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Record W4313518436 · doi:10.4038/jas.v18i1.10096

Macronutrient Composition, Functional and Textural Properties of Selected Traditional Sweetmeats of Sri Lanka

2023· article· en· W4313518436 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Agricultural Sciences – Sri Lanka · 2023
Typearticle
Languageen
FieldEngineering
TopicFreezing and Crystallization Processes
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsDPPHFood scienceABTSChemistryPolyphenolNutrientComposition (language)Dry matterAntioxidantFerricFood composition dataBotanyBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Purpose: Sri Lankan traditional sweetmeats occupy a special place in regular consumption, festivities and religious offerings. Sweetmeats are popular food items since ancient times, however, their compositional information are limited. The objective of this study is to provide information on macro-nutrients, energy intake, antioxidant potential and bioactive compounds of selected sweetmeats. Research method: Twenty-five sweetmeat prepared with standardized recipes were analyzed for major nutrients using standard analytical methods. Methanol (80%, v/v) extracts of these products were evaluated for antioxidant potential (AP) by Ferric Reducing Antioxidant Potential (FRAP), 2,2-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) scavenging activity and 2,2′-diphenyl-1-picrylhydrazyl radical (DPPH) radical scavenging assays. Findings: Almost all tested sweetmeats were energy-dense foods. Among the deep-fried foods, Beraliya kevum had the highest fat content 28.23±1.06 %. Kos eta aggala (68.05±1.30%) reported the highest carbohydrate content and Unduwalalu had the highest protein content (8.70±0.33%) among all the sweetmeats. The AP of Hal helapa made of rice flour, finger millet flour and Vateria copallifera was significantly (p<0.05) higher compared to all other sweetmeats; 222.44±5.34 mM TEAC/g dry matter by DPPH assay and 240.28±5.62 mM TEAC/g dry matter by ABTS assay. Stable polyphenolic compounds and Maillard reaction products generated during high temperatures of processing may be contributing to high AP. Originality/Value: These findings are useful to enhance the consumer awareness in making food choices based on the major nutrients and antioxidant potential. These data can be used to improve the health-related parameters of traditional sweetmeats by reformulating with healthy ingredients and meeting the health concerns of consumers.

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.

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 score0.661
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.187
Teacher spread0.157 · 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