Multivariate Diversity Analysis for Grain Micronutrients Concentration, Yield and Agro-morphological Traits in Pearl millet (Pennisetum glaucum (L) R. Br.)

Abstract

Micronutrient malnutrition resulting from the dietary deficiency of important minerals such as Iron (Fe), Zinc (Zn), Copper (Cu) and Manganese (Mn) in the staple food crops like pearl millet leads to ubiquitous food-related health problems. In context to this present investigation was undertaken to study the phenotypic diversity among 48 maintainer (B) and restorer lines (R) of pearl millet genotypes for grain micronutrients concentration, yield and agro-morphological traits using multivariate approach. Higher range, large value of Shannon-weaver Diversity Index for both traits and genotypes and large differences in mean values for most of the characters showed that sufficient diversity existed among the genotypes and traits. Cluster analysis using unweighted pair group method of arithmetic averages (UPGMA) grouped the genotypes into five clusters with varied number which suggested the clear differentiation among B and R lines with some exceptions. Clustering of pearl millet genotypes from different geographical locations or source/origin into same cluster has confirmed that they are genetically related, and possibly from the same progenitor, but could have been separated by geographical or ecological barrier. The principal component analysis (PCA) revealed that most of the variation (68.83%) was accounted by first four PCA and genotypes from maintainer were clustered into left side of the biplot graph while the lines from the restorer category were distributed throughout the PCA biplot graph. Average Diversity Index of 1.883 and 3.792 for genotypes and traits respectively, further validated that the genotypes were more diverse among themselves and for all the traits studied. Association studies revealed significant positive correlation of grain Fe content with the grain Zn and Cu content; grain yield per plant with the plant height, panicle weight and dry fodder yield per plant; panicle weight with plant height, panicle length and dry fodder yield; panicle length with plant height and dry fodder yield per plant and dry fodder yield per plant with plant height. It indicated the likely effectiveness of simultaneous improvement of all these characters along with grain micronutrients in pearl millet. Grain yield per plant showed non-significant positive or negative correlation with grain micronutrients concentration thus suggesting improvement in nutrient content without compromising yield. The significant negative association between the grain yield and panicle weight with days to flowering has the great advantages in pearl millet cultivation as crop can fit into multiple cropping system in arid and semi-arid environments.

Delineating multivariate divergence, heritability, trait association and identification of superior omega-3-fatty acid specific genotypes in linseed (Linum usitatissimum L.)

“…DIKSHIT and SHIVARAJ (2015) and KAUR et al (2018) also reported that linseed accessions did not necessarily assemble into the same cluster based on their geographical origins. Clustering of linseed accessions together regardless of their source supports the possibility of a common progenitor but separation by geographical or ecological isolation mechanisms as reported by KUMAR et al (2020) in pearl millet. The genotypes from the different geographical location falls under different clusters didn't rules out the pollen-mediated gene flow in linseed (JHALA et al, 2011) and ryegrass (MAITY et al, 2021).…”

“…High heritability coupled with high genetic advance for yield and related traits were reported in linseed by AKBAR et al, 2003;TADESSE et al, 2010;MIRZA et al, 2011;KUMAR et al, 2012;SIVARAJ et al, 2012;DIKSHIT and SIVARAJ, 2015;CHANDRAWATI et al, 2016;YOU et al, 2017;KAUR et al, 2018;DHIRHI and MEHTA, 2019. Grouping of genotypes into few numbers of homogenous clusters facilitates the selection of diverse lines for the hybridization purpose. It permits precise comparison among all the possible pairs of genotypes and provides an opportunity for bringing together gene constellations and yielding transgressive segregants from crossing between diverse lines (KUMAR et al, 2020). The distribution of 50 linseed genotypes into nine different clusters revealed considerable differences among linseed genotypes for yield and various morphological characters.…”

Genetic Dissection of Seedling Root System Architectural Traits in a Diverse Panel of Hexaploid Wheat through Multi-Locus Genome-Wide Association Mapping for Improving Drought Tolerance

“…The extent of phenotypic variation of the QTNs varied from R 2 = 1.8% for QTN-SOLRN at Chr 6A-AX-95244609 to R 2 = 38.6% for QTN-SOLRN at Chr 3B-AX-95150666. The highest number of QTNs was identified in chromosome 7B (44) followed by 6A (34), 3B (33), 7A (31), 1D (31), 2B (29), 1B (29) and 6B (27). Further, among the total 456 QTNs, 87 QTNs and 27 QTNs were repeatedly detected by two, three or more ML-GWAS models, respectively.…”

“…In contrast to the conventional QTL approach, the AM approach enables screening of a large number of alleles present in natural populations of species, thus providing greater resolution mapping of a target trait. In the past couple of years, AM has been widely applied to map traits in many crop species including wheat, rice, barley (Hordeum vulgare L.), maize and soybean (Glycine max L. Merril) [21,[24][25][26][27] with the availability of high-throughput genotyping and phenotyping platforms [22,23].…”

Agromorphological Diversity among Popcorn (Zea mays. everta) Landraces Grown in Zambia

“…Among the phenotypic, biochemical, and molecular methods [8,9] employed in the assessment of genetic diversity, the phenotypic method is a relatively inexpensive approach. A number of research efforts have utilized agromorphological traits as a singular approach or in combination with molecular markers to characterize and study the diversity of maize populations [10,11,12].…”