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Record W2954282230 · doi:10.5539/jas.v11n11p106

Agro-biochemical Traits of Sugarcane Varieties Grown in the Brazilian Semi Arid Region

2019· article· en· W2954282230 on OpenAlexvenueno aff
Ygor Herinque Leal, Alexandre Tavares da Rocha, Alexandre Campelo de Oliveira, Djalma Euzébio Simões Neto, João Thiago Correia Oliveira, Nathália Bandeira Diniz, Keila Aperecida Moreira, Sérgio Luiz Ferreira‐Silva

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSugarcane Cultivation and Processing
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarBiologyBiomass (ecology)AridAgronomyHorticultureProductivityEcology

Abstract

fetched live from OpenAlex

The objective of this research was to evaluate the productive response associate to biochemical indicators and oxidative enzymes activities involved in the water deficit resistance in eight sugarcane varieties (RB951541, RB931011, RB962962, RB867515, RB763710, RB72454, RB863129, and RB92579) grown in the semi-arid regions of Brazil. Compared to all other varieties, RB763710 was superior in the number of stems m-1, mean height, and stem diameter, production of whole plant fresh biomass and stem. When biochemical responses were obtained, all sugarcane varieties had a statistically similar solubility and maturity, regardless of the specific maturity rate of each cultivar. The increase in soluble carbohydrate levels occurred in the most stress-sensitive varieties and the variety RB763710 had the highest proline content. A lower general correlation was observed between the production of fresh biomass of stalks and the enzymatic activity. Among the varieties, RB763710 had the highest enzymatic activities which possibly provided greater tolerance to water stress due to the ability to maintain the redox state in the leaves of plants under water deficit. The study of the adaptation mechanisms of sugarcane against water deficit has contributed to the development and diffusion of genotypes tolerant to rainfed conditions, thus contributing to increased productivity even under adverse conditions, allowing maintenance and optimization of the production chains of sugarcane in rainfed regions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.226
Teacher spread0.208 · 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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Citations1
Published2019
Admission routes1
Has abstractyes

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