Study of Optimization Techniques in Agriculture

Title

Study of Optimization Techniques in Agriculture

Creator

Nanjundan, Preethi; Indu, P.V.; Thomas, Lijo

Description

In agriculture, optimization strategies are essential for raising production, sustainability, and resource efficiency. This abstract explores several agricultural optimization approaches and highlights their importance in contemporary farming operations. Obstacles to traditional agricultural operations include climate change, resource constraint, and shifting consumer preferences. Through the application of cutting-edge technologies and rigorous scientific methods, optimization strategies provide answers to these problems. Precision agriculture, which uses data-driven techniques like remote sensing, Geographic Information System (GIS), and Global Positioning System (GPS) to customize farming procedures to particular field conditions, is one important area of optimization. This helps farmers to maximize yields while minimizing waste and the environmental effect of inputs like water, fertilizer, and pesticides. In addition, optimization methods include selective breeding for genetic advancements and biotechnology, with the goal of creating crops with increased nutritional value, disease resistance, and production potential. Under the category of optimization approaches are integrated pest management solutions, which efficiently control pests and illnesses while using less chemical pesticides by applying ecological principles. In summary, agricultural optimization approaches offer a comprehensive strategy to tackle the issues that contemporary farming faces, encouraging resilience, productivity, and sustainability in food production systems. Given the changing global agricultural dynamics, it is imperative that these strategies be further researched and used in order to ensure environmental stewardship and food security. 2026 Scrivener Publishing LLC. All rights reserved.

Source

Driving Innovation by Dynamic Optimization: The Challenges of Reshaping Industry;pp.485-508

Date

01-01-2026

Publisher

wiley

Subject

AI advancements; Data exchange; Deep learning; Efficiency; Innovation; Integration; IoT; Transformative change

Coverage

Nanjundan P., Department of Data Science, CHRIST University, Pune Lavasa Campus, Pune, India; Indu P.V., Department of Data Science, CHRIST University, Pune Lavasa Campus, Pune, India; Thomas L., Department of Data Science, CHRIST University, Pune Lavasa Campus, Pune, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 978-139431572-7; 978-139431569-7;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1002/9781394315727.ch24

https://www.scopus.com/pages/publications/105038505796?origin=resultslist