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 using spatial-frequency domain imaging (SFDI) technique, for assessing the soluble solid content (SSC), firmness, and color parameters. A laboratory-based multispectral SFDI system was developed for acquiring SFDI of 140 “Golden Delicious” apples, from which absorption coefficient (μ_a) and reduced scattering coefficient (μ_s′) 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 the region of interest (ROI) on the average optical properties. Support vector machine (SVM), multiple linear regression (MLR), and partial least square (PLS) models were developed based on μ_a, μ_s′ and their combinations (μ_a × μ_s′ and μ_eff) for predicting apple qualities, among which SVM outperformed the best. Better prediction results for quality parameters based on the μ_a were observed than those based on the μ_s′, and the combinations further improved the prediction performance, compared to the individual μ_a or μ_s′. The best prediction models for SSC and firmness parameters [slope, flesh firmness (FF), and maximum force (Max.F)] were achieved based on the μ_a × μ_s′, whereas those for color parameters of b* and C* were based on the μ_eff, with the correlation coefficients of prediction as 0.66, 0.68, 0.73, 0.79, 0.86, and 0.86, respectively.