The dynamics of indigenous epiphytic bacterial and fungal communities of barley grains through the commercial malting process in Western Canada
Bibliographic record
Abstract
Microbial activity is present at every step of the malting process. It is, therefore, critical to manage the grain-associated microbial communities for the production of high-quality malts. This study characterized barley and malt epiphytic microbiota by metabarcoding the internal transcribed spacer (ITS) 2 region and the 16S rRNA gene V1–V4 metabarcodes, respectively. We elucidated the changes in the diversity and the compositional and functional changes of the grain-associated microbiota and inferred the impact of such changes on malting efficiency and premature yeast flocculation (PYF) of the commercial malt end product. Through the malting process, the fungal diversity decreased while bacterial community diversity increased. Lactic acid bacteria (LAB) and some mycotoxin-producing fungi (e.g. Fusarium spp.) were found to be significantly enriched in malts. Most potential fungal pathogens, however, did not change in abundance through the malting process. Fungi (e.g. Aureobasidium, Candida) and bacteria (e.g. LAB, Arthrobacter, Brachybacterium) with the potential to generate organic acids or exhibit high hydrolytic enzymatic activity for degrading the endosperm cell walls and storage proteins were detected in greater abundance in kilned malt, suggesting their contribution to malting efficiency. Bacterial and fungal operational taxonomic units (OTUs) associated with PYF-positive malt were mainly identified as Aureobasidium, Candida, and Leuconostoc, while Pleosporaceae, Steptococcus, and Leucobacter were associated with PYF-negative malt. The ecological networks of the field and steeped barley samples were found to be larger and denser, while that of the malt microbiome was smaller and less connected. A decrease in the proportion of negative interactions through the malting process suggested that malting destabilized the microbial networks. In summary, this study profiled the microbiota of commercial malting barley and malt samples in western Canada; the findings expanded our knowledge in the microbiology of malting while providing potential insights regarding the management of microbial-associated problems, such as PYF, in commercial malting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".