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Effect of integrated nutrient management on productivity, nutrient uptake and economics of greengram (Vigna radiata L.) in custard apple-based agri-horti system under rainfed condition

2015· article· en· W2232267747 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

VenueCurrent Advances in Agricultural Sciences(An International Journal) · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Science and Fertilization
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsCustard-appleKharif cropVignaNutrient managementVermicompostNutrientStrawAgronomyField experimentManureFertilizerDry matterMathematicsBiologyHorticulture

Abstract

fetched live from OpenAlex

A field experiment was carried out during kharif season of 2010 at Mirzapur (Uttar Pradesh) to determine the effect of inorganic fertilizers and organic manure on growth, yield and nutrient uptake by green gram (Vigna radiata L. cv. HUM-12). Integrated application of 50% RDF + 100% poultry manure (T6) recorded significantly higher dry matter (39.11 g plant-1), seed yield(1002 kg ha-1), straw yield(3102 kg ha-1) and nutrient uptake in grain (28.13, 3.72 and 10.06 NPK kg ha-1, respectively) of greengram, consequently resulted maximum gross return (75110 ha-1), net return (59263 ha-1) and benefit: cost ratio (4.56). Thus, combined application of inorganic fertilizer and organic manure was found to be the best for higher productivity and profitability of greengram cultivation in custard apple-based agri-horti system under rainfed condition.

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)0.002
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 score0.795
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.291
Teacher spread0.266 · 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