic effects, 10.51%to environmental effects and 17.83% to genotype × environment interaction effects (Table 2)
Summary
Maize (Zea mays L.) is an important food, feed and cash crop in east and southern Africa (ESA) grown predominantly by small-scale farmers. The low yields are attributed to a number of factors including low use of improved seed, climate variability, and low use of fertilizers contributing to declining soil fertility and poor crop management practices. These productivity constraining factors vary among maize growing environments and seasons within a year leading to unpredictable food security situations. Systematic evaluation of GEI effects for a given trait is useful for understanding varietal stability and strategic deployment of varieties (Acquaah, 2012), and has been exploited by breeders to identify and select more stable varieties recommended to farmers to reduce variability in performance from one production environment to another
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
