Abstract
CONTEXT: There is a growing interest in sustainable and year-round food production through protected agriculture. Greenhouses play a key role in this transition, but their performance varies significantly with climate conditions and operational strategies. OBJECTIVE: As a result, this study proposes a standardised and practical framework for evaluating greenhouse performance, grounded in a systematic analysis of key performance indicators (KPI). METHODS: A total of 16 key performance indicators (KPI) were identified from the literature and classified into three main categories: thermal, daylighting, and energy. From these, a refined set of 10 KPI was selected based on their applicability, non-redundancy, and relevance for both passive and active greenhouses. These KPI were applied to a case study involving a naturally ventilated, free-standing Gothic arch greenhouse, modelled using the TRNSYS dynamic simulation software. The model was validated using measured data and used to assess greenhouse performance under three distinct Canadian climates: cold (Montréal), very cold (Baie-Comeau), and subarctic (Kuujjuaq). RESULTS AND CONCLUSION: The analysis revealed that while some KPI, such as the average indoor air temperature (T¯ai,ND) and daily light integral (DLI), are essential for assessing crop survival, others provided insights into growing potential, operational climate control or the environmental and economic viability of the system. This study introduced two refined indicators for greenhouse cultivation in cold climates: TGSLlimit, which excludes lethal short-term cold events, and OGSL, which combines temperature and daylight to define realistic growing conditions. These demonstrated that combining different classes of KPI enabled more meaningful, comparative assessments of greenhouse suitability, offering practical guidance for optimising crop production and energy use under diverse climates. SIGNIFICANCE: This work contributes to a standardised and practical framework for evaluating greenhouse performance, paving the way for more informed decision-making in controlled environment agriculture.
| Original language | English |
|---|---|
| Article number | 104545 |
| Journal | Agricultural Systems |
| Volume | 231 |
| DOIs | |
| Publication status | Published - Jan 2026 |
!!!Keywords
- Agricultural science
- building performance simulation
- greenhouse energy simulations
- key performance indicators
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