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

Abstract

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.