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Optical Properties

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Abstract

Light is electromagnetic radiation that can be detected by the human eye. The visual appearance of food depends on optical phenomena such as absorption, reflection, scattering, gloss, and color. In this chapter, physical causes of refraction, diffraction, absorption, and transmission are explained in a concise and comprehensive way, and how these phenomena stem from the interaction between electromagnetic radiation and matter. They are illustrated by numerous examples. Causes for optical activity in food ingredients are explained and techniques such as polarimetry and ellipsometry are presented. Color is represented as a vector in different color systems and compared with visual sensation. At the end of the chapter, examples of applications are listed that can be used for further studies.

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References

  1. Fraden J (2016) Handbook of modern sensors physics, designs, and applications. https://doi.org/10.1007/978-3-319-19303-8

    Book  Google Scholar 

  2. Zawirska-Wojtasiak R (2006) Chirality and the nature of food authenticity of Aroma. Acta Sci Pol Technol Aliment 5:21

    CAS  Google Scholar 

  3. Maier NM, Franco P, Lindner W (2001) Separation of enantiomers: needs, challenges, perspectives. J Chromatogr A 906(1):3. https://doi.org/10.1016/S0021-9673(00)00532-X

    Article  CAS  PubMed  Google Scholar 

  4. Gibbs PR, Uehara CS, Nguyen PT, Willson RC (2003) Imaging polarimetry for high throughput chiral screening. Biotechnol Prog 19(4):1329. https://doi.org/10.1021/bp025729l

    Article  CAS  PubMed  Google Scholar 

  5. Mosandl A, Hener U, Fuchs S (2000) Natürliche Duft- und Aromastoffe — Echtheitsbewertung mittels enantioselektiver Kapillar-GC und/oder Isotopenverhältnis-massenspektrometrie. In: Günzler H (ed) Analytiker-Taschenbuch. Springer, Heidelberg. https://doi.org/10.1007/978-3-642-57180-0_2

    Chapter  Google Scholar 

  6. Fanali C, D’Orazio G, Gentili A, Fanali S (2019) Analysis of enantiomers in products of food interest. Molecules 24(6). https://doi.org/10.3390/molecules24061119

  7. D’Orazio G, Fanali C, Asensio-Ramos M, Fanali S (2017) Chiral separations in food analysis. TrAC Trends Anal Chem 96:151. https://doi.org/10.1016/j.trac.2017.05.013

    Article  CAS  Google Scholar 

  8. Meschede D (2006) Gerthsen Physik. Springer, Berlin. https://doi.org/10.1007/978-3-662-45977-5

    Book  Google Scholar 

  9. Sutrisno YA (2017) Noninvasive and painless urine glucose detection by using computer-based polarimeter. Mater Sci Eng 202:012030. https://doi.org/10.1088/1757-899X/202/1/012030

    Article  Google Scholar 

  10. Carroll A, Dick J, Selph L, Murphy M (2017) Using polarimetry to examine the kinetics of enzymatic reactions with the Parkinson’s disease drug L-DOPA. In: Research & Creative Activity Symposium, Montgomery, AL. Alabama State University. https://doi.org/10.1016/j.ijbiomac.2013.01.031

  11. Honig W, Moshudis E, Oette K (1981) Polarimetric determination of alpha-amylase activity (author’s transl). J Clin Chem Clin Biochem / Zeitschrift fur klinische Chemie und klinische Biochemie 19(10):1057

    CAS  PubMed  Google Scholar 

  12. Baykusheva D, Zindel D, Svoboda V, Bommeli E, Ochsner M, Tehlar A, Wörner HJ (2019) Real-time probing of chirality during a chemical reaction. Proc Natl Acad Sci 116(48):23923. https://doi.org/10.1073/pnas.1907189116

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Alexander M, Dalgleish DG (2006) Dynamic light scattering techniques and their applications in food science. Food Biophys 1(1):2. https://doi.org/10.1007/s11483-005-9000-1

    Article  Google Scholar 

  14. ISO 13320 (2020) Partikelgrößenanalyse - Partikelmessung durch Laserlichtbeugung. Beuth, Berlin. https://doi.org/10.31030/2333155

  15. Ruscitti O, Franke R, Hahn H, Babick F, Richter T, Stintz M (2008) Zum Einsatz der Partikelmesstechnik in der Prozessintensivierung. Chem Ing Techn 80(1-2):191. https://doi.org/10.1002/cite.200700168

    Article  CAS  Google Scholar 

  16. Xu R (2015) Light scattering: a review of particle characterization applications. Particuology 18:11. https://doi.org/10.1016/j.partic.2014.05.002

    Article  Google Scholar 

  17. Mollazade K, Omid M, Tab FA, Mohtasebi SS (2012) Principles and applications of light backscattering imaging in quality evaluation of agro-food products: a review. Food Bioprocess Technol 5(5):1465. https://doi.org/10.1007/s11947-012-0821-x

    Article  Google Scholar 

  18. Udayakumar N (2014) Visible light imaging. In: Manickavasagan A, Jayasuriya H (eds) Imaging with electromagnetic spectrum: applications in food and agriculture. Springer, Berlin, pp 67–86. https://doi.org/10.1007/978-3-642-54888-8_5

    Chapter  Google Scholar 

  19. DIN EN ISO/CIE 11664 (2020) Farbmetrik - Teil 1: CIE farbmetrische Normalbeobachter. Beuth, Berlin. https://doi.org/10.31030/3091836

  20. DIN EN ISO/CIE 11664 (2020) Farbmetrik - Teil 3: CIE-Farbwerte. Beuth, Berlin. https://doi.org/10.31030/3092071

  21. Kohlrausch F (1996) Praktische Physik Bd.1. Teubner, Stuttgart. https://doi.org/10.1007/978-3-322-87205-0

    Book  Google Scholar 

  22. DIN 5033 (2017) Farbmessung - Teil 1: Grundbegriffe der Farbmetrik. Beuth, Berlin. https://doi.org/10.31030/2705354

    Book  Google Scholar 

  23. Parkin A (2016) Colorimetry. In: Parkin A (ed) Digital imaging primer. Springer, Berlin, pp 269–281. https://doi.org/10.1007/978-3-540-85619-1_16

    Chapter  Google Scholar 

  24. Lübbe E (2013) Farbempfindung, Farbbeschreibung und Farbmessung. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-8348-2228-4

    Book  Google Scholar 

  25. ISO/CIE 11664-6 (2014) Farbmetrik - Teil 6: CIEDE2000 Formel für die Farbdifferenz. Beuth, Berlin

    Google Scholar 

  26. Kang SP (2011) Color in food evaluation. In: Gliński J, Horabik J, Lipiec J (eds) Encyclopedia of agrophysics. Springer, Dordrecht, pp 138–141. https://doi.org/10.1007/978-90-481-3585-1_236

    Chapter  Google Scholar 

  27. Culver CA, Wrolstad RE (2008) Color quality of fresh and processed foods. American Chemical Society; Distributed by Oxford University Press, Washington, DC. https://doi.org/10.1021/bk-2008-0983

    Book  Google Scholar 

  28. Wu D, Sun D-W (2013) Colour measurements by computer vision for food quality control – a review. Trends Food Sci Technol 29(1):5. https://doi.org/10.1016/j.tifs.2012.08.004

    Article  CAS  Google Scholar 

  29. Mohan S, Kato E, Drennen JK, Anderson CA (2019) Refractive index measurement of pharmaceutical solids: a review of measurement methods and pharmaceutical applications. J Pharm Sci 108(11):3478. https://doi.org/10.1016/j.xphs.2019.06.029

    Article  CAS  PubMed  Google Scholar 

  30. Jiménez-Márquez F, Vázquez J, Úbeda J, Sánchez-Rojas JL (2016) Temperature dependence of grape must refractive index and its application to winemaking monitoring. Sens Actuators B Chem 225:121. https://doi.org/10.1016/j.snb.2015.10.064

    Article  CAS  Google Scholar 

  31. Davis JP, Sweigart DS, Price KM, Dean LL, Sanders TH (2013) Refractive index and density measurements of peanut oil for determining oleic and linoleic acid contents. J Am Oil Chemists Soc 90(2):199. https://doi.org/10.1007/s11746-012-2153-4

    Article  CAS  Google Scholar 

  32. ISO 1743 (1982) Glucose syrup - determination of dry matter content- refractive index method. Vernier, Switzerland

    Google Scholar 

  33. Shin HJ, Choi SW, Ok G (2018) Qualitative identification of food materials by complex refractive index mapping in the terahertz range. Food Chem 245:282. https://doi.org/10.1016/j.foodchem.2017.10.056. Epub 2017 Oct 13

    Article  CAS  PubMed  Google Scholar 

  34. Mathew S, Raman M, Kalarikkathara PM, Rajan DP (2019) Techniques used in fish and fishery products analysis. In: Fish and fishery products analysis. Springer, Singapore. https://doi.org/10.1007/978-981-32-9574-2_5

    Chapter  Google Scholar 

  35. Tengesdal ØA (2012) Measurement of seawater refractive index and salinity by means of optical refraction. University, Bergen

    Google Scholar 

  36. Bagheri M, Kiani F, Koohyar F, Khang NT, Zabihi F (2020) Measurement of refractive index and viscosity for aqueous solution of sodium acetate, sodium carbonate, trisodium citrate, (glycerol + sodium acetate), (glycerol + sodium carbonate), and (glycerol + trisodium citrate) at T = 293.15 to 303.15 K and atmospheric pressure. J Mol Liq 309:113109. https://doi.org/10.1016/j.molliq.2020.113109

    Article  CAS  Google Scholar 

  37. Shehadeh A, Evangelou A, Kechagia D, Tataridis P, Chatzilazarou A, Shehadeh F (2020) Effect of ethanol, glycerol, glucose/fructose and tartaric acid on the refractive index of model aqueous solutions and wine samples. Food Chem 329:127085. https://doi.org/10.1016/j.foodchem.2020.127085

    Article  CAS  PubMed  Google Scholar 

  38. Robinson S, Dhanlaksmi N (2016) Photonic crystal based biosensor for the detection of glucose concentration in urine. Photonic Sens 7. https://doi.org/10.1007/s13320-016-0347-3

  39. Wu Y, Liu B, Wang J, Wu J, Mao Y, Ren J, Zhao L, Sun T, Nan T, Han Y, Liu X (2021) A novel temperature insensitive refractive index sensor based on dual photonic crystal fiber. Optik 226:165495. https://doi.org/10.1016/j.ijleo.2020.165495

    Article  CAS  Google Scholar 

  40. Li J (2020) A review: Development of novel fiber-optic platforms for bulk and surface refractive index sensing applications. Sens Actuators Rep 2(1):100018. https://doi.org/10.1016/j.snr.2020.100018

    Article  Google Scholar 

  41. Li K, Wang S, Wang L, Yu H, Jing N, Xue R, Wang Z (2017) Fast and sensitive ellipsometry-based biosensing. Sensors (Basel, Switzerland) 18(1):15. https://doi.org/10.3390/s18010015

    Article  CAS  PubMed  Google Scholar 

  42. Torricelli A, Spinelli L, Contini D, Vanoli M, Rizzolo A, Eccher Zerbini P (2008) Time-resolved reflectance spectroscopy for non-destructive assessment of food quality. Sens Instrumen Food Qual 2(2):82. https://doi.org/10.1007/s11694-008-9036-2

    Article  Google Scholar 

  43. Kim M, Lee K, Chao K, Lefcourt A, Jun W, Chan D (2008) Multispectral line-scan imaging system for simultaneous fluorescence and reflectance measurements of apples: multitask apple inspection system. Sens Instrumen Food Qual 2(2):123. https://doi.org/10.1007/s11694-008-9045-1

    Article  Google Scholar 

  44. Mizrach A, Lu RF, Rubino M (2009) Gloss evaluation of curved-surface fruits and vegetables. Food Bioprocess Technol 2(3):300. https://doi.org/10.1007/s11947-008-0083-9

    Article  Google Scholar 

  45. Pawluczyk R (1990) Modified Brewster angle technique for the measurement of the refractive index of a DCG layer. Appl Opt 29:589. https://doi.org/10.1364/AO.29.000589

    Article  CAS  PubMed  Google Scholar 

  46. Daear W, Mahadeo M, Prenner EJ (2017) Applications of Brewster angle microscopy from biological materials to biological systems. Biochim Biophys Acta Biomembr 1859(10):1749. https://doi.org/10.1016/j.bbamem.2017.06.016

    Article  CAS  PubMed  Google Scholar 

  47. Fernandes GM, Silva WR, Barreto DN, Lamarca RS, Lima Gomes PCF, Petruci JFS, Batista AD (2020) Novel approaches for colorimetric measurements in analytical chemistry – a review. Anal Chim Acta 1135:187. https://doi.org/10.1016/j.aca.2020.07.030

    Article  CAS  PubMed  Google Scholar 

  48. Lee Black D, McQuay MQ, Bonin MP (1996) Laser-based techniques for particle-size measurement: a review of sizing methods and their industrial applications. Prog Energy Combust Sci 22(3):267. https://doi.org/10.1016/S0360-1285(96)00008-1

    Article  Google Scholar 

  49. Ferro V, Mirabile S (2009) Comparing particle size distribution analysis by sedimentation and laser diffraction method. J Agric Eng. https://doi.org/10.4081/jae.2009.2.35

  50. ISO 22412 (2017) Particle Size Analysis – Dynamic Light Scattering (DLS). Beuth, Berlin

    Google Scholar 

  51. Barnes M, Dudbridge M, Duckett T (2012) Polarised light stress analysis and laser scatter imaging for non-contact inspection of heat seals in food trays. J Food Eng 112(3):183. https://doi.org/10.1016/j.jfoodeng.2012.02.040

    Article  Google Scholar 

  52. Rao P, Yu Z, Han H, Xu Y, Ke L (2019) Dynamic light scattering for food quality evaluation. In: Zhong J, Wang X (eds) Evaluation technologies for food quality. Woodhead Publishing, pp 535–557. https://doi.org/10.1016/B978-0-12-814217-2.00020-2

    Chapter  Google Scholar 

  53. Zhang B, Gu B, Tian G, Zhou J, Huang J, Xiong Y (2018) Challenges and solutions of optical-based nondestructive quality inspection for robotic fruit and vegetable grading systems: a technical review. Trends Food Sci Technol 81:213. https://doi.org/10.1016/j.tifs.2018.09.018

    Article  CAS  Google Scholar 

  54. Li S, Luo H, Hu M, Zhang M, Feng J, Liu Y, Dong Q, Liu B (2019) Optical non-destructive techniques for small berry fruits: a review. Artif Intell Agric 2:85. https://doi.org/10.1016/j.aiia.2019.07.002

    Article  Google Scholar 

  55. Xu C (2019) Electronic eye for food sensory evaluation. In: Zhong J, Wang X (eds) Evaluation technologies for food quality. Woodhead Publishing, pp 37–59. https://doi.org/10.1016/B978-0-12-814217-2.00004-4

    Chapter  Google Scholar 

  56. Koren D, Hegyesné Vecseri B, Kun-Farkas G, Urbin Á, Nyitrai Á, Sipos L (2020) How to objectively determine the color of beer? J Food Sci Technol 57(3):1183. https://doi.org/10.1007/s13197-020-04237-4

    Article  PubMed  PubMed Central  Google Scholar 

  57. Fengxia S, Yuwen C, Zhanming Z, Yifeng Y (2004) Determination of beer color using image analysis. J Am Soc Brew Chem 62(4):163. https://doi.org/10.1094/ASBCJ-62-0163

    Article  Google Scholar 

  58. Mendoza F, Dejmek P, Aguilera JM (2006) Calibrated color measurements of agricultural foods using image analysis. Postharvest Biol Technol 41(3):285. https://doi.org/10.1016/j.postharvbio.2006.04.004

    Article  Google Scholar 

  59. Camelo-Mendez GA, Vanegas-Espinoza PE, Escudero-Gilete ML, Heredia FJ, Paredes-Lopez O, Del Villar-Martinez AA (2018) Colorimetric analysis of hibiscus beverages and their potential antioxidant properties. Plant Food Hum Nutr 73(3):247

    Article  CAS  Google Scholar 

  60. Nannyonga S, Bakalis S, Andrews J, Mugampoza E, Gkatzionis K (2016) Mathematical modelling of color, texture kinetics and sensory attributes characterisation of ripening bananas for waste critical point determination. J Food Eng 190:205. https://doi.org/10.1016/j.jfoodeng.2016.06.006

    Article  Google Scholar 

  61. Pearson T, Brabec D, Haley S (2008) Color image based sorter for separating red and white wheat. Sens Instrumen Food Qual 2(4):280

    Article  Google Scholar 

  62. Yam KL, Papadakis SE (2004) A simple digital imaging method for measuring and analyzing color of food surfaces. J Food Eng 61(1):137. https://doi.org/10.1016/s0260-8774(03)00195-x

    Article  Google Scholar 

  63. Sant’Anna V, Gurak PD, Ferreira Marczak LD, Tessaro IC (2013) Tracking bioactive compounds with colour changes in foods – a review. Dyes Pigments 98(3):601. https://doi.org/10.1016/j.dyepig.2013.04.011

    Article  CAS  Google Scholar 

  64. Ijaz M, Li X, Zhang D, Hussain Z, Ren C, Bai Y, Zheng X (2020) Association between meat color of DFD beef and other quality attributes. Meat Sci 161:107954. https://doi.org/10.1016/j.meatsci.2019.107954

    Article  CAS  PubMed  Google Scholar 

  65. Faustman C, Suman SP (2017) The eating quality of meat: I—Color. In: Toldra F (ed) Lawrie’s meat science, 8th edn. Woodhead Publishing, pp 329–356. https://doi.org/10.1016/B978-0-08-100694-8.00011-X

    Chapter  Google Scholar 

  66. Warner R (2014) Measurement of meat quality | Measurements of water-holding capacity and color: objective and subjective. In: Dikeman M, Devine C (eds) Encyclopedia of meat sciences. Academic Press, Oxford, pp 164–171. https://doi.org/10.1016/B978-0-12-384731-7.00210-5

    Chapter  Google Scholar 

  67. Shenoy P, Innings F, Lilliebjelke T, Jonsson C, Fitzpatrick J, Ahrné L (2014) Investigation of the application of digital colour imaging to assess the mixture quality of binary food powder mixes. J Food Eng 128:140. https://doi.org/10.1016/j.jfoodeng.2013.12.013

    Article  Google Scholar 

  68. Nkhata SG (2020) Total color change (ΔE∗) is a poor estimator of total carotenoids lost during post-harvest storage of biofortified maize grains. Heliyon 6(10):e05173. https://doi.org/10.1016/j.heliyon.2020.e05173

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Hyun J-E, Lee S-Y (2020) Blue light-emitting diodes as eco-friendly non-thermal technology in food preservation. Trends Food Sci Technol 105:284. https://doi.org/10.1016/j.tifs.2020.09.008

    Article  CAS  Google Scholar 

  70. Gupta SD (2017) Light emitting diodes for agriculture. Springer, Singapore. https://doi.org/10.1007/978-981-10-5807-3

    Book  Google Scholar 

  71. Rousseau D (2016) Microstructural imaging of chocolate confectionery. In: Sozer N (ed) Imaging technologies and data processing for food engineers. Springer International, Cham, pp 311–333. https://doi.org/10.1007/978-3-319-24735-9_10

    Chapter  Google Scholar 

  72. Ercili-Cura D (2016) Imaging of fermented dairy products. In: Sozer N (ed) Imaging technologies and data processing for food engineers. Springer International, Cham, pp 99–128. https://doi.org/10.1007/978-3-319-24735-9_4

    Chapter  Google Scholar 

  73. Lorén N, Langton M, Hermansson AM (2007) Confocal fluorescence microscopy (CLSM) for food structure characterisation. In: McClements DJ (ed) Understanding and controlling the microstructure of complex foods. Woodhead Publishing, pp 232–260. https://doi.org/10.1533/9781845693671.2.232

    Chapter  Google Scholar 

  74. Liu YW, Pu HB, Sun DW (2017) Hyperspectral imaging technique for evaluating food quality and safety during various processes: a review of recent applications. Trends Food Sci Technol 69:25. https://doi.org/10.1016/j.tifs.2017.08.013

    Article  CAS  Google Scholar 

  75. Baiano A (2017) Applications of hyperspectral imaging for quality assessment of liquid based and semi-liquid food products: a review. J Food Eng 214:10. https://doi.org/10.1016/j.jfoodeng.2017.06.012

    Article  CAS  Google Scholar 

  76. Park B, Lu R (2015) Hyperspectral imaging technology in food and agriculture. https://doi.org/10.1007/978-1-4939-2836-1

  77. Feng CH, Makino Y, Oshita S, Martin JFG (2018) Hyperspectral imaging and multispectral imaging as the novel techniques for detecting defects in raw and processed meat products: current state-of-the-art research advances. Food Control 84:165. https://doi.org/10.1016/j.foodcont.2017.07.013

    Article  Google Scholar 

  78. Antequera T, Caballero D, Grassi S, Uttaro B, Perez-Palacios T (2021) Evaluation of fresh meat quality by Hyperspectral Imaging (HSI), Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI): a review. Meat Sci 172:108340. https://doi.org/10.1016/j.meatsci.2020.108340

    Article  CAS  PubMed  Google Scholar 

  79. Ma T, Li X, Inagaki T, Yang H, Tsuchikawa S (2018) Noncontact evaluation of soluble solids content in apples by near-infrared hyperspectral imaging. J Food Eng. https://doi.org/10.1016/j.jfoodeng.2017.12.028

  80. Nansen C, Singh K, Mian A, Allison BJ, Simmons CW (2016) Using hyperspectral imaging to characterize consistency of coffee brands and their respective roasting classes. J Food Eng 190:34. https://doi.org/10.1016/j.jfoodeng.2016.06.010

    Article  Google Scholar 

  81. Bernewitz R, Guthausen G, Schuchmann HP (2016) Imaging of double emulsions. In: Sozer N (ed) Imaging technologies and data processing for food engineers. Springer International, Cham, pp 69–98. https://doi.org/10.1007/978-3-319-24735-9_3

    Chapter  Google Scholar 

  82. Morris VJ (2007) Atomic force microscopy (AFM) techniques for characterising food structure. In: McClements DJ (ed) Understanding and controlling the microstructure of complex foods. Woodhead Publishing, pp 209–231. https://doi.org/10.1533/9781845693671.2.209

    Chapter  Google Scholar 

  83. Gunning AP, Morris VJ (2018) Getting the feel of food structure with atomic force microscopy. Food Hydrocoll 78:62. https://doi.org/10.1016/j.foodhyd.2017.05.017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Middendorf D, Bindrich U, Mischnick P, Juadjur A, Franke K, Heinz V (2016) Atomic Force Microscopy study on the effect of different lecithins in cocoa-butter based suspensions. Colloids Surf A Physicochem Eng Aspects 499:60. https://doi.org/10.1016/j.colsurfa.2016.03.057

    Article  CAS  Google Scholar 

  85. Gunning PA (2013) Light microscopy: principles and applications to food microstructures. In: Morris VJ, Groves K (eds) Food microstructures. Woodhead Publishing, pp 62–95. https://doi.org/10.1533/9780857098894.1.62

    Chapter  Google Scholar 

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  1. Food Engineering, Hochschule Osnabrück, University of Applied Sciences, Osnabrück, Germany

    Ludger O. Figura

  2. University of Florida, Gainesville, FL, USA

    Arthur A. Teixeira

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Figura, L.O., Teixeira, A.A. (2023). Optical Properties. In: Food Physics. Springer, Cham. https://doi.org/10.1007/978-3-031-27398-8_12

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