MétaCan
Menu
Back to cohort
Record W2081843439 · doi:10.2135/cropsci2005.06-0126

Yield Structure and Kernel Potential of Winter Wheat on the Canadian Prairies

2006· article· en· W2081843439 on OpenAlexaffabout
B. L. Duggan, Brian Fowler

Bibliographic record

VenueCrop Science · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCultivarBiologyYield (engineering)AgronomyGrowing seasonIrrigationGrain yieldSink (geography)PoaceaeWinter wheatKernel (algebra)HorticultureMathematicsGeography

Abstract

fetched live from OpenAlex

Improvements in agronomic practices and cultivars have allowed for expanded production of winter wheat ( Triticum aestivum L.) on the Canadian prairies. In this study, yield and yield components were measured in dry land and irrigation trials to identify the factors determining yield potential and sample uniformity. Although genotype × environment interactions were important contributors to variation in the yield determining factors, genotype and position of the kernel in the spike had the major influence on kernel weight. Large differences in kernels spikelet −1 and kernel weight indicated that these two variables were responsible for yield adjustments to stress during the spikelet and kernel development phase. Kernels from the lower and middle section of the spike and the proximal (A and B) floret positions were heavier than those from the upper spike section and the distal (C and D) floret positions. Artificially reducing spikelet numbers increased weight of the remaining kernels but only under dry land conditions. Weight of kernels in the C position was increased 22% when ovules of the proximal florets were removed during head initiation. These observations indicate that because growing season moisture availability is extremely variable on the Canadian prairies, an ability to compensate for limitations or excesses in sink size as the season progresses must be bred into cultivars if grain yield is to be maximized. This means that successful genotypes tend to have higher than average values for all yield components rather than one exceptionally high component and uniform seed size is difficult to achieve.

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 score0.898
Threshold uncertainty score0.976

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 studies0.0000.001
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 head0.013
GPT teacher head0.198
Teacher spread0.186 · 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

Citations33
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueCrop ScienceSame topicWheat and Barley Genetics and PathologyFrench-language works237,207