Hong Yongcustomizable Edible Oil Refining Systems For Diverse Applications/machine De Raffinage Du Petrole

Hong Yongcustomizable Edible Oil Refining Systems For Diverse Applications/machine De Raffinage Du Petrole
                                               
                                               
                                               
                                               
  • Hong Yongcustomizable Edible Oil Refining Systems For Diverse Applications/machine De Raffinage Du Petrole
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  • Can machine learning detect adulterated edible oils?
  • We described a protocol that combined machine learning algorithms with Raman spectroscopy or fatty acid composition to characterize edible oils. Our method yielded a high accuracy in classifying edible oil types and, accordingly, is an effective means of detecting adulterated oils.
  • Can edible oil-based nanomaterials be used in industrial applications?
  • Before realizing the industrial application of vegetable oils, the abovementioned problems need to be solved in a timely and effective manner. In addition, the preparation of edible oil-based nanomaterials and their synergy with other active ingredients are a focus of future research.
  • What is the best machine learning algorithm for edible oil classification?
  • Our approach is faster, more accurate, and provides a clear oil classification compared to standard PCA methods. The PCA with RF model was found to be the best performing machine learning algorithm for the classification of edible oils based on Raman spectra.
  • How is machine learning used in edible oil testing?
  • Machine learning algorithms were implemented in the Python 3.5.7 programming environment. To create an equally distributed training and test data set for each edible oil type, four brands from each of the ten oil types listed in S. Table 1 (only #1 to #40) were used for the machine learning and deep learning study.
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Small Scale Edible Oil Refining Machine Crude in Lesotho
                                               
                                               
                                               
                                               
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