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Record W4413380689 · doi:10.3389/fpls.2025.1500877

Comparative analysis of cranberry fruit rot fungal diversity in Massachusetts from wild, organic, and conventional ecosystems using multiplex PCR

2025· article· en· W4413380689 on OpenAlexaff
Salisu Sulley, Mura Jyostna Devi, Benjamin Cinget, Matteo Conti, Richard E. Bélanger, Frank L. Caruso, Leela Saisree Uppala

Bibliographic record

VenueFrontiers in Plant Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversité Laval
FundersCenter for Agriculture, Food and the Environment, University of Massachusetts AmherstUniversity of Massachusetts AmherstNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsBogSpecies richnessBiologyBotanyEcosystemPopulationSpecies diversityHorticultureEcologyPeatMedicine

Abstract

fetched live from OpenAlex

Cranberry fruit rot (CFR) has been a major challenge in cranberry production affecting fruit quality, particularly in Massachusetts and New Jersey. It is known to be a disease complex associated with several diverse fungi. This study provides the first comprehensive assessment of CFR fungal population dynamics across wild, organic, and conventional cranberry production systems in southeastern Massachusetts. By employing multiplex PCR, a high-throughput molecular method for the simultaneous detection of multiple fungi, we investigated the prevalence and diversity of 11 most commonly associated fruit rot fungi in 2021 and 2022, in 32 (23 conventional, 4 organic and 5 wild) and 50 (40 conventional, 4 organic and 6 wild) cranberry bogs respectively. Significant differences in the detection of CFR fungi were observed across these ecosystems. Conventional fields showed varied fruit rot incidence, ranging from 2-42% in 2021 and 1-48% in 2022. Species richness analysis indicated that on average, wild bogs were more species-rich and diverse, with 5.5 CFR fungi detected per sample compared to 4 CFR fungi in both conventional and organic bogs. Organic bogs exhibited a significant decline in species richness from 6 fungi in 2021 to 2 fungi in 2022. Except for Phomopsis vaccinii, which was not observed in organic bogs in either year, all 11 CFR fungi were detected across the ecosystems: some in both growing seasons and some in only one. Key CFR fungi such as Coleophoma empetri, Allantophomopsis cytisporea and Botryosphaeria vaccinii were consistently found across all ecosystems and both years of study. Analysis of year-to-year variation indicates that wild bogs exhibited higher fungal carryover, with 8 out of the 11 CFR fungi persisting from one year to the next, compared to 6 fungi in conventional bogs and 4 fungi in organic bogs. Notably, C. empetri, B. vaccinii, and A. cytisporea demonstrated year-to-year persistence across all three bog types. Among these, C. empetri exhibited the greatest persistence across all three ecosystems, with 96%, 100% and 60% of the conventional, organic and wild bogs maintaining its presence across both years. Colletotrichum spp. persisted in 43% of the conventional bogs but detected only in one of the two years studied in organic and wild bogs resulting in 0% persistence from one year to the next. The study also noted a general decrease in Botryosphaeria vaccinii and an increase in Physalospora vaccinii across all bog types. This research highlights the varying persistence and complex dynamics of CFR fungi across different cranberry ecosystems, as well as the potential impact of management practices on fungal populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.252
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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