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Record W2077893614 · doi:10.2135/cropsci2004.2095

Heterosis for Leaf CO<sub>2</sub> Exchange Rate during the Grain‐Filling Period in Maize

2004· article· en· W2077893614 on OpenAlexaffabout
Arman Ahmadzadeh, E. A. Lee, M. Tollenaar

Bibliographic record

VenueCrop Science · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsUniversity of Guelph
FundersInternational Maize and Wheat Improvement Center
KeywordsBiologyHeterosisHybridDry matterAgronomyInbred strainPoaceaeGrain yieldMaturity (psychological)Horticulture

Abstract

fetched live from OpenAlex

Heterosis for grain yield in maize ( Zea mays L.) manifests itself through its effects on the components of grain yield, dry matter accumulation at maturity, harvest index, and its effects on physiological processes underlying these components, such as leaf CO 2 exchange rate (CER). The objectives of this study were (i) to quantify the pattern of leaf CER throughout the grain‐filling period in maize hybrids and their parental inbred lines, and (ii) to determine the mode of inheritance of leaf CER during the grain‐filling period. Studies were performed with 12 F 1 hybrids and their seven inbred parents grown hydroponically in the field at the Cambridge Research Station, ON, Canada, in 2002. Data were recorded on leaf CER from silking to maturity, and grain yield, aboveground dry matter, and root dry matter at maturity. Mean leaf CER of hybrids was not different from that of their parental inbred lines at silking. However, significant differences became apparent 2 wk after silking and became increasingly larger as plants advanced toward maturity. In general, leaf CER differed among inbred lines but did not differ among hybrids. Combining ability analysis showed that predominantly additive genetic effects influence the expression of leaf CER late in the season. Finally, the maintenance of leaf CER throughout a plant's life cycle, rather than potential leaf CER, is positively associated with dry matter accumulation during the grain‐filling period and grain 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)0.001
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 score0.612
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.239
Teacher spread0.213 · 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

Citations43
Published2004
Admission routes2
Has abstractyes

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