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Record W3097907348

Genetic variation for physiological traits affecting drought tolerance among Ontario-adapted commercial soybean [Glycine max (L.) Merr.] varieties grown in 1-m rooting columns

2020· dissertation· en· W3097907348 on OpenAlexaboutno aff
Michael Gebretsadik Gebre

Bibliographic record

VenueThe Atrium (University of Guelph) · 2020
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsnot available
Fundersnot available
KeywordsGlycineBiologyHorticultureDrought toleranceBotanyAgronomyGenetics
DOInot available

Abstract

fetched live from OpenAlex

Drought stress significantly limits soybean production in Ontario. Identification of physiological traits to improve drought tolerance in soybean would benefit from controlled-environment phenotyping methods. It was hypothesized that elite Ontario-adapted soybean varieties would differ for drought tolerance. A greenhouse culture system was developed employing 1-m rooting columns filled with amended field soil, that presents field-like volumetric soil water content and rooting profiles by depth. Different levels of drought stress were simulated in this system by restoring soil water to 100% (control), 75% (mild stress) or 50% (drought stress) of the maximum soil water holding capacity by daily weighing and watering from first flower (R1) until maturity. The effect of applying fertilizer throughout the 1-m soil profile instead of confining it to the upper 30 cm was tested. Distributing fertilizer over the entire 1-m rooting depth resulted in deeper rooting and more soil water extraction at depth at the R1 stage; however, these effects did not persist until maturity and so did not affect drought tolerance. Fifteen Ontario-adapted commercial soybean varieties were compared for their drought tolerance, defined as the ratio of their seed yield under drought conditions compared to control conditions (seed yield ratio; SYR). Similar to the effects of drought in the field, pod number was by far the yield component most affected, with effects on seeds per pod and single-seed weight being relatively minor. Based on their SYR, two drought-sensitive varieties (Saska and OAC Drayton) and three drought-tolerant varieties (OAC Lakeview, OAC Champion, and PRO 2715R) were identified. Principal components analysis showed that drought-tolerant varieties were those that maintained relatively high water use, shoot dry matter, and pod number under stress. Varieties differed for root biomass distribution by depth, but not for soil water extraction profiles, and there was no evidence that differences in drought tolerance were associated with rooting traits among these fifteen varieties. This study helps define the physiological basis of soybean variety differences in drought tolerance, and provides novel phenotyping tools for soybean breeders to select for root function and yield formation traits that could improve soybean yield under drought stress.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score0.987

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 studies0.0010.000
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 head0.022
GPT teacher head0.203
Teacher spread0.181 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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