Cited by 560Spectroscopy and Chemometric AnalysesOptical Imaging and Spectroscopy TechniquesSpectroscopy Techniques in Biomedical and Chemical Research

The DOI matches its Crossref record; 94 of the 96 references it cites were found in a registry or an index.

Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: A review

Huang, Haibo, Yu, Haiyan, Xu, Huirong, Ying, Yibin·2008·Journal of Food Engineering

DOI 10.1016/j.jfoodeng.2007.12.022

Open this paper in CoChat — free account

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.

Integrity signals

Registry

Crossref · 10.1016/j.jfoodeng.2007.12.022

Cites

94 of 94 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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
Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques
Gómez, A. H., He, Y., & Pereira, A. G. (2005) · Journal of Food Engineering · doi:10.1016/j.jfoodeng.2005.06.036 · Cited by 365
Nondestructive Determination of Sugar Content in Satsuma Mandarin using Near Infrared (NIR) Transmittance.
Kawano, S., Fujiwara, T., & Iwamoto, M. (1993) · Journal of the Japanese Society for Horticultural Science · doi:10.2503/jjshs.62.465 · Cited by 233
Determination of Sugar Content in Intact Peaches by Near Infrared Spectroscopy with Fiber Optics in Interactance Mode.
Kawano, S., Watanabe, H., & Iwamoto, M. (1992) · Journal of the Japanese Society for Horticultural Science · doi:10.2503/jjshs.61.445 · Cited by 218
Process Analytical Chemistry
Workman, J., Koch, M. V., & Veltkamp, D. (2005) · Analytical Chemistry · doi:10.1021/ac050620o · Cited by 204
Detecting and Quantifying Sunflower Oil Adulteration in Extra Virgin Olive Oils from the Eastern Mediterranean by Visible and Near-Infrared Spectroscopy
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

Show all 96 references

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

Sorted by citations

Items 401–500 of 558

Rapid Detecting Soluble Solid Content of Pears Based on Near-Infrared Spectroscopy
Lu, M., Li, C., Li, L., Wu, Y., & Yang, Y. (2018) · IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) · doi:10.1109/imcec.2018.8469315 · Cited by 4
Quantification and characterisation of residual blood in fish muscle : impact of slaughtering methods
Olsen, S. H. (2011) · NORA - Norwegian Open Research Archives · Cited by 4
Dietary Fiber: Determination
Mongeau, R., & Brooks, S. P. J. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-384947-2.00228-2 · Cited by 4
Early-Stage Electrochemical Kinetics of Agave Distillates: Impact of Barrel Toasting on Polyphenol Extraction Dynamics
Piña-Torres, S. S., Gómez-Navarro, C. S., García-Aceves, M., Zárate-Navarro, M. A., Zárate‐Guzmán, A. I., Moral-Rodríguez, A. I., Francisco, C.-M., & Cano, L. A. R. (2026) · Foods · doi:10.3390/foods15010170 · Cited by 3
Evaluating biofibers’ properties and products by NIR spectroscopy
Costa, L. R., Ramalho, F. M. G., & Hein, P. R. G. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-824543-9.00023-2 · Cited by 3
GLCANet: Context Attention for Infrared Small Target Detection
Liu, R., Liu, Q., Wang, X., & Fu, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-981-99-8850-1_20 · Cited by 3
CONTROLLING AND MONITORING OF TEMPERATURE SYSTEM FOR LIVESTOCK
Khan, M. S., Ahmed, Z., Ashraf, M. W., Yasmeen, S., Imran, M. A., Baig, F., Yaseen, N., & Jabeen, S. (2014) · The Journal of Animal and Plant Sciences · Cited by 3
Biosensors for Fruit Quality Monitoring
Hooda, V., Chauhan, N., & Soni, S. (2021) · Concepts and strategies in plant sciences · doi:10.1007/978-3-030-66165-6_15 · Cited by 3
Determination of Specific Volume Fractions in Multicomponent Liquids Using Hydrogel-Functionalized Plasmonic Sensors
Herzog, J., Sobczyk, M., Schuster, C., Härtling, T., Wallmersperger, T., & Gerlach, G. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3371095 · Cited by 3
Non-Destructive In-Process Quality Evaluation Of Plant-Sourced Food During Drying
Nurkhoeriyati, T., Sturm, B., & Hensel, O. (2022) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/995/1/012025 · Cited by 3
Feasibility study of patch antenna for monitoring moisture content of made tea
Shivling, V. D., Singh, A., Bansod, B. K. S., Nag, U., & Meena, D. L. (2022) · Journal of Microwave Power and Electromagnetic Energy · doi:10.1080/08327823.2022.2107572 · Cited by 3
Discrimination of Fungicide-Contaminated Lettuces Based on Maximum Residue Limits Using Spectroscopy and Chemometrics
Neto, A. J. S., de Lima, J. L. M. P., Jardim, A. M. D. R. F., Lopes, D. D. C., & da Silva, T. G. F. (2024) · Horticulturae · doi:10.3390/horticulturae10080828 · Cited by 3
Improving the grain quality assessment fusing data from image and spectra analyses
Mladenov, M., Penchev, S., & Draganova, T. (2012) · IEEE International Conference on Intelligent Systems · doi:10.1109/is.2012.6335118 · Cited by 3
Prediction of the nutritional composition of the crop contents of free-living scarlet macaw chicks by near-infrared reflectance spectroscopy
Cornejo, J., Taylor, R., Sliffe, T., Bailey, C. A., & Brightsmith, D. J. (2012) · Wildlife Research · doi:10.1071/wr11130 · Cited by 3
Physical Sensors and Techniques
Toldr√°, F., Fito, P. J., Fito, P. J., & Castro-Gir√°ldez, M. (2008) · CRC Press eBooks · doi:10.1201/9781420045338.ch2 · Cited by 3
Using PLS and NIR spectra to model the first-breakage step of a grain milling process
Pastro, F. D., Facco, P., Bezzo, F., Zamprogna, E., & Barolo, M. (2016) · Computer-aided chemical engineering/Computer aided chemical engineering · doi:10.1016/b978-0-444-63428-3.50200-9 · Cited by 3
Local Impedance Spectroscopy: A Potential Tool to Characterize the Evolution of Emulsions and Foams
Held, M., Schwaller, P., Vaihinger, M., & Denkel, C. (2017) · Journal of Food Science and Engineering · doi:10.17265/2159-5828/2017.05.003 · Cited by 3
Prediction system for soluble solid content in Averrhoa Carambola based on Vis-NIR image
Rangkuti, M. Y., Saputro, A. H., & Imawan, C. (2017) · doi:10.1109/iceltics.2017.8253269 · Cited by 3
Cotton Revenue Apportioned between Lint Yield and Fiber Quality: A Precision Agriculture Perspective
Ge, Y., Thomasson, J. A., Morgan, C. L. S., Stanislav, S. M., & Sui, R. (2011) · The journal of cotton science/Journal of cotton science · Cited by 3
Environmental origin classification of coffee beans using infrared spectroscopy
Yusmanizar, Y., & Munawar, A. A. (2021) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/922/1/012014 · Cited by 3
Methodologies based on ASCA to elucidate the influence of a subprocess: Vinification as a case of study
Schorn‐García, D., Giussani, B., Busto, O., Aceña, L., Mestres, M., & Boqué, R. (2022) · Journal of Chemometrics · doi:10.1002/cem.3465 · Cited by 3
A Review: Protein-Fortified Low Moisture Extrusion
Beck, S. M., Knoerzer, K., & Arcot, J. (2017) · Elsevier eBooks · doi:10.1016/b978-0-08-100596-5.21101-3 · Cited by 3
Determinación no destructiva de parámetros de calidad de frutas y hortalizas mediante espectroscopía de reflectancia en el infrarrojo cercano
Rojas, F., & Ubina, K. (2009) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · Cited by 3
Transmisión óptica e imagen en visible e infrarrojo en frutas : ensayo de equipos comerciales
Torres, M. T. R. (2008) · doi:10.20868/upm.thesis.1469 · Cited by 3
Predicting cadmium accumulation in carrot (Daucus carota L.) using reflectance spectroscopy and machine learning
Maugeais, N., & Lassalle, G. (2025) · Food Control · doi:10.1016/j.foodcont.2025.111226 · Cited by 2
An overview of sample and spectrum preparation methods for near-infrared spectroscopy
Görbe, M. (2025) · Gradus · doi:10.47833/2025.1.eng.009 · Cited by 2
Spatial Variation of Cooked Temperature in Pork Measured by Spontaneous Raman Spectroscopy
Narvaez, K., Ballantyne, E., Wood, S. M., & Shipp, D. W. (2025) · Journal of Raman Spectroscopy · doi:10.1002/jrs.70000 · Cited by 2
Smart Food Production: Integration of IEC 61499 in Real-Time Control System
Buonocore, D., Paciello, V., da Rocha, H., Espírito-Santo, A., & Abrishambaf, R. (2025) · IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) · doi:10.1109/metroind4.0iot66048.2025.11122094 · Cited by 2
Near-infrared quantitative modelling of maize seed moisture based on hybrid spectroscopy and CARS-SPA coupling algorithm
Zhang, R., Wang, J., Wang, W., Xia, D., Bu, Y., & Yang, C. (2025) · Journal of Food Measurement & Characterization · doi:10.1007/s11694-025-03678-9 · Cited by 2
Optimizing NIR spectral preprocessing for PLS predictive accuracy: a systematic review (2019-2024)
Wahab, M., Zia, A., Ahmad, W., Zakarya, M., & Haleem, M. (2026) · Discover Applied Sciences · doi:10.1007/s42452-026-08608-y · Cited by 2
Physics-augmented hyperspectral sensing for soybean moisture assessment: Compensating packing density effects via computer vision
Han, M., Sun, T., Jin, Z., & Xu, M. (2026) · Journal of Agriculture and Food Research · doi:10.1016/j.jafr.2026.102881 · Cited by 2
Comparative Analysis of Wheat Grain Protein Content: Wet Chemistry and NIR Based Methods
Mahato, G., Graebner, R. C., Hunt, M., Namdar, G. F., Plunkett, R., Wood, D., Krause, M., Singh, S., Calderón, F. J., & Hagerty, C. H. (2026) · Food Analytical Methods · doi:10.1007/s12161-026-03123-7 · Cited by 2
Temperature Dependent NIR Spectroscopic Analysis for Food Grain Samples
Shah, M., Bhatt, C. B., & Dave, J. (2016) · Indian Journal of Science and Technology · doi:10.17485/ijst/2016/v9i9/85306 · Cited by 2
Off-line detection of milling processes of Pannon wheat classes by near infrared spectroscopic methods
Izsó, E., Bartalné-Berceli, M., Salgó, A., & Gergely, S. (2018) · Quality Assurance and Safety of Crops & Foods · doi:10.3920/qas2016.1059 · Cited by 2
A wavelength selection method based on optical properties for slight bruise detection on Fuji apples in the early stage
Cai, S., Zhang, S., Tan, Z., & Cheng, Q. (2023) · Optik · doi:10.1016/j.ijleo.2023.171121 · Cited by 2
Near-Infrared Spectroscopy
Yang, X., & Berzaghi, P. (2024) · Springer eBooks · doi:10.1007/978-3-031-76465-3_3 · Cited by 2
Utilization of Near Infrared (NIR) Spectrometry for Detection of Glass in the Waste-based Fuel
Škvařil, J., Kyprianidis, K., Avelin, A., Odlare, M., & Dahlquist, E. (2015) · Energy Procedia · doi:10.1016/j.egypro.2015.07.502 · Cited by 2
Towards automated detection of milk spot livers by diffuse reflectance spectroscopy
Cugmas, B., Bürmen, M., Jemec, J., Pernuš, F., & Likar, B. (2013) · Journal of Food Engineering · doi:10.1016/j.jfoodeng.2013.10.013 · Cited by 2
Near infrared microcoupler with multilayer isotropic metamaterials
Li, K., Tian, C., Liu, S., Zhang, J., Lv, H., & Zhu, X. (2015) · Journal of Applied Physics · doi:10.1063/1.4933068 · Cited by 2
In-line characterization of ground oilseeds concentration in solid-liquid dispersions in the food industry
Marconati, M., Haiduc, A. M., Berrut, S., Mora, F., Santomaso, A. C., & Cavinato, M. (2016) · LWT · doi:10.1016/j.lwt.2016.11.053 · Cited by 2
APPLICATION OF VIS/NIR SPECTROSCOPY TO ESTABLISH PEACH RIPENING AS AFFECTED BY ROOTSTOCK
Betemps, D. L., Fachinello, J. C., Machado, N. P., Galarça, S. P., Remorini, D., Massai, R., & Agati, G. (2015) · Acta Horticulturae · doi:10.17660/actahortic.2015.1084.87 · Cited by 2
Physical Sensors and Techniques
Cánovas, R., Suñer, P. J. F., Grau, A., & Maupoey, P. F. (2009) · CRC Press eBooks · doi:10.1201/9781420046359-c12 · Cited by 2
Precision opto-imaging techniques for seed quality assessment: prospects and scope of recent advances
Sarmah, B., Rajkhowa, R., Chakraborty, I., Govindaraju, I., Dwivedi, S. K., Mazumder, N., & Baruah, V. J. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-91068-2.00012-6 · Cited by 2
A Decision Support Tool to Analyze Food Properties from Near Infrared Spectroscopy*
Parrenin, L., Lorbieski, R., Jaraceski, J. C., Danjou, C., & Bruno Agard, A. (2023) · IEEE International Conference on Industry Applications · doi:10.1109/induscon58041.2023.10374963 · Cited by 2
Fingerprinting for Detecting Contaminants in Food
Böhme, K., Barros‐Velázquez, J., & Calo‐Mata, P. (2016) · Elsevier eBooks · doi:10.1016/b978-1-78242-251-8.00002-3 · Cited by 2
Growth and characterization of broad spectrum infrared emitting GaInAsP/InP heterostructures
Rakovics, V., Nádas, J., Réti, I., Dücső, C., & Battistig, G. (2016) · Journal of Crystal Growth · doi:10.1016/j.jcrysgro.2016.11.123 · Cited by 2
Fruit orientation in NIR transmission for vascular browning in apples
Sun, J., Künnemeyer, R., McGlone, A., & Tomer, N. (2017) · International Conference on Sensing Technology · doi:10.1109/icsenst.2017.8304490 · Cited by 2
NIR Spectroscopy Coupled with Chemometrics as a Tool for Quality Analysis of Beer Samples
Wójcicki, K. (2019) · Towaroznawcze Problemy Jakości. Polskie Towarzystwo Towaroznawcze · Cited by 2
Methods to Assess Biological Transformation of Biomass
Carrère, H., Αντωνοπούλου, Γ., Druilhe, C., Latrille, É., Lyberatos, G., Jimenez, J., Ντάϊκου, Ι., Παπαδοπούλου, Κ., Trably, É., & Trémier, A. (2020) · Springer eBooks · doi:10.1007/978-3-030-35020-8_5 · Cited by 2
Magnitude estimation—alignment of sensory and instrumental analysis
O’Sullivan, M. G. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819741-7.00012-2 · Cited by 2
The combined use of GC, PDSC and FT-IR techniques to characterize fat extracted from commercial complete dry pet food for adult cats
Zglińska, K., Niemiec, T., Bryś, J., Bryś, A., Łozicki, A., Kosieradzka, I., & Koczoń, P. (2020) · Open Chemistry · doi:10.1515/chem-2020-0146 · Cited by 2
Thoughts for Foods: Imaging Technology Opportunities for Monitoring and Measuring Food Quality
Eissa, A. H. A., Helyes, L., Romano, E., Albandary, A., & Ibrahim, A. (2021) · IntechOpen eBooks · doi:10.5772/intechopen.99532 · Cited by 2
Investigating physical properties of solid dosage forms during pharmaceutical processing : Process analytical applications of vibrational spectroscopy
Römer, M. (2008) · Työväentutkimus Vuosikirja · Cited by 2
Monitoring and Control of Mixing Operations
Fagan, C. C., Cullen, P. J., & O’Donnell, C. P. (2009) · Wiley eBooks · doi:10.1002/9781444312928.ch7 · Cited by 2
NIR techniques and chemometrics data analysis applied to food adulteration detection
Sabio, S. F. (2015) · UPCommons institutional repository (Universitat Politècnica de Catalunya) · Cited by 2
The cascade of physiological events leading to chilling injury : the effect of post-harvest hot water and molybdenum applications to lemon (citrus limon) fruit.
Mathaba, N. (2012) · Cited by 2
Vibrational and Fluorescence Spectroscopy
Cozzolino, D. (2017) · Wiley eBooks · doi:10.1002/9781118810224.ch8a · Cited by 2
Optical reflectance in fibrous tissues and skeletal muscles
Ranasinghesagara, J. C. (2008) · doi:10.32469/10355/6629 · Cited by 2
Nitrogen status assessment for multiple cultivars of strawberries using portable NIR spectrometers combined with cultivar recognition and multivariate analysisPreprint
Wu, G., Jiang, Q., Bai, Y., Tian, C., Pan, W. D., & Zhang, B. (2019) · doi:10.21203/rs.2.19371/v1 · Cited by 2
Research on nutrition and feeding of farmed shrimp
Cortés‐Jacinto, E., Villarreal, H., Lizárraga-Hernández, F. D., Méndez‐Martínez, Y., Cienfuegos‐Martínez, K., & Hernández, L. H. H. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-27358-2.00006-3 · Cited by 1
Chemometrics, Infrared Sensors and Precision Fermentation – Where are We?
Alagappan, S., Nastasi, J. R., Hoffman, L. C., & Cozzolino, D. (2026) · Food Reviews International · doi:10.1080/87559129.2026.2643455 · Cited by 1
Advanced spectroscopic techniques to investigate on the primary metabolome of the Vallo di Diano onion and highlight diagnostic compositional and nutraceutical features
Graziano, M. L., Ferrara, C., Cardiello, C., Pepe, R., Falco, E. D., & Mazzei, P. (2026) · Journal of Food Composition and Analysis · doi:10.1016/j.jfca.2026.109379 · Cited by 1
Complex assessment of grain quality using image and spectra analyses
Mladenov, M., Dejanov, M., & Tsenkova, R. N. (2014) · Journal of Food Measurement & Characterization · doi:10.1007/s11694-014-9179-2 · Cited by 1
Working with a Set of Filter near Infrared Instruments
Gatius, F., Llovera, A., Lloveras, J. G., & Puy, J. (2011) · Journal of Near Infrared Spectroscopy · doi:10.1255/jnirs.917 · Cited by 1
Espectroscopia do visível e infra-vermelho próximo para estimar sólidos solúveis e firmeza de polpa em função da época de colheita em pêssegos
Betemps, D. L., Fachinello, J. C., Galarça, S. P., Machado, N. P., Remorini, D., Massai, R., & Agati, G. (2014) · Semina Ciências Agrárias · doi:10.5433/1679-0359.2014v35n3p1257 · Cited by 1
El uso del NIRS como alternativa viable en el análisis químico en dietas para alimento animal.
Lizárraga-Hernández, F. D., Aguero-Fernandez, Y. M., Cortés‐Jacinto, E., Vega‐Villasante, F., Vargas-Ceballos, M. A., & Martín-Manzo, M. V. (2022) · Recursos Naturales y Sociedad · doi:10.18846/renaysoc.2022.08.08.02.0003 · Cited by 1
Nondestructive quality evaluation and monitoring of Braeburn apples by Spatially Resolved Spectroscopy
Nguyen, N., Tsuta, M., Erkinbaev, C., Mathijs, F., Cantero, G. P. M., Elorza, P. B., Verboven, P., Nicolaï, B. M., & Saeys, W. (2013) · Lirias · Cited by 1
A custom hardware classifier for bruised apple detection in hyperspectral images
Cárdenas, J., Figueroa, M. E., & Pezoa, J. E. E. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2188578 · Cited by 1
Estimation of Wheat Flour Ash Contents by Electron Spin Resonance Spectroscopy with Partial Least Squares Regression Analysis
Kameya, H., Tsuta, M., Fujita, K., Todoriki, S., & Sugiyama, J. (2016) · NIPPON SHOKUHIN KOGYO GAKKAISHI · doi:10.3136/nskkk.63.127 · Cited by 1
Non-destructive characterization of food microstructure and composition by Spatially Resolved Spectroscopy
Nguyen, N., Tsuta, M., Herremans, E., Watté, R., Erkinbaev, C., Verhoelst, E., Verboven, P., Nicolaï, B. M., & Saeys, W. (2011) · Lirias · Cited by 1
Interface Engineering to Enhance the Photoresponse of Core-Shell Structure Silicon Nanowire Photodetectors
Kim, K., Yoon, S., Cho, H., Meyyappan, M., & Baek, C.-K. (2019) · IEEE International Conference on Nanotechnology (IEEE-NANO) · doi:10.1109/nano46743.2019.8993954 · Cited by 1
Zastosowanie spektroskopii bliskiej podczerwieni do analizy wartości odżywczej produktów garmażeryjnych i makaronów dostępnych na polskim rynku
Dudkiewicz, A., Koźniewski, B., & Szymańska, A. (2020) · Zywnosc-nauka Technologia Jakosc · doi:10.15193/zntj/2020/123/337 · Cited by 1
Nondestructive Analysis of Soluble Solids Content in Apple with a Portable NIR Spectrometer
Guo, C., Han, C., Yan, H. H., & Li, L. (2022) · Springer eBooks · doi:10.1007/978-981-19-4884-8_16 · Cited by 1
Characterisation of soils with the use of instrumental techniques : a multivariate forensic study
Onions, K. L. (2009) · Cited by 1
Vibrational Spectroscopy Techniques in the Quality Assessment of Fruits and Vegetables
Polshin, E., Lammertyn, J., & Nicolaï, B. M. (2001) · Wiley eBooks · doi:10.1002/0470027320.s8954 · Cited by 1
Desenvolvimento e validação de métodos para quantificação de ivermectina em medicamentos veterinários
Arantes, J. F. M. (2011) · doi:10.47749/t/unicamp.2011.789367 · Cited by 1
Optical fibre sensor for fuel cell and other fluid concentration measurement
Fabian, M. (2013) · University of Limerick Institutional Repository (University of Limerick) · doi:10.34961/3546 · Cited by 1
Amylose content calibration model for the three types of selected rice grains using visible shortwave near infrared spectroscopy
Ibrahim, S. (2015) · Cited by 1
Effective use of product quality information in food supply chain logistics
Rijpkema, W. A. (2014) · doi:10.18174/305198 · Cited by 1
Rapid Estimation of Bioactive Phytochemicals in Vegetables and Fruits Using Near Infrared Reflectance Spectroscopy
Kumar, S., Singh, R., & Dhanani, T. (2017) · Wiley eBooks · doi:10.1002/9781119158042.ch35 · Cited by 1
The Use of Non‐destructive Techniques to Assess the Nutritional Content of Fruits and Vegetables
Amodio, M. L., Chaudhry, M. M. A., & Colelli, G. (2017) · Wiley eBooks · doi:10.1002/9781119158042.ch34 · Cited by 1
Microscale Modelling of Cellular Level Transport and Deformation during Food Drying
Rahman, M. M. (2018) · Queensland University of Technology · doi:10.5204/thesis.eprints.120676 · Cited by 1
Classification and quantification of defective and non-defective coffees by FTIR and NIR spectroscopy
Carneireiro, A. P. C. (2013) · Americanae (AECID Library) · Cited by 1
Fish Traceability and Authenticity
Sotelo, C. G., Gunnlaugsson, V. N., Schröder, U. B., Mendes, R. O., van Kappel, K., Silva, H. A., & Verrez‐Bagnis, V. (2023) · Wiley eBooks · doi:10.1002/9781394264728.ch4 · Cited by 1
Effect of processing and formulation on water migration through lipids
Duong, Q. (2014) · Cited by 1
Aplicación en tiempo real en almazaras de la tecnología aotf-nir para la mejora del control de producción, control de calidad y trazabilidad del aceite de oliva
Rodríguez, R. C. (2011) · Sumuntán: anuario de estudios sobre Sierra Mágina
Fast Discrimination of Nanfeng Mandarin Varieties Based on Near Infrared Spectroscopy Technique
Zhou, H., Zhou, C., Rao, H., & Liu, Y. (2011) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-3-642-18354-6_72
Study of innovative methods of control in the cereal productive chain for the production of beer and spirits
Sileoni, V. (2011) · AMS Dottorato Institutional Doctoral Theses Repository (University of Bologna) · doi:10.6092/unibo/amsdottorato/3575
Application of OSC in Sugar Content Evaluation of Chestnut Based on near Infrared Spectroscopy
Liu, J., Li, X. Y., Wang, W., Zhang, J., & Zhou, W. (2014) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.701-702.577
Ecological and rapid control of relevant technological factors of rapeseed oil pressing process
Radzio, A., Błaszczyk, A., & Jasiczak, J. (2013) · Towaroznawcze Problemy Jakości. Polskie Towarzystwo Towaroznawcze
Source Modulated Multiplexed Hyperspectral Imaging: Theory, Hardware and Application
Streeter, L. V. (2009) · Research Commons (University of Waikato)
Bioprocess monitoring and chemometric modelling of wine fermentations
Garlick, J. L. (2013) · SUNScholar (Stellenbosch University)
Industrial Implementation of the New Nir Laser-Based Sensor for Measuring Surface Moisture in Polymers
Hudoklin, D., Lopez, I. M., Begeš, G., Drnovšek, J., & Beguš, S. (2015) · International Congress of Metrology (CIM) · doi:10.1051/metrology/20150011003
ENGINEERING AND GINNING Cotton Revenue Apportioned between Lint Yield and Fiber Quality: A Precision Agriculture Perspective
Ge, Y., Thomasson, J. A., Stanislav, S. M., & Sui, R. (2011)
INTECHN PLATFORM FOR GRAIN SAMPLE QUALITY ASSESSMENT
Mladenov, M. (2011) · Bulgarian Portal for Open Science
Uso de espectrometria para investigação da qualidade da cana-de-açúcar em campo
Ferraz, M. N. (2015) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.11.2015.tde-16112015-145255
Sistema integrado de análise e distribuição de resultados aplicados à bebida de açaí
Koizimi, S. M. L. (2011) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
INDUSTRIAL IMPLEMENTATION OF THE NEW NIR LASER-BASED SENSOR FOR MEASURING SURFACE MOISTURE IN POLYMERS en œuvre industrielle d'un nouveau capteur, utilisant le proche infra-rouge laser, pour mesurer l'humidité en surface des polymères
Hudoklin, D., & López, M. (2015)
In-plant validation of an ethanol yield prediction equation
Korte, M. (2015) · doi:10.31274/etd-180810-4408
Broadband photon time of flight spectroscopy: advanced spectroscopic analysis for ensuring safety and performance of pharmaceutical tablets
Kamran, F., Nielsen, O. H., Andersson‐Engels, S., & Khoptyar, D. (2013) · Asia Communications and Photonics Conference · doi:10.1364/acp.2013.af3k.4

Authors: Huang, H., Yu, H., Xu, H., & Ying, Y.
Affiliations: Zhejiang University (CN)
Corresponding author: Ying, Yibin
ORCID: Huang, Haibo
Xu, Huirong
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)
DOI: 10.1016/j.jfoodeng.2007.12.022
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
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: A review

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks