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Enregistrement W3047216774

Food Chemistry 2018: Mathematical modeling of the chemical and sensory changes within almonds throughout storage- Ozan N Ciftci-University of Nebraska-Lincoln

2021· article· en· W3047216774 sur OpenAlexaboutno aff
Ozan N. Ciftci

Notice bibliographique

RevueJournal of animal research · 2021
Typearticle
Langueen
DomaineNursing
ThématiqueNuts composition and effects
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRoastingFood scienceChemistryLipid oxidationMoistureWater contentEnvironmental scienceCartonContaminationFatty acidPulp and paper industryHorticultureWaste managementAntioxidantBiologyEngineeringOrganic chemistry
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Additional investigations of almond degradation below typical industrial storage circumstances from a quantitative perspective are warranted. This education modelled the effects of packaging, temperature (TEMP), qualified humidity (RH), and boiling on chemical attributes of almonds kept according to common industry practices throughout 16 months. Almonds were assessed bimonthly for oxidation products, free fatty acids, moisture content, and water activity. Results indicated roasting almonds improved quality preservation. Models showed HBB (rather than PPB) to provide benefits to stability comparable to reductions in storage TEMP of ~15 to 30 °C. Roasted examples stayed stored in highA¢Â€Âbarrier bags (HBB) or polypropylene bags (PPB) at numerous mixtures of TEMP and RH. Raw samples were held in unlined cardboard cartons (UC) or PPB under the same conditions. Introduction: Due to their high percentage of unsaturated fatty acids, almonds are prone to oxidation (Sathe et al., 2008). Interior factors such as moisture happy (MC) of the nut, physical features of the nut, fatty acid arrangement, antioxidant content, and external area will also affect the rate of oxidation in almonds (Fennema, 1996; Shahidi & John, 2013). RH, O2 content, TEMP, light exposure, and packaging materials are all controllable factors that may affect the relative rates of oxidation in stored tree nuts. Almonds have been the largest specialty crop export in the United States (USDA, 2013). During storage, the physical and chemical quality of almonds will degrade and eventually result in consumer rejection. Roasting of almonds is also relevant to stability. Roasting of tree nuts is a common thermal process used to create specific flavor notes, darken color and add a more desirable crispy texture (Perren & Escher, 2013). Typically, the MC and a w are reduced while levels of CO2 and product brittleness are increased. Almond kernels have a compartmentalised microstructure that protects against oxidation, and evidence has shown this protective microstructure can be disrupted by roasting. The impact of extrinsic and intrinsic factors involved during storage on the quality of almonds requires further investigation and quantitation. This study aimed to measure the classical primary and secondary lipid oxidation products/markers (i.e., 1° – PV, FFA value, conjugated dienes value; 2° – 2A¢Â€Âthiobarbituric acid reactive substances) of almond degradation, as affected by roasting, packaging and storage conditions. Materials and methods: The effects of environmental storage conditions on raw and roasted almond quality characteristics were investigated with an incomplete factorial design. The combinations of factors were chosen in consultation with the Almond Board of California to be truly representative of storage strategies currently practiced by industry members. Different permutations of the possible factors produced 25 unique samples for assessment (Fig. 1). Raw almonds were divided into fourteen unique sample groups according to combinations of TEMP (n= 3), RH levels (n = 3), and packaging materials (n = 2). Two packaging materials were selected to compare the performance of raw almonds stored in current industry packaging strategies (UC) against more robust packaging strategies. Roasted almonds were divided into eleven unique sample groups according to predetermined combinations of TEMP (n = 3), RH levels (n = 3), and packaging materials (n = 2). Two packaging materials were selected to compare the performance of roasted almonds stored in current industry packaging strategies (sealed N2A¢Â€Âflushed HBB) against less robust packaging strategies (sealed N2A¢Â€Âflushed PPB). Sealed N2A¢Â€Âflushed PPB was used for both raw and roasted almonds to compare the performance of raw and roasted almonds packaged in identical packaging strategies. Roasted almond samples: Nonpareil’, supremeA¢Â€Âgrade, raw almond kernels with brown skins were processed and pasteurized as described above. Almonds were then dryA¢Â€Âroasted for 68 min at 122 °C at the Blue Diamond Growers’ Almond Processing Plant to achieve a light roast. All roasted almonds were pooled and mixed in a single composite sample prior to implementing the storage study. These samples are designated as “roasted” throughout the study. Grinding: FortyA¢Â€Âfive grams of whole almond kernels were ground using a Cuisinart DCGA¢Â€Â12BC (Cuisinart, East Windsor, NJ, USA) mill for 10 s with vigorous shaking. Samples were sorted and passed through a 16A¢Â€Âmesh Tyler standard screen (W.S. Tyler Industry Group, Mentor, OH, USA). This powder is referred to as ground almond powder. Free fatty acid (FFA) values: Free fatty acids were determined using the CPO by a modified procedure according to AOCS Official Method Ca 5aA¢Â€Â40 (AOCS, Urbana, IL, USA). Samples were evaluated in triplicate and reported as an FFA value (mg KOH required to neutralize 1 g of sample), calculated according to the following: FFA=(Ml koh*m*28.2)/(Mass(g)))*1.99 where M is the molarity of the KOH consumed; and mass represents the mass of the oil evaluated. Conclusion: Samples stored at the lowest assessed TEMP (4 °C) exhibited greater stability than those in higher TEMP. Samples stored at 50% RH exhibited greater stability than those stored at 65% RH. Our study found the roasting of almonds to improve product stability when packaged in PPB. Temperature and relative humidity are very important factors to the stability of almonds in storage, with higher TEMP and higher RH both consistently associated with more rapid physicochemical degradation. The choice of packaging will be dictated by economics and the storage conditions to which the almonds are subjected. The predictive models of degradation rates can be used to compare the expected quantitative effects of common industryA¢Â€Âpractice storage factors. It is suggested these predictive models be reviewed when determining appropriate storage strategies for almonds. another positive indicator of primary lipid oxidation, the modeled proliferation rates present less clear patterns regarding the importance of packaging materials. The two samples exhibiting the lowest proliferation rates were the two (raw and roasted) stored in PPB at 4 °C, marginally outperforming the roasted sample in HBB stored under the same TEMP. Acknowledgments: The authors acknowledge the Almond Board of California for its financial contribution to this research and Blue Diamond Almonds for helping to secure the raw and roasted ‘Nonpareil’ almonds necessary to complete this study. Note: This work is partly presented at 3rd International Conference on Food Chemistry & Nutrition May 16-18, 2018 Montreal, Canada.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,039

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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 Opus0,091
Tête enseignante GPT0,351
Écart entre enseignants0,260 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
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
Publié2021
Routes d'admission1
Résumé présentoui

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