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Starch Grain Quinoa (Chenopodium quinoa Willd.): Composition, Morphology and Physico-Chemical Properties

2021· article· en· W3144558817 on OpenAlexaff
Т.Н. Орлова, Mohammed Aïder

Bibliographic record

VenueFood Processing Techniques and Technology · 2021
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsChenopodium quinoaAmylopectinStarchAmyloseSolubilityChemical compositionFood scienceChemistryAgronomyBotanyBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Introduction. The main component of quinoa grain is starch, the properties of which affect the quality of quinoa-based food products. There is no information about quinoa starch in the Russian scientific literature. Therefore, the review summarizes and presents foreign knowledge about the isolation, chemical composition, structure, and physicochemical properties of quinoa starch Study objects and methods. The research featured scientific articles and chapters of scientific books on the structure and chemical composition of quinoa published over the past 10 years. The work used empirical and theoretical methods of scientific research. Results and its discussion. Currently, starch from quinoa grain is produced only under laboratory conditions by various methods of grinding and soaking. Most studies point to up to 10% of amylose in quinoa starch. Amylopectin in quinoa starch has a high number of short single chains and a very low number of long single chains, and their ratio is higher than that in other starches. The granule size of quinoa starch is 0.4–2.0 microns, which is significantly smaller than that of most starches. Quinoa starch belongs to polymorphic type A. The gelatinization temperature and enthalpy of quinoa starch are lower than those of amaranth, corn, sorghum, millet, and wheat starch, which is probably due to the fine structure of amylopectin. With an increase in temperature for every 10°C, the swelling force and solubility of quinoa starch increase on average by 21.5–27%. As the temperature rises from 55 to 65°C, the solubility index of quinoa starch increases sharply by 5–10 times. The viscosity of quinoa starch is significantly higher than that of most known starches. It also is more sensitive to enzymes. Conclusion. The work presents the results of scientific research on various matters: methods of starch isolation from quinoa, its chemical composition, and methods of amylose determination; structure of starch grains, their shape, type, and degree of crystallization; physicochemical properties of starch, including gelatinization, swelling, solubility, rheological properties, retrogradation, changes in the transparency of starch gel, and susceptibility to enzymes. The latter determines the choice of technological parameters in the development of formulations and food technologies, including functional foods for people with gluten intolerance (celiac disease). Further studies of the chemical composition of quinoa can help to meet the growing demand for these products and expand the range of the domestic market for gluten-free foods.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), 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".

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Citations4
Published2021
Admission routes1
Has abstractyes

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