In-Line Analysis of Ground Beef Using a Diode Array near Infrared Instrument on a Conveyor Belt

Abstract

In-line monitoring of the proximal composition of ground beef on a conveyer belt has been tested using a near infrared (NIR) reflectance instrument with a diode array detector. Sixty batches of coarsely ground beef were processed under industry conditions and monitored continuously. After removing signals originating from the belt itself, the remaining data were used to make partial least squares models for all samples at two different grinding sizes. The correlation coefficients were in the range 0.93-0.96, while the full cross-validated errors for fat and water were between 1.6 and 2.4%. The corresponding errors for protein were 0.5-0.8%. A forward variable selection method based on jack-knifing yielded similar results. The predictions were generally best for the smallest grinding size. The loading plots showed that there was a high interdependency between calibrations for the different components. Before implementation of the calibrations, they must be re-tested under industry conditions on new independent batches.

Feasibility of NIR interactance hyperspectral imaging for on-line measurement of crude composition in vacuum packed dry-cured ham slices

“…Up to now, NIR technology has been dominated by reflectance instruments measuring one or more locations on the surface of the sample. On-line applications for meat products have traditionally been restricted to ground meat (Hildrum, Nilsen, Westard, & Wahlgren, 2004;Shackelford, Wheeler, & Koohmaraie, 2004). More recently NIR has also been applied to intact meat products.…”

Domain Adaptation for In-Line Allergen Classification of Agri-Food Powders Using Near-Infrared Spectroscopy

“…ML models could be trained on static samples and directly transferred to the production line, but these are unlikely to be accurate when tested on moving materials. Several studies have shown this by focusing on the impact of motion conditions on acquired NIR spectra, for example, for monitoring minced beef [ 14 , 15 ], olive quality [ 16 ], food [ 17 ], and pharmaceutical powders [ 18 , 19 ]. For example, Dixit et al (2016) [ 15 ] noticed increased spectral noise, and Cama-Moncunill et al (2016) [ 17 ] showed changes to the intensity values of peaks under moving conditions.…”

NIR technology for on-line determination of superficial aw and moisture content during the drying process of fermented sausages

“…On-line applications in meat products have been mainly restricted to the determination of several components in ground meat (Hildrum, Nilsen, Westad, & Wahlgren, 2004;Isaksson, Nilsen, Tøgersen, Hammond, & Hildrum, 1996;Shackelford, Wheeler, & Koohmaraie, 2004;Tøgersen, Arnesen, Nilsen, & Hildrum, 2003;Tøgersen, Isaksson, Nilsen, Bakker, & Hildrum, 1999). NIR spectroscopy has been proved to be a useful technique to predict moisture, a w and NaCl in minced fermented sausages (Collell, Gou, Picouet, Arnau, & Comaposada, 2010).…”