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Record W7106014016 · doi:10.7939/83560

Impact of breeding selection and agronomy on cereal roots

2025· dissertation· en· W7106014016 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarAbiotic componentCropCroppingSelection (genetic algorithm)Randomized block designHordeum vulgarePlant breedingShoot

Abstract

fetched live from OpenAlex

Cereals are an important part of the prairie cropping system. Their production in the Canadian Prairies is hindered by several biotic and abiotic stresses and production challenges. To mitigate crop production challenges and improve yield, breeders have developed cultivars that are adapted to diverse environmental conditions by employing different management practices, such as the application of Plant Growth Regulators (PGRs). However, efforts to mitigate crop production challenges have focused on shoot traits (i.e., aboveground parameters), while studies on root traits are largely unexplored. Roots are crucial for anchorage, water, and nutrient uptake, and play a vital role in regulating plant metabolic and physiological functions. Addressing agronomic challenges from a root’s perspective is important to make crops more resilient to ever-growing problems compounded by climate change. Therefore, two experiments were conducted at the Plant Growth Facility, University of Alberta (UofA), and the Growth Chamber, Biological Science Building, UofA, respectively, to explore (i) the impact of breeding selection over time on root traits and (ii) the effects of PGR application on root traits of barley sown at different seeding rates. In the first experiment, we assessed the impact of breeding selection on the root traits of old versus current barley cultivars and winter wheat genotypes. The experiment was a Randomized Complete Block Design with four replications, repeated twice (blocks), with six barley cultivars (three old and three current cultivars) and four winter wheat genotypes (two old and two current). The old barley cultivar, Bonanza, had significantly higher total root length (TRL) compared to the current popular barley cultivar, AAC Synergy, with which it shares a similar pedigree. All other current barley cultivars (AB Standswell, AB Advantage, and AAC Synergy) sharing a similar pedigree with Bonanza had a significantly lower proportion of their TRL in the small root diameter \n class compared to Bonanza. Current winter wheat genotypes assessed had similar root traits and similar root diameter class distribution, with old winter wheat genotypes sharing a similar pedigree. Therefore, breeding selection conducted in the Canadian Prairies over the last 40 years, together with changes in tillage practices to conservation tillage, decreased TRL in the popular current barley variety, AAC Synergy, and enhanced root fineness in all current barley cultivars. No impact was observed in winter wheat. In the second experiment, we evaluated the effects of PGRs and seeding rates on popular Canadian feed and malting barley cultivars, along with one best-performing old cultivar (Kasota) selected from the first experiment. The study was a split-split-plot experiment with PGR treatments (PGR versus No-PGR/control), three barley seeding rates (1-plant/pot, 2-plants/pot, and 4 plants/pot), and three barley cultivars (AB Cattlelac - feed, Kasota - old, and AAC Synergy- malting barley cultivars) replicated four times; the study was repeated twice (blocks). Moddus (commercial PGR registered in Canada for barley) was sprayed at BBCH 31-32. Plant height, shoot dry weight, and total biomass significantly reduced at all seeding rates with PGR application, while tiller numbers significantly increased when one plant was sown per pot with PGR application. Total root length, total root surface area, root dry weight, root volume, and root shoot ratio significantly increased at all seeding rates with PGR application, while mean root diameter significantly reduced. Specific root length increased significantly with PGR application when one plant was sown per pot, while the other seeding rate showed no significant differences. Higher seeding rate significantly reduced shoots and root parameters in all assessed barley cultivars. There was a significant interaction of PGRs x seeding rates for tiller numbers and specific root length traits. Therefore, as the key finding is that PGR application and seeding rate singly or in combination significantly impacted barley root traits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.185
Teacher spread0.176 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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