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Record W2072959860 · doi:10.1134/s1021443712020197

Canopy and leaf photosynthetic characteristics and water use efficiency of sweet sorghum under drought stress

2012· article· en· W2072959860 on OpenAlexfundno aff
Tingting Xie, Peixi Su

Bibliographic record

VenueRussian Journal of Plant Physiology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
FundersNational Science Fund for Distinguished Young ScholarsUniversity of British ColumbiaNational Natural Science Foundation of China
KeywordsCanopyWater-use efficiencyPhotosynthesisAgronomyBiomass (ecology)Water contentMoisture stressSorghumYield (engineering)Sweet sorghumIrrigationBiologyHorticultureEnvironmental scienceBotany

Abstract

fetched live from OpenAlex

The objective of this paper was to examine the relationship between Water Use Efficiency (WUE) at the canopy and leaf levels, to determine soil moisture conditions, which can optimize yield, and WUE of sweet sorghum (Sorghum bicolor (Linn.) Moench), thus providing some theoretical foundation for using marginal land effectively and developing production of sweet sorghum. Three levels of soil moisture conditions were established, and photosynthetic characteristics and yield were measured. The canopy apparent photo-synthetic rate (CAP) and leaf photosynthetic rate (P N) were reduced gradually with increased drought stress, and the CAP was lower than the P N under every soil moisture conditions. The P N had a midday depression phenomenon, but the CAP did not exhibit this midday depression phenomenon under severe drought stress. The linear regression relationship of CAP and P N was CAP = 1.5945 + 0.1496 P N. The canopy apparent WUEC and leaf WUEL were the highest under moderate drought stress. The first was 5.3 and 5.8 times higher than the WUEL in mid-July and late August, respectively. The stem fresh biomass yield was 77 tons/ha under moderate drought stress and WUE of aboveground biomass yield (WUEB) was also the highest. Our results showed that moderate drought stress did not result in a significant reduction in biomass yield but increased WUE significantly.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.270

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 head0.008
GPT teacher head0.193
Teacher spread0.185 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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