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Applications: Food Science

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Near-Infrared Spectroscopy

Abstract

The combination of speed, accuracy and simplicity provided by NIR spectroscopy ensured its use as a preferred quality control tool in the food and beverage industries. These applications are increasingly simplified by the availability of readily available factory calibrations. A challenge receiving increasing attention is that of the detection of food adulteration, and a large effort is being made to evaluate NIR spectroscopy as a suitable method. The recent trend towards miniaturisation of NIR instruments contributes to the technology becoming portable and more affordable. The trust put into NIR spectroscopy as an effective analytical tool in the food industry will remain. In addition, investigations into new and innovative applications to the benefit of the food industry are seen on a daily basis.

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References

  1. M. Manley, Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials. Chem. Soc. Rev. 43, 8200–8214 (2014)

    Article  CAS  PubMed  Google Scholar 

  2. J.W. Ellis, Alterations in the infrared absorption spectrum of water in gelatin. J. Bath J. Chem. Phys. 6, 723–729 (1938)

    Google Scholar 

  3. P. Williams, J. Antoniszyn, M. Manley, Near-Infrared Technology: Getting the Best Out of Light (AFRICAN SUN MeDIA, Stellenbosch, 2019)

    Book  Google Scholar 

  4. T. Woodcock, G. Downey, C.P. O’Donnell, Better quality food and beverages: the role of near infrared spectroscopy. J. Near Infrared Spectrosc. 16, 1–29 (2008) and papers therein

    Google Scholar 

  5. N. Prieto, O. Pawluczyk, M.E.R. Dugan, J.L. Aalhus, A review of the principles and applications of near-infrared spectroscopy to characterize meat, fat, and meat products. Appl. Spectrosc. 71, 1403–1426 (2017)

    Google Scholar 

  6. V. Sileoni, O. Marconi, G. Perretti, Near-infrared spectroscopy in the brewing industry. Crit. Rev. Food Sci. Nutr. 55(12), 1771–1791 (2015)

    Article  CAS  PubMed  Google Scholar 

  7. D. Cozzolino, R.G. Damsbergs, L. Janik, W.U. Cynkar, M. Gishen, Analysis of grapes and wine by near infrared spectroscopy. J. Near Infrared Spectrosc. 14, 279–289 (2006) and papers therein

    Google Scholar 

  8. H. Wang, J. Peng, C. Xie, Y. Bao, Y. He, Fruit quality evaluation using spectroscopy technology: a review. Sensors 15, 11889–11927 (2015)

    Article  PubMed  PubMed Central  Google Scholar 

  9. M.I. González-Martín, P. Severiano-Pérez, I. Revilla, A.M. Vivar-Quintana, J.M. Hernández-Hierro, C. González-Pérez, I.A. Lobos-Ortega, Prediction of sensory attributes of cheese by near-infrared spectroscopy. Food Chem. 127, 256–263 (2011)

    Article  CAS  Google Scholar 

  10. S. Sunoj, C. Igathinathane, R. Visvanathan, Nondestructive determination of cocoa bean quality using FT-NIR spectroscopy. Comput. Electron. Agr. 124, 234–242 (2016)

    Article  Google Scholar 

  11. R. Vitale, M. Bevilacqua, R. Bucci, A.D. Magrì, A.L. Magrì, F. Marini, A rapid and non-invasive method for authenticating the origin of pistachio samples by NIR spectroscopy and chemometrics. Chemom. Intell. Lab. Syst. 121, 90–100 (2013)

    Article  CAS  Google Scholar 

  12. A. Pannico, R.E. Schouten, B. Basile, R. Romano, E.J. Woltering, C. Cirillo, Non-destructive detection of flawed hazelnut kernels and lipid oxidation assessment using NIR spectroscopy. J. Food Eng. 160, 42–48 (2015)

    Article  CAS  Google Scholar 

  13. M. Ferreiro-González, E. Espada-Bellido, L. Guillén-Cueto, M. Palma, C.G. Barroso, G.F. Barbero, Rapid quantification of honey adulteration by visible-near infrared spectroscopy. Talanta 188, 288–292 (2018)

    Article  PubMed  CAS  Google Scholar 

  14. N. Vanstone, A. Moore, P. Martos, S. Neethirajan, Detection of the adulteration of extra virgin olive oil by near-infrared spectroscopy and chemometric techniques. Food Qual. Saf. 2, 189–198 (2018)

    Article  CAS  Google Scholar 

  15. T. Hirschfeld, Salinity determination using NIRA. Appl. Spectrosc. 39, 740–741 (1985)

    Article  CAS  Google Scholar 

  16. S. Lohumi, S. Lee, H. Lee, B.K. Cho, A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration. Trends Food Sci. Tech. 46, 85–98 (2015)

    Article  CAS  Google Scholar 

  17. M. Manley, V. Baeten, Spectroscopic technique: near infrared (NIR) spectroscopy, in Modern Techniques for Food Authentication, ed. by Sun, D.-W., 2nd edn (Elsevier, Oxford, 2018), pp. 51–102

    Google Scholar 

  18. M.F. Devaux, D. Bertrand, Discrimination of bread-baking quality of wheats according to their variety by near infrared reflectance spectroscopy. Cereal Chem. 63(2), 151–154 (1986)

    Google Scholar 

  19. G. Downey, S. Byrne, E. Dwyer, Wheat trading in the Republic of Ireland: the utility of a hardness index derived by near infrared reflectance spectroscopy. J. Sci. Food Agric. 37, 762–766 (1986)

    Article  Google Scholar 

  20. A. Sirieix, G. Downey, Commercial wheat flour authentication by discriminant analysis of near infrared reflectance spectra. J. Near Infrared Spectrosc. 1, 187–197 (1993)

    Article  CAS  Google Scholar 

  21. D. Cozzolino, An overview of the use of infrared spectroscopy and chemometrics in authenticity and traceability of cereals. Food Res. Int. 60, 262–265 (2014)

    Article  CAS  Google Scholar 

  22. N. Prieto, R. Roehe, P. Lavín, G. Batten, S. Andrés, Application of near infrared reflectance spectroscopy to predict meat and meat products quality: a review. Meat Sci. 83, 175–186 (2009)

    Article  CAS  PubMed  Google Scholar 

  23. H.B. Ding, R.-J. Xu, Differentiation of beef and kangaroo meat by visible/near-infrared reflectance spectroscopy. J. Food Sci. 64(5), 814–817 (1999)

    Article  CAS  Google Scholar 

  24. J. McElhinney, G. Downey, C. O’Donnell, Quantification of lamp content in mixtures with raw minced beef using visible near and mid-infrared spectroscopy. J. Food Sc. 64(4), 587–591 (1999)

    Article  CAS  Google Scholar 

  25. F. Huang, Y. Li, J. Wu, J. Dong, Y. Wang, Identification of repeatedly frozen meat based on near-infrared spectroscopy combined with self-organizing competitive neural networks. Int. J. Food Prop. 19, 1007–1015 (2016)

    Article  CAS  Google Scholar 

  26. C. Alamprese, M. Casale, N. Sinelli, S. Lanteri, E. Casiraghia, Detection of minced beef adulteration with turkey meat by UV–vis, NIR and MIR spectroscopy. LWT-Food Sci. Technol. 53, 225–232 (2013)

    Article  CAS  Google Scholar 

  27. D.F. Barbin, A.T. Badaró, D.C.B. Honorato, E.Y. Ida, M. Shimokomakia, Identification of turkey meat and processed products using near infrared spectroscopy. Food Control 107, 106816 (2020)

    Article  CAS  Google Scholar 

  28. D. Liu, X.A. Zeng, D.-W. Sun, NIR spectroscopy and imaging techniques for evaluation of fish quality—a review. J. Appl. Spectrosc. Rev. 48, 609–628 (2013)

    Article  CAS  Google Scholar 

  29. J. Zhou, X. Wu, Z. Chen, J. You, S. Xiong, Evaluation of freshness in freshwater fish based on near infrared reflectance spectroscopy and chemometrics. LWT-Food Sci. Technol. 106, 145–150 (2019)

    Article  CAS  Google Scholar 

  30. N. O’Brien, C.A. Hulse, F. Pfeifer, H.W. Siesler, Near infrared spectroscopic authentication of seafood. J. Near Infrared Spectrosc. 21, 299–305 (2013)

    Article  CAS  Google Scholar 

  31. S. Grassi, E. Casiraghi, C. Alamprese, Handheld NIR device: a non-targeted approach to assess authenticity of fish fillets and patties. Food Chem. 243, 382–388 (2018)

    Article  CAS  PubMed  Google Scholar 

  32. D.J. Dahm, Explaining some light scattering properties of milk using representative layer theory. J. Near Infrared Spectrosc. 21(5), 323–339 (2013)

    Article  CAS  Google Scholar 

  33. S.E. Holroyd, The use of near infrared spectroscopy on milk and milk products. J. Near Infrared Spectrosc. 21, 311–322 (2013)

    Article  CAS  Google Scholar 

  34. T.M.P. Cattaneo, S.E. Holroyd, The use of near infrared spectroscopy for determination of adulteration and contamination in milk and milk powder: updating knowledge. J. Near Infrared Spectrosc. 21, 341–349 (2013) and papers therein

    Google Scholar 

  35. P.A.D.A. Filho, P. Volery, Broad-based versus specific NIRS calibration: determination of total solids in fresh cheeses. Anal. Chim. Acta 544, 82–88 (2005)

    Article  CAS  Google Scholar 

  36. E. Domingo, A.A. Tirelli, C.A. Nunes, M.C. Guerreiro, S.M. Pinto, Melamine detection in milk using vibrational spectroscopy and chemometrics analysis: a review. Food Res. Int. 60, 131–139 (2014)

    Article  CAS  Google Scholar 

  37. T. Sato, Application of principal component analysis on near infrared spectroscopic data of vegetable oils for their classification. J. Am. Oil Chem. Soc. 71(3), 293–298 (1994) and papers therein

    Google Scholar 

  38. K.M. Bewig, A.D. Clarke, C. Roberts, N. Unklesbay, Discriminant analysis of vegetable oils by near-infrared reflectance spectroscopy. J. Am. Oil Chem. Soc. 71(2), 195–200 (1994)

    Article  CAS  Google Scholar 

  39. P. Hourant, V. Baeten, M.T. Morales, M. Meurens, R. Aparicio, Oils and fats classification by selected bands of near-infrared spectroscopy. Appl. Spectrosc. 54(8), 1168–1174 (2000)

    Article  CAS  Google Scholar 

  40. S. Armenta, J. Moros, S. Garrigues, M. De La Guardia, The use of near-infrared spectrometry in the olive oil industry. Crit. Rev. Food Sci. Nutr. 50, 567–582 (2010)

    Article  CAS  PubMed  Google Scholar 

  41. E. Christopoulou, M. Lazaraki, M. Komaitis, K. Kaselimis, Effectivenes of determinations of fatty acids and triglycerides for the detection of adulteration of olive oils with vegetable oils. Food Chem. 84, 463–474 (2004)

    Article  CAS  Google Scholar 

  42. I.J. Wesley, F. Pacheco, A.E.J. McGill, Identification of adulterants in olive oils. J. Am. Oil Chem. Soc. 73(4), 515–518 (1996)

    Article  CAS  Google Scholar 

  43. A.A. Christy, S. Kasemsumran, Y. Du, Y. Ozaki, The detection and quantification of adulteration in olive oil by near infrared spectroscopy and chemometrics. Anal. Sci. 20, 935–940 (2004)

    Article  CAS  PubMed  Google Scholar 

  44. K.N. Basri, M.N. Hussain, J. Bakar, Z. Sharif, M.F.A. Khir, A.S. Zoolfakar, Classification and quantification of palm oil adulteration via portable NIR spectroscopy. Spectrochim. Acta, Part A 173, 335–342 (2017)

    Article  CAS  Google Scholar 

  45. N. Shilton, G. Downey, P.B. McNulty, Detection of orange juice adulteration by near-infrared spectroscopy. Sem. Food Anal. 3, 155–161 (1998)

    Google Scholar 

  46. E. Arendse, O.A. Fawole, L.S. Magwaza, U.L. Opara, Non-destructive prediction of internal and external quality attributes of fruit with thick rind: a review. J. Food Eng. 217, 11–23 (2018)

    Article  Google Scholar 

  47. E.J. Nascimento Marques, S.T. De Freitas, M. Fernanda Pimentel, C. Pasquini, Rapid and non-destructive determination of quality parameters in the ‘Tommy Atkins’ mango using a novel handheld near infrared spectrometer. Food Chem. 197, 1207–1214 (2016)

    Article  CAS  Google Scholar 

  48. M. García-Alvarez, J.F. Huidobro, M. Hermida, J.L. Rodríguez-Otero, Major components of honey analysis by near-infrared transflectance spectroscopy. J. Agric. Food Chem. 48, 5154–5158 (2000)

    Article  PubMed  CAS  Google Scholar 

  49. G. Downey, V. Fouratier, J.D. Kelly, Detection of honey adulteration by addition of fructose and glucose using near infrared transflectance spectroscopy. J. Near Infrared Spectrosc. 11, 447–456 (2003)

    Article  CAS  Google Scholar 

  50. J.D. Kelly, C. Petisco, G. Downey, Potential of near infrared transflectance spectroscopy to detect adulteration of Irish honey by beet invert syrup and high fructose corn syrup. J. Near Infrared Spectrosc. 14, 139–146 (2006)

    Article  CAS  Google Scholar 

  51. A. Guelpa, F. Marini, A. Du Plessis, R. Slabbert, M. Manley, Verification of authenticity of South African honey and fraud detection using NIR spectroscopy. Food Control 74, 1388–1396 (2017)

    Article  CAS  Google Scholar 

  52. C.M. McGoverin, J. Weeranantanaphan, G. Downey, M. Manley, Review: the application of near infrared spectroscopy to the measurement of bioactive compounds in food commodities. J. Near Infrared Spectrosc. 18(2), 87–111 (2010)

    Article  CAS  Google Scholar 

  53. B.G. Osborne, T. Fearn, Discriminant analysis of black tea by near infrared reflectance spectroscopy. Food Chem. 29, 233–238 (1988)

    Article  CAS  Google Scholar 

  54. A. Grant, J.G. Franklin, A.M.C. Davies, Near infra-red analysis: the use of multivariate statistics for investigation of variables in sample preparation and presentation of tea leaf. J. Sci. Food Agric. 42, 129–139 (1988)

    Article  Google Scholar 

  55. Q. Chen, J. Zhao, G. Zhang, X. Wang, Feasibility study on qualitative and quantitative analysis in tea by near infrared spectroscopy with multivariate calibration. Anal. Chim. Acta 572, 77–84 (2006)

    Article  CAS  PubMed  Google Scholar 

  56. M. Manley, E. Joubert, M. Botha, Quantification of the major phenolic compounds, soluble solid content and total antioxidant activity of green rooibos (Aspalathus linearis) by means of near infrared spectroscopy. J. Near Infrared Spectrosc. 14, 213–222 (2006)

    Google Scholar 

  57. A.M.C. Davies, F. McClure, Near infrared analysis of foods. Near infrared analysis in the Fourier domain with special reference to process control. Anal. Proc. 22, 321–322 (1985)

    Google Scholar 

  58. G. Downey, J. Boussion, D. Beauchêne, Authentication of whole and ground coffee beans by near infrared reflectance spectroscopy. J. Near Infrared Spectrosc. 2, 85–92 (1994)

    Article  CAS  Google Scholar 

  59. R.M. Correia, F. Tosato, E. Domingos, R.R.T. Rodrigues, L.F M. Aquino, P.R. Filgueiras, V. Lacerda Jr, W. Romão, Portable near infrared spectroscopy applied to quality control of Brazilian coffee. Talanta 176, 59–68 (2018)

    Google Scholar 

  60. I.S. Arvanitoyannis, M.N. Katsota, E.P. Psarra, E.H. Soufleros, S. Kallithraka, Application of quality control methods for assessing wine authenticity: use of multivariate analysis (chemometrics). Trends Food Sci. Technol. 10, 321–336 (1999)

    Article  CAS  Google Scholar 

  61. M. Manley, N. De Bruyn, G. Downey, Classification of three-year old, unblended South African brandy with near infrared spectroscopy. NIR News 14(5), 8–9, 11 (2003)

    Google Scholar 

  62. M.J.C. Pontes, S.R.B. Santos, M.C.U. Araújo, L.F. Almeida, R.A.C. Lima, E.N. Gaião, U.T.C.P. Souto, Classification of distilled alcoholic beverages and verification of adulteration by near infrared spectrometry. Food Res. Int. 39, 182–189 (2006)

    Google Scholar 

  63. M. Alcalà, M. Blanco, D. Moyano, N.W. Broad, N. O’Brien, D. Friedrich, F. Pfeifer, H.W. Siesler, Qualitative and quantitative pharmaceutical analysis with a novel hand-held miniature near infrared spectrometer. J. Near Infrared Spectrosc. 21, 445–457 (2013)

    Article  CAS  Google Scholar 

  64. R. Tsenkova, Aquaphotomics: dynamic spectroscopy of aqueous and biological systems describes peculiarities of water. J. Near Infrared Spectrosc. 17, 303–313 (2009)

    Article  CAS  Google Scholar 

  65. G. Bazar, R. Romvari, A. Szabo, T. Somogyi, V. Éles, R. Tsenkova, NIR detection of honey adulteration reveals differences in water spectral pattern. Food Chem. 194, 873–880 (2016)

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Food Science, Stellenbosch University, Private Bag X1, Matieland, 7602, Stellenbosch, South Africa

    Marena Manley & Paul James Williams

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  1. Marena Manley
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  2. Paul James Williams
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Correspondence to Marena Manley .

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Editors and Affiliations

  1. School of Science and Technology, Kwansei Gakuin University, Sanda, Japan

    Yukihiro Ozaki

  2. Institut für Analytische Chemie und Radiochemie, University of Innsbruck, Innsbruck, Tirol, Austria

    Christian Huck

  3. Nagoya University, Nagoya, Japan

    Satoru Tsuchikawa

  4. University of Copenhagen, Copenhagen, Denmark

    Søren Balling Engelsen

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Manley, M., Williams, P.J. (2021). Applications: Food Science. In: Ozaki, Y., Huck, C., Tsuchikawa, S., Engelsen, S.B. (eds) Near-Infrared Spectroscopy. Springer, Singapore. https://doi.org/10.1007/978-981-15-8648-4_15

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