| 光谱学与光谱分析 |
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| Study on Predicting Total Acid Content and Soluble Sugar of Tomato Juice by Near Infrared Optical Fiber Spectrometer Technique |
| ZHANG Bing-fang1, 2, YUAN Li-bo1*, ZHANG Bing-xiu3 |
1. College of Science, Harbin Engineering University, Harbin 150001, China
2. College of Science, Northeast Agricultural University, Harbin 150030, China
3. College of Horticulture, Northeast Agricultural University, Harbin 150030, China |
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Abstract In order to explore a simple, rapid and efficient tomato quality detection method, in the present experiment near infrared spectroscopy and optical fiber sensing technology were applied to quickly measure the nutrition ingredient content in tomato juice samples. The main instrument used in this experiment was near infrared optical fiber spectrometer in a wavelength range from 900 to 2 500 nm, which measured the absorbance of the tomato juice samples; A collection of one hundred and sixty-four tomato juice samples were selected as the standard samples, the spectra and the corresponding chemical value were measured. Partial least squares (PLS) was adopted to establish the mathematical model of the total acid and soluble sugar content in tomato juice samples, and the regression equation was statistically analysed. The total acid in tomato juice prediction correlation coefficient was 0.967, calibration standard deviation (RMSEC) was 0.133, standard error of prediction (RMSEP) was 0.103; the soluble sugar prediction correlation coefficient is 0.976, calibration standard deviation (RMSEC) was 0.463, and the standard error of prediction (RMSEP) was 0.460. The above data achieved better forecasting results, which showed that the method of quantitative analysis of tomato fruit multicomponent content was feasible. The method is rapid, simple and can do multicomponent analysis on the same sample simultaneously. It is a promising sensor and gradually becoming a international research focus in sensor field.
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Received: 2013-04-02
Accepted: 2013-07-21
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Corresponding Authors:
YUAN Li-bo
E-mail: lbyuan@vip.sina.com
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