746
Views
5
CrossRef citations to date
0
Altmetric
Reviews

Recent developments in vibrational spectral analyses for dynamically assessing and monitoring food dehydration processes

, , &

References

  • Achata, E. M., C. Esquerre, K. S. Ojha, B. K. Tiwari, and C. P. O'Donnell. 2021. Development of NIR-HSI and chemometrics process analytical technology for drying of beef jerky. Innovative Food Science & Emerging Technologies 69:102611. doi: 10.1016/j.ifset.2021.102611.
  • Afsah-Hejri, L., P. Hajeb, P. Ara, and R. J. Ehsani. 2019. A comprehensive review on food applications of Terahertz spectroscopy and imaging. Comprehensive Reviews in Food Science and Food Safety 18 (5):1563–621. doi: 10.1111/1541-4337.12490.
  • Aheto, J. H., X. Y. Huang, X. Y. Tian, R. Q. Lv, C. X. Dai, E. Bonah, and X. H. Chang. 2020. Evaluation of lipid oxidation and volatile compounds of traditional dry-cured pork belly: The hyperspectral imaging and multi-gas-sensory approaches. Journal of Food Process Engineering 43 (1):e13092. doi: 10.1111/jfpe.13092.
  • Amjad, W., S. O. J. Crichton, A. Munir, O. Hensel, and B. Sturm. 2018. Hyperspectral imaging for the determination of potato slice moisture content and chromaticity during the convective hot air drying process. Biosystems Engineering 166:170–83. doi: 10.1016/j.biosystemseng.2017.12.001.
  • Bhatta, S., T. Stevanovic Janezic, and C. Ratti. 2020. Freeze-drying of plant-based foods. Foods 9 (1):87. doi: 10.3390/foods9010087.
  • Borovkova, M., M. Khodzitsky, P. Demchenko, O. Cherkasova, A. Popov, and I. Meglinski. 2018. Terahertz time-domain spectroscopy for non-invasive assessment of water content in biological samples. Biomedical Optics Express 9 (5):2266–76. doi: 10.1364/BOE.9.002266.
  • Braeuer, A. S., J. J. Schuster, M. T. Gebrekidan, L. Bahr, F. Michelino, A. Zambon, and S. Spilimbergo. 2017. In situ Raman analysis of CO2-assisted drying of fruit-slices. Foods 6 (5):37. doi: 10.3390/foods6050037.
  • Carvalho, L. C., M. L. Leite, C. L. M. Morais, K. M. G. Lima, and G. H. A. Teixeira. 2019. Non-destructive assessment of the oxidative stability of intact macadamia nuts during the drying process by near-infrared spectroscopy. LWT-Food Science and Technology 103:101–7. doi: 10.1016/j.lwt.2018.12.056.
  • Carvalho, D. G., J. A. Sebben, N. F. de Moura, J. O. Trierweiler, and J. D. S. Espindola. 2019. Raman spectroscopy for monitoring carotenoids in processed Bunchosia glandulifera pulps. Food Chemistry 294:565–71. doi: 10.1016/j.foodchem.2019.04.120.
  • Chakravartula, S. S. N., C. Cevoli, F. Balestra, A. Fabbri, and M. Dalla Rosa. 2019. Evaluation of drying of edible coating on bread using NIR spectroscopy. Journal of Food Engineering 240:29–37. doi: 10.1016/j.jfoodeng.2018.07.009.
  • Chandrasekaran, S., S. Ramanathan, and T. Basak. 2013. Microwave food processing—A review. Food Research International 52 (1):243–61. doi: 10.1016/j.foodres.2013.02.033.
  • Cheng, W., D.-W. Sun, H. Pu, and Y. Liu. 2016a. Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat. LWT- Food Science and Technology 72:322–9. doi:10.1016/j.lwt.2016.05.003.
  • Cheng, W., D.-W. Sun, and J.-H. Cheng. 2016b. Pork biogenic amine index (BAI) determination based on chemometric analysis of hyperspectral imaging data. LWT 73:13–9. doi:10.1016/j.lwt.2016.05.031.
  • Cheng, W., D.-W. Sun, H. Pu, and Q. Wei. 2017. Chemical spoilage extent traceability of two kinds of processed pork meats using one multispectral system developed by hyperspectral imaging combined with effective variable selection methods. Food Chemistry 221:1989–96. doi:10.1016/j.foodchem.2016.11.093.
  • Cheng, W., D.-W. Sun, H. Pu, and Q. Wei. 2018. Heterospectral two-dimensional correlation analysis with near-infrared hyperspectral imaging for monitoring oxidative damage of pork myofibrils during frozen storage. Food Chemistry 248:119–27. doi:10.1016/j.foodchem.2017.12.050.
  • Cheng, W., K. M. Sørensen, R. J. Mongi, B. K. Ndabikunze, B. E. Chove, D.-W. Sun, and S. B. Engelsen. 2019. A comparative study of mango solar drying methods by visible and near-infrared spectroscopy coupled with ANOVA-simultaneous component analysis (ASCA). LWT-Food Science and Technology 112:108214. doi: 10.1016/j.lwt.2019.05.112.
  • Cho, J. S., J. Y. Choi, and K. D. Moon. 2020. Hyperspectral imaging technology for monitoring of moisture contents of dried persimmons during drying process. Food Science and Biotechnology 29 (10):1407–12. doi: 10.1007/s10068-020-00791-x.
  • Chranioti, C., S. Chanioti, and C. Tzia. 2016. Comparison of spray, freeze and oven drying as a means of reducing bitter aftertaste of steviol glycosides (derived from Stevia rebaudiana Bertoni plant)-Evaluation of the final products. Food Chemistry 190:1151–8. doi: 10.1016/j.foodchem.2015.06.083.
  • Collell, C., P. Gou, J. Arnau, and J. Comaposada. 2011. Non-destructive estimation of moisture, water activity and NaCl at ham surface during resting and drying using NIR spectroscopy. Food Chemistry 129 (2):601–7. doi: 10.1016/j.foodchem.2011.04.073.
  • Collell, C., P. Gou, J. Arnau, I. Munoz, and J. Comaposada. 2012. NIR technology for on-line determination of superficial a(w) and moisture content during the drying process of fermented sausages. Food Chemistry 135 (3):1750–5. doi: 10.1016/j.foodchem.2012.06.036.
  • Collell, C., P. Gou, P. Picouet, J. Arnau, and J. Comaposada. 2010. Feasibility of near-infrared spectroscopy to predict aw and moisture and NaCl contents of fermented pork sausages. Meat Science 85 (2):325–30. doi: 10.1016/j.meatsci.2010.01.022.
  • Craig, A. P., A. S. Franca, and J. Irudayaraj. 2013. Surface-enhanced Raman spectroscopy applied to food safety. Annual Review of Food Science and Technology 4:369–80. doi: 10.1146/annurev-food-022811-101227.
  • Craig, A. P., A. S. Franca, and J. Irudayaraj. 2015. Vibrational spectroscopy for food quality and safety screening. In High throughput screening for food safety assessment, ed. A. K. Bhunia, M. S. Kim, and C. R. Taitt, , 165–94. Cambridge, UK: Woodhead Publishing.
  • Crichton, S., B. Sturm, and A. Hurlbert. 2015. Moisture content measurement in dried apple produce through visible wavelength hyperspectral imaging. In 2015 ASABE annual international meeting (p. 1). American Society of Agricultural and Biological Engineers.
  • Crichton, S., L. Shrestha, A. Hurlbert, and B. Sturm. 2018. Use of hyperspectral imaging for the prediction of moisture content and chromaticity of raw and pretreated apple slices during convection drying. Drying Technology 36 (7):804–16. doi: 10.1080/07373937.2017.1356847.
  • Cui, Z.-W., S.-Y. Xu, D.-W. Sun, and W. Chen. 2005. Temperature Changes during Microwave-Vacuum Drying of Sliced Carrots. Drying Technology 23 (5):1057–74. doi:10.1081/DRT-200059136.
  • Cui, Z.-W., S.-Y. Xu, and D.-W. Sun. 2004a. Microwave–vacuum drying kinetics of carrot slices. Journal of Food Engineering 65 (2):157–64. doi:10.1016/j.jfoodeng.2004.01.008.
  • Cui, Z.-W., S.-Y. Xu, and D.-W. Sun. 2004b. Effect of Microwave-Vacuum Drying on the Carotenoids Retention of Carrot Slices and Chlorophyll Retention of Chinese Chive Leaves. Drying Technology 22 (3):563–75. doi:10.1081/DRT-120030001.
  • Cui, Z.-W., S.-Y. Xu, and D.-W. Sun. 2003. Dehydration of Garlic Slices by Combined Microwave-Vacuum and Air Drying. Drying Technology 21 (7):1173–84. doi:10.1081/DRT-120023174.
  • Czaja, T., E. Kuzawińska, A. Sobota, and R. Szostak. 2018. Determining moisture content in pasta by vibrational spectroscopy. Talanta 178:294–8. doi: 10.1016/j.talanta.2017.09.050.
  • Dai, Q., J.-H. Cheng, D.-W. Sun, Z. Zhu, and H. Pu. 2016. Prediction of total volatile basic nitrogen contents using wavelet features from visible/near-infrared hyperspectral images of prawn (Metapenaeus ensis). Food Chemistry 197:257–65. doi:10.1016/j.foodchem.2015.10.073.
  • Delwiche, S. R. 2015. Basics of spectroscopic analysis. In Hyperspectral imaging technology in food and agriculture , ed. B. Park, & R. Lu, 9–56. New York, USA: Springer.
  • Dénes, L., V. Zsom-Muha, L. Baranyai, and J. Felföldi. 2012. Modelling of apple slice moisture content by optical methods. Acta Alimentaria 41 (Supplement 1):39–51. doi: 10.1556/AAlim.41.2012.Suppl.4.
  • Devahastin, S., and C. Niamnuy. 2010. Invited review: Modelling quality changes of fruits and vegetables during drying: A review. International Journal of Food Science & Technology 45 (9):1755–67. doi: 10.1111/j.1365-2621.2010.02352.x.
  • Dufour, É. 2009. Principles of infrared spectroscopy. In Infrared spectroscopy for food quality analysis and control, ed. D.-W. Sun, 3–25. San Diego, USA: Academic Press.
  • Elavarasan, K., B. A. Shamasundar, F. Badii, and N. Howell. 2016. Angiotensin I-converting enzyme (ACE) inhibitory activity and structural properties of oven- and freeze-dried protein hydrolysate from fresh water fish (Cirrhinus mrigala). Food Chemistry 206:210–6. doi: 10.1016/j.foodchem.2016.03.047.
  • Fan, F.,. P. Xiang, and L. Zhao. 2021. Vibrational spectra analysis of amorphous lactose in structural transformation: Water/temperature plasticization, crystal formation, and molecular mobility. Food Chemistry 341 (Pt 1):128215. doi: 10.1016/j.foodchem.2020.128215.
  • Fellows, P. J. 2009. Dehydration. In Food processing technology, ed. P. J. Fellows,. 3rd ed., 481–524. Cambridge, UK: Woodhead Publishing.
  • Feng, Y. Z., and D.-W. Sun. 2012. Application of hyperspectral imaging in food safety inspection and control: A review. Critical Reviews in Food Science and Nutrition 52 (11):1039–58. doi: 10.1080/10408398.2011.651542.
  • Ferreira, D. S., O. F. Galão, J. A. L. Pallone, and R. J. Poppi. 2014. Comparison and application of near-infrared (NIR) and mid-infrared (MIR) spectroscopy for determination of quality parameters in soybean samples. Food Control. 35 (1):227–32. doi: 10.1016/j.foodcont.2013.07.010.
  • Galvis-Sánchez, A. C., I. C. Santos, R. B. R. Mesquita, J. A. Lopes, A. O. S. S. Rangel, and I. Delgadillo. 2013. Application of mid- and near-infrared spectroscopy for the control and chemical evaluation of brine solutions and traditional sea salts. Food Analytical Methods 6 (2):470–80. doi: 10.1007/s12161-012-9458-7.
  • Gonzalez-Mohino, A., T. Perez-Palacios, T. Antequera, J. Ruiz-Carrascal, L. S. Olegario, and S. Grassi. 2020. Monitoring the processing of dry fermented sausages with a portable NIRS device. Foods 9 (9):1294. doi: 10.3390/foods9091294.
  • Gowen, A. A., F. Marini, C. Esquerre, C. O’Donnell, G. Downey, and J. Burger. 2011. Time series hyperspectral chemical imaging data: Challenges, solutions and applications. Analytica Chimica Acta 705 (1-2):272–82. doi: 10.1016/j.aca.2011.06.031.
  • Guo, Q., D.-W. Sun, J. H. Cheng, and Z. Han. 2017. Microwave processing techniques and their recent applications in the food industry. Trends in Food Science & Technology 67:236–47. doi: 10.1016/j.tifs.2017.07.007.
  • Huang, H., H. Yu, H. Xu, and Y. Ying. 2008. Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: A review. Journal of Food Engineering 87 (3):303–13. doi: 10.1016/j.jfoodeng.2007.12.022.
  • Huang, H., Y. Shen, Y. Guo, P. Yang, H. Wang, S. Zhan, H. Liu, H. Song, and Y. He. 2017. Characterization of moisture content in dehydrated scallops using spectral images. Journal of Food Engineering 205:47–55. doi: 10.1016/j.jfoodeng.2017.02.018.
  • Huang, M., Q. Wang, M. Zhang, and Q. Zhu. 2014. Prediction of color and moisture content for vegetable soybean during drying using hyperspectral imaging technology. Journal of Food Engineering 128:24–30. doi: 10.1016/j.jfoodeng.2013.12.008.
  • Huang, M., W. Zhao, Q. Wang, M. Zhang, and Q. Zhu. 2015. Prediction of moisture content uniformity using hyperspectral imaging technology during the drying of maize kernel. International Agrophysics 29 (1):39–46. doi: 10.1515/intag-2015-0012.
  • Ishikawa, D., G. Ueno, and T. Fujii. 2017. Estimation method of moisture content at the meat surface during drying process by NIR pectroscopy and its application for monitoring of water activity. Japan Journal of Food Engineering 18 (3):135–43. doi: 10.11301/jsfe.17493.
  • Kamruzzaman, M., Y. Makino, and S. Oshita. 2016. Parsimonious model development for real-time monitoring of moisture in red meat using hyperspectral imaging. Food Chemistry 196:1084–91. doi: 10.1016/j.foodchem.2015.10.051.
  • Kauppinen, A., M. Toiviainen, O. Korhonen, J. Aaltonen, K. Jarvinen, J. Paaso, M. Juuti, and J. Ketolainen. 2013. In-line multipoint near-infrared spectroscopy for moisture content quantification during freeze-drying. Analytical Chemistry 85 (4):2377–84. doi: 10.1021/ac303403p.
  • Lee, D., S. Lohumi, B. K. Cho, S. H. Lee, and H. Jung. 2020. Determination of derying patterns of radish slabs under different drying methods using hyperspectral imaging coupled with multivariate analysis. Foods 9 (4):484. doi: 10.3390/foods9040484.
  • Lei, T., and D.-W. Sun. 2019. Developments of nondestructive techniques for evaluating quality attributes of cheeses: A review. Trends in Food Science & Technology 88:527–42. doi: 10.1016/j.tifs.2019.04.013.
  • Lei, T., and D.-W. Sun. 2020. A novel NIR spectral calibration method: Sparse coefficients wavelength selection and regression (SCWR). Analytica Chimica Acta 1110:169–80. doi: 10.1016/j.aca.2020.03.007.
  • Lei, T., X. H. Lin, and D.-W. Sun. 2019. Rapid classification of commercial Cheddar cheeses from different brands using PLSDA, LDA and SPA–LDA models built by hyperspectral data. Journal of Food Measurement and Characterization 13 (4):3119–29. doi: 10.1007/s11694-019-00234-0.
  • Li, J., and Z. Q. Qian. 2017. The application of image acquisition and analysis techniques to the field of drying. Food Engineering Reviews 9 (1):13–35. doi: 10.1007/s12393-016-9146-2.
  • Li, J., Z. Li, N. Wang, G. S. V. Raghavan, Y. Pei, C. Song, and G. Zhu. 2020. Novel sensing technologies during the food drying process. Food Engineering Reviews 12 (2):121–48. doi: 10.1007/s12393-020-09215-2.
  • Lin, X., and D.-W. Sun. 2020a. Recent developments in vibrational spectroscopic techniques for tea quality and safety analyses. Trends in Food Science & Technology 104:163–76. doi: 10.1016/j.tifs.2020.06.009.
  • Lin, X., and D.-W. Sun. 2020b. Investigation of moisture distribution of ginger slices and splits during hot-air drying and rehydration procedures by NIR hyperspectral imaging. In Sensing for agriculture and food quality and safety XII, ed. M. S. Kim, B. A. Chin, & B. K. Cho, Vol. 11421, 114210D. Internatonal Society for Optics and Photonics. doi: 10.1117/12.2558213.
  • Lin, X., J. L. Xu, and D.-W. Sun. 2019. Investigation of moisture content uniformity of microwave-vacuum dried mushroom (Agaricus bisporus) by NIR hyperspectral imaging. LWT-Food Science and Technology 109:108–17. doi: 10.1016/j.lwt.2019.03.034.
  • Lin, X., J. L. Xu, and D.-W. Sun. 2021. Comparison of moisture uniformity between microwave-vacuum and hot-air dried ginger slices using hyperspectral information combined with semivariogram. Drying Technology 39 (8):1044–58. doi: 10.1080/07373937.2020.1741006.
  • Lin, X., J. L. Xu, and D.-W. Sun. 2020. Evaluating drying feature differences between ginger slices and splits during microwave-vacuum drying by hyperspectral imaging technique. Food Chemistry 332:127407. doi: 10.1016/j.foodchem.2020.127407.
  • Liu, C., W. Liu, X. Lu, W. Chen, J. Yang, and L. Zheng. 2016. Potential of multispectral imaging for real-time determination of colour change and moisture distribution in carrot slices during hot air dehydration. Food Chemistry 195:110–6. doi: 10.1016/j.foodchem.2015.04.145.
  • Liu, D., D.-W. Sun, and X. A. Zeng. 2014. Recent advances in wavelength selection techniques for hyperspectral image processing in the food industry. Food and Bioprocess Technology 7 (2):307–23. doi: 10.1007/s11947-013-1193-6.
  • Liu, W., M. Zhang, B. Bhandari, and D. Yu. 2021. A novel combination of LF-NMR and NIR to intelligent control in pulse-spouted microwave freeze drying of blueberry. LWT-Food Science and Technology 137:110455. doi: 10.1016/j.lwt.2020.110455.
  • Liu, Y., D.-W. Sun, J. H. Cheng, and Z. Han. 2018. Hyperspectral imaging sensing of changes in moisture content and color of beef during microwave heating process. Food Analytical Methods 11 (9):2472–84. doi: 10.1007/s12161-018-1234-x.
  • Liu, Y., H. Pu, and D.-W. Sun. 2017. Hyperspectral imaging technique for evaluating food quality and safety during various processes: A review of recent applications. Trends in Food Science & Technology 69:25–35. doi: 10.1016/j.tifs.2017.08.013.
  • Liu, Y., Y. Sun, A. Xie, H. Yu, Y. Yin, X. Li, and X. Duan. 2017. Potential of hyperspectral imaging for rapid prediction of anthocyanin content of purple-fleshed sweet potato slices during drying process. Food Analytical Methods 10 (12):3836–46. doi: 10.1007/s12161-017-0950-y.
  • Lohumi, S., S. Lee, H. Lee, and B. K. Cho. 2015. A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration. Trends in Food Science & Technology 46 (1):85–98. doi: 10.1016/j.tifs.2015.08.003.
  • Lu, R., and B. Park. 2015. Introduction. In Hyperspectral imaging technology in food and agriculture, ed. B. Park, & R. Lu, 3–7. New York, USA: Springer.
  • Lu, R., and Y. R. Chen. 1999. Hyperspectral imaging for safety inspection of food and agricultural products. In Pathogen detection and remediation for safe eating, ed. Y. R. Chen, Vol. 3544, 121–33. Bellingham, USA: International Society for Optics and Photonics.
  • Ma, J., H. Pu, and D.-W. Sun. 2018. Predicting intramuscular fat content variations in boiled pork muscles by hyperspectral imaging using a novel spectral pre-processing technique. LWT 94:119–28. doi:10.1016/j.lwt.2018.04.030.
  • Ma, J, and D.-W. Sun. 2020. Prediction of monounsaturated and polyunsaturated fatty acids of various processed pork meats using improved hyperspectral imaging technique. Food Chemistry 321:126695 doi:10.1016/j.foodchem.2020.126695.
  • Ma, J., D.-W. Sun, B. Nicolai, H. Pu, P. Verboven, Q. Wei, and Z. Liu. 2019a. Comparison of spectral properties of three hyperspectral imaging (HSI) sensors in evaluating main chemical compositions of cured pork. Journal of Food Engineering 261:100–8. doi:10.1016/j.jfoodeng.2019.05.024.
  • Ma, J., D.-W. Sun, H. B. Pu, J. H. Cheng, and Q. Y. Wei. 2019b. Advanced techniques for hyperspectral imaging in the food industry: Principles and recent applications. Annual Review of Food Science and Technology 10:197–220. doi: 10.1146/annurev-food-032818-121155.
  • Ma, J., D.-W. Sun, and H. Pu. 2016. Spectral absorption index in hyperspectral image analysis for predicting moisture contents in pork longissimus dorsi muscles. Food Chemistry 197 (Pt A):848–54. doi: 10.1016/j.foodchem.2015.11.023.
  • Ma, J., D.-W. Sun, and H. Pu. 2017. Model improvement for predicting moisture content (MC) in pork longissimus dorsi muscles under diverse processing conditions by hyperspectral imaging. Journal of Food Engineering 196:65–72. doi: 10.1016/j.jfoodeng.2016.10.016.
  • Ma, J., D.-W. Sun, J. H. Qu, and H. Pu. 2017. Prediction of textural changes in grass carp fillets as affected by vacuum freeze drying using hyperspectral imaging based on integrated group wavelengths. Lwt - Food Science and Technology 82:377–85. doi: 10.1016/j.lwt.2017.04.040.
  • Ma, J., J. H. Qu, and D.-W. Sun. 2017. Developing hyperspectral prediction model for investigating dehydrating and rehydrating mass changes of vacuum freeze dried grass carp fillets. Food and Bioproducts Processing 104:66–76. doi: 10.1016/j.fbp.2017.04.007.
  • Mohammadi-Moghaddam, T., S. M. A. Razavi, M. Taghizadeh, B. Pradhan, A. Sazgarnia, and A. Shaker-Ardekani. 2018. Hyperspectral imaging as an effective tool for prediction the moisture content and textural characteristics of roasted pistachio kernels. Journal of Food Measurement and Characterization 12 (3):1493–502. doi: 10.1007/s11694-018-9764-x.
  • Moscetti, R., B. Sturm, S. O. Crichton, W. Amjad, and R. Massantini. 2018. Postharvest monitoring of organic potato (cv. Anuschka) during hot-air drying using visible-NIR hyperspectral imaging. Journal of the Science of Food and Agriculture 98 (7):2507–17. doi: 10.1002/jsfa.8737.
  • Moscetti, R., F. Raponi, S. Ferri, A. Colantoni, D. Monarca, and R. Massantini. 2018. Real-time monitoring of organic apple (var. Gala) during hot-air drying using near-infrared spectroscopy. Journal of Food Engineering 222:139–50. doi: 10.1016/j.jfoodeng.2017.11.023.
  • Moscetti, R., R. P. Haff, S. Ferri, F. Raponi, D. Monarca, P. Liang, and R. Massantini. 2017. Real-time monitoring of organic carrot (var. Romance) during hot-air drying using near-infrared spectroscopy. Food and Bioprocess Technology 10 (11):2046–59. doi: 10.1007/s11947-017-1975-3.
  • Netto, J. M. S., F. A. Honorato, P. M. Azoubel, L. E. Kurozawa, and D. F. Barbin. 2021. Evaluation of melon drying using hyperspectral imaging technique in the near infrared region. LWT-Food Science and Technology 143:111092. doi: 10.1016/j.lwt.2021.111092.
  • Nguyen-Do-Trong, N.,. J. C. Dusabumuremyi, and W. Saeys. 2018. Cross-polarized VNIR hyperspectral reflectance imaging for non-destructive quality evaluation of dried banana slices, drying process monitoring and control. Journal of Food Engineering 238:85–94. doi: 10.1016/j.jfoodeng.2018.06.013.
  • Nunes, C. A. 2014. Vibrational spectroscopy and chemometrics to assess authenticity, adulteration and intrinsic quality parameters of edible oils and fats. Food Research International 60:255–61. doi: 10.1016/j.foodres.2013.08.041.
  • Özdoğan, G., X. Lin, and D.-W. Sun. 2021. Rapid and noninvasive sensory analyses of food products by hyperspectral imaging: Recent application developments. Trends in Food Science & Technology 111:151–65. doi:10.1016/j.tifs.2021.02.044.
  • Pan, Y., D.-W. Sun, J.-H. Cheng, and Z. Han. 2018. Non-destructive Detection and Screening of Non-uniformity in Microwave Sterilization Using Hyperspectral Imaging Analysis. Food Analytical Methods 11 (6):1568–80. doi:10.1007/s12161-017-1134-5.
  • Parasoglou, P.,. E. Parrott, J. Zeitler, J. Rasburn, H. Powell, L. Gladden, and M. Johns. 2010. Quantitative water content measurements in food wafers using terahertz radiation. Terahertz Science and Technology 3 (4):176–82.
  • Pedreschi, F., V. H. Segtnan, and S. H. Knutsen. 2010. On-line monitoring of fat, dry matter and acrylamide contents in potato chips using near infrared interactance and visual reflectance imaging. Food Chemistry 121 (2):616–20. doi: 10.1016/j.foodchem.2009.12.075.
  • Porep, J. U., D. R. Kammerer, and R. Carle. 2015. On-line application of near infrared (NIR) spectroscopy in food production. Trends in Food Science & Technology 46 (2):211–30. doi: 10.1016/j.tifs.2015.10.002.
  • Pu, Y. Y., and D.-W. Sun. 2015. Vis-NIR hyperspectral imaging in visualizing moisture distribution of mango slices during microwave-vacuum drying. Food Chemistry 188:271–8. doi: 10.1016/j.foodchem.2015.04.120.
  • Pu, Y. Y., and D.-W. Sun. 2016. Prediction of moisture content uniformity of microwave-vacuum dried mangoes as affected by different shapes using NIR hyperspectral imaging. Innovative Food Science & Emerging Technologies 33:348–56. doi: 10.1016/j.ifset.2015.11.003.
  • Pu, Y. Y., and D.-W. Sun. 2017. Combined hot-air and microwave-vacuum drying for improving drying uniformity of mango slices based on hyperspectral imaging visualisation of moisture content distribution. Biosystems Engineering 156:108–19. doi: 10.1016/j.biosystemseng.2017.01.006.
  • Pu, Y. Y., M. Zhao, C. O’Donnell, and D.-W. Sun. 2018. Nondestructive quality evaluation of banana slices during microwave vacuum drying using spectral and imaging techniques. Drying Technology 36 (13):1542–53. doi: 10.1080/07373937.2017.1415929.
  • Qin, J., Y. Ying, and L. Xie. 2013. The detection of agricultural products and food using terahertz spectroscopy: A review. Applied Spectroscopy Reviews 48 (6):439–57. doi: 10.1080/05704928.2012.745418.
  • Qu, J. H., D.-W. Sun, J. H. Cheng, and H. Pu. 2017. Mapping moisture contents in grass carp (Ctenopharyngodon idella) slices under different freeze drying periods by Vis-NIR hyperspectral imaging. LWT-Food Science and Technology 75:529–36. doi: 10.1016/j.lwt.2016.09.024.
  • Retz, S., V. E. Porley, G. von Gersdorff, O. Hensel, S. Crichton, and B. Sturm. 2017. Effect of maturation and freezing on quality and drying kinetics of beef. Drying Technology 35 (16):2002–14. doi: 10.1080/07373937.2017.1295051.
  • Rongtong, B., T. Suwonsichon, P. Ritthiruangdej, and S. Kasemsumran. 2018. Determination of water activity, total soluble solids and moisture, sucrose, glucose and fructose contents in osmotically dehydrated papaya using near-infrared spectroscopy. Agriculture and Natural Resources 52 (6):557–64. doi: 10.1016/j.anres.2018.11.023.
  • Sathyanarayana, D. N. (Ed.). 2004. Vibrational spectroscopy: theory and applications. New Age International. https://newagepublishers.com/servlet/nagetbiblio?bno=000843
  • Sebben, J. A., J. da Silveira Espindola, L. Ranzan, N. Fernandes de Moura, L. F. Trierweiler, and J. O. Trierweiler. 2018. Development of a quantitative approach using Raman spectroscopy for carotenoids determination in processed sweet potato. Food Chemistry 245:1224–31. doi: 10.1016/j.foodchem.2017.11.086.
  • Shi, H., and P. Yu. 2017. Comparison of grating-based near-infrared (NIR) and Fourier transform mid-infrared (ATR-FT/MIR) spectroscopy based on spectral preprocessing and wavelength selection for the determination of crude protein and moisture content in wheat. Food Control. 82:57–65. doi: 10.1016/j.foodcont.2017.06.015.
  • Shrestha, L., R. Moscetti, S. Crichton, O. Hensel, and B. Sturm. 2018. Organic apples (cv. Elstar) quality evaluation during hot-air drying using Vis/NIR hyperspectral imaging. In IDS 2018. 21st international drying symposium proceedings, ed C. C. Juan-Andrés, C. P., Gabriela, and M. P., Antonio, 973–80. Valencia, Spain: Editorial Universitat Politècnica de València.
  • Sinelli, N., E. Casiraghi, S. Barzaghi, A. Brambilla, and G. Giovanelli. 2011. Near infrared (NIR) spectroscopy as a tool for monitoring blueberry osmo–air dehydration process. Food Research International 44 (5):1427–33. doi: 10.1016/j.foodres.2011.02.046.
  • Sirisomboon, P., M. Tanaka, T. Kojima, and P. Williams. 2012. Nondestructive estimation of maturity and textural properties on tomato ‘Momotaro’ by near infrared spectroscopy. Journal of Food Engineering 112 (3):218–26. doi: 10.1016/j.jfoodeng.2012.04.007.
  • Smith, B. C. 2003. Quantitative spectroscopy: Theory and practice. San Diego, USA: Academic Press. doi: 10.1016/B978-0-12-650358-6.X5000-3.
  • Stawczyk, J., I. Muñoz, C. Collell, and J. Comaposada. 2009. Control system for sausage drying based on on-line NIR aw determination. Drying Technology 27 (12):1338–43. doi: 10.1080/07373930903383620.
  • Sturm, B., S. Raut, B. Kulig, J. Münsterer, K. Kammhuber, O. Hensel, and S. O. J. Crichton. 2020. In-process investigation of the dynamics in drying behavior and quality development of hops using visual and environmental sensors combined with chemometrics. Computers and Electronics in Agriculture 175:105547. doi: 10.1016/j.compag.2020.105547.
  • Su, W. H., and D.-W. Sun. 2016. Multivariate analysis of hyper/multi-spectra for determining volatile compounds and visualizing cooking degree during low-temperature baking of tubers. Computers and Electronics in Agriculture 127:561–71. doi: 10.1016/j.compag.2016.07.007.
  • Su, W. H., and D.-W. Sun. 2017. Chemical imaging for measuring the time series variations of tuber dry matter and starch concentration. Computers and Electronics in Agriculture 140:361–73. doi: 10.1016/j.compag.2017.06.013.
  • Su, W. H., and D.-W. Sun. 2018. Fourier transform infrared and Raman and hyperspectral imaging techniques for quality determinations of powdery foods: A review. Comprehensive Reviews in Food Science and Food Safety 17 (1):104–22. doi: 10.1111/1541-4337.12314.
  • Su, W. H., S. Bakalis, and D.-W. Sun. 2018. Fourier transform mid-infrared-attenuated total reflectance (FTMIR-ATR) microspectroscopy for determining textural property of microwave baked tuber. Journal of Food Engineering 218:1–13. doi: 10.1016/j.jfoodeng.2017.08.016.
  • Su, W. H., S. Bakalis, and D.-W. Sun. 2019a. Advanced applications of near/mid-infrared (NIR/MIR) imaging spectroscopy for rapid prediction of potato and sweet potato moisture contents. In 2019 ASABE annual international meeting, 1. American Society of Agricultural and Biological Engineers.
  • Su, W. H., S. Bakalis, and D.-W. Sun. 2019b. Chemometric determination of time series moisture in both potato and sweet potato tubers during hot air and microwave drying using near/mid-infrared (NIR/MIR) hyperspectral techniques. Drying Technology 38 (5-6):806–23. doi: 10.1080/07373937.2019.1593192.
  • Su, W. H., S. Bakalis, and D.-W. Sun. 2019c. Fingerprinting study of tuber ultimate compressive strength at different microwave drying times using mid-infrared imaging spectroscopy. Drying Technology 37 (9):1113–30. doi: 10.1080/07373937.2018.1487450.
  • Sun, J., X. Zhang, X. Qiu, X. Zhu, T. Zhang, J. Yang, X. Zhang, and H. Wang. 2020. Hyperspectral data for predicting moisture content and distribution in scallops during continuous and intermittent drying. Drying Technology 36 (7):1–14.
  • Sun, Y., Y. Liu, H. Yu, A. Xie, X. Li, Y. Yin, and X. Duan. 2017. Non-destructive prediction of moisture content and freezable water content of purple-fleshed sweet potato slices during drying process using hyperspectral imaging technique. Food Analytical Methods 10 (5):1535–46. doi: 10.1007/s12161-016-0722-0.
  • Tian, X. Y., J. H. Aheto, C. X. Dai, Y. Ren, and J. W. Bai. 2021. Monitoring microstructural changes and moisture distribution of dry-cured pork: A combined confocal laser scanning microscopy and hyperspectral imaging study. Journal of the Science of Food and Agriculture 101 (7):2727–35. doi: 10.1002/jsfa.10899.
  • Tian, X. Y., J. H. Aheto, J. W. Bai, C. Dai, Y. Ren, and X. Chang. 2021. Quantitative analysis and visualization of moisture and anthocyanins content in purple sweet potato by Vis–NIR hyperspectral imaging. Journal of Food Processing and Preservation 45 (2):e15128. doi: 10.1111/jfpp.15128.
  • Tunde-Akintunde, T. Y. 2011. Mathematical modeling of sun and solar drying of chilli pepper. Renewable Energy. 36 (8):2139–45. doi: 10.1016/j.renene.2011.01.017.
  • von Gersdorff, G. J. E., B. Kulig, O. Hensel, and B. Sturm. 2021. Method comparison between real-time spectral and laboratory based measurements of moisture content and CIELAB color pattern during dehydration of beef slices. Journal of Food Engineering 294:110419. doi: 10.1016/j.jfoodeng.2020.110419.
  • von Gersdorff, G. J. E., V. E. Porley, S. K. Retz, O. Hensel, S. O. J. Crichton, and B. Sturm. 2018. Drying behavior and quality parameters of dried beef (biltong) subjected to different pre-treatments and maturation stages. Drying Technology 36 (1):21–32. doi: 10.1080/07373937.2017.1295979.
  • Wang, K., D.-W. Sun, and H. Pu. 2017. Emerging non-destructive terahertz spectroscopic imaging technique: Principle and applications in the agri-food industry. Trends in Food Science & Technology 67:93–105. doi: 10.1016/j.tifs.2017.06.001.
  • Wise, B. M., N. B. Gallagher, R. Bro, J. M. Shaver, W. Windig, and R. S. Koch. 2006. PLS Toolbox 3.5 for use with MATLAB. Eigenvector Research Incorporated.
  • Wokadala, O. C., C. Human, S. Willemse, and N. M. Emmambux. 2020. Rapid non-destructive moisture content monitoring using a handheld portable Vis–NIR spectrophotometer during solar drying of mangoes (Mangifera indica L.). Journal of Food Measurement and Characterization 14 (2):790–8. doi: 10.1007/s11694-019-00327-w.
  • Wu, D., and D.-W. Sun. 2013a. Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part I: Fundamentals. Innovative Food Science & Emerging Technologies 19:1–14. doi: 10.1016/j.ifset.2013.04.014.
  • Wu, D., and D.-W. Sun. 2013b. Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part II: Applications. Innovative Food Science & Emerging Technologies 19:15–28. doi: 10.1016/j.ifset.2013.04.016.
  • Wu, D., H. Shi, S. Wang, Y. He, Y. Bao, and K. Liu. 2012. Rapid prediction of moisture content of dehydrated prawns using online hyperspectral imaging system. Analytica Chimica Acta 726:57–66. doi: 10.1016/j.aca.2012.03.038.
  • Wu, D., S. Wang, N. Wang, P. Nie, Y. He, D.-W. Sun, and J. Yao. 2012. Application of time series hyperspectral imaging (TS-HSI) for determining water distribution within beef and spectral kinetic analysis during dehydration. Food and Bioprocess Technology 6 (11):2943–58. doi: 10.1007/s11947-012-0928-0.
  • Xie, A., D.-W. Sun, Z. Xu, and Z. Zhu. 2015. Rapid detection of frozen pork quality without thawing by Vis–NIR hyperspectral imaging technique. Talanta 139:208–15. doi:10.1016/j.talanta.2015.02.027.
  • Xie, C. Q., X. L. Li, P. C. Nie, and Y. He. 2013. Application of time series hyperspectral imaging (TS-HSI) for determining water content within tea leaves during drying. Transactions of the ASABE 56 (6):1431–40.
  • Xie, C., X. Li, Y. Shao, and Y. He. 2014. Color measurement of tea leaves at different drying periods using hyperspectral imaging technique. Plos One 9 (12):e113422. doi: 10.1371/journal.pone.0113422.
  • Xu, J. L., A. A. Gowen, and D.-W. Sun. 2018. Time series hyperspectral chemical imaging (HCI) for investigation of spectral variations associated with water and plasticizers in casein based biopolymers. Journal of Food Engineering 218:88–105. doi: 10.1016/j.jfoodeng.2017.09.006.
  • Yancey, J. W., J. K. Apple, J. F. Meullenet, and J. T. Sawyer. 2010. Consumer responses for tenderness and overall impression can be predicted by visible and near-infrared spectroscopy, Meullenet-Owens razor shear, and Warner-Bratzler shear force. Meat Science 85 (3):487–92. doi: 10.1016/j.meatsci.2010.02.020.
  • Yang, Q., D.-W. Sun, and W. Cheng. 2017. Development of simplified models for nondestructive hyperspectral imaging monitoring of TVB-N contents in cured meat during drying process. Journal of Food Engineering 192:53–60. doi: 10.1016/j.jfoodeng.2016.07.015.
  • Yaseen, T., D.-W. Sun, and J. H. Cheng. 2017. Raman imaging for food quality and safety evaluation: Fundamentals and applications. Trends in Food Science & Technology 62:177–89. doi: 10.1016/j.tifs.2017.01.012.
  • Younas, S., C. Liu, H. Qu, Y. Mao, W. Liu, L. Wei, L. Yan, and L. Zheng. 2020. Multispectral imaging for predicting the water status in mushroom during hot-air dehydration. Journal of Food Science 85 (4):903–9. doi: 10.1111/1750-3841.15081.
  • Younas, S., Y. Mao, C. H. Liu, M. A. Murtaza, Z. Ali, L. Wei, W. Liu, and L. Zheng. 2021. Measurement of water fractions in freeze-dried shiitake mushroom by means of multispectral imaging (MSI) and low-field nuclear magnetic resonance (LF-NMR). Journal of Food Composition and Analysis 96:103694. doi: 10.1016/j.jfca.2020.103694.
  • Younas, S., Y. Mao, C. H. Liu, W. Liu, T. Jin, and L. Zheng. 2021. Efficacy study on the non-destructive determination of water fractions in infrared-dried Lentinus edodes using multispectral imaging. Journal of Food Engineering 289:110226. doi: 10.1016/j.jfoodeng.2020.110226.
  • Yu, P., M. Huang, M. Zhang, and B. Yang. 2019. Optimal wavelength selection for hyperspectral imaging evaluation on vegetable soybean moisture content during drying. Applied Sciences 9 (2):331. doi: 10.3390/app9020331.
  • Zahid, A., Abbas, T. H. Imran, M. A. Qaraqe, K. A. Alomainy, A. Cumming, D. R. S. Abbasi. and Q. H. 2019. Characterization and water content estimation method of living plant leaves using Terahertz waves. Applied Sciences 9 (14):2781. doi: 10.3390/app9142781.
  • Zambrano, M. V., B. Dutta, D. G. Mercer, H. L. MacLean, and M. F. Touchie. 2019. Assessment of moisture content measurement methods of dried food products in small-scale operations in developing countries: A review. Trends in Food Science & Technology 88:484–96. doi: 10.1016/j.tifs.2019.04.006.
  • Zhang, M., H. Chen, A. S. Mujumdar, J. Tang, S. Miao, and Y. Wang. 2017. Recent developments in high-quality drying of vegetables, fruits, and aquatic products. Critical Reviews in Food Science and Nutrition 57 (6):1239–55. doi: 10.1080/10408398.2014.979280.
  • Zheng, J., and L. He. 2014. Surface-enhanced Raman spectroscopy for the chemical analysis of food. Comprehensive Reviews in Food Science and Food Safety 13 (3):317–28. doi: 10.1111/1541-4337.12062.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.