Deciphering the Rhizosphere and Geocaulosphere Microbiomes of Potato Following Inoculation with the Biocontrol Agent <i>Pseudomonas fluorescens</i> Strain LBUM223
Why this work is in the frame
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Bibliographic record
Abstract
The phenazine-1-carboxylic acid (PCA)-producing Pseudomonas fluorescens strain LBUM223 shows biocontrol potential against Streptomyces scabies, which causes common scab of potato. To better characterize the impact of inoculating this specific biocontrol agent under field conditions, the microbiomes of the rhizosphere and the geocaulosphere of potato plants were characterized using next-generation sequencing. A single initial application or biweekly applications of LBUM223 were performed up to 11 weeks after planting. Rhizosphere and geocaulosphere soils (when potato tubers were produced) were sampled every 2 weeks. Following soil DNA extractions, 16S rRNA gene amplification and sequencing were performed using the Illumina MiSeq technology. The QIIME pipeline was used for data analyses. Results were generated from 45 rhizosphere and 27 geocaulosphere samples, for which 63,502 and 44,469 different operational taxonomical units were observed. Diversity comparisons between both datasets were performed. To our knowledge, this is the first time that the geocaulosphere microbiome is characterized and compared with the rhizosphere microbiome following inoculation with a specific microorganism. Eleven phyla accounted for 95% of the diversity, with Actinobacteria, Proteobacteria, Chloroflexi, and Acidobacteria being the most abundant ones. Overall, the results obtained suggest that P. fluorescens strain LBUM223 does not significantly alter the autochthonous rhizosphere nor geocaulosphere microbiomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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 it