Year: 2025
Type: conference-paper
Abstract: The agricultural system in the mountainous areas of North China is rather complex. Here, there exists the phenomenon of fragmented cultivated land and various ecological conflict situations. Therefore, this study proposes a dynamic farming planning model of multiple plot types, hoping to achieve the synergistic improvement effect of the farming plan in terms of time and space from 2024 to 2030. This model comprehensively considers the different characteristics of the plots, involving types such as flat dry land, terraced fields, irrigated land and intelligent greenhouses. Moreover, it combines the requirements of the three-year rotation period of leguminous crops and the restriction of not allowing continuous cropping, thereby forming a decision-making model relying on 0-1 integer programming. The mixed solution was carried out using MATLAB and Python and spatial visualization processing was performed. The research results show that due to the off-season production of the intelligent greenhouse and the traditional open-air plots forming a complementary collaborative mechanism in time, the total revenue of the system expanded to 227,842.5 yuan, which was 8.8% higher than the average distribution scheme. Moreover, the dynamic rotation strategy of leguminous crops has significantly reduced the application of chemical fertilizers by 15%, which effectively confirms the technical approach that can simultaneously improve ecological and economic benefits. This model innovatively combines the spatio-temporal allocation mechanism of facility agriculture with the comprehensive plot constraint system, breaking through the technical bottlenecks such as the shortage in quantifying the spatial heterogeneity of plots and the lack of combination of dynamic crop rotation sequences in the existing agricultural planning models. It creates an extensible farming decision-making framework for resource-constrained areas. To promote the advancement of climate-smart agriculture and the United Nations Sustainable Development Goals, future research will employ dynamic market response mechanisms and integrate remote sensing monitoring and Internet of Things data streams to enhance the stability of models when making decisions in non-steady-state environments.
Authors: Chaoyue Sun, Han Gao, Yujie Zhang
Institution: Dalian Polytechnic University
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDGs: Zero hunger, Life on land
Open Access status: hybrid
OpenAlex ID: W4413520980