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Physiological Basis of Successful Breeding Strategies for Maize Grain Yield

2007· article· en· W2062529768 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCrop Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyDry matterAgronomyGermplasmSink (geography)PopulationContext (archaeology)CanopyEcology

Abstract

fetched live from OpenAlex

ABSTRACT During the maize ( Zea mays L.) hybrid era (1939 to present), commercial grain yields have improved nearly sixfold and the genetic component of the improvement has been estimated as approximately 60%. In this paper, we examine physiological factors and successful breeding strategies that underlie the yield improvement. Grain yield is the product of accumulating dry matter and allocating a portion of the total dry matter to the grain. The processes influencing dry matter accumulation are commonly referred to as the “source” components, while the processes influencing allocation of dry matter to the grain are referred to as the “sink” components. On the source side, changes in leaf canopy size and architecture account for only a minor portion of the improvement. The majority of the improvement in source capacity is due to visual and functional “stay‐green.” On the sink side, the improvement is through changes in the relationship between kernel number per plant and plant growth rate during a period bracketing silking. In a breeding context, these improvements have been made (i) in a “closed” germplasm pool stratified into heterotic groups; (ii) through use of a pedigree method of breeding structured to mimic reciprocal recurrent selection and thereby improving both additive and nonadditive genetic effects; and (iii) by a gradual increase in plant population densities during the hybrid era as the constant source of stress during both inbred line development and hybrid commercialization. Functional stay‐green and the sink establishment dynamics still represent opportunities for yield improvements. It is essential that source and sink are kept in balance, and that improvement in one accompanies a simultaneous improvement in the other. One strategy for exploiting these opportunities is to incorporate high plant population density trials into inbred line development programs.

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.

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 score0.843
Threshold uncertainty score0.284

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 studies0.0000.001
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 head0.060
GPT teacher head0.286
Teacher spread0.226 · 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