文献类型： 外文期刊

第一作者： Bai Tie-cheng

作者： Bai Tie-cheng;Mercatoris, Benoit;Bai Tie-cheng;Wang Tao;Chen You-qi

作者机构： Univ Liege, Gembloux Agrobio Tech, Biosyst Dynam & Exchanges, TERRA Teaching & Res Ctr, B-5030 Gembloux, Belgium;Tarim Univ, Coll Informat Engn, Alaer 843300, Peoples R China;Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China

关键词： Leaf moisture content; Near-infrared spectrum; Scattering noise; Pretreatment methods; Multiple scatter correction

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 2020影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2019 年 39 卷 4 期

页码：

收录情况： SCI

摘要： Precision irrigation for jujube crop in southern Xinjiang, China, is underlying to optimize the water use in such a drought-affected region. Water stress can be remotely assessed by evaluating the leaf moisture content using spectroscopy. These measurements are however affected by the presence of coarse sand and dust of the leaves induced by dry climates. This paper studied different methods to correct the spectral data in order to reduce the scattering noise with a baseline induced by such a jujube leaf covering. The reflectance of 120 leaf samples were measured by means of a near-infrared spectrometer (1 000 similar to 1 800 nm) and their moisture content was obtained by conventional drying method. The original reflectance spectrums were pre-processed by the normalization method, the moving smoothing method, the Savitzky-Golay (SG) convolution smoothing method, the SG first derivative method, the standard normal variables (SNV) method and the multiple scatter correction (MSC) method. The results of these different methods were compared and analyzed by means of partial leastsquares regressions (PLSR) allowing selecting sensitive spectral bands and establishing prediction models. The results showed that a significant reflectance peak related to the water content of the jujube leaves was located at 1 443 nm and that a local minimum of reflectance occurred at 1 661 nm. The predicition model based on the MSC method presented the best scattering noise reduction. The model performances were R-2 = 0. 750 4, RMSEP=-0. 034 3 and RMSEPCV-=0. 021 5. The five characteristic wavelengths were 1 002, 1 383, 1 411, 1 443 and 1 661 nm. In this experiment, the MSC method had a good ability to reduce the scattering noise generated by sand and dust covering. The preprocessing improved the selection ability of characteristic wavelengths and the accuracy of the prediction model. The results can therefore provide an effective detection method for the jujube leaf water in the sandy and dusty area of Southern Xinjiang, China.

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