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Record W1910204347 · doi:10.21273/hortsci.44.3.688

Organic Mulch Impact on Vegetation Dynamics and Productivity of Highbush Blueberry Under Organic Production

2009· article· en· W1910204347 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.

Bibliographic record

VenueHortScience · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsNova Scotia Department of Agriculture
Fundersnot available
KeywordsMulchWeedCompostAgronomyWeed controlNutrientBiologyBiomass (ecology)

Abstract

fetched live from OpenAlex

A 2-year study in Nova Scotia examined the effectiveness of thickly applied organic mulches as a method of weed control in highbush blueberries ( Vaccinium corymbosum L.), and assessed weed and mulch impact on crop growth, leaf nutrient concentration, yield, and quality under organic production management. Mulches, applied in-row at 20-cm depth, included pine needles (PN), manure–sawdust compost (MC), and seafood waste compost (SC). Competition from weeds negatively affected crop growth and productivity, reducing canopy volume (16% to 38%), leaf nitrogen concentration and berry yields (up to 92%), number (up to 91%), and specific weight (up to 21%). Among mulches, PN proved to be the most effective in suppressing weed growth with 55% less and 73% less aboveground weed biomass compared with the control in 2005 and 2006, respectively, although PN productivity effects were much more modest. One year after application, PN lost some efficacy at suppressing weeds but was still superior to both composts. Distribution of weed species was substantially altered by mulch treatment. Both composts prevented some weed emergence (i.e., sheep sorrel), but weed seeds germinating in composts, especially SC, experienced prolific growth likely as a result of available nutrients in composts. No detrimental effects on short-term plant productivity were noted despite high C:N ratios of PN and MC (72:1 and 48:1, respectively). Plant vigor and yield were typically higher for compost mulch treatments, especially in weed-free subplots, and composts provided more complete fertilization reflected in increased leaf tissue elemental (NPK) composition. Fruit soluble solid (sugar) content was found to be significantly lower in PN and MC compared with SC, whereas total phenolic content was unaffected by mulches. Mulch application can improve organic highbush blueberry productivity by improving soil properties, nutrient availability, and weed suppression; however, precautions should be taken to avoid excess nutrient loading and weed seed contamination of mulches.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.257
Teacher spread0.240 · 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