Research on Crop Planting Strategies Based on Market Factors

This study seeks to investigate optimal agricultural planting strategies in northern China by refining the planting structure to enhance profitability and mitigate the effects of natural risks on crop production. The primary objective is to attain the judicious distribution of agricultural resources and optimize economic gains. This study develops a crop cultivation strategy model with multi-objective linear programming. To improve planting profitability, it thoroughly examines the substitutability and complementarity across crops and utilizes multiple linear regression to refine model constraints, thus alleviating the negative impacts of natural risks on crop yields. The findings indicate that the refined planting strategy enhances annual revenues by 60.93% relative to the pre-optimization condition. Furthermore, the annual profit trajectory under the optimized plan remains remarkably aligned with the original strategy, affirming the model's efficacy and dependability. This paper presents a novel method for optimizing crop planting methods by merging multiple linear regression with multi-objective linear programming, hence improving the model's relevance in practical agricultural decision-making.

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Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2025-03-25
DOI
https://doi.org/10.54097/k6k9wh37
Primary Topic
Irrigation Practices and Water Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Crop Planting Strategies Based on Market Factors

Siyu Hou, Yubo Tao, Hao Gou
Highlights in Science Engineering and Technology
Irrigation Practices and Water Management
article

Research on Crop Planting Strategies Based on Market Factors

Siyu Hou, Yubo Tao, Hao Gou
article en

Abstract

This study seeks to investigate optimal agricultural planting strategies in northern China by refining the planting structure to enhance profitability and mitigate the effects of natural risks on crop production. The primary objective is to attain the judicious distribution of agricultural resources and optimize economic gains. This study develops a crop cultivation strategy model with multi-objective linear programming. To improve planting profitability, it thoroughly examines the substitutability and complementarity across crops and utilizes multiple linear regression to refine model constraints, thus alleviating the negative impacts of natural risks on crop yields. The findings indicate that the refined planting strategy enhances annual revenues by 60.93% relative to the pre-optimization condition. Furthermore, the annual profit trajectory under the optimized plan remains remarkably aligned with the original strategy, affirming the model's efficacy and dependability. This paper presents a novel method for optimizing crop planting methods by merging multiple linear regression with multi-objective linear programming, hence improving the model's relevance in practical agricultural decision-making.

Highlights in Science Engineering and TechnologyVol. 131
Openalex Percentile: Top 93%
Irrigation Practices and Water Management
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