Optimizing the timing of management interventions against fall armyworm in African smallholder maize: Modelling the pattern of larval population emergence and development

Lowry, Alyssa; Durocher-Granger, L.; Oronje, MaryLucy; Mutisya, Daniel L.; Mfune, Tibonge; Gitonga, Christine; Musesha, Monde; Taylor, Bryony; Wood, Suzy V.; Chacha, Duncan; Beale, Tim; Finch, Elizabeth A.; Murphy, Sean T.

doi:10.1016/j.cropro.2022.105966

Cited by 5 publications

(2 citation statements)

References 52 publications

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“…However, it also highlights the potential benefit of using a derived canopy temperature variable for modelling where using accurate vegetation-level temperature data could increase accuracy, such as crop pest modelling. 24 The accuracy of our model predictions was affected by the vegetation cover in the sites. When the model was run with canopy temperature data, the average model predictions had the highest accuracy (1 day error IETD) for sites with a vegetation cover of 40-70%.…”

Section: Discussionmentioning

confidence: 98%

“…This shows that canopy temperature is the most appropriate temperature variable to use when running the biopesticide performance model. However, it also highlights the potential benefit of using a derived canopy temperature variable for modelling where using accurate vegetation‐level temperature data could increase accuracy, such as crop pest modelling 24 …”

Section: Discussionmentioning

confidence: 99%

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An updated and validated model for predicting the performance of a biological control agent for the oriental migratory locust

Finch,

Li,

Cornelius

et al. 2023

Pest Management Science

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BackgroundThe oriental migratory locust is a major crop pest across Eastern and South‐Eastern Asia. Metarhizium anisopliae is an effective biopesticide agent used for locust control, but its performance is temperature dependent, and thus can be more variable than chemical pesticide performance. To predict biopesticide performance for the control of the oriental migratory locust, we adapted a previous temperature‐dependent model and validated it using field trial data. To increase the applicability of this model, we explored the use of readily available temperature variables, as well as our own satellite‐derived canopy temperature variable, to run the model.ResultsCompared to collected in‐situ temperature data, our canopy temperature variable most accurately represented the ambient temperature experienced by the locust. When the biopesticide performance model was run using this canopy temperature, and then compared to field trials results, the model predictions were more accurate than when the model was run with the other temperature variables. The accuracy of the biopesticide performance model was impacted by vegetation cover, but across the areas most associated with locust oviposition, growth and migration, the model predictions were satisfactorily accurate to guide biopesticide operational use.ConclusionWe validated the model in six provinces in China, representing the three agro‐ecological zones largely representative of the oriental migratory locust problem areas in China, Thailand, Cambodia and Vietnam. Whilst further validation work is needed, this model could be used in these countries to assess, at a fine spatial scale, the appropriateness of M. anisopliae for controlling the oriental migratory locust.This article is protected by copyright. All rights reserved.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

An updated and validated model for predicting the performance of a biological control agent for the oriental migratory locust

Finch,

Li,

Cornelius

et al. 2023

Pest Management Science

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Pest risk information, agricultural outcomes and food security: evidence from Ghana

Tambo,

Mbugua,

Duah

et al. 2023

Food Sec.

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This article investigates the short-term effects of an information intervention that provided early warning pest alerts and integrated pest management (IPM)-based advice to smallholder farmers. Specifically, this study focuses on fall armyworm (Spodoptera frugiperda) of maize in Ghana. We particularly examine the relationships between access to pest risk information and a number of outcomes, ranging from farmer’s knowledge to household food security. This study is based on survey data collected between December 2021 and January 2022 from 888 farm households operating 1305 maize fields. Results from doubly robust and switching regression models indicated that exposure to the pest risk information campaign was significantly (ρ < 0.05) associated with increases in the likelihood of optimal timing of fall armyworm control action and the adoption of multiple IPM practices, but it had no significant effect on pesticide use. Households who received the pest risk information obtained an average of 4% or 54 kg/ha (ρ < 0.01) gain in maize yield and were about 38% less likely (ρ < 0.01) than their non-recipient counterparts to report experiencing hunger, as measured by the household hunger scale. However, the pest risk information campaign was not associated with greater household dietary diversity. Further results indicated that households where the pest risk information was received by women, alone or together with their spouses, were more likely (ρ < 0.05) to achieve positive outcomes than if the recipient of information were male member of households. Overall, our findings imply that the dissemination of early warning pest alerts in combination with actionable IPM information to smallholder farmers can contribute to the adoption of sustainable crop protection technologies, and ultimately improve the standard of living of farm households.

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CASF-MNet: multi-scale network with cross attention mechanism and spatial dimension feature fusion for maize leaf disease detection

Sun,

He,

Zhang

2024

Crop Protection

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Optimizing the timing of management interventions against fall armyworm in African smallholder maize: Modelling the pattern of larval population emergence and development

Cited by 5 publications

References 52 publications

An updated and validated model for predicting the performance of a biological control agent for the oriental migratory locust

An updated and validated model for predicting the performance of a biological control agent for the oriental migratory locust

Pest risk information, agricultural outcomes and food security: evidence from Ghana

CASF-MNet: multi-scale network with cross attention mechanism and spatial dimension feature fusion for maize leaf disease detection

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