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Monitoring cotton (Gossypium hirsutum L.) leaf ion content and leaf water content in saline soil with hyperspectral reflectance

文献类型: 外文期刊

作者: Zhang, Lei 1 ; Zhou, Zhiguo 1 ; Zhang, Guowei 1 ; Meng, Yali 1 ; Chen, Binglin 1 ; Wang, Youhua 1 ;

作者机构: 1.Key Laboratory of Crop Growth Regulation, Ministry of Agriculture, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China;State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Anyang 455100, Henan, People’s Republic of China

2.Key Laboratory of Crop Growth Regulation, Ministry of Agriculture, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China

关键词: cotton;saline soil;hyperspectral reflectance;ion content;leaf water content;monitoring model

期刊名称:EUROPEAN JOURNAL OF REMOTE SENSING ( 影响因子:3.647; 五年影响因子:3.489 )

ISSN: 2279-7254

年卷期: 2014 年 47 卷

页码:

收录情况: SCI

摘要: The objectives of this study were to establish quantitative models for monitoring the leaf ion and water content under saline conditions. The best spectral indices for estimating leaf ion content and leaf water content were found to be normalized difference spectral indices (NDSI (R-1340, R-2306)), ratio spectral indices (RSI (R-2306, R-1347)) for K+, NDSI (R-1346, R-2276), RSI (R-2276, R-1343) for Na+, NDSI (R-1380, R-2307), RSI (R-2306, R-1350) for Ca2+; NDSI (R-1200, R-2211), RSI (R-2202, R-1361) for Mg2+; NDSI (R-1300, R-2250), RSI (R-2264, R-1335) for Cl-; NDSI (R-1154, R-2317), RSI (R-2317, R-1154) for SO42- and NDSI (R-1222, R-2264), RSI (R-2264, R-1321) for RWC, respectively. The regression models based on the above spectral indices were formulated with R-2 greater than 0.46. The high fit between the measured and estimated values indicate that the present models based on RSI could be used to estimate leaf ion and water content feasibly under saline conditions.

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