Predictive pest monitoring is an advanced approach to managing agricultural pests by forecasting their outbreaks before they cause significant damage. By utilizing tools such as weather data, satellite imagery, and pest detection technologies, farmers can anticipate pest movements and populations. Predictive models use this data to inform decision-making, enabling farmers to take preventative actions like adjusting planting schedules, using targeted pest control measures, or deploying biological control agents. This proactive strategy helps minimize crop damage, reduce pesticide use, and lower production costs, while also contributing to sustainable agricultural practices. Predictive pest monitoring enhances the resilience of crops, ensuring higher yields and more efficient pest management.
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