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Fan Y, Liao J, Zhou Q, Liu Y, Che L, Tang J. Rapid prediction of the chemical composition of pet food using a benchtop and handheld near-infrared spectrometer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 323:124916. [PMID: 39096679 DOI: 10.1016/j.saa.2024.124916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 07/29/2024] [Accepted: 07/29/2024] [Indexed: 08/05/2024]
Abstract
Quality of pet foods can be affected by many factors such as raw materials, formulations, and processing techniques. The pet food manufacturers require fast analyses to control the nutritional quality of their products. Herein, near-infrared spectroscopy (NIR) was evaluated to quantify the chemical composition of pet food, and the performances of two NIR spectrometers were investigated and compared: a benchtop instrument (1000-2500 nm) and a low-cost handheld instrument (900-1700 nm). Seventy cat food and thirty-six dog samples were characterized using reference methods for crude protein, crude fat, crude fibre, crude ash, moisture, calcium (Ca), and phosphorus (P). Principal component regression (PCR) and partial least squares regression (PLSR) were used to establish the models that involved the cat food and mixed model. The characteristic wavelengths were selected using a competitive adaptive reweighted-sampling (CARS) algorithm. The Optimal models obtained from the benchtop instrument for crude protein, crude fat, and moisture were classified as "Good" or "Very good" (Residual prediction variation (RPD) > 3), for crude fibre were classified as "Poor" (RPD>2), and for crude ash, Ca and P (RPD<2) were classified as "Very poor". The Optimal calibrations obtained from the handheld instrument for crude protein, crude fat, and moisture were classified as "Good" or "Very good" (RPD>3), for crude fibre, crude ash, Ca, and P were classified as "Very poor" (RPD<2). Generally, the the performance of benchtop and handheld instrument was close, and the cat food model outperformed the mixed model. Results from the current study revealed the potential to monitor the chemical compositions in pet food on a large scale.
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Affiliation(s)
- Yang Fan
- College of Life Science, Sichuan Agricultural University, Yaan 625014, China.
| | - Jinqiu Liao
- College of Life Science, Sichuan Agricultural University, Yaan 625014, China.
| | - Qiang Zhou
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China.
| | - Yang Liu
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China.
| | - Lianqiang Che
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China.
| | - Jiayong Tang
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China.
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2
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Godbout JM, Ladizinsky NC, Harris S, Postler ML, Sun X, Matsumoto T, Liang P. Non-destructive identification of varieties of Hawaii-grown avocados using near-infrared spectroscopy: Feasibility studies using bench-top and handheld spectrometers. PLoS One 2024; 19:e0303532. [PMID: 38843189 PMCID: PMC11156329 DOI: 10.1371/journal.pone.0303532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 04/26/2024] [Indexed: 06/09/2024] Open
Abstract
Avocados are an important economic crop of Hawaii, contributing to approximately 3% of all avocados grown in the United States. To export Hawaii-grown avocados, growers must follow strict United States Department of Agriculture Animal and Plant Health Inspection Service (USDA-APHIS) regulations. Currently, only the Sharwil variety can be exported relying on a systems approach, which allows fruit to be exported without quarantine treatment; treatments that can negatively impact the quality of avocados. However, for the systems approach to be applied, Hawaii avocado growers must positively identify the avocados variety as Sharwil with APHIS prior to export. Currently, variety identification relies on physical characteristics, which can be erroneous and subjective, and has been disputed by growers. Once the fruit is harvested, variety identification is difficult. While molecular markers can be used through DNA extraction from the skin, the process leaves the fruit unmarketable. This study evaluated the feasibility of using near-infrared spectroscopy to non-destructively discriminate between different Hawaii-grown avocado varieties, such as Sharwil, Beshore, and Yamagata, Nishikawa, and Greengold, and to positively identify Sharwil from the other varieties mentioned above. The classifiers built using a bench-top system achieved 95% total classification rates for both discriminating the varieties from one another and positively identifying Sharwil while the classifier built using a handheld spectrometer achieved 96% and 96.7% total classification rates for discriminating the varieties from one another and positively identifying Sharwil, respectively. Results from chemometric methods and chemical analysis suggested that water and lipid were key contributors to the performance of classifiers. The positive results demonstrate the feasibility of NIR spectroscopy for discriminating different avocado varieties as well as authenticating Sharwil. To develop robust and stable models for the growers, distributors, and regulators in Hawaii, more varieties and additional seasons should continue to be added.
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Affiliation(s)
- Jemma M. Godbout
- University of Hawaii at Hilo, Pacific Internship Program for Exploring Science, Hilo, Hawaii, United States of America
- USDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America
| | - Nicolas C. Ladizinsky
- USDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America
| | - Serenity Harris
- University of Hawaii at Hilo, Department of Physics and Astronomy, Hilo, Hawaii, United States of America
| | - Melissa L. Postler
- USDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America
| | - Xiuxiu Sun
- USDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America
| | - Tracie Matsumoto
- USDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America
| | - Peishih Liang
- USDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America
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Guzmán JL, Zarazaga LÁ, Martín-García AI, Delgado-Pertíñez M. Feeding Dairy Goats Dehydrated Orange Pulp Improves Cheese Antioxidant Content. Vet Sci 2024; 11:171. [PMID: 38668438 PMCID: PMC11053964 DOI: 10.3390/vetsci11040171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 04/29/2024] Open
Abstract
Agroindustrial by-products constitute an alternative source of feed livestock, and their use contributes to the sustainability of livestock systems and the circular bioeconomy. The effects of replacing cereal (0%, 40%, and 80%) with dehydrated orange pulp (DOP) in the diet of goats on the antioxidant and fatty acid (FA) contents of cheeses were evaluated. For a more suitable understanding of the role of coagulant enzymes in establishing the properties of the cheese, the effect of milk-clotting with animal and vegetable rennet was also analysed. The rennet did not substantially affect the FA or the antioxidant compounds, and the use of DOP did not affect the FA contents. However, the α-tocopherol levels, total phenolic compounds (TPC), and total antioxidant capacity (TAC) in cheeses increased as the percentage of DOP replacing cereals increased. Moreover, the high correlation obtained between the TAC and the TPC (r = 0.73) and α-tocopherol (r = 0.62) contents indicated the important role played by these compounds in improving the antioxidant capacity of the cheese. In conclusion, DOP is a suitable alternative to cereals in the diet of goats and improves the antioxidant status of the cheese produced.
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Affiliation(s)
- José Luis Guzmán
- Departamento de Ciencias Agroforestales, Escuela Técnica Superior de Ingeniería, Universidad de Huelva, “Campus de Excelencia Internacional Agroalimentario, ceiA3”, Campus de la Rábida, 21819 Palos de la Frontera, Spain; (J.L.G.); (L.Á.Z.)
| | - Luis Ángel Zarazaga
- Departamento de Ciencias Agroforestales, Escuela Técnica Superior de Ingeniería, Universidad de Huelva, “Campus de Excelencia Internacional Agroalimentario, ceiA3”, Campus de la Rábida, 21819 Palos de la Frontera, Spain; (J.L.G.); (L.Á.Z.)
| | | | - Manuel Delgado-Pertíñez
- Departamento de Agronomía, Escuela Técnica Superior de Ingeniería Agronómica, Universidad de Sevilla, Ctra. Utrera km 1, 41013 Sevilla, Spain
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Solberg LE, Wold JP, Dankel K, Øyaas J, Måge I. In-Line Near-Infrared Spectroscopy Gives Rapid and Precise Assessment of Product Quality and Reveals Unknown Sources of Variation-A Case Study from Commercial Cheese Production. Foods 2023; 12:foods12051026. [PMID: 36900546 PMCID: PMC10001380 DOI: 10.3390/foods12051026] [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: 01/14/2023] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 03/06/2023] Open
Abstract
Quality testing in the food industry is usually performed by manual sampling and at/off-line laboratory analysis, which is labor intensive, time consuming, and may suffer from sampling bias. For many quality attributes such as fat, water and protein, in-line near-infrared spectroscopy (NIRS) is a viable alternative to grab sampling. The aim of this paper is to document some of the benefits of in-line measurements at the industrial scale, including higher precision of batch estimates and improved process understanding. Specifically, we show how the decomposition of continuous measurements in the frequency domain, using power spectral density (PSD), may give a useful view of the process and serve as a diagnostic tool. The results are based on a case regarding the large-scale production of Gouda-type cheese, where in-line NIRS was implemented to replace traditional laboratory measurements. In conclusion, the PSD of in-line NIR predictions revealed unknown sources of variation in the process that could not have been discovered using grab sampling. PSD also gave the dairy more reliable data on key quality attributes, and laid the foundation for future improvements.
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Affiliation(s)
- Lars Erik Solberg
- Nofima—Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291 Tromsø, Norway
- Correspondence:
| | - Jens Petter Wold
- Nofima—Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291 Tromsø, Norway
| | - Katinka Dankel
- Nofima—Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291 Tromsø, Norway
| | | | - Ingrid Måge
- Nofima—Norwegian Institute for Food, Fisheries and Aquaculture Research, Muninbakken 9-13, Breivika, 9291 Tromsø, Norway
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García-García MDC, Martín-Expósito E, Font I, Martínez-García BDC, Fernández JA, Valenzuela JL, Gómez P, del Río-Celestino M. Determination of Quality Parameters in Mangetout ( Pisum sativum L. ssp. arvense) by Using Vis/Near-Infrared Reflectance Spectroscopy. SENSORS (BASEL, SWITZERLAND) 2022; 22:4113. [PMID: 35684734 PMCID: PMC9185268 DOI: 10.3390/s22114113] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 12/19/2022]
Abstract
Pisum sativum L. ssp. arvense, is colloquially called tirabeque or mangetout because it is eaten whole; its pods are recognized as a delicatessen in cooking due to its crunch on the palate and high sweetness. Furthermore, this legume is an important source of protein and antioxidant compounds. Quality control in this species requires the analysis of a large number of samples using costly and laborious conventional methods. For this reason, a non-chemical and rapid technique as near-infrared reflectance spectroscopy (NIRS) was explored to determine its physicochemical quality (color, firmness, total soluble solids, pH, total polyphenols, ascorbic acid and protein content). Pod samples from different cultivars and grown under different fertigation treatments were added to the NIRS analysis to increase spectral and chemical variability in the calibration set. Modified partial least squares regression was used for obtaining the calibration models of these parameters. The coefficients of determination in the external validation ranged from 0.50 to 0.88. The RPD (standard deviation to standard error of prediction ratio) and RER (standard deviation to range) were variable for quality parameters and showed values that were characteristic of equations suitable for quantitative prediction and screening purposes, except for the total soluble solid calibration model.
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Affiliation(s)
| | - Emilio Martín-Expósito
- Department of Agro-Food Engineering and Technology, IFAPA Centro La Mojonera, CAGPDS, 04745 Almería, Spain;
| | - Isabel Font
- ETSIIT, Campus Aynadamar, University of Granada, 18071 Granada, Spain;
| | | | - Juan A. Fernández
- Department of Agronomical Engineering, Technical University of Cartagena, 30203 Murcia, Spain;
| | - Juan Luis Valenzuela
- Department of Biology and Geology, Higher Engineering School, University of Almería, 04120 Almería, Spain;
| | - Pedro Gómez
- Department of Plant Breeding and Biotechnology, IFAPA Centro La Mojonera, CAGPDS, 04745 Almería, Spain;
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Stobiecka M, Król J, Brodziak A. Antioxidant Activity of Milk and Dairy Products. Animals (Basel) 2022; 12:245. [PMID: 35158569 PMCID: PMC8833589 DOI: 10.3390/ani12030245] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 12/30/2021] [Accepted: 01/16/2022] [Indexed: 02/06/2023] Open
Abstract
The aim of the study was to present a review of literature data on the antioxidant potential of raw milk and dairy products (milk, fermented products, and cheese) and the possibility to modify its level at the milk production and processing stage. Based on the available reports, it can be concluded that the consumption of products that are a rich source of bioactive components improves the antioxidant status of the organism and reduces the risk of development of many civilization diseases. Milk and dairy products are undoubtedly rich sources of antioxidant compounds. Various methods, in particular, ABTS, FRAP, and DPPH assays, are used for the measurement of the overall antioxidant activity of milk and dairy products. Research indicates differences in the total antioxidant capacity of milk between animal species, which result from the differences in the chemical compositions of their milk. The content of antioxidant components in milk and the antioxidant potential can be modified through animal nutrition (e.g., supplementation of animal diets with various natural additives (herbal mixtures, waste from fruit and vegetable processing)). The antioxidant potential of dairy products is associated with the quality of the raw material as well as the bacterial cultures and natural plant additives used. Antioxidant peptides released during milk fermentation increase the antioxidant capacity of dairy products, and the use of probiotic strains contributes its enhancement. Investigations have shown that the antioxidant activity of dairy products can be enhanced by the addition of plant raw materials or their extracts in the production process. Natural plant additives should therefore be widely used in animal nutrition or as functional additives to dairy products.
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Affiliation(s)
| | - Jolanta Król
- Department of Quality Assessment and Processing of Animal Products, Faculty of Animal Sciences and Bioeconomy, University of Life Sciences in Lublin, Akademicka 13, 20-950 Lublin, Poland; (M.S.); (A.B.)
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7
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Bittante G, Patel N, Cecchinato A, Berzaghi P. Invited review: A comprehensive review of visible and near-infrared spectroscopy for predicting the chemical composition of cheese. J Dairy Sci 2022; 105:1817-1836. [PMID: 34998561 DOI: 10.3168/jds.2021-20640] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 09/26/2021] [Indexed: 11/19/2022]
Abstract
Substantial research has been carried out on rapid, nondestructive, and inexpensive techniques for predicting cheese composition using spectroscopy in the visible and near-infrared radiation range. Moreover, in recent years, new portable and handheld spectrometers have been used to predict chemical composition from spectra captured directly on the cheese surface in dairies, storage facilities, and food plants, removing the need to collect, transport, and process cheese samples. For this review, we selected 71 papers (mainly dealing with prediction of the chemical composition of cheese) and summarized their results, focusing our attention on the major sources of variation in prediction accuracy related to cheese variability, spectrometer and spectra characteristics, and chemometrics techniques. The average coefficient of determination obtained from the validation samples ranged from 86 to 90% for predicting the moisture, fat, and protein contents of cheese, but was lower for predicting NaCl content and cheese pH (79 and 56%, respectively). There was wide variability with respect to all traits in the results of the various studies (standard deviation: 9-30%). This review draws attention to the need for more robust equations for predicting cheese composition in different situations; the calibration data set should consist of representative cheese samples to avoid bias due to an overly specific field of application and ensure the results are not biased for a particular category of cheese. Different spectrometers have different accuracies, which do not seem to depend on the spectrum extension. Furthermore, specific areas of the spectrum-the visible, infrared-A, or infrared-B range-may yield similar results to broad-range spectra; this is because several signals related to cheese composition are distributed along the spectrum. Small, portable instruments have been shown to be viable alternatives to large bench-top instruments. Last, chemometrics (spectra pre-treatment and prediction models) play an important role, especially with regard to difficult-to-predict traits. A proper, fully independent, validation strategy is essential to avoid overoptimistic results.
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Affiliation(s)
- Giovanni Bittante
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE) University of Padova (Padua), 35020 Legnaro, Italy
| | - Nageshvar Patel
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE) University of Padova (Padua), 35020 Legnaro, Italy
| | - Alessio Cecchinato
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE) University of Padova (Padua), 35020 Legnaro, Italy.
| | - Paolo Berzaghi
- Department of Animal Medicine, Production and Health (MAPS), University of Padova (Padua), 35020 Legnaro, Italy
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8
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Manuelian CL, Ghetti M, De Lorenzi C, Pozza M, Franzoi M, De Marchi M. Feasibility of pocket-sized near-infrared spectrometer for the prediction of cheese quality traits. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2021.104245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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9
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Effectiveness of two different at-line instruments for the assessment of cheese composition, major minerals and fatty acids content. Int Dairy J 2021. [DOI: 10.1016/j.idairyj.2021.105184] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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10
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Optimizing near Infrared Reflectance Spectroscopy to Predict Nutritional Quality of Chickpea Straw for Livestock Feeding. Animals (Basel) 2021; 11:ani11123409. [PMID: 34944187 PMCID: PMC8697932 DOI: 10.3390/ani11123409] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 11/25/2021] [Accepted: 11/27/2021] [Indexed: 11/17/2022] Open
Abstract
Simple Summary The potential of near infrared reflectance spectroscopy (NIRS) to predict the nutritive value of chickpea straw was identified. Spectral data of 480 samples of chickpea straw (40 genotypes) were scanned with a spectral range of 1108 to 2492 nm. The samples were reduced to 190 representative samples based on the spectral data then divided into a calibration set (160 samples) and a cross-validation set (30 samples). All 190 samples were analysed for dry matter, ash, crude protein, neutral detergent fibre, acid detergent fibre, acid detergent lignin, Zn, Mn, Ca, Mg, Fe, P, and in vitro gas production metabolizable energy using conventional methods. The prediction equations were generated by multiple regression analysis. The NIRS prediction equations in the study accurately predicted the nutritive value of chickpea straw (R2 of cross validation > 0.68; standard error of prediction < 1%). Chickpea straw nutritive value could be predicted using NIRS. Abstract Multidimensional improvement programs of chickpea require screening of a large number of genotypes for straw nutritive value. The ability of near infrared reflectance spectroscopy (NIRS) to determine the nutritive value of chickpea straw was identified in the current study. A total of 480 samples of chickpea straw representing a nation-wide range of environments and genotypic diversity (40 genotypes) were scanned at a spectral range of 1108 to 2492 nm. The samples were reduced to 190 representative samples based on the spectral data then divided into a calibration set (160 samples) and a cross-validation set (30 samples). All 190 samples were analysed for dry matter, ash, crude protein, neutral detergent fibre, acid detergent fibre, acid detergent lignin, Zn, Mn, Ca, Mg, Fe, P, and in vitro gas production metabolizable energy using conventional methods. Multiple regression analysis was used to build the prediction equations. The prediction equation generated by the study accurately predicted the nutritive value of chickpea straw (R2 of cross validation > 0.68; standard error of prediction < 1%). Breeding programs targeting improving food-feed traits of chickpea could use NIRS as a fast, cheap, and reliable tool to screen genotypes for straw nutritional quality.
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Simoni M, Goi A, De Marchi M, Righi F. The use of visible/near-infrared spectroscopy to predict fibre fractions, fibre-bound nitrogen and total-tract apparent nutrients digestibility in beef cattle diets and faeces. ITALIAN JOURNAL OF ANIMAL SCIENCE 2021. [DOI: 10.1080/1828051x.2021.1924884] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Marica Simoni
- Dipartimento di Scienze Medico-Veterinarie,University of Parma, Parma, Italy
| | - Arianna Goi
- Dipartimento di Agronomia, Alimenti, Risorse Naturali, Animali e Ambiente, University of Padova, Padova, Italy
| | - Massimo De Marchi
- Dipartimento di Agronomia, Alimenti, Risorse Naturali, Animali e Ambiente, University of Padova, Padova, Italy
| | - Federico Righi
- Dipartimento di Scienze Medico-Veterinarie,University of Parma, Parma, Italy
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12
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Moscovici Joubran A, Pierce KM, Garvey N, Shalloo L, O'Callaghan TF. Invited review: A 2020 perspective on pasture-based dairy systems and products. J Dairy Sci 2021; 104:7364-7382. [PMID: 33865573 DOI: 10.3168/jds.2020-19776] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 03/02/2021] [Indexed: 11/19/2022]
Abstract
Grazing pasture is the basis for dairy production systems in regions with temperate climates, such as in Ireland, New Zealand, parts of Australia, the United States, and Europe. Milk and dairy products from cows on pasture-based farms predominantly consuming fresh grazed grass (typically classified as "grass-fed" milk) have been previously shown to possess a different nutrient profile, with potential nutritional benefits, compared with conventional milk derived from total mixed ration. Moreover, pasture-based production systems are considered more environmentally and animal welfare friendly by consumers. As such, there is significant potential for market capitalization on grass-fed dairy products. As competition in this space increases, the regulations of what constitutes as grass-fed vary between different regions of the world. With this in mind, there is a need for clear and independently accredited grass-fed standards, defining the grass-fed criteria for labeling of products as such, subsequently increasing the clarity and confidence for the consumer. This review outlines the numerous effects of pasture production systems on dairy product composition, nutritional profile, and sustainability, and highlights potential future methods for authentication.
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Affiliation(s)
- Alice Moscovici Joubran
- Food For Health Ireland, University College Dublin, Dublin D04 V1W8, Ireland; School of Agriculture and Food Science, University College Dublin, Dublin D04 V1W8, Ireland
| | - Karina M Pierce
- Food For Health Ireland, University College Dublin, Dublin D04 V1W8, Ireland; School of Agriculture and Food Science, University College Dublin, Dublin D04 V1W8, Ireland
| | - Niamh Garvey
- Food For Health Ireland, University College Dublin, Dublin D04 V1W8, Ireland
| | - Laurence Shalloo
- Teagasc Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork P61 C996, Ireland
| | - Tom F O'Callaghan
- Food For Health Ireland, University College Dublin, Dublin D04 V1W8, Ireland; Teagasc Food Research, Moorepark, Fermoy, Co. Cork P61 C996, Ireland; School of Food and Nutritional Sciences, University College Cork, Cork T12 K8AF, Ireland.
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13
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Saugo M, Franzoi M, Niero G, De Marchi M. Mineral equilibrium in commercial curd and predictive ability of near-infrared spectroscopy. J Dairy Sci 2021; 104:3947-3955. [PMID: 33485688 DOI: 10.3168/jds.2020-18712] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 10/26/2020] [Indexed: 11/19/2022]
Abstract
Curd samples (n = 83) from 3 European dairy companies were analyzed for micellar and soluble mineral fractions content using inductively coupled plasma optical emission spectrometry as a gold standard method. The same curd samples were analyzed through 3 different near-infrared (NIR) instruments, and NIR spectra were merged with reference data. Prediction equations were developed using modified partial least squares analysis, and the accuracy of prediction was evaluated through leave-one-out cross validation. Overall, NIR spectroscopy was capable of predicting micellar and soluble mineral fractions in curd, but with differences among instruments. Fitting statistics showed that the visible NIR instrument in reflectance mode outperformed the NIR instrument in transmittance mode as well as the portable NIR instrument in reflectance mode. Prediction accuracies for most of the analyzed mineral fractions can be used for curd quality control in dairy companies and to aid in decision-making during the cheesemaking process.
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Affiliation(s)
- M Saugo
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - M Franzoi
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - G Niero
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
| | - M De Marchi
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
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14
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Loudiyi M, Temiz HT, Sahar A, Haseeb Ahmad M, Boukria O, Hassoun A, Aït-Kaddour A. Spectroscopic techniques for monitoring changes in the quality of milk and other dairy products during processing and storage. Crit Rev Food Sci Nutr 2020; 62:3063-3087. [PMID: 33381982 DOI: 10.1080/10408398.2020.1862754] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The application of spectroscopic techniques can help in alleviating problems encountered during the processing of milk and dairy products. Indeed, traditional analytical methods (e.g., physicochemical measurements, sensory, chromatography) are relatively expensive, time-consuming, and require chemicals and sophisticated analytical equipment, and skilled operators. Hence, there is a need to develop faster and less costly methods for accurately monitoring changes in the quality of milk and other dairy products during processing and storage.Many nondestructive and noninvasive instrumental techniques are available for inline and online monitoring of food. These include fluorescence spectroscopy, mid-infrared (MIR), near-infrared (NIR), nuclear magnetic resonance (NMR), etc. These techniques are usually used in combination with chemometric tools a to explore the information present in spectral data.This review article will discuss the potential of the above-mentioned spectroscopic techniques for monitoring chemical modifications of dairy products and the prediction of their functional properties during processing. The advantages and disadvantages of each technique are also discussed in this review. Finally, some conclusions are drawn, and the future trends of these methods are presented.
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Affiliation(s)
| | | | - Amna Sahar
- Department of Food Engineering/National Institute of Food Science and Technology, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | | | - Oumayma Boukria
- Applied Organic Chemistry Laboratory, Sciences and Techniques Faculty, Sidi Mohamed Ben Abedallah University, Fez, Morocco
| | - Abdo Hassoun
- Nofima, Norwegian Institute of Food, Norway Tromsø
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15
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Predicting the Electric Conductivity and Potassium Leaching of Coffee by NIR Spectroscopy Technique. FOOD ANAL METHOD 2020. [DOI: 10.1007/s12161-020-01843-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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16
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Rebellato AP, Caramês ETDS, Moraes PPD, Pallone JAL. Minerals assessment and sodium control in hamburger by fast and green method and chemometric tools. Lebensm Wiss Technol 2020. [DOI: 10.1016/j.lwt.2020.109438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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17
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Soulat J, Andueza D, Graulet B, Girard CL, Labonne C, Aït-Kaddour A, Martin B, Ferlay A. Comparison of the Potential Abilities of Three Spectroscopy Methods: Near-Infrared, Mid-Infrared, and Molecular Fluorescence, to Predict Carotenoid, Vitamin and Fatty Acid Contents in Cow Milk. Foods 2020; 9:foods9050592. [PMID: 32384636 PMCID: PMC7278693 DOI: 10.3390/foods9050592] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/30/2020] [Accepted: 05/01/2020] [Indexed: 12/20/2022] Open
Abstract
The objective of this work is to compare the ability of three spectroscopy techniques: molecular fluorescence, near-infrared (NIR), and mid-infrared with attenuated total reflectance (MIR-ATR) spectroscopy to predict the concentrations of 8 carotenoids, 6 vitamins and 22 fatty acids (FA) in cow’s milk. A dataset was built through the analysis of 242 frozen milk samples from different experiments. The milk compounds were analysed using reference methods and by NIR, MIR-ATR, and fluorescence to establish different predictive models. NIR spectroscopy allowed for better prediction of cis9-β-carotene, β-cryptoxanthin and the sum of carotenoids than the other techniques, with a coefficient of cross-validation in calibration (R2CV) > 0.60 and a coefficient of determination in validation (R2V) > 0.50. Their standard errors of prediction (SEP) were equal to 0.01, except for the sum of carotenoids (SEP = 0.15). However, MIR-ATR and fluorescence seem usable for the prediction of lutein and all-trans-β-carotene, respectively. These three spectroscopy methods did not allow us to predict (R2CV < 0.30) vitamin contents except, for vitamin A (the best R²CV = 0.65 with NIR and SEP = 0.15) and α-tocopherol (the best R²CV = 0.56 with MIR-ATR and SEP = 0.41), but all R²V were <0.30. NIR spectroscopy yielded the best prediction of the selected milk FA.
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Affiliation(s)
- Julien Soulat
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France; (J.S.); (D.A.); (B.G.); (C.L.); (B.M.)
| | - Donato Andueza
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France; (J.S.); (D.A.); (B.G.); (C.L.); (B.M.)
| | - Benoît Graulet
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France; (J.S.); (D.A.); (B.G.); (C.L.); (B.M.)
| | - Christiane L. Girard
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC J1M 0C8, Canada;
| | - Cyril Labonne
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France; (J.S.); (D.A.); (B.G.); (C.L.); (B.M.)
| | | | - Bruno Martin
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France; (J.S.); (D.A.); (B.G.); (C.L.); (B.M.)
| | - Anne Ferlay
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France; (J.S.); (D.A.); (B.G.); (C.L.); (B.M.)
- Correspondence: ; Tel.: +33(0)-4-73-62-45-13
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18
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Estimation of ‘Hass’ Avocado (Persea americana Mill.) Ripeness by Fluorescence Fingerprint Measurement. FOOD ANAL METHOD 2020. [DOI: 10.1007/s12161-020-01705-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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19
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Nondestructive VIS/NIR spectroscopy estimation of intravitelline vitamin E and cholesterol concentration in hen shell eggs. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2020. [DOI: 10.1007/s11694-019-00361-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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20
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Goi A, Manuelian CL, Currò S, Marchi MD. Prediction of Mineral Composition in Commercial Extruded Dry Dog Food by Near-Infrared Reflectance Spectroscopy. Animals (Basel) 2019; 9:ani9090640. [PMID: 31480585 PMCID: PMC6770719 DOI: 10.3390/ani9090640] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 08/22/2019] [Accepted: 08/29/2019] [Indexed: 12/19/2022] Open
Abstract
The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850-2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination; R2 = 0.89), K (R2 = 0.85), and Li (R2 = 0.74), followed by P, B, and Sr (R2 = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules.
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Affiliation(s)
- Arianna Goi
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - Carmen L Manuelian
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
| | - Sarah Currò
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - Massimo De Marchi
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
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21
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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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22
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Wiedemair V, Langore D, Garsleitner R, Dillinger K, Huck C. Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis. Molecules 2019; 24:E428. [PMID: 30682872 PMCID: PMC6385083 DOI: 10.3390/molecules24030428] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 01/18/2019] [Accepted: 01/22/2019] [Indexed: 11/16/2022] Open
Abstract
The performance of a newly developed pocket-sized near-infrared (NIR) spectrometer was investigated by analysing 46 cheese samples for their water and fat content, and comparing results with a benchtop NIR device. Additionally, the automated data analysis of the pocket-sized spectrometer and its cloud-based data analysis software, designed for laypeople, was put to the test by comparing performances to a highly sophisticated multivariate data analysis software. All developed partial least squares regression (PLS-R) models yield a coefficient of determination (R²) of over 0.9, indicating high correlation between spectra and reference data for both spectrometers and all data analysis routes taken. In general, the analysis of grated cheese yields better results than whole pieces of cheese. Additionally, the ratios of performance to deviation (RPDs) and standard errors of prediction (SEPs) suggest that the performance of the pocket-sized spectrometer is comparable to the benchtop device. Small improvements are observable, when using sophisticated data analysis software, instead of automated tools.
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Affiliation(s)
- Verena Wiedemair
- CCB-Center for Chemistry and Biomedicine, Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria.
| | - Dominik Langore
- CCB-Center for Chemistry and Biomedicine, Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria.
| | - Roman Garsleitner
- Chemical devision, HBLFA für Landwirtschaft und Ernährung, Lebensmittel und Biotechnologie Tirol,Rotholz 50a, 6200 Strass im Zillertal, Austria.
| | - Klaus Dillinger
- Chemical devision, HBLFA für Landwirtschaft und Ernährung, Lebensmittel und Biotechnologie Tirol,Rotholz 50a, 6200 Strass im Zillertal, Austria.
| | - Christian Huck
- CCB-Center for Chemistry and Biomedicine, Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria.
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23
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Fu H, Hu O, Xu L, Fan Y, Shi Q, Guo X, Lan W, Yang T, Xie S, She Y. Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid- and Near-Infrared Spectroscopy Coupled with Chemometrics. JOURNAL OF ANALYTICAL METHODS IN CHEMISTRY 2019; 2019:4372395. [PMID: 30719372 PMCID: PMC6334341 DOI: 10.1155/2019/4372395] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 09/06/2018] [Accepted: 09/27/2018] [Indexed: 06/09/2023]
Abstract
In this paper, mid- and near-infrared spectroscopy fingerprints were combined to simultaneously discriminate 12 famous green teas and quantitatively characterize their antioxidant activities using chemometrics. A supervised pattern recognition method based on partial least square discriminant analysis (PLSDA) was adopted to classify the 12 famous green teas with different species and quality grades, and then optimized sample-weighted least-squares support vector machine (OSWLS-SVM) based on particle swarm optimization was employed to investigate the quantitative relationship between their antioxidant activities and the spectral fingerprints. As a result, 12 famous green teas can be discriminated with a recognition rate of 100% by MIR or NIR data. However, compared with individual instrumental data, data fusion was more adequate for modeling the antioxidant activities of samples with RMSEP of 0.0065. Finally, the performance of the proposed method was evaluated and validated by some statistical parameters and the elliptical joint confidence region (EJCR) test. The results indicate that fusion of mid- and near-infrared spectroscopy suggests a new avenue to discriminate the species and grades of green teas. Moreover, the proposed method also implies other promising applications with more accurate multivariate calibration of antioxidant activities.
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Affiliation(s)
- Haiyan Fu
- The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central University for Nationalities, Wuhan 430074, China
| | - Ou Hu
- The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central University for Nationalities, Wuhan 430074, China
| | - Lu Xu
- College of Material and Chemical Engineering, Tongren University, Tongren 554300, Guizhou, China
| | - Yao Fan
- State Key Laboratory of Green Chemistry-Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China
| | - Qiong Shi
- The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central University for Nationalities, Wuhan 430074, China
| | - Xiaoming Guo
- The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central University for Nationalities, Wuhan 430074, China
| | - Wei Lan
- The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central University for Nationalities, Wuhan 430074, China
| | - Tianming Yang
- The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, School of Pharmaceutical Sciences, South-Central University for Nationalities, Wuhan 430074, China
| | - Shunping Xie
- Technology Center, China Tobacco Guizhou Industrial Co., Ltd., Guiyang 550009, Guizhou, China
| | - Yuanbin She
- State Key Laboratory of Green Chemistry-Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China
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24
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Investigations into the total antioxidant capacities of cultivars of gluten-free grains using near-infrared spectroscopy. Food Control 2019. [DOI: 10.1016/j.foodcont.2018.07.045] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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25
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Wiedemair V, Huck CW. Evaluation of the performance of three hand-held near-infrared spectrometer through investigation of total antioxidant capacity in gluten-free grains. Talanta 2018; 189:233-240. [DOI: 10.1016/j.talanta.2018.06.056] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 06/15/2018] [Accepted: 06/16/2018] [Indexed: 10/28/2022]
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26
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In vitro and in vivo antioxidant potential of milks, yoghurts, fermented milks and cheeses: a narrative review of evidence. Nutr Res Rev 2017; 31:52-70. [PMID: 28965518 DOI: 10.1017/s0954422417000191] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The antioxidant potential (AP) is an important nutritional property of foods, as increased oxidative stress is involved in most diet-related chronic diseases. In dairy products, the protein fraction contains antioxidant activity, especially casein. Other antioxidants include: antioxidant enzymes; lactoferrin; conjugated linoleic acid; coenzyme Q10; vitamins C, E, A and D3; equol; uric acid; carotenoids; and mineral activators of antioxidant enzymes. The AP of dairy products has been extensively studied in vitro, with few studies in animals and human subjects. Available in vivo studies greatly differ in their design and objectives. Overall, on a 100 g fresh weight-basis, AP of dairy products is close to that of grain-based foods and vegetable or fruit juices. Among dairy products, cheeses present the highest AP due to their higher protein content. AP of milk increases during digestion by up to 2·5 times because of released antioxidant peptides. AP of casein is linked to specific amino acids, whereas β-lactoglobulin thiol groups play a major role in the AP of whey. Thermal treatments such as ultra-high temperature processing have no clear effect on the AP of milk. Raw fat-rich milks have higher AP than less fat-rich milk, because of lipophilic antioxidants. Probiotic yoghurts and fermented milks have higher AP than conventional yoghurt and milk because proteolysis by probiotics releases antioxidant peptides. Among the probiotics, Lactobacillus casei/acidophilus leads to the highest AP. The data are insufficient for cheese, but fermentation-based changes appear to make a positive impact on AP. In conclusion, AP might participate in the reported dairy product-protective effects against some chronic diseases.
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27
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Manuelian CL, Currò S, Penasa M, Cassandro M, De Marchi M. Prediction of minerals, fatty acid composition and cholesterol content of commercial cheeses by near infrared transmittance spectroscopy. Int Dairy J 2017. [DOI: 10.1016/j.idairyj.2017.03.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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28
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Manuelian C, Currò S, Visentin G, Penasa M, Cassandro M, Dellea C, Bernardi M, De Marchi M. Technical note: At-line prediction of mineral composition of fresh cheeses using near-infrared technologies. J Dairy Sci 2017. [DOI: 10.3168/jds.2017-12634] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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29
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Methodologies for the Characterization of the Quality of Dairy Products. ADVANCES IN FOOD AND NUTRITION RESEARCH 2017; 82:237-275. [PMID: 28427534 DOI: 10.1016/bs.afnr.2016.12.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The growing interest of consumers in food quality and safety issues has contributed to the increasing demand for sensitive and rapid analytical technologies. Physicochemical, textural, sensory, etc., methods have been used to evaluate the quality and authenticity of milk and dairy products. Despite the importance of these standard methods, they are expensive and time consuming. Recently, spectroscopic methods have shown great potential due to speed of analysis, minimal sample preparation, high repeatability, low cost, and, most of all, the fact that these techniques are noninvasive and nondestructive and, therefore, could be applied to any on-line monitoring system. This chapter gave examples of the application of the most commonly traditional methods for the determination of the quality of milk and dairy products. A special focus is devoted to the use of infrared and fluorescence spectroscopies for the evaluation of the quality of dairy products.
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30
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Mir-Marqués A, Cervera ML, de la Guardia M. Mineral analysis of human diets by spectrometry methods. Trends Analyt Chem 2016. [DOI: 10.1016/j.trac.2016.07.007] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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31
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McDermott A, Visentin G, McParland S, Berry D, Fenelon M, De Marchi M. Effectiveness of mid-infrared spectroscopy to predict the color of bovine milk and the relationship between milk color and traditional milk quality traits. J Dairy Sci 2016; 99:3267-3273. [DOI: 10.3168/jds.2015-10424] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Accepted: 12/28/2015] [Indexed: 11/19/2022]
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32
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Revilla I, González-Martín MI, Vivar-Quintana AM, Blanco-López MA, Lobos-Ortega IA, Hernández-Hierro JM. Antioxidant capacity of different cheeses: Affecting factors and prediction by near infrared spectroscopy. J Dairy Sci 2016; 99:5074-5082. [PMID: 27085414 DOI: 10.3168/jds.2015-10564] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 02/21/2016] [Indexed: 11/19/2022]
Abstract
In this study, we analyzed antioxidant capacity of 224 cheese samples prepared using 16 varied mixtures of milk from cows, ewes, and goats, in 2 manufacturing seasons (winter and summer), and over 6mo of ripening. Antioxidant capacity was evaluated using the spectrophotometric 2,2-azinobis(3-ethylenebenzothiazoline-6-sulfonic acid) (ABTS) method. Total antioxidant capacity was significantly correlated with season of manufacturing and time of ripening but not with animal species providing the milk. Moreover, statistically significant correlations between the total antioxidant capacity and retinol (r=0.399), fat percentage (r=0.308), protein percentage (r=0.366), K (r=0.385), Mg (r=0.312), Na (r=0.432), and P (0.272) were observed. We evaluated the use of near infrared spectroscopy technology, together with the use of a remote reflectance fiber-optic probe, to predict the antioxidant capacity of cheese samples. The model generated allowed us to predict antioxidant capacity in unknown cheeses of different compositions and ripening times.
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Affiliation(s)
- I Revilla
- Food Technology Area, University of Salamanca, E. P. S. de Zamora, Avda. Requejo 33, 49022, Zamora, Spain.
| | - M I González-Martín
- Department of Analytical Chemistry, Nutrition and Bromatology, Faculty of Chemistry, University of Salamanca, Plaza de la Merced s/n. 37008 Salamanca, Spain
| | - A M Vivar-Quintana
- Food Technology Area, University of Salamanca, E. P. S. de Zamora, Avda. Requejo 33, 49022, Zamora, Spain
| | - M A Blanco-López
- Food Technology Area, University of Salamanca, E. P. S. de Zamora, Avda. Requejo 33, 49022, Zamora, Spain
| | - I A Lobos-Ortega
- National Institute of Agriculture and Livestock Research Remehue, Carretera Panamericana Sur Km 8, Osorno, Chile 5290000
| | - J M Hernández-Hierro
- Food Color and Quality Laboratory, Department of Nutrition and Food Science, Universidad de Sevilla, Facultad de Farmacia, 41012 Sevilla, Spain
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33
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Yilmaz-Ersan L, Ozcan T, Akpinar-Bayizit A, Sahin S. The Antioxidative Capacity of Kefir Produced from Goat Milk. ACTA ACUST UNITED AC 2016. [DOI: 10.7763/ijcea.2016.v7.535] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
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34
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Kamal M, Karoui R. Analytical methods coupled with chemometric tools for determining the authenticity and detecting the adulteration of dairy products: A review. Trends Food Sci Technol 2015. [DOI: 10.1016/j.tifs.2015.07.007] [Citation(s) in RCA: 133] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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35
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Madalozzo ES, Sauer E, Nagata N. Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration. JOURNAL OF FOOD SCIENCE AND TECHNOLOGY 2015; 52:1649-55. [PMID: 25745236 PMCID: PMC4348305 DOI: 10.1007/s13197-013-1147-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 07/26/2013] [Accepted: 08/08/2013] [Indexed: 10/26/2022]
Abstract
Near-infrared reflectance spectroscopy (NIRS) with partial least squares regression (PLSR) was used to determine levels of fat, protein and moisture in ricotta cheese without complex sample preparation. Spectra of 19 conventional and low-fat ricotta samples from different manufacturers were collected in duplicate, with 33 of the 38 spectra used as a calibration set and the remaining 5 spectra used as an external validation set. The best results were obtained by processing the spectral region between 1,100 and 2,500 nm. Multivariate models with six latent variables (LVs) showed good prediction capability for fat and protein determinations, with average relative errors (Er) of 6.37 % and 5.95 %, respectively. For moisture, a more robust model was obtained with 4 LVs, showing better prevision capacity and Er of 1.91 %.
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Affiliation(s)
- Elisângela Serenato Madalozzo
- />Departamento de Engenharia de Alimentos, Universidade Estadual de Ponta Grossa, CEP: 84030-900 Ponta Grossa, PR Brazil
| | - Elenise Sauer
- />Universidade Tecnológica Federal do Paraná, CEP: 84016-210 Ponta Grossa, PR Brazil
| | - Noemi Nagata
- />Departamento de Química, Universidade Federal do Paraná, Caixa Postal: 19081, CEP: 81531-980 Curitiba, PR Brazil
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36
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Direct determination of minerals in human diets by infrared spectroscopy and X-ray fluorescence. Microchem J 2014. [DOI: 10.1016/j.microc.2014.06.028] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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37
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Prediction of color and moisture content for vegetable soybean during drying using hyperspectral imaging technology. J FOOD ENG 2014. [DOI: 10.1016/j.jfoodeng.2013.12.008] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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38
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Schmitt S, Garrigues S, de la Guardia M. Determination of the Mineral Composition of Foods by Infrared Spectroscopy: A Review of a Green Alternative. Crit Rev Anal Chem 2014; 44:186-97. [DOI: 10.1080/10408347.2013.835695] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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39
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Using visible or near infrared spectroscopy (NIRS) on cheese to authenticate cow feeding regimes. Food Chem 2013; 141:209-14. [DOI: 10.1016/j.foodchem.2013.02.086] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2011] [Revised: 02/20/2013] [Accepted: 02/23/2013] [Indexed: 11/17/2022]
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40
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Boschetti L, Ottavian M, Facco P, Barolo M, Serva L, Balzan S, Novelli E. A correlative study on data from pork carcass and processed meat (Bauernspeck) for automatic estimation of chemical parameters by means of near-infrared spectroscopy. Meat Sci 2013; 95:621-8. [PMID: 23811103 DOI: 10.1016/j.meatsci.2013.06.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2013] [Revised: 05/30/2013] [Accepted: 06/03/2013] [Indexed: 11/17/2022]
Abstract
The use of near-infrared spectroscopy (NIRS) is proposed in this study for the characterization of the quality parameters of a smoked and dry-cured meat product known as Bauernspeck (originally from Northern Italy), as well as of some technological traits of the pork carcass used for its manufacturing. In particular, NIRS is shown to successfully estimate several key quality parameters (including water activity, moisture, dry matter, ash and protein content), suggesting its suitability for real time application in replacement of expensive and time consuming chemical analysis. Furthermore, a correlative approach based on canonical correlation analysis was used to investigate the spectral regions that are mostly correlated to the characteristics of interest. The identification of these regions, which can be linked to the absorbance of the main functional chemical groups, is intended to provide a better understanding of the chemical structure of the substrate under investigation.
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Affiliation(s)
- Lucio Boschetti
- CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova, PD, Italy
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41
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Identification of Imitation Cheese and Imitation Ice Cream Based on Vegetable Fat Using NMR Spectroscopy and Chemometrics. INTERNATIONAL JOURNAL OF FOOD SCIENCE 2013; 2013:367841. [PMID: 26904597 PMCID: PMC4745519 DOI: 10.1155/2013/367841] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Revised: 05/21/2013] [Accepted: 05/22/2013] [Indexed: 11/17/2022]
Abstract
Vegetable oils and fats may be used as cheap substitutes for milk fat to manufacture imitation cheese or imitation ice cream. In this study, 400 MHz nuclear magnetic resonance (NMR) spectroscopy of the fat fraction of the products was used in the context of food surveillance to validate the labeling of milk-based products. For sample preparation, the fat was extracted using an automated Weibull-Stoldt methodology. Using principal component analysis (PCA), imitation products can be easily detected. In both cheese and ice cream, a differentiation according to the type of raw material (milk fat and vegetable fat) was possible. The loadings plot shows that imitation products were distinguishable by differences in their fatty acid ratios. Furthermore, a differentiation of several types of cheese (Edamer, Gouda, Emmentaler, and Feta) was possible. Quantitative data regarding the composition of the investigated products can also be predicted from the same spectra using partial least squares (PLS) regression. The models obtained for 13 compounds in cheese (R (2) 0.75-0.95) and 17 compounds in ice cream (R (2) 0.83-0.99) (e.g., fatty acids and esters) were suitable for a screening analysis. NMR spectroscopy was judged as suitable for the routine analysis of dairy products based on milk or on vegetable fat substitutes.
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42
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Páscoa RN, Magalhães LM, Lopes JA. FT-NIR spectroscopy as a tool for valorization of spent coffee grounds: Application to assessment of antioxidant properties. Food Res Int 2013. [DOI: 10.1016/j.foodres.2013.01.035] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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43
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A Review of Optical Nondestructive Visual and Near-Infrared Methods for Food Quality and Safety. ACTA ACUST UNITED AC 2013. [DOI: 10.1155/2013/341402] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
This paper is a review of optical methods for online nondestructive food quality monitoring. The key spectral areas are the visual and near-infrared wavelengths. We have collected the information of over 260 papers published mainly during the last 20 years. Many of them use an analysis method called chemometrics which is shortly described in the paper. The main goal of this paper is to provide a general view of work done according to different FAO food classes. Hopefully using optical VIS/NIR spectroscopy gives an idea of how to better meet market and consumer needs for high-quality food stuff.
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44
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Schirone M, Tofalo R, Fasoli G, Perpetuini G, Corsetti A, Manetta AC, Ciarrocchi A, Suzzi G. High content of biogenic amines in Pecorino cheeses. Food Microbiol 2012; 34:137-44. [PMID: 23498190 DOI: 10.1016/j.fm.2012.11.022] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2012] [Revised: 11/19/2012] [Accepted: 11/20/2012] [Indexed: 10/27/2022]
Abstract
Pecorino refers to Italian cheeses made exclusively from raw or pasteurized ewes' milk, characterized by a high content of fat matter and it is mainly produced in the Middle and South of Italy by traditional procedures. The autochthonous microbiota plays an important role in the organoleptic traits of Pecorino cheese and it can influence biogenic amines (BA) content. The aim of this study was to characterize from microbiological and chemical point of view 12 randomly purchased commercial cheeses produced in Abruzzo region. Moreover, the BA content and the bacteria showing a decarboxylating activity were detected. For this purpose, a real-time quantitative PCR (qPCR) was applied to evaluate histamine and tyramine-producers. The samples were well differentiated for microbial groups composition, such as aerobic mesophilic bacteria, Enterobacteriaceae, coagulase-negative staphylococci, yeasts, enterococci, mesophilic and thermophilic lactobacilli. Pathogens such as Salmonella spp., Listeria monocytogenes and Escherichia coli O157:H7 were absent in all samples. In most samples the content of BA resulted to be high, with prevalence of histamine and tyramine. In particular, total BA content reached 5861 mg/kg in Pecorino di Fossa cheese. The qPCR method resulted to be very useful to understand the role of autochthonous Pecorino cheese microbiota on BA accumulation in many different products. In fact, since the ability of microorganisms to decarboxylate aminoacids is highly variable being in most cases strain-specific, the detection of bacteria possessing this activity is important to estimate the risk of BA cheese content.
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Affiliation(s)
- Maria Schirone
- Dipartimento di Scienze degli Alimenti, Università degli Studi di Teramo, Via C.R. Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
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Coppa M, Martin B, Agabriel C, Chassaing C, Sibra C, Constant I, Graulet B, Andueza D. Authentication of cow feeding and geographic origin on milk using visible and near-infrared spectroscopy. J Dairy Sci 2012; 95:5544-51. [DOI: 10.3168/jds.2011-5272] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2011] [Accepted: 06/21/2012] [Indexed: 11/19/2022]
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47
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Development and Analytical Validation of Robust Near-Infrared Multivariate Calibration Models for the Quality Inspection Control of Mozzarella Cheese. FOOD ANAL METHOD 2012. [DOI: 10.1007/s12161-012-9498-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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48
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Lénárt J, Szigedi T, Dernovics M, Fodor M. Application of FT-NIR spectroscopy on the determination of the fat and protein contents of lyophilized cheeses. ACTA ALIMENTARIA 2012. [DOI: 10.1556/aalim.41.2012.3.7] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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49
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Application of near infrared spectroscopy for the rapid determination of antioxidant activity of bamboo leaf extract. Food Chem 2012; 135:2147-56. [PMID: 22980783 DOI: 10.1016/j.foodchem.2012.07.011] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2012] [Revised: 06/05/2012] [Accepted: 07/02/2012] [Indexed: 11/22/2022]
Abstract
This study was carried out to evaluate the feasibility of using near infrared (NIR) spectroscopy for determining three antioxidant activity indices of the extract of bamboo leaves (EBL), specifically 2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing/antioxidant power (FRAP), and 2,2'-azinobis-(3-ethylbenz-thiazoline-6-sulfonic acid) (ABTS). Four different linear and nonlinear regressions tools (i.e. partial least squares (PLS), multiple linear regression (MLR), back-propagation artificial neural network (BP-ANN), and least squares support vector machine (LS-SVM)) were systemically studied and compared in developing the model. Variable selection was first time considered in applying the NIR spectroscopic technique for the determination of antioxidant activity of food or agricultural products. On the basis of these selected optimum wavelengths, the established MLR calibration models provided the coefficients of correlation with a prediction (r(pre)) of 0.863, 0.910, and 0.966 for DPPH, FARP, and ABTS determinations, respectively. The overall results of this study revealed the potential for use of NIR spectroscopy as an objective and non-destructive method to inspect the antioxidant activity of EBL.
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50
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Lu X, Rasco BA. Determination of Antioxidant Content and Antioxidant Activity in Foods using Infrared Spectroscopy and Chemometrics: A Review. Crit Rev Food Sci Nutr 2012; 52:853-75. [DOI: 10.1080/10408398.2010.511322] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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