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Stomatal limitation of photosynthesis in winter production of greenhouse tomato plants

2000· article· en· W2037048888 on OpenAlexaff
Olfa Ayari, Guy Samson, Martine Dorais, R. Boulanger, André Gosselin

Bibliographic record

VenuePhysiologia Plantarum · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsAgriculture and Agri-Food CanadaUniversité Laval
Fundersnot available
KeywordsLycopersiconPhotosynthesisStomatal conductanceGreenhousePhotosystem IIBiologyHorticultureBotanyAgronomy

Abstract

fetched live from OpenAlex

In May, greenhouse tomato ( Lycopersicon esculentum Mill.) plants near the end of their winter production cycle were shown to exhibit a diurnal photosynthetic decrease. In order to identify the physiological causes of this decline, we compared in May the photosynthetic characteristics of the fifth youngest leaves from tomato plants of different ages corresponding to a winter production (11‐month‐old plants) and to a spring production (5‐month‐old plants). Although the leaves were developed simultaneously under the same environmental conditions, only the ones from the winter production showed a diurnal decline of the in situ CO 2 assimilation rate (A CO 2 ). This was accompanied by a decline of internal CO 2 and stomatal conductance and by large accumulations of hexoses. When stomatal closure was relieved under saturated CO 2 concentration (5%) using a leaf‐disc electrode system, the fifth leaves of both tomato cultures had similar maximum quantum efficiency of O 2 evolution (Φ max ), light‐saturated rate of O 2 evolution (P max ) and quantum efficiency of photosystem II (PSII) photochemistry (ΔF/F′ m , q P and q N ). We concluded that the diurnal decline of A CO 2 observed in winter tomato production during May originates from a stomatal limitation that is not dependent on environmental conditions but rather related to the developmental stage of the plants.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.359

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 head0.015
GPT teacher head0.203
Teacher spread0.188 · 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

Citations16
Published2000
Admission routes1
Has abstractyes

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