Mango (Mangifera indica) processing generates a substantial amount of waste, ranging from 25 to 40

Cold stress is a major abiotic constraint to wheat production in temperate regions, particularly in the Kashmir Valley of north-western Himalayas, India, where prolonged low temperatures delay growth, reduce yield, and disrupt the rice–wheat cropping system. To address this challenge, we evaluated a panel of 340 nested synthetic hexaploid wheat introgression lines, developed by introgressing allelic diversity from Aegilops tauschii and Triticum durum into bread wheat. The panel was phenotyped for cold stress tolerance, electrolyte leakage index, and yield-related traits across three temperate environments and genotyped using the 35 K Axiom® Wheat Breeder’s Array. Genome-wide association study using FarmCPU and BLINK models identified 152 stable marker–trait associations (MTAs), with − log₁₀(P) values ranging from 3.00–14.64. Several stable MTAs surpassed the Bonferroni-adjusted significance threshold and were designated as high-confidence loci. A number of stable MTAs co-localized with previously reported genomic regions, whereas others represent potentially novel loci. Multiple pleiotropic loci were detected, indicating potential for simultaneous improvement of multiple traits. Haplotype analysis identified 32 major LD blocks significantly associated with target traits, with favorable haplotypes conferring enhanced stress tolerance and productivity. Several putative candidate genes were identified within chromosome-specific LD intervals of high-confidence MTAs. Literature mining, in silico expression profiling and network analyses further supported their functional relevance in cold stress adaptation and yield regulation. The identified genomic regions, haplotypes, and candidate genes provide valuable resources for marker-assisted and haplotype-based breeding to develop cold-tolerant, high-yielding wheat cultivars suited to temperate regions, thereby supporting the sustainability of rice–wheat cropping systems.

Wheat production is increasingly threatened by biotic and abiotic stresses, with stripe rust, caused by Puccinia striiformis f. sp. tritici being among the most devastating diseases. To dissect stripe rust resistance mechanisms, 329 diverse wheat genotypes were evaluated across six distinct environments in India (three locations over two years). The panel exhibited wide variation for stripe rust resistance and was genotyped using a 35K SNP-array. Genome-wide association study (GWAS) revealed 49 significant marker–trait associations (MTAs), explaining 1.58

Synthetic hexaploid wheat (SHW) has proven to be a valuable genetic resource. When conventionally bred with modern wheat varieties, it presents new potential for improved yield under abiotic stress conditions. In the northwestern plain zones (NWPZ), the reproductive phase of wheat is particularly vulnerable to rising temperatures, known as terminal heat stress. This often causes leaf damage, which then affects the source of individual stems, and studying source-sink dynamics by imposing source-sink manipulations at the individual culm level seems important. Therefore, the present study was conducted on 15 wheat introgression lines (doubled haploids) obtained from two synthetic wheats and two hexaploid wheats (SHW14102 ×BWL4444, SHW14102 ×BWL3531, and SHW3761 × BWL4444). These lines were phenotyped for five yield-related spike traits under late sown condition for two consecutive years 2020–21 and 2021–22. The source-sink ratios were modified by removing alternate spikelet rows at the 50

In the rice-wheat rotation system (RWS) of the Indo-Gangetic Plains (IGP) of India, the harvest date of kharif (wet-season) rice significantly affects the planting date of rabi (dry-season) wheat. Farmers in northwest and central India are exploring the possibility of planting wheat much earlier (October) than their usual sowing (November) in RWS to leverage residual soil moisture after rice harvest and to escape terminal heat stress. However, the current wheat cultivars are unsuitable for early planting due to warm temperatures experienced during October and early November. In addition to this, the challenge is further intensified by rapid population growth, diminishing arable land and unpredictable climatic conditions that widen the food demand-supply gap. Under such urgent circumstances, conventional breeding approaches are inadequate for delivering climate-resilient cultivars at the pace demanded by farmers. Therefore, the doubled haploid (DH) technique provides a strategic advantage by enabling the rapid fixation of desirable traits and accelerating the identification of heat-tolerant early-sown wheat genotypes. Accordingly, an experiment was conducted to screen the doubled haploids derived from the crosses between two synthetic wheats (SHW14102 and SHW3761) and two elite bread wheat lines (BWL4444 and BWL3531), i.e., SHW14102 × BWL4444, SHW14102 × BWL3531, and SHW3761 × BWL4444, under warm temperatures in the northwestern plain zones (NWPZ). The heat tolerance of 390 DHs was assessed under two environmental conditions (one location and 2 years). They were sown in the same location on two dates: October (juvenile heat stress) and November (favorable) during the winter seasons of 2020–21 and 2021–22. Genetic variability analysis, principal component analysis (PCA) and hierarchical clustering of phenotypic data were effective in identifying promising lines for juvenile heat stress. From the genetic variability analysis, 100 DHs out of 390 populations were selected for PCA and cluster analysis. They were screened for yield traits and then differentiated into three clusters. Cluster 1 had the highest value for grain yield, biomass, and thousand-grain weight, indicating its potential as a valuable germplasm for future breeding programs.

Wheat productivity and sustainability are constrained by low nitrogen use efficiency (NUE), while the genetic basis of NUE-related root traits in its wild progenitor Aegilops tauschii remains poorly explored. We hypothesized that natural allelic variation in Ae. tauschii can reveal loci controlling root architecture and nitrogen acquisition for wheat improvement. A panel of 123 sequence-characterized accessions was evaluated under field conditions at two nitrogen levels (recommended N120 and reduced N60) for root traits, flowering time, leaf morphology, kernel weight, and tissue nitrogen content. Genome-wide association analysis using 3.6 million SNPs identified 69 and 51 significant marker–trait associations under N60 and N120, respectively, including stable loci on chromosome 6D and novel regions on chromosomes 1D and 2D associated with root length, root volume, and shoot and grain nitrogen content. Quantitative RT-PCR provided preliminary functional evidence, revealing nitrogen-responsive expression of three candidate genes in roots (AET6Gv20610400, AET3Gv20907900, AET5Gv20603200) and two in shoots (AET3Gv20717100, AET6Gv20605200) during nitrogen starvation and recovery. These findings identify novel genomic regions and candidate genes for improving NUE through marker-assisted wheat breeding.

Micronutrient malnutrition, particularly deficiencies of iron, zinc, and protein in the human diet, remains a major global health challenge. Biofortification of staple crops such as wheat offers a cost-effective and sustainable approach to address the hidden hunger issue and improve nutritional quality by increasing the content of essential micronutrients. In this study, a panel of 283 diverse bread wheat genotypes was evaluated across eight environments (E1–E8) at three locations over three years to identify stable genomic regions associated with grain iron content (GFeC), grain zinc content (GZnC) and grain protein content (GPC). A multi-locus genome-wide association study (GWAS) was conducted to identify significant marker trait associations (MTAs) that were consistently detected across multiple environments, indicating their reliability for breeding. Significant phenotypic variation was observed across environments for GFeC (24.5–57.0 ppm), GZnC (18.0-89.9 ppm) and GPC (7.38–21.64

Over the past two decades, genomic prediction (GP), also known as genomic selection (GS), has been widely adopted in plant and animal breeding programs worldwide. GP is a promising approach that utilizes genomic markers to estimate genomic-estimated breeding values, facilitating the selection of superior individuals. In this study, we assessed the performance of five GP models-genomic best linear unbiased prediction (GBLUP), reproducing kernel Hilbert space regression (RKHS), and Bayesian methods (BayesA, BayesB, and BayesC)-for predicting seedling resistance and adult plant resistance (APR) to leaf/brown rust (LR), stem/black rust (SR), and yellow/stripe rust (YR) in wheat using a panel of 347 diverse germplasm accessions. At the seedling stage, the BayesB model showed consistently high performance, particularly for LR and SR datasets, whereas all models showed relatively poor accuracy for YR. For APR, both GBLUP and BayesB performed comparably well, especially for LR, whereas all models exhibited lower predictive ability for SR and YR. Furthermore, GWAS-guided GP analysis revealed that intermediate SNP densities (100 to 500 markers) significantly outperformed the full marker set across all rust types and stages, with prediction accuracy in some cases doubling or more. These findings suggest that the use of a full marker set may introduce noise and reduce efficiency, whereas selection of top-ranked GWAS-based markers enhances predictive power. Additionally, favorable allele analysis identified two promising lines-CRP-165/42 and HGP1-435-with broad-spectrum resistance at both seedling and adult stages, making them a valuable source for future rust-resistance breeding programs.

Wheat, a vital staple crop, suffers substantial post-harvest losses due to storage pests, particularly Rhyzopertha dominica. In this study, 73 backcross introgression lines (BILs), developed from the cross between Syn14135/BWL4444, were evaluated for resistance to R. dominica and utilized to map quantitative trait loci (QTLs) associated with this resistance. Three parameters viz. adult emergence, number of damaged grains, and grain weight loss were recorded at 30, 60, and 90 days after infestation, with all showing a consistent linear increase over time. Ten BILs exhibited high levels of resistance, with PN410, PN372, and PN266 showing strong and stable performance across all recorded parameters. All BILs, including the parents, were genotyped using a 35K Axiom SNP array to identify markers associated with resistance. Inclusive composite interval mapping (ICIM) detected four QTLs on chromosomes 4D, 7A, and 7D. Notably, QDg.pau-4D/QGwl.pau-4D on chromosome 4D showed a pleiotropic effect, contributing to both number of damaged grains and grain weight loss. Furthermore, QAe.pau-7A and QGwl.pau-7D were identified as high-confidence loci associated with resistance. Candidate genes underlying these QTLs included cytochrome P450s (CYPs), serine/threonine-protein kinases, NAC SECONDARY WALL THICKENING PROMOTING 3, and glutathione S-transferases, many of which are known to play roles in disease, pest and insect resistance in wheat and other crops. This study elucidates the genetic mechanisms underlying storage pest resistance in BILs and identifies key genomic regions and resistant lines that serve as valuable resources for breeding wheat varieties with improved post-harvest protection and reduced storage losses.

Water deficit is a major constraint to wheat productivity, necessitating the identification of genotypes with enhanced physiological resilience and stable yield under stress. The present study aimed to identify potential sources for water deficit tolerance and elucidate the physiological and biochemical mechanisms underlying water deficit tolerance in four introgression lines (ILs: 5U-24, 5U-26, 5U-27 and 5U-31). These ILs were developed from a cross involving a disomic substitution line DS5Ut(5 A) and wheat cultivars Pavon ph1b and WL711. Wheat variety PBW725 was used as check along with ILs, Pavon ph1b, WL711 and DS5Ut(5 A). The experiment was conducted under irrigated and rain-fed (water deficit) conditions and the responses were evaluated at anthesis and 15 days after anthesis. Rain-fed conditions caused a significant (p ≤ 0.05) reduction in grain yield across all genotypes while IL 5U-26 maintained its yield. Thousand-grain weight declined significantly in PBW725, WL711 and IL 5U-31, whereas it increased significantly in ILs 5U-24, 5U-26 and 5U-27. No significant effect was observed in Pavon ph1b and DS5Ut(5 A). All genotypes exhibited osmotic adjustment under water deficit through accumulation of proline, glycine betaine and total soluble sugars. Water deficit stress led to increased hydrogen peroxide and malondialdehyde contents, with comparatively lower accumulation in tolerant genotypes. Stress conditions also reduced relative water content, canopy temperature depression, chlorophyll content and quantum efficiency of PSII, while increasing non-photochemical quenching. These effects were more pronounced in IL 5U-31 and PBW725 at both growth stages. Stem reserve mobilization increased significantly under water deficit, with the highest enhancement observed in IL 5U-26. Principal component analysis indicated that enhanced stem reserve mobilization, higher soluble sugar content, better maintenance of relative water content, chlorophyll content and lower oxidative damage were key contributors to water deficit tolerance. Among the evaluated genotypes, IL 5U-26 exhibited the highest level of tolerance and can act as a potential donor for developing high-yielding, drought-resilient wheat cultivars.

This study investigates the enzymatic characteristics and interactions of trypsin and α-amylase from Rhyzopertha dominica and respective inhibitors from infested wheat lines during storage. We hypothesize that chromosomal segmental substitution lines (CSSLs) of wheat with higher initial concentrations of α-amylase and trypsin inhibitors maintain greater resistance against Rhyzopertha dominica over the storage periods; a defense that can be further improved by the application of exogenous inhibitors. A significant decline in trypsin and α-amylase inhibitor content was observed across wheat lines during prolonged storage, with PN 399 showing the least reduction, indicating their resilience behaviour. Trypsin activity peaked at a pH of 10.4 and showed maximum substrate affinity at 2 mM BApNA. Effective inhibitors of trypsin activity included Aprotinin and Leupeptin, reducing activity by up to 50

A field experiment was conducted over two consecutive rabi seasons (2017-18 and2018-19) at three locations in Punjab (Ludhiana, Faridkot, and Ballowal Saukhri). The experiment followed a Factorial Split Plot Design with three dates of sowing (D1 – 25th October, D2 – 15th November, D3 – 5th December) and three wheat cultivars (V1- WH1105, V2 - UNNAT PBW 550, V3 - PBW 590) in the main plots, and two irrigationtreatments (I1: Recommended, I2: Recommended ± weather forecast based) in the subplots. Across both seasons, the crop sown on 15th November consistently exhibited the highest tiller count and dry matter at harvest. Grain yield was significantly higher for D2 compared to D3, and was comparable to D1 across all three locations. Among the cultivars, UNNAT PBW550 yielded significantly more than PBW 590. Among the locations Ballowal Saukhri had lowest grain yield. Analysis indicated non-significant differences in yield under different irrigation schedules across the three sowing dates

Wheat is a major global staple food affected by three diseases: leaf rust (LR), stem rust (SR), and stripe rust (YR), all of which can cause substantial yield losses. Identifying genotypes with broad-spectrum resistance to diverse pathotypes of all three rusts remains a major challenge. In this study, we examined the genomic basis of resistance to three rust diseases LR, SR, and YR in a diverse panel of 346 bread wheat (Triticum aestivum) accessions. The seedling stage phenotypic evaluation was performed for 2 years using prevalent and virulent pathotypes. Based on best linear unbiased estimators, LR and YR displayed right-skewed distributions, whereas SR showed a bimodal pattern. Genotyping with the 35K Axiom Wheat Breeders Array, followed by quality control, yielded 11,910 high-quality single nucleotide polymorphisms (SNPs). Population structure analysis revealed five subpopulations and a whole genome linkage disequilibrium decay of 3.49 Mb. Multi-trait genome-wide association studies identified 11 significant SNPs distributed on chromosomes 3A, 3B, 3D, and 7B, which were associated with 47 disease resistance genes, 22 of which were highly expressed in at least one condition. The haplotype analysis revealed eight different haplotypes, where H006 and H007 were superior in terms of multiple rust resistance (MRR). Note that 17 elite accessions, including IC427824 and HGP1-359, were selected using multi-trait genotype ideotype distance index analysis. Three key Kompetitive allele specific polymerase chain reaction (KASP) markers, AX94381808, AX94874313, and AX94807942 were developed and validated. This integrated genomic approach advances the identification process and can accelerate the breeding of wheat cultivars with durable MRR.

Heat stress is a critical factor affecting global wheat production and productivity. In this study, out of 500 studied germplasm lines, a diverse panel of 126 wheat genotypes grown under twelve distinct environmental conditions was analyzed. Using 35 K single-nucleotide polymorphism (SNP) genotyping assays and trait data on five biochemical parameters, including grain protein content (GPC), grain amylose content (GAC), grain total soluble sugars (TSS), grain iron (Fe), and zinc (Zn) content, six multi-locus GWAS (ML-GWAS) models were employed for association analysis. This revealed 67 stable quantitative trait nucleotides (QTNs) linked to grain quality parameters, explaining phenotypic variations ranging from 3 to 44.5% under heat stress conditions. By considering the results in consensus to at least three GWAS models and three locations, the final QTNs were reduced to 16, with 12 being novel findings. Notably, two novel markers, AX-94461119 (chromosome 2A) and AX-95220192 (chromosome 7D), associated with grain Fe and Zn, respectively, were validated through Kompetitive Allele Specific Polymerase Chain Reaction (KASP) approach. Candidate genes, including the P-loop-containing nucleoside triphosphate hydrolases (NTPases), Bowman-Birk type proteinase inhibitors (BBI), and the NPSN13 protein, were identified within associated genomic regions. These genes could serve as potential targets for enhancing quality traits and heat tolerance in future wheat improvement programs.

Leaf rust (LR) is one the most widely distributed and serious pathogen hampering the wheat production globally. To combat the continuous evolution of pathogens and breakdown of resistance, matching resistance genes must be discovered at the same pace from the diverse sources. In this study, we identified the US genome species Aegilops kotschyi acc pau 396, which is resistant to the Indian Puccinia triticina pathotypes 109R31-1 (77 − 5), 21R55 (104-2), and 121R60-1 (77 − 9). An LR resistance introgression line, ILkots was developed from this accession of Aegilops kotschyi in the background of Triticum aestivum cultivar PBW343. To examine the genetics of transferred resistance, a mapping population of 222 F3:4 plants was generated by crossing ILkots with the LR-susceptible cultivar WL711NN. Field experiments were conducted using a randomized complete block design (RCBD). Genetic analysis revealed that resistance was conferred by a single, dominant gene temporarily designated as Lrkots. Bulked segregant analysis (BSA) in combination with AFFYMETRIX 35 K Wheat Breeders’ AXIOM array mapped Lrkots on chromosome 3DL. A partial genetic linkage map of the genomic region carrying Lrkots included five Kompetitive allele-specific PCR (KASP) markers and two simple sequence repeat (SSR) markers spanning 8.2 cM. Lrkots was flanked by the KASP marker AX-94,443,154 (0.32 cM) on the proximal end and the SSR marker Xbarc71 (7.9 cM) on the distal end, defining a 3 Mb region in the RefSeq v1.0 genome assembly. This interval contains eight candidate genes encoding protein domains involved in disease resistance responses.

Wheat (Triticum aestivum L.), a globally significant cereal crop and staple food, faces major production challenges due to abiotic stresses such as heat stress (HS), which pose a threat to global food security. To address this, a diverse panel of 126 wheat genotypes, primarily landraces, was evaluated across twelve environments in India, comprising of three locations, two years and two growing conditions. The study aimed to identify genetic markers associated with key agronomic traits in bread wheat, including germination percentage (GERM_PCT), ground cover (GC), days to booting (DTB), days to heading (DTHD), days to flowering (DTFL), days to maturity (DTMT), plant height (PH), grain yield (GYLD), thousand grain weight (TGW), and the normalized difference vegetation index (NDVI) under both timely and late-sown conditions using 35 K SNP genotyping assays. Multi-locus GWAS (ML-GWAS) was employed to detect significant marker-trait associations, and the identified markers were further validated using Kompetitive Allele Specific PCR (KASP). Six ML-GWAS models were employed for this purpose, leading to the identification of 42 highly significant and consistent quantitative trait nucleotides (QTNs) under both timely and late sown conditions, controlled by 20 SNPs, explaining 3–58

The Karnal bunt (KB) caused by Tilletia indica is an internationally quarantine-significant disease of wheat. The disease can be effectively managed by harnessing genetic resistance in wild and related wheat species. Thus, in the present study a set of 206 introgression lines derived from wheat progenitors (Triticum monococcum, Aegilops tauschii, T. dicoccoides) and non-progenitors (T. araraticum, Ae. triuncialis) was screened for KB resistance during cropping seasons 2021–2022 and 2022–2023. Out of the 142 introgression lines derived from progenitor wheat species, 11 lines derived from T. monococcum were found to be completely resistant while two (T. dicoccoides 360/Ae. Tauschii 9783//PBW 730/3/PBW 671-1, PDW 233/Ae. tauschii 14119//PBW 729/3/PBW 730-3) derived from T. dicoccoides and Ae. tauschii displayed a high level of KB resistance. Furthermore, out of 64 introgression lines derived from non-progenitors, thirteen lines derived from Ae. triuncialis exhibited completely resistant reactions. Additionally, two lines derived from T. araraticum exhibited the highest resistance. The majority of the lines derived from T. monococcum and Ae. triuncialis exhibited resistance against T. indica. Thus, these identified introgressions derived from both wheat progenitor and non-progenitor are promising KB resistance donors and can be utilized further for developing disease resistant cultivars.

Stripe rust caused by Puccinia striiformis f.sp. tritici (Pst) is one of the most devastating diseases of wheat. The ability to produce new pathotypes, breakdown of rust resistance genes and spread over longer distances makes the management of stripe rust a very difficult task. Among all the control measures, use of resistant varieties is very economical and environmentally safe strategy. So, in the present study, efforts were made to mine stripe rust resistance genes from set of 376 European winter wheat lines by seedling reaction test (SRT) against four most prevalent pathotypes of Puccinia striiformis (238S119, 110S119, 110S84 and 46S119) and field evaluation at two different locations Ludhiana (2021–2022, 2022–2023) and Gurdaspur (2022–2023). Seedling response based on Infection type (IT) against each pathotype was categorized into resistant (IT < 3) and susceptible (IT > 3). Out of 374 (germinated) germplasm lines; 258 showed resistance response and 4 showed susceptible response against all the test pathotypes of Pst, 112 lines showed variable responses in terms of virulence to only one, two and three pathotypes combinations. Based on AUDPC (area under disease progress curve) and FRS (final rust severity), 9 showed highly resistant response with AUDPC and FRS = 0 at both the locations against stripe rust. Gene postulation was done by gene-matching technique. Four Yr genes (Yr5, Yr10, Yr15, Yr24/Yr26) were found effective against the test pathotypes. So, closely linked SSR and KASP markers for these genes were used to confirm the presence of these genes. Based on race specific phenotyping IT (< 2), field evaluation (AUDPC < 100) and marker data the presence of Yr5, Yr10, Yr15, Yr24/Yr26 were detected singly or in combination.