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Record W2372765715

The Effects of Fertilizer Application Operation on Physiology and Yield of Wheat

2008· article· en· W2372765715 on OpenAlexvenueno aff
LU Yin-gang

Bibliographic record

VenueSeed · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
Fundersnot available
KeywordsNitrate reductaseDry matterFertilizerYield (engineering)AgronomyNitrogenChlorophyllChemistryNutrientNitrateBiologyMaterials science
DOInot available

Abstract

fetched live from OpenAlex

The test based on high-yield characteristics of wheat cultivation technology,taking Guizi-4 as the tested material,designed different fertilizer application disposing,analysised and compared the effect of fertili- zation on physiological characteristics and yield of wheat,at the premise of N,P,K on consistent ratio in the whole growth period.The result showed that application in a range of 0 -270 kg/hm2 significantly increased dry matter accumulation of wheat,nitrogen accumulation,chlorophyll content,root vigor,leaf nitrate reductase activity and yield.Under applying Nitrogen Fertilizer in the same proportion as base and top-dress fertilizer, and increasing the nitrogen amount from 225 kg/hm~2 to 270 kg/hm~2,the dry matter accumulation and chloro- phyU content will increase,roots vigor and leaf nitrate reductase activity will strengthen,but the nitrogen accu- mulation of a plant and the yield is not obviously different in the same treatment.In this experimental condi- tion,applying 225 kg/hm~2 nitrogen in the jointing stage is the major way to coordinate nutrient supply and time allocation,to regulate and control the contradiction between the yield and physiological regulation of wheat.

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)0.000
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 score0.809
Threshold uncertainty score0.072

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 head0.012
GPT teacher head0.203
Teacher spread0.191 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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