Near-Infrared Spectroscopy and Geostatistical Analysis for Modeling Spatial Distribution of Analytical Constituents in Bulk Animal By-Product Protein Meals.

Autor: Adame-Siles JA; 1 Department of Animal Production, Non-Destructive Spectral Sensor Unit, Faculty of Agricultural and Forestry Engineering, University of Córdoba, Córdoba, Spain., Fearn T; 2 Department of Statistical Science, University College London, London, UK., Guerrero-Ginel JE; 1 Department of Animal Production, Non-Destructive Spectral Sensor Unit, Faculty of Agricultural and Forestry Engineering, University of Córdoba, Córdoba, Spain., Garrido-Varo A; 1 Department of Animal Production, Non-Destructive Spectral Sensor Unit, Faculty of Agricultural and Forestry Engineering, University of Córdoba, Córdoba, Spain., Maroto-Molina F; 1 Department of Animal Production, Non-Destructive Spectral Sensor Unit, Faculty of Agricultural and Forestry Engineering, University of Córdoba, Córdoba, Spain., Pérez-Marín D; 1 Department of Animal Production, Non-Destructive Spectral Sensor Unit, Faculty of Agricultural and Forestry Engineering, University of Córdoba, Córdoba, Spain.
Jazyk: angličtina
Zdroj: Applied spectroscopy [Appl Spectrosc] 2017 Mar; Vol. 71 (3), pp. 520-532. Date of Electronic Publication: 2016 Dec 22.
DOI: 10.1177/0003702816683958
Abstrakt: Control and inspection operations within the context of safety and quality assessment of bulk foods and feeds are not only of particular importance, they are also demanding challenges, given the complexity of food/feed production systems and the variability of product properties. Existing methodologies have a variety of limitations, such as high costs of implementation per sample or shortcomings in early detection of potential threats for human/animal health or quality deviations. Therefore, new proposals are required for the analysis of raw materials in situ in a more efficient and cost-effective manner. For this purpose, a pilot laboratory study was performed on a set of bulk lots of animal by-product protein meals to introduce and test an approach based on near-infrared (NIR) spectroscopy and geostatistical analysis. Spectral data, provided by a fiber optic probe connected to a Fourier transform (FT) NIR spectrometer, were used to predict moisture and crude protein content at each sampling point. Variographic analysis was carried out for spatial structure characterization, while ordinary Kriging achieved continuous maps for those parameters. The results indicated that the methodology could be a first approximation to an approach that, properly complemented with the Theory of Sampling and supported by experimental validation in real-life conditions, would enhance efficiency and the decision-making process regarding safety and adulteration issues.
Databáze: MEDLINE