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 : The essential role of photosynthesis in defining net zero carbon dioxide 2 emissions for equilibrium calculations
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Title : Micromammal diversity and health in agricultural landscapes: A focus on body condition
Linas Balciauskas, Nature Research Centre, Lithuania
Title : Suitaiology: Technical goals and general concept designing for applications in mountain areas
Dachang Zhang, National Research Center for Geoanalysis and Water & Eco Crisis Foundation, United States
Title : Environmental Health Impact Assessment (EHIA) process for agricultural and horticultural processes - Case study as ginning of Indian seed-cotton (or kapas)
Vijayan Gurumurthy Iyer, Techno-Economic-Environmental Study and Check Consultancy Services, India
Title : Farm safety day camp programming for youth
Jason A Hedrick, The Ohio State University, United States
Title : The influence of intensive and organic agriculture activity on the quality of ground and surface water
Laima Cesoniene, Vytautas Magnus University, Lithuania