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Record W2064552463 · doi:10.1071/ar07340

Effects of low temperature on grain filling, amylose content, and activity of starch biosynthesis enzymes in endosperm of basmati rice

2008· article· en· W2064552463 on OpenAlexaff
Nisar Ahmed, Masahiko Maekawa, Ian J. Tetlow

Bibliographic record

VenueAustralian Journal of Agricultural Research · 2008
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEndospermStarch synthaseAmyloseStarchSucrose synthaseFood scienceChemistryRipeningEnzymeOryza sativaGlycogen debranching enzymeBiochemistryBiosynthesisGranule (geology)Glycogen branching enzymeGlycogen phosphorylaseAmylopectinBotanyAgronomyHorticultureSucroseBiologyInvertase

Abstract

fetched live from OpenAlex

The effects of low temperature on amylose contents and activities of key enzymes related to starch biosynthesis in basmati rice (Oryza sativa L.) endosperm were investigated. Low temperature treatment prolonged the grain-filling period from 32 days to 53 days, but had no significant effect on the final grain weight. Results showed that low temperature during grain filling had no significant effect on total starch content but increased the amylose content in the mature endosperm of hulled rice by 21%. The measurable activities of sucrose synthase (SuSy), ADP-glucose pyrophosphorylase (AGPase), starch phosphorylase (SPase), starch branching enzyme (SBE), and soluble starch synthase (SS) in endosperms developed at 12°C were lower than those at 22°C when compared at a similar ripening stage on an endosperm basis, but the activity of granule-bound starch synthase (GBSS) was significantly higher than the corresponding activity in endosperms developing at 22°C. These findings suggest that GBSS might play a crucial role in increasing amylose during low-temperature growth conditions.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.081
GPT teacher head0.317
Teacher spread0.235 · 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

Citations48
Published2008
Admission routes1
Has abstractyes

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