The Effect of Breadfruit (Artocarpus Altilis) Flour on Textural Properties of Comminuted Beef Compared with Other Flour Sources
Notice bibliographique
Résumé
ObjectivesBreadfruit flour as an ingredient in processed meat products has not previously been investigated. The objectives of this study were to investigate the effect of breadfruit (Artocarpus altilis) flour on textural properties of comminuted beef when compared with other flour sources.Materials and MethodsAll flour sources were obtained commercially and were unmodified. Flour sources included breadfruit, corn, soy, tapioca, and wheat. Beef samples originating from one master 15 kg batch of ground beef were comminuted to include 500 g lean beef, 200 g water, and 17.5 g salt. Comminuted beef samples were then prepared with breadfruit flour and other flour sources at varying inclusion levels (0, 1, 2, 3, 4, and 5%). Cooking loss was determined after comminuted beef samples were prepared and cooked to 72°C in a circulating water bath. Texture profile analysis (TPA) was determined using a texture analyzer (TA.XT Plus; Stable Micro Systems Ltd.) with a 30 kg load cell. The prepared and cooked samples were cut into 15 mm diameter and 10 mm thick samples and were compressed twice to 75% of their original height at a cross-head speed of 1.5 mm/s. Data were collected on the following TPA parameters- hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience. The entire experiment (preparation of comminuted beef with flour at differing inclusion levels) was conducted in its entirety 3 times for each treatment. Statistical analyses were conducted using the MIXED procedure of SAS (SAS Inst. Inc., Cary, NC) with fixed effects of flour source, inclusion level, and their interaction. LS means were separated using the PDIFF option with a Tukey’s adjustment. The LS means were further separated using polynomial estimate statements to analyze linear and quadratic effects for inclusion level of each flour source.ResultsFlour source, flour inclusion level, and their interaction significantly affected cooking loss (P < 0.05). Cooking loss of comminuted beef prepared with breadfruit flour and the other flour sources decreased at differing rates as the inclusion level increased (Linear P < 0.05). The interaction of flour source and flour inclusion level affected a number of texture profile parameters, namely hardness (P = 0.05) and cohesiveness (P < 0.01). Hardness was at similar values and decreased as inclusion level increased (0 to 5%) for comminuted beef prepared with breadfruit and soy flour; while hardness was at greater values and remained constant or increased as inclusion level increased (0 to 5%) for comminuted beef prepared with corn, wheat, and tapioca flour. Cohesiveness decreased in value as inclusion level increased (0 to 5%) for breadfruit and soy flour; while cohesiveness remained constant or increased as inclusion level increased (0 to 5%) for comminuted beef prepared with corn, wheat, and tapioca flour. Overall, there were significant linear relationships (P < 0.05) as the inclusion of breadfruit flour was increased (0 to 5%) for cooking loss, hardness, cohesiveness, gumminess, chewiness, and resilience.ConclusionThe results indicate that breadfruit is a promising ingredient in comminuted beef products. Greater research is warranted to further examine the effect of breadfruit starch on rheological characteristics and microstructure of emulsified beef products; as well as, determine the most appropriate inclusion level of optimal product formation.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».