MétaCan
Menu
Back to cohort
Record W4285137990 · doi:10.5267/j.ccl.2022.6.001

Assessment of the technological quality characters and chemical composition for some Egyptian Faba bean germplasm

2022· article· en· W4285137990 on OpenAlexvenueno aff
Abeer A. Ahmed, Shaaban K. Mohamed, Shaban A. A. Abdel‐Raheem

Bibliographic record

VenueCurrent Chemistry Letters · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGermplasmCultivarComposition (language)HorticultureChemical compositionBiologyTanninAgronomyChemistryBotany

Abstract

fetched live from OpenAlex

Increasing the yield and nutritional value of faba beans is one of the main objectives of the common bean cultivar improvement programs due to its contribution to terminate protein deficiency malnutrition in developing countries and raising the income level of smallholder farmers. In this study, the technological quality of bean seeds from twenty-four genotypes were evaluated (twenty germplasm and four improved cultivars (Misr 1, Giza 429, Giza 716, Giza 843). The results showed a significant diversity in the Egyptian bean germplasm in their quality traits compared to the control cultivars and indicated that the genotypes had a high hydration coefficient that ranged between (98.6-112.4%). While most of the genotypes for cotyledons to hull ratio met the commercial criteria that ranged between (7.41-6.41%). Twenty genotypes had the highest total soluble solids (6.90-11.78%) and were superior to the control cultivars. The seeds chemical composition analysis showed that the genotypes differed in their composition such as protein (26.65 to 30.72 %.), carbohydrate (58.00 to 62.25%), tannin (70.67 to 157.45%), phenols (35.23-51.02 %), and moisture (9.15 to 10.45%).

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 score0.762
Threshold uncertainty score0.189

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.252
Teacher spread0.228 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Chemistry LettersSame topicGenetic and Environmental Crop StudiesFrench-language works237,207