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Enregistrement W7025352918

Upgrading of by-products of the seafood industry

2006· dissertation· en· W7025352918 sur OpenAlexaboutno aff

Notice bibliographique

RevueMedia (https://www.suub.uni-bremen.de/) · 2006
Typedissertation
Langueen
DomaineEnergy
ThématiqueAlgal biology and biofuel production
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSpirulina (dietary supplement)Biomass (ecology)Production (economics)Product (mathematics)Food productsFermentation
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The question of how knowledge of certain organisms can be used to upgrade whole product lines lies at the centre of current research. For the purpose of clarification, this process, in-cluding control and assessment of the interactions between process design and properties, was divided into four steps through observation, analysis, and evaluation completed at pre-determined intervals:1.Substance characterisation2.Narrowing of goals3.Product and process conceptualisation4.Application and optimisationPotential sources of the blue pigment phycocyanine were studied within the framework of "substance characterisation". If enough can be extracted at an acceptable price, phycocya-nine can be widely used in organic foods and cosmetics. Phycocyanine can be extracted through the use of Cyanobacteria, whose substitute Spirulina sp. yields more than 3.000 tons of biomass annually and is sold in many health food markets mainly in the U.S., Canada, Japan, and Europe. Products based on Spirulina were analysed based on their concentration of phycocyanine and were compared with Spirulina strains from independent reference stocks. To "narrow the goals", Spirulina products that hadn't been characterised/identified were appropriately classified, and the fermentation behaviour of comparable strains, based on an increased yield of phycocyanine, were studied. This process determined that different cul-tures from the same collection of strains had a higher production potential as those that had been used for biomass production. This could also be further increased by targeted fermenta-tion optimisation. This observation leads to the conclusion that previous production strains were chosen specifically based on their biomass productivity. However, there are more ap-propriate strains from which to extract phycocyanine. So that production isn't bound to cer-tain strains that are easily available, which makes a business vulnerable to competition, a genetic marker was developed with the goal of a "unique selling proposition." This marker allows unknown isolates to be tested for their phycocyanine production potential. Appropri-ate samples could be subjected to fermentation screening and used for production.The phase "product- and process conceptualisation" was further illustrated through a study of the processing of the arctic prawn Pandalus borealis. 10.000 tons of these prawns are fished annually from the seas surrounding the EU. A by-product of this processing is a wastewater which, besides proteins and fats, contains carotinoides, in particular astaxanthin. Astaxanthin has commercial value in the production of aquaculture products, such as farmed salmon or crustaceans, to create the red flesh colouring expected by the consumer. Astaxan-thin is produced by several microorganisms in nature, however it is artificially created through chemical syntheses to standardise aquaculture feed. By implementing flotation methods used by the wastewater treatment industry, the released matter from the processing of the prawns could be separated and dried to a residual moisture of 10%, making it capable of being stored. A vacuum paddle wheel dryer proved particularly useful for the steps of "application and optimisation". The product derived from this process contained 336 mg/kg DW of astaxanthin, which is four times more astaxanthin as is currently used in feed for aquacultures. This product, as well as astaxanthin components, could be combined with fishmeal and plant proteins for fish or crustacean farming, which would be especially rele-vant in farms who are restricted from using synthetic ingredients in their feed.In conclusion, the sensible combination of nature and engineering creates potential upgrad-ing concepts to create valuable products from what would otherwise be waste material. This creates new possibilities even for small businesses, and besides lowering the environmental impact of wastewater, it also raises the (cost effectiveness, efficiency, profitability) of a whole manufacturing process.

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: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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 Opus0,014
Tête enseignante GPT0,237
Écart entre enseignants0,223 · 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'étudeExpérimental (laboratoire)
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
Publié2006
Routes d'admission1
Résumé présentoui

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