Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa
This study introduces a computational index that employs fuzzy sets theory to identify potential deployment sites for push-pull as a component in the integrated management of Fall Armyworm (FAW) in Africa. The index, validated through known push-pull testing sites and informed by insights from field...
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Elsevier
2025-02-01
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025009107 |
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| author | Komi Mensah Agboka Henri E.Z. Tonnang Emily Kimathi Elfatih M. Abdel-Rahman John Odindi Onisimo Mutanga Saliou Niassy |
| author_facet | Komi Mensah Agboka Henri E.Z. Tonnang Emily Kimathi Elfatih M. Abdel-Rahman John Odindi Onisimo Mutanga Saliou Niassy |
| author_sort | Komi Mensah Agboka |
| collection | DOAJ |
| description | This study introduces a computational index that employs fuzzy sets theory to identify potential deployment sites for push-pull as a component in the integrated management of Fall Armyworm (FAW) in Africa. The index, validated through known push-pull testing sites and informed by insights from field data and practical observations, is primarily based on companion plants (Desmodium intortum and Brachiaria brizantha), livestock, and maize as covariates. The study developed a set of rules linking each selected covariate to the output as membership functions, which are later combined using an algebraic operator. It identifies extensive maize farms across Africa potentially suitable for Push-Pull technology, although the suitability varies by region. Farms in the eastern and southern regions are predicted to be highly suitable, while the suitability of farms in West Africa is expected to improve over time due to the perennial nature and agronomic benefits of companion plants. The index is proposed as a metric for deploying push-pull technology, providing a roadmap for effective agronomic practices in Africa, and assisting farmers and decision-makers in the integrated management of FAW. Overall, our results indicate that the fuzzy-based computational index is an effective tool for identifying potential areas to maximise the benefits of push-pull technology as a key component of integrated FAW management. Our study identifies appropriate areas for application, allowing for the careful use of resources and increasing the likelihood of effective pest management. This approach will ultimately safeguard cereal crops, boost agricultural productivity, and aid in ensuring food security in Africa. |
| format | Article |
| id | doaj-art-adf8233a160d4c7aabaaf9eee5dc0168 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-adf8233a160d4c7aabaaf9eee5dc01682025-02-11T04:35:17ZengElsevierHeliyon2405-84402025-02-01114e42530Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in AfricaKomi Mensah Agboka0Henri E.Z. Tonnang1Emily Kimathi2Elfatih M. Abdel-Rahman3John Odindi4Onisimo Mutanga5Saliou Niassy6International Centre of Insect Physiology and Ecology (icipe), P.O. Box 30772 00100, Nairobi, Kenya; University of KwaZulu-Natal, School of Agricultural, Earth, and Environmental Sciences, Pietermaritzburg 3209, South Africa; Corresponding author. International Centre of Insect Physiology and Ecology (icipe), P.O. Box 30772 00100, Nairobi, Kenya.University of KwaZulu-Natal, School of Agricultural, Earth, and Environmental Sciences, Pietermaritzburg 3209, South AfricaIGAD Climate Prediction and Application Centre (ICPAC), Nairobi, KenyaInternational Centre of Insect Physiology and Ecology (icipe), P.O. Box 30772 00100, Nairobi, Kenya; University of KwaZulu-Natal, School of Agricultural, Earth, and Environmental Sciences, Pietermaritzburg 3209, South AfricaUniversity of KwaZulu-Natal, School of Agricultural, Earth, and Environmental Sciences, Pietermaritzburg 3209, South AfricaUniversity of KwaZulu-Natal, School of Agricultural, Earth, and Environmental Sciences, Pietermaritzburg 3209, South AfricaAfrican Union Inter-African Phytosanitary Council (AU-IAPSC), P.O. Box 4170, Yaoundé, Cameroon; Department of Zoology and Entomology, University of Pretoria, Private Bag X20, Hatfield 0028, South AfricaThis study introduces a computational index that employs fuzzy sets theory to identify potential deployment sites for push-pull as a component in the integrated management of Fall Armyworm (FAW) in Africa. The index, validated through known push-pull testing sites and informed by insights from field data and practical observations, is primarily based on companion plants (Desmodium intortum and Brachiaria brizantha), livestock, and maize as covariates. The study developed a set of rules linking each selected covariate to the output as membership functions, which are later combined using an algebraic operator. It identifies extensive maize farms across Africa potentially suitable for Push-Pull technology, although the suitability varies by region. Farms in the eastern and southern regions are predicted to be highly suitable, while the suitability of farms in West Africa is expected to improve over time due to the perennial nature and agronomic benefits of companion plants. The index is proposed as a metric for deploying push-pull technology, providing a roadmap for effective agronomic practices in Africa, and assisting farmers and decision-makers in the integrated management of FAW. Overall, our results indicate that the fuzzy-based computational index is an effective tool for identifying potential areas to maximise the benefits of push-pull technology as a key component of integrated FAW management. Our study identifies appropriate areas for application, allowing for the careful use of resources and increasing the likelihood of effective pest management. This approach will ultimately safeguard cereal crops, boost agricultural productivity, and aid in ensuring food security in Africa.http://www.sciencedirect.com/science/article/pii/S2405844025009107Fuzzy inference systemsSpodoptera frugiperdaTechnology transferPush-pull |
| spellingShingle | Komi Mensah Agboka Henri E.Z. Tonnang Emily Kimathi Elfatih M. Abdel-Rahman John Odindi Onisimo Mutanga Saliou Niassy Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa Heliyon Fuzzy inference systems Spodoptera frugiperda Technology transfer Push-pull |
| title | Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa |
| title_full | Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa |
| title_fullStr | Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa |
| title_full_unstemmed | Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa |
| title_short | Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa |
| title_sort | steering conservation biocontrol at the frontlines a fuzzy logic approach unleashing potentials of climate smart intercropping as a component within the integrated management of fall armyworm in africa |
| topic | Fuzzy inference systems Spodoptera frugiperda Technology transfer Push-pull |
| url | http://www.sciencedirect.com/science/article/pii/S2405844025009107 |
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