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Record W2922375386 · doi:10.5539/jas.v11n4p549

Implications of Agricultural Gypsum Doses in Physical-Hydric Attributes of a Typic Haplortox and on Root Growth and Soybean Productivity

2019· article· en· W2922375386 on OpenAlexvenueno aff
Francisco de Assis Guedes, Deonir Secco, Luiz Antônio Zanão Júnior, Luciene Kazue Tokura, Marcos Felipe Leal Martins

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsnot available
Fundersnot available
KeywordsGypsumHydraulic conductivityHydric soilBulk densityEnvironmental scienceAgronomyRandomized block designIrrigationPorosityAgricultureProductivitySoil waterSoil scienceChemistryMaterials scienceBiology

Abstract

fetched live from OpenAlex

The response to agricultural gypsum, as a conditioner of the root environment in depth, has been observed for most annual crops. These responses are attributed to the better distribution of roots of the crops in depth in the soil by the reduction of chemical impediments, caused by the exchangeable aluminum and calcium deficiency in these layers, which allows to the plants the use of greater volume of water when they occur summer. In this way, the objective of this study was to evaluate the effects of gypsum doses on physical-hydric attributes, root growth and soybean productivity. The experiment was conducted at the Agronomic Institute of Paraná (IAPAR) in Santa Tereza do Oeste-PR. The soil was classified as Typic Haplortox. Five doses of agricultural gypsum were evaluated: 0; 3; 6; 9 and 12 t ha-1, in outline randomized block design with six repetitions. Soil density, total porosity, macroporosity, microporosity and saturated hydraulic conductivity were evaluated at layers of 0.0-0.1; 0.1-0.2 and 0.2-0.3 m. Soybean productivity and root growth were also evaluated. Data were submitted to regression analysis. The physical attributes soil density, macroporosity and saturated hydraulic conductivity did not differ significantly with the application of the gypsum doses in the 0.0-0.1 and 0.2-0.3 m layers. However, in the 0.1-0.2 m layer, due to pressures imposed by the machines and agricultural implements deforming the soil, there were significant differences in the physical attributes of the density, macroporosity and saturated hydraulic conductivity. There was no significant difference in grain productivity and root growth of soybean.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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