International Crops Research Institute for the Semi-Arid Tropics
ICRISAT Open Access RepositoryNot a member yet
12134 research outputs found
Sort by
Building Climate Resilience in Agrifood Systems Through AI- Powered Agromet Advisory Services
Get PDFSouth Asia’s agrifood systems are highly vulnerable to climate variability, with frequent droughts, floods, and heatwaves threatening rainfed farming and rural livelihoods. Traditional district-level advisories lack the precision and timeliness required for effective risk management at the farm scale. To address this, ICRISAT and its partners have developed AI-powered platforms—the Intelligent Systems Advisory Tool (iSAT) and Next-Gen Climate Services Dashboard (NGCS)—which integrate historical climate data, real-time forecasts, and local agronomic information to generate automated, context-specific advisories. These systems employ machine learning and decision-tree logic to translate complex weather data into actionable insights, enabling timely recommendations on sowing, irrigation, and crop protection. Field pilots across India have demonstrated significant improvements in yield and decision-making, with 72% of farmers rating the advisories as highly useful. The platforms are now being scaled under India’s Monsoon Mission-III and adapted for Africa through CGIAR’s Climate Action and Digital Transformation Accelerator initiatives, positioning AI-driven advisory systems as global public goods for climate-resilient agriculture
Strengthening livestock systems through Sorghum-based fodder value chain innovations in southern India
No full textCONTEXT
India, a prominent global milk producer, faces suboptimal animal milk productivity primarily due to feed and fodder deficits and malnutrition of milch animals. In Tamil Nadu, landrace, dual-purpose and multi-cut sorghum fodder cultivars play a pivotal role in providing much-needed fodder under rainfed and limited irrigation conditions.
OBJECTIVE
This research aims to comprehensively understand and identify strategies to address the fodder shortage issue by optimizing the sorghum fodder value chain.
METHODS
We took interviews with various stakeholders in the fodder industry to gather required data. The study encompassed all types of sorghum fodder, including landraces, dual-purpose, and multi-cut varieties, being supplied through six distinct value chains. We collected data from 407 household farmers and 30 traders and processors through structured and semi structured interviews and focus group discussion.
RESULTS AND CONCLUSIONS
The study identified Channel I, involving direct transactions between producers and end-users (primarily dairy farmers and commercial dairy farms) emerged as the most efficient marketing channel for green fodder, offering competitive prices of INR⁎ 1500 per ton for landrace, INR 1675 per ton for dual-purpose, and INR 1950 per ton for multicut fodder varieties. Among these fodder types, multicut fodder stands out as the most efficient option, ensuring farmers a consistent supply of green fodder while simultaneously reducing cost of production. Furthermore, the silage produced from dual-purpose and multicut fodder commands a superior market value, amounting INR 6500 per ton which is distributed via Channel I, thereby rendering the fodder production highly lucrative. We also compare the different variants of fodder sorghum with its close competitor maize and found out multicut fodder sorghum is the best option for the farmers.
SIGNIFICANCE
This research underscores the potential of promoting multicut sorghum fodder varieties as a pivotal solution to mitigate the fodder deficit issue. This strategic shift can contribute significantly to increased milk production and farm revenue, ultimately strengthening livestock systems in Southern India
Developing Striga resistance in sorghum by modulating host cues through CRISPR/Cas9 gene editing
No full textSorghum (Sorghum bicolor L.) is a primary food staple grain for millions in Sub-Saharan Africa (SSA). It is mainly constrained by the parasitic weed Striga, which causes up to 100% yield losses and affects over 60% of cultivable farmlands and livelihoods. In this study, CRISPR/Cas9 technology is utilized to induce mutations in core strigolactone (SL) biosynthetic genes, i.e., CCD7, CCD8, MAX1, in addition to an uncharacterized gene (DUF) in the fine-mapped 400 kb lgs1 region in sorghum to develop durable Striga resistance. Two sorghum cultivars were delivered with the expression cassettes through immature embryo-based Agrobacterium-mediated transformation. Our study demonstrated transformation and gene editing efficiencies of ~ 70 and up to 17.5% (calculated based on the numuber of established plants), respectively, in two sorghum genotypes. Subsequent analysis of homozygous E0 lines in the E1 generation confirmed stable integration of mutations for all targeted genes. Loss-of-function mutations in the CCD7, CCD8, MAX1, and DUF genes led to a significant downregulation of the expression of associated genes in the SL biosynthetic pathway. The phenotypic analysis of edited lines revealed changes in phenotypic patterns compared to wild-type plants. Analysis of root exudates showed significant reductions in SL production in edited lines compared to wild-type plants. Striga infection experiments demonstrated delayed or reduced emergence rates of Striga in edited lines with lower SL production, highlighting the potential for genetically altering SL production to control Striga infestations. This study provides insights into the functional roles of CCD7, CCD8, MAX1, and DUF genes in sorghum towards reduced and/or altered SL production and improved resistance to Striga infestations
Breeding Climate-Resilient Groundnut in the Climate Change Era: Current Breeding Strategies and Prospects
No full textAs climate change presents unprecedented challenges to global agriculture, ensuring the resilience of staple crops has become imperative for food security. Groundnut cultivation faces increasing vulnerability to shifting climatic patterns, necessitating innovative approaches for sustainable crop improvement. This chapter explains the current state of breeding strategies for improving climate resilience in groundnut (Arachis hypogaea L.), a vital oilseed and protein source. It encompasses traditional breeding methods, advanced molecular techniques, and novel cutting-edge genomic tools. Through critical analysis, we discuss the efficacy of these strategies in fortifying groundnut plants against challenges such as drought, temperature extremes, and emerging diseases. The genetic diversity within groundnut germplasm and wild relatives as sources of adaptive traits are discussed, emphasizing the importance of broadening the genetic base. The incorporation of QTLs and markers for selection to expedite the breeding process has been explored, shedding light on their role in creating groundnut varieties with increased stress tolerance. To overcome extended generation times, we explore the transformative potential of speed breeding, which enables multiple generations within a year. Genomic engineering technology provides a solution for developing stress resilience. Transgenic groundnut lines show resistance to various stresses. These strategies play an important role in sustainable groundnut improvement during adverse environmental challenges. This chapter highlights the potential of these advanced technologies for precise trait manipulation and acceleration of the breeding cycle in groundnut
Male migration and the transformation of gendered agriculture work: a comparative exploration of heterogeneity across selected Indian states
Get PDFMale migration among agriculture-dependent households has emerged as an important livelihood strategy for coping with poverty, food insecurity, climate change, and several other risks and shocks in the Global South. Emerging research on the impacts of male migration on women’s agency, especially in agricultural production and decision-making, paints a one-size-fits-all picture. This paper, through a comparative, qualitative analysis of the implications of male out-migration on gender roles and responsibilities in agriculture across four different agroecologies in India – forested, mountainous, semi-arid, and coastal – highlights the heterogeneity in women’s experiences of male migration in the Indian context. While the nature of migration and the amount and regularity of remittances shape the increase or decline in women’s work and responsibilities, factors like age, caste, class, life stage, and context also play a significant role. We note that current scholarship has given too much importance to the narrative on remittance-driven livelihoods at the cost of multiple factors that shape women’s roles, experiences, and strategic choices in migrant-sending communities. What appears critical for transformative change is state policy that facilitates and enables collective action, central to overcoming the patriarchal constraints women encounter, especially as they shift from labouring to managerial roles in farming
Assessing Soil Degradation in Agricultural Landscapes of Semi-Arid Tropics Using Proximal and Remote Sensing-Based Diffuse Reflectance Spectroscopy
Get PDFMonitoring soil degradation using the soil degradation index (SDI) is a complex process. Typically, multiple soil parameters are measured under laboratory conditions to create such a composite parameter. Because conventional soil testing methods are tedious and time-consuming, frequent monitoring of soil degradation through SDI continues to be a challenging task. With diffuse reflectance spectroscopy (DRS) emerging as a rapid soil testing method, the major objective of this study is to examine the DRS approach for estimating SDIs in a degradation-prone dryland landscape of Maharashtra, India. Accordingly, surface soil samples were collected from 141 locations and 20 different soil parameters were measured in these samples. Six key parameters were identified to formulate the SDI following a minimum dataset (MDS) approach: soil organic carbon content (SOC), soil erodibility index (eMCR), available S, available Mn, the ratio between exchangeable Ca to Mg and silt content. Spectral reflectance data collected under laboratory conditions and those extracted from multispectral imaging data from Sentinel-2 L2A over the visible to infrared (VNIR) region were used to estimate SDIs and its six indicators by calibrating two popular chemometric models: support vector regression (SVR) and feature selection-based partial-least-squares regression (PLSRFS). Results showed that the SDI values could be estimated from the laboratory-measured DRS data with the coefficient of determination (R2) value of 0.81 and root-mean-squared error (RMSE) value of 0.03. Similarly, chemometric models also performed well for the MSI data (R2 = 0.52; RMSE = 0.04). Although the laboratory-based DRS approach provided greater estimation accuracy, low RMSE values associated with the MSI data showed that SDI may be effectively mapped for the entire study area at high spatial resolution (~10 m for Sentinel-2 L2A data). Correlation analyses between mapped SDI and crop yield further showed yield declines with increasing soil degradation for different rainfed crops, while no such trends were observed for the irrigated crops, suggesting that irrigation management in dryland areas may circumvent land degradation challenges
QTL mapping and candidate gene identification for fodder quality traits in Pearl millet
Get PDFBackground
Pearl millet is an excellent forage crop with significant potential for forage production. Its fodder is rich in protein, calcium, phosphorus and other essential minerals while being low in undesirable components such as hydrocyanic acid and oxalic acid. Globally, the shortage of high-quality fodder poses challenges for maintaining animal health and productivity, ultimately impacting dairy farmers. Therefore, improving pearl millet for fodder traits should be a priority to meet the global demand for nutritious livestock feed.
Results
Significant variability was observed for all forage quality related traits at both locations. A linkage map was constructed using 755 single-nucleotide polymorphisms (SNPs) markers, spanning a total length of 3080.44 cM. A total 8, 6 and 10 QTLs were identified for Ludhiana, Abohar and across the locations, respectively, for fodder quality. A common genomic interval with flanking markers S6_234379851- S6_64109715 was associated with IVOMD, CP and ME at all locations, with 10–34% phenotypic variance. Further, expression analysis identified BHLH 148, Resistance to phytophthora, Laccase 15, cytochrome P450, PLIM2c, GRF11, NEDD AXR1, NAC 92 and TF 089 as differentially expressed candidate genes in the leaf tissues of parental lines. A phylogenetic tree constructed using these genes revealed two clades identified with six paralogous events. Additionally, a phylogenetic tree of eight cereal species showed that the majority of shared similarity with the Pgl genes, suggestinga recent speciation event among them. Common genes, including cytochrome P450, PLIM2c, NEDD AXR1 and NAC domains were identified between QTL regions and expression analysis.
Conclusion
The differentially expressed genes incorporating the regulatory elements governing the lignin pathway have direct or indirect effects on fodder digestibility and quality. Exploiting these factors can contribute to the direct improvement of fodder quality. The identified QTLs and candidate genes from this study could facilitate the development of gene based markers for fodder improvement
Recent advances in biotechnology and bioengineering for efficient microalgal biofuel production
Get PDFMicroalgal biofuels have emerged as a promising avenue for meeting the growing demands for clean and efficient energy. However, the integration of microalgae into the biofuel industry is still in the early stages, primarily due to low productivity and high production costs. To address these challenges, researchers are actively exploring innovative methods to enhance biomass, concurrently increasing lipid and carbohydrate content. This review paper discusses the unique attributes of microalgae that make them attractive candidates for biofuel production. Advancements in cultivation techniques, such as photobioreactor design, co-cultivation strategies (microalgae-microalgae, microalgae-bacteria, and microalgae-fungi), and the optimization of nutrient conditions (carbon, nitrogen, and phosphorus) as well as environmental factors (salinity, light, and temperature) were explored to enhance biomass and lipid productivity. Furthermore, genetic engineering tools (genetic elements, gene interference, genome editing, and genome reconstruction) and omics technologies (genomics, transcriptomics, and proteomics) were discussed to gain a deeper understanding of microalgal lipid synthesis metabolism. The application of these techniques in microalgae facilitates enhanced lipid productivity, improved stress tolerance, optimized carbon sequestration and utilization, and reduced harvesting and processing costs. The study also delves into the decision-making process related to software selection, with the overarching goal of improving performance, profitability, and sustainability while mitigating risks, operational costs, and environmental impacts. Additionally, this review highlights future perspectives on large-scale microalgal biofuel production and its industry
Marker-Assisted Selection (MAS), Quality Control and METs in Groundnut Breeding Pipeline at ICRISAT to Enhance Genetic Gain
No full textGroundnut, an oil and food legume crop is valued for its nutritional content, including protein and essential fatty acids. The EiB (Excellence in Breeding) low-density genotyping service is a shared KASPTM genotyping platform serving all CGIAR centers and their partner programs. The EiB low-density genotyping service is based on Kompetitive Allele Specific PCR (KASP) markers. Groundnut has 82 QC SNPs based on PIC (polymorphism information content) and 49 trait-specific SNPs on the EiB portal. ICRISAT groundnut breeding pipeline employs a 10-SNP panel selected based on parental polymorphism for confirming the hybridity of the F1s. During 2023-24, the program has confirmed the hybridity of 564 F1 plants. A 10-SNP panel is employed for MAS that include, two SNP markers, snpAH00116 and snpAH0002 to select
FAD2A mutant alleles on A- and B- genomes, respectively. For the major QTL governing late leaf spot (LLS) resistance, snpAH0004, snpAH0005, snpAH0010, and snpAH0014, and for
the major QTL governing rust resistance, snpAH0017, snpAH00135, snpAH00137 and snpAH0026 are employed in the breeding pipeline. A mid-density genotyping panel containing
2500 SNP markers distributed across 20 groundnut chromosomes is used to genotype all the lines (~200 per annum) advanced to Stage I multi-environment testing (MET). The SNPs for
the mid-density panel have been identified using the whole genome re-sequencing of 263 cultivated accessions of groundnut reference. The mid-density genotype data is employed for line purity, and to determine gBLUPs that is used for parent selection for recycling, and Genomic Selection (GS). Cultivars tailored for specific adaptation to a target agro-climatic zone maximizes realized genetic potential. This requires identifying homogenous production
units (HPUs) and testing within a HPU to minimize the G X E and select the lines best suited for a HPU. ICRISAT has adopted a multi-environment testing (MET) strategy guided by the characterization of environment. A set of 27 advanced breeding lines were evaluated across two HPUs during Rainy 2022, using an alpha lattice design with two replications. Best linear unbiased predictors (BLUP) based analysis revealed, ICGVs 211022, 211021 and 211008 were specifically adapted to HPU 2 comprising of Gujarat state, while ICGVs 211019 and 211020 thrived in HPU 6 comprising southern states of India. Interestingly, ICGVs 211029 and 211016
exhibited broad adaptability for both the HPUs. According to Smith-Hazel multi trait indices, positive selection gain was observed for seed yield and shelling percentage in HPU 2. Overall both HPUs exhibited a net positive selection gain. The index consistently identified ICGVs 211020 and 211022 as superior ideotypes in both HPUs, ensuring selection reliability and wider adaptability. These multi-trait selection indices help breeders sustain progress in key traits like pod yield, while preserving the genetic gains in secondary traits like shelling outturn. The consistent positive selection gain across the HPUs underscores the effectiveness of targeted breeding in improving yield
Transforming aquatic weeds into resources: Pontederia crassipes, water hyacinth mining for circular bioeconomy
Get PDFGlobally, a positive shift to renewable and sustainable bioenergy usage has been witnessed over the years. An ideal resource should contribute equally to bioeconomy, circular economy and sustainable development. One such less explored resource is an aquatic weed, Pontederia crassipes, commonly known as water hyacinth, which is documented as one of the major invasive aquatic weeds due to its rapid reproduction, capacity to deplete nutrients from water bodies, and adaptation to new habitats. In particular, water hyacinths, which are abundant in India, are a rich source of nutrients and lignocellulosic biomass that may be utilized as a precursor for producing bioenergy and biofuel. At present all management and control strategies lack sustainable use of water hyacinth and in turn harm the surrounding ecosystem. This abundant source of biomass is underutilized, undermanaged, and difficult to collect. Tapping into management and harvesting strategies with efficient biomass conversion from water hyacinth, could lead to solutions for multi-level problems of current circular bioeconomic challenges in India. In this review, we critically discuss water hyacinth issues and management strategies and their potential use as a circular bioeconomic resource using relevant business models and case studies. To efficiently harvest, we present unique weed mining methodologies for the successful collection, treatment, and long-term utilization of the aforementioned bioresource. As a direct result, there may be a feasible answer to the growing need for biomass and bioenergy. Using water hyacinth, an invasive weed by nature, in a circular bioeconomic manner would also significantly advance numerous UN sustainable development objectives