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
National Research Center for Geoanalysis and Water & Eco Crisis Foundation, United States
Srinivasa Rao Mentreddy
Alabama A&M University, United States
Alexandra D Solomou
Hellenic Agricultural Organization – Dimitra, Institute of Mediterranean Forest Ecosystems (IMFE), GreeceSubmit your abstract Today
Title : Socioeconomic constraints in implementing integrated pest management (IPM) in crops and solutions for sustainability
Shashi Vemuri, Professor Jayashankar Telangana State Agricultural University, India
Title : Food security in the SDG era: Challenges, opportunities, and climate-smart solutions
Shabbar Ali, University of Agriculture Faisalabad, Pakistan
Title : Exploration of the insecticidal properties of Juniperus communis L. essential oil on the grain weevil
Tadjine Nacera, Blida1 University, Algeria
Title : Risk extension: A step to capability for building farmers’ resilience and adaptation to climate changes
Rasha Mohamed El Sayed Shabana, Agricultural Research Center, Egypt
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 : Seed-cotton (or kapas) agricultural pollution and environmental health impact assessment
Vijayan Gurumurthy Iyer, Techno-Economic-Environmental Study and Check Consultancy Services, India