International Crops Research Institute for the Semi-Arid Tropics
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Consensus genomic regions and key genes for biotic, abiotic and key nutritional traits identified using meta- QTL analysis in peanut
Get PDFPeanut (Arachis hypogaea L.), a key oilseed crop in the U.S., plays a significant role in agriculture and the economy but faces challenges from biotic and abiotic stresses, including aflatoxin contamination caused by Aspergillus flavus and A. parasiticus. Despite many large-effect QTLs identified for yield and key traits, their use in breeding is limited by unfavorable genetic interactions. To overcome this, we aimed to identify consensus genomic regions and candidate genes linked to key traits by analyzing QTL data from 30 independent studies conducted over the past 12 years, focusing on biotic, abiotic, aflatoxin, morphological, nutritional, phenological, and yield-associated traits. Using genetic map information, we constructed consensus maps and performed a meta-analysis on 891 QTLs, leading to the identification of 70 Meta-QTLs (MQTLs) with confidence intervals ranging from 0.07 to 9.63 cM and an average of 2.33 cM. This reduction in confidence intervals enhances the precision of trait mapping, making the identified MQTLs more applicable for breeding purposes. Furthermore, we identified key genes associated with aflatoxin resistance in MQTL5.2 (serine/threonine-protein kinase, BOI-related E3 ubiquitin-protein ligase), MQTL5.3, MQTL7.3, and MQTL13.1. Similarly, for yield-related traits in MQTL3.1–MQTL3.4 (mitogen-activated protein kinase, auxin response factor), MQTL11.2 (MADS-box protein, squamosa promoter-binding protein), and MQTL14.1. Genes related to oil composition within MQTL5.2 (fatty-acid desaturase FAD2, linoleate 9S-lipoxygenase), MQTL9.3, MQTL19.1 (acyl-CoA-binding protein, fatty acyl-CoA reductase FAR1), MQTL19.4, and MQTL19.5. Nutritional traits like iron and zinc content are linked to MQTL1.1 (probable methyltransferase, ferredoxin C), MQTL10.1, and MQTL12.1. These regions and genes serve as precise targets for marker-assisted breeding to enhance peanut yield, resilience, and quality
Transitioning Farming Systems for Resilience and Food Security in Malawi
Get PDFA two-day Stakeholders’ Workshop on Sustainable Transitioning of Farming Systems, held on 12-13 December 2024 at the Sunbird Capital Hotel in Lilongwe, brought together key agricultural stakeholders, researchers, policymakers, and development partners to explore solutions to enhance the resilience and sustainability of Malawi’s mixed farming systems. Organized by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) under the CGIAR Initiative on Sustainable Intensification of Mixed Farming Systems (SI-MFS), the event highlighted critical pathways for improving productivity, resilience, and food security in southern Africa's agricultural sector
Optimizing Irrigation Water and Nutrient Management Strategies for Maize Production through a Participatory Approach on the Selected Irrigation Schemes of Eastern Amhara, Ethiopia
No full textIn the semi-arid regions of Eastern Amhara, inadequate and unevenly distributed rainfall negatively affects rainfed agriculture, particularly maize production. To address this, a pre-scale-up study was conducted to evaluate improved irrigation technologies using the Farmer Research Extension Group (FREG) approach. Two irrigation practices traditional and improved were compared at Golina1 and Sedeni sites. The improved practice included the use of the Melkassa-6Q maize variety, row planting (75 cm × 30 cm), furrow irrigation (with specific dimensions and gradient), a seed rate of 25 kg ha⁻¹, and recommended fertilizers (200 kg ha⁻¹ Urea and 50 kg ha⁻¹ NPS). In contrast, the traditional practice involved local varieties, broadcast sowing (40 kg ha⁻¹), traditional flooding at 12-day intervals, and lower fertilizer rates (50 kg ha⁻¹ Urea and NPS). The improved practice significantly outperformed the traditional method, achieving higher green cob yields (38,125 ha⁻¹ at Golina1 and 34,330 ha⁻¹ at Sedeni), better water productivity (17 and 16 cobs m⁻³), and greater net benefits (222,575 ETB ha⁻¹ and 174,487 ETB ha⁻¹, respectively). This represented yield increases of 29.9% and 30.2%, and net benefit improvements of 79.63% and 86.84% over traditional practices. Additionally, improved irrigation reduced seasonal water demand by 72.4 mm and 131.6 mm, indicating substantial water savings. Overall, the study demonstrated that improved irrigation and agronomic practices significantly enhance maize yield, water use efficiency, and profitability, and were positively received by participating farmers
Markets and Value Chain Study of Major Commodities in the Dryland Regions of Maharashtra
Get PDFThe International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), in partnership with the Ground Water Surveys and Development Agency (GSDA), is conducting a collaborative study focused on improving agricultural systems and livelihoods in rural Maharashtra, India. The study emphasizes both resource efficiency and enhanced agricultural productivity. It also explores sustainable farming practices and effective market integration for smallholder farmers. The central goal is to support rural
communities by strengthening natural resource management, introducing climate-resilient farming techniques, and improving market access for key agricultural commodities. This initiative adopts a comprehensive approach to agricultural development, combining economic advancement with ecological sustainability and social empowerment. By equipping farmers with improved knowledge and practices and
strengthening linkages across the agricultural value chain—from production to market—the project seeks to improve farmers’ incomes and reduce their vulnerability to climate and market risks. A critical focus of the study is on optimizing the use of land and water resources while promoting farming systems that are both environmentally responsible and economically viable. The project also seeks to identify and promote region-specific innovations that align with agro-ecological conditions and local market opportunities. Improved market access is a core pillar of this intervention. By enhancing the efficiency of input supply chains and improving the terms under which farmers engage with output markets, the project aims to ensure that smallholder producers receive fair returns for their produce. Stronger value chain integration will also increase the availability of quality inputs and improve the competitiveness of rural farmers in regional markets
Dissecting genomic regions and candidate genes for pod borer resistance and component traits in pigeonpea minicore collection
Get PDFBackground: Pigeonpea is an important leguminous food crop primarily grown in tropical and subtropical regions of the world and is a rich source of high-quality protein. Biotic (weed, disease, and insect pests) and abiotic stresses have significantly reduced the production and productivity of pigeonpea. Helicoverpa armigera, also known as the pod borer, is a major pest in pigeonpea. A substantial investigation is needed to comprehend the genetic and genomic underpinnings of resistance to H. armigera. Genetic improvement by genomics-assisted breeding (GAB) is an effective approach for developing high-yielding H. armigera-resistant cultivars. Still, no genetic markers and genes linked to this key trait have been detected in pigeonpea. In this context, a set of 146 pigeonpea minicore accessions were evaluated for four H. armigera-resistant component traits, namely, pod borer resistance (PBR), days to 50% flowering (DF), days to maturity (DM), and grain yield (GY), for three consecutive seasons under field conditions.
Results: Phenotypic data of pod borer resistance and component traits, along with the whole-genome resequencing (WGRS) data for 4,99,980 single nucleotide polymorphisms (SNPs), were utilised to perform multi-locus genome-wide association study (GWAS) analysis. Two models [settlement of MLM under progressively exclusive relationship (SUPER) and fixed and random model circulating probability unification (FarmCPU)] detected 14 significant marker–trait associations (MTAs) for PBR and three component traits. The MTAs with significant effect were mainly identified on chromosomes CcLG02, CcLG04, CcLG05, CcLG07, and CcLG11. These MTAs were subsequently delineated with key candidate genes associated with pod borer resistance (probable carboxylesterase 15, microtubule-associated protein 5, FAR1-RELATED SEQUENCE, and omega-hydroxypalmitate O-feruloyl transferase 4), days to maturity (RING-H2 finger protein ATL7 and leucine-rich repeat receptor-like protein kinase), and grain yield (secretory carrier-associated membrane protein and glutaredoxin-C5 chloroplastic).
Conclusion: These research findings reported significant MTAs and candidate genes associated with pod borer resistance and component traits. Further lab-based pod bioassay screening identified four minicore accessions, namely, ICP 10503, ICP 655, ICP 9691, and ICP 9655 (moderately resistant genotypes), showing the least damage rating and larval weight gain %, compared to the susceptible checks. After validating the significant MTAs, the associated SNP markers can be effectively utilised in indirect selection, which offers potential gains for such quantitative traits with low heritability and can improve insect management more sustainably. The significant MTAs, candidate genes, and resistant accessions reported in this study may be utilised for the development of pod borer-resistant pigeonpea varieties
Exploring Genetic Diversity in Maturity Duration among Pigeonpea Genotypes Grown under Off-season (Rabi) Conditions
Get PDFPigeonpea (Cajanus cajan L. Millspaugh) is an important legume crop cultivated in rainfed areas due to its adaptability and soil-enriching properties. This study evaluated 250 genotypes from the PI-GAP (Pigeonpea International Genome-Wide Association Panel) for days to maturity under rabi season at ICRISAT, Patancheru. Maturity ranged from 92 to 209 days, with a mean of 141 days. Genotypes were grouped into five maturity classes, with most falling in the early category. Analysis of variance showed significant genetic effects (p < 0.001), supported by moderate GCV and PCV, high heritability (97.63%), and high genetic advance. A strong positive correlation (r = 0.78) was observed between plant height and days to maturity. Principal Component Analysis revealed that PC1 explained 88.64% of the total variance. These results highlight the potential of early and late maturing lines for target-specific pigeonpea breeding under diverse cropping systems
Industry perspective, genetics and genomics of peanut blanchability
Get PDFBlanching is the process of removing the testa or seed coat (skin) from peanuts, and a genotype's capacity to release its testa is referred to as its blanchability. The genotype, seed quality, harvest date, level of maturity, as well as the length of time and temperature of the post-harvest storage period, all influence peanut's blanchability. This characteristic holds significant value in the production of food items made from peanuts. However, major research on this economically significant trait in breeding programmes has been limited. Blanchability is reported to be a highly heritable and genetically regulated trait, thus breeding and selection should be effective. Blanchability reports to be fixed in the early generations due to its relatively simple genetic control, hence choice of parents which have good blanchability is of utmost importance in a breeding programme. Since blanching percentage possess high genetic control with very low genotype × environment (G×E) interactions, effective selection for improved blanchability can be conducted in early generations. In peanut, blanchability is a great target trait for marker-assisted selection (MAS), but possess few factors that makes it difficult breeding target. These factors, include the high cost operations to measure blanchability and the relatively large seed size in particular, prevent testing in early generations. In this review, we emphasize genetic research on this trait, its relationship to other traits, factors influencing it, methods of measurement, its industrial significance, as well as initiatives and difficulties related to its improvement
Molecular signatures that translate across omics layers and crops under high aluminium and low phosphorus stress facilitate the identification of reliable molecular targets for genotyping in lentil
Get PDFAluminium toxicity and phosphorus deficiency are co-existing characteristics of low pH stress that significantly affect the grain yield of crops. The increasing acidity of Indian soils potentially limits the cultivable area for lentil (Lens culinaris), the third most widely consumed pulse. Breeding for tolerance requires an understanding of interdependent biological responses, but the molecular characterization of integrated tolerance remains elusive. Therefore, this study aimed to integrate high aluminium and low phosphorus stress responsive associations across the genomics, transcriptomics, proteomics, and metabolomics of multiple crop species. The overlapping molecular signatures were fine mapped to 23 candidates that serve multiple regulatory roles crucial for cellular homeostasis. Most of these genes have not been adequately discussed in the context of soil acidity tolerance. Thus, a multi-omics guided regulatory framework was developed to provide new insights into tolerance mechanisms. In silico genotyping of 29 lentil genotypes across 588 genes related to transomics loci yielded seven nonsynonymous and three synonymous variants likely associated with their differential response to stress. The results suggest comprehensive genotyping of multi-omics specific targets to identify potential candidates for marker-trait association studies. In conclusion, data-driven exploratory analysis of multi-omics variants highlights potential biomarkers as targets for genetically improving complex biological traits
Drought Tolerance and Seed Coat Biochemical Resistance to Aspergilus flavus Infestation and Aflatoxin Contamination in Peanut
No full textDrought stress severity leads to Aflatoxin B1 (AFB1) contamination (AC) increases in peanuts. Identifying drought-tolerant (DT) genotypes with resistance to Aspergillus flavus (A. flavus) colonization and/or infection could contribute to developing peanuts varieties resistant to aflatoxin contamination in the semi-arid tropics. This study aims to identify DT genotypes with seed coat biochemical resistance to A. flavus infestation and aflatoxin contamination. Experiments were carried out at ICRISAT Sahelian Centre to assess peanuts genotypes under
intermittent water-stress (WS) regime imposed at pod filling stage and well-watered (WW) conditions. Parameters including pods yield and its components, A. flavus colonization
incidence, aflatoxin contamination and seed coat total polyphenol (SCTPP) were investigated. The findings revealed significant decrease of pods yield and its components, except the number of immature pods per plant (IMPN) and the aflatoxin contamination which increased up to 67% and 55% respectively. Genotypes ICG 2106, ICG 311, ICG 4684, ICG 4543, and ICG 1415 revealed drought tolerance and low aflatoxin content. Furthermore, these genotypes showed a
significant relationship between the aflatoxin resistance and the seed coat total polyphenol under the two water treatments (r2 = 0.80; r2 = 0.82), suggesting that despite WS, their seed coats were maintained intact, resulting in minimized aflatoxin contamination under an intermittent water deficit
Artificial Intelligence for Monitoring Pest and Disease in Groundnuts
No full textGroundnut (Arachis hypogaea L.), also known as peanut, is a vital legume crop grown globally for its high oil (40-50%) and protein (25-30%) content. Groundnut crop improve soil fertility through nitrogen fixation, making them ideal for crop rotation in rainfed and semi-arid regions. However, pests and diseases significantly impact groundnut production, causing 25-50% yield losses globally. Novel digital tools that use Artificial intelligence (AI) and machine learning for disease diagnosis in groundnut are available to farmers. Digital apps like ‘Plantix’ provide
valuable diagnoses of pests and diseases by processing images of plant damage symptoms sourced from a smartphone. These images provide time and geolocation data, delivering
insights into the spatial and temporal spread of pests and diseases. This study presents results from the years 2023 to 2024 on a range of groundnut pests, diseases, and nutrient deficiencies. Over 96 % of notifications were sourced from India out of 548,854 received globally through Plantix app in groundnut. Indian states of Gujarat, Rajasthan, Andhra Pradesh, Maharashtra and Uttar Pradesh accounted to 66 % of these notifications. Results show that there was significantly higher reported incidence of foot and collar rot (53,461), tobacco caterpillar (41,576) bud necrosis (39,006), Helicoverpa (31,165) and leaf miners (28,653) when compared to other pests and diseases from the farmer fields. Real-time push notifications based on the user location were useful to alert the farmers on the prevalence of pest and disease. AI-based applications are useful in monitoring groundnut pests and diseases, leading to improved
extension services