Leaf wetness duration measurements in a citrus canopy

[摘要] Leaf wetness duration (LWD) is a key component of most disease-warning systems which are designed to help growers to determine when to apply control measures to suppress plant diseases. Since LWD is a complex phenomenon due to its spatial and temporal variability, this can affect the performance of such systems. Despite the importance of LWD, it is not usually measured at most standard weather stations because of lack of standard sensor and protocol. This study was carried out to evaluate and characterize the spatial variability of LWD within a citrus canopy and also to evaluate the performance of two commercially available wetness sensors, namely the Campbell Scientific wetness sensor (Model 237) and the Decagon wetness sensor by comparing them with visual observation of water droplets on the leaves. A total of 6 sensors were installed in the upper and lower canopy levels of the citrus canopy to measure LWD at Welgenvallen Experimental Farm of the University of Stellenbosch from 27 July until 30 November 2012. A total of 62 days were visually observed for LWD. Four of the wetness sensors (2 of each type) were mounted at the upper canopy level (top two-thirds), whilst the other two were placed in the lower one-third of the canopy-one on either side. All the sensors were installed at 45o facing South. Other weather parameters such as air temperature, relative humidity, net radiation above the citrus canopy as well as the leaf temperature were measured by a nearby automatic weather station. Visual observation of LWD showed the mean daily LWD in the upper canopy level was significantly (p<0.05) longer, by about 1.7 h, in the upper canopy level than in the lower canopy level. However, no significant differences were noted between the lower eastern and western canopy levels, with a difference of only 24 minutes. When rain was the source of wetness, there was no significant difference between LWD at any of the canopy positions due to penetration of rainfall through canopy to lowest level. The mean daily LWD in the upper canopy was 15.5 h compared to 14.3 and 14.1 h in the lower eastern and western canopy positions. Based on these facts, it can then be concluded that the spatial variability of LWD has to be considered if measurements of LWD are used as inputs to disease-warning system. The linear regression analysis between measured and visually observed LWD showed that the sensors installed in the upper canopy level provided higher accuracy than the sensors placed in the lower canopy level. Although some researchers recommend painting the Campbell sensors, these results showed that even the unpainted Campbell sensors installed in the upper canopy level of a citrus canopy can be used to measure LWD with acceptable accuracy. During dew days, the sensors at the upper canopy level had a MAE of about 1 h compared to more than 2 h for the sensors placed in the lower canopy. An analysis of leaf and air temperature exhibited that in 96% of the nights when dew was observed, dew deposition in the citrus canopy commenced whenever the leaf temperature fell below the ambient dew point temperature. The first occurrence of dew deposition was mostly observed between 19h45 and 22h00, whilst dew dry-off took place more frequently between 8h45 and 10h30. On average, both the visually observed as well as the sensor predicted 'first onset of dew' was more than 30 minutes after the leaf temperature had fallen below the ambient dew point temperature. It then follows that leaf temperature together with the dew point temperature can be used as an indicator for the onset of dew deposition in citrus canopy. A study was also conducted under field conditions to evaluate Newton-Raphson iterative method as an alternative approach in the indirect determination of leaf temperature from meteorological data. Three field experiments were performed at two different sites at Cape Peninsula University of Technology, Bellville Campus near Cape Town, using three different plants. Leaf temperatures predicted from the iteration method were compared with field measurements of leaf temperatures obtained from a Ficus microcarpa (local tree), potted Strelitzia nicolai flowering plant and Agapanthus praecox, another indigenous flowering plant growing at CPUT nursery complex. The strongest relation, characterized by reasonable precision (R2 = 0.89), high accuracy (D = 0.96) and a fairly high value of the confidence index (C = 0.91) was obtained when A. praecox was used, whilst S. nicolai yielded a poorer relationship (R2 = 0.71; D = 0.77; C = 0.64), and F. microcarpa had the worst correlation. Leaf temperature computed by the iteration process showed a tendency of underestimation in all these experiments. LWD can be also predicted from both empirical and physical models. Finally, a study was also undertaken with the objective to compare the performance of a physical model (SWEB) and an empirical model (RH) using the weather data for the 62 d of measurement. Both models exhibited a similar trend to that of the sensors, in that the accuracy was higher in the top of the canopy compared to the bottom of the canopy. The result also confirmed that models are poor estimators of LWD at the lower canopy levels. The RH model, however, performed better than the SWEB model with a higher fraction of correct estimates (Fc), correct success index (CSI) and lower false alarm ratio (FAR) when considering all the hours for both levels during wet and rainy events. An analysis of the distribution of the errors showed that whilst the SWEB showed a tendency to overestimate LWD, the converse was true for the RH model. Based on these results, it is concluded that if locally calibrated, the RH model can estimate LWD with acceptable accuracy. Consequently, citrus growers who cannot afford to install wetness sensors may therefore consider the use of RH model as part of their disease-warning system. Nevertheless a site-specific calibration is required prior to the use of the model.

[发布机构] University of the Free State