Meeting the projected 70% rise in agricultural output by 2050 to sustain a global population of 9.6 billion poses a formidable challenge amid intensifying biotic and abiotic stresses. Traditional breeding methods, although foundational, are limited in their ability to improve complex polygenic traits such as yield, stress tolerance, and disease resistance. Genomic selection (GS) has emerged as a transformative approach that leverages genome-wide markers to predict breeding values with higher accuracy and efficiency. Unlike marker-assisted selection (MAS) and genome-wide association studies (GWAS), which emphasize major-effect loci, GS captures the cumulative contribution of numerous small-effect loci, enabling faster genetic gains for complex traits. This review outlines the conceptual framework, evolution, and integration of GS with cutting-edge technologies such as high-throughput genotyping, phenomics, multi-omics, and machine learning. It also discusses key achievements, implementation strategies, and the potential of GS to enhance selection accuracy, shorten breeding cycles, and develop climate-resilient, high-yielding cultivars. The integration of GS within modern breeding pipelines represents a paradigm shift toward sustainable crop improvement and global food security in an era of climatic uncertainty.

Drought and heat stress increasingly threaten global wheat (Triticum aestivum L.) production, posing major challenges to food security and sustainable agriculture. Identifying genotypes that combine high yield potential with physiological resilience across diverse environments is essential for developing climate-smart wheat cultivars. The objective of this study was to identify high-yielding and physiologically resilient wheat genotypes with stable performance across diverse environments under drought and heat stress using multivariate and multi-trait analytical approaches. Forty-nine wheat genotypes comprising 43 promising breeding lines (G1–G43) and six released checks (G44–G49) were evaluated across eight locations representing distinct mega-environments during the 2022–23 Rabi season. Trials were conducted under normal (N), drought (D), and late-sown heat (H) conditions. Grain yield, biomass, and key physiological traits were analyzed using multivariate approaches and multi-trait indices to assess genotype performance, stability, and adaptability under drought and heat stress conditions. Highly significant (p ≤ 0.001) effects of genotype, environment, and genotype × environment (G×E) interaction were observed for all traits. Mean grain yield declined from 6.5 t ha⁻¹ under normal conditions to 4.5 t ha⁻¹ (–31

Enhancing low nitrogen (LN) tolerance is crucial for maintaining wheat productivity, particularly in the era of climate change and increasing input costs. This study aimed to identify high-yielding, LN-tolerant, and stable wheat genotypes using integrated multivariate approaches. Fifty diverse genotypes, including globally sourced germplasm and landmark Indian cultivars, were evaluated across three agro-climatic zones under two nitrogen regimes for two consecutive years. Pooled ANOVA revealed significant effects of genotype, nitrogen level, and genotype x environment interaction. Hierarchical clustering identified four clusters, with cluster I comprising high-yielding, nitrogen-efficient genotypes. For grain yield under nitrogen stress, NARBADA 4 was the only genotype with a BLUP based Z-score above + 2, indicating exceptional stability and yield potential. Based on the GGE's Mean vs. Stability plot for grain yield, KRL 1-4 exhibited the highest mean performance coupled with stability. A novel metric, Gaind (decadal gain index) was introduced to assess genetic gains for LN tolerance across decades. Decadal trend analysis showed non-linear gains in low-N tolerance, peaking in the 1970s and 2000s but declining in the 2010s. Comprehensive multivariate index analysis based on pooling the index ranks highlighted MACS 6222, NARBADA 4, MACS 2496, K 307, and HI 1544 as the most promising genotypes. These genotypes are promising for LN-specific breeding and genetic improvement programs, offering potential for both commercial cultivation and the mapping of nitrogen use efficiency traits. The findings pave the way for developing widely adapted LN-tolerant wheat cultivars.

Wheat (Triticum aestivum L.) is among the most extensively grown staple crops worldwide. A set of 188 recombinant inbred lines (RILs) derived from a cross between HD2932 and Synthetic 46 was evaluated over three consecutive years (2021-22, 2022-23, and 2023-24) for plant height (PH), spike length (SL), spikelets per spike (SPS), thousand kernel weight (TKW), kernel length (KL), kernel width (KW), and kernel thickness (KT). The population displayed wide phenotypic variability with quantitative inheritance for all the traits. High-density genotyping was performed using 910 SSR markers and a 35K SNP array. Twenty-eight QTLs, including six for PH, two for SL, three for SPS, two for TKW, five for KL, six for KW, and four for KT distributed across 16 chromosomes were identified. QTkw.iari_4B, flanked by Xgwm149-AX-94559916, was detected in all three environments (Q × E not formally tested) consistently and co-localized with QTLs for PH, KL, and KT, indicating a potentially important genomic region for yield improvement. Promising lines such as RIL 122 and RIL 66 exhibited superior kernel characteristics, while RIL 155 showed lower expression values. In silico analysis identified 28 candidate genes within these QTL regions, offering insights into trait regulation. These findings may serve as potential resources for marker-assisted selection in wheat breeding programs to enhance yield and grain quality parameters.

Durum wheat (Triticum durum Desf.) is an important species in wheat where drought poses a significant challenge for its productivity and world food security. The study was carried out during winter (rabi) season 2021–22 and 2022–23 at University of Agricultural Sciences, Dharwad, Karnataka to investigate the genetic variability and association between morphological and drought-responsive traits for grain yield in durum wheat collected from International Center for Agricultural Research in the Dry Areas (ICARDA) and International Maize and Wheat Improvement Center (CIMMYT). Pooled analysis of variance revealed highly significant differences (P<0.05) in the quantitative traits suggesting the indeed variability among the germplasm lines and their response to selection. Under moisture stress conditions, the genotypes exhibited high variability for traits like tillers/m, flag leaf area, peduncle length, number of grains/spike and grain yield. These traits exhibiting high genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) under both stress and non-stress condition indicates ample scope for improvement in the traits, when selection is practiced. Increase in grain yield under moisture stress was observed to be positively correlated with various factors, including the number of tillers/m, flag leaf area, peduncle length, plant height, and the number of grains/spike. Principal component analysis (PCA) explained under PC1 and PC2 showed insight for selecting traits and genotypes to improve grain yield under moisture stress where, the direct selection is ineffective. In this analysis, a total of 11 distinct components were identified, with the first four accounting for approximately 60 per cent of the variation under moisture stress conditions. The first two components exhibited strong associations with phenological, agronomic and yield-related characteristics. Germplasm lines were classified based on stress tolerance index. Tolerant (77) with STI value > 0.9, moderately tolerant (18) with STI value 0.8–0.9, and susceptible (130) with STI value < 0.8 based on their sensitivity to drought stress. In the tolerant category, the genotypes GDP2022-246, GDP2022-198, GDP2022-52, GDP2022-216, and GDP2022-47 demonstrated promising performance with good grain yield under moisture stress conditions.

Introduction:Septoria blotch is a globally significant disease, which ranks second in importance after wheat rusts that causes substantial yield losses. The development of Septoria blotch resistant cultivars through molecular approaches is both economical and sustainable strategy to contain the disease. Methods:For identifying genomic regions associated with resistance to Septoria tritici blotch (STB) and Septoria nodorum blotch (SNB) in wheat, a genome-wide association study (GWAS) was conducted using a diverse panel of 191 spring and winter wheat genotypes. The panel was genotyped using DArTseq™ technology and phenotyped under natural field conditions for three cropping seasons (2019-2020, 2020-2021, and 2021-2022) and under artificially inoculated field conditions for two cropping seasons (2020-2021 and 2021-2022). Additionally, the panel was phenotyped under greenhouse conditions for STB (five mixed isolates in a single experiment) and SNB (four independent isolates and a purified toxin in five different independent experiments). Results and Discussion:GWAS identified nine marker-trait associations (MTAs), including six MTAs for different isolates under greenhouse conditions, two MTAs under natural field conditions, and one MTA under artificially inoculated field conditions. A pleiotropic MTA (100023665) was identified on chromosome 5B governing resistance against SNB isolate Pn Sn2K_USA and SNB purified toxin Pn ToxA_USA and explaining 30.73% and 46.94% of phenotypic variation, respectively. In silico analysis identified important candidate genes belonging to the leucine-rich repeat (LRR) domain superfamily, zinc finger GRF-type transcription factors, potassium transporters, nucleotide-binding site (NBS) domain superfamily, disease resistance protein, P-loop containing nucleoside triphosphate hydrolase, virus X resistance protein, and NB-ARC domains. The stable and major MTAs associated with disease resistant putative candidate genes are valuable for further validation and subsequent application in wheat septoria blotch resistance breeding.

In the postgenomics era, genomics‐assisted crop improvement has gained importance. Identifying closely linked markers to the desired trait is essential to practice indirect selection; association mapping through genome‐wide association studies (GWAS) has emerged as a popular approach to identify such associations owing to its relative advantages over QTL mapping. Understanding the fundamentals of GWAS is critical to reducing the high rate of false positive discoveries and effectively utilizing true associations in crop breeding. The success of GWAS depends on several key factors including population size, marker type and density, model, trait's heritability, population structure and phenotyping. Several empirical studies on GWAS realized impacts on crop improvement are recently being reported. For a holistic understanding of the technology, we briefly discuss the concept of linkage disequilibrium, mapping populations (structured and unstructured), modelling marker–trait associations, genetic associations through the statistical framework, mixed linear model, multilocus mixed model, appropriate model selection, machine learning in GWAS, confounding constraints in GWAS, population structure, rare and less frequent alleles, cryptic genetic relatedness, extreme phenotype–GWAS (XPGWAS) and current status of GWAS in crop improvement are reviewed.

Saccharum spontaneum, a wild progenitor of sugarcane, serves as a vital source of genes for resistance to biotic and abiotic stresses, particularly tolerance to water stress. To assess the drought tolerance potential of Saccharum spontaneum, 40 accessions along with two checks were evaluated in four environments for four drought-related traits, namely fresh biomass per clump (FBM), dry biomass per clump (DBM), tiller number per clump (TILL), and stalk height (SH) under control and drought treatments. Significant reductions in trait values were observed in each of these traits, and analysis of variance revealed significant differences among the accessions for stress tolerance and differential performance of accessions in control and drought. Among five computed stress tolerance indices for four traits, drought tolerance coefficient (DC) and geometric mean productivity (GMP) were uncorrelated, and promising genotypes were selected based on an integrated comprehensive index termed as membership function value for drought tolerance (MFVD) for each trait and across the traits. Considering environment-wise and pooled multivariate analyses, accessions IND 04–1372, IND 99–847, IND 99–850, IND 99–984, and IND 03–1307 were considered to be tolerant to drought and could serve as potential parents for trait introgression through developing trait-specific genetic stocks via interspecific hybridization.

Amidst shifting climate patterns, sugarcane rusts pose a significant challenge, particularly in the early stages of crop growth. Understanding the responses of parental sugarcane clones to rust pathogens is vital for redefining breeding programs to identify resistant varieties. An evaluation of the rust resistance of sugarcane parental clones engaged in India's breeding efforts revealed varying degrees of resistanceincluding resistant (R), moderately resistant (MR), moderately susceptible (MS), and susceptible (S). Over the crop seasons spanning from 2016 to 2022, a comprehensive field screening of 280 sugarcane clones for rust resistance, followed by the artificial screening of rust-free clones identified 144 clones (51.43

Identifying drought-tolerant accessions from the vast Saccharum spontaneum gene pool is crucial for their effective use in pre-breeding programs. In this study, 169 S. spontaneum accessions along with two checks were evaluated under control and drought stress conditions in augmented design. Eleven morpho-physiological traits were recorded, and drought tolerance was quantified through Drought tolerance Coefficient (DC). Among the traits, dry biomass per clump was most affected by moisture stress. DC also served as measure for genotypes’ drought tolerance levels, which ranged from 0.01 to 0.97 for dry biomass. Advanced multivariate selection indices—Factor Analysis and Ideotype Design (FAI-BLUP) and the Multi-trait Genotype-Ideotype Distance Index (MGIDI)—were applied to DC values. At a 5

Background Wheat rusts are important biotic stresses, development of rust resistant cultivars through molecular approaches is both economical and sustainable. Extensive phenotyping of large mapping populations under diverse production conditions and high-density genotyping would be the ideal strategy to identify major genomic regions for rust resistance in wheat. The genome-wide association study (GWAS) population of 280 genotypes was genotyped using a 35 K Axiom single nucleotide polymorphism (SNP) array and phenotyped at eight, 10, and, 10 environments, respectively for stem/black rust (SR), stripe/yellow rust (YR), and leaf/brown rust (LR). Results Forty-one Bonferroni corrected marker-trait associations (MTAs) were identified, including 17 for SR and 24 for YR. Ten stable MTAs and their best combinations were also identified. For YR, AX-94990952 on 1A + AX-95203560 on 4A + AX-94723806 on 3D + AX-95172478 on 1A showed the best combination with an average co-efficient of infection (ACI) score of 1.36. Similarly, for SR, AX-94883961 on 7B + AX-94843704 on 1B and AX-94883961 on 7B + AX-94580041 on 3D + AX-94843704 on 1B showed the best combination with an ACI score of around 9.0. The genotype PBW827 have the best MTA combinations for both YR and SR resistance. In silico study identifies key prospective candidate genes that are located within MTA regions. Further, the expression analysis revealed that 18 transcripts were upregulated to the tune of more than 1.5 folds including 19.36 folds (TraesCS3D02G519600) and 7.23 folds (TraesCS2D02G038900) under stress conditions compared to the control conditions. Furthermore, highly expressed genes in silico under stress conditions were analyzed to find out the potential links to the rust phenotype, and all four genes were found to be associated with the rust phenotype. Conclusion The identified novel MTAs, particularly stable and highly expressed MTAs are valuable for further validation and subsequent application in wheat rust resistance breeding. The genotypes with favorable MTA combinations can be used as prospective donors to develop elite cultivars with YR and SR resistance.

Winter sprouting potential and red rot resistance are two key parameters for successful sugarcane breeding in the subtropics. However, the cultivated sugarcane hybrids had a narrow genetic base; hence, the present study was planned to evaluate the Erianthus procerus genome introgressed Saccharum hybrids for their ratooning potential under subtropical climates and red rot tolerance under tropical and subtropical climates. A set of 15 Erianthus procerus derived hybrids confirmed through the 5S rDNA marker, along with five check varieties, were evaluated for agro-morphological, quality, and physiological traits for two years (2018–2019 and 2019–2020) and winter sprouting potential for three years (2018–2019, 2019–2020, and 2020–2021). The experimental material was also tested against the most prevalent isolates of the red rot pathogen in tropical (Cf671 and Cf671 + Cf9401) and subtropical regions (Cf08 and Cf09). The E. procerus hybrid GU 12—19 had the highest winter sprouting potential, with a winter sprouting index (WSI) of 10.6, followed by GU 12—22 with a WSI of 8.5. The other top-performing hybrids were as follows: GU 12—21 and GU 12—29 with a WSI of 7.2 and 6.9, respectively. A set of nine E. procerus-derived hybrids, i.e., GU04 (28) EO—2, GU12—19, GU12—21, GU12—22, GU12—23, GU12—26, GU12—27, GU12—30, and GU12—31, were resistant to the most prevalent isolates of red rot in both tropical and subtropical conditions. The association analysis revealed significant correlations between the various traits, particularly the fibre content, with a maximum number of associations, which indicates its multifaceted impact on sugarcane characteristics. Principal component analysis (PCA) summarised the data, explaining 57.6% of the total variation for the measured traits and genotypes, providing valuable insights into the performance and characteristics of the Erianthus procerus derived hybrids under subtropical climates. The anthocyanin content of Erianthus procerus hybrids was better than the check varieties, ranging from 0.123 to 0.179 (2018–2019) and 0.111 to 0.172 (2019–2020); anthocyanin plays a vital role in mitigating cold injury, acting as an antioxidant in cool weather conditions, particularly in sugarcane. Seven hybrids recorded a more than 22% fibre threshold, indicating their industrial potential. These hybrids could serve as potential donors for cold tolerance and a high ratooning ability, along with red rot resistance, under subtropical climates.

Markers linked to quantitative trait loci (QTL) must be validated in diverse genetic materials before they can be reliably used in molecular breeding programs. Here, 30 simple sequence repeat markers linked to QTL for grain iron content (GFeC), grain zinc content (GZnC), and grain protein content (GPC) were analyzed in 56 diverse dicoccum wheat genotypes. Seven markers were validated, including four (Xwmc617, Xbarc67, Xwmc283, Xgwm361) for grain iron content, one (Xbarc146) for both grain iron and protein contents; one more for grain protein (Xgwm408) and one for grain zinc content (Xgwm271). The segregating F2 population developed from the high-quality local landrace GPM DIC 87, and the high-yielding low-quality commercial cultivar (HW 1098) was used to revalidate the identified QTL-linked markers. As a result, Xgwm271 and Xbarc67 were re-validated in the F2 population, with values for phenotypic variation explained (PVE) of 56.50

Context Untapped wheat germplasm is conserved globally in genebanks. Evaluating it for grain quality and yield will help achieve nutritional and food security. Aims We aimed to evaluate the Indian National Genebank bread wheat core collection for grain quality, phenology and yield, to identify potential donor germplasm. Methods 1485 accessions were grown at three locations in India during winter 2015–2016 to evaluate test weight, grain protein content, sedimentation value (SV), days to spike emergence, days to maturity, grain yield and thousand-grain weight (TGW). Key results Best linear unbiased estimates indicated mean protein of 13.3%, 14.7%, and 13.0% and yield of 73.0 g/m, 70.9 g/m and 66.6 g/m at Ludhiana, Pune, and Varanasi locations, respectively. The SV ranged from 26.6–65.6 mL and 17.7–66.6 mL at the Ludhiana and Pune locations, respectively. The top 10 accessions were identified for all the studied traits. Six high protein accessions, with consistent protein of more than 15% along with moderate Thousand-grain and test weights were further validated and assessed for stability across environments. Grain protein content was correlated negatively with thousand-grain weight and yield, but positively with days to maturity and spike emergence. Conclusion The identified accessions with high trait values could be used in future breeding programmes to develop high yielding biofortified cultivars to address protein malnutrition and also cultivars with suitable end-product quality. Implications The diversity in a core collection can be exploited to develop modern high yielding bread wheat cultivars with higher grain protein content and suitable end-product quality.

Multi-environment data of four popular timely and four late-sown bread wheat varieties was examined for five crop seasons at five locations i.e., 25 environments to derive sustainability index (SI) in twelve quality traits and grain yield. SI was very high in bread and chapati quality, test weight, and flour recovery; moderate in protein, grain hardness, biscuit quality, gluten strength, and gluten quality; and poor in gluten, zinc, and iron contents. The adverse effect of late plating was realized in the sustainability of sedimentation value, gluten index, and iron. Variation sources impactful in the vulnerable quality were trait-specific. Crop year was the primary variation source in grain hardness, protein, sedimentation value, gluten index, and biscuit quality whereas location effect was the key in protein, gluten, iron, and zinc contents. Even in the commercial varieties, genotypes regulated the variations recorded in the strength and quality of the gluten. Genotypic differences in sustaining quality were observed for biscuit quality in timely-sown wheat, and gluten index and iron in the late-sown wheat. The analogy has been drawn between the quality and productivity of wheat for sustainability and the effect of the variation sources. Prospects of improvisation have been explored by selection of a better genotype or location. It has been envisaged that climatic variations can be challenging in sustaining the quality of gluten; grain hardness and iron content.

The present study was aimed to quantify the effect of growth regulator (GR) chlormequat chloride on lodging and yield attributes in the three recently released bread-wheat varieties in India. The findings indicate that, lodging incidence in high yielding wheat cultivars can be successfully reduced by a single spray of GR chlormequat chloride at the first node formation stage. A single treatment of GR significantly increased the yield/plot in all three wheat varieties and the effect of the second spray on grain yield was less incremental on study genotypes. Further, there was a differential GR×genotype interaction observed in yield and yield component traits. The lodging percentage in treatments showed a significant positive correlation with plant height and negative correlation with grain yield/plot and biomass. The higher yield of genotypes with GR treatment was attributed to increased tiller number, grain numbers per spike, thousand kernel weight and less lodging.

Sugarcane (Saccharum spp.) is an important commercial crop, which provides 40

Sugarcane rust incited by Puccinia melanocephala (brown rust) and P. kuehnii (orange rust) becomes very severe under warm,moist climatic conditions. Though there were methods to screen rust resistance under artificial conditions where rust is prevalent, there is no method to screen the rust resistance in a place where rust occurrence is not regular and severe. To overcome this problem, a simple method was devised to screen sugarcane leaves challenged with rust uredospores and maintaining the setup under optimum relative humidity and temperature for 15-20 days for identifying the rust resistant sugarcane clones. This method of rust screening is simple and easy, fast and reliable and many clones can be screened in short period of 20 days.

The innovations and progress in genome editing/new breeding technologies have revolutionized research in the field of functional genomics and crop improvement. This revolution has expanded the horizons of agricultural research, presenting fresh possibilities for creating novel plant varieties equipped with desired traits that can effectively combat the challenges posed by climate change. However, the regulation and social acceptance of genome-edited crops still remain as major barriers. Only a few countries considered the site-directed nuclease 1 (SDN1) approach-based genome-edited plants under less or no regulation. Hence, the present review aims to comprise information on the research work conducted using SDN1 in crops by various genome editing tools. It also elucidates the promising candidate genes that can be used for editing and has listed the studies on non-transgenic crops developed through SDN1 either by Agrobacterium-mediated transformation or by ribo nucleoprotein (RNP) complex. The review also hoards the existing regulatory landscape of genome editing and provides an overview of globally commercialized genome-edited crops. These compilations will enable confidence in researchers and policymakers, across the globe, to recognize the full potential of this technology and reconsider the regulatory aspects associated with genome-edited crops. Furthermore, this compilation serves as a valuable resource for researchers embarking on the development of customized non-transgenic crops through the utilization of SDN1.