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Record W7019474630

Genetic variation and genome-environment association of alfalfa (Medicago sativa L.) populations under long-term grazing

2022· dissertation· en· W7019474630 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsGrazingMedicago sativaForageRandomized block designGenetic variationCattle grazingLegumeSubspeciesGenetic diversity
DOInot available

Abstract

fetched live from OpenAlex

Alfalfa (Medicago sativa. L) is the most valuable forage legume for the beef, dairy, and forage industries in Canada with approximately 4 million hectares of alfalfa and alfalfa-grass mixtures in Western Canada. Alfalfa forage production has been limited by low stand persistence due to the negative impacts of environmental factors and continuous grazing. The objectives of this study were: 1) to identify the phenotypic and genetic diversities of alfalfa populations collected from long-term grazing sites across four soil zones of Saskatchewan; 2) to compare genetic structure of the populations from long-term grazing sites to commercial alfalfa cultivars released between 1926 and 1980; 3) to identify the SNP markers linked to morphological traits and nutritive values; and 4) to detect SNP markers associated with environmental factors associated with plant persistence at long-term grazing sites. This study collected alfalfa populations across four soil zones of Saskatchewan representing 14 alfalfa stands with minimum 25 years of grazing history. The seven agro-morphological and three nutritive value traits of the 14 alfalfa populations from long-term grazing were evaluated in a replicated field trial using a nested randomized complete block design (RCBD). The genotyping-by-sequencing (GBS) reads were aligned to the Medicago sativa reference genome and 19,853 high-quality SNPs were generated. The STRUCTURE analysis identified that the alfalfa populations from long-term grazing sites were the hybrid cross from subspecies Medicago sativa subsp. sativa (hereafter M. sativa) and M. falcata. Plants from the Black soil zone produced the highest forage dry matter yield, plant height, and stem number, while the lowest values for these traits were recorded plants from the Brown soil zone. This was because the alfalfa populations from the Black soil zone had maintained more of the M. sativa genome over long-term grazing, while the alfalfa populations from the Brown soil zone maintained more of the M. falcata genome. The genotype-environment association (GEA) identified 70 SNPs for the alfalfa populations with grazing history including summer extreme temperature (22 SNPs), growing season precipitation (15 SNPs), soil nutrient (30 SNPs), and soil pH (3 SNPs). Fifty-three candidate genes were significantly associated with eight environmental factors, which were mainly involved in plant resistances to biotic and abiotic stresses, such as heat, drought, salt and diseases. The genome-wide-association-study (GWAS) analysis identified nine SNPs associated with stem number and nutritive value on the Medicago sativa reference genome. Once validated, these markers and candidate genes identified in the study would be useful for developing markers for marker-assisted selection to improve alfalfa cultivars with enhanced tolerance to long-term grazing and environmental stresses in Western Canada.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.171
Teacher spread0.161 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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