IITA Bibliography is a collection of agricultural research publications produced by IITA scientists, research fellows, and students from 1972 to date. The collection includes journal articles, books and book chapters, conference proceedings, training and extension materials, theses, and other publications. IITA conducts research in these thematic areas: biotechnology and plant breeding, natural resource management, social science and agribusiness, plant production and plant health, and nutrition and human health.

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  • The ‘Nigerian Diet’ and its evolution: review of the existing literature and household survey data 

    Petrikova, I.; Bhattacharjee, R.; Fraser, P.D. (2023-01)
    Natural and social science studies have commonly referenced a ‘typical’ or ‘habitual’ Nigerian diet, without defining what such a diet entails. Our study, based on a systematic review of the existing literature and an analysis of household-level survey data, describes the general outline of a common Nigerian diet and how it varies based on spatial, demographic, and socio-economic characteristics. We further try to establish whether Nigeria has embarked on a dietary transition common in most modern ...
  • Integrating APSIM model with machine learning to predict wheat yield spatial distribution 

    Kheir, A.M.S.; Mkuhlani, S.; Mugo, J.W.; Elnashar, A.; Nangia, V.; Devare, M.; Govind, A. (2023-09)
    Traditional simulation models are often point based; thus, more research is needed to emphasize spatial simulation, providing decision-makers with fast recommendations. Combining machine learning algorithms with spatial process-based models could be considered an appropriate solution. We created a spatial model in R (APSIMx_R) to generate fine-resolution data from coarse-resolution data, which is typically available at the regional level. The APSIM crop model outputs were then deployed to train ...
  • Large language models and agricultural extension services 

    Tzachor, A.; Devare, M.; Richards, C.; Pypers, P.; Ghosh, A.; Koo, J.; Johal, S.; King, B. (2023-11)
    Several factors have traditionally hampered the effectiveness of agricultural extension services, including limited institutional capacity and reach. Here we assess the potential of large language models (LLMs), specifically Generative Pre-trained Transformer (GPT), to transform agricultural extension. We focus on the ability of LLMs to simplify scientific knowledge and provide personalized, location-specific and data-driven agricultural recommendations. We emphasize shortcomings of this technology, ...
  • Impact of agribusiness empowerment interventions on youth livelihoods: insight from Africa 

    Adeyanju, D.; Mburu, J.; Gituro, W.; Chumo, C.; Mignouna, D.; Mulinganya, N. (2023-11)
    This study generates evidence to understand the impact of agribusiness empowerment programmes on youth livelihoods in developing countries based on the ENABLE-TAAT programme implemented in Kenya, Nigeria, and Uganda. A multistage sampling technique was used in obtaining primary agribusiness-level data from a sample of 1435 young agripreneurs from the study countries. An Endogenous Treatment Effect Regression (ETER) model was used to assess the impact of programme participation on youth livelihoods ...

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