Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric Algorithms
In this work, we quantified goat milk powder adulteration by adding urea, melamine, and starch individually and simultaneously, with the utilization of near infrared (NIR) spectroscopy coupled with chemometrics. For single-adulterant samples, the successive projections algorithm (SPA) selected three...
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| Format: | Article |
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MDPI AG
2022-03-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/12/3/434 |
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| author | Xin Zhao Yunpeng Wang Xin Liu Hongzhe Jiang Zhilei Zhao Xiaoying Niu Chunhua Li Bin Pang Yanlei Li |
| author_facet | Xin Zhao Yunpeng Wang Xin Liu Hongzhe Jiang Zhilei Zhao Xiaoying Niu Chunhua Li Bin Pang Yanlei Li |
| author_sort | Xin Zhao |
| collection | DOAJ |
| description | In this work, we quantified goat milk powder adulteration by adding urea, melamine, and starch individually and simultaneously, with the utilization of near infrared (NIR) spectroscopy coupled with chemometrics. For single-adulterant samples, the successive projections algorithm (SPA) selected three, three, and four optimal wavelengths for urea, melamine, and starch, respectively. Models were built based on partial least squares regression (PLS) and the selected wavelengths, exhibiting good predictive ability with an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>R</mi><mi>p</mi><mn>2</mn></msubsup></mrow></semantics></math></inline-formula> above 0.987 and an RMSEP below 0.403%. For multiple-adulterants samples, PLS2 and multivariate curve resolution alternating least squares (MCR-ALS) were adopted to build the models to quantify the three adulterants simultaneously. The PLS2 results showed adequate precision and results better than those of MCR-ALS. Except for urea, MCR-ALS models presented good predictive results for milk, melamine, and starch concentrations. MCR-ALS allowed detection of adulteration with new and unknown substitutes as well as the development of models without the need for the usage of a large data set. |
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| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-09T20:13:22Z |
| publishDate | 2022-03-01 |
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| series | Agriculture |
| spelling | doaj.art-2a9a17b194cc4f99b8574602092dfb7a2023-11-24T00:06:17ZengMDPI AGAgriculture2077-04722022-03-0112343410.3390/agriculture12030434Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric AlgorithmsXin Zhao0Yunpeng Wang1Xin Liu2Hongzhe Jiang3Zhilei Zhao4Xiaoying Niu5Chunhua Li6Bin Pang7Yanlei Li8College of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaCollege of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaCollege of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaCollege of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaCollege of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaCollege of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaCollege of Quality and Technical Supervision, Hebei University, Baoding 071002, ChinaIn this work, we quantified goat milk powder adulteration by adding urea, melamine, and starch individually and simultaneously, with the utilization of near infrared (NIR) spectroscopy coupled with chemometrics. For single-adulterant samples, the successive projections algorithm (SPA) selected three, three, and four optimal wavelengths for urea, melamine, and starch, respectively. Models were built based on partial least squares regression (PLS) and the selected wavelengths, exhibiting good predictive ability with an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>R</mi><mi>p</mi><mn>2</mn></msubsup></mrow></semantics></math></inline-formula> above 0.987 and an RMSEP below 0.403%. For multiple-adulterants samples, PLS2 and multivariate curve resolution alternating least squares (MCR-ALS) were adopted to build the models to quantify the three adulterants simultaneously. The PLS2 results showed adequate precision and results better than those of MCR-ALS. Except for urea, MCR-ALS models presented good predictive results for milk, melamine, and starch concentrations. MCR-ALS allowed detection of adulteration with new and unknown substitutes as well as the development of models without the need for the usage of a large data set.https://www.mdpi.com/2077-0472/12/3/434goat milk powderadulterationnear infrared spectroscopypartial least squares regressionmultivariate curve resolution alternating least squares |
| spellingShingle | Xin Zhao Yunpeng Wang Xin Liu Hongzhe Jiang Zhilei Zhao Xiaoying Niu Chunhua Li Bin Pang Yanlei Li Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric Algorithms Agriculture goat milk powder adulteration near infrared spectroscopy partial least squares regression multivariate curve resolution alternating least squares |
| title | Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric Algorithms |
| title_full | Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric Algorithms |
| title_fullStr | Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric Algorithms |
| title_full_unstemmed | Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric Algorithms |
| title_short | Single- and Multiple-Adulterants Determinations of Goat Milk Powder by NIR Spectroscopy Combined with Chemometric Algorithms |
| title_sort | single and multiple adulterants determinations of goat milk powder by nir spectroscopy combined with chemometric algorithms |
| topic | goat milk powder adulteration near infrared spectroscopy partial least squares regression multivariate curve resolution alternating least squares |
| url | https://www.mdpi.com/2077-0472/12/3/434 |
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