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Record W7045608407

BIOCONTROL OF ROOT ROT COMPLEX IN FIELD PEA AND LENTIL AND COMPLETE GENOME ANALYSIS OF BIOCONTROL BACTERIA

2023· dissertation· en· W7045608407 on OpenAlexfundaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCollege of Agriculture and Bioresources, University of SaskatchewanMinistry of Agriculture - SaskatchewanUniversity of Regina
KeywordsBiological pest controlPantoea agglomeransOomyceteField peaSativumRoot rotPhytophthora capsiciPathosystem
DOInot available

Abstract

fetched live from OpenAlex

Aphanomyces root rot (ARR), caused by the soil-borne oomycete pathogen, Aphanomyces euteiches, is a destructive disease of legumes, most notably to field pea (Pisum sativum L.) and lentil (Lens culinaris L.). It commonly occurs as root rot complex (RRC) along with other soil-borne pathogens, including Fusarium avenaceum and F. oxysporum, which collectively result in significant crop damage leading to complete loss of productivity. Currently, in Canada, the available management strategies against RRC are inadequate. However, a recent study at the University of Saskatchewan identified soil bacteria, Lysobacter capsici K-Hf-H2, Pseudomonas simiae K-Hf-L9 and Pantoea agglomerans PSV1-7, as potential biocontrol agents against ARR in field pea under controlled growth chamber condition. Therefore, the purpose of this study was to i) investigate the potential for biological control of RRC caused by A. euteiches, F. avenaceum and F. oxysporum and ii) unravel the mechanisms by which biocontrol was achieved. To achieve these objectives, L. capsici K-Hf-H2, P. simiae K-Hf-L9 and P. agglomerans PSV1-7 were evaluated against RRC in field pea and lentil under controlled growth chamber conditions, and the strains’ whole genomes were sequenced, annotated, and comparatively analyzed using bioinformatics tools. Also, laboratory-based general functional experiments, siderophores production, proteolytic and cellulolytic capacities, and desiccation tolerance were conducted. Additionally, the current state of the science "biological control of ARR" was determined via a quantitative meta-analysis review using data extracted from published articles investigating the biocontrol of ARR in pea. My meta-analysis findings suggest potential for biological control of ARR and the need for more field trials to demonstrate the higher efficacy level observed under growth chamber conditions. Compared to P. simiae K-Hf-L9 and P. agglomerans PSV1-7, L. capsici K-Hf-H2 demonstrated the highest significant biocontrol efficacy against RRC in field pea and lentil, with higher efficacy in field pea. Moreover, my genome analyses identified several genes and gene clusters encoding various traits potentially involved in the suppression of RRC. Such genetic determinants detected in L. capsici K-Hf-H2 genome include genes encoding for Heat Stable Antifungal Factor (HSAF), endoglucanase (cellulase), chitinase, extracellular zinc proteases (metalloendopeptidase), aminopeptidases and siderophores. In P. simiae K-Hf-L9 and P. agglomerans PSV1-7 genomes, gene and gene clusters encoding iron acquisition, chitin metabolism and protein degradation were detected. I also found evidence that L. capsici K-Hf-H2, P. simiae K-Hf-L9 and P. agglomerans PSV1-7 chelate iron through siderophore production and hydrolyze protein via proteolytic activity. Furthermore, L. capsici K-Hf-H2 and P. simiae K-Hf-L9 were positive for cellulolytic activity. Therefore, my findings indicate the great potential of biological control of RRC in field pea and lentil. Also, the findings in this study represent a significant contribution to the effort of biological control of RRC in field pea and lentil in Canada.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.175
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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