Inbred lines generated from 10 maize population developed between 1979 and 2008 were used to investigate the inbreeding depression of tropical maize varieties developed at different breeding eras and evaluated in (optimal and stressed) condition. Across all the environments used for this study, estimates of inbred depression (I) for grain yield which ranged from 15.63% for optimum environment to 35.85 under stem borer infestation, showed differences in the severity of the effects of practicing inbreeding in each of the populations and the different environments. The highest values of inbreeding depression for grain yield were recorded under stem borer infestation. The effect of inbreeding was the most severe for var. DMR-LSR-W under borer infestation and least for DMR-LSR-Y in stress free environment. This is an indication that the responses of the maize populations to inbreeding as well as the rate of attaining homozygosity differed with environments. Across the four different environments under which the genotypes were evaluated, average inbreeding depression for grain yield were greater relative to other traits considered which should be expected since grain yield is a quantitatively inherited trait, governed by many genes each with minor effects.
Maize is a major staple food and source of income for over 90% of the population in South Sudan however, average yield is very low (0.5-0.9 t/ha). Little research has been done on maize improvement in the country and farmers mainly depend on local and unimproved cultivars. Identification and release of adapted and high yielding hybrids may elevate average maize yield (t/ha) among the resource-poor farmers in the country. Improved maize hybrids from the region have not been tested under South Sudanese environments.
Objective
s of the study were to: (i) determine genotype by environment interactions among some regional maize genotypes; (ii) estimate genetic components and heritability for yield performances; and (iii) identify high yielding maize hybrids adapted to agroecologies of South Sudan. At least 48 maize genotypes including elite hybrids and open-pollinated varieties (OPV) adapted across sub-Saharan Africa and two local cultivars collected from local farmers in South Sudan were evaluated across five locations within greenbelt and ironstone plateau agro-ecologies over three years (2013-2015). Experiments were set up in a 12 × 4 alpha lattice design with 2 replications. Standard agronomic practices were followed and data recorded on yield traits and resistance to major diseases. Across locations and years analysis revealed significant differences among genotypes due to genotype and genotype × environment interactions (
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In salinity affected areas, variation in salinity level is the major cause of yield fluctuations in rice during the dry season (
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Seed starch content (SSC) is a decisive factor influencing soy food quality. Variation in SSC affects the composition of major components, oil, and protein in soybean seeds. Therefore, understanding G × E interaction of SSC is important to produce soybeans with stable SSC. In the present study, G × E interactions of 17 soybean genotypes having different SSC (0.24–1.48%) and correlation of SSC with crude protein (CP) and crude fat (CF) were investigated. The genotypes were evaluated for SSC and other traits at two planting dates across three locations over two years (2015 and 2016). The genotype × year, genotype × location, and genotype × year × location interactions were found to be significant (
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Eight advanced breeding lines of cowpea [
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Perennial poor fruit-set and variability in tree yield are among major problems of cashew nut production. Thus, development of improved stable genotypes would be a sustainable strategy to address this perpetual problem in order to boost income and livelihood of many smallholder farmers of this important commodity crop. Here, we have applied additive main effect and multiplicative interaction (AMMI) and genotype, genotype by environment (GGE) biplot analysis to a 3-year multi-locational trial data on nine yield component characters of cashew to evaluate phenotypic stability across diverse environments. Variance analysis showed significant variability in the cashew genotypes and strong influence of genotype by environment (GxE) on tree yield as none of the genotypes was stable for any of the yield components across locations. GxE data showed that a substantial portion of the variation was explained by the genotype (highly heritable), accounting for between 10% and 87% of the variation, while the environment accounted for between 0.7% and 37%. Data showed significant higher values of interaction (GxE) than the respective values for environment, and were mostly captured and could be explained by the first principal component axis (IPCA 1) for all the yield component characters. There was an inverse relationship between stability and yield as the best three yielding genotypes (KT_26, IW_222 and IW_31) were found to be the most unstable. Among the yield component tested, hermaphrodite flowers per panicle, nuts per panicle, nuts per tree, nut weight, and tree fruiting efficiency were identified to be critical components for nut yield. Although there was wide variation between the three environments evaluated, the data effectively identified two mega-environments (ME), and two superior genotypes (IW_222 and KT_26) suitable for these two mega-environments. The GxE complex exposes the short-comings of broad recommendations of common agronomic-husbandry technologies across diverse cashew ecologies as each mega-environment would require specific adaptable technologies for optimal plant output. Above all, the data presented here underscore the importance of multi-locational evaluation of genotypes for varietal development in cashew.
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