Green revolution to genome revolution: driving better resilient crops against environmental instability.

Crop improvement programmes began with traditional breeding practices since the inception of agriculture. Farmers and plant breeders continue to use these strategies for crop improvement due to their broad application in modifying crop genetic compositions. Nonetheless, conventional breeding has significant downsides in regard to effort and time. Crop productivity seems to be hitting a plateau as a consequence of environmental issues and the scarcity of agricultural land. Therefore, continuous pursuit of advancement in crop improvement is essential. Recent technical innovations have resulted in a revolutionary shift in the pattern of breeding methods, leaning further towards molecular approaches. Among the promising approaches, marker-assisted selection, QTL mapping, omics-assisted breeding, genome-wide association studies and genome editing have lately gained prominence. Several governments have progressively relaxed their restrictions relating to genome editing. The present review highlights the evolutionary and revolutionary approaches that have been utilized for crop improvement in a bid to produce climate-resilient crops observing the consequence of climate change. Additionally, it will contribute to the comprehension of plant breeding succession so far. Investing in advanced sequencing technologies and bioinformatics will deepen our understanding of genetic variations and their functional implications, contributing to breakthroughs in crop improvement and biodiversity conservation.

Biochemical assessment of oat genotypes revealed variability in grain quality with nutrition and crop improvement implications.

Oat is a potent source of nutrients and bioactive compounds offering potential health benefits and role in combating micronutrient malnutrition problems. To exploit nutritional and quality traits of oats, a biochemical assessment of 112 oat genotypes was conducted. The high range of variability for total phenol (1.7-31.3 mg/g), ß-glucan (1.0-8.0 mg/g), calcium (1.91-4.34 mg/g), zinc (3.80-6.50 mg/100 g), iron (0.66-4.89 mg/100 g) and manganese (2.88-8.0 mg/100 g) was revealed among genotypes. A higher amount of iron and zinc was found in genotypes OS-6, HFO-638, HFO-915 & HFO-918, whereas, elevated levels of manganese and zinc were recorded in genotypes OS-403 & OL-1804. The results revealed groups of low phytic acid oat genotypes containing high crude protein (HFO-52, HFO-270, HFO-330), ß-glucan (HFO-62, HFO-588, HFO-926). A significant positive correlation was obtained between copper with iron, manganese, and calcium content. These findings could be useful for developing value-added oat food products and novel oat varieties.

Association Mapping for Yield Attributing Traits and Yellow Mosaic Disease Resistance in Mung Bean [Vigna radiata (L.) Wilczek].

Mung bean [Vigna radiata (L.) Wilczek] is an important short-duration grain legume widely known for its nutritional, soil ameliorative, and cropping system intensification properties. This study aims at evaluating genetic diversity among mung bean genotypes and detecting genomic regions associated with various yield attributing traits and yellow mosaic disease (YMD) resistance by association mapping. A panel of 80 cultivars and advanced breeding lines was evaluated for 10 yield-related and YMD resistance traits during kharif (monsoon) and summer seasons of 2018-2019 and 2019-2020. A total of 164 genome-wide simple sequence repeat (SSR) markers were initially screened, out of which 89 were found polymorphic which generated 317 polymorphic alleles with an average of 3.56 alleles per SSR locus. The number of alleles at each locus varied from 2 to 7. The population genetic structure analysis grouped different genotypes in three major clusters and three genetically distinct subpopulations (SPs) (i.e., SP-1, SP-2, and SP-3) with one admixture subpopulation (SP-4). Both cluster and population genetic structure analysis categorized the advanced mung bean genotypes in a single group/SP and the released varieties in other groups/SPs, suggesting that the studied genotypes may have common ancestral history at some level. The population genetic structure was also in agreement with the genetic diversity analysis. The estimate of the average degree of linkage disequilibrium (LD) present at the genome level in 80 mung bean genotypes unveiled significant LD blocks. Over the four seasons, 10 marker-trait associations were observed significant for YMD and four seed yield (SY)-related traits viz., days to flowering, days to maturity, plant height, and number of pods per plant using the mixed linear model (MLM) method. These associations may be useful for marker-assisted mung bean yield improvement programs and YMD resistance.