Liu Xiaogang, Tan Yuting, Dong Jianhua, Wu Jie, Wang Xinle, Sun Zhiqing
Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming, 650500, China.
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China.
Sci Rep. 2025 Jan 2;15(1):8. doi: 10.1038/s41598-024-84073-0.
Arabica coffee, as one of the world's three native coffee species, requires rational planning for its growing areas to ensure ecological and sustainable agricultural development. This study aims to establish a decision-making framework using Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM), with a focus on assessing the habitat suitability of Arabica coffee in Yunnan Province, China. The impacts of climate, topography, soil, and socio-economic factors were considered by selecting 13 criteria through correlation analysis. Indicator weights were determined using the Best-Worst Method (BWM), while weighted processing was conducted using the Base-Criterion Method (BCM). Sensitivity analysis was performed to verify the accuracy and stability of the model. Additionally, several decision models were evaluated to investigate regionalizing Arabica coffee habitats in Yunnan. The results highlighted that minimum temperature during the coldest month is crucial for evaluation purposes. The BWM-GIS model identified suitable areas comprising 13.55% of the total area as most suitable, 27.46% as suitable, and 59.00% as unsuitable, whereas corresponding values for the BCM-GIS model were 9.97%, 30.43%, and 59.59%. Despite employing different decision-making methods, both models yielded similar and consistent results. The suitable areas mainly encompass Dehong, Pu'er, Lincang, Xishuangbanna, Baoshan, southern Chuxiong, eastern Honghe, southern Yuxi, and parts of Wenshan. BWM-GIS achieved an area under curve (AUC) value of 0.891, while BCM-GIS obtained an AUC value of 0.890, indicating the stability and reliability of the models. Among them, the evaluation process of BCM-GIS was simpler and more realistic. Therefore, it has high feasibility and practical value in practical application. The findings from this study provide a significant scientific foundation for optimizing Yunnan Province.
阿拉比卡咖啡作为世界三大原生咖啡品种之一，需要对其种植区域进行合理规划，以确保生态和可持续农业发展。本研究旨在利用地理信息系统（GIS）和多准则决策（MCDM）建立一个决策框架，重点评估中国云南省阿拉比卡咖啡的栖息地适宜性。通过相关性分析选择13个标准，考虑了气候、地形、土壤和社会经济因素的影响。使用最佳-最差方法（BWM）确定指标权重，同时使用基准准则方法（BCM）进行加权处理。进行敏感性分析以验证模型的准确性和稳定性。此外，还评估了几个决策模型，以研究云南省阿拉比卡咖啡栖息地的区域划分。结果表明，最冷月的最低温度对评估至关重要。BWM-GIS模型确定适宜区域占总面积的13.55%为最适宜，27.46%为适宜，59.00%为不适宜，而BCM-GIS模型的相应值分别为9.97%、30.43%和59.59%。尽管采用了不同的决策方法，但两个模型都得出了相似且一致的结果。适宜区域主要包括德宏、普洱、临沧、西双版纳、保山、楚雄南部、红河东部、玉溪南部和文山部分地区。BWM-GIS的曲线下面积（AUC）值为0.891，而BCM-GIS的AUC值为0.890，表明模型的稳定性和可靠性。其中，BCM-GIS的评估过程更简单、更符合实际。因此，它在实际应用中具有较高的可行性和实用价值。本研究结果为优化云南省提供了重要的科学依据。
