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Record W3049168871 · doi:10.5539/jas.v12n9p235

Income Generation of Non-wood Forest Products in an Innovative Integrated Crop-Livestock-Forestry System

2020· article· en· W3049168871 on OpenAlexvenueno aff
Marcos Miranda Toledo, Diego Passo dos Santos, J. M. F. Frazão, Fábio Afonso Mazzei Moura de Assis Figueiredo, Joaquim Bezerra Costa

Bibliographic record

VenueJournal of Agricultural Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão
KeywordsCommercializationAgroforestryLivestockAgricultural scienceProduction (economics)ForestryCropAmazon rainforestPer capitaAgricultureGeographyAgricultural economicsBusinessEnvironmental scienceEconomicsBiology

Abstract

fetched live from OpenAlex

The wide extension area occupied by babassu palm (Atallea speciosa Mart. Ex Spreng) is usually considered as an important obstacle for agricultural activities, such as crop production and pasture maintenance in Brazil. This study aimed to evaluate the non-wood forest product use and income generated in an Integrated Crop-Livestock-Forestry (ICLF) system using babassu palm as the main forestry component in a rural area of Pindaré-Mirim, a municipality of Maranhão state, in the Amazon Eastern Region, Brazil. In order to rise a well-balanced agroforestry system in numerous rural areas of the country, three main questions were addressed in this study: 1) What is the production of babassu fruits in the system? 2) Is the babassu extractivism income economically suitable for traditional communities of women babassu breakers? 3) Which commercialization scenario of NWFP could generate more income? Data on phenology and fruit production, processing of all fruit components, and commercialization of babassu products were collected in two 12-month seasons of palm production (2017/2018 and 2018/2019). The mean fruit production reached 2,345.49 kg ha-1 season-1, resulting in an estimate of income generation ranging from R$ 8,206.96 ha-1 season-1 to R$ 36,628.54 ha-1 season-1, depending on the commercialization scenario. These numbers were compared to the statewide monthly income per household of R$ 605.00 and to the per capita monthly income of 54% of the municipality of less than R$ 499.00. The real field data and the estimates for two seasons of using babassu palm, as the innovative forestry component in ICLF system, demonstrated that babassu NWFP could generate substantial income for the surrounding user communities. Such innovative agricultural system may contribute to change people understanding, diversifying agrarian production, improving the socioeconomic household welfare, and reducing the long-term conflicts between livestock activities and babassu palm existence in Brazil.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.039
GPT teacher head0.237
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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