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APROVEITAMENTO ENERGÉTICO DE RESÍDUOS FLORESTAIS COMO ALTERNATIVA AO CONSUMO DE LENHA NA FUMICULTURA DO SUL DO BRASIL

2019· article· pt· W3034258578 on OpenAlexaffabout
Carline Andréa Welter, Jorge Antônio de Farias, Luana Dessbesell, Rafael da Silva Rech, Fábio Eduardo Roesch

Bibliographic record

VenueENERGIA NA AGRICULTURA · 2019
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsLakehead University
Fundersnot available
KeywordsForestryGeographyEnvironmental scienceHumanitiesArt

Abstract

fetched live from OpenAlex

APROVEITAMENTO ENERGÉTICO DE RESÍDUOS FLORESTAIS COMO ALTERNATIVA AO CONSUMO DE LENHA NA FUMICULTURA DO SUL DO BRASIL
 
 CARLINE ANDRÉA WELTER1, JORGE ANTONIO DE FARIAS2, LUANA DESSBESELL3 RAFAEL DA SILVA RECH4, FÁBIO EDUARDO ROESCH5
 
 1 Doutoranda do PPG em Engenharia Florestal – UFSM, Av. Roraima nº 1000, prédio 44B, bairro Camobi, CEP 97105-900, Santa Maria, RS, Brasil. carlinewelter@gmail.com
 2 Professor do Departamento de Ciências Florestais – UFSM, Av. Roraima nº 1000, prédio 44B, bairro Camobi, CEP 97105-900, Santa Maria, RS, Brasil. fariasufsm@gmail.com
 3 PhD Forest Sciences, Natural Resources Management Department- Lakehead University (LU), 955 Oliver Road, Postal Code: P7B 5E1, Thunder Bay, Ontario, Canada. luana.dessbesell@gmail.com
 4 Engenheiro Florestal – UFSM, Av. Roraima nº 1000, prédio 44B, bairro Camobi, CEP 97105-900, Santa Maria, RS, Brasil. raafael.rech@hotmail.com
 5 Japan Tobacco International. Centro de Desenvolvimento Agronômico, Extensão e Treinamento (Adet), Estrada Cerro Alegre Baixo s/n, CEP 96860-000, Santa Cruz do Sul, RS, Brasil. Fabio.Roesch@jti.com
 
 RESUMO: Os objetivos do trabalho foram: caracterizar a fumicultura na região sul do Brasil; verificar o consumo de biomassa na cura do tabaco; verificar a disponibilidade de resíduos do processamento mecânico da madeira como alternativa de fornecimento de biomassa para fins energéticos. O tabaco, mesmo ocupando 18% da área das propriedades, foi responsável por, em média, 53% da renda do produtor na safra 2017/2018. Observou-se um consumo maior de lenha em comparação à serragem, para cada kg de tabaco curado, 2,75 e 2,69 kg, respectivamente. Com relação à disponibilidade de resíduos florestais, foi demonstrado que existe um volume significativo para aproveitamento energético, e ainda ocioso, principalmente os oriundos do processamento de madeira. O uso da serragem em substituição à lenha foi tecnicamente viável e elevaria o nível de comprometimento do setor com a sustentabilidade da atividade fumageira.
 
 Palavras-chave: tabaco, energia de biomassa, agricultura familiar
 
 FOREST RESIDUES ENERGY USE AS AN ALTERNATIVE TO FIREWOOD IN TOBACCO FARMING OF SOUTHERN BRAZIL
 
 ABSTRACT: The objective was to characterize the tobacco culture in the southern states of Brazil also analyze the consumption of biomass in tobacco curing, and access availability of mechanical processing wood residues as an alternative supply of biomass for energy purposes. Tobacco, despite occupying only 18% of the properties area, it accounted for an average 53% of the farmers income in 2017/2018 crop. There was also a higher consumption of firewood compared to sawdust for each kg of cured tobacco, 2.75 and 2.69 kg, respectively. Regarding the forest residues availability, there is a significant amount of forest residues for energy recovery level that still idle, especially those from the wood processing. The sawdust usage to replace firewood was technically practicable and would raise the level of commitment of tobacco sector bringing more sustainability to this activity.
 
 Keywords: tobacco, biomass energy, family farming

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, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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 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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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