Precision Agriculture Technologies for Early Detection of Crop Pests and Diseases
Year: 2024
Type: article
Abstract: Crop pests and diseases pose significant challenges to agricultural productivity and food security worldwide. Traditional methods for detecting and managing these threats often rely on manual scouting and blanket pesticide applications, which can be labor-intensive, time-consuming, and environmentally harmful. Precision agriculture technologies offer promising solutions for early detection and targeted management of crop pests and diseases. This review article provides a comprehensive overview of the latest precision agriculture tools and techniques for monitoring crop health, detecting pests and diseases, and guiding site-specific interventions. Key technologies discussed include remote sensing, proximal sensing, machine learning, robotics, and Internet of Things (IoT) sensors. The article highlights the potential of these technologies to improve the timeliness, accuracy, and efficiency of pest and disease detection while reducing reliance on chemical inputs. It also discusses the challenges and opportunities for integrating these technologies into current agricultural practices and extension services. The review concludes with recommendations for future research and development to advance precision agriculture solutions for sustainable crop protection.
Source: UTTAR PRADESH JOURNAL OF ZOOLOGY
Authors: Dipanwita Chattopadhyay, Y. Balachandra, Ashoka, P, Kailas Sampat Pagire, Thaneshwar Kumar Sahu, Narinder Panotra, G. Manisankar, Kurru Charitha, Bal veer Singh
Institutions: Brainware University, Acharya N. G. Ranga Agricultural University, University of Agricultural Sciences, Dharwad, Dr Panjabrao Deshmukh Krishi Vidyapeeth, Chhattisgarh Swami Vivekanand Technical University, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Visva-Bharati University, Chandra Shekhar Azad University of Agriculture and Technology
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4404051404