Improvement of Oil Valorization Extracted from Fish By-Products Using a Handheld near Infrared Spectrometer Coupled with Chemometrics

Abstract

A handheld near infrared (NIR) spectrometer was used for on-site determination of the fatty acids (FAs) composition of industrial fish oils from fish by-products. Partial least square regression (PLSR) models were developed to correlate NIR spectra with the percentage of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs) and, among them, omega-3 (ω-3) and omega-6 (ω-6) FAs. In a first step, the data were divided into calibration validation datasets, obtaining good results regarding R2 values, root mean square error of prediction (RMSEP) and bias. In a second step, all these data were used to create a new calibration, which was uploaded to the handheld device and tested with an external validation set in real time. Evaluation of the external test set for SFAs, MUFAs, PUFAs and ω-3 models showed promising results, with R2 values of 0.98, 0.97, 0.97 and 0.99; RMSEP (%) of 0.94, 1.71, 1.11 and 0.98; and bias (%) values of −0.78, −0.12, −0.80 and −0.67, respectively. However, although ω-6 models achieved a good R2 value (0.95), the obtained RMSEP was considered high (2.08%), and the bias was not acceptable (−1.76%). This was corrected by applying bias and slope correction (BSC), obtaining acceptable values of R2 (0.95), RMSEP (1.09%) and bias (−0.05%). This work goes a step further in the technology readiness level (TRL) of handheld NIR sensor solutions for the fish by-product recovery industry.

Application of Chromatographic and Spectroscopic-Based Methods for Analysis of Omega-3 (ω-3 FAs) and Omega-6 (ω-6 FAs) Fatty Acids in Marine Natural Products

“…Unsupervised pattern recognition of PCA and supervised pattern recognition of linear discriminant analysis (LDA) and Soft Independent Modeling of Class Analogies (SIMCA) have been generated to investigate the potential substitution of valuable fish species with cheaper materials [ 18 ]. A multivariate calibration technique of partial least squares regression (PLSR) has been successfully developed to build prediction models for determining fatty acids content (%) from eight fish oil samples [ 19 ]. Figure 3 presents the scheme of chemometrics application for analyzing omega-3 or omega-6 fatty acids using spectroscopic and chromatographic-based methods.…”

The Potential of Acorn Extract Treatment on PUFAs Oxidative Stability: A Case Study on Fish Cooking Wastewater

“…Estimates suggest that for some types of fish and processing methods, 70% of the processed fish results in byproducts [ 10 , 11 ]. These byproducts, encompassing bone, frame, skin, internal organs, and muscle, represent a rich reservoir of PUFAs.…”

“…These byproducts, encompassing bone, frame, skin, internal organs, and muscle, represent a rich reservoir of PUFAs. These byproducts hold high potential in numerous sectors, particularly the food industry [ 2 , 4 , 10 ]. The waste generated during the fish canning process has also been recognized as a rich source of countless bioactive compounds such as lipids, proteins, bio-polymers, and minerals.…”

“…Fish cooking wastewater represents a source of significant amounts of proteins and Ω-3 [ 4 , 12 ]. Valorizing these byproducts aligns with the principles of a circular economy approach and helps mitigate the technical, economic, and environmental issues associated with their elimination [ 9 , 10 , 12 , 13 ].…”

Valorization of Food Processing By-Products

“…Some methods were applied to evaluate the fatty acid content and their profile. One of them, which utilized the near infrared reflectance (NIR), was applied to fish by-products classification [ 18 ].…”