Anju Mahendru Singh

Construct core collections using the information measure 'Length of Encoded Attribute Values' (LEAV) using qualitative and/or quantitative trait data as described by Balakrishnan and Suresh (2001a) and (2001b) .

Implements multiple allocation and selection strategies of sampling to construct core collections primarily from clustered or grouped germplasm collection data. Provides methods for allocating entries to clusters/groups based on group sizes, group-wise distance-based diversity metrics, and group-wise diversity index estimates. Includes procedures for selecting entries within clusters/groups through random sampling, genetic distance-based approaches, and optimized diversity metric–based selection methods. See the package documentation for more, including full list of references for the methods implemented.

Provides a comprehensive framework for analyzing diversity from frequency/abundance count data. Implements a wide range of classical and entropy-based diversity indices, including Berger-Parker, Simpson (and related variants), Shannon, Brillouin, McIntosh, Margalef, Menhinick and Smith-Wilson. Supports permutation-based hypothesis tests for comparing groups with respect to diversity (global and pairwise comparisons), as well as confidence interval estimation using multiple bootstrap methods. Includes functionality for generating diversity profiles based on parametric families such as Hill numbers, Rényi entropy, and Tsallis entropy. The methods are applicable to ecological community data (species abundance counts) and genetic or phenotypic class frequency data.

Background: The nutritional composition of wheat is pivotal for food security and public health, given its global significance as a staple crop. This study focuses on 274 diverse wheat germplasm accessions to evaluate the biochemical traits: starch, protein, amylose, total soluble sugars (TSSs), and phytic acid. This research seeks to provide insights that can inform variability in the nutritional composition of wheat germplasm and targeted breeding strategies designed to optimize dietary outcomes. The correlation matrix aids in identifying germplasm with desirable biochemical traits, such as high‐protein accessions with lower starch or high‐amylose accessions for improved functional properties. Results: Quantitative analysis revealed that starch content ranged from 52.30 to 76.49 g/100 g, while protein levels varied from 8.5% to 19.07%, exhibiting significant inverse correlations with starch ( r = −0.61) and amylose ( r = −0.96). Amylose content ranged from 7.87 to 17.59 g/100 g, and TSS levels ranged from 3.27 to 5.76 g/100 g. Phytic acid ranged from 0.39 to 1.13 g/100 g. Principal component analysis (PCA) demonstrated that the first two components explained 84.5% of the variance, while hierarchical cluster analysis (HCA) identified three distinct clusters based on these nutritional traits. Conclusion: This research provides a comprehensive overview of the genetic variability in wheat germplasm, facilitating targeted breeding strategies for developing nutrient‐dense varieties. The robust correlation matrix supports the identification of specific germplasm suited for specific applications, promoting sustainable agriculture. Future investigations should focus on genomic interactions and sustainable methodologies to enhance long‐term agricultural resilience.

India is a treasure trove of biological diversity with its plant genetic resources playing a crucial role in the crop improvement serving as the foundation for the country’s sustainable food and nutritional security. India’s in vitro genebank (IVG) is part of the National Genebank at the Indian Council of Agricultural Research-National Bureau of Plant Genetic Resources (ICAR-NBPGR). The IVG houses distinctive multi-crop repository that utilizes several tissue culture techniques for short- to medium-term storage in in vitro active genebank (IVAG) and cryoconservation approaches for long-term storage in in vitro base genebank (IVBG). In IVAG, germplasm is conserved under normal and slow growth conditions with a subculture period of 1–36 months depending on the species/genotype and conservation approach. Currently, the IVAG holds 2,038 germplasm accessions (69 genera and 171 species) from six crop groups, viz. (a) tropical fruit crops (449), (b) temperate and minor tropical fruit crops (408), (c) tuber crops (530), (d) bulbous and ornamental crops (187), (e) medicinal and aromatic plants (232), and (f) spices and industrial crops (232). For long-term conservation, in vitro produced explants of various species are cryopreserved at the IVBG in liquid nitrogen. Utilizing various cryoconservation procedures, 347 accessions from several crop groups have been successfully conserved in the IVBG. Over the past four decades, in vitro conservation has been accomplished by the above mentioned cutting-edge techniques. This report highlights the efforts and achievements of the National Genebank in conserving horticultural genetic resources through in vitro and cryoconservation.

The study of polymorphism of glutenin makes it possible to identify and isolate desirable genotypes with higher grain quality. In the last few years, only a part of the genetic diversity among the modern and popular wheat germplasm and varieties based on the polymorphism of glutenin subunits are captured. To address this 107 wheat varieties released across different agricultural zones in India, were used to investigate HMW-GS and LMW-GS allele polymorphism, gene diversity and genetic variation in the Glu-1 and Glu-3 loci. Among the different HMW-GS, the highest genetic variation was observed at the Glu-D1 locus with both Glu-D1a and Glu-D1d possessing genetic variation of 0.490, 0.484 respectively. The highest genetic variation at the Glu-A3 locus was observed at the Glu-A3c and GluA3b possessing a genetic variation of 0.463, 0.411 respectively. This was followed by the Glu-B3j having a genetic variation of 0.386 at the Glu-B3 locus. Over 20 years a remarkable increase in the Glu-D1d allele is observed in the newly released varieties in India. Among all the zones, Glu-A1-null is the least frequent allele at the Glu-1 locus, however, it is present as the predominant allele in the NHZ of India. This study elucidates the relationships of these HMW and LMW allelic frequencies and genetic variation with their geographical distribution over the two different periods. This study provides reference data that can be used to assist the breeding, quality evaluation and development of good-quality wheat varieties.