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Record W4386284040 · doi:10.3390/horticulturae9090979

Asparagus (Asparagus officinalis L.) Root Distribution: Cultivar Differences in Mature Plantings

2023· article· en· W4386284040 on OpenAlexaboutno aff
Dan Drost

Bibliographic record

VenueHorticulturae · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
FundersUtah Agricultural Experiment StationUtah State University
KeywordsAsparagusOfficinalisBiologyDry weightHorticultureCultivarBiomass (ecology)BotanyAgronomy

Abstract

fetched live from OpenAlex

Annual plant growth patterns and seasonal conditions have both been shown to influence asparagus (Asparagus officinalis L.) root development over time. Root biomass and distribution changes in mature asparagus cultivars are herein illustrated and described. Asparagus root length density and biomass were estimated from soil cores using a systematic field sampling approach each spring. Soil cores (0.9 m deep) were divided into 0.15 m lengths and fleshy roots collected from the soil. Root length density and dry weights were determined and root distribution maps generated from collected data. As asparagus plantings matured, the sampling year had a significant influence on root development. Fleshy roots grew deeper into the soil each year but the majority of roots of Atlas, Guelph Millennium, and Jersey Giant were found in the upper 60 cm of the soil profile. For the three cultivars evaluated, minor differences in root length and root weight occurred. By Year 6, Atlas showed a decrease in root length and weight when compared to Guelph Millennium and Jersey Giant. While spear yield differences between the varieties were not significant, Atlas tended to produce more very large and large spears compared to Guelph Millennium and Jersey Giant. These results increase our understanding of asparagus 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.

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 score0.271
Threshold uncertainty score0.540

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 head0.026
GPT teacher head0.226
Teacher spread0.201 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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