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Enregistrement W6992633025

Meat-pulse bars: A novel dried meat snack with added pulse flour and its physicochemical, storage, and sensory properties

2023· dissertation· en· W6992633025 sur OpenAlexfundno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueFood Drying and Modeling
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaCollege of Agriculture and Bioresources, University of SaskatchewanStrong
Mots-clésWater activityCitric acidMoistureWater contentPulse (music)Snack foodTap water
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Novel beef-pulse bars with addition of pulse flours were produced in this study. Effects of pulse addition on the physicochemical and sensory properties of meat-pulse bars were evaluated, and functional behaviours of pulse flours were revealed and guidance for consumer preferences toward the products were provided. In Study 1, 12% (w / w) pulse flours were added to beef bars and various treatments were prepared with different pulse flours (black bean, lentil, both infrared (IR) heated), product acidity (pH < 5.0, 5.3) and water activity (Aw < 0.85, 0.90) (regulation standards of being shelf-stable). Processing parameters, physicochemical properties, storage behavior, and sensory properties of the products were evaluated. No significant differences were found in processing parameters between beef-black bean and beef-lentil bars, although beef-black bean bars had a darker color and lower Warner-Bratzler (WB) shear values compared to beef-lentil ones. Higher target water activity (0.90) reduced product drying time and cook loss, but did not affect pH and color. Product acidity increased upon the usage of glucono delta-lactone and encapsulated citric acid (to pH below 5.3), but had no impact on other parameters. Storage at high temperature (HT, 40 ºC) introduced greater decrease in product water activity, moisture content, color parameters, and increase in WB shear values than at room temperature (RT, 20 °C), but relatively stable properties were observed during RT storage. No difference in storage behaviour was observed between beef-black bean and beef-lentil samples, but beef-lentil bars at higher target water activity and hence higher moisture exhibited less changes and more stable properties over storage. Consumer sensory evaluation of the products was performed by young consumers (age 9 – 17) as an in-class activity. They were also asked to complete a survey on their snacking behaviours and altitude toward the products. Hedonic scores of products of all treatments were relatively high (5 out of 6), indicating high consumer acceptance. Consumers from lower age group (9 – 14, n = 72) showed a preference toward less firm texture, and consumers from both groups (9 - 19, n = 95) indicated preference toward moister texture and enhanced flavor. Young consumers agreed that this novel product appeared to be a healthier snack option than those they usually consume, which might help improve the nutrition quality of their diet. Study 2 was a more comprehensive analysis of the effect of different addition levels of lentil flour (0, 6, 12, 18%, w / w). Lentil flour was also subjected to tempering the seeds for 24 h and subsequent IR heating to achieve higher starch gelatinization level. Beef-lentil bars were added with 6%, 12%, and 18% non-tempered (NT), IR heated flour, and 6% and 12% higher-gelatinized (HG), IR heated flour, and a meat-only control. Neither the addition level nor the tempering period, and hence starch gelatinization, of lentil flour showed influence on product cook loss and drying period. Product pH was not changed with addition levels and starch gelatinization of the lentil flour. As the addition level increased, carbohydrate content of meat-lentil bars increased, fat content decreased, but protein content remained constant. During storage, all samples experienced reduced water activity and moisture content, darkening color, increased textural strength, as determined by Warner Bratzler shear and three-point bending tests, and promoted lipid oxidation. Samples with higher addition levels and starch gelatinization of lentil flour demonstrated a firmer and more cohesive texture, potentially contributing to the lesser texture change over storage. Samples with higher addition levels and starch gelatinization of lentil flour displayed a brighter and more yellow color, also associated with lesser change and more stable color over storage. Lentil flour treatment at higher levels (12% and above) was associated with slower lipid oxidation during storage, while differences in starch gelatinization level did not influence lipid oxidation. Meat-lentil bars at high lentil flour addition (18% NT) had the greatest color (more yellow) and texture (dryer) changes. Take-home packages of samples and accompanying scoresheets were provided to consumers (age 19 – 69, n = 47) for tasting at their convenience. Intensity and hedonic scores of all samples were generally acceptable (6 out of 8), with no difference detected for aroma, flavor intensities and overall acceptability among treatments. In conclusion, the meat-pulse bars developed in this work received high consumer acceptance by both young and adult consumers. With both young and adult consumers viewed the meat-pulse bars as a tasty and healthy snacking option, this positive perception could be leveraged in marketing campaigns to promote the consumption of these products.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,858
Score d'incertitude au seuil0,898

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,170
Écart entre enseignants0,149 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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