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HARDNESS PHENOMENON IN BEACH PEA (Lethyrus maritimus L.)

2013· article· en· W4239951063 on OpenAlexaff
U.D. Chavan, Ryszard Amarowicz, FEREIDOON SHAHIDI

Bibliographic record

VenueIndonesian Journal of Agricultural Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsField peaStarchGerminationWater contentPea proteinHorticultureAgronomyBiologyBotanyFood scienceChemistryCropEngineering

Abstract

fetched live from OpenAlex

Beach pea is mostly grown on seashores and it contains higher amount of protein than other legumes. However, the pea has several undesirable attributes, such as long cooking time and hard to germinate (imbibitions) that limited its use as food. The present investigation aimed to study the physico-chemical properties, cooking characteristics and hull crude fibre structure of beach pea as compare to other similar legumes. Standard methods of processing pulses were used for present study. Beach pea seeds contained very low grain weight, density, hydration capacity, hydration index, swelling capacity and swelling index than the green pea and field pea. Beach pea had higher amount of crude protein, ash, crude fibre and polyphenols, but lower in starch content than the green pea and field pea. Without any treatment to beach pea seeds the water uptake capacity was very low. Mechanical treatment to beach pea seeds increased<br />the water uptake percentage. The recovery of hull was 3 to 6 times higher in beach pea than that of green pea and field pea. The crude protein content in beach pea hull was 2-5% higher than others. The beach pea hull, dhal and whole seeds were good source of macro- and micro- minerals than that of the other two peas. The electron microscopic structure of beach pea hull crude fibre showed a very close and compact structure than green pea and field pea hull crude fibre structure. Lowering the hardness of beach pea seeds with mechanical or chemical treatments will give more scope for their utilization in the human nutrition.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.227

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 science0.0010.000
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 head0.010
GPT teacher head0.204
Teacher spread0.194 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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