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Record W3092564081 · doi:10.21273/horttech04677-20

Fall-bearing Year Herbicides and Spring-nonbearing Year Foramsulfuron Applications for Hair Fescue Management in Lowbush Blueberry

2020· article· en· W3092564081 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHortTechnology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsDalhousie University
FundersDalhousie UniversityDepartment of Agriculture, Nova Scotia
KeywordsTuftInflorescenceRandomized block designRosa × damascenaAgronomyPerennial plantHorticultureBiologyBotanyEssential oil

Abstract

fetched live from OpenAlex

Hair fescue ( Festuca filiformis ) is a tuft-forming perennial grass that reduces yields in lowbush blueberry ( Vaccinium angustifolium ) fields. Nonbearing year foramsulfuron applications suppress hair fescue, but there is interest in increasing suppression through foramsulfuron use in conjunction with fall-applied herbicides. The objective of this research was to determine the main and interactive effects of fall-bearing year herbicide applications and spring-nonbearing year foramsulfuron applications on hair fescue. The experiment was a 5 × 2 factorial arrangement of fall-bearing year herbicide (none, terbacil, pronamide, glufosinate, dichlobenil) and spring-nonbearing year foramsulfuron application (0, 35 g·ha −1 ) arranged in a randomized complete block design at lowbush blueberry fields in Portapique and Stewiacke, Nova Scotia, Canada. Spring-nonbearing year foramsulfuron applications did not reduce total tuft density or consistently reduce flowering tuft density, flowering tuft inflorescence number, or flowering tuft seed production. Fall-bearing year pronamide applications reduced hair fescue density for the 2-year production cycle, although additional bearing year density reductions occurred when pronamide was followed by spring-nonbearing year foramsulfuron applications at Stewiacke. Fall-bearing year dichlobenil applications reduced total and flowering tuft density at each site, although reductions in flowering tuft inflorescence number and seed production were most consistent when followed by spring-nonbearing year foramsulfuron applications at Stewiacke. Suppression extended into the bearing year at each site, and dichlobenil should be examined further for hair fescue control. Fall-bearing year glufosinate applications reduced hair fescue total tuft density at each site and flowering tuft density and flowering tuft seed production at Stewiacke. Fall-bearing year glufosinate applications followed by spring-nonbearing year foramsulfuron applications also reduced nonbearing year flowering tuft inflorescence number and bearing year hair fescue seedling density at Stewiacke, indicating that this treatment may reduce hair fescue seedling recruitment at some sites. Fall-bearing year terbacil applications did not suppress hair fescue and are not recommended for hair fescue management in lowbush blueberry.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.186

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 communication0.0000.000
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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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