Author(s)

Shiqi Cui, Yaqiang Sui, Yan Wang

Corresponding Author

Shiqi Cui

Abstract

Agricultural cropping planning in mountainous areas faces challenges such as crop diversity, plot heterogeneity and market uncertainty. To this end, this paper constructs a plot optimization model for the years 2024-2030 for 41 types of crops in rural mountainous areas of North China, with the objective of maximizing net returns. The model is based on planting and yield data in 2023, and considers two market scenarios: overproduction of crops in Scenario 1 is stagnant and unprofitable, and overproduction is sold at a 50% discount in Scenario 2. The model introduces a price-sensitive volume discount mechanism, which maps price reduction to volume reduction through crop sensitivity coefficients to characterize the pattern of change in returns. The model combines a number of agricultural constraints, such as plot suitability, three-year crop rotation, continuous crop limitation, minimum area and concentration, etc., and is optimized year by year using genetic algorithms. The results show that Scenario 1 favors the allocation of high profit crops (e.g., morel mushrooms, elm yellow mushrooms) and realizes about 45.2 million yuan net return, which is suitable for the scenario of limited market capacity; Scenario 2 tends to be high yielding crops (e.g., soybeans, cucumbers) and realizes about 17 million yuan return, which is suitable for the environment of demand growth or discount price stability. The study provides optimization paths for mountain agriculture to adapt to different market scenarios.

Keywords

Genetic Algorithm, Crop Planting Decision, Price Sensitivity, Crop Rotation Optimization, Market Scenario Analysis