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Weather-Based Yield Prediction

Weather-Based Yield Prediction

Accurate weather-based yield prediction is essential for modern agriculture. Using advanced technologies like remote sensing, AI, and big data analytics, farmers can forecast crop performance based on climatic variables such as temperature, rainfall, and humidity. These predictions help in planning irrigation, pest control, and harvest schedules, reducing losses and maximizing output. Weather-based models integrate historical data and real-time monitoring to provide localized insights. For instance, drought-prone areas can adjust planting dates or switch to resilient crop varieties based on predictions. Governments and agribusinesses are investing in these tools to support food security and climate adaptation. Such innovations ensure informed decision-making, empowering farmers to tackle uncertainties effectively.

Committee Members
Speaker at Agriculture and Horticulture 2025 - Dachang Zhang

Dachang Zhang

National Research Center for Geoanalysis and Water & Eco Crisis Foundation, United States
Speaker at Agriculture and Horticulture 2025 - Edgar Omar Rueda Puente

Edgar Omar Rueda Puente

Universidad de Sonora, Mexico
Speaker at Agriculture and Horticulture 2025 - Linas Balciauskas

Linas Balciauskas

Nature Research Centre, Lithuania
Agri 2025 Speakers
Speaker at Agriculture and Horticulture 2025 - Rao Mylavarapu

Rao Mylavarapu

Univeristy of Florida, United States
Speaker at Agriculture and Horticulture 2025 - Omar Sulaiman Belhaj

Omar Sulaiman Belhaj

The University of Texas at El Paso, United States
Speaker at Agriculture and Horticulture 2025 - Roselyne Aleyo

Roselyne Aleyo

Massey University and Agresearch Grasslands Campus, New Zealand
Speaker at Agriculture and Horticulture 2025 - Jenny Lindblom

Jenny Lindblom

Lulea University of Technology, Sweden
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