In Situ Monitoring of Sugar Content in Breakfast Cereals Using a Novel FT-NIR Spectrometer
Source abstract
Abstract
This research demonstrates simultaneous predictions of individual and total sugars in breakfast cereals using a novel, handheld near-infrared (NIR) spectroscopic sensor. This miniaturized, battery-operated unit based on Fourier Transform (FT)-NIR was used to collect spectra from both ground and intact breakfast cereal samples, followed by real-time wireless data transfer to a commercial tablet for chemometric processing. A total of 164 breakfast cereal samples (60 store-bought and 104 provided by a snack food company) were tested. Reference analysis for the individual (sucrose, glucose, and fructose) and total sugar contents used high-performance liquid chromatography (HPLC). Chemometric prediction models were generated using partial least square regression (PLSR) by combining the HPLC reference analysis data and FT-NIR spectra, and associated calibration models were externally validated through an independent data set. These multivariate models showed excellent correlation (Rpre ≥ 0.93) and low standard error of prediction (SEP ≤ 2.4 g/100 g) between the predicted and the measured sugar values. Analysis results from the FT-NIR data, confirmed by the reference techniques, showed that eight store-bought cereal samples out of 60 (13%) were not compliant with the total sugar content declaration. The results suggest that the FT-NIR prototype can provide reliable analysis for the snack food manufacturers for on-site analysis.
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Research context
OpenAlex topics: Spectroscopy and Chemometric Analyses · Spectroscopy Techniques in Biomedical and Chemical Research · Advanced Chemical Sensor Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Food Science and Technology, The Ohio State University, 110 Parker Food Science and Technology Building, 2015 Fyffe Road, Columbus, OH 43210, USA
Department of Food Engineering, Faculty of Engineering, Adnan Menderes University, Aydin 09100, Turkey
ElectroScience Laboratory, The Ohio State University, 1330 Kinnear Road, Columbus, OH 43212, USA
Department of Food Engineering, Faculty of Engineering and Natural Sciences, Gumushane University, Gumushane 29100, Turkey
References (48)
Show source-provided references
1. (2020, January 09). Credence Research Breakfast Cereals Market by Product (Hot Cereals, Ready to Eat)—Growth, Future Prospects, Competitive Analysisi and Forecast to 2016–2023. Available online: https://www.credenceresearch.com/report/breakfast-cereals-market.
2. (2020, January 09). Grand View Research Breakfast Cereal Market Size, Share & Trends Analysis Report by Product (RTE, Hot Cereal), by Distribution Channel (Supermarket, E-Commerce, Convenience Store), by Region, Vendor Landscape, and Segment Forecasts, 2018–2025. Available online: https://www.grandviewresearch.com/industry-analysis/breakfast-cereals-market.
3. Perdon, A.A., Poutanen, K.S., and Schonauer, S.L. (2020). Breakfast Cereals and How They Are Made—Introduction, Elsevier Inc.10.1016/B978-0-12-812043-9.00001-1 ↗
4. The Benefits of Breakfast Cereal Consumption: A Systematic Reviewof the Evidence Base10.3945/an.114.006247 ↗
5. Breakfast cereals—Why all the bad press?10.1111/j.1467-3010.2009.01797.x ↗
6. Nutritional quality, labelling and promotion of breakfast cereals on the New Zealand market10.1016/j.appet.2014.06.019 ↗
7. (2020, July 09). FDA Guidance for Industry: Guide for Developing and Using Data Bases for Nutrition Labeling, Available online: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/guidance-industry-guide-developing-and-using-data-bases-nutrition-labeling.
8. Laboratory determined sugar content and composition of commercial infant formulas, baby foods and common grocery items targeted to children10.3390/nu7075254 ↗
9. The use of invertase for determination of sucrose. Application to cereals, cereal products, and other plant materials
10. Changes in sugar profile during infant cereal manufacture10.1016/S0308-8146(01)00170-4 ↗
11. Gas-Liquid Chromatographic Analysis of Sugars in Ready-to-Eat Breakfast Cereals10.1111/j.1365-2621.1980.tb03889.x ↗
12. Comparative evaluation of extraction procedures and method validation for determination of carbohydrates in cereals and dairy products by capillary electrophoresis10.1002/jssc.200600370 ↗
13. Optimization and Validation of an HPAEC-PAD Method for the Quantification of FODMAPs in Cereals and Cereal-Based Products10.1021/acs.jafc.9b00382 ↗
14. (2007). AOAC International AOAC Official Method 982.14, Official Methods of Analysis.
15. Analysis of mono- and disaccharides in milk-based formulae by high-performance liquid chromatography with refractive index detection10.1016/j.chroma.2004.06.002 ↗
16. Near-Infrared Reflectance Measurement of Total Sugar Content of Breakfast Cereals10.1366/0003702854250338 ↗
17. Wang, T., and Rodriguez-Saona, L.E. (2012). Rapid Determination of Sugar Level in Snack Products Using Infrared Spectroscopy. J. Food Sci., 77.10.1111/j.1750-3841.2012.02824.x ↗
18. Predicting macronutrients and energy content of snack products using FT-NIR analysis and chemometric techniques10.1016/j.jfoodeng.2020.109954 ↗
19. Measurement of fat and sucrose in dry cake mixes by near infrared reflectance spectroscopy10.1111/j.1365-2621.1983.tb00304.x ↗
20. Application of Portable and Handheld Infrared Spectrometers for Determination of Sucrose Levels in Infant Cereals10.1007/s12161-013-9763-9 ↗
21. Shotts, M.-L., Plans, M., Wong, K., Milligan, A.M., Aykas, D.P., and Rodriguez-Saona, R.E. (2020). Application of mid-infrared portable spectrometer for the rapid determination of trans-fatty acid content in lipid extracts of snack and bakery products. J. AOAC Int.10.1093/jaoacint/qsaa116 ↗
22. Fast method for the determination of total fat and trans fatty-acids content in bakery products based on microwave-assisted Soxhlet extraction and medium infrared spectroscopy detection10.1016/j.aca.2004.04.067 ↗
23. Application of NIR and MIR spectroscopy in quality control of potato chips10.1016/j.jfca.2008.09.003 ↗
24. Analytical Methods Assessing potato chip oil quality using a portable infrared spectrometer combined with pattern recognition analysis10.1039/C5AY02387D ↗
25. Rodriguez-Saona, L., Aykas, D.P., Borba, K.R., and Urbina, A.U. (2020). Miniaturization of Optical Sensors and their Potential for High-Throughput Screening of Foods. Curr. Opin. Food Sci.10.21748/am20.117 ↗
26. Matching portable NIRS instruments for in situ monitoring indicators of milk composition10.1016/j.foodcont.2017.01.004 ↗
27. Application of a portable handheld infrared spectrometer for quantitation of trans fat in edible oils10.1007/s11746-011-1814-z ↗
28. Authentication of commercial honeys based on Raman fingerprinting and pattern recognition analysis10.1016/j.foodcont.2020.107346 ↗
29. Determination of sucrose content in sugar beet by portable visible and near-infrared spectroscopy10.1016/j.foodchem.2014.06.117 ↗
30. Zhu, G., and Tian, C. (2018). Determining sugar content and firmness of ‘Fuji’ apples by using portable near-infrared spectrometer and diffuse transmittance spectroscopy. J. Food Process Eng., 41.10.1111/jfpe.12810 ↗
31. Calibration Transfer from Micro NIR Spectrometer to Hyperspectral Imaging: A Case Study on Predicting Soluble Solids Content of Bananito Fruit (Musa acuminata)10.1007/s12161-017-1055-3 ↗
32. Ultra-portable, wireless smartphone spectrometer for rapid, non-destructive testing of fruit ripeness10.1038/srep32504 ↗
33. Comprehensive study of solid pharmaceutical tablets in visible, near infrared (NIR), and longwave infrared (LWIR) spectral regions using a rapid simultaneous ultraviolet/visible/NIR (UVN) + LWIR laser-induced breakdown spectroscopy linear arrays detection system and a fast acousto-optic tunable filter NIR spectrometer10.1364/OE.25.026885 ↗
34. Color compensation and comparison of shortwave near infrared and long wave near infrared spectroscopy for determination of soluble solids content of “Fuji” apple10.1016/j.postharvbio.2015.12.027 ↗
35. Partial least squares regression and projection on latent structure regression (PLS Regression)10.1002/wics.51 ↗
36. Salt and sugars content of breakfast cereals in the UK from 1992 to 201510.1017/S1368980016003463 ↗
37. Nieto, C., Patiño, S.R.G., Tolentino-Mayo, L., Carriedo, A., and Barquera, S. (2017). Characterization of breakfast cereals available in the Mexican market: Sodium and sugar content. Nutrients, 9.10.3390/nu9080884 ↗
38. Examining the Nutritional Quality of Breakfast Cereals Marketed to Children10.1016/j.jada.2008.01.003 ↗
39. Prediction of Total Dietary Fiber by Near-Infrared Reflectance Spectroscopy in Cereal Products Containing High Sugar and Crystalline Sugar10.1021/jf9703260 ↗
40. Near-infrared analysis of soluble and insoluble dietary fiber fractions of cereal food products10.1021/jf0116552 ↗
41. Development of a rapid, non-destructive method for egg content determination in dry pasta using FT-NIR technique10.1016/j.jfoodeng.2011.06.024 ↗
42. Comparison of NIR and MIR spectroscopic methods for determination of individual sugars, organic acids and carotenoids in passion fruit10.1016/j.foodres.2013.10.051 ↗
43. Mid-infrared spectroscopy as a tool for rapid determination of internal quality parameters in tomato10.1016/j.foodchem.2010.10.012 ↗
44. Quantification of glucose, fructose and sucrose in bayberry juice by NIR and PLS10.1016/j.foodchem.2008.10.076 ↗
45. Determining sucrose and glucose levels in dual-purpose sorghum stalks by Fourier transform near infrared (FT-NIR) spectroscopy10.1002/jsfa.6606 ↗
46. Rapid determination of sucrose in chocolate mass using near infrared spectroscopy10.1016/j.aca.2008.10.049 ↗
47. Burns, D.A., and Ciurczak, E.W. (2008). Application of NIR Spectroscopy to Agricultural Products. Handbook of Near-Infrared Analysis, CRC Press.
48. Fast, R.B., and Caldwell, E.F. (2000). Application of Nutritional and Flavoring/Sweetening Coatings. Breakfast Cereals and How They Are Made, American Association of Cereal Chemists.10.1094/1891127152 ↗