International Crops Research Institute for the Semi-Arid Tropics
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Future of Pulses and Legumes Seed Systems in India
Get PDFIndia is one of the world’s largest producers and consumers of pulses. These grains are the cornerstone of India’s food and nutrition security, and the country’s ability to meet future demand depends on how swiftly it can transform its seed systems
Construction and Analysis of Pangenome Graphs for Aspergillus flavus and Aspergillus parasiticus to Elucidate Genetic Diversity and Aflatoxin Production
No full textAspergillus flavus and Aspergillus parasiticus are opportunistic pathogens that can infect various agricultural crops, such as corn and peanuts, and produce carcinogenic secondary metabolites called aflatoxins, threatening safe food production. These species vary in their ability to produce the carcinogenic aflatoxins and other secondary metabolites. To capture the complete genomic diversity within a species, the genomes of multiple strains can be assembled by constructing a pangenome. A linear pangenome for 346 A. flavus isolates called AflaPan was published and was considered a closed pangenome, as the addition of new genomes did not significantly increase the variant pool. However, AflaPan was limited in its ability to depict
large structural variations (>50bp). Our goal is to construct a graph based pangenome to provide a more accurate understanding of individual genomes and their relationship with others by capturing larger structure variants. Initially, we assembled and constructed a pangenome
graph for the 225 A. flavus isolates we sequenced. This analysis revealed a total of 729,852 variants, including 542,577 single nucleotide polymorphisms (SNPs) and 189,267 (non-SNPs). Notably, the highest variant density was observed on chromosome 3, which contains the aflatoxin biosynthesis pathway gene cluster. Using the genotypes derived from the pangenome graph, we created a phylogenetic tree that revealed a clustering of 46 isolates from Georgia and Mississippi, which exhibited remarkably similar genotypes. These isolates showed a 2 kb insertion on chromosome 1 and an 8.7 kb insertion on chromosome 8. Our next step will be to gradually add publicly available genomes of 332 A. flavus and 51 A. parasiticus isolates to the subset pangenome to test if the pangenome is closed. This will allow us to analyze additional variations and compare them to the previously established AflaPan pangenome. Finally, we will use the pangenome graph as genotyping tool for genome-wide association studies (GWAS)
to dissect aflatoxin biosynthesis pathways and other morphological phenotypes of interest
Vegetable grafting: a scientific innovation to enhance productivity and profitability of tomato growers under climate change
Get PDFIntroduction: Vegetable grafting is a recent innovation in vegetable cultivation that has a great potential for enhancing crop productivity and profitability under climate change scenarios, besides its potential to reduce the cost of cultivation.
Methods: The present strategic research focused on assessing the performance of grafted and non-grafted tomato cultivars (PHS-448 & Sahoo) in Naturally Ventilated Polyhouse (NVPH) and open field (OF) conditions.
Results and discussion: The results revealed that grafted tomatoes expressed significantly (p80) of yield with plant height, middle leaves chlorophyll, and leaf area, irrespective of the grafted and non-grafted combinations. The present investigation concluded that cultivating grafted tomatoes helps farmers achieve maximum productivity and profitability in both NVPH and open field conditions. However, a proper policy framework is necessary to promote and scale up grafted vegetable technology to enhance the profitability of vegetable growers in climate change scenarios
Association mapping and candidate gene identification for drought tolerance in sorghum
No full textWater is essential for plant growth and drought is one of the most predominant constraints on crop yield. Sorghum is a well-known drought tolerant crop model and sorghum landraces possess novel alleles for local adaptation. In this study, we evaluated the sorghum mini core panel of 239 globally sampled landraces for shoot and root growth under drought conditions simulated by 10%/20% polyethylene glycol (PEG) in 2020 and 2024 and measured drought tolerance by Seedling Tolerance Coefficient (STC). Phenotypic analysis showed that more accessions produced more roots than longer roots when exposed to 10% PEG, but at 20% PEG, more accessions produced longer roots than more roots, reflecting the adaptability of some accessions to drought stress. However, PEG reduced shoot growth in all accessions in both years. Genomewide association study (GWAS) on 33 32 growth and 19 STC traits identified 22 loci, 19 of which were mapped to the STC traits and 17 of the 19 to STC of shoot weight. Eleven of the 22 loci are were colocated with 23 previously mapped drought related QTLs; 15 of these 23 QTLs were either mapped to green leaf area, total number of green leaves or chlorophyll content. We also found 19 candidate genes for 12 of the 22 loci. Five of those genes show either preferential or specific expression in the roots according to GeneAtlas v2. One candidate gene from a locus colocated with a previously mapped chlorophyll fluorescence QTL has been shown to increase chlorophyll fluorescence in maize in another study. Based on the response of root length and dry weight, we identified IS 30533 as the most tolerant and IS 32439 as the most sensitive accession. Results from this study lays foundation to further characterize the sorghum mini core panel for novel drought tolerance genes
Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach
Get PDFLong-term field experiments (LTEs) provide invaluable insights into temporal yield patterns of agronomic interventions. However, the number of LTEs and agronomic management options tested withing these experiments remain limited compared to the diversity of farming systems in West Africa. Well-tested crop models may be used to identify crop management strategies with high temporal yield stability. This study examines the yield stability of pearl millet and rice under various management options in West Africa, utilizing both experimental and modeling approaches. The Agricultural Production Systems Simulator (APSIM) for pearl millet and rice were calibrated and tested for locally-recommended varieties using LTE data from Niger (pearl millet) and Senegal (rice). Yield stability was evaluated with multiple metrics, including the adjusted coefficient of variation, the sustainable yield index, and the Finlay-Wilkinson regression coefficient. Both APSIM models exhibited a strong performance for grain yield, with Willmott’s indices of agreement at 0.74 for pearl millet and 0.90 for rice, and absolute root mean square errors of 0.19 and 1.20 Mg ha-1, respectively. The models effectively reproduced yield stability patterns across a variety of management options including planting date, planting density, fertilizer treatments, and residue retention. Combining fertilizer applications with crop residue retention enhanced yield stability in pearl millet, while season-specific nitrogen management strategies reduced yield variability in rice. Our study underscores the potential of well-tested crop models to complement LTEs in investigating pearl millet and rice yield stability, offering actionable insights for agronomic intensification strategies to enhance productivity and sustainability
Application of plant breeding and genomics for improved sorghum and millet grain nutritional quality
No full textMicronutrient malnutrition due to declined staple food crop nutrition has been a major global challenge in low- and middle-income countries (LMICs). Micronutrients are needed in lesser amounts but are vital for the human body’s functions. Addressing this issue is crucial for improving the health and productivity of populations worldwide. Sorghum and millets are important staples globally, providing inexpensive sources of energy and micronutrients with moderate protein content (7%–14%) and affordable for low-income populations. Enhancing the micronutrient concentration in sorghum and millets benefits impoverished communities and complements existing efforts to combat micronutrient malnutrition. A key focus of breeding programs is to improve the nutritional quality of these crops, and progress has been made in developing varieties with superior micronutrient profiles. The introduction of these improved cultivars is growing, highlighting the importance of integrating this research into mainstream breeding programs. This chapter focuses on classical breeding and genomic methods in the context of improving the concentrations and physiological availability of micronutrients, sorghum, and millet grains
Millets for a sustainable future
Get PDFOur current agricultural system faces a perfect storm—climate change, a burgeoning population, and unpredictable outbreaks such as COVID-19 which disrupt food production, particularly for vulnerable populations in developing countries. A paradigm shift in agriculture practices is needed to tackle these issues. One solution is the diversification of crop production. While ~56% of the plant-based protein stems from three major cereal crops (rice, wheat, and maize), underutilized crops such as millets, legumes, and other cereals are highly neglected by farmers and the research community. Millets are one of the most ancient and versatile orphan crops with attributes such as fast growing, high yielding, withstanding harsh environments, and rich in micronutrients such as iron and zinc, making them appealing to achieve agronomic sustainability. Here, we highlight the contribution of millet to agriculture and focus on the genetic diversity of millet, genomic resources, and next-generation omics and their applications under various stress conditions. Additionally, integrative omics technologies could identify and develop millets with desirable phenotypes having high agronomic value and mitigating climate change. We emphasize that biotechnological interventions, such as genome-wide association, genomic selection, genome editing, and artificial intelligence/machine learning, can improve and breed millets more effectively
Advancing Groundnut Breeding: High-Throughput Genotyping Panels for Precision and Efficiency
No full textGroundnut, an allotetraploid legume crop, serves as an important source of food, feed, and confectioneries worldwide. Translational genomics research has accelerated precision breeding efforts in groundnut using marker-assisted and genomic selection approaches. To support these
efforts, three cost-effective and high-throughput genotyping panels have been developed to facilitate genetic studies and breeding applications. We developed high density genotyping
array with 58K SNP markers which has been extensively used by global peanut research community. The first mid-density genotyping assay, comprises 5081 SNP markers, including
5000 highly informative SNPs with high polymorphism information content (PIC) derived from previously developed high-density ‘Axiom_Arachis’ array of 58,233 SNPs. An additional 81 SNPs associated with resilience and quality traits were incorporated for marker-assisted selection. This panel demonstrated robust performance, with PIC values ranging from 0.34 to 0.37 and explained 82.08% of genetic variance across 2573 genotypes from diverse sets of breeding populations. This panel holds promise for possible deployment in the identification of varietal seed mixture, genetic purity within gene bank germplasms and seed systems,
foreground and background selection in backcross breeding programs, genomic selection, and sparse trait mapping studies in groundnut. The second panel, a mid-density array of 2500 SNP markers with an average density of 1 SNP per Mbp, is powerful tool for global groundnut breeding programmes. These SNPs were identified through whole-genome resequencing of 263 cultivated groundnut accessions representing diverse agronomic types and geographical
regions. The panel includes 20-quality control (QC) and 72 associated markers for 8 key traits, namely leaf rust resistance, late leaf spot resistance, net blotch resistance, high oleic acid, seed weight, shelling percentage, fresh seed dormancy and blanchability. Designed through rigorous filtering processes, this panel is particularly suited for marker-assisted backcrossing, diversity analyses, and to study genetic purity for efficient germplasm management. Together, these
genotyping panels provide versatile tools for advancing groundnut breeding programs, enabling precise and efficient genetic interventions for sustainable crop improvement
Integration of Sensor-Based Technology for Modernizing Groundnut Breeding and Enhancing Genetic Gain
No full textIntegrating sensor-based technology has significantly transformed groundnut breeding by enhancing precision, improving trait selection, and accelerating genetic gain. This modernization addresses key challenges in phenotyping efficiency, environmental adaptation, and postharvest assessment, ultimately improving breeding outcomes. A key component in this transformation is the Target Population of Environments (TPE) characterization. Breeders can better define representative trial locations and map field variability by combining environmental data with UAV imagery. UAVs equipped with RGB, and multispectral sensors
efficiently capture canopy cover, plant height, and biomass across large areas, improving trial design and ensuring selections align with real-world conditions. High-throughput phenotyping platforms like LeasyScan have enhanced the evaluation of critical traits such as early vigor, canopy establishment, and water use efficiency. UAV imaging further strengthens this process by enabling non-invasive, rapid data collection, improving the accuracy of trait selection while reducing labor and evaluation timelines. This improved efficiency is crucial for accelerating genetic gain. Postharvest assessment has also advanced with the adoption of Harvestmaster to correct yields based on moisture content at harvest time. Computed Tomography (CT) imaging offers a non-destructive method for evaluating shelling percentage, kernel weight, and grade. The CT-based pipeline streamlines the assessment process, ensuring superior product quality
and enhancing operational efficiency. Nutritional profiling has improved by adopting Near-
Infrared Spectroscopy (NIRS), which enables rapid fatty acid profiling. This innovation
facilitates the identification of high-oleic acid groundnut lines, supporting breeding programs
in developing varieties that meet nutritional and market demands. The groundnut breeding
program has improved trait precision, reduced evaluation timelines, and strengthened data
quality by integrating UAV imaging, CT imaging, and sensor-based phenotyping tools. These
advancements enable better-informed breeding decisions, enhance selection intensity, and
shorten breeding cycles, driving genetic gain. The integration of these technologies has
positioned ICRISAT’s groundnut breeding program as a model of innovation, ensuring climateresilient
development. These high-quality varieties address farmer needs and contribute to
sustainable agriculture
Identification of Genomic Regions and Candidate Genes for High Resveratrol Content in Groundnut
No full textGroundnut (Arachis hypogaea L.) is a vital oilseed legume grown mainly in Asia, Africa, and America which is a good source of amino acids and nutrients as well as some useful
phytochemicals such as folic acid, tocopherol, flavonoids, and resveratrol. Resveratrol is a potent antioxidant that inhibits reactive oxygen species, offering potential medicinal benefits such as weight loss, anticancer, antimicrobial, anti-inflammatory, immunomodulatory, and
cardioprotective effects. A mini-core collection of 184 accessions has been used in this study to identify genomic regions, candidate genes and superior haplotypes for high resveratrol content in groundnut. Phenotypic evaluations conducted over two consecutive seasons revealed these genotypes ICG8760, ICG11426, ICG76, ICG9905, and ICG7243 exhibiting high concentrations of resveratrol measuring 787.86 μg/kg, 1635.14 μg/kg, 2737.00 μg/kg, 2796.20 μg/kg, and 3134.71 μg/kg, respectively. A GWAS analysis with a 58K "Axiom_Arachis" SNP array identified 12 significant marker-trait associations (MTAs) across two growing seasons.
Additionally, whole-genome re-sequencing (WGRS) revealed 21 MTAs in season 1 and 17 MTAs in season 2. Interestingly on chromosome Ah02/A02 and B02 consistent markers have
been identified with both 58K and WGRS analysis. Candidate genes identified include beta glucosidase 11, cytochrome C oxidase assembly protein COX15, Protein kinase family protein, Transcription factor EF1B, Zinc ion binding protein involved in resveratrol biosynthetic pathway. Moreover, genetic analysis reveals substantial phenotypic variation in resveratrol content, with beta-glucosidase 11-related SNPs explaining up to 91.97% of the variation, suggesting key genetic contributors to resveratrol biosynthesis. The identified MTAs will enable the identification of genomic regions, candidate genes, and desirable haplotypes for
introgressing genes responsible for high-resveratrol content into elite varieties, supporting advancements in groundnut breeding programs