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Determination of the oxidative stability of olive oil using an integrated system based on dielectric spectroscopy and computer vision

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Information Processing in Agriculture 2019年第1期6卷 20-25页

作者： Alireza Sanaeifar Abdolabbas Jafari Department of Biosystems Engineering Shiraz UniversityShirazIran Lincoln Agritech Ltd. Lincoln UniversityLincolnNew Zealand

During storage,olive oil may suffer degradation leading to an inferior quality level when purchased and *** stability is one of the most important parameters for maintaining the quality of olive oil,which affects its acceptability and market *** current methods of predicting the oxidative stability of edible oils are costly and *** aim of the present research is to demonstrate the use of dielectric spectroscopy integrated with computer vision for determining the oxidative stability index(OSI)of olive *** most effective features were selected from the extracted dielectric and visual features for each olive oil *** machine learning techniques were employed to process the raw data to develop an oxidative stability prediction algorithm,including artificial neural network(ANN),support vector machine(SVM)and multiple linear regression(MLR).The predictive models showed a great agreement with the results obtained by the Rancimat instrument that was used as a reference *** best result for modelling the oxidative stability of olive oil was obtained using SVM technique with the R-value of *** can be concluded that this new approach may be utilized as a perfect replacement for quicker and cheaper assessment of olive oil oxidation.

关键词： Computer vision Dielectric spectroscopy Olive oil oxidative stability index

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