Near-infrared spectroscopic sensing system for on-line milk quality assessment in a milking robot
Open accessAbstract
A near-infrared (NIR) spectroscopic sensing system was constructed on an experimental basis. This system enabled NIR spectra of raw milk to be obtained in an automatic milking system (milking robot system) over a wavelength range of 600-1050nm. Calibration models for determining three major milk constituents (fat, protein and lactose), somatic cell count (SCC) and milk urea nitrogen (MUN) of unhomogenized milk were developed, and the precision and accuracy of the models were validated. The coefficient of determination (r ²) and standard error of prediction (SEP) of the validation set for fat were 0.95 and 0.25%, respectively. The values of r ² and SEP for lactose were 0.83 and 0.26%, those for protein were 0.72 and 0.15%, those for SCC were 0.68 and 0.28logSCC/mL, and those for MUN were 0.53 and 1.50mg/dL, respectively. These results indicate that the NIR spectroscopic system can be used to assess milk quality in real-time in an automatic milking system. The system can provide dairy farmers with information on milk quality and physiological condition of an individual cow and, therefore, give them feedback control for optimizing dairy farm management. By using the system, dairy farmers will be able to produce high-quality milk and precision dairy farming will be realized.
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Shao et al. used an in situ portable visible NIR (Vis-NIR) fiber-optic probe to measure intracellular carotenoid content in Spirulina sp. suspensions, predicting carotenoid content using three PLSR prediction models with correlation coefficients as high as 0.96.
“Shao et al . [71] used an in situ portable visible NIR (Vis-NIR) fiber-optic probe to measure intracellular carotenoid content in Spirulina sp. suspensions. In the study, carotenoid content was predicted using three PLSR prediction models with correlation coefficients as high as 0.96.”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [71]
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Cites
Indicators of inflammation in the diagnosis of mastitis
Py�r�l�, S. (2003) · Veterinary Research · doi:10.1051/vetres:2003026 · Cited by 540 · see citing works
Evaluation of Milk Urea Nitrogen as a Diagnostic of Protein Feeding
Nousiainen, J., Shingfield, K. J., & Huhtanen, P. J. (2004) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(04)73178-1 · Cited by 390 · see citing works
Near-Infrared Spectroscopy for Dairy Management: Measurement of Unhomogenized Milk Composition
Tsenkova, R. N., Atanassova, S., Toyoda, K., et al. (1999) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(99)75484-6 · Cited by 216 · see citing works
Association Between Milk Urea Nitrogen and Fertility in Ohio Dairy Cows
Rajala‐Schultz, P. J., Saville, W. J. A., Frazer, G. S., et al. (2001) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(01)74498-0 · Cited by 166 · see citing works
Somatic cell count determination in cow's milk by near-infrared spectroscopy: a new diagnostic tool.
Tsenkova, R. N., Atanassova, S., Kawano, S., et al. (2001) · Journal of Animal Science · doi:10.2527/2001.79102550x · Cited by 125 · see citing works
Frank, B., & Swensson, C. (2002) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(02)74257-4 · Cited by 121 · see citing works
Godden, S., Lissemore, K. D., Kelton, D. F., et al. (2001) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(01)74573-0 · Cited by 120 · see citing works
Near-infrared spectroscopic sensing system for online monitoring of milk quality during milking
Kawamura, S., Kawasaki, M., Nakatsuji, H., et al. (2007) · Sensing and Instrumentation for Food Quality and Safety · doi:10.1007/s11694-006-9001-x · Cited by 82 · see citing works
Self-citationDevelopment of an automatic rice-quality inspection system
Kawamura, S., Natsuga, M., Takekura, K., et al. (2003) · Computers and Electronics in Agriculture · doi:10.1016/s0168-1699(03)00015-2 · Cited by 76 · see citing works
Self-citationUse of regular milking records versus daily records for nutrition and other kinds of management
Svennersten‐Sjaunja, K., Sjaunja, L.-O., Bertilsson, J., et al. (1997) · Livestock Production Science · doi:10.1016/s0301-6226(97)00023-7 · Cited by 47 · see citing works
Miyamoto, K., Kawauchi, M., & Fukuda, T. (1998) · Journal of Near Infrared Spectroscopy · doi:10.1255/jnirs.146 · Cited by 35 · see citing works
Natsuga, M., & Kawamura, S. (2006) · Transactions of the ASABE · doi:10.13031/2013.21712 · Cited by 34 · see citing works
Self-citationAnalysis of Milk Constituents by the Near Infrared Spectrophotometric Method
Sato, T., Yoshino, M., FURUKAWA, S., et al. (1987) · Nihon Chikusan Gakkaiho · doi:10.2508/chikusan.58.698 · Cited by 32 · see citing works
Kawamura, S., Takekura, K., & Itoh, K. (2002) · 2002 Chicago, IL July 28-31, 2002 · doi:10.13031/2013.9608 · Cited by 3 · see citing works
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Research works printed but not linked: 2
- Natsuga, M., Kawamura, S., Itoh, K., 2001. Determination of the Quality of High-Moisture Wheat Using Near-Infrared Spectroscopy (Part 1) -Determination of Moisture and Protein Content in High-Moisture Wheat. J. Jpn. Soc. of Agricultural Machinery. 63(1), 93-99.
- Natsuga, M., Kawamura, S., Itoh, K., 2002. Effects of Wavelength Range and Light Path-length on the Accuracy of the Constituent Analysis of Raw Milk Using Near-infrared Spectroscopy. J. Jpn. Soc. of Agricultural Machinery. 64(5), 83-88.
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On-line application of near infrared (NIR) spectroscopy in food production
Porep, J. U., Kammerer, D. R., & Carle, R. (2015) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2015.10.002 · Cited by 611 · see citing works
Podevin, M., Fotidis, I. A., & Angelidaki, I. (2018) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2017.1398132 · Cited by 34 · see citing works
A review of precision technologies in pasture-based dairying systems
Shalloo, L., Byrne, T., Leso, L., Ruelle, E., Starsmore, K., Geoghegan, A., Werner, J., & O’Leary, N. (2021) · Irish Journal of Agricultural and Food Research · doi:10.15212/ijafr-2020-0119 · Cited by 20 · see citing works
“68) by a near-infrared spectroscopic sensing system (Kawasaki et al., 2008) or additionally with optical methods, biosensors or sensor arrays.”
Background
- Authors
- Kawasaki, M., Kawamura, S., Tsukahara, M., Morita, S., Komiya, M., & Natsuga, M.
- Affiliations
- Hokkaido University (JP)
- Rakuno Gakuen University (JP)
- Yamagata University (JP)
- Corresponding author
- Kawamura, Shuso
- Venue
- Computers and Electronics in Agriculture
- Publisher
- Elsevier BV
- Published
- 2008-08
- Volume
- 63
- Issue
- 1
- Pages
- 22-27
- ISSN
- 0168-1699 (ISSN-L)
- OpenAlex
- W2070263327
- Cited by
- 134
- References
- 14
- Citations by year
- 2026: 6 · 2025: 5 · 2024: 15 · 2023: 5 · 2022: 5 · 2021: 25 · 2020: 16 · 2019: 4 · 2018: 5 · 2017: 6 · 2016: 10 · 2015: 5 · 2014: 2 · 2013: 6 · 2012: 8
- FWCI
- 3.34
- Type
- journal article
- Language
- en
- Open access
- Locations
- Computers and Electronics in Agriculture (publishedVersion)
- Institutional Repositories DataBase (IRDB) (submittedVersion)
- Hokkaido University Collection of Scholarly and Academic Papers (Hokkaido University) (submittedVersion)
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Milk Quality and Mastitis in Dairy Cows
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Keywords
- near-infrared spectroscopy, milk quality testing, automatic milking systems, milk fat, milk protein, lactose, somatic cell count, milk urea nitrogen, precision dairy farming, calibration models
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