Adaptation of microalgae bioprospected from stressed environments in Northern Ontario for the production of lipids
Notice bibliographique
Résumé
Photosynthetic green microalgae are a promising bio-feedstock that can be used to generate lipids for transesterification into biodiesel and/or various human health products such as polyunsaturated fatty acids. Unfortunately, due to their cultivation requirements, such as high energy requirements and carbon dioxide (CO2) as a carbon source, large-scale biomass production generally remains uneconomical. To address this issue, the use of industrial flue gas as a low-cost source of CO2 and a biorefinery approach to help mend the economic burden of microalgae-based products with an emphasis on creating co-products from lipid-extracted biomass (LEB) are assessed in this thesis. Microalgae’s ability to sequester CO2 through photosynthesis is also advantageous in mitigating harmful industrial emissions. While these flue gases can have high concentrations of CO2, they also can contain numerous contaminants (e.g., heavy metals, particulate matter) that discourage microalgae growth, and therefore their ability to fix CO2. But, the most significant issue can be high nitrous oxide (NOx) and sulphuric dioxide (SO2) concentrations within a flue gas that cause acidification when bubbled through liquid media. It is due to this acidification that finding the productive microalgae species to grow in those systems can be problematic. To address this, bioprospecting acid-tolerant microalgae from low pH environments in active and non-active mining sites was explored and the acidophilic species present identified through DNA sequence analysis. Bioprospected algal species were then grown in acidic conditions similar to those created by bubbling flue gas from a nickel smelter into water (pH 2.5). From this work, it was found that the acid-tolerant green microalgae in the genus Coccomyxa acclimated to the acidic conditions with suitable growth rates (0.136 day-1) and biomass production (25.71 mg L-1day-1). However, anabolic production of target biochemical molecules, such as lipids, is the key step in the bio-product process. It is known that microalgae have the ability to accumulate bioactive compounds when placed in stressed environments, such as high illumination and low nutrient availability, but little is known an about the impact of low pH and in particular the lipid composition of acidophilic microalgae. Research confirmed that the lipid compositions of bioprospected acid-tolerant microalgae was in the target range (13%). However, further work showed that an increased total lipid content (up to 27%), with a desirable rise in the relative level of health beneficial higher polyunsaturated fatty acid, could be achieved by applying dark stress at the end of the exponential growth phase. It is, therefore, proposed that this approach could be an easy, low-cost method to enhance lipid productivity
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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) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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.
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 ».