Hyperspectral imaging technology for monitoring of moisture contents of dried persimmons during drying process
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Hyperspectral imaging technology for monitoring of moisture contents of dried persimmons during drying process Jeong-Seok Cho1 • Ji-Young Choi2 • Kwang-Deog Moon2
Received: 28 February 2020 / Revised: 18 June 2020 / Accepted: 24 June 2020 Ó The Korean Society of Food Science and Technology 2020
Abstract The moisture content of persimmons during drying was monitored by hyperspectral imaging technology. All persimmons were dried using a hot-air dryer at 40 °C and divided into seven groups according to drying time: semi-dried persimmons (Cont), 1 day (DP-1), 2 days (DP-2), 3 days (DP-3), 4 days (DP-4), 5 days (DP-5), and 6 days (DP-6). Shortwave infrared hyperspectral spectra and moisture content of all persimmons were analyzed to develop a prediction model using partial least squares regression. There were obvious absorption bands: two at approximately 971 nm and 1452 nm were due to water absorption related to O–H stretching of the second and first overtones, respectively. The R-squared value of the optimal calibration model was 0.9673, and the accuracy of the moisture content measurement was 95%. These results indicate that hyperspectral imaging technology can be used to predict and monitor the moisture content of dried persimmons during drying.
& Kwang-Deog Moon [email protected] Jeong-Seok Cho [email protected] Ji-Young Choi [email protected] 1
United States Department of Agriculture, Agricultural Research Service, 950 College Station Rd, Athens, GA 30605, USA
2
Department of Food Science and Technology, Kyungpook National University, 80 Daehak-ro, Daegu 41566, South Korea
Keywords Dried persimmons Moisture content Hyperspectral imaging Partial least squares regression Spectra pre-processing
Introduction Dried persimmons have good qualitative properties and an extended shelf-life (Nicoleti et al., 2005). Drying reduces the moisture content (MC) of the material and minimizes qualitative changes during its storage. MC is one of the critical parameters in determining the quality of whole dried persimmons; therefore, many studies have reported various methods for drying them (Ca´rcel et al., 2010). Generally, many producers rely on their empirical knowledge when producing dried persimmons. Therefore, the final products have different levels of MC and other qualitative properties such as texture, taste, and color. Therefore, it is essential to develop a method for monitoring MC during drying persimmons. Hyperspectral imaging (HSI) technology is widely used as a non-destructive method to investigate the local distribution of components and monitor chemical changes using near-infrared electromagnetic radiation (Huang et al., 2014a, b). Spectroscopic methods of analysis provide limited spatial information regarding samples; however, HSI technology can provide three-dimensional information that consists of both the spatial and spectral intensity information across the whole surface a sample (Eady et al., 2018). Thus, HSI technology can provide information on the distribution of chemical components throu
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