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Record W7066574456

Identification of genomic regions associated with fall dormancy and winter survival in alfalfa (Medicago sativa) to improve persistency and forage yield for the northern climate

2024· dissertation· en· W7066574456 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.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaDairy Farmers of CanadaUniversity of Saskatchewan
KeywordsForageCultivarDormancyPerennial plantMonocultureYield (engineering)Adaptation (eye)
DOInot available

Abstract

fetched live from OpenAlex

Alfalfa (Medicago sativa L) is foundational to the success of beef, dairy and forage industries in Canada. In Canadian prairie alone, about 2.8 million ha of alfalfa monoculture and alfalfa-based mixtures are cultivated. Understanding the interaction between alfalfa fall dormancy (FD) and winter survival (WS) at a molecular level is crucial for the development of high-yielding winter-hardy alfalfa cultivars with high adaptation to the northern environmental conditions. The objectives of the study were to: 1) investigate the relationship between FD and WS of 27 alfalfa populations with varying FD scores (1 to 10) at Clavet, SK and St-Augustin-de-Desmaures, QC; and 2) conduct a Genome Wide Association Study (GWAS) to identify molecular markers and candidate genes associated with FD and WS. Phenotypic data on fall plant height (FH), spring height (SH), WS, and annual forage biomass were collected from 2019 to 2021. High WS rates (>80%) were observed in alfalfa cultivars with FD = 1-5; 55V48 (FD5), SAR(L)3 (FD4), Peace (FD2), and AC Yellowhead (FD1), at both sites. Importantly, 6010DTF2 (FD6) and CUF(L)3 (FD9) showed good to fair survival rate as well. The correlation between WS and FH was non-significant (r =0.04, P=0.06) at St-Augustin and Clavet (r =-0.07, P=0.1). The GWAS analysis identified 129 SNPs associated FH and SH. Among these, there were six candidate genes, namely SAG39 protease, RICESLEEPER 2 protein, Bax Inhibitor-1, ETHYLENE INSENSITIVE 3-like 3 protein, glutamate-rich WD repeat-containing protein 1, CBBY-like protein with known functions in vital plant processes such as stress responses, cell death, growth regulation, and adaptation to the environmental conditions. Once validated, markers and candidate genes identified in the study could be useful for marker-assisted selection to develop alfalfa cultivars with enhanced winter hardiness and reduced FD in northern 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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.999

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 science0.0010.000
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 head0.008
GPT teacher head0.184
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