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Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: A review
Abstract
Over the past 30 years, on/in-line near infrared (NIR) spectroscopy has proved to be one of the most efficient and advanced tools for continuous monitoring and controlling of process and product quality in food processing industry. A lot of work has been done in this area. This review focuses on the use of NIR spectroscopy for the on/in-line analysis of foods such as meat, fruit, grain, dairy products, beverage and other areas, and mainly looks at the literature published in the last 10 years. The topics covered emphasize the methods designed for on/in-line measurement of data, chemometric treatment, as well as interpretation of the experimental observations. Finally, problems relating to the successful applications of on/in-line NIR spectroscopy in production processes have been briefly outlined.
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“Currently, there are few reviews of vibrational spectroscopy as it pertains to the microalgae industry [9,17-19]; however, these reviews do not take into account the technological progress and development of on-line/in-line vibrational spectroscopy implemented in bioprocess, pharmaceutical, and liquid and solid food industries [20-28]”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [23]
Citations
Cites
Handbook of Near-Infrared Analysis
Burns, D. A., & Ciurczak, E. W. (2001) · CRC Press eBooks · doi:10.1201/9781003042204 · Cited by 1,472
Near‐Infrared Spectroscopy in Food Analysis
Osborne, B. G. (2000) · Wiley eBooks · doi:10.1002/9780470027318.a1018 · Cited by 986
Firmness, dry-matter and soluble-solids assessment of postharvest kiwifruit by NIR spectroscopy
McGlone, A., & Kawano, S. (1998) · Postharvest Biology and Technology · doi:10.1016/s0925-5214(98)00007-6 · Cited by 380
Gómez, A. H., He, Y., & Pereira, A. G. (2005) · Journal of Food Engineering · doi:10.1016/j.jfoodeng.2005.06.036 · Cited by 365
Kawano, S., Fujiwara, T., & Iwamoto, M. (1993) · Journal of the Japanese Society for Horticultural Science · doi:10.2503/jjshs.62.465 · Cited by 233
Kawano, S., Watanabe, H., & Iwamoto, M. (1992) · Journal of the Japanese Society for Horticultural Science · doi:10.2503/jjshs.61.445 · Cited by 218
Workman, J., Koch, M. V., & Veltkamp, D. (2005) · Analytical Chemistry · doi:10.1021/ac050620o · Cited by 204
Downey, G., McIntyre, P. S., & Davies, A. N. (2002) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf0257188 · Cited by 184
Rapid Detection of Kernel Rots and Mycotoxins in Maize by Near-Infrared Reflectance Spectroscopy
Berardo, N., Pisacane, V., Battilani, P., Scandolara, A., Pietri, A., & Marocco, A. (2005) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf0512297 · Cited by 180
Detection of Brownheart in ‘Braeburn’ apple by transmission NIR spectroscopy
Clark, C. J., McGlone, A., & Jordan, R. B. (2003) · Postharvest Biology and Technology · doi:10.1016/s0925-5214(02)00122-9 · Cited by 179
Research works printed but not linked: 6
- Burns, 2001, vol. 27
- Choi, 1998, Development of apple sorter by soluble solid content using photodiodes, Proceeding of Winter Conference of KSAM, Suwon, 3, 362
- Engel, 1997, On-the-go grain protein sensing is near, Better Crops with Plant Food, 81, 20
- He, 2001, Detecting device for on-line detection of internal quality of fruits using near infrared spectroscopy and the related experiments, Transactions of the Chinese Society of Agricultural Engineering, 17, 146
- Schwarze, 1997, Continuous fat analysis in the meat industry, Process Control Quality, 9, 133
- Sinelli, 2004, Application of NIR spectroscopy in on-line monitoring of dough proofing and bread staling, Tecnica Molitoria, 55, 1075
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THz spectroscopy detection method for GMOs based on adaptive particle swarm optimization
Liu, J., Mao, L., Ku, J., He, J., & Fan, L. (2016) · Optical and Quantum Electronics · doi:10.1007/s11082-015-0259-2 · Cited by 12
Luna, A. S., Pinho, J. S. A., & Machado, L. C. (2016) · Analytical Methods · doi:10.1039/c6ay01351a · Cited by 12
Georgieva, M., Nebojan, I., Mihalev, K., Yoncheva, N., Kljusurić, J. G., & Kurtanjek, Ž. (2013) · Hrčak Portal of scientific journals of Croatia (University Computing Centre) · Cited by 12
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Mirschel, G., Daikos, O., Heymann, K., Decker, U. P., Scherzer, T., Sommerer, C., Genest, B., & Steckert, C. (2014) · Progress in Organic Coatings · doi:10.1016/j.porgcoat.2014.05.012 · Cited by 11
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Non-destructive Measurement of Sugar Content in Chestnuts Using Near-Infrared Spectroscopy
Liu, J., Li, X., Li, P., Wang, W., Zhang, J., Zhou, W., & Zhou, Z. (2011) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-3-642-18369-0_28 · Cited by 11
2025 photonics for agrifood roadmap: towards a sustainable and healthier planet
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Spectral-AI technologies for food safety: Advances, challenges, and future directions
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Morawski, R. Z. (2012) · Metrology and Measurement Systems · doi:10.2478/v10178-012-0056-1 · Cited by 10
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Beguš, S., Begeš, G., Drnovšek, J., & Hudoklin, D. (2014) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2014.10.032 · Cited by 10
Fauteux‐Lefebvre, C., Lavoie, F. B., & Gosselin, R. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b04626 · Cited by 10
Rey‐Bayle, M., Bendoula, R., Caillol, N., & Roger, J. (2019) · Journal of Near Infrared Spectroscopy · doi:10.1177/0967033519830062 · Cited by 10
del Río, V., Callao, M. P., Larrechi, M. S., de Espinosa, L. M., Ronda, J. C., & Cádiz, V. (2008) · Analytica Chimica Acta · doi:10.1016/j.aca.2008.10.071 · Cited by 10
Prediction Models for Soil Properties Using VIS-NIR Spectroscopy
Ando, M., Arakawa, M., & Funatsu, K. (2009) · Journal of Computer Aided Chemistry · doi:10.2751/jcac.10.53 · Cited by 10
Lebot, V. (2012) · Journal of root crops · Cited by 10
Wu, X., Wu, B., Sun, J., & Li, M. (2014) · International Journal of Food Engineering · doi:10.1515/ijfe-2014-0117 · Cited by 10
Classification of Orange Growing Locations Based on the Near-infrared Spectroscopy Using Data Mining
Dan, S., Yang, S. X., Tian, F., & Den, L. (2015) · Intelligent Automation & Soft Computing · doi:10.1080/10798587.2015.1095474 · Cited by 10
Tian, H., Li, T., Nie, L., Zang, L., Zang, H., & Zeng, Y. (2016) · Journal of Innovative Optical Health Sciences · doi:10.1142/s179354581750002x · Cited by 10
Determination of Antioxidant Activity and Polyphenols Content in Chips by Raman and IR Spectroscopy
Mazurek, S., Szostak, R., Kita, A., Kucharska, A. Z., Sokół‐Łętowska, A., & Hamouz, K. (2017) · Food Analytical Methods · doi:10.1007/s12161-017-0972-5 · Cited by 10
Xia, Z., Yi, T., & Liu, Y. (2019) · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · doi:10.1016/j.saa.2019.117777 · Cited by 10
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Elamshity, M. G., & Alhamdan, A. M. A. (2025) · Foods · doi:10.3390/foods14173060 · Cited by 9
Wu, G., Jiang, Q., Bai, Y., Tian, C., Pan, W., Jin, X., & Zhang, B. (2020) · IEEE Access · doi:10.1109/access.2020.3007862 · Cited by 9
Applications of infrared processing in the food industry
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Abdul, R., Riana, L., & Lumakso, F. A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-21493-6.00006-x · Cited by 9
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Rongtong, B., Suwonsichon, T., Ritthiruangdej, P., & Kasemsumran, S. (2018) · Journal of Near Infrared Spectroscopy · doi:10.1177/0967033518808054 · Cited by 9
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Zhang, L., Hu, H., Zhou, Y., Miao, J., Ouyang, G., & Chen, X. (2022) · ACS Photonics · doi:10.1021/acsphotonics.2c01293 · Cited by 8
Liu, F., Cai, W., & Shao, X. (2013) · Vibrational Spectroscopy · doi:10.1016/j.vibspec.2013.05.014 · Cited by 8
Melado-Herreros, Á., Nieto‐Ortega, S., Olabarrieta, I., Ramilo-Fernández, G., Sotelo, C. G., Teixeira, B., Velasco, A., & Mendes, R. O. (2022) · Journal of Food Engineering · doi:10.1016/j.jfoodeng.2022.110979 · Cited by 8
Olivos, M., Gajardo, H. A., Salvo-Garrido, S. I., Gonzalez, A., & Muñoz, C. (2015) · IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) · doi:10.1109/chilecon.2015.7400347 · Cited by 8
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Wu, D., & Sun, D. (2016) · Wiley eBooks · doi:10.1002/9781118350676.ch13 · Cited by 8
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Alagappan, S., Hoffman, L. C., & Cozzolino, D. (2025) · Critical Reviews in Analytical Chemistry · doi:10.1080/10408347.2025.2601695 · Cited by 7
Drees, A., Bockmayr, B., Bockmayr, M. L., & Fischer, M. J. (2023) · Foods · doi:10.3390/foods12152939 · Cited by 7
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Senni, L., Laureti, S., Rizwan, M. K., Burrascano, P., Hutchins, D. A., Davis, L. A. J., & Ricci, M. (2019) · NDT & E International · doi:10.1016/j.ndteint.2018.12.012 · Cited by 7
Agudo, B., Delgado, J. V., López, M., & Rodríguez, P. L. (2020) · Archivos de Zootecnia · doi:10.21071/az.v69i265.5033 · Cited by 7
Hu, H., Huang, Q., & Zhang, Q. (2023) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3580858 · Cited by 7
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Stothers, L. S., Macnab, A. J., Mutabazi, S., Mukisa, R., Molavi, B., & Shadgan, B. (2016) · Journal of Spectroscopy · doi:10.1155/2016/1241862 · Cited by 7
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Wang, X., Wu, Q., Li, L., Wang, P., Wang, Y., Wei, W., Ma, X., Shu, J., Zhang, K., & Ma, D. (2022) · PLoS ONE · doi:10.1371/journal.pone.0270315 · Cited by 7
Oelkrug, D., Boldrini, B., & Rebner, K. (2016) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-016-9582-0 · Cited by 7
Fox, G. P., & O’Hare, T. J. (2017) · Burleigh Dodds series in agricultural science · doi:10.19103/as.2016.0001.14 · Cited by 7
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Monti, M., Pellacani, S., Strani, L., D’Alessandro, A., Cocchi, M., Giussani, B., & Durante, C. (2025) · Microchemical Journal · doi:10.1016/j.microc.2025.116378 · Cited by 6
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Cornehl, L., Gauweiler, P., Zheng, X., Krause, J., Schwander, F., Töpfer, R., Gruna, R., & Kicherer, A. (2024) · Frontiers in Plant Science · doi:10.3389/fpls.2024.1386951 · Cited by 6
Sun, X., Zhu, L., & Liu, D. (2025) · Infrared Physics & Technology · doi:10.1016/j.infrared.2024.105703 · Cited by 6
Xu, L., Deng, D., Cai, C.-B., & Yang, H. (2011) · Journal of Automated Methods and Management in Chemistry · doi:10.1155/2011/323196 · Cited by 6
Wang, S., Liu, X., Tamura, T., Kyouno, N., Zhang, H., & Chen, J. Y. (2020) · Analytical Letters · doi:10.1080/00032719.2020.1858092 · Cited by 6
Castro‐Reigía, D., Ortiz, M. C., Sanllorente, S., García, I., & Sarabia, L. A. (2024) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2024.105092 · Cited by 6
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Application of Near-infrared Spectroscopy in Batch Process Control
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Weishaupt, I., Zimmer, M., Neubauer, P. B., & Schneider, J. (2020) · Journal of Food Science · doi:10.1111/1750-3841.15307 · Cited by 6
Kim, J., Faqeerzada, M. A., Kim, M. S., Baek, I., Alvseike, O. A., & Cho, B. (2025) · Food Control · doi:10.1016/j.foodcont.2025.111330 · Cited by 5
Shen, N., Wang, J., Wang, X., Ma, J., & Wu, S. (2025) · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · doi:10.1016/j.saa.2025.127358 · Cited by 5
Tanaka, T., Saputro, R. H., Ishii, H., Shibayama, S., Kurosawa, M., Nakatsuka, O., & Maeda, T. (2025) · Japanese Journal of Applied Physics · doi:10.35848/1347-4065/ae30ed · Cited by 5
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Abeshu, Y., & Zewdu, A. (2020) · Agriculture and Food Sciences Research · doi:10.20448/journal.512.2020.71.38.45 · Cited by 5
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Yoshikawa, I., Hosoe, S., Hikima, Y., Watari, M., & Ohshima, M. (2023) · Industrial & Engineering Chemistry Research · doi:10.1021/acs.iecr.3c00216 · Cited by 5
Analysis of Quality in Fruit by NIR Spectrum
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Lopes, M. B., Amorim, A., Calado, C. R. C., & Costa, P. R. (2018) · Journal of Marine Science and Engineering · doi:10.3390/jmse6040147 · Cited by 5
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Gu, C., Xiang, B., Su, Y., & Xu, J. (2013) · American Journal of Analytical Chemistry · doi:10.4236/ajac.2013.43015 · Cited by 5
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Zia, A., Husnain, M., Buck, S., Richetti, J., Hulm, E., Ral, J.-P. F., Rolland, V., & Sirault, X. R. R. (2025) · Current Research in Food Science · doi:10.1016/j.crfs.2025.101030 · Cited by 4
Lamptey, F. P., Teye, E., Odoi-Yorke, F., Otoo, G. S., Abano, E. E., Amuah, C. L. Y., & Kaburi, S. A. (2026) · Journal of Near Infrared Spectroscopy · doi:10.1177/09670335261434638 · Cited by 4
Hruska, Z., Yao, H., Kincaid, R., Tao, F., Brown, R. L., Cleveland, T. E., Rajasekaran, K., & Bhatnagar, D. (2020) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.03152 · Cited by 4
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Vogel, W. J., Osborne, T. Z., James, R. T., & Cohen, M. J. (2016) · Environmental Monitoring and Assessment · doi:10.1007/s10661-016-5605-8 · Cited by 4
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Cozzolino, D., Dupont, M. F., Elbourne, A. J., Truong, V. K., Power, A., & Chapman, J. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818732-6.00009-5 · Cited by 4
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Metadata
- Authors
- Huang, H., Yu, H., Xu, H., & Ying, Y.
- Affiliations
- Zhejiang University (CN)
- Corresponding author
- Ying, Yibin
- Venue
- Journal of Food Engineering
- Publisher
- Elsevier BV
- Published
- 2008-08
- Volume
- 87
- Issue
- 3
- Pages
- 303-313
- ISSN
- 0260-8774 (ISSN-L)
- OpenAlex
- W1972600584
- Cited by
- 560
- References
- 96
- Citations by year
- 2026: 22 · 2025: 28 · 2024: 22 · 2023: 29 · 2022: 25 · 2021: 29 · 2020: 33 · 2019: 43 · 2018: 33 · 2017: 45 · 2016: 41 · 2015: 46 · 2014: 30 · 2013: 32 · 2012: 32
- FWCI
- 2.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Food Engineering (publishedVersion)
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Keywords
- near-infrared spectroscopy, real-time process monitoring, food quality control, beverages, meat, fruits, grain, dairy products, chemometrics, food processing
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