The Canadian Integrated Northern Greenhouse: four-season testing and future opportunities
Notice bibliographique
Résumé
Abstract. Food security has become a prominent issue in northern Canada, and the high cost of transportation is a critical factor that contributes to the inaccessibility of fresh produce. Keeping in mind that many constraints, including environmental, cultural and economic barriers, cause food insecurity in northern Canada, local food production is one proposed solution to the northern food crisis. Initiated at McGill University by the Biomass Production Laboratory, the Canadian Integrative Northern Greenhouse (CING) unit is a completely integrative design that could allow northern Canadian communities to grow their own fresh and nutritious food, year-round. The CING unit is a hybrid between a northern greenhouse and a growth chamber, housed in a shipping container. It was designed to be adaptive, functioning as a typical solar greenhouse when solar light provides considerable heat and light, and as a closed growth chamber during the night and colder, darker winter conditions. Other components, such as a vertical hydroponic growing system, inter-canopy LED lighting, heating and ventilation, as well as a complete automation system, have all been designed specifically to fit the CING unit‘s requirements. The first working CING unit prototype is now functional and full-scale testing is now complete. The main objective of these tests was to compare the dry mass and plant health, as well as environmental and weather data of lettuce grown in the CING unit over 4 consecutive growing cycles to plants grown in a typical glass research greenhouse, tested lasted 3 to 4 weeks. In addition, we wished to demonstrate that even with less energy consumption, growing conditions in the CING unit were comparable to those found in a typical research greenhouse. The secondary experiment concerned the comparison of a biological nutrient solution and an inorganic nutrient solution, in both growth environments. The first cold condition growing 3 weeks test run (December 2018) was performed when temperatures were below freezing point (0 °C) outside the CING. Subsequent tests were completed in Spring and Summer 2018. In cold conditions, lettuce plants grew in the CING, but to a lesser extent than in the research greenhouse, on the average fresh and dry mass basis of the plants grown. In the research greenhouse, both nutrient solution treatments resulted in greater yields than in the CING, but the difference between treatments in the CING was less obvious. In the greenhouse, the inorganic nutrient solution resulted in a greater yield than the biological nutrient solution for every test. The greatest yield obtained in the CING was in March 2019, where the plants grown achieved 72% of the dry weight of the plants grown in the research greenhouse. Being the first prototype of its kind, the CING needs multiple improvements to be a fully functional unit, but efforts are being made to implement a unit in northern Canada, since different northern researchers have expressed interest in hosting such a unit. However, designing a unit that would fit the needs of a community must be done in full communication with future owners and operators of this food production unit. Building a pilot unit in a northern region is the next clear step for this project.
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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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».