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 : Socioeconomic constraints in implementing integrated pest management (IPM) in crops and solutions for sustainability
Shashi Vemuri, Professor Jayashankar Telangana State Agricultural University, India
Title : Food security in the SDG era: Challenges, opportunities, and climate-smart solutions
Shabbar Ali, University of Agriculture Faisalabad, Pakistan
Title : Exploration of the insecticidal properties of Juniperus communis L. essential oil on the grain weevil
Tadjine Nacera, Blida1 University, Algeria
Title : Risk extension: A step to capability for building farmers’ resilience and adaptation to climate changes
Rasha Mohamed El Sayed Shabana, Agricultural Research Center, Egypt
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 : Seed-cotton (or kapas) agricultural pollution and environmental health impact assessment
Vijayan Gurumurthy Iyer, Techno-Economic-Environmental Study and Check Consultancy Services, India