Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS)
Joint Authors
Xu, Shengyong
Kuai, Jie
Guo, Cheng
Lu, Kun
Feng, Yaoze
Zhou, Guangsheng
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-20
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The chemical composition of rape stalk is the physiological basis for its lodging resistance.
By taking the advantage of NIRS, we developed a rapid method to determine the content of six key composition without crushing the stalk.
Rapeseed stalks in the mature stage of growth were collected from three cultivation modes over the course of 2 years.
First, we used the near-infrared spectroscope to scan seven positions on the stalk samples and took their average to form the spectral data.
The stalks were then crushed and sieved; then the ratio of carbon and nitrogen, ratio of acid-insoluble lignin and lignin, and the content of soluble sugar and cellulose were determined using the combustion method, weighing method, and colorimetric method, respectively.
The partial least squares regression (PLSR) method was used to establish a prediction model between the spectral data and the chemical measurements, and all models were evaluated by an internal interaction verification and an external independent test set sample.
To improve the accuracy of the model and reduce the computing time, some optimization methods have been applied.
Some outliers were removed, and then the data were preprocessed to determine the best spectral information band and the optimal principal component number.
The results showed that elimination of outliers effectively improved the precision of the prediction model and that no spectral pretreatment method exhibited the highest prediction accuracy.
In summary, the NIRS-based prediction model could facilitate the rapid nondestructive detection in the key components of rapeseed stalk.
American Psychological Association (APA)
Kuai, Jie& Xu, Shengyong& Guo, Cheng& Lu, Kun& Feng, Yaoze& Zhou, Guangsheng. 2019. Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS). Journal of Spectroscopy،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1192179
Modern Language Association (MLA)
Kuai, Jie…[et al.]. Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS). Journal of Spectroscopy No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1192179
American Medical Association (AMA)
Kuai, Jie& Xu, Shengyong& Guo, Cheng& Lu, Kun& Feng, Yaoze& Zhou, Guangsheng. Prediction Model of the Key Components for Lodging Resistance in Rapeseed Stalk Using Near-Infrared Reflectance Spectroscopy (NIRS). Journal of Spectroscopy. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1192179
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1192179