The Research of Nondestructive Testing of Apple Acidity Based on Near Infrared Spectroscopy

2012 ◽  
Vol 239-240 ◽  
pp. 243-246
Author(s):  
Ke Zhao ◽  
Hong Wei Si ◽  
Yan Xiong
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Least Squares Method ◽  
Single Point ◽  
Maximum Diameter ◽  
Fiber Optic Probe ◽  
Optic Probe ◽  
Infrared Reflection Spectroscopy ◽  
Partial Least Squares Method

the detection of the apple internal acidity using near infrared reflection spectroscopy is researched in this paper. This paper also elaborates the principle of partial least squares (PLS), and models spectral data by using the partial least squares method. Focuses on the comparison of the single points measurement and multiple points measurement in the Apple’s maximum diameter measurements, gets the following conclusions: a single point spectral scans can not accurately predict the internal acidity of the apple, the experimental precision of the multi-points measurement is higher then the single points measurement. The authors suggest that the measurement of average spectral values by multi-fiber optic probe should be used for the detection of the apple acidity.

N-way partial least squares combined with new self-construction strategy—A promising approach of using near infrared spectral data for quantitative determination of multiple compounds

2019 ◽  
Vol 28 (2) ◽  
pp. 113-121
Author(s):  
Xiang-Zhi Zhang ◽  
Ai-Jun Ma ◽  
Na Feng ◽  
Bao Qiong Li
Keyword(s):  
Quantitative Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Least Squares Method ◽  
Three Dimensional ◽  
Near Infrared Spectra ◽  
Infrared Spectral ◽  
Construction Strategy ◽  
Partial Least Squares Method

Because of the complexity of near infrared spectral data, effective strategies are necessary proposed for accurate quantitative analysis purpose. This work explores a new self-construction strategy for the arrangement of conventional near infrared two-dimensional spectra into new self-constructed three-dimensional spectra, and investigate the feasibility of N-way partial least squares combined with the new self-constructed three-dimensional near infrared spectra for obtaining accurate quantitative determination results. A proof-of-concept model system, the quantitative analysis of four components (moisture, oil, protein, and starch) in corn samples, was applied to evaluate the performance of the proposed strategy. The ability of the newly proposed approach to predict the target compounds was checked with test samples. The established models have good predictive power for the target compounds with acceptable values of Rp (range from 0.82 to 0.997) and RMSEP (range from 0.03 to 0.47). Compared with partial least squares method on pretreated near infrared spectra and N-way partial least squares method on the basis of near infrared self-constructed three-dimensional spectra, the proposed method is competitive.

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