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Record W2976345510 · doi:10.5539/jas.v11n17p28

Fatty Acids and Sugars in Lablab Seed Produced in Virginia (A Non-traditional Location)

2019· article· en· W2976345510 on OpenAlexvenueno aff
Harbans L. Bhardwaj, Anwar A. Hamama

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsLablab purpureusDolichosStachyoseRaffinoseLegumeBiologyLinoleic acidSugarForageCropFatty acidSucroseBotanyFood scienceAgronomyHorticultureBiochemistry

Abstract

fetched live from OpenAlex

Lablab [Lablab purpureus (L.) Sweet], a relatively unknown crop in the United States of America, is understood to be adapted to Southern USA. Even though, previous studies conducted in Virginia have indicated that Lablab can be produced in Virginia as a forage crop, composition of lablab seed produced in Virginia is unknown. To alleviate this limitation, seeds of seventeen lablab lines from a replicated field study, that was conducted for two years, were analyzed for concentrations of fatty acids and sugars. Results indicated that genotypes had mostly significant effects on concentrations of fatty acids and sugars. Prominent fatty acids in lablab seeds, grown in Virginia (USA), were linoleic (53.5%), palmitic (15.8%), and linolenic (14.1%). Mean saturated and total unsaturated fatty acids in lablab seeds were 22.2 and 77.6%, respectively. Mean concentrations of sucrose, fructose, and glucose concentrations in lablab seed were 1.45, 0.42, and 0.78 g per 100 g meal. Mean concentrations of total non-nutritive sugars (Raffinose+Stachyose+Verbascose) in lablab seed were 4.96 g per 100 g meal. Correlations between several nutritional quality traits in lablab seed were observed to be significant. A comparison of nutritional quality of lablab seed with literature values of black bean, navy bean, kidney bean, pinto bean, and pea indicated that lablab has potential as a new food legume for United States of America.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.205
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 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".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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