The role of biospectroscopy and chemometrics as enabling technologies for upcycling of raw materials from the food industry.

It is important to utilize the entire animal in meat and fish production to ensure sustainability. Rest raw materials, such as bones, heads, trimmings, and skin, contain essential nutrients that can be transformed into high-value products. Enzymatic protein hydrolysis (EPH) is a bioprocess that can upcycle these materials to create valuable proteins and fats. This paper focuses on the role of spectroscopy and chemometrics in characterizing the quality of the resulting protein product and understanding how raw material quality and processing affect it. The article presents recent developments in chemical characterisation and process modelling, with a focus on rest raw materials from poultry and salmon production. Even if some of the technology is relatively mature and implemented in many laboratories and industries, there are still open challenges and research questions. The main challenges are related to the transition of technology and insights from laboratory to industrial scale, and the link between peptide composition and critical product quality attributes.

Rapid nondestructive determination of edible meat content in crabs (Cancer pagurus) by near-infrared imaging spectroscopy.

This article presents a method by which noncontact near-infrared (NIR) interactance imaging spectroscopy can be applied to determine the amount of edible meat in single live crabs (Cancer pagurus) on a conveyor belt at high speed. The physiology and optical properties of the crabs are presented and discussed in order to explain the requirements for representative spectroscopic sampling. Two different sampling and calibration strategies are discussed. One strategy is based on the extraction of one average NIR spectrum from certain locations in each crab. The other strategy relies on first making a model based on average spectra from a certain location, and then using this model for pixel-wise prediction of the meat content within the crabs. A measure of the predicted distribution of meat is then used for calibration. Reference measurements of meat content were based on an objective quantitative metric of the meat content. The results show that NIR imaging enables on-line grading of the crabs with a correlation of 0.96 with the measured meat content. Due to seasonal variations in the crabs, a piece-wise regression strategy performs slightly better than a global model. Pixel-wise predictions of meat content provide informative images showing the distribution and amount of meat within each crab.

Noncontact salt and fat distributional analysis in salted and smoked salmon fillets using X-ray computed tomography and NIR interactance imaging.

To be able to monitor the salting process of cold smoked salmon, a nondestructive imaging technique for salt analysis is required. This experiment showed that X-ray computed tomography (CT) can be used for nondestructive distributional analysis of NaCl in salmon fillets during salting, salt equilibration, and smoking. The combination of three X-ray voltages (80, 110, and 130 kV) gave the best CT calibrations for NaCl, with a prediction error (root mean square error of cross-validation, RMSECV) of 0.40% NaCl and a correlation (R) of 0.92 between predicted values and reference values. Adding fat predictions based on NIR interactance imaging further improved the NaCl prediction performance, giving RMSECV = 0.34% NaCl and R = 0.95. It was also found that NIR interactance imaging alone was able to predict NaCl contents locally in salted salmon fillets with RMSECV = 0.56% and R = 0.86.