Smart Cropping Pattern: A Systematic Study of Sustainable Agriculture Optimization Model

Mushthofa, Mushthofa
Suripin, Suripin
Wulandari, Dyah Ari
Qomaruddin, Mochammad

International Journal of Engineering, Science and Information Technology
Vol 5, No 3 (2025)

Irrigated agriculture accounts for more than 40% of global food production despite covering only about 20% of the world's agricultural land. However, climate change, water constraints, and multisectoral pressures on natural resources demand greater efficiency in the management of agricultural systems. One key strategy is determining optimal cropping patterns under conditions of water and land constraints. This study aims to review mathematical approaches, especially Linear Programming (LP)-based optimization models, in developing efficient and sustainable cropping pattern strategies. This study was conducted through a systematic literature review of 185 scientific articles from the Scopus and ScienceDirect databases in the period 2014–2025. The analysis was carried out using the PRISMA method and visualization of research trends through VOS viewer software. The results of the review indicate that optimization models, especially Linear Programs, have been widely used to develop data-based land and water allocation strategies, considering agronomic, economic, and environmental aspects. The increasing number of publications in the last decade reflects the urgency of this theme and the shift towards quantitative-based decision-making in agricultural systems. This study provides a conceptual and applicative basis for the development of sustainable planting strategies that are adaptive to environmental changes.