Evaluation of fungal infection in peaches based on optical and microstructural properties

Authors: SUN, YE - Nanjing Agricultural University; Lu, Renfu; WANG, XIAOCHAN - Nanjing Agricultural University

Submitted to: Postharvest Biology and Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/13/2020
Publication Date: 4/1/2020
Citation: Sun, Y., Lu, R., Wang, X. 2020. Evaluation of fungal infection in peaches based on optical and microstructural properties. Postharvest Biology and Technology. 165:111181. https://doi.org/10.1016/j.postharvbio.2020.111181.
DOI: https://doi.org/10.1016/j.postharvbio.2020.111181

Interpretive Summary: Peaches are susceptible to fungal infection after harvest, which can spread quickly to healthy fruit in the batch. It is therefore important that infected peaches be removed as soon as possible in order to minimize economic loss to growers and retailers. However, the symptom of fungal infection is difficult to detect at its early stage of development. This research was therefore aimed at evaluating the changes of optical and microstructural properties of peach fruit during fungal infection and assessing the feasibility of using optical properties for detection of fungus-infected peaches. Optical absorption and scattering properties over the spectral region of 600-1000 nm were measured, using a spatially resolved spectroscopy, from 300 healthy and disease-infected peaches over a period of four days. The color of the fruit peel and pulp for all normal and infected fruit was measured, followed by microstructural analysis of peel and pulp tissues, including infected cell area, infection rate and cell features extracted from light and scanning electron microscopy images for selected normal and diseased peaches. Results showed that the optical absorption and scattering properties at the wavelengths of 670 nm and 970 nm were correlated with the microstructural parameters of fruit peel and pulp. Fungal infection had more pronounced effects on the two optical parameters than on the microscopic structural parameters. Classification models were developed, based on the two optical parameters, which achieved 70% and 88% accuracies, when the peaches were classified into four (based on infection time) and two (i.e., healthy and diseased) classes, respectively. This research demonstrated that optical properties are related to the microstructural properties of peaches, and they can provide a useful means for detecting fungal infection in peaches.

Technical Abstract: The objective of this research was to measure the optical and microstructural properties of peaches during fungal infection, and classify the fungal infected peaches based on the optical parameters. Spectra of the absorption and reduced scattering coefficients over 600-1,000 nm for 300 healthy and fungal infected peaches over a period of four days were measured by using a spatially-resolved spectroscopic technique. The colour and microstructural features of fruit pulp and peel were measured, using colorimetry, light microscopy and scanning electron microscopy (SEM), as indicators of the changes in tissue appearance and internal quality in infected peaches. The absorption and reduced scattering spectra of peaches exhibited a pattern of decrease during the fungal infection, and their values at the wavelengths of 670 nm and 970 nm were correlated with the microstructural parameters of fruit peel and pulp (i.e., mycelial area, intrusion rate, and the energy, entropy and contrast extracted from the SEM images). Significant differences in the microstructural parameters between healthy and infected peaches were found after three days of inoculation for the peel tissues and after two days for pulp tissues. Significant differences in both absorption and reduced scattering coefficients between the healthy and infected peaches after one day of inoculation were also observed. It was found that the optical parameters were more sensitive to disease infection than some of the microstructural parameters. Partial least squares discriminant analysis (PLSDA) models were developed, based on the two optical parameters and their combinations, for classifying diseased and healthy peaches. The PLSDA model for combination of the two optical parameters (i.e., absorption coefficient multiplied by reduced scattering coefficient) achieved 70% and 88% accuracies, respectively, when the peaches were classified into four (based on inoculation days) and two (i.e., healthy and diseased) classes. This research demonstrated that optical properties can be used for assessing quality or structural changes and detecting disease infection in peach fruit.