Abstract
The objective of the present study is to obtain fundamental knowledge to monitor remotely the physiological-ecological status of crops in fields (Figs 1, 2). In this paper the relationships between transpiration rate, stomatal resistance, canopy temperature, vapor pressure deficit (VPD) and photosynthetically active radiation (PAR) were investigated. A model for estimating transpiration, which was constructed using the heat balance equations, was also examined. 1. The transpiration rate had close positive correlations with the canopy temperature, VPD and PAR, although the coefficients were not significant in some cases (Table 1). 2. The stomatal diffusion resistance was closely correlated to the canopy temperature and PAR by negative coefficients and slightly correlated to the VPD. The PAR had a relatively larger negative influence on the stomatal resistance than the canopy temperature (Table 1). 3. The transpiration rate was estimated by a multi-regression equation of the canopy temperature, VPD and PAR with a coefficient of 0.84. The stomatal resistance was also estimated by a multi-regression equation of the canopy temperature and PAR with a coefficient of 0.73. These regression coefficients were relatively small, indicating that the relationship between some factors were non-linear, and that factors such as windspeed may have influenced the results (Eq. 1, 2). 4. Although those relationships described above were qualitatively ascertained, correlation coefficients obtained were not high (0.6∼0.8) enough to be used for the monitoring. 5. A model for estimating transpiration was presented, which was constructed of heat balance equations with a single leaf (Eq. 3∼7). The estimated transpiration rate calculated by substituting remotely sensed data into the model was closely correlated to the transpiration measured by means of a steady state porometer (Fig. 3, r=0.95**). As a result, the possibility was suggested to be able to estimate remotely and in real time the transpiration rate of field crops by means of the multi-sensing. An estimation model of stomatal resistance was also examined for the remote monitoring (Eq. 8∼10).
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