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With research staff from more than 70 countries, and offices across the globe, IFPRI provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition in developing countries.

researcher spotlight

Kinya Kaibung’a

Kinya Kaibung’a is a Research Officer with the Development Strategies and Governance Unit, based in Nairobi, Kenya. She has a keen interest in leveraging machine learning, AI, and other cutting-edge technologies to boost climate resilience and food security in smart agriculture systems.

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  • Agricultural Insurance: Innovations, Policies, and Pathways to Scale

    Farm households face numerous risks that can discourage investments and trap them in poverty. Insurance should be a useful tool to reduce these hazards, but agricultural risks are inherently difficult to insure against. Willingness and capacity to pay insurance premiums also range widely. The lack of adequate agricultural insurance is a major concern for governments,…

  • Navigating Risk: Challenges in Agricultural Commodity Shipping and Insurance Markets

    Shipping is at the heart of global agricultural trade, with more than 80 percent of staple crops and oilseeds moving by sea, yet maritime routes have become increasingly uncertain. Attacks on vessels in strategic corridors, drought‑restricted passages, and sharply rising war‑risk insurance premiums have created levels of exposure not seen in years. Bulk agricultural cargoes…

  • Advancing Poverty Graduation in Fragile Contexts: A New Agenda for Research and Policy

    Multifaceted livelihoods interventions that target households in extreme poverty are extremely effective in reducing extreme poverty, with consistent gains in income, consumption, savings, and psychosocial well-being. These interventions, often called graduation models, have been widely evaluated, but most evidence comes from stable rural settings. In fragile and conflict-affected environments where poverty is increasingly concentrated, household-level…

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Working Paper

Predicting agricultural productivity under climate change using crop yield emulator

2026Braide, Tamunotonye M.; Thomas, Timothy S.; Robertson, Richard D.
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Predicting agricultural productivity under climate change using crop yield emulator

This study develops a crop yield emulator as a computationally efficient alternative to the DSSAT process-based model, enabling fast, large-scale assessments of how temperature, rainfall, CO2, and nitrogen influence crop yields. Implemented using fixed-effects polynomial regression in R, the emulator was trained on DSSAT outputs and validated across seven globally important crops, maize, wheat (spring and winter), rice (indica and japonica), soybeans, sorghum, groundnuts, and potatoes. It showed high predictive accuracy (R2 > 0.90) for most crops, especially spring wheat, groundnut, and potato, and performed reliably under climate scenarios such as RCP7.0. The emulator captured key crop-specific responses, such as maize’s sensitivity to heat and nonlinear yield responses to nitrogen inputs. While its performance is slightly lower for maize and Indica rice compared to other crops, it remains a scalable and cost-effective tool for climate scenario analysis. This tool offers valuable support for agricultural decision-making and climate adaptation planning by enabling rapid, data-driven insights into yield outcomes under future conditions.

Year published

2026

Authors

Braide, Tamunotonye M.; Thomas, Timothy S.; Robertson, Richard D.

Citation

Braide, Tamunotonye M.; Thomas, Timothy S.; and Robertson, Richard D. 2026. Predicting agricultural productivity under climate change using crop yield emulator. IFPRI Modeling Systems Technical Paper 5. Washington, DC: International Food Policy Research Institute. https://hdl.handle.net/10568/183869

Keywords

Agricultural Productivity; Climate Change; Crop Yield; Yield Forecasting; Nitrogen; Carbon Dioxide; Regression Analysis

Language

English

Access/Licence

Open AccessCC-BY-4.0

Source

Source record

Project

Foresight

Record type

Working Paper

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Journal Article

Uncovering the climate vulnerability of China’s poverty alleviation frontiers

2026Zhao, Feng; Zuo, Lijun; Zhou, Yuyu; You, Liangzhi; Huang, Huabing; Sun, Rui; Zhao, Yuanyuan; Li, Xunhuan; Zhang, Dawei; Meng, Ran
Details

Uncovering the climate vulnerability of China’s poverty alleviation frontiers

Year published

2026

Authors

Zhao, Feng; Zuo, Lijun; Zhou, Yuyu; You, Liangzhi; Huang, Huabing; Sun, Rui; Zhao, Yuanyuan; Li, Xunhuan; Zhang, Dawei; Meng, Ran

Citation

Zhao, Feng; Zuo, Lijun; Zhou, Yuyu; You, Liangzhi; Huang, Huabing; et al. 2026. Uncovering the climate vulnerability of China’s poverty alleviation frontiers. Global Environmental Change 98(July 2026): 103140. https://doi.org/10.1016/j.gloenvcha.2026.103140

Country/Region

China

Keywords

Asia; Eastern Asia; Climate Change; Vulnerability; Poverty Alleviation; Rural Development; Climate Resilience; Spatial Data; Climate-smart Agriculture

Language

English

Access/Licence

Limited Access

Links

https://doi.org/10.1016/j.gloenvcha.2026.103140 Source record

Record type

Journal Article

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Journal Article

Genetic technologies to enhance crop nutritional value under climate change

2026
Van Der Straeten, Dominique; Bulut, Mustafa; Cao, Da; Aharoni, Asaph; Bouis, Howarth E.; Granell, Antonio; Gruissem, Wilhelm; Lindberg Møller, Birger; Martin, Cathie; Puchta, Holger
…more Sreenivasulu, Nese; Tissier, Alain; Tripathi, Leena; Van Montagu, Marc; Fernie, Alisdair R.
Details

Genetic technologies to enhance crop nutritional value under climate change

Year published

2026

Authors

Van Der Straeten, Dominique; Bulut, Mustafa; Cao, Da; Aharoni, Asaph; Bouis, Howarth E.; Granell, Antonio; Gruissem, Wilhelm; Lindberg Møller, Birger; Martin, Cathie; Puchta, Holger; Sreenivasulu, Nese; Tissier, Alain; Tripathi, Leena; Van Montagu, Marc; Fernie, Alisdair R.

Citation

Van Der Straeten, Dominique; Bulut, Mustafa; Cao, Da; Aharoni, Asaph; Bouis, Howarth E.; et al. 2026. Genetic technologies to enhance crop nutritional value under climate change. Nature 654(8120): 877-891. https://doi.org/10.1038/s41586-026-10593-6

Keywords

Genetic Techniques; Biofortification; Nutritive Value; Nutrient Improvement; Climate Change

Language

English

Access/Licence

Limited Access

Links

https://doi.org/10.1038/s41586-026-10593-6 Source record

Record type

Journal Article

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