Automated Ribosomal Intergenic Spacer Analysis to Detect Pathogenic Fungi in Dark-Colored Spots on Apple Fruits

Abstract

Dark-colored spots (DCSs) found on apples at harvest time worldwide significantly reduce the commercial value of the fruits. In this study, we conducted an automated ribosomal intergenic spacer analysis (ARISA) to reliably detect fungal pathogens in these lesions. The fragment sizes of peaks for eight species and two species complexes that might cause DCSs on apples in northern Honshu Island, Japan, were determined on the basis of the ARISA. The fragment sizes for six species (Botryosphaeria kuwatsukai, Diplocarpon mali, Mycosphaerella pomi, Neonectria galligena, Phlyctema vagabunda, and Venturia inaequalis) were unique, enabling their detection in a single ARISA trial. However, two other species and two species complexes had similar fragment sizes. To identify these fungi, PCR amplifications using species- or genus-specific primers were needed. Using this method to examine the fresh tissue of DCSs (i.e., after removing the epidermis) on commercially produced apples resulted in the detection of six fungal species and two Colletotrichum species complexes. Because the pathogenic fungi in the tissue underlying lesions are most likely the causal agents, these fungi could be responsible for the DCSs on apple fruits. An automated analysis of the PCR products amplified for the ARISA enables the rapid examination of many samples. These results indicate that the ARISA-based technique developed in the present study is useful for the accurate, reliable, and comprehensive detection of the pathogens causing DCSs on apple fruits. [Graphic: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Keywords

• apple
• automated ribosomal intergenic spacer analysis
• dark-colored spots (DCSs)
• detection
• fungal pathogen
• postharvest diseases