Portable spectroscopy system determination of acid value in peanut oil based on variables selection algorithms

The acid value (AV) is an essential parameter for the quality and safety evaluation of peanut oil. In this study, for efficiently and real-time monitor of acid value (AV) in peanut oil, a portable spectroscopy system was first developed and combined with variables selection algorithms to measure aci...

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Veröffentlicht in:Measurement : journal of the International Measurement Confederation 2017-06, Vol.103, p.179-185
Hauptverfasser: Yang, Mingxiu, Chen, Quansheng, Kutsanedzie, Felix Y.H., Yang, Xiaojing, Guo, Zhiming, Ouyang, Qin
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container_title Measurement : journal of the International Measurement Confederation
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creator Yang, Mingxiu
Chen, Quansheng
Kutsanedzie, Felix Y.H.
Yang, Xiaojing
Guo, Zhiming
Ouyang, Qin
description The acid value (AV) is an essential parameter for the quality and safety evaluation of peanut oil. In this study, for efficiently and real-time monitor of acid value (AV) in peanut oil, a portable spectroscopy system was first developed and combined with variables selection algorithms to measure acid value (AV) in peanut oils. Developed portable spectroscopy system was applied for transmittance spectrum data acquisition after which partial least squares (PLS) and several variables selection algorithms synergy interval partial least square (Si-PLS), genetic algorithm (GA), genetic algorithm combined with Si-PLS namely GA-Si-PLS, ant colony optimization (ACO) algorithms were systemically studied and comparatively used for modeling. The performances of these models were evaluated according to correlation coefficients squared in the prediction set (RP) and root mean square error of prediction (RMSEP). The results showed that the variables selection methods could select more significant variables and improve the model performance, especially for the GA-Si-PLS model with the best performance than other variables selection algorithms with RP=0.9426 and RMSEP=0.2980. Finally, the paper draws a conclusion that the developed portable spectroscopy system combined with a suitable variables selection methods could be used for the simultaneous and rapid measurement of acid value in peanut oil.
doi_str_mv 10.1016/j.measurement.2017.02.037
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In this study, for efficiently and real-time monitor of acid value (AV) in peanut oil, a portable spectroscopy system was first developed and combined with variables selection algorithms to measure acid value (AV) in peanut oils. Developed portable spectroscopy system was applied for transmittance spectrum data acquisition after which partial least squares (PLS) and several variables selection algorithms synergy interval partial least square (Si-PLS), genetic algorithm (GA), genetic algorithm combined with Si-PLS namely GA-Si-PLS, ant colony optimization (ACO) algorithms were systemically studied and comparatively used for modeling. The performances of these models were evaluated according to correlation coefficients squared in the prediction set (RP) and root mean square error of prediction (RMSEP). The results showed that the variables selection methods could select more significant variables and improve the model performance, especially for the GA-Si-PLS model with the best performance than other variables selection algorithms with RP=0.9426 and RMSEP=0.2980. 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In this study, for efficiently and real-time monitor of acid value (AV) in peanut oil, a portable spectroscopy system was first developed and combined with variables selection algorithms to measure acid value (AV) in peanut oils. Developed portable spectroscopy system was applied for transmittance spectrum data acquisition after which partial least squares (PLS) and several variables selection algorithms synergy interval partial least square (Si-PLS), genetic algorithm (GA), genetic algorithm combined with Si-PLS namely GA-Si-PLS, ant colony optimization (ACO) algorithms were systemically studied and comparatively used for modeling. The performances of these models were evaluated according to correlation coefficients squared in the prediction set (RP) and root mean square error of prediction (RMSEP). The results showed that the variables selection methods could select more significant variables and improve the model performance, especially for the GA-Si-PLS model with the best performance than other variables selection algorithms with RP=0.9426 and RMSEP=0.2980. Finally, the paper draws a conclusion that the developed portable spectroscopy system combined with a suitable variables selection methods could be used for the simultaneous and rapid measurement of acid value in peanut oil.</abstract><cop>London</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.measurement.2017.02.037</doi><tpages>7</tpages></addata></record>
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subjects Acid value
Acids
Algorithms
Ant colony optimization
Correlation coefficients
Determination
Genetic algorithms
Least squares
Mathematical models
Peanut oil
Peanuts
Portability
Portable NIR spectroscopy system
Quality control
Spectrum analysis
Variables selection algorithms
Vegetable oils
title Portable spectroscopy system determination of acid value in peanut oil based on variables selection algorithms
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