MétaCan
Menu
Back to cohort
Record W2773582212 · doi:10.5539/jas.v10n1p180

Physicochemical and Microbiological Properties and Humic Substances of Composts Produced with Food Residues

2017· article· en· W2773582212 on OpenAlexvenueno aff
Ana Kaline da Costa Ferreira, Nildo da Silva Dias, Francisco Souto de Sousa, Daianni Ariane da Costa Ferreira, Cleyton dos Santos Fernandes, L. E. F. LUCAS, Kaline Dantas Travassos, Francisco Vaniés da Silva Sá

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCompostManureChemistryFood scienceHumic acidGreen wastePoultry litterEnvironmental chemistryAgronomyFertilizerNutrientBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The consolidation of a wide and effective management system of solid residues, especially biodegradable ones, is one of the great challenges of current society. Composting was evaluated as an option of organic fertilization for soil enrichment, using raw food residues in substitution to bovine manure. The compost piles were built with 30% of biodegradable residues mixed with 70% of ground tree pruning material. The effects of different proportions of food residues (FR) and bovine manure (BM) as source of carbon were tested in 5 treatments (T1 = 15%BM + 15%FR, T2 = 20%BM + 10%FR, T3 = 10%BM + 20%FR, T4 = 30%BM and T5 = control, 30%FR), in randomized blocks, under open field conditions for 90 days. The pH, temperature and moisture content of the compost were measured weekly. The aged compost was evaluated for physicochemical and microbiological properties and carbon contents in the humic substances. The analyses of the results indicated that all studied composts reached the maturation stage with satisfactory contents of humic substances, macronutrients, and micronutrients, indicating that food residues can be used as a source of carbon in compost piles to produce organic fertilizers. The contents of the evaluated chemical contaminants were much lower than those established in the main legislation and current normative instructions and, in terms of contamination by pathogens, there was the absence of total coliforms, thermo tolerant coliforms, and Salmonellas.

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 score0.524
Threshold uncertainty score0.440

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 studies0.0010.001
Scholarly communication0.0000.000
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 head0.039
GPT teacher head0.233
Teacher spread0.194 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicComposting and Vermicomposting TechniquesFrench-language works237,207