Optics and photonics for food quality and nutrition
DOI:
https://doi.org/10.32870/jbf.v5i10.116Keywords:
optics, agriphotonics, laser, food quality, nutrients, food 3D printing, spectroscopy, obesityAbstract
Optical and photonic technologies (OPT) have a profound impact on many aspects of everyday life. In the agrifood sector, they have proven especially valuable for enabling precision agriculture and crop monitoring, as well as for applications such as food quality control, removal of surface contaminants, and detection of food fraud. This article briefly highlights a few examples of OPT applications in the field of nutrition. Spectroscopic techniques, in particular, are highly effective for analyzing the presence of nutrients, first in plants, then in food products, and even within the human body. Emerging innovations such as laser 3D printing and laser cooking offer promising avenues for producing customized foods tailored to individual dietary requirements. Finally, OPT-based methods provide reliable tools for assessing obesity and related health parameters.
Downloads
References
Acosta, M., Quiñones, A., Munera, S., de Paz, J. M., & Blasco, J. (2023). Rapid prediction of nutrient concentration in Citrus leaves using Vis-NIR spectroscopy. Sensors, 23(14), 6530. https://doi.org/10.3390/s23146530
Acosta, M., Rodríguez-Carretero, I., Blasco, J., de Paz, J. M., & Quiñones, A. (2023). Non-destructive appraisal of macro- and micronutrients in persimmon leaves using Vis/NIR hyperspectral imaging. Agriculture, 13(4), 916. https://doi.org/10.3390/agriculture13040916
Al-Azzawi, A. (2007). Fiber Optics: Principles and Practices. CRC Press.
Ali, L. M., Ahmed, A. E. R. A. E. R., Hasan, H. E. S., Suliman, A. E. R. E., & Saleh, S. S. (2022). Quality characteristics of strawberry fruit following a combined treatment of laser sterilization and guava leaf-based chitosan nanoparticle coating. Chemical and Biological Technologies in Agriculture, 9(1), 80. https://doi.org/10.1186/s40538-022-00343-x
Armand, T., Poupi, T., Nfor, K. A., Kim, J.-I., & Kim, H.-C. (2024). Applications of artificial intelligence, machine learning, and deep learning in nutrition: A systematic review. Nutrients, 16(7), 1073. https://doi.org/10.3390/nu16071073
Bennett, J. P., Liu, Y. E., Quon, B. K., Kelly, N. N., Wong, M. C., Kennedy, S. F., … & Shepherd, J. A. (2022). Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner. Clinical Nutrition, 41(1), 211–218. https://doi.org/10.1016/j.clnu.2021.11.031
Blutinger, J. D., Meijers, Y., Chen, P. Y., Zheng, C., Grinspun, E., & Lipson, H. (2018). Characterization of dough baked via blue laser. Journal of Food Engineering, 232, 56–64. https://doi.org/10.1016/j.jfoodeng.2018.03.022
Blutinger, J. D., Meijers, Y., Chen, P. Y., Zheng, C., Grinspun, E., & Lipson, H. (2019). Characterization of CO2 laser browning of dough. Innovative Food Science and Emerging Technologies, 52, 145–157. https://doi.org/10.1016/j.ifset.2018.11.013
Blutinger, J. D., Tsai, A., Storvick, E., Seymour, G., Liu, E., Samarelli, N., … & Lipson, H. (2021). Precision cooking for printed foods via multiwavelength lasers. Npj Science of Food, 5(1), 24. https://doi.org/10.1038/s41538-021-00107-1
Blutinger, J. D., Cooper, C. C., Karthik, S., Tsai, A., Samarelli, N., Storvick, E., … & Lipson, H. (2023). The future of software-controlled cooking. Npj Science of Food, 7(1), 6. https://doi.org/10.1038/s41538-023-00182-6
Borugadda, P., & Kalluri, H. K. (2025). A comprehensive analysis of artificial intelligence, machine learning, deep learning and computer vision in food science. Journal of Future Foods. Available online 8 July 2025. https://doi.org/10.1016/j.jfutfo.2025.07.002
Butt, M. A., Voronkov, G. S., Grakhova, E. P., Kutluyarov, R. V., Kazanskiy, N. L., & Khonina, S. N. (2022). Environmental monitoring: A comprehensive review on optical waveguide and fiber-based sensors. Biosensors, 12(11), 1038. https://doi.org/10.3390/bios12111038
Chandra, A., Kumar, V., Garnaik, U. C., Dada, R., Qamar, I., Goel, V. K., & Agarwal, S. (2024). Unveiling the molecular secrets: A comprehensive review of Raman Spectroscopy in biological research. ACS Omega, 9(51), 50049–50063. https://doi.org/10.1021/acsomega.4c00591
Chavan, P., Yadav, R., Sharma, P., & Jaiswal, A. K. (2023). Laser light as an emerging method for sustainable food processing, packaging, and testing. Foods, 12(16), 2983. https://doi.org/10.3390/foods12162983
Duarte Molina, F., Gomez, P. L., Castro, M. A., & Alzamora, S. M. (2016). Storage quality of strawberry fruit treated by pulsed light. Fungal decay, water loss and mechanical properties. Innovative Food Science Emerging Technologies, 34, 267–274. https://doi.org/10.1016/j.ifset.2016.01.019
Dutta, S., & Paul, D. (2023). A review on design and development of smartphone-integrated optical fiber sensors. Fiber and Integrated Optics, 42(5), 162–184. https://doi.org/10.1080/01468030.2023.2261006
European Commission (2020). Farm to Fork strategy. https://food.ec.europa.eu/system/files/2020-05/f2f_action-plan_2020_strategy-info_en.pdf (Accessed on 20 October 2025)
Elsherif, M., Salih, A. E., Muñoz, M. G., Alam, F., AlQattan, B., Antonysamy, D. S., …& Butt, H. (2022). Optical fiber sensors: Working principle, applications, and limitations. Advanced Photonics Research, 3(11), 2100371. https://doi.org/10.1002/adpr.202100371
Fujimaru, T., Ling, Q., & Morrissey, M. T. (2012). Effects of Carbon Dioxide (CO2) laser perforation as skin pretreatment to improve sugar infusion process of frozen blueberries. Journal of Food Science, 77(2), E45–E51. https://doi.org/10.1111/j.1750-3841.2011.02525.x
Fujiwara, K., Igeta, Y., Toba, K., Ogawa, J., Furukawa, H., Hashizume, M., … & Ito, N. (2025). Laser cook fusion: Layer-specific gelation in 3D food printing via blue laser irradiation. Food and Bioprocess Technology, 18(7), 6265–6281. https://doi.org/10.1007/s11947-025-03817-6
GNR. (2022). Global Nutrition Report. https://globalnutritionreport.org/reports/2022-global-nutrition-report/ (Accessed on 6 October 2025)
Gonca, S., Polat, B., Ozay, Y., Ozdemir, S., Kucukkara, I., Atmaca, H., & Dizge, N. (2023). Investigation of diode laser effect on the inactivation of selected Gram negative bacteria, Gram positive bacteria and yeast and its disinfection on wastewater and natural milk. Environmental Technology, 44(9), 1238–1250. https://doi.org/10.1080/09593330.2021.2000036
Gracia Julià, A. (2019). Laser cooking system applied to a 3D food printing device [Doctoral dissertation]. UAB, Barcelona.
Guarnieri Lopez, M., Matthes, K.L., Sob, C., Bender, N., & Staub, K. (2023). Associations between 3d surface scanner derived anthropometric measurements and body composition in a cross-sectional study. European Journal of Clinical Nutrition, 77(10), 972–981. https://doi.org/10.1038/s41430-023-01309-4
Gupta, S., Huang, C. H., Singh, G. P., Park, B. S., Chua, N.-H., & Ram, R. J. (2020). Portable Raman leaf-clip sensor for rapid detection of plant stress. Scientific Reports, 10(1), 20206. https://doi.org/10.1038/s41598-020-76485-5
Han, Y., Cheng, Q., Wu, W., & Huang, Z. (2023). DPF-Nutrition: Food nutrition estimation via depth prediction and fusion. Foods, 12(23), 4293. https://doi.org/10.3390/foods12234293
He, H.-J., da Silva Ferreira, M. V., Wu, Q., Karami, H., & Kamruzzaman, M. (2025). Portable and miniature sensors in supply chain for food authentication: a review. Critical Reviews in Food Science and Nutrition, 65(20), 3966–3986. https://doi.org/10.1080/10408398.2024.2380837
Hernandez-Aguilar, C., Dominguez-Pacheco, A., Ivanov Tsonchev, R., Cruz-Orea, A., Ordonez-Miranda, J., Sanchez-Hernandez, G., & Perez-Reyes, M. C. J. (2024). Sustainable laser technology for the control of organisms and microorganisms in agri-food systems: a review. International Agrophysics, 38(1), 87–119. https://doi.org/10.31545/intagr/177513
Hong, C., Shi, M., Wang, S., Yang, Y., & Pu, Z. (2025). Novel analysis based on Raman spectroscopy in nutrition science. Analytical Methods, 17, 1977–1996. https://doi.org/10.1039/D4AY02129K
Jiang, L., Qiu, B., Liu, X., Huang, C., & Lin, K. (2020). DeepFood: Food image analysis and dietary assessment via deep model. IEEE Access, 8, 47477–47489. https://doi.org/10.1109/ACCESS.2020.2973625
Juárez, I. D., Naron, A., Blank, H., Polymenis, M., Threadgill, D. W., Bailey, R. L., …& Kurouski, D. (2025). Noninvasive optical sensing of aging and diet preferences using Raman spectroscopy. Analytical Chemistry, 97(1), 969–975. https://doi.org/10.1021/acs.analchem.4c05853
Karnachoriti, M., Chatzipetrou, M., Touloupakis, E., Kontos, A. G., & Zergioti, I. (2025). Raman spectroscopy as a tool for real-time nutrient monitoring in bioreactor cultivation of microalgae. Journal of Raman Spectroscopy, 56(9), 817–826. https://doi.org/10.1002/jrs.6841
Lee, C. K. W., Xu, Y., Yuan, Q., Chan, Y. H., Poon, W. Y., Zhong, H., …& Li, M. G. (2025). Advanced 3D food printing with simultaneous cooking and generative AI design. Advanced Materials, 37(13), 2408282. https://doi.org/10.1002/adma.202408282
Liu, D., Zuo, E., Wang, D., He, L., Dong, L., & Lu, X. (2025). Deep Learning in food image recognition: A comprehensive review. Applied Sciences, 15(14), 7626. https://doi.org/10.3390/app15147626
Maiman, T. H. (2017). The Laser Inventor: Memories of Theodore H. Maiman. Springer International Publisher.
McCarter, D. (1999). Infrared Food Warming Device. US Patent N. 6,294,769 B1
McHugh, T. (2018). Freeze-drying fundamentals. Food Technology, 72((1), 72–74.
Mignani, A. G., Ciaccheri, L., Cucci, C., Mencaglia, A. A., Cimato, A., Attilio, C., …& Dossena, A. (2008). EAT-by-LIGHT: Fiber-optic and micro-optic devices for food quality and safety assessment. IEEE Sensors Journal, 8(7), 1342–1354. https://doi.org/10.1109/JSEN.2008.926971
Mohamed, S., Tharwat, C., Khalifa, A., Elbagoury, Y., Refaat, H., Ahmed, S. F., …& Swillam, M. A. (2025). Photo-degradation of water and food pathogens using cheap handheld laser. In S. Kaierle & K. R. Kleine (Eds.), High-Power Laser Materials Processing: Applications, Diagnostics, and Systems XIV (Vol. 13356, pp. 106-109). https://doi.org/10.1117/12.3043613
Munzenmayer, P., Ulloa, J., Pinto, M., Ramirez, C., Valencia, P., Simpson, R., & Almonacid, S. (2020). Freeze-drying of blueberries: effects of Carbon Dioxide (CO2) laser perforation as skin pretreatment to improve mass transfer, primary drying time, and quality. Foods, 9(2). https://doi.org/10.3390/foods9020211
Narsaiah, K., Jha, S. N., Bhardwaj, R., Sharma, R., & Kumar, R. (2012). Optical biosensors for food quality and safety assurance - a review. Journal of Food Science and Technology, 49(4), 383–406. https://doi.org/10.1007/s13197-011-0437-6
Nasim, H., & Jamil, Y. (2014). Diode lasers: From laboratory to industry. Optics and Laser Technology, 56, 211–222. https://doi.org/10.1016/j.optlastec.2013.08.012
Payne, W. Z., & Kurouski, D. (2021). Raman spectroscopy enables phenotyping and assessment of nutrition values of plants: a review. Plant Methods, 17(1), 78. https://doi.org/10.1186/s13007-021-00781-y
Petersen, M., Yu, Z., & Lu, X. (2021). Application of Raman spectroscopic methods in food safety: A review. Biosensors, 11(6), 187. https://doi.org/10.3390/bios11060187
Pinto, M., Kusch, C., Belmonte, K., Valdivia, S., Valencia, P., Ramírez, C., & Almonacid, S. (2024). Application of CO2-laser micro-perforation technology to freeze-drying whole strawberry (Fragaria ananassa Duch.): Effect on primary drying time and fruit quality. Foods, 13(10). https://doi.org/10.3390/foods13101465
Pirhadi M, Shariatifar N, Pirhadi S, Khodaei SM, & Mazaheri Y. (2024) Developing infrared spectroscopy methods for identification of food fraud and authenticity - a review. Journal of Biochemicals and Phytomedicine, 3(1), 59-65. https://doi.org/10.34172/jbp.2024.12
Pouladzadeh, P., Shirmohammadi, S., & Al-Maghrabi, R. (2014). Measuring calorie and nutrition from food image. IEEE Transactions on Instrumentation and Measurement, 63(8), 1947–1956. https://doi.org/10.1109/TIM.2014.2303533
Righini, G. C., & Ferrari, M. (Eds). (2020a). Integrated Optics. Volume 1: Modeling, Materials Platforms and Fabrication Techniques. The IET.
Righini, G. C., & Ferrari, M. (Eds). (2020b). Integrated Optics. Volume 2: Characterization, Devices and Applications. The IET.
Rodriguez, A., & Kurouski, D. (2023). Raman spectroscopy enables non-invasive and quantitative assessment of macronutrients in baked foods. Journal of Raman Spectroscopy, 54(9), 899–904. https://doi.org/10.1002/jrs.6528
Smeesters, L., Venturini, F., Paulus, S., Mahlein, A.-K., Perpetuini, D., Cardone, D., …& Mignani, A. G. (2025). 2025 photonics for agrifood roadmap: towards a sustainable and healthier planet. Journal of Physics: Photonics, 7(3), 032501. https://doi.org/10.1088/2515-7647/adbea9
Sosa-Holwerda, A., Park, O.-H., Albracht-Schulte, K., Niraula, S., Thompson, L., & Oldewage-Theron, W. (2024). The role of artificial intelligence in nutrition research: A scoping review. Nutrients, 16(13). https://doi.org/10.3390/nu16132066
Spence, C., & Velasco, C. (2025). Digital Dining. Springer Cham.
Stankoski, S., Kiprijanovska, I., Gjoreski, M., Panchevski, F., Sazdov, B., Sofronievski, B., …& Gjoreski, H. (2024). Controlled and real-life investigation of optical tracking sensors in smart glasses for monitoring eating behavior using deep learning: Cross-sectional study. JMIR mHealth uHealth, 12, e59469. https://doi.org/10.2196/59469
Svelto, O. (2010). Principles of Laser (5th ed.). Springer.
Tan, J. Y., Ker, P. J., Lau, K. Y., Hannan, M. A., & Tang, S. G. H. (2019). Applications of photonics in agriculture sector: a review. Molecules, 24(10). https://doi.org/10.3390/molecules24102025
Teng, X., Zhang, M., & A. S.Mujumdar, A.S. (2021). Potential application of laser technology in food processing. Trends in Food Science and Technology, 118(A), 711–722. https://doi.org/10.1016/j.tifs.2021.10.031
Tinsley, G. M., Moore, M. L., Benavides, M. L., Dellinger, J. R., & Adamson, B. T. (2020). 3Dimensional optical scanning for body composition assessment: A 4 component model comparison of four commercially available scanners. Clinical Nutrition, 39(10), 3160–3167. https://doi.org/10.1016/j.clnu.2020.02.008
UNICEF (2025). 2025 Child Nutrition Report: Feeding Profit. How food environments are failing children. https://www.unicef.org/reports/feeding-profit. (Accessed on 6 October 2025)
Wang, H., Tian, H., Ju, R., Ma, L., Yang, L., Chen, J., & Liu, F. (2024). Nutritional composition analysis in food images: an innovative Swin Transformer approach. Frontiers in Nutrition, 11, 1454466. https://doi.org/10.3389/fnut.2024.1454466
Wells, J.C.K., Ruto, A., & Treleaven P. (2008). Whole-body three-dimensional photonic scanning: a new technique for obesity research and clinical practice. International Journal of Obesity, 32(2), 232–238. https://doi.org/10.1038/sj.ijo.0803727
Wen, B., Cui, S., Suo, X., & Supapvanich, S. (2023). Stress response of fresh-cut potatoes to laser irradiation before processing can prevent discoloration and maintain overall quality. Postharvest Biology and Technology, 197, 112213. https://doi.org/10.1016/j.postharvbio.2022.112213
Zhang, R., & Amft, O. (2018). Monitoring chewing and eating in free-living using smart eyeglasses. IEEE Journal of Biomedical and Health Informatics, 22(1), 23–32. https://doi.org/10.1109/JBHI.2017.2698523
Zidichouski, J. A., Mastaloudis, A., Poole, S. J., Reading, J. C., & Smidt, C. R. (2009). Clinical validation of a noninvasive, Raman spectroscopic method to assess carotenoid nutritional status in humans. Journal of the American College of Nutrition, 28(6), 687–693. https://doi.org/10.1080/07315724.2009.10719802
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Author
This work is licensed under a Creative Commons Attribution 4.0 International License.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
