MétaCan
Menu
Back to cohort
Record W2149689171 · doi:10.21273/horttech.21.6.759

Effects of Using Water Treated by Artificial Wetlands on Root Rot Suppression and Tomato Growth

2011· article· en· W2149689171 on OpenAlex
Nicolas Gruyer, Martine Dorais, Gérald J. Zagury, Beatrix Alsanius

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHortTechnology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsPolytechnique MontréalAgriculture and Agri-Food CanadaUniversité Laval
FundersAgriculture and Agri-Food CanadaSvenska Forskningsrådet Formas
KeywordsAgronomyPythium ultimumTypha angustifoliaBiologyHorticultureRoot rotPopulationRandomized block designWetlandEnvironmental scienceRhizoctonia solaniEcology

Abstract

fetched live from OpenAlex

The objectives of this study were to evaluate the risks and benefits of using artificial wetland-treated waters to irrigate tomato plants ( Lycopersicom esculentum ) and the potential for suppression of Pythium ultimum . The experiment was conducted in a greenhouse using tap water (control) and treated waters coming from three types of horizontal subsurface flow artificial wetlands filled with pozzolana and implanted with common cattail ( Typha latifolia ). Wetland units contained either a simple [artificial wetland with sucrose (AWS)] or complex [artificial wetland with compost (AWC)] carbon source or no [artificial wetland with no carbon (AW)] additional carbon source. A complete randomized split-block design comparing root sensitivity to root rot (inoculated and uninoculated plants) in main plots and four nutrient solutions [1) control, 2) treated water from AWS, 3) treated water from AWC, and 4) treated water from AW] in subplots was used in six replications. Tomato plants were inoculated with P. ultimum twice during the experimental period. The use of treated waters reduced the in vivo root Pythium population by 84% and 100% when the treated waters were from AWS and AWC, respectively. In vitro trials showed that sterilization or membrane filtration (0.2 μm) of treated waters significantly reduced the potential for suppression of P. ultimum , suggesting that microbial activity played an important role. On the other hand, all AW-treated waters had a negative effect on root development of uninoculated young tomato plants. Root dry weights of plants irrigated with treated waters was 56% lower than in control plants, while their shoot:root ratio was two times higher for plants irrigated with treated waters. The inoculated and AWC-treated water treatments also reduced the Fv:Fm ratio of dark-adapted leaves, representing the maximum quantum efficiency of photosystem II. Organic compounds present in treated waters, expressed as total and dissolved organic compounds, may have affected tomato root development.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.454

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 head0.007
GPT teacher head0.192
Teacher spread0.184 · 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