Descriptive statistical analysis and variability studies in germplasm collections of Barnyard Millet (Echinochloa frumentacea L.)

Abstract

A study was conducted to evaluate the variability among fifty three genotypes of Barnyard millet in Randomized Block Design with two replications. The traits viz., plant height, flag leaf width, inflorescence length, the number of racemes per panicle, length of lower raceme left, test weight, relative water content, proline content and harvest index were found to be negatively skewed indicating the predominance of additive gene action. Thus these traits could be considered for selection criteria, while selecting genotypes for crop improvement. Analysis of genetic variability revealed that peduncle length, grain yield, stem girth, the number of tillers, fodder yield, proline content and flag leaf width established relatively high GCV value and thus these characters could be exploited for successful isolation of desirable accessions for the characters concerned. High heritability coupled with high genetic advance were observed for the traits like days to 50% flowering, plant height, flag leaf length, flag leaf width, inflorescence length and panicle breadth, the number of racemes/panicle, peduncle length, length of lower raceme -right, the number of nodes, stem girth, the number of tillers, fodder yield, relative water content, proline and grain yield which implied the presence of additive gene effects, controlling these traits. Hence the selection for these traits could be effective for improvement of any desired genotype.

Genetic variability and association analysis in barnyard millet (Echinochloa frumentaceae) under multiple environments

“…All traits recorded maximum heritability which concur with the findings of Monika et al (2021) for fodder yield. Similar findings were reported by Vanniarajan and Chandirakala (2020) and Renganathan et al (2018) on barnyard millet (Table 3). High hertitability for grain yield per plant, plant height and flag leaf breadth were in accordance with the findings of Vetriventhan and Upadhayaya, (2018) in proso millet.…”

“…It was followed by grain yield per plant (40.55%) and single ear head weight (38.82%). High PCV and GCV values for breadth of flag leaf and grain yield per plant were similar to the findings of Shet et al (2009) in finger millet; Shanmuganathan (2010) andAnil kumar et al (2019) in pearl millet; Vemanna et al (2013) and Nirosh et al (2021) in sorghum; Nandini et al (2016) in little millet; Vanniarajan and Chandirakala (2020). The results on GCV and PVC of the traits, fodder yield per plant, grain yield per plant, single ear head weight and number of productive tillers were in accordance with the results of Nirubana et al (2017) and Jyoti et al (2018) in kodo millet.…”

“…Less difference was observed between PCV and GCV values which indicated the lesser influence of environment for all the traits. The results were on par with Jyoti et al (2018) and Vanniarajan and Chandirakala (2020).…”

Genetic variability and association analysis of yield and yield attributing traits in little millet (Panicum sumatrense Roth. ex. Roem. and Schultz.)

“…As a result, by using different genotypes as parents to create hybrids, these features could be improved. Similar results were revealed by Vanniarajan and Chandirakala (2020) in Barnyard millet.…”

“…Skewness is a statistical tool that is widely used in plant breeding to better understand the characteristics of quantitative traits (Fisher, 1932). One of the primary advantages of skewness is that it can help breeders to determine the type of gene action responsible for a particular trait, as positive skewness often suggests additive gene action while negative skewness is more indicative of non-additive gene action (Vanniarajan and Chandirakala, 2020) The aim of this study was to investigate the variability that existed within the little millet germplasm. In addition, the relationship between yield and yield attributing traits was explored through correlation analysis.…”