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Record W2183116444 · doi:10.4141/cjps2011-089

A potential retardant for lodging resistance in direct seeded rice (<i>Oryza sativa</i> L.)

2012· article· en· W2183116444 on OpenAlexvenueno aff
Uma Rani Sinniah, Sri Wahyuni, Bambang Surya Adji Syahputra, Saikat Gantait

Bibliographic record

VenueCanadian Journal of Plant Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
Fundersnot available
KeywordsPanicleOryza sativaPaclobutrazolPlant stemCultivarAgronomyBiologyYield (engineering)HorticultureMaterials science

Abstract

fetched live from OpenAlex

Sinniah, U. R., Wahyuni, S., Syahputra, B. S. A. and Gantait, S. 2012. A potential retardant for lodging resistance in direct seeded rice ( Oryza sativa L.). Can. J. Plant Sci. 92: 13–18. Yield losses in rice are heavy, particularly when lodging occurs after heading. A major contributing factor towards lodging is the tall phenotypic characteristic of the plant. In rice, application of growth retardant can reduce plant height by means of internode retardation. In this study, paclobutrazol at 50, 100 and 200 ppm was applied as a foliar application at panicle initiation on MR 219 and MR 84 cultivars and its effects on growth, lodging resistance and yield were studied. Foliar-applied growth retardant inhibited plant growth and retarded internode and culm length but increased culm diameter. All treated plants had higher bending resistance compared with the control. A significant positive correlation was observed between increased culm diameter and stem bending resistance (r=0.885). Histological studies showed greater compaction of parenchyma cells with thickening of parenchyma cell walls. Treatments with either 50 or 100 ppm paclobutrazol gave significant retardation of internodes and gave higher stem bending resistance with significant increase in yield.

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)0.002
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 score0.793
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.018
GPT teacher head0.206
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 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

Citations34
Published2012
Admission routes1
Has abstractyes

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