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Gender Differences in Farmers' Indigenous Knowledge of Vegetables Disease Management: Implication for Artificial Intelligence-Enabled Farmers' Decision Support System

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dc.contributor.authorDeji, Olanikeen
dc.contributor.authorAdisa, Priscillaen
dc.contributor.authorOgunbona, Philipen
dc.contributor.authorFaniyi, Ebunoluwaen
dc.contributor.authorOlowoyo, Olamideen
dc.contributor.authorJubril, Abimbolaen
dc.contributor.authorOmotola, Olajideen
dc.contributor.authorOlukayode, Samuelen
dc.coverage.countryNigeriaen
dc.date.accessioned2024-07-03T12:56:11Zen
dc.date.available2024-07-03T12:56:11Zen
dc.date.issued2021en
dc.description.abstractThe study was carried out in Osun State, Nigeria with the aim to analyse male and female vegetable farmers’ indigenous knowledge of disease management. It specifically assessed the indigenous knowledge of male and female farmers on the symptoms, causes, curative, and preventive measures of the vegetable crop diseases. This was done with the aim to provide gender-responsive benchmark data that could enhance the effective adoption of AI-enabled decision support system for crop disease management. Structured interview schedule was used to elicit quantitative data from 106 respondents (59 males and 47 females) for the study. Descriptive statistics was used to analyse the data. Majority of the male and female farmers used indigenous knowledge in identifying the symptoms, causes, curative and preventive measures of most common vegetable crop diseases. Expert/Extension professional-based human intelligence was also a major source of information on crop disease management among the male and female farmers, but the female farmers experienced lower extension contacts than the males. Scientific study and integration of gender responsive and enabling indigenous knowledge on crop disease management into the AI-enabled farmers’ decision support system involving experts and extension professionals is recommended for effectiveness and sustainabilityen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationDeji, O. F., Adisa, P. T., Ogunbona, P. O., Faniyi, E. O., Olowoyo, O. A., Jubril, A. M., Omotola, O. A. & Olukayode, S. (2021). Gender differences in farmers’ indigenous knowledge of vegetable disease management: Implications for artificial intelligence-enabled farmers’ decision support system. Proceedings of the 30th Annual National Congress of the Rural Sociological Association of Nigeria (RuSAN), pp. 40-43 https://administrative.rusan.org.ng/storage/conference-full-editions-doc/Conference-Proceeding-Edition-30th.pdfen
dc.identifier.urihttps://hdl.handle.net/10919/120581en
dc.identifier.urlhttps://administrative.rusan.org.ng/storage/conference-full-editions-doc/Conference-Proceeding-Edition-30th.pdfen
dc.language.isoenen
dc.publisherRural Sociological Association of Nigeriaen
dc.titleGender Differences in Farmers' Indigenous Knowledge of Vegetables Disease Management: Implication for Artificial Intelligence-Enabled Farmers' Decision Support Systemen
dc.typeConference proceedingen
dc.type.dcmitypeTexten

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