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30 May 2022 Open-source Python software for the implementation of multivariate and machine learning algorithms for quantitative and qualitative NIRS analysis of virgin olive oil
Mar Garrido-Cuevas, Ana Garrido-Varo, Dolores C. Pérez-Marín
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Proceedings Volume PC12120, Sensing for Agriculture and Food Quality and Safety XIV; PC1212004 (2022) https://doi.org/10.1117/12.2620102
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States
Abstract
Software tools for chemometric analysis of NIRS data have existed since the first NIRS instruments appeared on the market in the late 1970s. Generally, these software appear attached to a certain instrumentation. Recently, some works have started to use open-source software, such as R and Python, but the development status is still in its infancy, particularly in the case of the latter. This work tries to generate information on the potential of the open-source Python software for the implementation of multivariate algorithms and signal pre-treatment methods for the quantitative and qualitative NIRS analysis of olive oils.
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Mar Garrido-Cuevas, Ana Garrido-Varo, and Dolores C. Pérez-Marín "Open-source Python software for the implementation of multivariate and machine learning algorithms for quantitative and qualitative NIRS analysis of virgin olive oil", Proc. SPIE PC12120, Sensing for Agriculture and Food Quality and Safety XIV, PC1212004 (30 May 2022); https://doi.org/10.1117/12.2620102
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KEYWORDS
Near infrared spectroscopy
Machine learning
Statistical analysis
Chemometrics
Computer programming
Computer programming languages
Linear filtering
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