SMARTerra, a High-Resolution Decision Support System for Monitoring Plant Pests and Diseases

The prediction and monitoring of plant diseases and pests are key activities in agriculture. These activities enable growers to take preventive measures to reduce the spread of diseases and harmful insects. Consequently, they reduce crop loss, make pesticide and resource use more efficient, and preserve plant health, contributing to environmental sustainability. We illustrate the SMARTerra decision support system, which processes daily measured and predicted weather data, spatially interpolating them at high resolution across the entire Sardinia region. From these data, SMARTerra generates risk predictions for plant pests and diseases. Currently, models for predicting the risk of rice blast disease and the hatching of locust eggs are implemented in the infrastructure. The web interface of the SMARTerra platform allows users to visualize detailed risk maps and promptly take preventive measures. A simple notification system is also implemented to directly alert emergency responders. Model outputs by the SMARTerra infrastructure are comparable with results from in-field observations produced by the LAORE Regional Agency. The infrastructure provides a database for storing the time series and risk maps generated, which can be used by agencies and researchers to conduct further analysis.

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Publication Details

Journal
Applied Sciences
Published
2024-09-13
DOI
https://doi.org/10.3390/app14188275
Primary Topic
Smart Agriculture and AI
Type
article
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article

SMARTerra, a High-Resolution Decision Support System for Monitoring Plant Pests and Diseases

Andréa Pinna, Giuliano Fois, C. Milesi, Fabio Maggio et al.
Applied Sciences
Smart Agriculture and AI
article

SMARTerra, a High-Resolution Decision Support System for Monitoring Plant Pests and Diseases

Andréa Pinna, Giuliano Fois, C. Milesi, Fabio Maggio, Michele Fiori, Marco Secondo Gerardi
article en

Abstract

The prediction and monitoring of plant diseases and pests are key activities in agriculture. These activities enable growers to take preventive measures to reduce the spread of diseases and harmful insects. Consequently, they reduce crop loss, make pesticide and resource use more efficient, and preserve plant health, contributing to environmental sustainability. We illustrate the SMARTerra decision support system, which processes daily measured and predicted weather data, spatially interpolating them at high resolution across the entire Sardinia region. From these data, SMARTerra generates risk predictions for plant pests and diseases. Currently, models for predicting the risk of rice blast disease and the hatching of locust eggs are implemented in the infrastructure. The web interface of the SMARTerra platform allows users to visualize detailed risk maps and promptly take preventive measures. A simple notification system is also implemented to directly alert emergency responders. Model outputs by the SMARTerra infrastructure are comparable with results from in-field observations produced by the LAORE Regional Agency. The infrastructure provides a database for storing the time series and risk maps generated, which can be used by agencies and researchers to conduct further analysis.

Applied SciencesVol. 14(18)
Agenzia Regionale per la Protezione Ambientale del Piemonte (IT), Center for Advanced Studies Research and Development in Sardinia (IT)
Openalex Percentile: Top 92%
Smart Agriculture and AI
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SMARTerra, a High-Resolution Decision Support System for Monitoring Plant Pests and Diseases — Andréa Pinna, Giuliano Fois, et al. · Applied Sciences (2024) | TGRS Research Map | TGRS