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Record W2153259580 · doi:10.1080/00103620600822952

Residual Effect of Copper and Zinc from Fertilizers on Plant Concentration, Phytotoxicity, and Crop Yield Response

2006· article· en· W2153259580 on OpenAlexaff
Umesh Gupta, Y. P. Kalra

Bibliographic record

VenueCommunications in Soil Science and Plant Analysis · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceAgriculture and Agri-Food Canada
Fundersnot available
KeywordsPhytotoxicityCopperZincAgronomyYield (engineering)CropCrop yieldResidualChemistryEnvironmental scienceBiologyHorticultureMaterials scienceMathematicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract To avoid toxicity resulting in reduced crop yields and/or phytotoxic symptoms on the foliage, information on the residual effect of micronutrient fertilization after periods of application is desirable. This article includes discussion on the micronutrients copper (Cu) and zinc (Zn), because they are essential and are of concern from plant and animal standpoints. In general, no detrimental effects in yield reduction or phytotoxicity were noted from Cu applications of up to 50 kg Cu ha−1 to barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.). Barley was an exception where 50 kg Cu ha−1 decreased yield by about 12% in the first‐year crop. The Cu levels in plants did not exceed 9 mg kg−1. Studies showed that Zn applications of 50 kg ha−1 for 2 years in succession and the resulting crop tissue Zn levels as high as 105 mg kg−1 did not cause any phytotoxicity in cereals. The results of this study suggest that cereals can tolerate high levels of Cu and Zn.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score0.696

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 studies0.0000.000
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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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 designObservational
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

Citations28
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueCommunications in Soil Science and Plant AnalysisSame topicPlant Micronutrient Interactions and EffectsFrench-language works237,207