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Prediction of pig fatty acids composition by near-infrared spectroscopy using neural networks and support vector machine
[post]
2022
unpublished
This work reports on the development and optimization of NIRs technology for the prediction of fatty acids in pig carcasses in the slaughterhouse; use of this technology would enable implementation of a data pretreatment and modelling system. Two years of spectral data from different producers were used to construct a robust model that can predict four fatty acids. For outlier detection of high-dimensional data, an optimized method, the optimized Local Outlier Factor (LOF), was used to remove
doi:10.21203/rs.3.rs-1811254/v1
fatcat:kctcs4saafds7cdcqbcjig3ysy