Screening of effective biocontrol agents against postharvest litchi downy blight caused by Peronophythora litchii
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biocontrol agents (BCAs) could be used for the control of postharvest decay of fruit. In this study, biocontrol bacteria were isolated from litchi soil, leaves and fruit tissues, and their efficacy on the control of postharvest litchi downy blight, caused by Peronophythora litchii, were determined. After evaluating the ability of 188 bacterial isolates to produce certain enzymes and metabolites, and their antagonistic activity in vitro against P. litchii, as well as preliminary identification of 82 representative isolates based on 16 S rDNA sequencing, five isolates including Bacillus amyloliquefaciens PP19 and LI24, Exiguobacterium acetylicum SI17, B. pumilus PI26, and B. licheniformis HS10 were selected for further assessments in several trials in 2016 and 2017. In comparison with control treatment, isolates PP19, SI17 and PI26 could delay the disease development of postharvest litchi downy blight. Furthermore, isolates PP19 and SI17 were able to colonize fruit pericarp without affecting fruit quality. Additionally, the colonization of PP19 changed the microbial community composition on litchi pericarp as demonstrated by pericarp microbiome sequencing. This is the first report of an E. acetylicum acted as a BCA against a phytopathogenic oomycete P. litchii. We conclude that PP19 and SI17 can be used as effective BCAs against postharvest litchi downy blight, especially applied during preharvest stage.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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