Shao Yang, Ye Dan, Ouyang Zhen, Huang Lu-Qi, Peng Hua-Sheng, Zhang Xiao-Bo, Zhu Shou-Dong, Yu Yi-Fan, Jiang Fang-Rong
School of Pharmacy, Jiangsu University, Zhenjiang 212013, China.
National Resource Centre of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Zhongguo Zhong Yao Za Zhi. 2016 Sep;41(17):3169-3175. doi: 10.4268/cjcmm20161709.
In this study, ecological factors, occurrence records, the essential oil components content were used to predict the potential geographical distribution and quality division of Mentha haplocalyx in China based on the MaxEnt modeling and geographic information system(GIS). The AUC of ROC curve was above 0.950,indicating that the predictive results with the maximum model were highly precise. The results showed that the main environmental factors determining the potential distribution were annual average precipitation (the contribution rate, 45.87%), mean temperature of wettest quarter (11.92%), mean temperature of warmest quarter (7.84%), average monthly precipitation of May (6.80%), standard deviation of seasonal temperature variation (4.42%), mean temperature of the coldest quarter (3.47%) and altitude (2.92%). The environmental variables in the highly potential areas were determined as annual average precipitation around [530,1 465] mm, mean temperature of wettest quarter around [24.5,29] ℃, mean temperature of the warmest quarter around [25.5,29] ℃, average monthly precipitation of May around [67,133] mm, standard deviation of temperature seasonal change around [8 333,9 643], mean temperature of the coldest quarter around [1.7,8.3] ℃ and the altitude around [0,165] mm. The best quality distribution of M. haplocalyx was mainly located in Jiangsu, Anhui, Shandong, Zhejiang and Heilongjiang. The zoning results basically coincide with the actual situation. The quality division of M. haplocalyx can be used for providing a scientific basis for selection of artificial planting base and guidance of its production.
本研究基于最大熵模型(MaxEnt)和地理信息系统(GIS),利用生态因子、发生记录、精油成分含量来预测中国薄荷的潜在地理分布和质量区划。ROC曲线的AUC大于0.950,表明最大熵模型的预测结果具有很高的精度。结果表明,决定潜在分布的主要环境因子为年平均降水量(贡献率45.87%)、最湿润季度平均温度(11.92%)、最温暖季度平均温度(7.84%)、5月平均月降水量(6.80%)、季节温度变化标准差(4.42%)、最寒冷季度平均温度(3.47%)和海拔(2.92%)。高潜力区域的环境变量确定为年平均降水量在[530,1465]毫米左右、最湿润季度平均温度在[24.5,29]℃左右、最温暖季度平均温度在[25.5,29]℃左右、5月平均月降水量在[67,133]毫米左右、温度季节变化标准差在[8333,9643]、最寒冷季度平均温度在[1.7,8.3]℃左右以及海拔在[0,165]毫米左右。薄荷的最佳质量分布主要位于江苏、安徽、山东、浙江和黑龙江。区划结果基本与实际情况相符。薄荷的质量区划可为人工种植基地的选择及其生产指导提供科学依据。