MétaCan
Menu
Back to cohort
Record W2806236876 · doi:10.5539/jas.v10n7p359

Biofertigation of Forage With Effluents From a Cattle Slaughterhouse Green Line: Impacts on Physical-Chemical Indicators of Soil Quality and on Production Biomass

2018· article· en· W2806236876 on OpenAlexvenueno aff
Joaquim José de Carvalho, José Maria Rodrigues da Luz, Jaqueline Henrique, José Geraldo Delvaux Silva, Raphael Bragança Alves Fernandes, Sheila Souza da Silva Ribeiro, José Expedito Cavalcante da Silva

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsWastewaterEnvironmental scienceEffluentManureLeaching (pedology)Biomass (ecology)IrrigationAgronomyGreen manureFertigationBrachiariaSoil qualityForageEnvironmental engineeringSoil waterBiology

Abstract

fetched live from OpenAlex

Cattle slaughterhouses are potential causes the environmental impacts, as it require a large volume of water in meat processing, generate large effluents amount, and promote the Cerrado deforestation for animal husbandry. Therefore, we aim was carried out to assess the effects of the soil application of a green line wastewater from a cattle slaughterhouse in the Brachiaria brizantha growth. The M1 and M2 managements did not contain wastewater of slaughterhouse. The wastewater from the 3rd stabilization pond (M3 to M5), from reception box (M6 to M8), and manure (M9 and M10) were used in the biofertigation managements. The physical-chemical indicators levels did not show significant differences (p < 0.05) before soil preparation and after managements. However, biofertigation in the Cerrado soil can provide a mitigation of the leaching of fine soil particles and cations. In addition, maximum nitrogen dose of wastewater provided a higher leaf biomass productivity than commercial nitrogen. Thus, the fertigation with wastewater can reduce the use of water bodies to crops irrigation and the incorporation of new areas with native vegetation to the agricultural production systems.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.294

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 studies0.0000.001
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 head0.250
Teacher spread0.239 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicWastewater Treatment and ReuseFrench-language works237,207