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The decay and microbial succession of apples with bitter rot across a vegetation diversity gradient

dataset
posted on 2024-01-27, 00:15 authored by Peter-Bell labs shared submissions
In this study we monitored decay rates and succession of fungi of apples with bitter rot in tree canopies, and on the soil surface in tree rows, grass drive rows, and nearby diverse plant communities. We hypothesized that decay would occur most rapidly within diverse plant communities, which would provide a more diverse array of potential fungal decomposers. Apples in tree canopies became dry and mummified and carried more Colletotrichum gene marker copies into the following growing season than did apples on the soil surface. Of the soil surface samples, those in grass drive rows and diverse plant communities remained moist, decayed faster, and had the sharpest decreases in Colletotrichum gene marker copies, while apples in tree rows dried out and had slightly slower decay rates and decreased Colletotrichum gene marker copies. Fungal composition across all decaying apples was dominated by yeasts, with higher genus-level richness, diversity, and evenness in apples from tree canopies than those on the soil surface. In soil surface apples, we observed clear successional waves of Pichia, Kregervanrija, and [Candida] yeasts, with similar but distinctly diverging fungal composition. Our results show that orchard floor management can influence fungal succession in apples with bitter rot, but suggests that bitter rot management should primarily focus on removing infected apples from tree canopies.

Funding

National Institute of Food and Agriculture, GNE16-180-32231

National Science Foundation, NA

National Institute of Food and Agriculture, Project PEN04694, Accession number 1018736

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2021-05-24

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

sequence analysis

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJNA732466

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