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Record W2066846885 · doi:10.4141/cjps07060

Wild blueberry response to phosphorus applied to Prince Edward Island soils

2008· article· en· W2066846885 on OpenAlexvenueaboutno aff
Kevin Sanderson, Leonard J. Eaton

Bibliographic record

VenueCanadian Journal of Plant Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsnot available
Fundersnot available
KeywordsLoamPodzolSoil waterFertilizerPhosphorusAgronomyVacciniumNutrientEnvironmental scienceSoil testChemistryHorticultureBiologySoil scienceEcology

Abstract

fetched live from OpenAlex

Pressure on growers to protect the environment and reduce input costs has increased the need to more effectively use fertilizers. Two experiments were conducted to evaluate the response of wild blueberries to soil-applied P on loamy sand to sandy loam Orthic Podzol soils in Prince Edward Island over three cropping cycles from 1992 to 1997. The sites had soil test (Mehlich-3) P levels from 33 to 44 µg P g -1 , which are rated as L- for blueberries in the PEI Soil and Feed Testing Laboratory Standards. Treatments consisted of soil-applied P at 0, 10, 20, 30 and 40 kg ha -1 applied to the same plots in the sprout year in each of three consecutive cropping cycles. There was a positive linear relationship between application rate of P and extractable soil P and leaf tissue P concentration. Over the 6 yr of the study, soil extractable P increased on average 1.1 µg P g -1 for each kg of soil-applied P compared with the control where no soil P was applied. Increases in levels of tissue P concentration were less dramatic. Plant growth and yields were not affected by rate of soil-applied P fertilizer. This study indicates that on sites with low soil test P, application of soil-applied P did not benefit wild blueberry production. By conserving P fertilizer, growers can also reduce the potential for environmental damage caused by the buildup of soil P. Key words: Phosphorus, soil and leaf nutrient concentrations, wild blueberry, Vaccinium angustifolium Ait., yield

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)0.001
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 score0.923
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.025
GPT teacher head0.229
Teacher spread0.204 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations14
Published2008
Admission routes2
Has abstractyes

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