Guest Editors
Prof. Dr. Sumin Kim
Email: sumin.kim@dankook.ac.kr
Affiliation: Department of Environmental Horticulture & Landscape Architecture, College of Life Science & Biotechnology, Dankook University, Cheonan-si, Republic of Korea
Homepage:
Research Interests: simulation, physiology, precision agriculture, agrivoltaic system
Prof. Dr. Sojung Kim
Email: sojungkim@dgu.ac.kr
Affiliation: Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, Republic of Korea
Homepage:
Research Interests: simulation, agriculture, optimization, machine learning model
Summary
This special issue explores innovative and comprehensive strategies for improving crop yield through integrated approaches that combine advances in genetics, agronomy, technology, and sustainable practices. With the increasing global demand for food security and the challenges posed by climate change, it is essential to develop multifaceted solutions that enhance productivity while maintaining environmental health. Contributions in this issue cover a wide range of topics, including precision agriculture, biotechnological innovations, soil and water management, crop modeling, and the integration of digital tools. Emphasizing interdisciplinary collaboration, the special issue aims to provide insights into how combined approaches can optimize crop performance, increase resilience, and promote sustainable agriculture systems. The collected research and reviews will serve as a valuable resource for researchers, agronomists, and policymakers dedicated to advancing crop production efficiency and ensuring future food security.
The goal of this research topic is to utilize advanced multi-modeling systems to estimate impacts of biotic or abiotic stress on crop yields or to evaluate the impacts of various cropping management on crop yields. This involves leveraging recent advances in integrating machine learning models with different models to improve the accuracy of predictions and broaden the scale of simulations.
· Develop of integrated modeling system to simulate impacts of various stress factors on crop yields;
· To suggest optimal cropping management to increase crop yields under various environmental conditions;
· To develop integrated models to optimize biotic stress (e.g. disease, insects, and virus) management;
· Simulations of changes in environmental conditions and yields of crops, including grain and horticultural crops, in open-field or greenhouse environments.
Keywords
crop yield enhancement, integrated approaches, sustainable agriculture, precision agriculture, biotechnological innovations, climate resilience
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