Accepted Manuscript
Quality changes of salmon by-products during storage: assessment and quanti- fication by NMR
Elena Shumilina, Rasa Slizyte, Revilija Mozuraityte, Anastasiya Dykyy, Timo A. Stein, Alexander Dikiy
PII: S0308-8146(16)30777-4 DOI: http://dx.doi.org/10.1016/j.foodchem.2016.05.088 Reference: FOCH 19237
To appear in: Food Chemistry
Received Date: 19 August 2015 Revised Date: 10 May 2016 Accepted Date: 13 May 2016
Please cite this article as: Shumilina, E., Slizyte, R., Mozuraityte, R., Dykyy, A., Stein, T.A., Dikiy, A., Quality changes of salmon by-products during storage: assessment and quantification by NMR, Food Chemistry (2016), doi: http://dx.doi.org/10.1016/j.foodchem.2016.05.088
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Quality changes of salmon by-products during storage: assessment and quantification by NMR. Elena Shumilina1, Rasa Slizyte2, Revilija Mozuraityte2, Anastasiya Dykyy1, Timo A. Stein1 and Alexander Dikiy 1,*
1 Norwegian University of Science and Technology (NTNU), Norway 2 SINTEF Fisheries and Aquaculture, Norway
Running title: NMR of salmon by-products Keywords: Salmon by-products; fish metabolites; NMR of fish by-products Chemical compounds studied in this article
Creatine (PubChem CID: 586); Phosphocreatine (PubChem CID: 9548602); Taurine (PubChem CID: 1123); Anserine (PubChem CID: 112072); Trimethylamine N-oxide (PubChem CID: 1145); Trimethylamine (PubChem CID: 1146); Cadaverine (PubChem CID: 273); Putrescine (PubChem CID: 1045); Tyramine (PubChem CID: 5610); Histamine (PubChem CID: 774);
*- corresponding author, e-mail address for correspondence: [email protected]
Abstract Safe utilization of fish by-products is an important task due to increasing fish consumption. It can provide new valuable food/feed and will increase the economical profit and sustainability of the fishery industry. NMR spectroscopy is a reliable tool able to monitor qualitative and quantitative changes in by-products. In this work the trichloroacetic acid extracts of salmon backbones, heads and viscera stored at industrially relevant temperatures (4 and 10°C) were studied using NMR. Twenty-five metabolites were detected and the possibility of salmon by-products utilization as a source of anserine, phosphocreatine and taurine was discussed. Statistical data elaboration allowed determining the main processes occurring during by-products storage: formation of trimethylamine and biogenic amines, proteolysis and different types of fermentations. By-products freshness was evaluated using a multi-parameter approach: the trimethylamine and biogenic amines concentration changes were compared with Ki and H-values and safe temperatures and times for storage of salmon by-products were proposed.
1. Introduction The increasing world population leads to a larger demand for fish and fishery products worldwide. Thus development of sustainable fish farming practices gains an important role as one of the measures to preserve limited natural fish resources. The global production of farmed salmon in 2011 reached 1.93 million tonnes and most of the fish are filleted with the fillet yielding about 55% of the total fish (FAO, 2014). Consequently, salmon processing generates considerable quantities of residual material. Viscera and trimmings account for about 50% of the salmon by-products, while heads and backbones make for about 7 and 8%, respectively (Olafsen, Richardsen, Nystøyl, Strandheim, & Kosmo, 2014). This material contains valuable high-quality protein, fatty acids, vitamins, and minerals, among others. The market for products with nutritional and health beneficial ingredients is growing. Fish proteins and hydrolysates can supply the increasing demand for animal-derived proteins and can also be used as valuable nutritional ingredients in different products and diet formulations (FAO, 2014). The utilization of fish by-products may become an important industry: heads and backbones left after filleting can be used as raw materials for the production of sausages, cakes, gelatin, sauces and viscera can be used as a potential source of protein hydrolysates (FAO, 2014). However, the fast decomposition of fish by-products may become a challenge for their successful market penetration. With prolonged storage time and increased temperature, freshness and quality of by-products irreversibly decrease and hygienic regulations may restrict their use due to food safety and quality issues. Consequently, accurate qualitative and quantitative monitoring of these changes is important for further by-products processing and utilization. Quality changes of marine products can be detected by sensory evaluation and/or by using classical standard analytical methods. However, these methods are time and human source demanding and can be not sensitive enough. Therefore, more advanced and sensitive techniques for quality and quantity evaluation are needed. In this work nuclear magnetic resonance (NMR) spectroscopy was used to qualitatively and quantitatively monitor water- soluble metabolites present in salmon by-products and detect their changes during storage. Principal component analysis (PCA) was used to evidence the most important changes in by- products composition and concentration. The data obtained from this study show that it is possible to detect high-added value compounds in salmon by-products and to determine their safe processing using NMR spectroscopy.
2. Materials and methods 2.1 Sample preparation. Fresh farmed salmons (Salmo salar) from Salmar/Nutrimar (Norway) were used for the tests. Heads and backbones from more than 15 fish were collected from the filleting lines. These rest raw materials and whole fish were packed separately, placed on ice and transported to the lab (SINTEF, Trondheim, Norway) immediately after production. To obtain the salmon viscera, fish were hand filleted on slaughter day (day 0). The obtained viscera were kept on ice (max 1 hour) until further processing. Heads were minced in a Hobart mincer using 10 mm holes. The minced heads (MH) were kept on ice (max 1 hour) until further processing. The whole heads (WH), whole backbones and viscera were placed in 10 L buckets with a cover and stored at different temperatures (4 and 10°C) for up to 7 days. At sampling day, the whole samples (heads, backbones and viscera) were minced separately in a Hobart mincer using 10 mm holes to produce a homogenous batch of each by-product. The minced raw materials were kept on ice (max 1 hour) until TCA extraction (see below).
2.2 Sampling. Chemical quality and stability of the analysed by-products were followed at two storage temperatures: 4 and 10°C for up to 7 days. Sampling was carried out at: 0 (T0), 1 (T1), 2
(T2), 3 (T3) and 7 (T7) days after slaughter.
2.3 Chemicals. Deuterium oxide (D2O, 99.9%) was purchased from Cambridge Isotope Laboratories Inc. (Andover, MA, USA). 3-(Trimethylsilyl)-propionic-2,2,3,3-d4 acid sodium salt (TSP, 98 atom % D) from Armar Chemicals (Dottingen, Switzerland), trichloroacetic acid (TCA) from Sigma-Aldrich (St. Louis, MO, USA). Potassium hydroxide from Sigma-Aldrich was used for pH adjustments.
2.4 TCA extract preparation. Five grams of each of the mentioned by-product samples were subjected to two-steps TCA-extraction. In more details: firstly, the sample was homogenized with 4:1 (v/w) volumes of 7.5% (w/v) ice-cold trichloroacetic acid, centrifuged and the supernatant was collected. Secondly, the remaining insoluble fish residues were further homogenized with TCA as described above. Supernatants from these two extractions were combined and the pH of the resulting solutions was adjusted to pH 7.0 using 9M KOH. All extraction steps were carried out at 4°C. The extracts were divided into 1.5 ml aliquots and stored at -80°C until analysis.
2.5 Sample Preparation for NMR Analysis. 900 µL of the sample extract were mixed with 100 µL of 1 mM TSP in 20 mM phosphate buffer, pH 7.0 in an Eppendorf tube and centrifuged at 20000xg for 5 min. 600 µL of the centrifuged sample were transferred in a standard 5mm NMR tube.
2.6 NMR experiments. 1D 1H, 2D 1H-1H total correlation spectroscopy (TOCSY), 1H- 13C heteronuclear single quantum correlation (HSQC) and 1H- 13C heteronuclear multiple bond correlation (HMBC) NMR spectra were acquired at 300K with a Bruker Avance 600-MHz spectrometer equipped with 5-mm z-gradient TXI (H/C/N) cryoprobe. All the NMR experiments mentioned above were acquired with the standard Bruker pulse sequences noesygppr1d; mlevgpphprzf; hsqcetgpprsisp2.2 and hmbcgplpndprqf, correspondingly and using the standard settings. For metabolites quantification the 1D 1H experiments (Bruker, noesygppr1d pulse sequence) with the following setting were used: number of scans ns=4; TD=32K; sw=20 ppm; aq=1.36 sec and constant receiver gain (RG=28.5). All spectra were processed by carrying out phase and baseline correction, integration and signal-to-noise (S/N) calculation using the TopSpin 3.2 software (Bruker, Germany). NMR assignment was performed using both the registered experiments and the available NMR databases (Biological Magnetic Resonance Data Bank (BMRB) and the Human Metabolome Database (HMDB)). The ERETIC2 (Electronic Reference To access In-vivo Concentrations, Topspin 3.2, Bruker) quantification tool and a custom Python script were used for metabolites quantification. The spectra were calibrated against an external standard assigning a chemical shift of 0 ppm to the TSP signal in both 1H and 13C dimensions.
2.7 Data Analysis. Principal Component Analysis (PCA). NMR spectra were examined using TopSpin 3.2 and AMIX- Viewer, version 3.9.14 (Bruker BioSpin, Billerica, MA, USA). Normalized to the average mass of the extracted salmon tissues and volume of extractions 1H NMR spectra were overlaid to detect inconsistencies in water suppression, shimming or baseline correction. PCA of 1D 1H NMR spectra was performed with the Statistics toolbox within the AMIX software using the following settings: variable size bucketing, 12-0.05 ppm spectral width and water signal exclusion. Manual bucketing was performed in order to include all peaks in the relative bucket for a total of 74 buckets. Strongly overlapped spectral features were excluded from analysis. Error analysis. Signal-to-noise ratios (S/N) were detected using the TopSpin software, where the
S/N ratio is calculated using the following formula: S/N= Imax/(2*σnoise); where Imax is the maximum amplitude of the peak and σnoise is the standard deviation of the noise region (12-11 ppm). It was assumed that only the signals with S/N ratio greater than 3 can be considered as reliably detectable (Maniara, Rajamoorthi, Rajan, & Stockton, 1998). The value and the uncertainty for the individual metabolite concentrations were calculated with a custom analysis script using Python 2.7 with libraries Numpy and Matplotlib. For each peak integral the uncertainty was estimated using the following equation1: