Research On Crop Planting Optimization Based On Yield And Profit Analysis

Abstract

With the development of agricultural modernization, data-driven crop cultivation decision models have performed well in addressing challenges such as climate change, market fluctuations, and resource constraints, becoming an important means of improving yields, optimizing structures, reducing costs, and achieving maximum crop revenue. In this study, we selected corn, pork, soybeans, and live cattle as the futures composite indicators from commodity futures, using data from January, March, June, and the beginning of September 2024, and integrated and differenced the data before using time series models to predict the approximate prices of agricultural products for 2025 and beyond. We combined the Monte Carlo model to provide the optimal cultivation plan, predicting that the estimated profit of vegetable-type farm products in the first quarter of 2025 is 0.88 million yuan. This model is capable of conducting yield predictions for various types of farmland and offering individualized planting strategies in accordance with the specific characteristics of different farmlands.