ArticleMicrobiome2019
Microbiome-driven identification of microbial indicators for postharvest diseases of sugar beets.
Article in Microbiome, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 94 citations in OpenAlex.
- The Integrated Management of Sugar-Beet Soilborne Diseases Through Rhizosphere Microbiome Strategies: A Critical Review of Agronomic Evidence and Application Gaps.Plants (Basel, Switzerland) · 2026Review
- Divergent assembly patterns of core and non-core microbial taxa under low environmental heterogeneity in the surface waters of the Xisha Islands.Microbiology spectrum · 2026Article
- Optimizing antimicrobial dosing of bacterial isolates from sugar beet factories to reduce sucrose losses.Applied and environmental microbiology · 2026Article
- Article
- Microbial succession and tissue-specific restructuring of bacterial and fungal communities during post-harvest onion bulb rotting.Frontiers in microbiology · 2026Article
- Integrating Microbiomes for Regenerative Food Systems: Recent Insights, Implementations, and Emerging Trends.Food science & nutrition · 2025Review
- The Effects of Experimental Warming on Phyllosphere Microbial Communities of Picea asperata and Fargesia nitida in Eastern Tibetan Plateau, China.Current microbiology · 2025Article
- Deciphering the Distinct Associations of Rhizospheric and Endospheric Microbiomes with Capsicum Plant Pathological Status.Microbial ecology · 2025Article
- Phenotypic variation in growth and biofilm formation ofFrontiers in microbiology · 2025Article
- Root Microbiome and Metabolome Traits Associated with Improved Post-Harvest Root Storage for Sugar Beet Breeding Lines Under Southern Idaho Conditions.International journal of molecular sciences · 2024Article
- Profiling of the Citrus Leaf Endophytic Mycobiota Reveals Abundant Pathogen-Related Fungal Groups.Journal of fungi (Basel, Switzerland) · 2024Article
- Quality Changes and Fungal Microbiota Dynamics in Stored Jujube Fruits: Insights from High-Throughput Sequencing for Food Preservation.Foods (Basel, Switzerland) · 2024Article
- Microbiome-based classification models for fresh produce safety and quality evaluation.Microbiology spectrum · 2024Article
- Changes in Microbial Composition During the Succession of Biological Soil Crusts in Alpine Hulun Buir Sandy Land, China.Microbial ecology · 2024Article
- Multiomics Reveals the Key Microorganisms and Metabolites in the Resistance to Root Rot Disease ofGenes · 2023Article
- Pathogenic fungi shape the fungal community, network complexity, and pathogenesis in kiwifruit.Microbial biotechnology · 2023Article
- Composition and variability of core phyllosphere fungal mycobiota on field-grown broccoli.Environmental microbiome · 2023Article
- Understanding the sugar beet holobiont for sustainable agriculture.Frontiers in microbiology · 2023Review
- Effects of rice blast biocontrol strainFrontiers in microbiology · 2023Article
- Exploring the antibacterial potential of plant extracts and essential oils againstFrontiers in microbiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSugar loss due to storage rot has a substantial economic impact on the sugar industry. The gradual spread of saprophytic fungi such as Fusarium and Penicillium spp. during storage in beet clamps is an ongoing challenge for postharvest processing. Early detection of shifts in microbial communities in beet clamps is a promising approach for the initiation of targeted countermeasures during developing storage rot. In a combined approach, high-throughput sequencing of bacterial and fungal genetic markers was complemented with cultivation-dependent methods and provided detailed insights into microbial communities colonizing stored roots. These data were used to develop a multi-target qPCR technique for early detection of postharvest diseases.
resultsThe comparison of beet microbiomes from six clamps in Austria and Germany highlighted regional differences; nevertheless, universal indicators of the health status were identified. Apart from a significant decrease in microbial diversity in decaying sugar beets (p ≤ 0.01), a distinctive shift in the taxonomic composition of the overall microbiome was found. Fungal taxa such as Candida and Penicillium together with the gram-positive Lactobacillus were the main disease indicators in the microbiome of decaying sugar beets. In contrast, the genera Plectosphaerella and Vishniacozyma as well as a higher microbial diversity in general were found to reflect the microbiome of healthy beets. Based on these findings, a qPCR-based early detection technique was developed and confirmed a twofold decrease of health indicators and an up to 10,000-fold increase of disease indicators in beet clamps. This was further verified with analyses of the sugar content in storage samples.
conclusionBy conducting a detailed assessment of temporal microbiome changes during the storage of sugar beets, distinct indicator species were identified that reflect progressing rot and losses in sugar content. The insights generated in this study provide a novel basis to improve current or develop next-generation postharvest management techniques by tracking disease indicators during storage.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.