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Record W2008148527 · doi:10.4141/cjps09007

Interplant root competition leads to an overcrowding effect in maize

2009· article· en· W2008148527 on OpenAlexvenueno aff
Wenyuan Jiang, Kai Wang, Guosheng Jiang, Qi Wu, Jian Zhang, Shuting Dong, Ping Liu

Bibliographic record

VenueCanadian Journal of Plant Science · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsnot available
Fundersnot available
KeywordsShootCompetition (biology)BiologyAgronomyOvercrowdingHybridPlant ecologyNutrientHorticultureBotany

Abstract

fetched live from OpenAlex

We conducted an experiment with two maize hybrids (Zea mays L.) to examine the effect of interplant root competition on root growth and to evaluate the impact to total plant performance. Two maize hybrids (Jinhai 5 and Denghai 3719) were grown either with no root competition in their own plot (owners) or as individuals sharing twice the space and nutrients (sharers). Plants were sampled every other week after pollination to track changes in root and shoot biomass. The carbohydrate allocation was smaller in the roots of sharers compared with owners at the pro-phase of grain filling and shoot accumulation was slightly accelerated during this period. However, at the lag phase, the accumulation rate in the shoots of individual plants was distinctly lower than in owners, as a result of earlier root senescence. Overall, shoot mass was reduced by 8% in sharers of both hybrids, while they showed a similar root to shoot ratio compared with the owners. Although the “sharing” treatment was confounded by larger soil spaces, the effects of larger soil volume and interplant root competition were different, and demonstrate that interplant root competition has an inhibitory effect on roots. Maize plants displayed an overcrowding effect (or an escape strategy) by allocating more carbohydrate to the shoots at the expense of the roots when faced with interplant root competition.Key words: Overcrowding effect, interplant root competition, maize (zea mays L.), root discrimination

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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
Published2009
Admission routes1
Has abstractyes

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