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Record W2909872342 · doi:10.5539/jas.v11n2p376

Biometric and Chemical Characterization of Fruits From Selections of Platonia insignis Mart., Native of the State of Maranhão, Brazil

2019· article· en· W2909872342 on OpenAlexvenueno aff
Raudielle Ferreira dos Santos, José Ribamar Gusmão Araújo, Andressa Caroline Neves, Paulo Alexandre Fernandes Rodrigues de Melo, L. P. V. Silva, Wyayran Fernando Sousa Santos, B. M. M. Mendes, Ana Júlia Castor da Rocha, Mariléia Barros Furtado, Mário Luiz Ribeiro Mesquita

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsTitratable acidOrganolepticHorticultureBiologyBrixBotanyFood scienceSugar

Abstract

fetched live from OpenAlex

Brazil has a range of fruit species, especially native ones, which play an important role in the life of local populations, but are still little studied, as is the case of bacuri (Platonia insignis Mart.). P. insignis is a fruit tree species native from Amazon region and has great economic potential, mainly due to its excellent organoleptic and nutritional characteristics. Therefore, there is a need for research that seeks the proper use of the species, as well as the selection of superior genotypes. Thus, the objective of this study was to characterize biometric and chemically fruits of eight selections of native P. insignis plants, from the municipalities of Presidente Juscelino and Santa Rita both located in Lower Munim region, state of Maranhão, Brazil. For the biometric characterization, 20 fruits, individually, were analyzed as to mass, longitudinal diameter, transverse diameter, conformation index, seed number, parthenocarpic segments number, pulp yield and bark mass, and for the chemical characterization, samples composed of six fruits were analyzed as to soluble solids (°Brix), total acidity (% citric acid), soluble solids/acidity ratio and pH. There was significant difference for all characteristics evaluated. High coefficients of variation were observed, indicating variability among the selections and possibility of taking advantage for the genetic improvement. The results allow to indicate the fruits analyzed, both for the industrial market and for the in natura consumption, especially for the ‘Domingão’ and ‘Mamão’ selections.

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 score0.540
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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