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Record W1891039566 · doi:10.6000/1927-5129.2015.11.50

Effect of Different Techniques on Germination Efficacy and Antioxidant Capacity of Indigenous Legumes of Pakistan

2015· article· en· W1891039566 on OpenAlexvenueno aff
Dur‐e‐shahwar Sattar, Tahira Mohsin Ali, Abid Hasnain

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
FundersUniversity of Karachi
KeywordsGerminationGallic acidRadicleLegumeHorticultureBiologyFilter paperAntioxidant capacityAntioxidantBotanyAgronomyFood scienceChemistry

Abstract

fetched live from OpenAlex

The present study investigated five different strategies for germination, utilizing distinctive substrata like jute bag, separating funnel, muslin cloth, filter paper and aluminum foil followed by evaluation of percent germination, radicle size, weight gain, total phenols and antioxidant activity of eleven indigenous legumes. The results revealed that jute bag displayed the most elevated percent germination in all legumes (84-96) % with the exception of kabuli chick pea, desi chick pea, garbanzo bean and cow pea which demonstrated improved percent germination when filter paper was utilized as substrata. The longest root length (3.1cm) was seen in cow pea when filter paper was used as substrata. It was additionally observed that jute bag demonstrated the highest increment in total phenolic compounds after germination in soy bean i.e. 6.3 mg gallic acid/gram. Among all germinated legumes, cowpea demonstrated the most elevated amount of total antioxidant activity (98.1%) when either filter paper or separating funnel was utilized. The results revealed that every bean requires optimum sprouting technique/conditions inorder to enhance its antioxidant capacity to maximum extent.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.163

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.264
Teacher spread0.241 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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