Skip to main content

Near-Infrared Spectroscopy for Milk Quality Analysis: The State of the Art

  • Chapter
  • First Online:
Aquaphotomics for Bio-diagnostics in Dairy

Abstract

Contemporary management of dairy farms involves automated milking systems that control the production process and are opening the way for the development of precision dairy farming on a worldwide level. Such trend makes it clear that methods for milk quality control for the near future will need to be easily incorporated into the existing automated milking equipment. An excellent candidate for this role is near-infrared spectroscopy (NIRS)—a very rapid, non-destructive and environmentally friendly method that does not require sample preparation or high initial investments and necessitates only low running costs. Compared to traditional analytical methods, NIRS offers the advantage of simultaneous determination of multiple components per measurement and real-time information; it is generally considered a perfect technology for rapid and efficient food analysis. Initial attempts to apply NIRS for measurements of standard milk components—fat, lactose and protein—have avoided raw milk, because of difficulties coming from strong water absorption and scattering by fat globules. However, over time due to the technological developments, advancements in techniques of data analysis and novel knowledge successful applications of NIRS are reported for measurements of standard milk components in raw milk, somatic cell count, solid-not-fat content, milk urea nitrogen and even the fatty acids.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Díaz-Carrillo E, Munoz-Serrano A, Alonso-Moraga A, Serradilla-Manrique JM (1993) Near infrared calibrations for goat`s milk components: protein, total casein, αs, β and κ-casein, fat and lactose. J Near Infrared Spectrosc 1:141–146

    Article  Google Scholar 

  2. Murayama K, Czarnik-Matusewicz B, Wu Y, et al (1999) Chemometrics and two-dimensional correlation spectroscopy in analysis of near-infrared spectra of protein. In: Ozaki Y, Noda I (eds) Two-dimensional correlation spectroscopy. AIP, Melville, New York, U.S.A, pp 183–196

    Google Scholar 

  3. Tse C, Barkema HW, DeVries TJ et al (2018) Impact of automatic milking systems on dairy cattle producers’ reports of milking labour management, milk production and milk quality. Animal 12:2649–2656. https://doi.org/10.1017/S1751731118000654

    Article  CAS  PubMed  Google Scholar 

  4. John AJ, Clark CEF, Freeman MJ et al (2016) Review: milking robot utilization, a successful precision livestock farming evolution. Animal 10:1484–1492. https://doi.org/10.1017/S1751731116000495

    Article  CAS  PubMed  Google Scholar 

  5. Shortall J, Foley C, Sleator RD, O’Brien B (2018) The effect of dairy cow breed on milk production, cow traffic and milking characteristics in a pasture-based automatic milking system. Livest Sci 209:1–7. https://doi.org/10.1016/j.livsci.2018.01.002

    Article  Google Scholar 

  6. Cortés V, Blasco J, Aleixos N et al (2019) Monitoring strategies for quality control of agricultural products using visible and near-infrared spectroscopy: a review. Trends Food Sci Technol 85:138–148. https://doi.org/10.1016/j.tifs.2019.01.015

    Article  CAS  Google Scholar 

  7. Pasquini C (2018) Near infrared spectroscopy: a mature analytical technique with new perspectives—a review. Anal Chim Acta 1026:8–36. https://doi.org/10.1016/j.aca.2018.04.004

    Article  CAS  PubMed  Google Scholar 

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

    Google Scholar 

  9. Büning-Pfaue H (2003) Analysis of water in food by near infrared spectroscopy. Food Chem 82:107–115. https://doi.org/10.1016/S0308-8146(02)00583-6

    Article  CAS  Google Scholar 

  10. Khan MKI (2019) Advances in noninvasive food analysis, 1st edn. CRC Press

    Book  Google Scholar 

  11. Cattaneo TMP, Holroyd SE (2013) The use of near infrared spectroscopy on milk and milk products. J Near Infrared Spectrosc 21:311–322. https://doi.org/10.1255/jnirs.1055

    Article  CAS  Google Scholar 

  12. Ozaki Y (2012) Near-infrared spectroscopy—its versatility in analytical chemistry. Anal Sci 28:545–563. https://doi.org/10.2116/analsci.28.545

    Article  CAS  PubMed  Google Scholar 

  13. Czarnecki MA, Morisawa Y, Futami Y, Ozaki Y (2015) Advances in molecular structure and interaction studies using near-infrared spectroscopy. Chem Rev 115:9707–9744. https://doi.org/10.1021/cr500013u

    Article  CAS  PubMed  Google Scholar 

  14. Siesler HW, Ozaki Y, Kawata S, Heise H (2002) Near-infrared spectroscopy: principles, instruments, applications. Wiley-VCH Verlag GmbH, Weinheim, Germany

    Google Scholar 

  15. Sato T, Yoshino M, Furukawa S et al (1987) Analysis of milk constituents by the near infrared spectrophotometric method. Nihon Chikusan Gakkaiho 58:698–706. https://doi.org/10.2508/chikusan.58.698

    Article  CAS  Google Scholar 

  16. Baer RJ, Frank JF, Loewenstein M (1983) Compositional analysis of nonfat dry milk by using near infrared diffuse reflectance spectroscopy. J Assoc Off Anal Chem 66:858–863

    CAS  PubMed  Google Scholar 

  17. Devir S, Renkema JA, Huirne RBM, Ipema AH (1993) A new dairy control and management system in the automatic milking farm: basic concepts and components. J Dairy Sci 76:3607–3616. https://doi.org/10.3168/JDS.S0022-0302(93)77701-2

    Article  Google Scholar 

  18. Rossing W, Devir S, Hogewert PH, et al (1994) Robotic milking: state of art. In: Proceedings of the 3rd international dairy housing conference. ASAE Publications, Florida, USA, pp 92–101

    Google Scholar 

  19. Schmilovitch Z, Maltz E, Austerweil M (1992) Fresh raw milk composition analysis by NIR spectroscopy. In: Prospects for automatic milking. EAAP Publ. No. 65. PUDOC Scientific Publ, Wageningen, Netherlands, pp 193–198

    Google Scholar 

  20. Gonda HL, Lindberg JE (1994) Evaluation of dietary nitrogen utilization in dairy cows based on urea concentrations in blood, urine and milk, and on urinary concentration of purine derivatives. Acta Agric Scand Sect A - Anim Sci 44:236–245. https://doi.org/10.1080/09064709409410904

    Article  Google Scholar 

  21. Svennersten-Sjaunja K, Sjaunja L-OO, Bertilsson J, Wiktorsson H (1997) Use of regular milking records versus daily records for nutrition and other kinds of management. Livest Prod Sci 48:167–174. https://doi.org/10.1016/S0301-6226(97)00023-7

    Article  Google Scholar 

  22. Tsenkova R, Grigorov T (1990) Analysis of milk fat and water content by near infrared spectroscopy. Farm Mach 27:81–86

    Google Scholar 

  23. Tsenkova R, Iordanova KI, Shinde Y (1992) Near infrared spectroscopy for evaluating milk quality. In: Ipema AH (ed) Prospects for automatic milking. Pudoc Scientific Publishers, Wageningen, Netherlands, pp 185–193

    Google Scholar 

  24. Šašić S, Ozaki Y (2001) Short-wave near-infrared spectroscopy of biological fluids. 1. Quantitative analysis of fat, protein, and lactose in raw milk by partial least-squares regression and band assignment. Anal Chem 73:64–71. https://doi.org/10.1021/ac000469c

    Article  CAS  PubMed  Google Scholar 

  25. Kamishikiryo-Yamashita H, Oritani Y, Takamura H, Matoba T (1994) Protein content in milk by near-infrared spectroscopy. J Food Sci 59:313–315. https://doi.org/10.1111/j.1365-2621.1994.tb06956.x

    Article  CAS  Google Scholar 

  26. Laporte MF, Paquin P (1999) Near-infrared analysis of fat, protein, and casein in cow’s milk. J Agric Food Chem 47:2600–2605. https://doi.org/10.1021/JF980929R

    Article  CAS  PubMed  Google Scholar 

  27. Kawamura S, Kawasaki M, Nakatsuji H, Natsuga M (2007) Near-infrared spectroscopic sensing system for online monitoring of milk quality during milking. Sens Instrum Food Qual Saf 1:37–43. https://doi.org/10.1007/s11694-006-9001-x

    Article  Google Scholar 

  28. de la Roza-Delgado B, Garrido-Varo A, Soldado A et al (2017) Matching portable NIRS instruments for in situ monitoring indicators of milk composition. Food Control 76:74–81. https://doi.org/10.1016/j.foodcont.2017.01.004

    Article  CAS  Google Scholar 

  29. Kawasaki M, Kawamura S, Tsukahara M et al (2008) Near-infrared spectroscopic sensing system for on-line milk quality assessment in a milking robot. Comput Electron Agric 63:22–27. https://doi.org/10.1016/J.COMPAG.2008.01.006

    Article  Google Scholar 

  30. Muñiz R, Cuevas-Valdés M, de la Roza-Delgado B (2020) Milk quality control requirement evaluation using a handheld near infrared reflectance spectrophotometer and a bespoke mobile application. J Food Compos Anal 86.https://doi.org/10.1016/j.jfca.2019.103388

  31. Coppa M, Revello-Chion A, Giaccone D et al (2014) Comparison of near and medium infrared spectroscopy to predict fatty acid composition on fresh and thawed milk. Food Chem 150:49–57. https://doi.org/10.1016/J.FOODCHEM.2013.10.087

    Article  CAS  PubMed  Google Scholar 

  32. Coppa M, Ferlay A, Leroux C et al (2010) Prediction of milk fatty acid composition by near infrared reflectance spectroscopy. Int Dairy J 20:182–189. https://doi.org/10.1016/J.IDAIRYJ.2009.11.003

    Article  CAS  Google Scholar 

  33. Villar A, Gorritxategi E, Aranzabe E et al (2012) Low-cost visible–near infrared sensor for on-line monitoring of fat and fatty acids content during the manufacturing process of the milk. Food Chem 135:2756–2760. https://doi.org/10.1016/J.FOODCHEM.2012.07.074

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Roumiana Tsenkova .

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Tsenkova, R., Muncan, J. (2022). Near-Infrared Spectroscopy for Milk Quality Analysis: The State of the Art. In: Aquaphotomics for Bio-diagnostics in Dairy. Springer, Singapore. https://doi.org/10.1007/978-981-16-7114-2_2

Download citation

Publish with us

Policies and ethics