Genetic variability and breeding potential of Flintisa Composite of maize in two levels of technology

Abstract

The purpose this study was to verify the breeding potential of Flintisa Composite for low (LT) and high (HT) technology of cultivation, and the best selection strategy to be adopted. For this reason half-sib progenies were evaluated in the two technological levels. In HT, it was used basic fertilization, two top dressing and supplementary irrigation. In LT, these practices were suppressed, and less fertile soil was used. Except for grain yield (GY), heritability was high at plant level and at progenies mean level. With mass selection, estimated gains ranged from 3.3% (GY in LT) to 41.8% (tassel branches number in LT). For half-sib selection, estimated gains ranged from 4.7% (plant height in HT) to 23.6% (erect plants in HT). For ear height, stratified mass selection in just one environment should be valid for both. Half-sib selection, with S 1 recombination should be adopted in specific selection programs for LT and HT.

Environmental impact and genetic expressions of new drought tolerant maize genotypes in derived savannah agro-ecology

“…The highest value obtained from number of grains per cob was followed by cob dry weight, leaf dry matter and plant height. Phenotypic variance is influenced by genotypic variance and environmental variance (Andrade, 2019). Among the four traits with high phenotypic variances, number of grains per cob and leaf dry matter had higher genotypic variance than environmental variance, while cob dry weight and plant height had higher environmental variance than genotypic variance.…”

Effect of selection response for yield related traits in early and later generations of groundnut (Arachis hypogaea L.)

“…This low productivity is attributed to the narrow genetic base of the crop and rainfed cultivation, which renders the crop vulnerable to various biotic and abiotic stresses (Toker and Mutlu 2011). Variability is fundamental for the success of a selection work (Andrade 2019) since, progress in breeding programs depends on the amount of variability available in the population (Vinithashri et al 2019). Standard measures of variability, namely range, variance, and standard error, were commonly used to assess the variability JH Kamdar et al and gene action for desirable traits.…”

Estimation of Breeding Parameters from Phenotypic Data of F4:5 RIL in Ethiopian Malt Barley (Hordeum distichum L.) Breeding Population

“…Plant breeding programs are based on the e ective maintaining and reuse/shu ing of genetic variation aimed at generating new and improved combinations of alleles and assembling them in a single superior genetic background [1,2]. Genetic variation can be obtained from germplasm sources such as landraces or exotic lines from foreign countries that could be directly used to exploit the inherent genetic variance.…”