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Record W2943664602 · doi:10.5539/jas.v11n7p29

Growth Response of Four Conilon Coffee Varieties (Coffea canephora Pierre ex A. Froehner) to Different Shading Levels

2019· article· en· W2943664602 on OpenAlexvenueno aff
Bruno dos Passos Assis, Eduardo Gross, Norma Eliane Pereira, Marcelo Schramm Mielke, Gedeon Almeida Gomes Júnior

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsCoffea canephoraShadingBiologyHorticultureCoffea arabicaBotanyCoffeaColonization

Abstract

fetched live from OpenAlex

In order to select a conilon coffee (Coffea canephora Pierre ex A. Froehner) adapted to shade, four varieties (C153, JM2, LB1 and GG) were submitted to four shade levels (0, 30, 50 and 70) with evaluation of plant height, stem diameter, collar diameter, number of plagiotropic branches, number of fruits, root colonization by arbuscular mycorrhizal fungi and leaf anatomy. The experiment was carried out on a completely randomized design, in a 4 × 4 factorial scheme with ten replicates. We used organic compost based on cocoa shells for plant nutrition and cow urine for phytopathogenic fungi control. There was interaction between variety and shade factors for most of coffee characteristics analyzed. In general all coffee characteristics evaluated mainly fruit number and length of fruiting branches, significantly increased with increasing shade. Coffee varieties tested respond differently to the increasing of shade levels and leaf anatomy demonstrated the reduction of mesophyll thickness as the shading increased. The effect of shade levels on fruit yield fit to a positive linear regression for all four coffee varieties tested but the mycorrhizal colonization no presented differences among coffee varieties and shade levels. The varieties C153 and GG presented highlighted anatomical, growth and productive characteristics and can be indicated for shading cultivation, for example on agroforestry systems.

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 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 score0.880
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.026
GPT teacher head0.224
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 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

Citations8
Published2019
Admission routes1
Has abstractyes

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