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1. CN106018332 - Near-infrared-spectrum citrus yellow shoot disease field detection method

Office China
Application Number 102016000581372
Application Date 21.07.2016
Publication Number 106018332
Publication Date 12.10.2016
Publication Kind A
IPC
G01N 21/359
GPHYSICS
01MEASURING; TESTING
NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
21Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
17Systems in which incident light is modified in accordance with the properties of the material investigated
25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
35using infra-red light
359using near infra-red light
G01N 21/3563
GPHYSICS
01MEASURING; TESTING
NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
21Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
17Systems in which incident light is modified in accordance with the properties of the material investigated
25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
35using infra-red light
3563for analysing solids; Preparation of samples therefor
CPC
G01N 21/359
GPHYSICS
01MEASURING; TESTING
NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
21Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
17Systems in which incident light is modified in accordance with the properties of the material investigated
25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
35using infra-red light
359using near infra-red light
G01N 21/3563
GPHYSICS
01MEASURING; TESTING
NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
21Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
17Systems in which incident light is modified in accordance with the properties of the material investigated
25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
35using infra-red light
3563for analysing solids; Preparation of samples therefor
Applicants SOUTH CHINA AGRICULTURAL UNIVERSITY
Inventors ZENG XINNIAN
CHEN DONGMEI
WANG HUATANG
Title
(EN) Near-infrared-spectrum citrus yellow shoot disease field detection method
(ZH) 一种柑桔黄龙病的近红外光谱田间检测方法
Abstract
(EN)
The invention discloses a near-infrared-spectrum citrus yellow shoot disease field detection method. The field detection method includes the following steps that S1, a standard sample spectrum set is established: a miniature portable near-infrared spectrometer is adopted to directly detect and read near-infrared spectroscopy data of citrus plant leaves infected with citrus yellow shoot disease bacteria and citrus plant leaves without the citrus yellow shoot disease bacteria in a field; S2, a qualitative classification judgment model is established: the near-infrared spectroscopy data in the step S1 are subjected to correction and preprocessing, then characteristic values of their near-infrared spectroscopy are respectively extracted, and then an optimal PLS-DA qualitative classification judgment model is obtained through training of a training set and verification of a verification set; S3, qualitative judgment is conducted on unknown samples: the optimal PLS-DA qualitative classification judgment model established in the step S2 is used for directly distinguishing whether citrus leaf samples to be detected have infected with citrus yellow shoot diseases or not in the field, only 3-5 leaves are needed to be scanned in the field for a single plant, and rapid real-time definite diagnosis making can be achieved only by consuming 1-2 minutes. The method can be used for rapid diagnosis of the citrus yellow shoot disease in the field, is simple and convenient to operate, rapid and accurate, does not produce any damage to the samples and is friendly to the environment.

(ZH)
本发明公开了一种柑桔黄龙病的近红外光谱田间检测方法,所述检测应用方法包括如下步骤:S1.标准样品光谱集的建立:采用微型便携式近红外光谱仪于田间直接探测读取感染柑桔黄龙病病菌和不带黄龙病病菌柑桔植株叶片的近红外光谱学数据;S2.定性分类判别模型的建立:将S1中的近红外光谱学数据进行校正和预处理后,分别提取其近红外光谱学的特征值,经训练集训练和验证集验证后得到最优的PLS‑DA定性分类判别模型;S3.未知样品的定性判别:用S2建立的最优的PLS‑DA定性分类判别模型于田间直接区分待测柑桔叶片样本是否已感染柑桔黄龙病,单一植株仅需现场扫描3~5个叶片,耗时仅需1~2 min,便可实现快速实时确诊。本发明方法可进行柑桔黄龙病的田间快速诊断,操作简便,快速准确,对样本不产生任何损伤,并对环境友好。