Frost‐affected lentil (<i>Lens culinaris</i> M.) compositional changes through extrusion: Potential application for the food industry
Notice bibliographique
Résumé
Abstract Background and objectives Lentil ( Lens culinaris M.) is a high value, highly nutritional grain which originated in Middle‐East. More recently lentil has gained favor in Western countries due to the high value in production and the benefits they provide agronomically; however, growing lentil in countries such as Australia, Canada, and the United States is not without its challenges. One is the high probability of damage due to radiant frost either before flowering or during pod‐filling. The effects of which is most noticeable in the appearance of the seed reduce the value and usability of crops. On the other hand, a generation of well informed, health‐conscious, and environmentally concerned consumers has driven the demand for affordable and healthy food alternatives. Such demand has resulted in a growing industry for protein extraction and novel food production. If used for protein extraction or novel food production, the visual appearance of seeds is no longer an important quality trait. Lentil seeds damaged through frost that still retain a high nutritional composition may be the perfect candidate for a low‐cost substrate in novel food production while improving the outcomes for growers and industry alike. Findings This study used as a model extrusion technology to investigate the use of flour derived from Grade 1 (premium quality) and downgraded frost‐damaged lentil and to monitor compositional changes during extrusion. The study concentrated on how total protein, individual carbohydrates, and phenolic acids changed through high‐temperature, high‐pressure extrusion. Overall flours made from composite lentil–wheat flour had significantly higher concentrations of protein and carbohydrates than the base wheat flour. No significant differences were observed for total protein or carbohydrates between Grade 1 and frost‐damaged flours; however, extrusion significantly reduced total protein concentration as well as maltose and glucose concentration but did not alter the concentration of fructose, sucrose, or the raffinose family oligosaccharides (RFOs). As expected, phenolic acids, procyanidin, kaempferol glycoside, and kaempferol trihexoside were detected in lentil–wheat composites but not in wheat. All phenolic acids significantly increased with increasing concentrations of lentil flour in composite; however, their concentration decreased as a result of the extrusion process. Differences in concentrations of procyanidin and kaempferol glycoside were detected between Grade 1 and frost‐affected lentil in both the composite flour and the extrudate. Conclusions The extrusion process has the effect of altering the composition of the raw material. This was evident by a decrease in protein percentage phenolic compounds and to a lesser effect the water‐soluble carbohydrates. No changes in RFOs was observed. The complete loss of glucose and a significant reduction in maltose provide a healthier carbohydrate profile as the carbohydrates are low fermentable sugars. The reduction in phenolic acids a result of extrusion may help to reduce the antinutritional activity particularly in grains where the concentration of phenolic acids is high. This study found that functionality of downgraded lentil is similar to the premium grade, and more expensive raw material. This knowledge may assist in reducing the increasing issue of food waste where often downgraded products are not used in the production of food. Significants and novelty In order to meet world food security needs, it is predicted that global food production will need to increase by at least 70% by 2050. Therefore, the utilization of all possible protein sources including downgraded pulses, such as lentil, will become increasingly more important. Furthermore, due to climate change increasingly more variable weather conditions will result in the production of below optimum grains. Understanding how to best utilize both premium and downgraded grains is a desirable outcome to minimize food waste.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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) | 0,000 | 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 tête enseignante, 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 ».