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Record W2031234190 · doi:10.1094/phyto-97-9-1071

Edaphic Soil Levels of Mineral Nutrients, pH, Organic Matter, and Cationic Exchange Capacity in the Geocaulosphere Associated with Potato Common Scab

2007· article· en· W2031234190 on OpenAlexaboutno aff
George Lazarovits, Jacquelyn Hill, Greg Patterson, Kenneth L. Conn, N. S. Crump

Bibliographic record

VenuePhytopathology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsEdaphicSoil waterCommon scabCation-exchange capacityBiologyOrganic matterSoil pHNutrientVeterinary medicineHorticultureAgronomyStreptomycesEcologyBacteriaMedicine

Abstract

fetched live from OpenAlex

ABSTRACT In order to determine possible relationships between geocaulosphere soil properties and severity of common scab of potato caused by Streptomyces scabies, soils were collected from representative commercial potato fields in Canada: in Simcoe and Dufferin Counties, Ontario and across Prince Edward Island (PEI) in August 2004. Soils immediately adjacent to tubers were sampled and analyzed for select edaphic factors and for pathogen presence using polymerase chain reaction (PCR) tests with primers that amplify a region of the TxtA gene involved in regulating the biosynthesis of the thaxtomin toxin family. Individual tubers were assessed visually for scab severity. The relationships between soil chemical factors and disease severity were investigated for each region to detect the strongest relationships. Principal component analysis revealed a distinctive clustering of samples with respect to disease severity in PEI but not in Ontario soils. Total and percent saturation of K (%K) were the only factors found associated with high disease severity in soils from both provinces. In PEI soils, pH, Mg, Ca, Cu, and %K, %Mg, %Ca, and %Na were associated with high disease severity, whereas cation exchange capacity (CEC) and Al were correlated with low disease severity soils. In Ontario, high Mn content was strongly correlated with low disease severity soils, whereas %K and organic matter content were correlated with disease severity. Partitioning samples into presence or absence of the TxtA PCR product with corresponding high or low severity showed further significant relationships in the data. There was an excellent correlation between Streptomyces spp. presence as detected by PCR and disease severity in PEI soils; however, the relationship was not as clear in Ontario soils, where many PCR-positive soils had low disease incidence. Principal component and partial least square analysis indicated that disease severity was predicted by soil factors such as organic matter, CEC, pH, Al, %Ca, %Mg, and %K for PEI but not for Ontario soils. The data reveal that the relationship between scab severity and soil chemical components is complex and potentially soil specific.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.216
Teacher spread0.191 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations49
Published2007
Admission routes1
Has abstractyes

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