Quality of Cut Spray Roses Grown in a Seasonal Cultivation Environment of a Smart Farm in Honam, Korea

Abstract

In this study we assessed the quality of cut spray roses grown in a seasonal cultivation environment at a smart farm in the Honam area of Korea. The smart farm consists of a multi-span glass greenhouse that can be monitored in real time through CCTV. This farm is among those that are the first generation of smart farms. In the cultivation environment of the greenhouse the maximum temperature during summer was higher than at other seasons, and the daily light integral was less than the minimum light requirements during the winter. In addition, relative humidity was significantly higher in fall and winter, with a vapor pressure deficit of 0.3 kPa in winter. The change in pH of the nutrient solution was insignificant, but the electronic conductivity was found to be out of the proper range in spring and summer. Morphological characteristics and vase life were investigated for the rose cultivars ‘Egg Tart’, ‘Flash Dance’, ‘Pink Yoyo’, and ‘Super Sensation’, which are widely cultivated at smart farms. Stem length increased for most varieties but stem diameter was smaller, floret number was lower, and the flower diameter was less in winter than in other seasons. The Hunter value L was higher in summer, owing to higher discoloration in summer than in winter. The cultivars ‘Flash Dance’, ‘Pink Yoyo’, and ‘Super Sensation’ exhibited the longest vase life in the fall, and all three cultivars were found to have shorter vase life in winter and summer. Based on these results, we conclude that high temperatures in the summer and low daily light integral and high relative humidity in the winter have negative effects on flower size, petal color, and vase life. Therefore, in order to produce high-quality cut roses, it is necessary to improve the smart farm environment control system. In the smart farm in this study, the complex environment of the ground can be controlled. Once a large enough set of data is analyzed and a decision support system is designed based on the accumulated data, the development of more advanced smart farms will be facilitated.