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Record W4315647764 · doi:10.1139/cjps-2022-0090

Root morphology, growth, and physiology in Begonia (<i>Malus</i> × <i>micromalus</i>) grown in copper hydroxide containers

2023· article· en· W4315647764 on OpenAlexvenueno aff
Yumei Zhou, Ming Yang, Jifeng Deng, Zhijuan Tai, Dongtao Luan, Siyi Zhu, Jingjing Jia, Zhuo Yang, Yuxin Luo, Wen Wu

Bibliographic record

VenueCanadian Journal of Plant Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhosphorusTaprootChemistryHorticultureSowingLateral rootAnimal scienceLimeShootMalusBotanyHydroxideBiology

Abstract

fetched live from OpenAlex

A major concern with container seedlings is root circling and deformation that will affect post-planting performance and stability. To improve root quality, 3-year-old Begonia ( Malus × micromalus) plants were grown in the containers treated on interior surfaces with different concentrations of copper hydroxide (Cu(OH)2) (0, 40, 80, 120, 160, and 200 g L−1) for 1 year. Compared with the standard container control (SC) and carrier asphalt container control (AC), the number of terminal lateral roots and lateral root volume were increased by 21% and 13% at 80 and 120 g L−1 Cu(OH)2 but decreased by 8% and 10% at 200 g L−1 Cu(OH)2. Only 80 g L−1 Cu(OH)2 increased the plant height and root weight, while other concentrations of Cu(OH)2 resulted in the declines. Phosphorus and potassium were improved with lower concentrations of Cu(OH)2 but decreased with 160 and 200 g L−1 Cu(OH)2. No significant difference in the concentrations of soluble protein and sugars in leaves was observed between Cu(OH)2 treatments and the controls. AC decreased nitrogen concentration in leaves by 12% over the SC across the whole growing season and increased taproot diameter by 17%. Our results indicate that 80 g L−1 Cu(OH)2 was the optimum concentration for root pruning and the maintenance of physiological function. Disadvantages in growth and physiology gradually showed up with increased concentrations.

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 score0.013

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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