356
M. Manley and P. J. Williams
15.14 Conclusion
NIR spectroscopy has developed into a prominent analytical quality control tool
in the food and beverage industries, due to its distinctive combination of speed,
accuracy and simplicity. The requirement for the development of calibration models
for each application and commodity is nowadays addressed by the availability of a
number of factory calibrations readily available. The capabilities of NIR spectroscopy
instrumentation are continually improving to maximise its performance, and the
availability of small handheld instruments makes NIR spectroscopy portable and
more affordable.
References
1. M. Manley, Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis
of biological materials. Chem. Soc. Rev. 43, 8200–8214 (2014)
2. J.W. Ellis, Alterations in the infrared absorption spectrum of water in gelatin. J. Bath J. Chem.
Phys. 6, 723–729 (1938)
3. P. Williams, J. Antoniszyn, M. Manley, Near-Infrared Technology: Getting the Best Out of
Light (AFRICAN SUN MeDIA, Stellenbosch, 2019)
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
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)
6. V. Sileoni, O. Marconi, G. Perretti, Near-infrared spectroscopy in the brewing industry. Crit.
Rev. Food Sci. Nutr. 55(12), 1771–1791 (2015)
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
8. H. Wang, J. Peng, C. Xie, Y. Bao, Y. He, Fruit quality evaluation using spectroscopy technology:
a review. Sensors 15, 11889–11927 (2015)
9. M.I. González-Martín, P. Severiano-Pérez, I. Revilla, A.M. Vivar-Quintana, J.M. HernándezHierro, C. González-Pérez, I.A. Lobos-Ortega, Prediction of sensory attributes of cheese by
near-infrared spectroscopy. Food Chem. 127, 256–263 (2011)
10. S. Sunoj, C. Igathinathane, R. Visvanathan, Nondestructive determination of cocoa bean quality
using FT-NIR spectroscopy. Comput. Electron. Agr. 124, 234–242 (2016)
11. R. Vitale, M. Bevilacqua, R. Bucci, A.D. Magrì, A.L. Magrì, F. Marini, A rapid and noninvasive method for authenticating the origin of pistachio samples by NIR spectroscopy and
chemometrics. Chemom. Intell. Lab. Syst. 121, 90–100 (2013)
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)
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)
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)
15. T. Hirschfeld, Salinity determination using NIRA. Appl. Spectrosc. 39, 740–741 (1985)
M. Manley and P. J. Williams
15.14 Conclusion
NIR spectroscopy has developed into a prominent analytical quality control tool
in the food and beverage industries, due to its distinctive combination of speed,
accuracy and simplicity. The requirement for the development of calibration models
for each application and commodity is nowadays addressed by the availability of a
number of factory calibrations readily available. The capabilities of NIR spectroscopy
instrumentation are continually improving to maximise its performance, and the
availability of small handheld instruments makes NIR spectroscopy portable and
more affordable.
References
1. M. Manley, Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis
of biological materials. Chem. Soc. Rev. 43, 8200–8214 (2014)
2. J.W. Ellis, Alterations in the infrared absorption spectrum of water in gelatin. J. Bath J. Chem.
Phys. 6, 723–729 (1938)
3. P. Williams, J. Antoniszyn, M. Manley, Near-Infrared Technology: Getting the Best Out of
Light (AFRICAN SUN MeDIA, Stellenbosch, 2019)
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
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)
6. V. Sileoni, O. Marconi, G. Perretti, Near-infrared spectroscopy in the brewing industry. Crit.
Rev. Food Sci. Nutr. 55(12), 1771–1791 (2015)
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
8. H. Wang, J. Peng, C. Xie, Y. Bao, Y. He, Fruit quality evaluation using spectroscopy technology:
a review. Sensors 15, 11889–11927 (2015)
9. M.I. González-Martín, P. Severiano-Pérez, I. Revilla, A.M. Vivar-Quintana, J.M. HernándezHierro, C. González-Pérez, I.A. Lobos-Ortega, Prediction of sensory attributes of cheese by
near-infrared spectroscopy. Food Chem. 127, 256–263 (2011)
10. S. Sunoj, C. Igathinathane, R. Visvanathan, Nondestructive determination of cocoa bean quality
using FT-NIR spectroscopy. Comput. Electron. Agr. 124, 234–242 (2016)
11. R. Vitale, M. Bevilacqua, R. Bucci, A.D. Magrì, A.L. Magrì, F. Marini, A rapid and noninvasive method for authenticating the origin of pistachio samples by NIR spectroscopy and
chemometrics. Chemom. Intell. Lab. Syst. 121, 90–100 (2013)
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)
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)
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)
15. T. Hirschfeld, Salinity determination using NIRA. Appl. Spectrosc. 39, 740–741 (1985)