Using thermography to estimate leaf transpiration rates in cut roses for the development of vase life prediction models

Abstract

While the flower market has traditionally placed emphasis on the external quality (appearance) of cut flowers, the internal quality (longevity) has become increasingly important for retail marketing and consumers. In this study, we investigated key factors affecting the vase life of cut roses via multiple regression analysis (MRA) and examined the use of thermography for estimating the internal quality of flowers. The MRA results show that the vase life of cut roses depends primarily on, and is affected negatively by, transpiration in the dark, as well as high humidity growing conditions. A strong correlation (r 2 = 0.86 in the dark, r 2 = 0.82 in the light) was observed between leaf transpiration rate and leaf temperature differences (estimated with thermography). Finally, we developed vase life prediction models using environmental parameters and phenotypic parameters using either transpiration in the dark (VL-model 1) or leaf temperature difference (VL-model 2). The MRA results indicate that no significant difference exists between the predictive ability of VL-model 1 and VL-model 2. Thus, thermography is an effective technique for estimating leaf transpiration rate and is a practical approach for developing vase life prediction techniques.