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

BACKGROUND: The 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. RESULTS: Compared 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 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. CONCLUSION: We 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. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Predicting Overwintering of Wheat Stripe Rust in Central and Northwestern China.

Stripe rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss. (Pst), is an important disease of wheat. In China, Pst management has focused on the Gansu region where the pathogen can complete its annual cycle, including oversummering and overwintering. From this region, Pst inoculum is dispersed to the southern Yangtze River region in the late autumn/early winter and then to the main wheat production regions in the following spring. We used historical weather data (1995 to 2016) and field stripe rust assessment data (8 years) in the spring to evaluate the performance of a published model for predicting the potential of Pst overwintering in the Gansu region. Both predicted and observed values of rust overwintering in the Gansu region varied greatly between years and between sites within a single year, indicating the value of predicting rust overwintering for disease management. The model predictions fitted with observed values satisfactorily. All high incidences of rust in the spring were observed in the fields of the monitoring sites where the high potential of overwintering was predicted. Conversely, the predicted rust overwintering potential was also close to zero in the fields where rust was not observed in the spring. There were many false-positive predictions, which may be attributable to the absence of rust in autumn seedlings. This model can be used to target rust management in the spring and its effectiveness will be further improved if autumn rust assessment can be carried out.