Key issues in incorporating proximal and remote sensor data into farm decision-making

Adélia M. O. Sousa, José R. Marques da Silva,João Serrano,Shakib Shahidian, Duarte Lobo da Silveira, Manuela Simões,Ana Cristina Gonçalves, Maria João P. Caldinhas,Vasco Fitas da Cruz, Arilson J. de Oliveira Júnior, Silvia R. Lucas de Souza, Diogo R. Coelho,Patrícia Lourenço,Fátima F. Baptista

Smart farms: Improving data-driven decision making in agriculture Burleigh Dodds Series in Agricultural Science(2024)

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摘要
This chapter presents five study cases on the application of smart technologies in farming and forestry systems. The first of these study cases presents the results of a long-term study to calibrate a Grassmaster II capacitance probe to estimate pasture productivity in the Mediterranean Montado ecosystem. The second case study presents a methodology for identifying yield zones within an olive grove based on Sentinel-2 satellite data. The third case study provides an overview of different remote sensing sensors, data and methodologies used for estimating forest biomass. The fourth case study assesses the carbon footprint of horticultural crops such as potato, onion, carrot, melon and watermelon. The final case study focuses on precision livestock farming, specifically a mobile application focused on thermal comfort.
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