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
Sadygova Madina Karipullovna
Vavilov University, Russian Federation
Srinivasa Rao Mentreddy
Alabama A&M University, United States
Dilip Nandwani
Tennessee State University, United States
Nedyalka Valcheva
Vocational High School, Bulgaria
Stephen Jennewein
University of Florida, United States
Jason A Hedrick
The Ohio State University, United StatesSubmit 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 : Socioeconomic constraints in implementing Integrated Pest Management (IPM) in crops and solutions for sustainability
Shashi Vemuri, Professor Jayashankar Telangana State Agricultural University, India
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 : The use of CHP condensate water in greenhouse cultivation
Lisa Huybrechts, Proefstation voor de Groenteteelt vzw, Belgium
Title : Characterization of isolated strains of microorganisms from mineral, mountain, and spring waters from France, Italy, England, South Korea, Japan, the Netherlands, Austria, Spain, Singapore, Germany, Switzerland, Greece, Turkey, Dubai, and Bulgaria.
Nedyalka Valcheva, Vocational High School, Bulgaria
Title : Markers of PM produced by biomass combustion and development of a sampling and analysis technique
Enrico Paris , CREA-IT , Italy