Rapid measurement of total acid content (TAC) in vinegar using near infrared spectroscopy based on efficient variables selection algorithm and nonlinear regression tools

Chen, Quansheng; Ding, Jian Ning; Cai, Jun; Zhao, Jing

doi:10.1016/j.foodchem.2012.05.011

Cited by 80 publications

(25 citation statements)

References 27 publications

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“…Inferior results were obtained with the FNS II (RPD = 7.95) and with the Corona 45 VIS/NIR (RPD = 7.44). Results for the FNS-I were similar to findings reported by Fan et al [7] and by Chen et al [6], who recorded r 2 values of 0.97–0.99 and SECV values of 0.15–0.25, respectively.…”

Section: Resultssupporting

confidence: 90%

Characterizing and Authenticating Montilla-Moriles PDO Vinegars Using Near Infrared Reflectance Spectroscopy (NIRS) Technology

Haba

Arias

Ramírez

et al. 2014

Sensors

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This study assessed the potential of near infrared (NIR) spectroscopy as a non-destructive method for characterizing Protected Designation of Origin (PDO) “Vinagres de Montilla-Moriles” wine vinegars and for classifying them as a function of the manufacturing process used. Three spectrophotometers were evaluated for this purpose: two monochromator instruments (Foss NIRSystems 6500 SY-I and Foss NIRSystems 6500 SY-II; spectral range 400–2,500 nm in both cases) and a diode-array instrument (Corona 45 VIS/NIR; spectral range 380–1,700 nm). A total of 70 samples were used to predict major chemical quality parameters (total acidity, fixed acidity, volatile acidity, pH, dry extract, ash, acetoin, methanol, total polyphenols, color (tonality and intensity), and alcohol content), and to construct models for the classification of vinegars as a function of the manufacturing method used. The results obtained indicate that this non-invasive technology can be used successfully by the vinegar industry and by PDO regulators for the routine analysis of vinegars in order to authenticate them and to detect potential fraud. Slightly better results were achieved with the two monochromator instruments. The findings also highlight the potential of these NIR instruments for predicting the manufacturing process used, this being of particular value for the industrial authentication of traditional wine vinegars.

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Section: Resultssupporting

confidence: 90%

Characterizing and Authenticating Montilla-Moriles PDO Vinegars Using Near Infrared Reflectance Spectroscopy (NIRS) Technology

Haba

Arias

Ramírez

et al. 2014

Sensors

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“…Support vector machine (SVM), proposed by Vapnik, is a promising method to fulfill this goal (Shi et al, 2013). Due to its attractive advantages and excellent performances comparing with other conventional learning algorithms such as back propagation artificial neural network (BP-ANN) and linear discriminant analysis (LDA), SVM has been widely applied in many fields (Bao et al, 2014;Q. Chen, Ding, Cai, & Zhao, 2012).…”

Section: Introductionmentioning

confidence: 99%

Monitoring of fermentation process parameters of Chinese rice wine using attenuated total reflectance mid-infrared spectroscopy

Long

et al. 2015

Food Control

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“…Therefore, the relationship between the changes of chemical components and the nitrogen content is very complicated and tends to exhibit a nonlinear correlation. ELM is a typically nonlinear algorithm, and is stronger than PLS with respect to the level of self-learning and self-adjustment (Chen et al, 2012). Hence, it was useful for improving the prediction performance of the model.…”

Section: Discussionmentioning

confidence: 99%

Determination of lettuce nitrogen content using spectroscopy with efficient wavelength selection and extreme learning machine

Gao¹,

Mao²,

Zhang³

2015

Zemdirbyste-Agriculture

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Measuring the nitrogen content of plants is useful for nitrogen fertilizer management. The aim of this work is to explore the use of spectroscopy for estimating lettuce leaf nitrogen content. Leaf reflectance spectra were measured using a spectroradiometer with a range of 350-2500 nm, and 160 fresh lettuce leaves given five different nitrogen treatments were used for spectra acquisition and total nitrogen determination. Interval partial least squares (iPLS), synergy interval partial least squares (siPLS), and siPLS combined with genetic algorithms (GA-siPLS) were used to select the optimal intervals or variables. Partial least squares (PLS) and extreme learning machine (ELM) methods were used to develop calibration models. One characteristic wavelength region (470-590 nm) using 120 variables was selected by iPLS; four characteristic wavelength regions (440-530, 530-620, 620-710 and 890-980 nm) using 362 variables were selected by siPLS, and 56 wavelength variables were selected by GA-siPLS. Six different regression models were established for nitrogen content by PLS and ELM based on optimal intervals or variables. The results imply that GA-siPLS is an efficient variable selection algorithm and ELM is a successful nonlinear regression tool. Furthermore, GA-siPLS combined with ELM is a feasible method for measuring nitrogen content in lettuce, as it performed better than other models. The optimal results achieved a root mean square error of prediction (RMSEP) = 0.2890% and correlation coefficient Rp = 0.9218.

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Rapid measurement of total acid content (TAC) in vinegar using near infrared spectroscopy based on efficient variables selection algorithm and nonlinear regression tools

Cited by 80 publications

References 27 publications

Characterizing and Authenticating Montilla-Moriles PDO Vinegars Using Near Infrared Reflectance Spectroscopy (NIRS) Technology

Characterizing and Authenticating Montilla-Moriles PDO Vinegars Using Near Infrared Reflectance Spectroscopy (NIRS) Technology

Monitoring of fermentation process parameters of Chinese rice wine using attenuated total reflectance mid-infrared spectroscopy

Determination of lettuce nitrogen content using spectroscopy with efficient wavelength selection and extreme learning machine

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