Metagenomic analysis of bacterial diversity in pigeon pea after soaking in water
Bibliographic record
Abstract
This study investigated the diversity of bacterial community in the samples of pigeon pea (Cajanus cajan L. Millsp.) soaked in water for 12 h and 24 h. The detection of certain bacterial species in the samples that can be isolated and potentially be used as starter cultures in the development of pigeon pea‐based functional foods is the importance of this study. For bacterial identification, the V1–V9 regions on the 16S ribosomal RNA gene were amplified using 27F and 1492R primers under specific polymerase chain reaction conditions. Genomic DNA (130 ng) was sequenced on the R9.4 flow cell by Oxford Nanopore Technologies using a GridION sequencer. Library preparations were conducted using a Native Barcoding Kit 24 V14 (SQK‐NBD114.24). Primary data were acquired using MinKNOW version 22.05.7. A total of 13 bacterial families and 89 genera were identified in the pigeon pea sample soaked for 12 h, and 26 families and 90 genera were identified in the pigeon pea soaked for 24 h. The values of five diversity indices showed that the sample soaked in water for 24 h had richer bacterial abundance and diversity than for 12 h. Shannon and Simpson values revealed the higher bacterial diversity in the samples collected at 24 h than in those collected at 12 h. Species observation and abundance‐based coverage estimators (ACE) values demonstrated that the samples collected at 24 h harbored higher bac‐ terial richness than those collected at 12 h. Bacterial communities during soaking of the pigeon pea were dominated by the family Enterobacteriaceae and genus Enterobacter. The presence of bacterial genera like Lacticaseibacillus, Lentilactobacillus, and Secundilactobacillus is interesting because of their importance as starter cultures for fermented plant‐based milk products
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".