Authentication of Organic Feed by Near-Infrared Spectroscopy Combined with Chemometrics: A Feasibility Study
| Autor: | S.M. van Ruth, Ana Garrido-Varo, Alba Tres, J.C. van der Veer, M.D. Perez-Marin |
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| Rok vydání: | 2012 |
| Předmět: |
Organic product
spectra compound feedingstuffs Analytical chemistry oil Models Biological 01 natural sciences Chemometrics meat 0404 agricultural biotechnology reflectance spectroscopy Fingerprint Resampling Partial least squares regression samples Least-Squares Analysis BU Microbiological & Chemical Food Analysis Netherlands Second derivative Mathematics 2. Zero hunger Spectroscopy Near-Infrared business.industry Fatty Acids 010401 analytical chemistry orthogonal signal correction Discriminant Analysis Pattern recognition 04 agricultural and veterinary sciences General Chemistry RIKILT B&T Authenticiteit en Nutrienten Linear discriminant analysis Animal Feed 040401 food science 0104 chemical sciences products classification Binary classification ingredient composition Feasibility Studies Food Organic BU Microbiologische & Chemische Voedselanalyse Artificial intelligence General Agricultural and Biological Sciences business |
| Zdroj: | Journal of Agricultural and Food Chemistry, 60(33), 8129-8133 Journal of Agricultural and Food Chemistry 60 (2012) 33 |
| ISSN: | 1520-5118 0021-8561 |
| Popis: | Organic products tend to retail at a higher price than their conventional counterparts, which makes them susceptible to fraud. In this study we evaluate the application of near-infrared spectroscopy (NIRS) as a rapid, cost-effective method to verify the organic identity of feed for laying hens. For this purpose a total of 36 organic and 60 conventional feed samples from The Netherlands were measured by NIRS. A binary classification model (organic vs conventional feed) was developed using partial least squares discriminant analysis. Models were developed using five different data preprocessing techniques, which were externally validated by a stratified random resampling strategy using 1000 realizations. Spectral regions related to the protein and fat content were among the most important ones for the classification model. The models based on data preprocessed using direct orthogonal signal correction (DOSC), standard normal variate (SNV), and first and second derivatives provided the most successful results in terms of median sensitivity (0.91 in external validation) and median specificity (1.00 for external validation of SNV models and 0.94 for DOSC and first and second derivative models). A previously developed model, which was based on fatty acid fingerprinting of the same set of feed samples, provided a higher sensitivity (1.00). This shows that the NIRS-based approach provides a rapid and low-cost screening tool, whereas the fatty acid fingerprinting model can be used for further confirmation of the organic identity of feed samples for laying hens. These methods provide additional assurance to the administrative controls currently conducted in the organic feed sector. |
| Databáze: | OpenAIRE |
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