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Wali K, Khan HA, Sica P, Van Henten EJ, Meers E, Brunn S. Application of fourier transform infrared photoacoustic spectroscopy for quantification of nutrient contents and their plant availability in manure and digestate. Heliyon 2024; 10:e28487. [PMID: 38596044 PMCID: PMC11002050 DOI: 10.1016/j.heliyon.2024.e28487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 03/12/2024] [Accepted: 03/20/2024] [Indexed: 04/11/2024] Open
Abstract
In this study, we assess the feasibility of using Fourier Transform Infrared Photoacoustic Spectroscopy (FTIR-PAS) to predict macro- and micro-nutrients in a diverse set of manures and digestates. Furthermore, the prediction capabilities of FTIR-PAS were assessed using a novel error tolerance-based interval method in view of the accuracy required for application in agricultural practices. Partial Least-Squares Regression (PLSR) was used to correlate the FTIR-PAS spectra with nutrient contents. The prediction results were then assessed with conventional assessment methods (root mean square error (RMSE), coefficient of determination R2, and the ratio of prediction to deviation (RPD)). The results show the potential of FTIR-PAS to be used as a rapid analysis technique, with promising prediction results (R2 > 0.91 and RPD >2.5) for all elements except for bicarbonate-extractable P, K, and NH4+-N (0.8 < R2 < 0.9 and 2 < RPD <2.5). The results for nitrogen and phosphorus were further evaluated using the proposed error tolerance-based interval method. The probability of prediction for nitrogen within the allowed limit is calculated to be 94.6 % and for phosphorus 83.8 %. The proposed error tolerance-based interval method provides a better measure to decide if the FTIR-PAS in its current state could be used to meet the required accuracy in agriculture for the quantification of nutrient content in manure and digestate.
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Affiliation(s)
- Khan Wali
- Agricultural Biosystems Engineering Group, Wageningen University & Research, Wageningen, 6708 PB, Netherlands
| | - Haris Ahmad Khan
- Data Science, Crop Protection Development, Syngenta, Basel, Switzerland
| | - Pietro Sica
- Department of Plant and Environmental Sciences, Plant and Soil Science Section, University of Copenhagen, Copenhagen, Frederiksberg C 1871, Denmark
| | - Eldert J. Van Henten
- Agricultural Biosystems Engineering Group, Wageningen University & Research, Wageningen, 6708 PB, Netherlands
| | - Erik Meers
- Department of Green Chemistry and Technology, University of Gent, Gent, 9820, belgium
| | - Sander Brunn
- Department of Plant and Environmental Sciences, Plant and Soil Science Section, University of Copenhagen, Copenhagen, Frederiksberg C 1871, Denmark
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Tengstrand E, Måge I, Solberg LE, Afseth NK, Wold JP. Diagnosing the cage of covariance to increase understanding and robustness of spectroscopic calibration models. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 310:123877. [PMID: 38241929 DOI: 10.1016/j.saa.2024.123877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 01/08/2024] [Accepted: 01/08/2024] [Indexed: 01/21/2024]
Abstract
When vibrational spectroscopy is used for quantification purposes, multivariate analysis is often used to extract information from covariances between the spectra and any given reference values. In complex samples, there is a high risk that the constituents covary with each other. In such scenarios many methods may confuse the analytes and use signal from several analytes, rather than just the analyte of interest. While this allows the method to use more signal, and thus have a better effective signal-to-noise ratio, it also makes them less robust to changes to the chemical composition in the samples. This effect has been termed the cage of covariance. In order to avoid cage of covariance to affect predictive performances, it is highly important to have simple diagnostic tools to analyze and review this effect. Therefore, in the present paper, a systematic overview of tools for diagnosing and quantifying the cage of covariance in spectroscopic calibration models is provided. A collection of previously published methods with some expansions is provided, as well as two completely new tools: covariance ratio and virtual spiking. Practical applications of the tools on three different datasets are also shown.
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Affiliation(s)
- Erik Tengstrand
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway.
| | - Ingrid Måge
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Lars Erik Solberg
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Nils Kristian Afseth
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Jens Petter Wold
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
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Kristoffersen KA, Måge I, Wubshet SG, Böcker U, Riiser Dankel K, Lislelid A, Rønningen MA, Afseth NK. FTIR-based prediction of collagen content in hydrolyzed protein samples. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 301:122919. [PMID: 37295376 DOI: 10.1016/j.saa.2023.122919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 05/04/2023] [Accepted: 05/25/2023] [Indexed: 06/12/2023]
Abstract
Fourier transform infrared spectroscopy (FTIR) is a powerful analytical tool that has been used for protein and peptide characterization for decades. In the present study, the objective was to investigate if FTIR can be used to predict collagen content in hydrolyzed protein samples. All samples were obtained from enzymatic protein hydrolysis (EPH) of poultry by-products providing a span in collagen content from 0.3% to 37.9% (dry weight), and the FTIR analysis was performed using dry film FTIR. Since nonlinear effects were revealed by calibration using standard partial least squares (PLS) regression, Hierarchical Cluster-based PLS (HC-PLS) calibration models were constructed. The HC-PLS model provided a low prediction error when validated using an independent test set (RMSE = 3.3% collagen), while validation using real industrial samples also showed satisfying results (RMSE = 3.2%). The results corresponded well with previously published FTIR-based studies of collagen, and characteristic spectral features for collagen were well identified in the regression models. Covariance between collagen content and other EPH related processing parameters could also be ruled out in the regression models. To the authors' knowledge, this is the first time that collagen content has been systematically studied in solutions of hydrolysed proteins using FTIR. This is also one of few examples where FTIR is successfully used to quantify protein composition. The dry-film FTIR approach presented in the study is expected to be an important tool in the growing industrial segment that is based on sustainable utilization of collagen-rich biomass.
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Affiliation(s)
- Kenneth Aase Kristoffersen
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway; Faculty of Chemistry, Biotechnology, and Food Science, NMBU - Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway
| | - Ingrid Måge
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Sileshi Gizachew Wubshet
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Ulrike Böcker
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Katinka Riiser Dankel
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Andreas Lislelid
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway; Department of Mechanical, Electronics and Chemical Engineering, Faculty of Technology, Art and Design, OsloMet - Oslo Metropolitan University, P.O. Box 4, St. Olavs plass, NO-0130 Oslo, Norway
| | - Mats Aksnes Rønningen
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway; Department of Mechanical, Electronics and Chemical Engineering, Faculty of Technology, Art and Design, OsloMet - Oslo Metropolitan University, P.O. Box 4, St. Olavs plass, NO-0130 Oslo, Norway
| | - Nils Kristian Afseth
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway.
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Lintvedt TA, Andersen PV, Afseth NK, Heia K, Lindberg SK, Wold JP. Raman spectroscopy and NIR hyperspectral imaging for in-line estimation of fatty acid features in salmon fillets. Talanta 2023; 254:124113. [PMID: 36473242 DOI: 10.1016/j.talanta.2022.124113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 11/14/2022] [Accepted: 11/16/2022] [Indexed: 12/03/2022]
Abstract
Raman spectroscopy was compared with near infrared (NIR) hyperspectral imaging for determination of fat composition (%EPA + DHA) in salmon fillets at short exposure times. Fillets were measured in movement for both methods. Salmon were acquired from several different farming locations in Norway with different feeding regimes, representing a realistic variation of salmon in the market. For Raman, we investigated three manual scanning strategies; i) line scan of loin, ii) line scan of belly and iii) sinusoidal scan of belly at exposure times of 2s and 4s. NIR images were acquired while the fillets moved on a conveyor belt at 40 cm/s, which corresponds to an acquisition time of 1s for a 40 cm long fillet. For NIR images, three different regions of interest (ROI) were investigated including the i) whole fillet, ii) belly segment, and iii) loin segment. For both Raman and NIR measurements, we investigated an untrimmed and trimmed version of the fillets, both relevant for industrial in-line evaluation. For the trimmed fillets, a fat rich deposition layer in the belly was removed. The %EPA + DHA models were validated by cross validation (N = 51) and using an independent test set (N = 20) which was acquired in a different season. Both Raman and NIR showed promising results and high performances in the cross validation, with R2CV = 0.96 for Raman at 2s exposure and R2CV = 0.97 for NIR. High performances were obtained also for the test set, but while Raman had low and stable biases for the test set, the biases were high and varied for the NIR measurements. Analysis of variance on the squared test set residuals showed that performance for Raman measurements were significantly higher than NIR at 1% significance level (p = 0.000013) when slope-and-bias errors were not corrected, but not significant when residuals were slope-and-bias corrected (p = 0.28). This indicated that NIR was more sensitive to matrix effects. For Raman, signal-to-noise ratio was the main limitation and there were indications that Raman was close to a critical sample exposure time at the 2s signal accumulation.
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Affiliation(s)
- Tiril Aurora Lintvedt
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway; Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, 1432, Norway.
| | - Petter Vejle Andersen
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
| | - Nils Kristian Afseth
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
| | - Karsten Heia
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
| | - Stein-Kato Lindberg
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
| | - Jens Petter Wold
- Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, Tromsø, 9291, Norway
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Chernukha I, Kotenkova E, Pchelkina V, Ilyin N, Utyanov D, Kasimova T, Surzhik A, Fedulova L. Pork Fat and Meat: A Balance between Consumer Expectations and Nutrient Composition of Four Pig Breeds. Foods 2023; 12:foods12040690. [PMID: 36832765 PMCID: PMC9955543 DOI: 10.3390/foods12040690] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 02/08/2023] Open
Abstract
Food fat content is one of the most controversial factors from a consumer's point of view. Aim: (1) The trends in consumer attitudes towards pork and the fat and meat compositions in Duroc and Altai meat breeds and Livny and Mangalitsa meat and fat breeds were studied. (2) Methods: Netnographic studies were used to assess Russian consumer purchasing behavior. Protein, moisture, fat, backfat fatty acid content from pigs, longissimus muscles, and backfat from (A) Altai, (L) Livny, and (M) Russian Mangalitsa breeds were compared with those from (D) Russian Duroc. Raman spectroscopy and histology were applied to the backfat analysis. (3) Results: The attitude of Russian consumers to fatty pork is contradictory: consumers note its high fat content as a negative factor, but the presence of fat and intramuscular fat is welcomed because consumers positively associate them with better taste, tenderness, flavor, and juiciness. The fat of the 'lean' D pigs did not show a "healthy" fatty acid ratio, while the n-3 PUFA/n-6 PUFA ratio in the fat of the M pigs was the best, with significant amounts of short-chain fatty acids. The highest UFA content, particularly omega 3 and omega 6 PUFA, was found in the backfat of A pigs with a minimum SFA content. The backfat of L pigs was characterized by a larger size of the adipocytes; the highest monounsaturated and medium chain fatty acid contents and the lowest short-chain fatty acid content; the ratio of omega 3 to omega 6 was 0.07, and the atherogenicity index in L backfat was close to that of D, despite the fact that D pigs are a meat type, while L pigs are a meat and fat type. On the contrary, the thrombogenicity index in L backfat was even lower than the D one. (4) Conclusions: Pork from local breeds can be recommended for functional food production. The requirement to change the promotion strategy for local pork consumption from the position of dietary diversity and health is stated.
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FTIR-PCA Approach on Raw and Thermally Processed Chicken Lipids Stabilized by Nano-Encapsulation in β-Cyclodextrin. Foods 2022; 11:foods11223632. [PMID: 36429225 PMCID: PMC9689604 DOI: 10.3390/foods11223632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 10/26/2022] [Accepted: 11/11/2022] [Indexed: 11/16/2022] Open
Abstract
This study evaluated similarities/dissimilarities of raw and processed chicken breast and thigh lipids that were complexed by β-cyclodextrin, using a combined FTIR-PCA technique. Lipid fractions were analyzed as non-complexed and β-cyclodextrin-complexed samples via thermogravimetry, differential scanning calorimetry and ATR-FTIR. The lipid complexation reduced the water content to 7.67-8.33%, in comparison with the β-cyclodextrin hydrate (~14%). The stabilities of the complexes and β-cyclodextrin were almost the same. ATR-FTIR analysis revealed the presence of important bands that corresponded to the C=O groups (1743-1744 cm-1) in both the non-complexed and nano-encapsulated lipids. Furthermore, the bands that corresponded to the vibrations of double bonds corresponding to the natural/degraded (cis/trans) fatty acids in lipids appeared at 3008-3011 and 938-946 cm-1, respectively. The main FTIR bands that were involved in the discrimination of raw and processed chicken lipids, and of non-complexed and complexed lipids, were evaluated with PCA. The shifting of specific FTIR band wavenumbers had the highest influence, especially vibrations of the α(1→4) glucosidic bond in β-cyclodextrin for PC1, and CH2/3 groups from lipids for PC2. This first approach on β-cyclodextrin nano-encapsulation of chicken lipids revealed the possibility to stabilize poultry fatty components for further applications in various ingredients for the food industry.
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Qu C, Li Y, Du S, Geng Y, Su M, Liu H. Raman spectroscopy for rapid fingerprint analysis of meat quality and security: Principles, progress and prospects. Food Res Int 2022; 161:111805. [DOI: 10.1016/j.foodres.2022.111805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 07/06/2022] [Accepted: 08/18/2022] [Indexed: 11/28/2022]
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Pchelkina V, Chernukha I, Nikitina M, Ilin N. Pig adipose tissue of two different breeds and locations: morphology and Raman studies. FOODS AND RAW MATERIALS 2022. [DOI: 10.21603/2308-4057-2023-1-547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
According to the recent data, there are 4–5-local pig breeds left in Russia by now. Livni is among them. This breed is characterized by high fat content. Back fat has been analyzed earlier. We aimed to assess fat morphometrics from other localizations in pigs.
Sacral, axillary, and perirenal fat samples from 6-month-old Duroc and Livni pig breeds were analyzed using morphological and Raman-based techniques.
Livni adipocytes were characterized by dense packing with a polyhedron-like structure. In Duroc fat, they were more rounded (spherical). A “two-phase” cell disperse was identified in all samples. Fat cells in Livni pigs were bigger than those in the Duroc breed: 70–102%; 15–18 and 26% for sacral, axillary, and perirenal locations. Differences in the intensity of the Raman signal between the samples were found: in the samples of subcutaneous adipose tissue, more intense peaks were observed, which are responsible for unsaturation; the samples of Livni axillary fat were characterized by greater unsaturation than sacral fat.
Livni and Duroc adipocytes differ from each other in form and size and the difference depends on location. Pork fat from local breeds is expected to have potentially more health protecting (for animals) and health promoting (for consumers) properties.
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Affiliation(s)
| | - Irina Chernukha
- V.M. Gorbatov Federal Research Center for Food Systems of RAS
| | - Marina Nikitina
- V.M. Gorbatov Federal Research Center for Food Systems of RAS
| | - Nikolai Ilin
- V.M. Gorbatov Federal Research Center for Food Systems of RAS
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Shen SK, Wu ZY, Chen YW, Dong XP, Liu FJ, Ding ZW. Monitoring the lipid oxidation and flavor of Russian sturgeon fillets treated with low temperature vacuum heating: formation and relationship. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2022; 102:4609-4619. [PMID: 35174491 DOI: 10.1002/jsfa.11819] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/02/2022] [Accepted: 02/17/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Sturgeon is one of the most precious fish resources worldwide. Low temperature vacuum heating (LTVH) has been confirmed as a good way of maintaining food quality. However, there is a lack of in-depth studies assessing the impact of LTVH on lipid oxidation and flavor formation. RESULTS The present study compared the effect of LTVH and traditional cooking on lipid oxidation and flavor of sturgeon fillets. In total, 13 fatty acids were detected, of which polyunsaturated fatty acids content was the highest (P < 0.05). LTVH prevented the formation of conjugated diene and thiobarbituric acid reactive substances (P < 0.05), as manifested by an increased signal intensity of free radicals of electron spin resonance. The characteristic peaks intensity of lipid by Raman at 970 cm-1 , 1080 cm-1 and 1655 cm-1 were reduced, whereas peaks at 1068 cm-1 and 1125 cm-1 displayed the opposite trend. Confocal fluorescence microscopy showed that the lipids particles were reduced and distributed more evenly with an increase in heating temperature. Principal component analysis of electronic nose cannot effectively separate all groups; however, gas chromatography-ion migration spectrometry showed that the volatile flavor compounds were relatively stable during LTVH. Correlation analysis of all the above lipid oxidation indices and characteristic flavor substances showed that each treatment group was located in different quadrants and demonstrated great differentiation. CONCLUSION Overall, the results of the present study support the view that LTVH is a healthier way of cooking. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Shi-Ke Shen
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, China
- Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, China
| | - Zheng-Yang Wu
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, China
- Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, China
| | - Yue-Wen Chen
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, China
- Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, China
| | - Xiu-Ping Dong
- School of Food Science and Technology, Dalian Polytechnic University, Dalian, China
- National Engineering Research Center of Seafood, Dalian, China
| | - Fei-Jian Liu
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, China
- Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, China
| | - Zhi-Wen Ding
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, China
- Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition, Zhejiang Gongshang University, Hangzhou, China
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Prediction of the Lipid Degradation and Storage Time of Chilled Beef Flank by Using Raman Spectroscopy and Chemometrics. FOOD ANAL METHOD 2022. [DOI: 10.1007/s12161-022-02276-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Afseth NK, Dankel K, Andersen PV, Difford GF, Horn SS, Sonesson A, Hillestad B, Wold JP, Tengstrand E. Raman and near Infrared Spectroscopy for Quantification of Fatty Acids in Muscle Tissue-A Salmon Case Study. Foods 2022; 11:962. [PMID: 35407049 PMCID: PMC8997921 DOI: 10.3390/foods11070962] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/18/2022] [Accepted: 03/22/2022] [Indexed: 01/27/2023] Open
Abstract
The aim of the present study was to critically evaluate the potential of using NIR and Raman spectroscopy for prediction of fatty acid features and single fatty acids in salmon muscle. The study was based on 618 homogenized salmon muscle samples acquired from Atlantic salmon representing a one year-class nucleus, fed the same high fish oil feed. NIR and Raman spectra were used to make regression models for fatty acid features and single fatty acids measured by gas chromatography. The predictive performance of both NIR and Raman was good for most fatty acids, with R2 above 0.6. Overall, Raman performed marginally better than NIR, and since the Raman models generally required fewer components than respective NIR models to reach high and optimal performance, Raman is likely more robust for measuring fatty acids compared to NIR. The fatty acids of the salmon samples co-varied to a large extent, a feature that was exacerbated by the overlapping peaks in NIR and Raman spectra. Thus, the fatty acid related variation of the spectroscopic data of the present study can be explained by only a few independent principal components. For the Raman spectra, this variation was dominated by functional groups originating from long-chain polyunsaturated FAs like EPA and DHA. By exploring the independent EPA and DHA Raman models, spectral signatures similar to the respective pure fatty acids could be seen. This proves the potential of Raman spectroscopy for single fatty acid prediction in muscle tissue.
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Affiliation(s)
- Nils Kristian Afseth
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
| | - Katinka Dankel
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
| | - Petter Vejle Andersen
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
| | - Gareth Frank Difford
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
| | - Siri Storteig Horn
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
| | - Anna Sonesson
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
| | | | - Jens Petter Wold
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
| | - Erik Tengstrand
- Nofima AS—The Norwegian Institute of Food, Fisheries and Aquaculture Research, Osloveien 1, NO-1431 Ås, Norway; (K.D.); (P.V.A.); (G.F.D.); (S.S.H.); (A.S.); (J.P.W.); (E.T.)
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Cui N, Zhao T, Han Z, Yang Z, Wang G, Ma Q, Liang L. Characterisation of oil oxidation, fatty acid, carotenoid, squalene and tocopherol components of hazelnut oils obtained from three varieties undergoing oxidation. Int J Food Sci Technol 2022. [DOI: 10.1111/ijfs.15669] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Nana Cui
- State Key Laboratory of Tree Genetics and Breeding Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry Chinese Academy of Forestry Beijing 100091 China
- National Forestry and Grassland Innovation Alliance on Hazelnut Beijing 100091 China
- Hazelnut Engineering and Technical Research Center of the State Forestry and Grassland Administration Beijing 100091 China
| | - Tiantian Zhao
- State Key Laboratory of Tree Genetics and Breeding Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry Chinese Academy of Forestry Beijing 100091 China
- National Forestry and Grassland Innovation Alliance on Hazelnut Beijing 100091 China
- Hazelnut Engineering and Technical Research Center of the State Forestry and Grassland Administration Beijing 100091 China
| | - Zhentai Han
- Institute of Forest Ecology Environment and Protection Chinese Academy of Forestry Beijing 100091 China
| | - Zhen Yang
- State Key Laboratory of Tree Genetics and Breeding Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry Chinese Academy of Forestry Beijing 100091 China
- National Forestry and Grassland Innovation Alliance on Hazelnut Beijing 100091 China
- Hazelnut Engineering and Technical Research Center of the State Forestry and Grassland Administration Beijing 100091 China
| | - Guixi Wang
- State Key Laboratory of Tree Genetics and Breeding Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry Chinese Academy of Forestry Beijing 100091 China
- National Forestry and Grassland Innovation Alliance on Hazelnut Beijing 100091 China
- Hazelnut Engineering and Technical Research Center of the State Forestry and Grassland Administration Beijing 100091 China
| | - Qinghua Ma
- State Key Laboratory of Tree Genetics and Breeding Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry Chinese Academy of Forestry Beijing 100091 China
- National Forestry and Grassland Innovation Alliance on Hazelnut Beijing 100091 China
- Hazelnut Engineering and Technical Research Center of the State Forestry and Grassland Administration Beijing 100091 China
| | - Lisong Liang
- State Key Laboratory of Tree Genetics and Breeding Key Laboratory of Tree Breeding and Cultivation of the State Forestry and Grassland Administration, Research Institute of Forestry Chinese Academy of Forestry Beijing 100091 China
- National Forestry and Grassland Innovation Alliance on Hazelnut Beijing 100091 China
- Hazelnut Engineering and Technical Research Center of the State Forestry and Grassland Administration Beijing 100091 China
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13
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Logan BG, Hopkins DL, Schmidtke LM, Fowler SM. Assessing chemometric models developed using Raman spectroscopy and fatty acid data for Northern and Southern Australian beef production systems. Meat Sci 2022; 187:108753. [DOI: 10.1016/j.meatsci.2022.108753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 01/07/2022] [Accepted: 01/31/2022] [Indexed: 11/29/2022]
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14
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Prediction of fatty acids composition in the rainbow trout Oncorhynchus mykiss by using Raman micro-spectroscopy. Anal Chim Acta 2022; 1191:339212. [PMID: 35033269 DOI: 10.1016/j.aca.2021.339212] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/26/2021] [Accepted: 10/23/2021] [Indexed: 11/21/2022]
Abstract
The importance of poly-unsaturated fatty acids (PUFAs) in food is crucial for the animal and human development and health. As a complementary strategy to nutrition approaches, genetic selection has been suggested to improve fatty acids (FAs) composition in farmed fish. Gas chromatography (GC) is used as a reference method for the quantification of FAs; nevertheless, the high cost prevents large scale phenotyping as needed in breeding programs. Therefore, a calibration by means of Raman scattering spectrometry has been established in order to predict FA composition of visceral adipose tissue in rainbow trout Onchorhynchus mykiss. FA composition was analyzed by both GC and Raman micro-spectrometry techniques on 268 individuals fed with three different feeds, which have different FA compositions. Among the possible regression methods, the ridge regression method, was found to be efficient to establish calibration models from the GC and spectral data. The best cross-validated R2 values were obtained for total PUFAs, omega-6 (Ω-6) and omega-3 (Ω-3) PUFA (0.79, 0.83 and 0.66, respectively). For individual Ω-3 PUFAs, α-linolenic acid (ALA, C18:3), eicosapentaenoic acid (EPA, C20:5) and docosahexenoic acid (DHA, C22:6) were found to have the best R2 values (0.82, 0.76 and 0.81, respectively). This study demonstrates that Raman spectroscopy could be used to predict PUFAs with good correlation coefficients on adipocytes, for future on adipocytes physiology or for large scale and high throughput phenotyping in rainbow trout.
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15
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Wang K, Li Z, Li J, Lin H. Raman spectroscopic techniques for nondestructive analysis of agri-foods: A state-of-the-art review. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2021.10.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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16
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Forsberg J, Nielsen PM, Engelsen SB, Sørensen KM. On-Line Real-Time Monitoring of a Rapid Enzymatic Oil Degumming Process: A Feasibility Study Using Free-Run Near-Infrared Spectroscopy. Foods 2021; 10:2368. [PMID: 34681417 PMCID: PMC8535312 DOI: 10.3390/foods10102368] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 09/29/2021] [Accepted: 09/30/2021] [Indexed: 11/26/2022] Open
Abstract
Enzymatic degumming is a well established process in vegetable oil refinement, resulting in higher oil yield and a more stable downstream processing compared to traditional degumming methods using acid and water. During the reaction, phospholipids in the oil are hydrolyzed to free fatty acids and lyso-phospholipids. The process is typically monitored by off-line laboratory measurements of the free fatty acid content in the oil, and there is a demand for an automated on-line monitoring strategy to increase both yield and understanding of the process dynamics. This paper investigates the option of using Near-Infrared spectroscopy (NIRS) to monitor the enzymatic degumming reaction. A new method for balancing spectral noise and keeping the chemical information in the spectra obtained from a rapid changing chemical process is suggested. The effect of a varying measurement averaging window width (0 to 300 s), preprocessing method and variable selection algorithm is evaluated, aiming to obtain the most accurate and robust calibration model for prediction of the free fatty acid content (% (w/w)). The optimal Partial Least Squares (PLS) model includes eight wavelength variables, as found by rPLS (recursive PLS) calibration, and yields an RMSECV (Root Mean Square Error of Cross Validation) of 0.05% (w/w) free fatty acid using five latent variables.
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Affiliation(s)
- Jakob Forsberg
- Food Analytics and Biotechnology, Department of Food Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark; (S.B.E.); (K.M.S.)
| | - Per Munk Nielsen
- Novozymes, Oils & Fats Application Research, Biologiens Vej 2, DK-2800 Kongens Lyngby, Denmark;
| | - Søren Balling Engelsen
- Food Analytics and Biotechnology, Department of Food Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark; (S.B.E.); (K.M.S.)
| | - Klavs Martin Sørensen
- Food Analytics and Biotechnology, Department of Food Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark; (S.B.E.); (K.M.S.)
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17
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Hyperspectral imaging and chemometrics as a non-invasive tool to discriminate and analyze iodine value of pork fat. Food Control 2021. [DOI: 10.1016/j.foodcont.2021.108145] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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18
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Wang J, Chen Q, Belwal T, Lin X, Luo Z. Insights into chemometric algorithms for quality attributes and hazards detection in foodstuffs using Raman/surface enhanced Raman spectroscopy. Compr Rev Food Sci Food Saf 2021; 20:2476-2507. [DOI: 10.1111/1541-4337.12741] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 02/08/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022]
Affiliation(s)
- Jingjing Wang
- College of Biosystems Engineering and Food Science, Key Laboratory of Agro‐Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang Key Laboratory for Agri‐Food Processing, National‐Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang University Hangzhou People's Republic of China
| | - Quansheng Chen
- School of Food and Biological Engineering Jiangsu University Zhenjiang People's Republic of China
| | - Tarun Belwal
- College of Biosystems Engineering and Food Science, Key Laboratory of Agro‐Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang Key Laboratory for Agri‐Food Processing, National‐Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang University Hangzhou People's Republic of China
| | - Xingyu Lin
- College of Biosystems Engineering and Food Science, Key Laboratory of Agro‐Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang Key Laboratory for Agri‐Food Processing, National‐Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang University Hangzhou People's Republic of China
| | - Zisheng Luo
- College of Biosystems Engineering and Food Science, Key Laboratory of Agro‐Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang Key Laboratory for Agri‐Food Processing, National‐Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang University Hangzhou People's Republic of China
- Ningbo Research Institute Zhejiang University Ningbo People's Republic of China
- Fuli Institute of Food Science Hangzhou People's Republic of China
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19
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20
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Daoust F, Nguyen T, Orsini P, Bismuth J, de Denus-Baillargeon MM, Veilleux I, Wetter A, Mckoy P, Dicaire I, Massabki M, Petrecca K, Leblond F. Handheld macroscopic Raman spectroscopy imaging instrument for machine-learning-based molecular tissue margins characterization. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-200306SSR. [PMID: 33580641 PMCID: PMC7880244 DOI: 10.1117/1.jbo.26.2.022911] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 01/19/2021] [Indexed: 05/08/2023]
Abstract
SIGNIFICANCE Raman spectroscopy has been developed for surgical guidance applications interrogating live tissue during tumor resection procedures to detect molecular contrast consistent with cancer pathophysiological changes. To date, the vibrational spectroscopy systems developed for medical applications include single-point measurement probes and intraoperative microscopes. There is a need to develop systems with larger fields of view (FOVs) for rapid intraoperative cancer margin detection during surgery. AIM We design a handheld macroscopic Raman imaging system for in vivo tissue margin characterization and test its performance in a model system. APPROACH The system is made of a sterilizable line scanner employing a coherent fiber bundle for relaying excitation light from a 785-nm laser to the tissue. A second coherent fiber bundle is used for hyperspectral detection of the fingerprint Raman signal over an area of 1 cm2. Machine learning classifiers were trained and validated on porcine adipose and muscle tissue. RESULTS Porcine adipose versus muscle margin detection was validated ex vivo with an accuracy of 99% over the FOV of 95 mm2 in ∼3 min using a support vector machine. CONCLUSIONS This system is the first large FOV Raman imaging system designed to be integrated in the workflow of surgical cancer resection. It will be further improved with the aim of discriminating brain cancer in a clinically acceptable timeframe during glioma surgery.
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Affiliation(s)
- François Daoust
- Polytechnique Montreal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Tien Nguyen
- Polytechnique Montreal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | | | | | | | - Israel Veilleux
- Polytechnique Montreal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | | | | | | | | | - Kevin Petrecca
- McGill University, Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, Montreal, Quebec, Canada
| | - Frédéric Leblond
- Polytechnique Montreal, Department of Engineering Physics, Montreal, Quebec, Canada
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
- Address all correspondence to Frédéric Leblond,
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21
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Gao F, Ben-Amotz D, Zhou S, Yang Z, Han L, Liu X. Comparison and chemical structure-related basis of species discrimination of animal fats by Raman spectroscopy using near-infrared and visible excitation lasers. Lebensm Wiss Technol 2020. [DOI: 10.1016/j.lwt.2020.110105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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22
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Zhang W, Ma J, Sun DW. Raman spectroscopic techniques for detecting structure and quality of frozen foods: principles and applications. Crit Rev Food Sci Nutr 2020; 61:2623-2639. [DOI: 10.1080/10408398.2020.1828814] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Wenyang Zhang
- School of Food Science and Engineering, South China University of Technology, Guangzhou, China
- Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou, China
- Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou, China
| | - Ji Ma
- School of Food Science and Engineering, South China University of Technology, Guangzhou, China
- Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou, China
- Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou, China
- State Key Laboratory of Luminescent Materials and Devices, Center for Aggregation-Induced Emission, South China University of Technology, Guangzhou, China
| | - Da-Wen Sun
- School of Food Science and Engineering, South China University of Technology, Guangzhou, China
- Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou, China
- Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou, China
- Food Refrigeration and Computerized Food Technology (FRCFT), Agriculture and Food Science Centre, University College Dublin, National University of Ireland, Dublin 4, Ireland
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23
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Rohman A, Windarsih A. The Application of Molecular Spectroscopy in Combination with Chemometrics for Halal Authentication Analysis: A Review. Int J Mol Sci 2020; 21:E5155. [PMID: 32708254 PMCID: PMC7403989 DOI: 10.3390/ijms21145155] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 04/25/2020] [Accepted: 04/29/2020] [Indexed: 12/18/2022] Open
Abstract
Halal is an Arabic term used to describe any components allowed to be used in any products by Muslim communities. Halal food and halal pharmaceuticals are any food and pharmaceuticals which are safe and allowed to be consumed according to Islamic law (Shariah). Currently, in line with halal awareness, some Muslim countries such as Indonesia, Malaysia, and Middle East regions have developed some standards and regulations on halal products and halal certification. Among non-halal components, the presence of pig derivatives (lard, pork, and porcine gelatin) along with other non-halal meats (rat meat, wild boar meat, and dog meat) is typically found in food and pharmaceutical products. This review updates the recent application of molecular spectroscopy, including ultraviolet-visible, infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies, in combination with chemometrics of multivariate analysis, for analysis of non-halal components in food and pharmaceutical products. The combination of molecular spectroscopic-based techniques and chemometrics offers fast and reliable methods for screening the presence of non-halal components of pig derivatives and non-halal meats in food and pharmaceutical products.
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Affiliation(s)
- Abdul Rohman
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
- Institute of Halal Industry and Systems (IHIS), Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
| | - Anjar Windarsih
- Research Division for Natural Product Technology (BPTBA), Indonesian Institute of Sciences (LIPI), Yogyakarta 55861, Indonesia
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24
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Monitoring yeast fermentations by nonlinear infrared technology and chemometrics-understanding process correlations and indirect predictions. Appl Microbiol Biotechnol 2020; 104:5315-5335. [PMID: 32328682 DOI: 10.1007/s00253-020-10604-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 03/19/2020] [Accepted: 04/01/2020] [Indexed: 10/24/2022]
Abstract
Fermentation processes are still compromised by a lack of monitoring strategies providing integrated process data online, ensuring process understanding, control, and thus, optimal reactor efficiency. The crucial demand for online monitoring strategies, not only encouraged by the PAT initiative but also motivated by modern paradigms such as circular economy and sustainability, has driven research and industry to provide "next-generation process technology": in other words, technology tailored toward industrial needs. Mid-infrared (MIR) spectroscopy as such is superior to near-infrared (NIR) spectroscopy since it provides significantly enhanced selectivity. However, due to high costs and a lack of instrumental robustness, MIR spectroscopy is outcompeted by NIR when it comes to industrial application. The lack of chemometric expertise, model understanding, and practical guidance might add to the slow acceptance of industrial MIR application. This work demonstrates the use of novel MIR, so-called non-linear infrared (NLIR) technology and the importance of model understanding, exemplarily investigated on a lab-scale yeast fermentation process. The six analytes glucose, ethanol, glycerol, acetate, ammonium, and phosphate were modeled by partial least squares (PLS) based on spectral data, demonstrating the potential of the novel technology facilitating online data acquisition and the necessity of investigating indirect predictions. KEY POINTS: • NLIR spectra were acquired online during a yeast fermentation process • PLS models were constructed for six components based on uncorrelated samples • Glucose, ethanol, ammonium, and phosphates were modeled with errors of less than 15% • Acetate and glycerol were shown to rely on indirect predictions.
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25
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Ma J, Sun DW. Prediction of monounsaturated and polyunsaturated fatty acids of various processed pork meats using improved hyperspectral imaging technique. Food Chem 2020; 321:126695. [PMID: 32247889 DOI: 10.1016/j.foodchem.2020.126695] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 03/20/2020] [Accepted: 03/24/2020] [Indexed: 12/21/2022]
Abstract
Freezing, heating, and pickling are common processes for pork meats. Unsaturated fatty acids including monounsaturated fatty acids and polyunsaturated fatty acids are indispensable nutrition beneficial to human's health and growth. However, Unsaturated fatty acids are affected by processing methods. Hyperspectral imaging is a novel technique widely used for food quality and safety evaluation. In the current study, the contents of monounsaturated and polyunsaturated fatty acids were assessed by Hyperspectral imaging. Optimal wavelengths were selected by the regression coefficients curves of partial least squares regression models. The least-squares support vector machine models established achieved a better coefficient of determination in the Monte Carlo validation set than the partial least squares regression models developed and the R2MV values for the least squares - support vector machine models based on selected optimal wavelengths were higher than 0.81. Finally, colour maps of the contents of monounsaturated and polyunsaturated fatty acids were developed.
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Affiliation(s)
- Ji Ma
- School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China
| | - Da-Wen Sun
- School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China; Food Refrigeration and Computerized Food Technology, University College Dublin, National University of Ireland, Agriculture and Food Science Centre, Belfield, Dublin 4, Ireland.
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26
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Cheng W, Sørensen KM, Engelsen SB, Sun DW, Pu H. Lipid oxidation degree of pork meat during frozen storage investigated by near-infrared hyperspectral imaging: Effect of ice crystal growth and distribution. J FOOD ENG 2019. [DOI: 10.1016/j.jfoodeng.2019.07.013] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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27
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Chen Q, Xie Y, Xi J, Guo Y, Qian H, Cheng Y, Chen Y, Yao W. Characterization of lipid oxidation process of beef during repeated freeze-thaw by electron spin resonance technology and Raman spectroscopy. Food Chem 2018; 243:58-64. [DOI: 10.1016/j.foodchem.2017.09.115] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 09/15/2017] [Accepted: 09/21/2017] [Indexed: 10/18/2022]
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28
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Gao F, Xu L, Zhang Y, Yang Z, Han L, Liu X. Analytical Raman spectroscopic study for discriminant analysis of different animal-derived feedstuff: Understanding the high correlation between Raman spectroscopy and lipid characteristics. Food Chem 2018; 240:989-996. [DOI: 10.1016/j.foodchem.2017.07.143] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2016] [Revised: 08/02/2016] [Accepted: 07/26/2017] [Indexed: 10/19/2022]
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29
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Kucha CT, Liu L, Ngadi MO. Non-Destructive Spectroscopic Techniques and Multivariate Analysis for Assessment of Fat Quality in Pork and Pork Products: A Review. SENSORS 2018; 18:s18020377. [PMID: 29382092 PMCID: PMC5855493 DOI: 10.3390/s18020377] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 01/07/2018] [Accepted: 01/10/2018] [Indexed: 12/31/2022]
Abstract
Fat is one of the most important traits determining the quality of pork. The composition of the fat greatly influences the quality of pork and its processed products, and contribute to defining the overall carcass value. However, establishing an efficient method for assessing fat quality parameters such as fatty acid composition, solid fat content, oxidative stability, iodine value, and fat color, remains a challenge that must be addressed. Conventional methods such as visual inspection, mechanical methods, and chemical methods are used off the production line, which often results in an inaccurate representation of the process because the dynamics are lost due to the time required to perform the analysis. Consequently, rapid, and non-destructive alternative methods are needed. In this paper, the traditional fat quality assessment techniques are discussed with emphasis on spectroscopic techniques as an alternative. Potential spectroscopic techniques include infrared spectroscopy, nuclear magnetic resonance and Raman spectroscopy. Hyperspectral imaging as an emerging advanced spectroscopy-based technology is introduced and discussed for the recent development of assessment for fat quality attributes. All techniques are described in terms of their operating principles and the research advances involving their application for pork fat quality parameters. Future trends for the non-destructive spectroscopic techniques are also discussed.
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Affiliation(s)
- Christopher T Kucha
- Department of Bioresource Engineering, McGill University, Macdonald Campus 21,111 Lakeshore Road, Ste-Anne-de-Bellevue, Quebec, QC H9X 3V9, Canada.
| | - Li Liu
- Department of Bioresource Engineering, McGill University, Macdonald Campus 21,111 Lakeshore Road, Ste-Anne-de-Bellevue, Quebec, QC H9X 3V9, Canada.
| | - Michael O Ngadi
- Department of Bioresource Engineering, McGill University, Macdonald Campus 21,111 Lakeshore Road, Ste-Anne-de-Bellevue, Quebec, QC H9X 3V9, Canada.
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30
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St-Arnaud K, Aubertin K, Strupler M, Madore WJ, Grosset AA, Petrecca K, Trudel D, Leblond F. Development and characterization of a handheld hyperspectral Raman imaging probe system for molecular characterization of tissue on mesoscopic scales. Med Phys 2017; 45:328-339. [PMID: 29106741 DOI: 10.1002/mp.12657] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 09/27/2017] [Accepted: 10/11/2017] [Indexed: 12/20/2022] Open
Abstract
PURPOSE Raman spectroscopy is a promising cancer detection technique for surgical guidance applications. It can provide quantitative information relating to global tissue properties associated with structural, metabolic, immunological, and genetic biochemical phenomena in terms of molecular species including amino acids, lipids, proteins, and nucleic acid (DNA). To date in vivo Raman spectroscopy systems mostly included probes and biopsy needles typically limited to single-point tissue interrogation over a scale between 100 and 500 microns. The development of wider field handheld systems could improve tumor localization for a range of open surgery applications including brain, ovarian, and skin cancers. METHODS Here we present a novel Raman spectroscopy implementation using a coherent imaging bundle of fibers to create a probe capable of reconstructing molecular images over mesoscopic fields of view. Detection is performed using linear scanning with a rotation mirror and an imaging spectrometer. Different slits widths were tested at the entrance of the spectrometer to optimize spatial and spectral resolution while preserving sufficient signal-to-noise ratios to detect the principal Raman tissue features. The nonbiological samples, calcite and polytetrafluoroethylene (PTFE), were used to characterize the performance of the system. The new wide-field probe was tested on ex vivo samples of calf brain and swine tissue. Raman spectral content of both tissue types were validated with data from the literature and compared with data acquired with a single-point Raman spectroscopy probe. The single-point probe was used as the gold standard against which the new instrument was benchmarked as it has already been thoroughly validated for biological tissue characterization. RESULT We have developed and characterized a practical noncontact handheld Raman imager providing tissue information at a spatial resolution of 115 microns over a field of view >14 mm2 and a spectral resolution of 6 cm-1 over the whole fingerprint region. Typical integration time to acquire an entire Raman image over swine tissue was set to approximately 100 s. Spectra acquired with both probes (single-point and wide-field) showed good agreement, with a Pearson correlation factor >0.85 over different tissue categories. Protein and lipid content of imaged tissue were manifested into the measured spectra which correlated well with previous findings in the literature. An example of quantitative molecular map is presented for swine tissue and calf brain based on the ratio of protein-to-lipid content showing clear delineations between white and gray matter as well as between adipose and muscle tissue. CONCLUSION We presented the development of a Raman imaging probe with a field of view of a few millimeters and a spatial resolution consistent with standard surgical imaging methods using an imaging bundle. Spectra acquired with the newly developed system on swine tissue and calf brain correlated well with an establish single-point probe and observed spectral features agreed with previous finding in the literature. The imaging probe has demonstrated its ability to reconstruct molecular images of soft tissues. The approach presented here has a lot of potential for the development of surgical Raman imaging probe to guide the surgeon during cancer surgery.
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Affiliation(s)
- Karl St-Arnaud
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada.,Imaging & Engineering, Centre Hospitalier Universitaire de Montréal Research Center (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada
| | - Kelly Aubertin
- Imaging & Engineering, Centre Hospitalier Universitaire de Montréal Research Center (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada.,CRCHUM/Montreal Cancer Institute, 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada
| | - Mathias Strupler
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada
| | - Wendy-Julie Madore
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada.,Imaging & Engineering, Centre Hospitalier Universitaire de Montréal Research Center (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada
| | - Andrée-Anne Grosset
- CRCHUM/Montreal Cancer Institute, 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada.,Dept. of Pathology and Cellular Biology, University of Montreal, Montreal, QC, H3T 1J4, Canada
| | - Kevin Petrecca
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University St., Montreal, QC, H3A 2B4, Canada
| | - Dominique Trudel
- Dept. of Pathology, Centre Hospitalier Universitaire de Montréal (CHUM), Montreal, QC, H2X 3J4, Canada.,CRCHUM/Montreal Cancer Institute, 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada.,Dept. of Pathology and Cellular Biology, University of Montreal, Montreal, QC, H3T 1J4, Canada
| | - Frédéric Leblond
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada.,Imaging & Engineering, Centre Hospitalier Universitaire de Montréal Research Center (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada
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31
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Aru V, Lam C, Khakimov B, Hoefsloot HC, Zwanenburg G, Lind MV, Schäfer H, van Duynhoven J, Jacobs DM, Smilde AK, Engelsen SB. Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis. Trends Analyt Chem 2017. [DOI: 10.1016/j.trac.2017.07.009] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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32
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Tao F, Ngadi M. Recent advances in rapid and nondestructive determination of fat content and fatty acids composition of muscle foods. Crit Rev Food Sci Nutr 2017; 58:1565-1593. [PMID: 28118034 DOI: 10.1080/10408398.2016.1261332] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Conventional methods for determining fat content and fatty acids (FAs) composition are generally based on the solvent extraction and gas chromatography techniques, respectively, which are time consuming, laborious, destructive to samples and require use of hazard solvents. These disadvantages make them impossible for large-scale detection or being applied to the production line of meat factories. In this context, the great necessity of developing rapid and nondestructive techniques for fat and FAs analyses has been highlighted. Measurement techniques based on near-infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance and hyperspectral imaging have provided interesting and promising results for fat and FAs prediction in varieties of foods. Thus, the goal of this article is to give an overview of the current research progress in application of the four important techniques for fat and FAs analyses of muscle foods, which consist of pork, beef, lamb, chicken meat, fish and fish oil. The measurement techniques are described in terms of their working principles, features, and application advantages. Research advances for these techniques for specific food are summarized in detail and the factors influencing their modeling results are discussed. Perspectives on the current situation, future trends and challenges associated with the measurement techniques are also discussed.
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Affiliation(s)
- Feifei Tao
- a Department of Bioresource Engineering , McGill University , Ste-Anne-de-Bellevue , Quebec , Canada
| | - Michael Ngadi
- a Department of Bioresource Engineering , McGill University , Ste-Anne-de-Bellevue , Quebec , Canada
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33
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Lo Fiego DP, Minelli G, Volpelli LA, Ulrici A, Macchioni P. Calculating the iodine value for Italian heavy pig subcutaneous adipose tissue from fatty acid methyl ester profiles. Meat Sci 2016; 122:132-138. [PMID: 27522249 DOI: 10.1016/j.meatsci.2016.08.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Revised: 07/13/2016] [Accepted: 08/03/2016] [Indexed: 11/25/2022]
Abstract
In this work, different equations were compared as for their effectiveness in predicting the iodine value (IV), based on fatty acid (FA) composition of subcutaneous adipose tissue of Italian heavy pigs. In particular, six equations were tested: AOCS (1); modified AOCS (2), including all unsaturated FA (UFA); regression models obtained using the stepwise regression procedure as variable selection method, calculated considering only UFA (3) or all the FA (4); regression models obtained using the backward elimination procedure, calculated considering only UFA (5) or all the FA (6). The comparison of the equations performance, estimated using an external test set, showed that the use of regression models led to significant enhancements of prediction accuracy with respect to the AOCS equations. Using both equations 4 and 6, the average paired differences between experimental and predicted IV values were not statistically significant. Therefore, it is possible to use these equations for IV estimation of the subcutaneous adipose tissue of Italian heavy pigs.
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Affiliation(s)
- Domenico Pietro Lo Fiego
- Department of Life Sciences, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy; Interdipartimental Research Centre for Agri-Food Biological Resources Improvement and Valorisation, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy
| | - Giovanna Minelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy; Interdipartimental Research Centre for Agri-Food Biological Resources Improvement and Valorisation, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy.
| | - Luisa Antonella Volpelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy; Interdipartimental Research Centre for Agri-Food Biological Resources Improvement and Valorisation, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy
| | - Alessandro Ulrici
- Department of Life Sciences, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy; Interdipartimental Research Centre for Agri-Food Biological Resources Improvement and Valorisation, University of Modena and Reggio Emilia, Padiglione Besta, Via G. Amendola 2, 42122 Reggio Emilia, Italy
| | - Paolo Macchioni
- Department of Agricultural and Food Sciences, University of Bologna, Via G. Fanin 44, 40127 Bologna, Italy
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34
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Baum A, Hansen P, Nørgaard L, Sørensen J, Mikkelsen J. Rapid quantification of casein in skim milk using Fourier transform infrared spectroscopy, enzymatic perturbation, and multiway partial least squares regression: Monitoring chymosin at work. J Dairy Sci 2016; 99:6071-6079. [DOI: 10.3168/jds.2016-10947] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 04/21/2016] [Indexed: 11/19/2022]
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35
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Troy DJ, Ojha KS, Kerry JP, Tiwari BK. Sustainable and consumer-friendly emerging technologies for application within the meat industry: An overview. Meat Sci 2016; 120:2-9. [PMID: 27162095 DOI: 10.1016/j.meatsci.2016.04.002] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 03/24/2016] [Accepted: 04/05/2016] [Indexed: 10/22/2022]
Abstract
New and emerging robust technologies can play an important role in ensuring a more resilient meat value chain and satisfying consumer demands and needs. This paper outlines various novel thermal and non-thermal technologies which have shown potential for meat processing applications. A number of process analytical techniques which have shown potential for rapid, real-time assessment of meat quality are also discussed. The commercial uptake and consumer acceptance of novel technologies in meat processing have been subjects of great interest over the past decade. Consumer focus group studies have shown that consumer expectations and liking for novel technologies, applicable to meat processing applications, vary significantly. This overview also highlights the necessity for meat processors to address consumer risk-benefit perceptions, knowledge and trust in order to be commercially successful in the application of novel technologies within the meat sector.
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Affiliation(s)
- Declan J Troy
- Teagasc Food Research Centre, Ashtown, Dublin 15, Ireland.
| | | | - Joseph P Kerry
- Food Packaging Group, School of Food and Nutritional Sciences, University College Cork, Cork, Ireland
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36
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Foca G, Ferrari C, Ulrici A, Ielo MC, Minelli G, Lo Fiego DP. Iodine Value and Fatty Acids Determination on Pig Fat Samples by FT-NIR Spectroscopy: Benefits of Variable Selection in the Perspective of Industrial Applications. FOOD ANAL METHOD 2016. [DOI: 10.1007/s12161-016-0478-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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37
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Liu X, Schmidt H, Mörlein D. Feasibility of boar taint classification using a portable Raman device. Meat Sci 2016; 116:133-9. [PMID: 26882212 DOI: 10.1016/j.meatsci.2016.02.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 01/27/2016] [Accepted: 02/05/2016] [Indexed: 12/20/2022]
Abstract
The feasibility of Raman spectroscopy for boar taint detection and classification was investigated using tainted and untainted backfat samples of 46 boars. For this exploratory study, backfat samples were selected according to their levels of androstenone and skatole as determined by gas chromatography and their sensory score by a trained panel. Raman spectra were collected with a portable device at freshly cut surfaces of frozen-thawed samples. Both inner and outer layers of subcutaneous fat were studied. Their varying level of unsaturation was reflected in the Raman spectra. Partial least squares regression discriminant analysis (PLS-DA) was applied to the spectra together with various pre-processing methods. A model using only spectra obtained at the inner layer resulted in the highest classification accuracy for boar taint (81% of samples correctly classified). The discrimination is shown to reflect differences in the degree of fatty acid saturation between tainted and untainted boars. In conclusion, the findings suggest that with further development Raman spectroscopy may be used to classify boar taint.
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Affiliation(s)
- Xiaoye Liu
- Key laboratory of Meat Processing and Quality Control, Ministry of Education, College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, PR China; Department of Animal Science, University of Göttingen, D-37075 Göttingen, Germany
| | - Heinar Schmidt
- University of Bayreuth, Bioanalytical Science and Food Analysis - Research Center of Food Quality, D-95326 Kulmbach, Germany
| | - Daniel Mörlein
- Department of Animal Science, University of Göttingen, D-37075 Göttingen, Germany.
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38
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Pork as a Source of Omega-3 (n-3) Fatty Acids. J Clin Med 2015; 4:1999-2011. [PMID: 26694475 PMCID: PMC4693156 DOI: 10.3390/jcm4121956] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Revised: 12/08/2015] [Accepted: 12/08/2015] [Indexed: 12/03/2022] Open
Abstract
Pork is the most widely eaten meat in the world, but typical feeding practices give it a high omega-6 (n-6) to omega-3 (n-3) fatty acid ratio and make it a poor source of n-3 fatty acids. Feeding pigs n-3 fatty acids can increase their contents in pork, and in countries where label claims are permitted, claims can be met with limited feeding of n-3 fatty acid enrich feedstuffs, provided contributions of both fat and muscle are included in pork servings. Pork enriched with n-3 fatty acids is, however, not widely available. Producing and marketing n-3 fatty acid enriched pork requires regulatory approval, development costs, quality control costs, may increase production costs, and enriched pork has to be tracked to retail and sold for a premium. Mandatory labelling of the n-6/n-3 ratio and the n-3 fatty acid content of pork may help drive production of n-3 fatty acid enriched pork, and open the door to population-based disease prevention polices (i.e., food tax to provide incentives to improve production practices). A shift from the status-quo, however, will require stronger signals along the value chain indicating production of n-3 fatty acid enriched pork is an industry priority.
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