Germplasm is a valuable natural resource that provides knowledge about the genetic composition of a species and is crucial for conserving plant diversity. Germplasm protection strategies not only involve rescuing plant species threatened with extinction, but also help preserve all essential plants, on which rests the survival of all organisms. The successful use of genetic resources necessitates their diligent collection, storage, analysis, documentation, and exchange. Slow growth cultures, cryopreservation, pollen and DNA banks, botanical gardens, genetic reserves, and farmers’ fields are a few germplasm conservation techniques being employed. However, the adoption of in-vitro techniques with any chance of genetic instability could lead to the destruction of the entire substance, but the improved understanding of basic regeneration biology would, in turn, undoubtedly increase the capacity to regenerate new plants, thus expanding selection possibilities. Germplasm conservation seeks to conserve endangered and vulnerable plant species worldwide for future proliferation and development; it is also the bedrock of agricultural production.

A meta-QTL analysis was conducted in Indian mustard to identify robust and stable meta-QTLs (MQTLs) by utilizing 1504 available QTLs, which included 891 QTLs for yield-related traits and 613 QTLs for quality traits. For yield-related traits, a total of 57 MQTLs (YRTs_MQTLs) were uncovered from the clustering of 560 projected QTLs, which had a 4.18-fold smaller confidence interval (CI) than that of the initial QTLs, whereas, for quality traits, as many as 51 MQTLs (Quality_MQTLs) were derived from 324 projected QTLs, which had a 2.65-fold smaller CI than that of the initial QTLs. Sixteen YRTs_MQTLs were observed to share chromosomal positions with 16 Quality_MQTLs. Moreover, four most promising YRTs_MQTLs and eight Quality-MQTLs were also selected and recommended for use in breeding programs. Four of these selected MQTLs were also validated with significant SNPs that were identified in previously published genome-wide association studies. Further, in silico functional analysis of some promising MQTLs allowed the detection of as many as 1435 genes, which also involved 15 high-confidence candidate genes (CGs) for yield-related traits and 46 high-confidence CGs for quality traits. After validation, the identified CGs can also be exploited to model the plant architecture and to improve quality traits through marker-assisted breeding, genetic engineering, and genome editing approaches.

Germplasm is a valuable natural resource in plant diversity that is crucial for its potential use. It provides knowledge about a species genetic composition. Germplasm protection strategies are not just planting hope threatened with extinction, they preserve medicinal and other essential plants on which survival rests. The successful use of genetic plant resources necessitates diligent collection, storage, analysis, documentation, and germplasm exchange. Slow growth cultures, cryopreservation, pollen and DNA banks, botanic gardens, genetic reserves and farmer’s fields are few conservation techniques. However, usage of an in vitro procedure with any chance of genetic instability leads to the destruction of the entire substance. Improved understanding of basic regeneration biology would, in turn, undoubtedly increase the capacity to regenerate plants from in vitro harvested explants, thus expanding selection possibilities. Germplasm conservation seeks to conserve endangered and vulnerable plant species worldwide for future proliferation and development; it is also the bedrock of agricultural production.

A field experiment was conducted at Dry land farm, S.V. Agricultural College, Tirupati in Kharif 2018 to study the effect of Plant Growth Regulators and micronutrients on growth, yield and quality of sorghum. The objective of the study was to assess the visual comparison among genotypes on the basis of multiple traits and also to graphically describe the interrelationships among all measured traits on the basis of overall pattern of the data for the 42 genotypes of pearl millet that were evaluated for 22 physiological, nutritional, and yield related traits in a randomized complete block design, using GT biplot analysis through which, the principal components PC1 and PC2 explained 45.63% of the total variation based on all the traits and the genotypes. The GT biplot analysis is a powerful statistical tool for studying relationship among traits, evaluating cultivars based on multiple traits and for identifying those that are superior in certain traits. Few yield related traits, SPAD Chlorophyll Meter Reading (SCMR), harvest index, Leaf Area Index (LAI), Leaf Area Duration (LAD) and protein content had a positive relationship with yield which were recognized as crucial traits for boosting grain yield and nutritional quality. The genotypes ATP-15, ATP-13, ATP-10, ATP-16, ATP-5, ATP-7, ATP-11, ATP-18, ATP-14 and ATP-12 showed superior performance for grain yield as well as other yield contributing traits. Whereas, the genotypes ICHiFe-18, ICHiFe-12, ATP-3, ICHiFe-21, ATP-2, ICHiFe-20, ATP-4, ATP-8, ATP-15, ICHiFe-14, ICHiFe-4, ICHiFe-2 and ICHiFe-5 showed superior performance for nutritional traits. By considering all the studied traits, the genotype ATP-15 was selected as the ideal and most desirable cultivar.

The authors would like to make the following correction to the published paper