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Empowering agriculture through agro-climate advisory services: pathway to resilience in Ethiopia
No full textScaling up and institutionalizing robust Agro-Climate Advisory (AgCA) systems is critical for building resilient agricultural systems, safeguarding food security, and improving the livelihoods of millions of smallholder farmers in Ethiopia and across the Global South.4 page
Farmers agronomic management responses to extreme drought and rice yields in Bihar, India
No full textIn 2022, the Indian state of Bihar experienced its sixth driest year in over a century. To document the consequences and farmer responses to the meteorological drought, real-time survey data was collected across 11 districts of Bihar. We then developed a causal machine learning model to quantify drought impacts on rice production and to characterize how access to affordable irrigation from electric pumps mitigated productivity losses. This model addresses the empirical challenge of conducting a counterfactual causal analysis when a factor like drought affects nearly all sampled farmers. In the 2022 event, drought led to rice acreage reduction, transplanting delays, damage to seedling nurseries, and higher use rates of supplemental irrigation. For fields that were planted, average yield losses from water stress were estimated as 0.94 t/ha (∼23 % yield loss) with these losses reduced by 0.3 t/ha in fields with access to electric tubewells. Agronomic management practices such as earlier transplanting were also identified as complementary strategies that increased the adaptation value of investments in irrigation. To reduce the impact of drought in Bihar, additional investments in electric irrigation infrastructure are needed along with focused extension efforts and decision support systems that empower farmers to make economically and sustainably rational use of available water resources to maintain yield and profitability
Combining ability and heterosis analysis for mineral content in the leafy vegetable Gynandropsis gynandra (L.) Briq.
No full textSpider plant (Gynandropsis gynandra) is a leafy vegetable rich in micronutrients, including minerals, vitamins, and secondary metabolites, making it a valuable opportunity crop for combating hidden hunger and promoting human health. However, knowledge of the inheritance of mineral content is limited, which hinders the development of improved cultivars for wider cultivation. To address this, 118 F1 experimental hybrids involving 26 parental lines were generated from a North Carolina mating design II. The F1s and their parents were evaluated across two years (2019 and 2020) for gene action, combining ability effects and heterosis of leaf mineral (zinc, copper, manganese, calcium, magnesium, sodium, phosphorus, and potassium) content. Significant differences (p < 0.001) were observed among and between hybrids and parents for iron, zinc, copper, manganese, calcium, magnesium, sodium, phosphorus, and potassium contents. The genotype x year interaction was also significant, with variance greater than the genotypic variance. Significant general and specific combining ability effects, together with variance components analysis, revealed that both additive and nonadditive gene action controlled mineral content, with a predominance of nonadditive gene action. Mid- and best-parent heterosis ranged from -80.4% to 389.5% for mineral content. Parents with good general combining ability were identified, as well as crosses with high specific combining ability and heterosis. There were significant and moderate to strong correlations between mean hybrid performance, specific combining ability effects, and heterosis levels, and low to moderate correlations between general combining ability and the performance of the mean parents. We conclude that hybridization in G. gynandra contributes to improving the mineral content. G. gynandra can be used as a model crop to study the genetic mechanism underlying heterosis in leafy vegetables
Sustainable insect pest management options for rice production in Sub-Saharan Africa
No full textRice production in Sub-Saharan Africa (SSA) faces significant challenges due to insect pest infestations, which threaten food security and farmer livelihoods. This review examines the major insect pests affecting rice in SSA and highlights sustainable management strategies, drawing on successful case studies. It explores successful methods, including the use of biological control agents in Nigeria; neem-based pesticides in Tanzania; push-pull technology in Kenya; agroecological practices in Mali; resistant rice varieties in Ghana and Nigeria; integrated farming systems in Liberia, Guinea Conakry, Nigeria, Kenya and Madagascar; and farmer field schools in Zambia. Emerging technologies such as biotechnology and precision agriculture offer further additional opportunities to enhance pest control when effectively integrated within existing IPM frameworks. However, financial constraints, limited awareness, policy-related challenges, and inadequate infrastructure continue to limit widespread adoption. In this context, the review identifies critical research gaps, including the need for region-specific solutions, improved biopesticides, and long-term assessment of sustainable practices. Policy recommendations call for greater government investments, capacity-building programs, supportive regulatory environments, and stronger collaboration among researchers, development partners, and local stakeholders. Addressing these challenges can foster resilient and sustainable rice production systems across SSA
Boosting genomic prediction transferability with sparse testing
No full textBackground/Objectives: Improving sparse testing is essential for enhancing the efficiency of genomic prediction (GP). Accordingly, new strategies are being explored to refine genomic selection (GS) methods under sparse testing conditions. Methods: In this study, a sparse testing approach was evaluated, specifically in the context of predicting performance for tested lines in untested environments. Sparse testing is particularly practical in large-scale breeding programs because it reduces the cost and logistical burden of evaluating every genotype in every environment, while still enabling accurate prediction through strategic data use. To achieve this, we used training data from CIMMYT (Obregon, Mexico), along with partial data from India, to predict line performance in India using observations from Mexico. Results: Our results show that incorporating data from Obregon into the training set improved prediction accuracy, with greater effectiveness when the data were temporally closer. Across environments, Pearson’s correlation improved by at least 219% (in a testing proportion of 50%), while gains in the percentage of matching in top 10% and 20% of top lines were 18.42% and 20.79%, respectively (also in a testing proportion of 50%). Conclusions: These findings emphasize that enriching training data with relevant, temporally proximate information is key to enhancing genomic prediction performance; conversely, incorporating unrelated data can reduce prediction accuracy
Data Harmonization Workshop towards FAIR and AI-Ready Data
No full textWorkshop Premise: The Data Harmonization Workshop brought together members of 12 CGIAR Centers in a hybrid four day event to develop a practical approach to foster a FAIR and AI-Ready data ecosystem across Centers, starting with data publishing. Building on past efforts, the workshop prioritized consensus building, focusing on key agreements for data publishing in two initial domains: Agronomy and Socioeconomics & Gender (with planned inclusion of further domains). Workshop Achievements: Outcomes include Key Agreements to steer further iteration and implementation of Data Harmonization efforts for AoW1 of the CGIAR Digital Transformation Accelerator. Outputs included (1) Draft Harmonization Guidelines, (2) Core Variables for agronomy and socioeconomics, and a (3) Two-pathway Model for Adoption (Mandate and User Motivation). Next steps include finalizing v0.1 of Harmonization Guidelines, expanding coverage across additional domains, and initiating the work plan agreed during the session.28 page
Consumption expenditure effects of adoption against drought tragedy in drought prone area of Eastern Hararghe, Ethiopia
No full textAnnual consumption expenditure of the households seriously affected by climate shocks in the country where the major livelihood of the community depends on rain based agriculture where adaptation should be key strategy against climate shocks effect. This study investigated the effects of crop diversification and irrigation practices adoption on consumption expenditure against drought in drought prone area of Eastern Hararghe. Both primary and secondary data was used for this study. Irrigation practices and crop diversification practices were mainly practiced and considered as climate smart agricultural practices here. Multistage procedure applied and data collected from 430 samples during 2023 year. From Hararghe zone four districts were randomly selected. To investigate effects of crop diversification and irrigation practices on consumption expenditure two-stage least square model was used. Three months scales’ standard precipitation index was applied to analysis drought using 33 years rainfall data. Result revealed that livestock, drought experience, labor, adopting crop diversity, irrigation practices and household income positively increased consumption expenditure whereas market distance, family size and drought affected negatively. So, it is crucial to more advances farmers and experts’ information on climate shocks particularly drought and adoption practices that minimize drought effects. The policymakers ought to develop farmers’ income generating activities and weather related information service to enhance adoption of crop diversification and irrigation facilities to combat the current and future drought effect
India's fertilizer policies: implications for food security, environmental sustainability, and climate change
No full textTo ensure food security, the Government of India has implemented various policies since the 1950s to provide enough and affordable fertilizer for farmers. Based on quantitative data, this paper provides a comprehensive and systematic analysis of how these policies influenced the fertilizer consumption and nutrient management and their influence on the socio-economic status of rural producers as well as environmental and climate outcomes. Increases in food grain production have paralleled the consumption of fertilizers. Even though the population of India increased more than three times from 1961 to 2022, per capita availability of rice remained almost the same, and that of wheat increased by 2.4 times. The price of urea has continuously decreased since 1977, but the price of diammonium phosphate fell only after the decontrol of phosphatic and potassium fertilizer in 1992, and the implementation of nutrient-based subsidies in 2010. Fertilizer policies have been linked to reductions in rural poverty and the contribution of agriculture to India's gross domestic product. However, the overuse of subsidized urea and underuse of phosphatic and potassium fertilizers have resulted in economic and nutrient use inefficiencies, reduced crop yields, and increased environmental risks, including nitrous oxide emissions and nitrate leaching. India's fertilizer policies must address these environmental challenges while ensuring food security for the growing population. Balanced fertilization should be incentivized through recalibrating subsidies and adopting soil nutrient-based recommendations. Gradual liberalization of urea pricing, alongside measures to ensure the affordability of phosphatic and potassium fertilizers for small and marginal farmers, will be essential to address the food-fertilizers-climatic crisis
Nitrogen fertilization strategy for Swiss winter wheat under climate-induced rainfall reduction: A model-based assessment
No full textReduced rainfall and nitrogen (N) use in warm-summer humid continental climates may lower wheat yields. Our study employs the DSSAT-Nwheat process-based crop simulation model to quantify the effects of N input and rainfall on various phenological stages of the Swiss wheat genotype CH Nara, calibrated and evaluated using field data from 2018 to 2022. Simulations over 42 years (1981-2022) across five different Cambisols used historical daily weather data to test rainfall reductions from 20 % to 100 % during three critical periods (30 days before anthesis, 30 days after anthesis, and +/- 30 days around anthesis) as well as throughout the entire season. Nitrogen fertilizer treatments ranged from zero to 140 kg N ha-1. The model accurately simulated yields with an RMSE of 895.5 kg ha-1 during calibration and 1091.4 kg ha-1 during validation. Results showed that yields were not adversely affected by rainfall reductions up to 40 %, regardless of N levels or timing. However, yields significantly declined when reductions exceeded 60 %, especially with N applications above 100 kg ha-1. Optimal yields were noted at 140 kg N ha-1, but benefits decreased under scenarios of reduced rainfall, indicating that N recommendations may need to be lowered in response to projected rainfall reductions. This study provides quantitative guidance for adapting wheat fertilization strategies to maintain productivity while accounting for future rainfall variability
Nitrogen management utilizing 4R nutrient stewardship: A sustainable strategy for enhancing NUE, reducing maize yield gap and increasing farm profitability
No full textThe imbalanced use of fertilizers, particularly the inefficient application of nitrogen (N), has led to reduced nitrogen use efficiency (NUE), lowered crop yields and increased N losses in Nepal. This study aimed to enhance yields, NUE and farm profitability by optimizing N fertilizer rates, application timing and methods through multilocation trials and demonstrations. In 2017, 57 field trials were conducted in two mid-hill districts using a completely randomized block design. The treatments included control (CK), NPK omission (N0, P0 and K0), variable N rates (60, 120, 180 and 210 kg N ha-1) and top-dressing timings (120 kg N ha-1 applied at knee height and shoulder height, V6, V10 and V8 stages). A full dose of recommended P (60 kg ha-1) and K (40 kg ha-1) were applied at planting, while N was top-dressed in two equal splits at knee-height and shoulder-height growth stages for P and K omission treatments, as well as for treatment with variable N rates. Grain yields responded quadratically, with optimum N rates ranging from 120 to 180 kg ha-1 across the districts. N applied at 120 kg ha-1 and top-dressed at V6 and V10 increased maize yield by 20-25%, partial factor productivity of nitrogen (PFPN) by 12%, agronomic efficiency of nitrogen (AEN) by 21% and gross margin by 10% compared to conventional knee and shoulder height application. In 2018 and 2019, fertilizer BMPs, including V6 and V10 top-dressing and the urea briquette deep placement (UDP) were demonstrated on 102 farmers' fields across five mid-hill districts to compare their agronomic and economic significance over traditional farmers' practice (FP). UDP, validated in 2018 field trials, increased yields by 34% (8.8 t ha-1) and urea top-dressing at V6 and V10 increased yield by 33% (8.7 t ha-1) compared to FP (5.8 t ha-1), reducing the average yield gap by 3.0 t ha-1. Moreover, the gross margin was increased by 39% (V6 and V10) and 40% (UDP) over FP. The findings highlight the need for widespread adoption of fertilizer BMPs to close the yield gap and maximize profitability with minimal nitrogen footprint