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Record W3005889956 · doi:10.1002/agj2.20180

The coordinated increase in stomatal density and vein dimensions during genetic improvement in rice

2020· article· en· W3005889956 on OpenAlexaff
Lilian Wu, Hugo J. de Boer, Zhang Zixiao, Xueliang Chen, Yanying Shi, Shaobing Peng, Fei Wang

Bibliographic record

VenueAgronomy Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsOryza sativaStomatal conductanceBiologyTranspirationPhotosynthesisIdeotypeAgronomyYield (engineering)Stomatal densityHeterosisHorticultureCropBotanyHybrid

Abstract

fetched live from OpenAlex

Abstract Rice ( Oryza sativa L. ssp. indica ) has experienced three distinct phases of considerable yield increases: Green Revolution, utilization of heterosis, and the combination of ideotype and inter‐subspecific hybrid breeding. Crop breeding and selection for high yield have increased radiation use efficiency in modern indica rice varieties. However, the underlying leaf morphological and physiological changes have not been established. Field and pot experiments were conducted in 2016 and 2017. We investigated the relationships between the anatomical maximum stomatal conductance ( g max ), operational stomatal conductance ( g op ), and the anatomy of the stomata and vein in relation to leaf‐level transpiration and photosynthesis across historical indica rice varieties. The results showed that flag leaf temperature of new varieties was reduced relative to the temperature of older varieties due to increased g op and leaf transpirational cooling. Both high stomatal density and larger veins were increased in new varieties with improved yield potential, while no change was observed in stomatal length and vein density. There was a significant correlation between stomatal density and g op as well as between g op and the light‐saturated photosynthetic rate. The present study reveals that historical selection for high yield is accompanied by leaf morphological changes that contribute to enhanced g op , leaf cooling, and photosynthesis of irrigated rice inhabiting hot, high light environments.

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 score0.020
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.171
Teacher spread0.167 · 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

Citations23
Published2020
Admission routes1
Has abstractyes

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