Quality evaluation of sweet potatoes (Ipomoea batatas L.) of different varieties using laser light backscattering imaging technique
Non-destructive quality monitoring for horticultural products by means of optical imaging methods have gained wide interest in recent years. This study sought to investigate the potential use of laser-light backscattering imaging technique (LLBI) for non-invasive quality evaluation of sweet potatoes...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
Elsevier
2020
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/87371/ https://www.sciencedirect.com/journal/scientia-horticulturae |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Non-destructive quality monitoring for horticultural products by means of optical imaging methods have gained wide interest in recent years. This study sought to investigate the potential use of laser-light backscattering imaging technique (LLBI) for non-invasive quality evaluation of sweet potatoes of different varieties after being harvested and stored at ambient temperature. A total of 360 newly harvested samples from the three varieties of locally-produced sweet potatoes in Malaysia i.e. Keledek Anggun 3, Keledek Jingga, and Keledek Kuning were purchased and stored in an ambient room temperature (28–30 °C) for a period of twenty one (21) days. After each 7-day 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 flesh color properties (L*, a*, b*) as reference quality parameters (QP) were measured right after BSI acquisitions. Multiple Linear Regression (MLR) was applied to correlate and predict the relationship between the extracted backscattering parameters (BP) and the QP. Results revealed that there were significant changes (P < 0.05) in the BP during storage for both wavelengths applied. Among all the QP, the textural properties gave the highest correlation (r> 0.70) with BP, particularly the Keledek Kuning variety. The 658 nm wavelength showed better prediction results than 780 nm with r > 0.85 in measuring the textural properties. Thus, the study demonstrated the feasibility of LLBI as a useful non-destructive technique to evaluate the quality of sweet potatoes and can be further utilized for online optical quality grading. |
|---|