Internal quality evaluation of sweet potatoes (Ipomoea batatas L.) at different storage temperatures using laser light backscattering imaging technique
Laser-light backscattering imaging (LLBI) has gained wide interest as a non-destructive technique for quality monitoring of various agricultural and food products. In this study, the potential use of LLBI technique to evaluate the quality parameters (QP) of the different sweet potato (Ipomoea batata...
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Format: | Thesis |
Language: | English |
Published: |
2020
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Subjects: | |
Online Access: | http://psasir.upm.edu.my/id/eprint/89922/1/FK%202020%2078%20ir.pdf http://psasir.upm.edu.my/id/eprint/89922/ |
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Institution: | Universiti Putra Malaysia |
Language: | English |
Summary: | Laser-light backscattering imaging (LLBI) has gained wide interest as a non-destructive technique for quality monitoring of various agricultural and food products. In this study, the potential use of LLBI technique to evaluate the quality parameters (QP) of the different sweet potato (Ipomoea batatas L.) varieties during storage was investigated. A total of 1,080 samples from the three varieties of locally-produced sweet potatoes in Malaysia namely Keledek Anggun 3, Keledek Jingga, and Keledek Kuning were purchased and stored into three different storage temperatures (5 °C, 15 °C, and 30 °C) for a period of 21 days (d). After every 7 d of storage, respective samples were taken out and backscattering images (BSI) were acquired using a charge-coupled device (CCD) camera attached with laser diodes emitting lights at 658 nm and 780 nm wavelengths, respectively. Quality attributes such as moisture content (MC), soluble solid content (SSC), textural properties (hardness, fracturability, adhesiveness), and color properties (L*, a*, b*) were measured right after BSI acquisitions as standard reference QP. Multiple Linear Regression (MLR) was applied to correlate and predict the relationship between the extracted backscattering parameters (BP) and the QP. Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) were also employed to classify and visualize the possible clustered variations of the BP in both wavelengths across the different varieties and storage conditions. Results revealed that there were significant changes (P<0.05) in the BP during storage for both wavelengths. Scanning Electron Microscopy (SEM) analysis also showed obvious changes in the microstructural properties of the stored sweet potatoes. Among all the QP, SSC and textural properties obtained the highest coefficient of correlation, r > 0.70 with BP, particularly in the Keledek Kuning variety. The 658 nm wavelength showed better prediction results than 780 nm with r > 0.85 in measuring the textural properties. Moreover, 15 °C storage showed suitability of the technique with favorable correlation results (r > 0.50) in the QP across all the varieties. Thus, the study demonstrated the feasibility of LLBI as a useful non-destructive technique to evaluate the quality of sweet potatoes during storage and can be further utilized for online optical quality grading of other agricultural products. |
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