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 : 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