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Record W4312225116 · doi:10.21273/hortsci16734-22

Prevention of Phytotoxic Effects of Regenerative In Situ Electrochemical Hypochlorination in Recirculating Hydroponic Systems

2022· article· en· W4312225116 on OpenAlexaff
Serge Lévesque, Thomas Graham, Dorin Bejan, Jamie Lawson, Mike Dixon

Bibliographic record

VenueHortScience · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPhytotoxicityLactucaChloramineNitrateAmmoniumFertilizerChemistryNutrientShootBiomass (ecology)HorticultureAgronomyBiology

Abstract

fetched live from OpenAlex

Recirculating nutrient solutions were treated using dimensionally stable anode (DSA)-based regenerative in situ electrochemical hypochlorination (R is E Hc ) in a deep water culture hydroponic lettuce ( Lactuca sativa ) production system. Phytotoxic effects were noted and attributed to the formation of chloramines in treated nutrient solutions containing ammonium. The presence of chloramines resulted in a decrease in overhead biomass by 53% using 2.27 mA/cm 2 and 83% with 4.55 mA/cm 2 . Adding ultraviolet light as a tertiary treatment stage allowed the photodecomposition of chloramines, which prevented phytotoxicity in crops and caused no significant differences in growth between treatments. Furthermore, using a nitrate-based fertilizer also served to prevent phytotoxic effects in crops and showed no significant differences in growth between the control and 4.55 mA/cm 2 . In addition, it was found that the electrochemical flow cell (EFC) treatment resulted in a 13% increase in shoot biomass using 2.27 mA/cm 2 . The study demonstrated that phytotoxic effects can be prevented with the use of regenerative in situ hypochlorination through proper management and monitoring techniques in recirculating hydroponic systems.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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