AUTHOR=Peng Hehuan , Zhang Chang , Sun Zhizhong , Sun Tong , Hu Dong , Yang Zidong , Wang Jinshuang 

TITLE=Optical Property Mapping of Apples and the Relationship With Quality Properties

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2022.873065

DOI=10.3389/fpls.2022.873065

ISSN=1664-462X

ABSTRACT=This paper reports on the measurement of optical property mapping of apples at the wavelengths of 460, 527, 630 and 710 nm by using spatial-frequency domain imaging (SFDI) technique, for assessing the soluble solids content (SSC), firmness and color parameters. A laboratory-based multispectral SFDI system was developed for acquiring spatial-frequency domain images of 140 ‘Golden Delicious’ apples, from which absorption coefficient (ua) and reduced scattering coefficient (us') mappings were quantitatively determined using the three-phase demodulation coupled with curve-fitting method. There was no noticeable spatial variation in the optical property mapping based on the resulting effect of different sizes of region of interest on the average optical properties. Support vector machine (SVM), multiple linear regression (MLR) and partial least squares (PLS) models were developed based on ua, us' and their combinations (ua*us' and ueff) for predicting apple qualities, among which SVM outperformed the best. Better prediction results for quality parameters based on the ua were observed than those based on the us', and the combinations further improved the prediction performance, compared to the individual ua or us'. The best prediction models for SSC and firmness parameters (slope, flesh firmness and maximum force) were achieved based on the ua*us', while those for color parameters of b* and C* were based on the ueff, with the correlation coefficients of prediction as 0.66, 0.68, 0.73, 0.79, 0.86 and 0.86, respectively.