In-line Raman spectroscopy for characterization of an industrial poultry raw material stream.

In this work, we evaluated the feasibility of Raman spectroscopy as an in-line raw material characterization tool for industrial process control of the hydrolysis of poultry rest raw material. We established calibrations (N = 59) for fat, protein, ash (proxy for bone) and hydroxyproline (proxy for collagen) in ground poultry rest raw material. Calibrations were established in the laboratory using poultry samples with high compositional variation. Samples were measured using a wide area illumination Raman probe at varying working distance (6 cm, 9 cm, 12 cm) and probe tilt angle (0°, 30°) to mimic expected in-line variations in the measurement situation. These moderate variations did not significantly affect performance for any analytes. The obtained calibrations were tested in-line with continuous measurements of the ground poultry by-product stream at a commercial hydrolysis facility over the course of two days. Measurements were acquired under demanding conditions, e.g. large variations in working distance. Reasonable estimates of compositional trends were obtained. Validation samples (N = 19) were also reasonably well predicted, with RMSEP _corr  = [0.14, 1.37, 2.36, 1.51]% for hydroxyproline, protein, fat and ash, respectively. However, there were indications that further calibration development and robustification of pre-processing would be advantageous, particularly with respect to hydroxyproline and protein models. It is the authors' impression that with such efforts, potentially in combination with development of practical measurement setup, the use of Raman spectroscopy as a process control tool for the hydrolysis of poultry rest raw materials is within reach.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Tiril Aurora Lintvedt reports equipment, drugs, or supplies was provided by MarqMetrix Inc.
(Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)