International Crops Research Institute for the Semi-Arid Tropics
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Groundnut Breeding Advancements: Efforts Towards Genomic Selection for Quicker Genetic Gains
No full textGroundnut (Arachis hypogaea L.) is an important food crop in sub-Saharan Africa, and worldwide. Among the major causes for low yields is the susceptibility of cultivated varieties
to the Groundnut Rosette Disease (GRD) and leaf spots. Genomic selection (GS), characterized by a model calibrated on phenotype and genotype information of a training population is used to predict genomic estimated breeding values (GEBVs). The essence of GS in any breeding program is to accelerate the selection progress by shortening generation interval and increase in selection intensity, thus a resource saving breeding method. Traditional breeding methods are augmented by GS that has the ability to forecast GEBVs with enough precision for selection across multiple generations that eliminates the need for extensive phenotyping and speeds up genetic gains. To support these efforts, vector-host interaction studies have been conducted, populations to support GRD markers support developed, evaluated and genotyped; an African core set genotyped, a genome-wide association analysis for loci associated key traits done, and studies on prediction models building on studies from earlier efforts, such high-density
genotyping and prediction accuracy for different GS models and cross validation approaches for key traits. The valuable results on vector-host interaction forms a basis for further
characterization of these genotypes using the GRD validated molecular markers to understand the physiological basis of the varied reaction to vector and disease incidence. Sequencing the genome of the aphid species on groundnut is crucial to inform the diversity of the vector and give insights on how microbial effector proteins, host targets and plant immune receptors coevolve. The validation of the GRD markers will be a breakthrough in breeding efforts through marker assisted selection for this trait, while at the same time providing genetic information to improve the prediction of GS models. The genome wide association mapping marker set was very informative, comparable to the Africa core set study. The marker set would be ideal for future development of quality check (QC) and mid-density panel markers. The prediction accuracy increased and genetic variation decreased when large-effect SNPs were fitted as fixed factors. We envisage to enhance the superiority of the GS results further through multienvironment prediction models, and more quality phenotypic details of the key traits in question. These efforts will provide an array of tools for use to achieve quick genetic gains in the groundnut breeding programs
Current Status of Aflatoxin Mitigation in Groundnut
No full textAflatoxin contamination of peanuts continues to be a major problem in peanut trade and a health risk for consumers in many African countries. Farmers are increasingly being
encouraged to grow and expand the acreage under peanut production. However, for smallholder farmers to benefit fully, solutions must be found to reduce aflatoxin contamination. The status of mitigating aflatoxin contamination, in African countries, along the groundnut value chain will be discussed. Holistic mitigation strategies that are deployed during production and postharvest, increased consumer awareness, and safe end use alternatives provide the best current options
Identification of a Homologue of DOG 1 Within a Major QTL Region of Seed Dormancy in Groundnut (Arachis hypogaea L.)
No full textGroundnut (Arachis hypogaea L.), an important oilseed and food crop, is encountered by end season rains leading to in situ germination. Seed dormancy of 2-3 weeks is essential to escape this problem. In this study, a major QTL (qDORM_A04_MET) for seed dormancy was identified by mapping with MITE and SSR markers using a recombinant inbred line population derived from non-dormant parent (TG 51) and dormant parent (TG 22). This QTL explained 12% phenotypic variation due to seed dormancy in the RIL population and covered 46 Mb map-interval in chromosome A04. While, QTL-Seq has revealed a broader region of Arahy.04 that has significant association with dormancy phenotype in terms of ΔSNP index in this genomic region. This broader region of A04 has several significant InDels, which were used to
design PCR based markers. These markers were used for re-mapping of dormancy QTL and identified a relatively smaller genomic region with significant QTL detection. Sequence
comparison and gene annotation analysis of this new QTL version qDORM_A04_MET revealed six putative genes related to seed dormancy. Of them, a homologue of ‘Delay Of Germination 1 (DOG 1) was found upregulated commonly among three near isogenic dormant lines compared to their respective non-dormant counterpart. Thus, the present report describes
identification of DOG1 homologue in Arahy.04 towards its putative role in seed dormancy using both genomics, transcriptomics and conventional genetic mapping approach
Transforming Pest Management with Artificial Intelligence Technologies: The Future of Crop Protection
Get PDFWith increasing global population and limited expansion of cultivated land, it is necessary to identify innovative solutions for enhancement of agricultural productivity and meet growing food demand. Despite significant advancements in crop protection methods, substantial annual crop losses persist particularly due to pests. Artificial Intelligence (AI) has emerged as a transformative tool to reform crop protection strategies. With the support of machine learning and deep learning algorithms, AI enables precise pest detection, risk assessment, monitoring, and forecasting thereby minimizing crop losses and maximizing yields. Further, AI integrates expert system and decision support system with crop management aspects for precise and timely decisions for farmers to enhance the crop productivity. In this review article, attempts are taken to explore the applications, implications, and future prospects of AI in field of pest management, emphasizing its pivotal role in agriculture and thus ensuring food security among evolving challenges
Introduction: Breeding Climate Resilient and Future-Ready Pulse Crops
No full textPulse crops are widely cultivated and consumed across the globe, playing a vital role as key sources of protein and other essential nutrients. Many traditional and modern culinary dishes rely heavily on staple pulse crops like chickpea, lentil, mung bean, pigeon pea and black gram, while some pulses have industrial uses. This compilation explores the latest advancements in breeding pulse crops to make them resilient to climate change, with an emphasis on improving resistance to biotic and abiotic stresses, along with yield traits. The varietal development process is becoming more efficient and precise thanks to new methods such as genome editing, genomic selection, haplotype-based breeding and speed breeding, which also help in reducing resource utilisation. Also, to further enhance production, there is a need to focus on adopting artificial intelligence (AI) and machine learning (ML)-driven breeding tools, thereby lowering developmental costs and saving time. The current challenge is to effectively integrate and apply these advanced techniques and methods into ongoing crop improvement initiatives
Scaling Delivery Strategy for Harmonized Digital Fertilizer and Agronomic Solutions (HaFAS) for Transforming Crop Production in Ethiopia
Get PDFThe Problem: Ethiopia's agriculture sector, which employs over 70% of the population, faces significant challenges in enhancing crop productivity and maintaining soil health. Over 70% of cultivated agricultural land is used to produce cereals, using 60% of the rural workforce. Moreover, over 50% of the daily caloric intake of an average household in Ethiopia is from wheat, sorghum, and maize. Yet, there are substantial yield gaps in maize, wheat, teff, and sorghum, with actual yields far below their potential. Inefficient fertilization practices, including incorrect application rates based on blanket recommendations that do not account for variations in soil type, topography, and crop type, limit the effectiveness of fertilizer use. Soil quality has been a concern of the Ethiopian government for some time, with soil fertility research starting in the 1950s. Affordability of fertilizer has become a major issue, even among commercial farmers, since the onset of the Russian Ukrainian war. The Ethiopian government is committed to improving crop productivity, as demonstrated by their expenditure of $1.1 billion on 1.35 million metric tons of fertilizer imports in 2023. Increasing fertilizer use efficiency is central to maximizing the benefit from its fertilizer investment and minimizing the potential negative impacts of its use on the environment. In addition, as fertilizer is mostly distributed through cooperatives, fertilizer is mostly accessed by market-oriented male farmers. The government recognizes that women’s access to advisory services, in person or digital, is 41% lower than men’s.
The Core Innovation: The core innovation is a digital localized agronomy and fertilizer advisory tool (LAFA) that combines and harmonizes earlier work on two separately developed digital tools, the NextGen Fertilizer Advisory System developed by the Alliance of CIAT and Bioversity, and the landscape-based Specific Fertilizer Recommendation (LANDWise) developed by ICRISAT. There are other agro-advisory services, such as climate information, lime application advice, and crop-specific soil and agronomic advice that can be potentially bundled into LAFA and/or broader Harmonized Digital Fertilizer and Agronomic Solutions (HaFAS). The HaFAS framework is modular, meaning innovations and improvements in one part of the HaFAS ecosystem do not affect other parts of the system.
Through a convening harmonization meeting in September 2023 and a subsequent launch meeting in November 2023, a harmonized digital decision-support tool (DST) framework led by the Ministry of Agriculture (MoA) and NARS (EIAR and RARIs) was adopted, which integrated multiple decision support tools (DSTs) into a comprehensive agro-advisory system, principally using digital delivery channels to service rural farmers directly or through extension personnel. The HaFAS will provide public access to data contributed by multiple organizations in a “Coalition of the Willing (CoW),” including a national soil database, remote sensing databases, and decades of findings from on-farm trials on fertilizer response for specific crops. A major component is harmonized site-specific fertilizer recommendations and bundled agro-advisories tailored to specific crop and geographic needs and adapted to variable climate scenarios, referred to as the Localized Agronomy and Fertilizer Advisory (LAFA).
Extensive field validations of the LAFA have been conducted in 2024 across 1,570 farmers' fields to ensure the recommendations are practical and context specific. Data are being analyzed during the first quarter of 2025. The LAFA integrates machine learning, the QUEFTS model, extensive agronomic data, and geospatial covariates to provide optimized fertilizer recommendations. Practitioners can integrate the LAFA into user-friendly interfaces, such as APIs, dashboards, chatbots, IVR, mobile apps, web apps, and SMS, to ensure accessibility and practicality. This initiative aligns with the government's focus on Digital Agriculture Roadmap 2032 and modernized agricultural strategies on digital agriculture and extension advisory services (DAEAS). It is of note that the core now harmonized innovation, LAFA, is still under wide-scale validation in 2025 under different paths and referred to as the pre-scaling period
The Case for Scaling: Harmonized Digital Fertilizer & Agronomic Solutions (HaFAS), Ethiopia
Get PDFEthiopia's agriculture sector, a cornerstone of its economy, employs over 70% of the population, but is hampered by generic fertilizer advice and a $1.1 billion USD annual fertilizer import bill. Yet, an innovative digital tool offers a solution - the Harmonized Digital Fertilizer and Agronomic Solutions (HaFAS), integrates advanced data to deliver precise, site-specific fertilizer and agro-advisory recommendations. The innovations’ bold ambition to reach 6.85 million farmers by 2040 (including 2.05 million women and 2.74 million youth), would boost national cereal production from 31.6 million to 140 million metric tons and enhance food security and economic resilience
Nutrition and health-promoting characteristics of millets: Evidence from meta-analyzes and intervention studies with a focus on diet-responsive diseases in India
No full textMillet foods are essentially whole grain which provides greater nutrient density than refined wheat and rice foods, now the staples for many. Millets are also a much-needed climate-resilient crop. There is great interest to assess whether more millets in the diet will have health benefits crucially to reduce diet-responsive diseases such as childhood stunting and anemia, which remain highly prevalent in India and others such as obesity which is increasing along with consequential cardiovascular diseases and type 2 diabetes. Millets vary considerably in nutritional composition both within and between species of millet and critically there are very few data on key nutrient bioavailability and how it is influenced by food processing, cooking, etc. While there is evidence that millets have the potential to reduce the risk of some of the prevalent diet-responsive conditions, the evidence base is rather old and needs considerable updating with up-to-date millet types and robust experimental designs
Differential impacts of regenerative agriculture practices on soil organic carbon: a meta-analysis of studies from India
Get PDFRegenerative agriculture (RA) is heralded as a transformative solution to combat climate change, enhance biodiversity, and improve soil health. However, its effectiveness across diverse agroclimatic contexts remains underexplored. This meta-analysis synthesizes results from 147 peer-reviewed studies across India's major agro-ecological and agro-climatic regions. Using a random-effects model, we estimate the soil organic carbon (SOC) change attributable to a suite of RA practices, including organic amendments (farmyard manure, green manure, compost, and biochar), conservation tillage, crop residue retention, and fertilizer management. Biochar application resulted in the highest SOC gain, followed by farmyard manure, green manure, compost, and fertilizer management. Conservation tillage and crop residue retention demonstrated moderate, yet consistent, carbon benefits across time scales. The SOC gains were most significant over durations exceeding five years and varied across agro-ecological regions, with semi-arid and sub-humid regions showing particularly strong responses. The findings affirm that RA practices effectively sequester carbon, particularly when applied over longer durations and in regionally adapted combinations
From Millet’s ‘Pearl’ To Desert’s ‘Gold’: GHB 538 Improved (Maru Sona) Emerges through Genomics-assisted Breeding
No full textDowny mildew (DM) is the most devasting disease of pearl millet caused by Sclerospora graminicola (Sacc.) Schroet, remains a major biotic constraint to pearl millet production in India. Looking to this constraint, Junagadh Agricultural University, Junagadh (Gujarat), in collaboration with ICRISAT (International Crops Research Institute for the Semi-Arid Tropics), Hyderabad, decided to improve notified popular pearl millet hybrid GHB-538 through marker-assisted backcross breeding due to which this hybrid make a comeback in as improved version. Christened Maru Sona or Desert Gold in the local language, the new version is equipped with the genes to fend off devastating downy mildew disease and was released for cultivation in Gujarat state and A1 zone dry regions of Rajasthan, Gujarat, Haryana during kharif season. The pearl millet hybrid GHB 538 Improved was developed by introgression of downy mildew resistance QTLs from P7-3-P13 and 863B-P2-P7 lines in the pollen parent J-2340 of earlier released GHB-538 with marker-assisted backcross method using foreground selection and notified at state and national level for kharif season cultivation. The screening against downy mildew of GHB 538 Improved was carried out under the downy mildew sick plot, and yield trials testing work against original GHB-538 was carried out at state and national levels across different locations. In comparison to the original hybrid, Maru Sona shows markedly high resistance to downy mildew disease along with an increase in grain yield (3.5 and 1.8%) and dry fodder yield (10.8 and 1.9%); it also hallmarks early flowering (44 and 45 days) at state and AICRP testing, respectively. It also shows resistance reaction to other pearl millet diseases and possesses good quality parameters