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.
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 : Monitoring, threats and conservation strategies for plant biodiversity in Greek forest ecosystems
Alexandra D Solomou, Hellenic Agricultural Organization – Dimitra, Institute of Mediterranean Forest Ecosystems (IMFE), Greece
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 : Improving food system awareness with agritourism: The Tour de Farm in Duval County, Florida
Stephen Jennewein, University of Florida, 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
Title : Sustainable land management by agrivoltaics in Colombia’s post-conflict regions: An integrated approach from the water–energy–food nexus
Sebastian Caceres Garcia, University Nacional de Colombia, Colombia