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.
Dachang Zhang
Water & Eco Crisis Foundation, United States
Srinivasa Rao Mentreddy
Alabama A&M University, United States
Usha R Palaniswamy
Maria College, United States
Jason A Hedrick
The Ohio State University, United States
Dilip Nandwani
Tennessee State University, United States
Stephen Jennewein
University of Florida, United States
Alene Alemu Tesfamichael
Edelmark AS, NorwaySubmit your abstract Today
Title : Development of Virginia mountain mint as a potential commercial crop in the southern USA
Srinivasa Rao Mentreddy, Alabama A&M University, United States
Title : Suitaiology: A strategic science for reframing agricultural risks under climate extremes — from water-use efficiency to water-situation wisdom
Dachang Zhang, Water & Eco Crisis Foundation, United States
Title : Agroecological practices and their effects on ecosystem services in sustainable mediterranean cropping systems
Fabio Gresta, University of Messina, Italy
Title : Cultivating green wisdom: Urban horticulture techniques for home vegetable cultivation in small spaces for older adults
Consuelo Lima Navarro de Andrade, State University of Feira de Santana (UEFS), Brazil
Title : Teaching food and nutrition security as a critical concern in higher education capstone
Usha R Palaniswamy, Maria College, United States
Title : Assessment of spraying effectiveness using heavy-duty agricultural UAVs in high-growing crops: Spray deposition and canopy coverage efficiency
Tytus Berbec, Institute of Soil Science and Plant Cultivation - State Research Institute, Poland