Advances in non-destructive evaluation of nutritional value as an index of quality of fruits and vegetables using hyperspectral imaging
2010
Bato, PM, Philippines Univ. Los Baños, College, Laguna (Philippines). Coll. of Engineering and Agro-Industrial Technology
Recently, consumers are more concerned with better health enhanced food products. The quality estimation and testing of agricultural produce is more incessantly pursued than ever before. In this research, a hyperspectral imaging system that combined spectral and image information to evaluate the quality of eggplant in terms of anthocyanin pigment content distribution (Solanum melongena L.) was developed. The imaging system consisted of a liquid crystal tunable filter and a CCD camera that acquires images from 420 nm to 750 nm at 2 nm intervals. Using multiple linear regression between spectral images and absorbance values measured from chemical analysis, calibration models were generated and applied to form the distribution maps of anthocyanin pigment in eggplant. The results showed that the spectral image at 716 nm and the acetic acid solution extracted pigment at 525 nm had strong correlation. The one-wavelength model had a correlation coefficient (r) of 0.969 with a standard error of calibration (SEP) of 0.054. By applying this calibration equation, distribution maps and graps of percent anthocyanin pigment absorbance were constructed to estimate the anthocyanin pigment in eggplant. To account for the effects of fruit size, the distance between the camera and samples was varied by around 30 mm to cover the mean radius of eggplant. However, it was found out that camera height did not affect the measured values of anthocyanin pigment on the surface of the fruit. The study hsoed that hyperspectral imaging method could be used to measure anthocyanin pigment content with high accuracy.
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