Artificial Intelligence (AI) is revolutionizing the agricultural landscape, offering innovative solutions to enhance efficiency and productivity. Through advanced data analysis, machine learning, and predictive modeling, AI enables farmers to make data-driven decisions, optimize resource allocation, and mitigate risks. AI-powered technologies, such as precision farming and autonomous machinery, contribute to sustainable agriculture by minimizing resource wastage and improving crop yields. Additionally, AI applications in crop monitoring and disease detection help farmers identify potential issues early on, allowing for timely interventions. This synergy between technology and agriculture not only increases overall productivity but also fosters environmental sustainability. As AI continues to evolve, its integration into agriculture holds great promise for addressing global food challenges and creating a more resilient and efficient farming ecosystem.
Title : The essential role of photosynthesis in defining net zero carbon dioxide 2 emissions for equilibrium calculations
Dave White, Climate Change Truth Inc, United States
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