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Buonaiuto G, Cavallini D, Mammi LME, Ghiaccio F, Palmonari A, Formigoni A, Visentin G. The accuracy of NIRS in predicting chemical composition and fibre digestibility of hay-based total mixed rations. ITALIAN JOURNAL OF ANIMAL SCIENCE 2021. [DOI: 10.1080/1828051x.2021.1990804] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Giovanni Buonaiuto
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum - University of Bologna, Ozzano dell'Emilia (BO), Italy
| | - Damiano Cavallini
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum - University of Bologna, Ozzano dell'Emilia (BO), Italy
| | - Ludovica Maria Eugenia Mammi
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum - University of Bologna, Ozzano dell'Emilia (BO), Italy
| | - Francesca Ghiaccio
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum - University of Bologna, Ozzano dell'Emilia (BO), Italy
| | - Alberto Palmonari
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum - University of Bologna, Ozzano dell'Emilia (BO), Italy
| | - Andrea Formigoni
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum - University of Bologna, Ozzano dell'Emilia (BO), Italy
| | - Giulio Visentin
- Dipartimento di Scienze Mediche Veterinarie, Alma Mater Studiorum - University of Bologna, Ozzano dell'Emilia (BO), Italy
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2
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Gomaa WMS, Feng X, Zhang H, Zhang X, Zhang W, Yan X, Peng Q, Yu P. Application of advanced molecular spectroscopy and modern evaluation techniques in canola molecular structure and nutrition property research. Crit Rev Food Sci Nutr 2020; 61:3256-3266. [PMID: 32787447 DOI: 10.1080/10408398.2020.1798343] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
This review aims to provide research update and progress on applications of advanced molecular spectroscopy to current research on canola related bio-processing technology, molecular structure, and nutrient utilization and availability. The studies focused on how inherent molecular structure changes affect nutritional quality of canola and its co-products from bio-processing. The molecular spectroscopic techniques (SR-IMS, DRIFT, ATR-FTIR) used for molecular structure and nutrition association were reviewed, including the synchrotron radiation with infrared microspectroscopy, the synchrotron radiation with soft x-ray microspectroscopy, the diffuse reflectance infrared Fourier transform spectroscopy, the grading near infrared reflectance spectroscopy, and the Fourier transform infrared vibrational spectroscopy. Nutritional evaluation with other techniques in association with molecular structure was also reviewed. This study provides updated research progress on application of molecular spectroscopy in combination with various nutrition evaluation techniques to current research in the canola-related bio-oil/bio-energy processing and nutrition sciences.
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Affiliation(s)
- Walaa M S Gomaa
- Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Canada
| | - Xin Feng
- Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Canada.,School of Life Science and Engineering, Foshan University, Foshan, China
| | - Huihua Zhang
- School of Life Science and Engineering, Foshan University, Foshan, China
| | - Xuewei Zhang
- Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Canada.,College of Animal Science and Animal Veterinary, Tianjin Agricultural University, Tianjin, China
| | - Weixian Zhang
- College of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, China
| | - Xiaogang Yan
- Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Canada.,The Branch Academy of Animal Science, Jilin Academy of Agricultural Science, Gongzhuling, China
| | - Quanhui Peng
- Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Canada.,Animal Nutrition Institute, Sichuan Agricultural University, Ya'an, China
| | - Peiqiang Yu
- Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Canada
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3
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Chapman J, Elbourne A, Truong VK, Cozzolino D. Shining light into meat – a review on the recent advances in
in vivo
and carcass applications of near infrared spectroscopy. Int J Food Sci Technol 2019. [DOI: 10.1111/ijfs.14367] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- James Chapman
- School of Science RMIT University GPO Box 2476 Melbourne Victoria 3001 Australia
| | - Aaron Elbourne
- School of Science RMIT University GPO Box 2476 Melbourne Victoria 3001 Australia
| | - Vi Khanh Truong
- School of Science RMIT University GPO Box 2476 Melbourne Victoria 3001 Australia
| | - Daniel Cozzolino
- School of Science RMIT University GPO Box 2476 Melbourne Victoria 3001 Australia
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4
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Stocco G, Cipolat-Gotet C, Ferragina A, Berzaghi P, Bittante G. Accuracy and biases in predicting the chemical and physical traits of many types of cheeses using different visible and near-infrared spectroscopic techniques and spectrum intervals. J Dairy Sci 2019; 102:9622-9638. [PMID: 31477307 DOI: 10.3168/jds.2019-16770] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 07/06/2019] [Indexed: 11/19/2022]
Abstract
Near-infrared spectroscopy (NIRS) has been widely used to determine various composition traits of many dairy products in the industry. In the last few years, near-infrared (NIR) instruments have become more and more accessible, and now, portable devices can be easily used in the field, allowing the direct measurement of important quality traits. However, the comparison of the predictive performances of different NIR instruments is not simple, and the literature is lacking. These instruments may use different wavelength intervals and calibration procedures, making it difficult to establish whether differences are due to the spectral interval, the chemometric approach, or the instrument's technology. Hence, the aims of this study were (1) to evaluate the prediction accuracy of chemical contents (5 traits), pH, texture (2 traits), and color (5 traits) of 37 categories of cheese; (2) to compare 3 instruments [2 benchtop, working in reflectance (R) and transmittance (T) mode (NIRS-R and NIRS-T, respectively) and 1 portable device (VisNIRS-R)], using their entire spectral ranges (1100-2498, 850-1048, and 350-1830 nm, respectively, for NIRS-R, NIRS-T and VisNIRS-R); (3) to examine different wavelength intervals of the spectrum within instrument, comparing also the common intervals among the 3 instruments; and (4) to determine the presence of bias in predicted traits for specific cheese categories. A Bayesian approach was used to develop 8 calibration models for each of 13 traits. This study confirmed that NIR spectroscopy can be used to predict the chemical composition of a large number of different cheeses, whereas pH and texture traits were poorly predicted. Color showed variable predictability, according to the trait considered, the instrument used, and, within instrument, according to the wavelength intervals. The predictive performance of the VisNIRS-R portable device was generally better than the 2 laboratory NIRS instruments, whether with the entire spectrum or selected intervals. The VisNIRS-R was found suitable for analyzing chemical composition in real time, without the need for sample uptake and processing. Our results also indicated that instrument technology is much more important than the NIR spectral range for accurate prediction equations, but the visible range is useful when predicting color traits, other than lightness. Specifically for certain categories (i.e., caprine, moldy, and fresh cheeses), dedicated calibrations seem to be needed to obtain unbiased and more accurate results.
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Affiliation(s)
- Giorgia Stocco
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy; Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy.
| | - Claudio Cipolat-Gotet
- Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy
| | - Alessandro Ferragina
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
| | - Paolo Berzaghi
- Department of Animal Medicine, Production and Health (MAPS), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
| | - Giovanni Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
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5
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Protected Designation of Origin (PDO), Protected Geographical Indication (PGI) and Traditional Speciality Guaranteed (TSG): A bibiliometric analysis. Food Res Int 2017; 103:492-508. [PMID: 29389640 DOI: 10.1016/j.foodres.2017.09.059] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2017] [Revised: 09/16/2017] [Accepted: 09/21/2017] [Indexed: 11/22/2022]
Abstract
Despite the importance of the literature on food quality labels in the European Union (PDO, PGI and TSG), our search did not find any review joining the various research topics on this subject. This study aims therefore to consolidate the state of academic research in this field, and so the methodological option was to elaborate a bibliometric analysis resorting to the term co-occurrence technique. Analysis was made of 501 articles on the ISI Web of Science database, covering publications up to 2016. The results of the bibliometric analysis allowed identification of four clusters: "Protected Geographical Indication", "Certification of Olive Oil and Cultivars", "Certification of Cheese and Milk" and "Certification and Chemical Composition". Unlike the other clusters, where the PDO label predominates, the "Protected Geographical Indication" cluster covers the study of PGI products, highlighting analysis of consumer behaviour in relation to this type of product. The focus of studies in the "Certification of Olive Oil and Cultivars" cluster and the "Certification of Cheese and Milk" cluster is the development of authentication methods for certified traditional products. In the "Certification and Chemical Composition" cluster, standing out is analysis of the profiles of fatty acids present in this type of product.
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6
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Prieto N, Pawluczyk O, Dugan MER, Aalhus JL. A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products. APPLIED SPECTROSCOPY 2017; 71:1403-1426. [PMID: 28534672 DOI: 10.1177/0003702817709299] [Citation(s) in RCA: 105] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Consumer demand for quality and healthfulness has led to a higher need for quality assurance in meat production. This requirement has increased interest in near-infrared (NIR) spectroscopy due to the ability for rapid, environmentally friendly, and noninvasive prediction of meat quality or authentication of added-value meat products. This review includes the principles of NIR spectroscopy, pre-processing methods, and multivariate analyses used for quantitative and qualitative purposes in the meat sector. Recent advances in portable NIR spectrometers that enable new online applications in the meat industry are shown and their performance evaluated. Discrepancies between published studies and potential sources of variability are discussed, and further research is encouraged to face the challenges of using NIRS technology in commercial applications, so that its full potential can be achieved.
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Affiliation(s)
- Nuria Prieto
- 1 Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, AB, Canada
| | | | | | - Jennifer Lynn Aalhus
- 1 Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, AB, Canada
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7
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Vlachos A, Arvanitoyannis IS, Tserkezou P. An Updated Review of Meat Authenticity Methods and Applications. Crit Rev Food Sci Nutr 2017; 56:1061-96. [PMID: 24915333 DOI: 10.1080/10408398.2012.691573] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Adulteration of foods is a serious economic problem concerning most foodstuffs, and in particular meat products. Since high-priced meat demand premium prices, producers of meat-based products might be tempted to blend these products with lower cost meat. Moreover, the labeled meat contents may not be met. Both types of adulteration are difficult to detect and lead to deterioration of product quality. For the consumer, it is of outmost importance to guarantee both authenticity and compliance with product labeling. The purpose of this article is to review the state of the art of meat authenticity with analytical and immunochemical methods with the focus on the issue of geographic origin and sensory characteristics. This review is also intended to provide an overview of the various currently applied statistical analyses (multivariate analysis (MAV), such as principal component analysis, discriminant analysis, cluster analysis, etc.) and their effectiveness for meat authenticity.
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Affiliation(s)
- Antonios Vlachos
- a Department of Agriculture, Ichthyology, and Aquatic Environment, School of Agricultural Sciences, University of Thessaly , Volos , Hellas , Greece
| | - Ioannis S Arvanitoyannis
- a Department of Agriculture, Ichthyology, and Aquatic Environment, School of Agricultural Sciences, University of Thessaly , Volos , Hellas , Greece
| | - Persefoni Tserkezou
- a Department of Agriculture, Ichthyology, and Aquatic Environment, School of Agricultural Sciences, University of Thessaly , Volos , Hellas , Greece
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8
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Li B, Zhou Y, Zhao M, Hou B, Zhang D, Wang Q, Huang Y. Visible and Near-Infrared Hyper-Spectral Imaging for the Identification of the Type of Wax on Pears. J FOOD PROCESS PRES 2016. [DOI: 10.1111/jfpp.12749] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Baicheng Li
- Ministry of Education Optical Instrument and Systems Engineering Center, and Shanghai Key Laboratory of Modern Optical System; University of Shanghai for Science and Technology; No.516 Jungong Road Shanghai 200093 China
| | - Yao Zhou
- Ministry of Education Optical Instrument and Systems Engineering Center, and Shanghai Key Laboratory of Modern Optical System; University of Shanghai for Science and Technology; No.516 Jungong Road Shanghai 200093 China
| | - Mantong Zhao
- Ministry of Education Optical Instrument and Systems Engineering Center, and Shanghai Key Laboratory of Modern Optical System; University of Shanghai for Science and Technology; No.516 Jungong Road Shanghai 200093 China
| | - Baolu Hou
- Ministry of Education Optical Instrument and Systems Engineering Center, and Shanghai Key Laboratory of Modern Optical System; University of Shanghai for Science and Technology; No.516 Jungong Road Shanghai 200093 China
| | - Dawei Zhang
- Ministry of Education Optical Instrument and Systems Engineering Center, and Shanghai Key Laboratory of Modern Optical System; University of Shanghai for Science and Technology; No.516 Jungong Road Shanghai 200093 China
| | - Qi Wang
- Ministry of Education Optical Instrument and Systems Engineering Center, and Shanghai Key Laboratory of Modern Optical System; University of Shanghai for Science and Technology; No.516 Jungong Road Shanghai 200093 China
| | - Yuanshen Huang
- Ministry of Education Optical Instrument and Systems Engineering Center, and Shanghai Key Laboratory of Modern Optical System; University of Shanghai for Science and Technology; No.516 Jungong Road Shanghai 200093 China
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9
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Hyperspectral imaging for real-time monitoring of water holding capacity in red meat. Lebensm Wiss Technol 2016. [DOI: 10.1016/j.lwt.2015.11.021] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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10
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Calamari L, Ferrari A, Minuti A, Trevisi E. Assessment of the main plasma parameters included in a metabolic profile of dairy cow based on Fourier Transform mid-infrared spectroscopy: preliminary results. BMC Vet Res 2016; 12:4. [PMID: 26739274 PMCID: PMC4704406 DOI: 10.1186/s12917-015-0621-4] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Accepted: 12/16/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Although a metabolic profile represents a valid tool utilized in dairy herds to determine abnormalities in blood chemistry related to an increased risk of production diseases, there are no studies on application of Fourier Transform mid-infrared (FT-MIR) spectroscopy. This study assesses the potential application of FT-MIR to analyze the main blood biochemical parameters included in the metabolic profile of dairy cows. Infrared transmission spectra were acquired for 35 plasma samples (two replicates on each sample) of Italian Friesian dairy cows (14 primiparous and 21 pluriparous), all without clinical events, and at different stages of lactation, although mainly in the transition phase. Each sample was also analyzed independently using accepted reference clinical chemical methods and these results were used as calibrating values to perform predictive models by PLS method using cross validation. RESULTS Measured blood parameters concentrations were all within the reference ranges reported for healthy dairy cows. The number of extracted factors with the PLS procedure for each prediction model ranged between 3 and 7. The coefficient of determination (R(2)) of the prediction models ranged between 0.1 to values close to 1. R(2) values greater than 0.9 were observed for the prediction models of total cholesterol, total protein, globulin, and albumin; values between 0.75 and 0.9 were observed for urea, NEFA, and total bilirubin, while values of R(2) lower than 0.6 were observed for all minerals and for enzyme activity. The range error ratio (RER) and prediction to deviation (RPD) ranged from 5.1 to 43.8 and from 1 to 13.8 for RER and RPD, respectively. Values of RPD greater than 5 were observed for total cholesterol, total protein, albumin, and globulin. RPD ranged between 2 and 5 for the prediction models of urea, NEFA, and total bilirubin, while RPD and RER were low for minerals and enzyme activities. CONCLUSIONS Although the results of this study require further validation, the use of FT-MIR spectroscopy was possible and provides fairly accurate measurement of various parameters of great importance in the evaluation of the metabolic and inflammatory status in dairy cows.
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Affiliation(s)
- Luigi Calamari
- Istituto di Zootecnica, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, Piacenza, 29122, Italy.
| | - Annarita Ferrari
- Istituto di Zootecnica, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, Piacenza, 29122, Italy.
| | - Andrea Minuti
- Istituto di Zootecnica, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, Piacenza, 29122, Italy.
| | - Erminio Trevisi
- Istituto di Zootecnica, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del Sacro Cuore, Piacenza, 29122, Italy.
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12
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Wu D, Sun DW. Application of visible and near infrared hyperspectral imaging for non-invasively measuring distribution of water-holding capacity in salmon flesh. Talanta 2013; 116:266-76. [DOI: 10.1016/j.talanta.2013.05.030] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2012] [Revised: 05/08/2013] [Accepted: 05/14/2013] [Indexed: 10/26/2022]
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13
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Novel non-invasive distribution measurement of texture profile analysis (TPA) in salmon fillet by using visible and near infrared hyperspectral imaging. Food Chem 2013; 145:417-26. [PMID: 24128497 DOI: 10.1016/j.foodchem.2013.08.063] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2012] [Revised: 03/08/2013] [Accepted: 08/14/2013] [Indexed: 11/22/2022]
Abstract
This study developed a pushbroom visible and near-infrared hyperspectral imaging system in the wavelength range of 400-1758 nm to determine the spatial distribution of texture profile analysis (TPA) parameters of salmon fillets. Six TPA parameters (hardness, adhesiveness, chewiness, springiness, cohesiveness, and gumminess) were analysed. Five spectral features (mean, standard deviation, skew, energy, and entropy) and 22 image texture features obtained from graylevel co-occurrence matrix (GLCM) were extracted from hyperspectral images. Quantitative models were established with the extracted spectral and image texture signatures of samples based on partial least squares regression (PLSR). The results indicated that spectral features had better ability to predict TPA parameters of salmon samples than image texture features, and Spectral Set I (400-1000 nm) performed better than Spectral II (967-1634 nm). On the basis of the wavelengths selected by regression coefficients of PLSR models, instrumental optimal wavelengths (IOW) and predictive optimal wavelengths (POW) were further chosen to reduce the high dimensionality of the hyperspectral image data. Our results show that hyperspectral imaging holds promise as a reliable and rapid alternative to traditional universal testing machines for measuring the spatial distribution of TPA parameters.
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Peiretti PG, Meineri G, Masoero G. NIRS of body and tissues in growing rabbits fed diets with different fat sources and supplemented with Curcuma longa. WORLD RABBIT SCIENCE 2013. [DOI: 10.4995/wrs.2013.1148] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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15
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Vibrational Spectroscopy. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/b978-0-444-59562-1.00005-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
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16
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Wu D, Sun DW, He Y. Application of long-wave near infrared hyperspectral imaging for measurement of color distribution in salmon fillet. INNOV FOOD SCI EMERG 2012. [DOI: 10.1016/j.ifset.2012.08.003] [Citation(s) in RCA: 146] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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17
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ElMasry G, Sun DW, Kamruzzaman M, Barbin D, Allen P. Hyperspectral Imaging—A New Era of Applications in Non-Destructive Sensing of Meat Quality. ACTA ACUST UNITED AC 2012. [DOI: 10.1255/nirn.1322] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Gamal ElMasry
- FRCFT, School of Biosystems Engineering, University College Dublin (UCD), Belfield, Dublin 4, Ireland
- Agricultural Engineering Department, Faculty of Agriculture, Suez Canal University, Ismailia, Egypt
| | - Da-Wen Sun
- FRCFT, School of Biosystems Engineering, University College Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Mohammed Kamruzzaman
- FRCFT, School of Biosystems Engineering, University College Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Douglas Barbin
- FRCFT, School of Biosystems Engineering, University College Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Paul Allen
- Ashtown Food Research Centre (AFRC), Teagasc, Dublin 15, Ireland
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Tres A, van der Veer G, Perez-Marin MD, van Ruth SM, Garrido-Varo A. Authentication of organic feed by near-infrared spectroscopy combined with chemometrics: a feasibility study. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2012; 60:8129-8133. [PMID: 22844991 DOI: 10.1021/jf302309t] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Organic products tend to retail at a higher price than their conventional counterparts, which makes them susceptible to fraud. In this study we evaluate the application of near-infrared spectroscopy (NIRS) as a rapid, cost-effective method to verify the organic identity of feed for laying hens. For this purpose a total of 36 organic and 60 conventional feed samples from The Netherlands were measured by NIRS. A binary classification model (organic vs conventional feed) was developed using partial least squares discriminant analysis. Models were developed using five different data preprocessing techniques, which were externally validated by a stratified random resampling strategy using 1000 realizations. Spectral regions related to the protein and fat content were among the most important ones for the classification model. The models based on data preprocessed using direct orthogonal signal correction (DOSC), standard normal variate (SNV), and first and second derivatives provided the most successful results in terms of median sensitivity (0.91 in external validation) and median specificity (1.00 for external validation of SNV models and 0.94 for DOSC and first and second derivative models). A previously developed model, which was based on fatty acid fingerprinting of the same set of feed samples, provided a higher sensitivity (1.00). This shows that the NIRS-based approach provides a rapid and low-cost screening tool, whereas the fatty acid fingerprinting model can be used for further confirmation of the organic identity of feed samples for laying hens. These methods provide additional assurance to the administrative controls currently conducted in the organic feed sector.
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Affiliation(s)
- A Tres
- RIKILT, Wageningen University and Research Centre, P.O. Box 230, 6700 AE Wageningen, The Netherlands.
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Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging. Food Res Int 2011. [DOI: 10.1016/j.foodres.2011.05.001] [Citation(s) in RCA: 219] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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