Prediction of fatty acid content in sheep milk by Mid-Infrared spectrometry with a selection of wavelengths by Genetic Algorithms
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- 作者：Marco Careddaa ; Margherita Addisa ; Ignazio Ibbab ; Riccardo Leardic ; Maria Francesca Scintua ; Giovanni Pireddaa ; Gavino Sannad ; sanna@uniss.it" class="auth_mail" title="E-mail the corresponding author
- 关键词：Sheep milk ; Fatty acids ; Mid-Infrared spectroscopy ; Genetic Algorithms ; Partial Least Square regression
- 刊名：LWT - Food Science and Technology
- 出版年：2016
- 出版时间：January 2016
- 年：2016
- 卷：65
- 期：Complete
- 页码：503-510
- 全文大小：1217 K
文摘
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Predictive models for fatty acids in sheep milk by FT-MIR spectroscopy were built.
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PLS regressions were computed between milk spectra and fatty acid reference values.
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Genetic Algorithms were used to select the informative spectral subsets.
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Validated models show low prediction errors in comparison to reference values.
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Validated models may be useful as evaluation tools for sheep milk payment purposes.