文献类型：期刊文献

英文题名：Use of infrared thermal imaging to diagnose health of Ammopiptanthus mongolicus in northwestern China

作者：Yuan, Weijie[1,2] Yu, Yi[1] Yue, Yongde[1] Wang, Ji[3] Zhang, Fengchun[4] Dang, Xiaohong[3]

第一作者：Yuan, Weijie;原伟杰

通信作者：Yu, Y[1]

机构：[1]Int Ctr Bamboo & Rattan, Beijing 100102, Peoples R China;[2]Chinese Acad Forestry, Forestry Expt Ctr North China, Beijing 102300, Peoples R China;[3]Inner Mongolia Agr Univ, Coll Ecol & Environm Sci, Hohhot 010019, Peoples R China;[4]Minist Environm Protect, Foreign Econ Cooperat Off, Beijing 100035, Peoples R China

年份：2015

卷号：26

期号：3

起止页码：605-612

外文期刊名：JOURNAL OF FORESTRY RESEARCH

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000358612800007)】；

基金：This work was supported by the national forestry nonprofit industry research projects of China, "Diagnosis of rare and endangered plants Ammopiptanthus mongolicus degradation and research of conservation technology" (No. 201304305).

语种：英文

外文关键词：Photosynthetic parameters; Plant stress; Stomatal conductance; Thermography; Three-temperature (3T) model; Plant-transpiration transfer coefficient

摘要：Population of the rare and endangered species Ammopiptanthus mongolicus (Maxim.) Cheng f. declined rapidly in China's arid region and Central Asia. There is an urgent need to protect this species, which is particularly important in maintaining biodiversity throughout the arid region of northwestern China. By analyzing the infrared thermal images based on plant-transpiration transfer coefficient (h (at)) and photosynthetic parameters, we made quantitative and accurate diagnoses of the plant growth and health status of A. mongolicus. Using an LI-COR6400 photosynthesis system, we measured the net photosynthetic rate (P (n)), stomatal conductance (G (s)), and transpiration rate (T (r)). Infrared thermal images obtained in the field were processed by ENVI4.8 software to calculate surface temperatures of the plant subjects. We found that the plant transpiration transfer coefficient of A. mongolicus was in the order of old plants > young plants > intermediate-aged plants. Declining health levels of young, intermediate, and old plants were divided into three categories: < 0.4, 0.4-0.7, and > 0.7. The coefficient showed a significant negative correlation with T (r), G (s), and P (n), indicating that they can simultaneously reflect the state of plant growth. By establishing h(at) and photosynthetic parameters in regression model Y = a-blnx, we can accurately diagnose plant growth and decline of plant health conditions.