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Record W2340386112 · doi:10.5539/jas.v8n5p122

Effect of Root-Zone Temperature on the Growth and Fruit Quality of Hydroponically Grown Strawberry Plants

2016· article· en· W2340386112 on OpenAlexvenueno aff
Masaru Sakamoto, Mayuka Uenishi, Kengo Miyamoto, Takahiro Suzuki

Bibliographic record

VenueJournal of Agricultural Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsnot available
FundersKindai University
KeywordsDNS root zoneAscorbic acidSugarFragariaHorticultureBiologyBiomass (ecology)InflorescenceHydroponicsBotanyAgronomyFood scienceIrrigation

Abstract

fetched live from OpenAlex

<p>It has been reported that soil temperature modulates the growth and quality of many leafy vegetables and some fruit vegetables; however, this effect has not been sufficiently reported for strawberry plants. Here using a deep flow technique hydroponic system, we investigated the effect of various root-zone temperatures (10 °C, 20 °C, and 30 °C) on the plant growth and fruit quality of strawberry plants grown at an air temperature of 20 °C. The high root-zone temperature treatment (30 °C) decreased oxygen consumption and cell viability of the roots, resulting in withering of most of the plants after 2 months of treatment. In contrast, roots exposed to low temperature (10 °C) showed higher biomass production than those exposed to ambient condition (20 °C), whereas leaf growth was only slightly influenced. The biomass of reproductive organs, such as inflorescences and fruits, were increased in plants treated with a low root-zone temperature, suggesting the activation of reproductive growth by low temperature. However, the contents of ascorbic acid and sugar in fruits were not significantly influenced by the cooling of the root-zone, although the fruit maturation period was significantly prolonged by low temperature. These data indicate that manipulation of root-zone temperature could alter the vegetative and reproductive growth of hydroponically grown strawberry plants.</p>

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.184

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
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 head0.021
GPT teacher head0.278
Teacher spread0.256 · 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

Citations40
Published2016
Admission routes1
Has abstractyes

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