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Record W1978329109 · doi:10.1080/01904160903391081

PERFORMANCE OF DUALEX IN SPRING WHEAT FOR CROP NITROGEN STATUS ASSESSMENT, YIELD PREDICTION AND ESTIMATION OF SOIL NITRATE CONTENT

2009· article· en· W1978329109 on OpenAlex
Nicolas Tremblay, Zhijie Wang, C. Bélec

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Plant Nutrition · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsNitrogenYield (engineering)Grain yieldCropAgronomyNitrateCrop yieldMathematicsGrowing seasonEnvironmental scienceChemistryBiology

Abstract

fetched live from OpenAlex

Abstract Dualex and SPAD are devices developed for the purpose of testing crop nitrogen (N) status. These instruments were used in a wheat experiment in order to compare their respective performance in assessing leaf nitrogen (N) concentration, response to N topdressing application, soil nitrate (NO3)-N levels and in predicting grain yield. The experiment included different N rates in 2005 and 2006 in the Montérégie region of Quebec, Canada. Dualex readings correlated negatively with SPAD readings, leaf N concentration, soil NO3-N content and wheat grain yield. SPAD alone and the ratio of SPAD to Dualex measurements (Chl/Phen) were linearly related to N application rate but no effect of N application rate was found for individual Dualex parameters. However, both SPAD and Dualex readings were affected by year effects. The Dualex was also capable of indirect evaluation of in-season soil NO3-N accumulation and the prediction of wheat yield, but more so as Chl/Phen. Keywords: SPADDualexnitrogen statussoil NO3-Ngrain yield ACKNOWLEDGMENTS The authors would like to thank Edith Fallon, Marcel Tétreault, Noura Ziadi, Konkordia Enr. Farm, Martel's Farm, the L’Acadie Experimental Farm and the summer student crew. This work was supported by the GAPS program of Agriculture and Agri-Food Canada. Notes ** indicate significance at 1% levels. *** and NS indicate significant effects at 0.1% levels and non-significant, respectively.

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 score0.752
Threshold uncertainty score0.088

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 head0.040
GPT teacher head0.243
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