为实现智能温室切花玫瑰的高产稳产和高效益生产，聚焦智能温室切花玫瑰产量的驱动因素，以兰州新区现代农业示范园花卉产业基地为例，通过主成分分析法( PCA)，系统分析了 2021年 7月至 2024年 6月期间的生产数据。研究发现，室内平均光照强度、室内平均温度及累计反渗透( OR)水灌水量等因素，对玫瑰产量与品质具有决定性影响。生产总成本、人员配置、室内平均 CO₂浓度及累计施肥量等因素通过优化生产效率、环境稳定性和营养需求，间接促进产量提升；销售单价作为市场影响因素，对产量具有重要影响。主成分分析结果表明，提取的 4个主成分累计方差贡献率达 85.461%，其中室内平均光照强度、室内平均温度及累计 OR水灌水量在第 1主成分中占据主导地位，生产总成本、人员配置等因素在第 2主成分中影响显著，销售单价在第 3主成分中起决定性作用。综合提出了科学调控环境因素、优化间接管理措施、制定合理市场策略及强化数据驱动决策等建议，为智能温室切花玫瑰种植管理提供了理论支撑和实践指导。

To achieve high, stable yield and efficient production of cut rose in smart greenhouses, this study focused on theyield driving factors of cut rose production in smart greenhouses taking the Flower Industry Base of the Modern Agricultural Demon.stration Park in Lanzhou New Area as an example. By employing Principal Component Analysis (PCA) method, production data fromJuly 2021 to June 2024 were systematically analyzed. Results showed that factors such as indoor average light intensity, indoor aver.age temperature, and cumulative OR-water irrigation volume had a decisive impact on rose yield and quality. Factors including totalproduction costs, staffing, indoor average carbon dioxide concentration, and cumulative fertilizer applicationrates indirectly promotedyield improvement by optimizing production efficiency, environmental stability, and nutrient supply. As a market influence factor,sales unit price also had an important influence on yield. The results of PCA indicated that the cumulative variance contribution rate ofthe 4 extracted principal components reached 85.461%. Among them, indoor average light intensity, indoor average temperature, andcumulative OR-water irrigation volume played dominant roles in the first principal component, while factors such as total productioncosts and staffing had significant effects in the second principal component, and sales unit price played a decisive role in the third prin.cipal component. Based on these findings, recommendations were proposed, including scientifically regulating environmental factors,optimizing indirect management measures, formulating reasonable market strategies, and strengthening data-driven decision-making,so as to provide theoretical support and practical guidance for the cultivation and management of cut roses in smart greenhouses.

S685.12；S629