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Record W2615062099

PENGARUH PEMBERIAN PUPUK KCl TERHADAP N, P, K TANAH DAN SERAPAN TANAMAN PADA INCEPTISOL UNTUK TANAMAN JAGUNG DI SITU HILIR, CIBUNGBULANG, BOGOR

2017· article· id· W2615062099 on OpenAlexaboutno aff
F Fi’liyah, N Nurjaya, S Syekhfani

Bibliographic record

VenueJurnal Tanah dan Sumberdaya Lahan · 2017
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryCropInceptisolFertilizerYield (engineering)HorticultureUreaAgronomySoil waterBiologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

KCl is an inorganic fertilizer needed by maize plant for photosynthesis processes, vegetative crop growth, improving yield in the forms of flower and fruit. The purpose in this study was to understand the effect of KCl on soil N, P, and K, and nutrient uptake by maize plant.  Treatments tested in this study were P0 = control; P1 = KCl 100 (from Canada); P2 = KCl 25 (froml Rusia); P3 = KCl 50 (from Rusia); P4 = KCl 75 (from Rusia); P5 = KCl 100 (from Rusia); P6 = KCl 125 (from Rusia); P7 = KCl 150 (from Rusia). Each treatment was supplied with Urea 350 kg ha -1 and SP-36 250 kg ha -1 as basal fertilizers. Results of this study showed that that application of different doses of KCl fertilizer significantly affected maize yield as well as N, P, and K uptake by maize. The highest dry seed yield of 6.97 t ha -1 was observed for the P5 treatment. The highest N uptake of 34.68 kg ha -1 was observed for the P1 treatment, the highest P uptake of 8.58 kg ha -1 was on the P7 treatment, and the highest K uptake of 23.38 kg ha -1 was on the P7 treatment. Application of KCl fertilizer resulted in residual N, K and P that ranging from 0.0769-0.0821%, 64.24-104.44 ppm, and 0.261-0.326%, 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.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0030.002
Open science0.0050.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.240
Teacher spread0.223 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2017
Admission routes1
Has abstractyes

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