Operational exposure of leaf wetness sensors

Agricultural and Forest Meteorology 126 (2004) 59–72 www.elsevier.com/locate/agrformet

Operational exposure of leaf wetness sensors Paulo C. Sentelhasa,*, Terry J. Gillespieb, Mark L. Gleasonc, Jose´ Eduardo B.A. Monteiroa, Sara T. Hellandc a

Grupo de Agrometeorologia, Departamento de Cieˆncias Exatas, ESALQ, Universidade de Sa˜o Paulo, Caixa Postal 9, 13418-900 Piracicaba, Sa˜o Paulo, Brazil b Agrometeorology Group, Department of Land Resource Science, Ontario Agricultural College, University of Guelph, Guelph, Ont., Canada N1G 2W1 c Department of Plant Pathology, Iowa State University, Ames, IA 50011, USA Accepted 18 May 2004

Abstract Leaf wetness duration (LWD) is a key factor in plant disease occurrence in many phytopathosystems and, consequently, an important variable in disease warning systems. Measurement of LWD is often problematic because of the lack of a standard sensor, and lack of a standard exposure protocol. Accordingly, operational aspects of LWD exposure were evaluated using data from experiments in three different locations: Elora, Ontario, Canada; Ames, IA, USA; and Piracicaba, SP, Brazil. LWD sensors (flat, printed-circuit) were installed at different heights and angles, and above or inside different crops: turfgrass and corn in Elora; turfgrass and muskmelon in Ames; and turfgrass and cotton in Piracicaba. Visual observations of dew onset and dry-off were made for comparison with the different sensor positions. At Elora and Piracicaba, sensors deployed 30 cm above turfgrass and between 158 and 458 to horizontal showed the smallest errors in relation to visual observations of turfgrass wetness, for both dew onset and dry-off. Assuming the sensor at 30 cm and 308 as a reference for LWD measurements over turfgrass it was possible to identify significant differences among the different sensor heights and angles, showing that the position of the sensor had a strong effect on LWD measurements. Sensors at 190 cm measured shorter average LWD – 97 min for Elora and 54 min for Piracicaba – than sensors at 30 cm. No significant difference was observed between the sensors at 30 and 70 cm in both places. In Ames, the average difference in LWD between the sensors at 30 and 150 cm (both deployed at 458) was 33 min. In relation to the angle of deployment, sensors at 08 and 158 measured longer average LWD – 38 min for Elora and 56 min for Piracicaba – than sensors at 308 and 458. LWD measured by sensors near the standard screen height over turfgrass differed considerably from LWD measured by sensors in the canopy, especially during periods with less than 15 h of wetness. In contrast, sensors at 30 cm

* Corresponding author. Present address: Department of Land Resource Science, University of Guelph, Guelph, Ont., Canada N1G 2W1. Tel.: +1 519 824 4110x52206; fax: +1 519 824 5730. E-mail addresses: [email protected], [email protected] (P.C. Sentelhas), [email protected] (T.J. Gillespie), [email protected] (M.L. Gleason), [email protected] (Jose´ Eduardo B.A. Monteiro), [email protected] (S.T. Helland). 0168-1923/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.agrformet.2004.05.009

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over the turfgrass showed potential for use in operational plant disease management systems because they provided much more accurate estimates of crop LWD despite large differences in crop height and structure. # 2004 Elsevier B.V. All rights reserved. Keywords: Leaf wetness duration; Plant disease warning system; Corn; Cotton; Muskmelon

1. Introduction Leaf wetness duration (LWD) is one of the most important agrometeorological parameters influencing plant disease epidemiology. In general, the presence of wetness on plant surfaces provides the free water required by pathogens to germinate and infect foliar tissue. This parameter is used as an input in many disease warning systems (Huber and Gillespie, 1992; Kim et al., 2002) which make use of the fungicide sprays more rational (Gillespie et al., 1993), and allows for risk analysis of a given plant disease when applied in forecast models (Hijmans et al., 2000). LWD is a difficult variable to measure since there is no observation standard, both for sensor and exposure conditions (Magarey, 1999; Madeira et al., 2002). However, the use of LWD sensors may be necessary in some operational systems for plant disease control, where estimations by empirical or physical models are too complex. Such estimations may require meteorological variables that are not widely measured, such as net radiation, and adjustments or calibrations for different climatic conditions and crops (Gillespie and Barr, 1984). There are three types of LWD sensors (Gillespie and Kidd, 1978; Getz, 1991): static leaf wetness instruments, which give only an indication of wet or dry conditions; mechanical leaf wetness instruments, that record changes in sensor length, size or weight caused by wetness; and electronic leaf wetness instruments that promote a change in sensor impedance. Static leaf wetness instruments are those that have no mechanical or electronic parts such as the Duvdevani dew gauge (Getz, 1991). These devices are typically very rudimentary and provide little useful information, since a poor correlation with dew duration in various crops has been documented (Getz, 1991). Mechanical leaf wetness instruments were used intensively for LWD measurements until 1970

(Lomas, 1965; Lomas and Shashoua, 1970), and despite their limitations, these sensors have been used in several places recently (Zangvil, 1996). Following some earlier attempts to measure LWD by changes in electrical resistance, Davis and Hughes (1970) introduced the idea of treating flat plate electrical grids with gray water-based paint to increase the degree of moisture sensitivity. Concerned about this issue, Gillespie and Kidd (1978) studied mock leaf sensors made from electrical impedance grids using different latex paint colors and confirmed that a very light gray paint resulted in greatest accuracy in sensing initial wetness and dry-off of a crop. Subsequently, several authors developed and/or compared the performance of different types of new electronic LWD sensors (Smith and Gilpatrick, 1980; Weiss and Lukens, 1981; Weiss and Hagen, 1983; Bathakur, 1985; Gillespie and Duan, 1987; Weiss et al., 1988; Armstrong et al., 1993; Wei et al., 1995; Geisler et al., 1996; Miranda et al., 2000). In general, the sensors’ performance was adequate but differences among sensors were detected that depended on the characteristics of each one and on operational aspects of sensor exposure. Gillespie and Duan (1987) developed and tested a cylindrical sensor, trying to simulate crops that have cylindrical leaves, such as onions (Allium cepa L.). It was found that cylinders registered dew onset later and dry-off earlier than flat plates of similar width, so they suggested caution if monitoring LWD for flat leaves with cylindrical sensors. Weiss and Lukens (1981) and Weiss and Hagen (1983) also found differences among electronic LWD sensors of different characteristics. The flat plate style was less effective to measure LWD than a frame with a piece of white cotton cloth on a grid network of fine wires. Site-specific sensors have also been tested (Weiss et al., 1988; Bathakur, 1985; Armstrong et al., 1993; Geisler et al., 1996; Miranda et al., 2000). Despite the apparent advantage of these sensors because they mount directly on a leaf, some operational problems such as contact between the

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wires and the leaf, leaf size, and deterioration of the leaf, have made them less useful for operational measurements. Despite the enormous effort to develop accurate electronic sensors, operational aspects of LWD measurements have not been extensively discussed. As reported by Davis and Hughes (1970), the performance of their electronic system to monitor vegetative wetting depends basically on the correct exposure of the sensor in the field. Some studies have concentrated on operational aspects of LWD monitoring in order to establish the best way to make this measurement. The first attempt to establish a standard to measure LWD was made by Gillespie and Kidd (1978). These authors found that a 208 angle of deployment was the best to measure LWD in an onion crop, using a flat plate with an electrode gap of 1 mm. Later, Wei et al. (1995) developed a similar sensor adapted to measure LWD on fruits inside greenhouses. They concluded that for their sensor, with an electrode gap of 0.25 mm, paint was not required to obtain an accurate match between sensor response and visual observations of leaf wetness. On the other hand, Lau et al. (2000) and Sentelhas et al. (2004) found that latex painting was desirable for LWD commercial flat plate sensors in tomato (Lycopersicum esculentum Mill) and cotton (Gossypium hirsutum L.) fields, respectively. According to these authors, the use of two or three coats of white latex paint, after heat treatment, was enough to reduce the variability among the sensors. Lau et al. (2000) also found that the angle of deployment can significantly affect accuracy and precision of LWD measurements, because of its influence on sensor water holding capacity, but that compass direction of orientation had no significant effect on response to dew onset and dry-off. However, little has been done to investigate various LWD measurement positions under standard conditions over turfgrass in a weather station, and to correlate these measurements with LWD in different crops. Based on the above considerations, it was hypothesized that a suitably exposed sensor at a weather station could provide sufficiently accurate estimates of LWD on nearby crops to be useful for operational disease management schemes. To test this hypothesis the following goals were set:

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(a) Evaluate the effects of different heights and angles of deployment of LWD sensors over turfgrass at a weather station. (b) Compare these data with LWD measured in three different nearby crops: corn (Zea mays L.), cotton (G. hirsutum L.), and muskmelon (Cucumis melo L.).

2. Materials and methods 2.1. Leaf wetness duration sensors Flat, printed-circuit sensors (Model 237, Campbell Scientific, Logan, UT) were used to measure LWD. These sensors consist of a 1-mm-thick circuit board with interlacing gold-plated copper fingers. All the sensors were treated with two or three coats of offwhite latex paint, as suggested by Gillespie and Kidd (1978), Lau et al. (2000) and Sentelhas et al. (2004), to increase the ability of the sensors to detect small amounts of wetness (drops with less than 1 mm diameter). They were tested in a laboratory chamber connected to a dew point generator to evaluate the possible but undesirable influence of relative humidity (RH) on measurements. Initially, as all the sensors began to respond with RH lower than 80%, they were submitted to a heat treatment in an oven (60–70 8C for 12 h) to remove or to deactivate hygroscopic components of the paint. After this treatment the sensors did not respond to high RH in the absence of free water. Only condensation on the sensors should lower the impedance between the fingers, which is measured by a data-logger. The threshold logger reading for the LWD sensor to be considered wet was determined in a laboratory by applying a drop of water of 1 mm diameter on the sensor with a syringe needle and noting the ratio of the measured voltage (Vs) to the excitation voltage (Vx). Each LWD sensor was mounted on a section of PVC or metal tubing (Fig. 1) and installed in the field at several positions as will be described later. 2.2. Field experiments The field experiments were set up in three different locations under different climatic conditions (Table 1). Three sites were used in order to obtain comparisons

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Fig. 1. Painted Campbell Sci. Model 237 leaf wetness sensor mounted on a section of PVC.

between LWD measured at a weather station and LWD in a variety of nearby crops. The use of both northern and southern hemisphere weather stations allowed data to be gathered in both boreal and austral summers. The experiments were not intended to compare between sites, therefore identical protocols were not used at each site. At Elora, Ontario, Canada (438490 N, 808350 W), the LWD sensors were installed over mowed turfgrass (1 ha plot) and just below the top of a corn canopy, about 200 m to the northwest of the turfgrass field, from 28 July to 7 October 2003, totaling 71 days of measurements. Eight sensors were installed over the turfgrass at five heights (30, 70, 110, 150, and 190 cm) and deployed at 308 facing north. In addition, sensors at Table 1 Average climatic conditions during the period of the experiments, in 2003, in Ames, IA, USA, Elora, Ontario, Canada, and Piracicaba, SP, Brazil Place

Ta (8C)

RH (%)

Prec (mm)

Winda (m s1)

Ames, IA, USA Elora, Ontario, Canada Piracicaba, SP, Brazil

20.5 16.0 18.6

75.1 83.1 65.7

197 344 45

3.0 1.8 1.4

Ta: average temperature; RH: average relative humidity; Prec: total rainfall; and Wind: average wind speed. a Wind speed was measured at 2 m in Elora and Piracicaba, and at 3 m in Ames.

30 cm height were deployed facing north at four angles of deployment (08, 158, 308, and 458). In the corn field, the LWD sensor was installed at the height of the upper leaves, with the height of the sensor adjusted every week to follow the plants’ growth and development. At Ames, IA, USA (428010 N, 938460 W), LWD sensors were installed over mowed turfgrass at 30 and 150 cm height and deployed facing north at 458 to horizontal, and just below the top of a muskmelon canopy at the same angle, from 23 July to 7 October 2003, totaling 69 days of measurements. At Piracicaba, SP, Brazil (228420 S, 478300 W), experiments were carried out in two phases. The first phase was conducted in a cotton field from 17 December 2000 to 2 April 2001, totaling 69 days of measurements. In this experiment, six LWD sensors were installed just below the top of the cotton canopy, with the height of the sensors adjusted every week to follow the plants’ growth and development. Another sensor was installed near the edge of the field over bare soil at 170 cm height. In the second phase of the experiment, from 7 July to 24 September 2003, totaling 50 days, LWD measurements were made over mowed turfgrass at five heights (30, 70, 110, 150, and 190 cm), all deployed at 308. Two additional angles of deployment (08 and 458) were also tested at 150 cm height. Based on Lau et al. (2000), all sensors utilized in the experiments were installed facing north. All

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LWD sensors were connected to data-loggers (models CR10, 21X or CR23X, Campbell Scientific, Logan, UT) programmed to measure every 1, 5 or 10 s (depending on the number of sensors). The output measured from the LWD sensors was the percentage of the 1 h time interval in which the sensor was wet. 2.3. Visual observation of dew onset and dry-off Visual observations of dew onset and dry-off on mowed turfgrass were made at Elora and Piracicaba, from near the end of July to 24 September 2003, in order to evaluate the performance of the LWD sensors. A total of seven nights (times given in Table 2) of clear sky and light wind were selected to observe dew onset and 11 mornings (times given in Table 2) were selected to observe dew or rain dry-off in Elora. In Piracicaba, only dew dry-off was observed,

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during 14 mornings (times given in Table 3). Dew onset was not observed in Piracicaba because during the winter, in this region, the condensation starts normally after midnight. The visual observation of dew onset was based on the first appearance of small droplets over the blade of turfgrass leaves and was not confused with guttation or exudation from cut blades. A flashlight was used to detect the presence of condensation by the change in leaf reflectance. Visual observations were made every 15 min, using at least five replications (samples of 10 leaves). For dew dryoff, visual and tactile observations were used with the same sampling replication (Geisler et al., 1996). When the surface was judged ‘‘dry’’ using this technique, at least 80% of the canopy was free of liquid water but there still may have been some moisture lingering in unsampled spots that would evaporate shortly after the observation time. Simultaneously, visual observation

Table 2 Difference between observed dew onset and dry-off and measurement by the flat plate sensors at several heights and angles over mowed turfgrass, at Elora, Ontario, Canada, during the summer of 2003 Day

Timea

Difference = measured  observed (min) Height of the sensor (at 308) (cm)

Dew onset 30 August 5 September 6 September 11 September 12 September 13 September 14 September MAE ME Wetness ending 31 August 4 September 6 September 8 September 9 September 10 September 12 September 13 September 17 September 20 September 24 September MAE ME

Angle of the sensor (at 30 cm) (8)

190

150

110

70

30

0

15

30

45

20:15 19:45 20:15 20:15 20:15 20:15 19:00

30.0 – 30.0 60.0 45.0 60.0 30.0 42.5 22.5

30.0 30.0 0.0 60.0 0.0 60.0 30.0 30.0 12.9

30.0 60.0 0.0 45.0 15.0 60.0 15.0 32.1 6.4

15.0 15.0 15.0 45.0 30.0 75.0 15.0 30.0 8.6

0.0 15.0 15.0 60.0 45.0 15.0 15.0 23.6 15.0

0.0 0.0 15.0 30.0 30.0 60.0 15.0 21.4 17.1

0.0 0.0 15.0 15.0 30.0 75.0 0.0 19.3 19.3

0.0 15.0 15.0 60.0 45.0 15.0 15.0 23.6 15.0

0.0 0.0 15.0 45.0 15.0 60.0 0.0 19.3 6.4

10:15 09:45 10:00 09:30 10:00 10:30 10:00 10:00 10:30 10:00 10:30

45.0 0.0 – 90.0 75.0 45.0 45.0 45.0 45.0 45.0 30.0 46.5 46.5

60.0 45.0 0.0 90.0 75.0 60.0 45.0 45.0 60.0 45.0 30.0 50.4 50.4

30.0 0.0 15.0 60.0 45.0 30.0 45.0 15.0 15.0 45.0 30.0 30.0 27.3

45.0 15.0 30.0 45.0 30.0 15.0 45.0 0.0 15.0 45.0 30.0 25.9 20.4

45.0 0.0 15.0 15.0 30.0 45.0 0.0 30.0 15.0 15.0 15.0 20.4 20.4

45.0 0.0 30.0 30.0 30.0 30.0 30.0 30.0 45.0 30.0 45.0 31.4 31.4

0.0 45.0 30.0 15.0 0.0 30.0 0.0 15.0 30.0 15.0 30.0 19.1 5.4

45.0 0.0 15.0 15.0 30.0 45.0 0.0 30.0 15.0 15.0 15.0 20.4 20.4

15.0 0.0 45.0 30.0 0.0 45.0 15.0 15.0 45.0 30.0 15.0 23.2 20.4

MAE: mean absolute error; ME: mean error. a Time when dew onset or wetness ending was observed visually.

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Table 3 Difference between observed dew dry-off and measurement by the flat plate sensors at several heights and angles over mowed turfgrass, in Piracicaba, SP, Brazil, during the winter of 2003 Day

Timea

Difference = measured  observed (min) Height of the sensor (at 308) (cm)

Dew dry-off 31 July 1 August 7 August 13 August 14 August 27 August 28 August 29 August 3 September 4 September 5 September 17 September 18 September 19 September MAE ME

08:10 08:40 09:20 10:30 08:30 09:30 09:00 08:10 08:45 08:20 08:00 08:00 07:50 08:00

Angle of the sensor (at 150 cm) (8)

190

150

110

70

30

0

15

30

45

20.0 40.0 40.0 30.0 30.0 120.0 240.0 50.0 25.0 0.0 100.0 10.0 20.0 – 55.8 31.2

20.0 20.0 40.0 10.0 50.0 130.0 180.0 40.0 35.0 0.0 100.0 0.0 20.0 – 49.8 25.0

10.0 30.0 10.0 50.0 10.0 – – 150.0 55.0 60.0 20.0 20.0 30.0 90.0 44.6 21.3

10.0 40.0 20.0 0.0 30.0 80.0 110.0 20.0 125.0 70.0 30.0 20.0 30.0 50.0 45.4 6.8

40.0 40.0 20.0 10.0 60.0 80.0 110.0 10.0 5.0 20.0 60.0 30.0 30.0 80.0 42.5 8.2

30.0 40.0 100.0 30.0 110.0 – – – – – – 20.0 30.0 – 51.4 51.4

– – – – – – – – – – – – – – – –

20.0 20.0 40.0 10.0 50.0 130.0 180.0 40.0 35.0 0.0 100.0 0.0 20.0 – 49.8 25.0

20.0 10.0 30.0 40.0 20.0 120.0 180.0 50.0 35.0 10.0 70.0 10.0 10.0 – 46.5 32.7

MAE: mean absolute error; ME: mean error. a Time when dew dry-off was observed visually.

of dew was made in the corn field at Elora. For dew onset and dry-off observations at the corn field, a total of nine nights and 13 mornings (times given in Table 4) were selected. The same procedure used at the turfgrass field to observe dew deposition and evaporation was used in the corn field. 2.4. Variability among the sensors To quantify the magnitude of the variability among LWD sensors, all the nine sensors used in the Elora experiments were installed over the turfgrass field at the same height (30 cm) and angle (308) for 10 days following the turfgrass and corn observations described above. Time of dew onset and dry-off as well as the LWD were analyzed during this period. 2.5. Data analysis At dew onset and dry-off times, visual data from Elora were compared with data from the sensors. The difference between observed and measured data was calculated and then the mean error (ME), which describes the direction of the error bias, and mean

absolute error (MAE), which indicate the magnitude of the average error, were determined for each of the nine sensors; eight at different heights and angles over the turfgrass and one in the corn field. Elora data from the 10-day period with all LWD sensors at the same position were then evaluated in order to determine the magnitude of the variability among them. Coefficient of variation (%CV), mean (MD), and mean absolute differences (MAD), in relation to the overall LWD average, were determined and the results were considered when the average LWD values of the sensors at different positions were compared, as will be described. For the experiments in Ames and Piracicaba, the comparison with all sensors at the same height was not available. However, all the sensors used the same procedure of painting and heat treatment, so the variability among sensors at Elora should also be an indication of expected sensor variability at the other two sites. The second step was to evaluate the effect of the different heights and angles of the sensors during all periods of LWD measurements. For this purpose, LWD data from Elora, Ames, and Piracicaba were ¯ of LWD. Analysis of used to calculate the averages (X) variance and paired data analysis were conducted to

P.C. Sentelhas et al. / Agricultural and Forest Meteorology 126 (2004) 59–72 Table 4 Difference between observed LWD and measurement by the flat plate sensor at the top of the corn canopy, in Elora, during the summer of 2003 Day Dew onset 27 August 28 August 30 August 5 September 6 September 11 September 12 September 13 September 14 September MAE ME Wetness ending 28 August 29 August 31 August 4 September 6 September 8 September 9 September 10 September 12 September 13 September 17 September 20 September 24 September MAE ME

Timea

Differenceb (min)

20:30 21:00 21:15 19:45 20:15 21:15 20:15 20:00 19:45

15.0 45.0 0.0 15.0 15.0 30.0 30.0 45.0 30.0 25.0 21.7

10:45 12:00 10:30 10:15 10:30 09:30 10:30 11:00 10:15 10:15 10:45 09:45 10:30

0.0 30.0 0.0 15.0 15.0 15.0 15.0 15.0 15.0 0 15.0 0.0 0.0 10.4 5.8

MAE: mean absolute error; ME: mean error. a Time when dew onset or wetness ending was observed visually. b Difference = measured  observed.

compare the LWD averages obtained by the sensors at different heights and angles. Finally, LWD data from the turfgrass field, from the lowest (30 cm) and highest sensors (190 cm for Elora, 150 cm for Ames, and 170 cm for Piracicaba) were correlated, by simple linear regression, with LWD data from the top of corn, cotton, and muskmelon canopies.

3. Results 3.1. Sensor position versus visual LWD measurements in turfgrass In Elora, the height of measurement had a stronger effect on dew onset and dry-off than the angle of

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deployment (Table 2). For sensors angled at 308, the MAE between visual observation on turfgrass and measurements for dew onset decreased from 42.5 min for the sensor at 190 cm to 23.6 min for the sensor at 30 cm. For dew dry-off, this range was even greater, from 46.5 min for the sensor at 190 cm to 20.4 min for the sensor at 30 cm. The same pattern was observed for dew dry-off in Piracicaba (Table 3), where MAE ranged from 55.8 min for the sensor at 190 cm to 42.5 min for the sensor at 30 cm. The tendency of the sensors, except for the one at 70 cm in Elora and Piracicaba and 110 cm in Piracicaba, was to respond to dew onset later (positive ME) and to dew dry-off earlier (negative ME) than the visual observations (Tables 2 and 3). For different angles of deployment of the sensors installed at 30 cm above the turfgrass surface, in Elora, the comparison between visual observation and measurements did not show a clear difference, especially among the sensors at 158, 308, and 458 (Table 2). For dew onset, MAE ranged from 19.3 to 23.6 min, and for dew dry-off MAE ranged from 19.1 to 23.2 min. The sensor deployed at 08 had an MAE similar to the other angles for dew onset but had a consistent early dry-off (MAE = 31.4 min, ME = 31.4 min), which is related to its greater exposure to solar radiation during the morning. In Piracicaba, the sensor at 458 was the one that presented the smallest MAE during dry-off in comparison to sensors deployed at 08 and 308. Differences in MAE among the sensors at different angles were also small, but the differences among ME values showed that the sensor at 08 had a tendency to measure dew dry-off consistently late while sensors at 308 and 458 normally measured dew dry-off between 25 and 33 min early, respectively. This pattern again is related to the exposure to solar radiation during the morning. In Piracicaba (lat = 228420 S), during the winter, the sensors deployed facing north at 308 and 458 received more energy from the sun than the sensor deployed at 08. Just the opposite was observed in Elora (lat = 438490 N), where during the summer the sensor deployed at 08 received more energy than the sensors angled to the north. Considering the results presented above, the sensor installed at 30 cm and angled at 308 over the turfgrass was selected as a convenient reference for comparison with LWD measurements from other sensors during further analyses in this study.

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The performance of the flat plate sensor (308) in the corn field was also evaluated by comparing the measurements with visual dew observations (Table 4). The differences between the dew onset and dry-off measured by the sensor and observed visually were similar to those obtained with the sensors at the turfgrass field, with MAE of 25.0 and 10.4 min, respectively. In this case, however, the ME showed a nearly consistent tendency of earlier evening dew detection by the sensor than observed visually on corn leaves and a weaker tendency of earlier dew evaporation from the sensor in the morning. These results are similar to 15– 30 min differences between sensor and visual observations data obtained by Pedro (1980) for corn and soybean leaves, and by Lau et al. (2000), for tomato leaflets, confirming the good capability of the flat plate sensor for measuring LWD in the corn.

3.2. Variability among the LWD sensors Fig. 2 presents the variability among the sensors in terms of the absolute and relative differences between each sensor and the average of all of them, for dew onset and dry-off. The mean absolute difference for dew onset was 7 min and for dew dry-off was 15 min. The %CV for LWD was 2.35% (Fig. 3), or approximately 22 min for the average daily measured LWD of 15.93 h. According to Pedro (1980) and Magarey (1999), differences of 15–30 min between visual observations and the measurements are not significant for operational purposes, relative to the errors inherent in measurement and observation due to the spatial variability of wetness occurrence. This variability among the sensors was used to interpret the height and angle data measured for longer periods, consider-

Fig. 2. Variability among the LWD flat plate sensors when all of them were installed at the same height (30 cm) and angle (308). The X-axis labels indicate the position (height and angle) at which each sensor was used during the measurements – 190: at 190 cm and 308; 150: at 150 cm and 308; 110: at 110 cm and 308; 70: 70 cm and 308; 30: 30 cm and 308; 15G: at 30 cm and 158; 45G: at 30 cm and 458; 0G: at 30 cm and 08; and Corn: in the corn field at height of upper leaves and 308. Solid line represents the average.

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Fig. 3. Daily (bar) and average (solid line) coefficient of variation (%CV) for all sensors installed at the same height (30 cm) and angle (308).

Fig. 4. Average LWD obtained with the flat plate sensors at different heights, deployed at 308, in (a) Elora, (b) Piracicaba, and (c) Ames. Averages followed by the same letter are not significantly different at the 1% probability level.

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Sensors at 190 cm measured shorter average LWD – 97 min for Elora and 54 min for Piracicaba – than sensors at 30 cm. No significant difference was observed between the sensors at 30 and 70 cm in both places. On the other hand, differences were observed in Elora among the sensors at 110, 150, and 190 cm, while in Piracicaba no significant difference was detected for these sensors, except between 110 and 150 cm (Fig. 4). In Ames, the average difference between the sensors at 30 and 150 cm (both deployed at 458), about 33 min, was significant. In relation to the angle of deployment (Fig. 5), sensors at 08 and 158 measured longer average LWD – 38 min for Elora and 56 min for Piracicaba – than sensors at 308 and 458. Sensors deployed at small angles to the horizontal normally face the sky more than the sensors deployed at greater angles, resulting in a more intensive cooling process and, consequently, greater dew deposition. This position also allows these sensors to store more water during the night, requiring more time during the morning to evaporate the water. In Elora no significant difference was observed between sensors at 308 and 458 (Fig. 5a), but in Piracicaba the difference between these two angles of deployment, about 25 min, was significant (Fig. 5b).

Fig. 5. Average LWD obtained with the flat plate sensors at different angles, deployed at 30 cm, in (a) Elora and (b) Piracicaba. Averages followed by the same letter are not significantly different at the 1% probability level.

ing the differences as negligible when they were less than 22 min. 3.3. Effect of different heights and angles on all LWD measurements Under all conditions of measurement at the turfgrass sites (total of 71 days for Elora, 69 days for Ames, and 50 days for Piracicaba), LWD data obtained at different heights and angles were compared, assuming a sensor deployed at 30 cm and 308 as a reference (Figs. 4 and 5). It was possible to identify statistically significant differences among the different heights and angles of deployment, showing that the position of the sensor has a strong effect on LWD measurements.

3.4. Relationship between LWD measured at the weather station and in three different crops One obvious choice for locating a ‘‘standard’’ measurement of LWD in a weather station would be to position the sensor at the standard screen height used for temperature observations. The linear regression relationships between the LWD data obtained by the sensors at the nearest position to standard screen height over the turfgrass (190 cm for Elora, 150 cm for Ames, and 170 cm for Piracicaba) and those obtained in the top of the corn (240 cm), cotton (100 cm) and muskmelon (20 cm) canopies are presented in Fig. 6. Particularly for corn and cotton, and to a lesser degree for muskmelon, the relationships show a definite correlation between LWD near the standard screen height above the turfgrass and in the crop, despite the differences in crop height, leaf area, and structure. For corn and cotton crops the dispersion of the data (R2corn ¼ 0:83 and R2cotton ¼ 0:92) was less than the dispersion obtained for muskmelon (R2muskmelon ¼ 0:65), probably because of the differ-

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Fig. 6. Relationship between the LWD measured at the top of the crop and at the highest position over mowed turfgrass, in (a) Elora (turfgrass at 190 cm and corn at 240 cm), (b) Piracicaba (turfgrass at 170 cm and cotton at 100 cm), and (c) Ames (turfgrass at 150 cm and muskmelon at 20 cm).

ence between the sensors’ position in the crops – about 20 cm for muskmelon, 100 cm for cotton, and 240 cm for corn – in relation to the turfgrass sensor’s position near screen height. However, all three relationships show the same tendency, with the crops showing greater values of LWD for periods with less than 15 h of wetness. For the periods with LWD > 15 h, caused mainly by rainfall (Fig. 6), less difference was detected between wetness on the crop and near screen height over the turfgrass.

When LWD data from corn and muskmelon were plotted against LWD from the sensor at 30 cm over turfgrass (308 sensor at Elora, 458 sensor at Ames; Fig. 7), the relationships were improved considerably, with slopes and R2 values of 1.03 and 0.93 for corn, and 1.02 and 0.84 for muskmelon. The relationship between LWD caused by both dew and rain in the crop and at 30 cm above the turfgrass field showed little effect of the large differences in plant architecture, leaf size and area, and crop height.

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Fig. 7. Relationship between the LWD measured at the top of the crop and at 30 cm over mowed turfgrass, in (a) Elora (corn at 240 cm) and (b) Ames (muskmelon at 20 cm).

4. Discussion This analysis has shown that the height and angle of exposure of a painted flat plate LWD sensor has a strong effect on the measurements when installed over turfgrass. Comparing the data from the sensors and from visual observations, it was verified that height has much more influence on the measurements than the angle of deployment. Based on this comparison, the sensors installed at 30 cm and deployed at 158, 308 or 458 showed the smallest errors. These results are

similar to Lau et al. (2000) who identified the angle of 458 as the best for LWD measurements in a tomato crop, and Gillespie and Kidd (1978) who also tested different angles of LWD flat plate sensors in an onion crop and concluded that 208 was better than 608. In our case, for the nights and mornings of visual observations, the sensor deployed at 158 measured dew dry-off very accurately (ME = 5.4 min), but showed a consistently early onset (ME = 19.3 min). Considering all measurements, the sensor deployed at 158 showed longer LWD (40–50 min) than the sensors at 308 and 458 (Fig. 5), probably because of its greater exposure to the sky at night. By comparing with the reference sensor at 30 cm and 308 and noting that the variability among all the sensors used for LWD measurement was very small (CV = 2.35%) when they were compared at the same height and angle, it was possible to see clearly the effect of the different sensor positions on LWD measurement. This effect has been reported before for LWD measurements within different crops (Davis and Hughes, 1970; Gillespie and Kidd, 1978; Lau et al., 2000), but this is the first study to document the influence of different heights and angles on the choice of a standard condition for LWD observations in a weather station. From our findings, it was observed that angle of deployment, except 08, is less critical to measure LWD than sensor height, and that there was an inverse relationship between sensor height and LWD in all studied places. The use of LWD sensors installed over the turfgrass, either near the standard height of the temperature/ relative humidity shield or at 30 cm, showed a definite correlation with LWD in the upper canopy of different crops, for the locations in this study, but the 30 cm relationship was clearly stronger. For corn and muskmelon crops, the use of 30 cm-height observations over turfgrass to estimate LWD at the crop level resulted in average overestimations of only 2–3% (Fig. 7), which is similar in magnitude to the variability among sensors. Gleason et al. (1994) used LWD data from sensors exposed about 30 cm above turfgrass in disease management schemes. Such measurements at 30 cm have the practical purpose of avoiding interference with growers’ field operations. Our comparison measurements of LWD in melons and over nearby turfgrass confirm that Gleason et al. (1994) made a good choice of sensor position for their studies. Our finding that this

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sensor exposure over turfgrass also mimicked the LWD measured in a tall canopy of corn was surprising. Based on these results, we cautiously suggest that a sensor at 30 cm with an angle of deployment ranging from 308 to 458 should be considered as a possible standard for LWD measurements in weather station conditions. Further comparison observations involving more crops and climatic regions are clearly desirable, and such a standard sensor exposure would clearly not suffice when surrounding crops were irrigated and the weather station was rainfed. Few studies in the literature have tried to correlate LWD over turfgrass as in a weather station with LWD data in adjacent crops. On the other hand, the most accurate and precise models for LWD estimates, like Pedro and Gillespie (1982a, 1982b), Zhang and Gillespie (1990), Gleason et al. (1994), Rao et al. (1998), and Magarey (1999), use standard weather station data. The strong correlations obtained in this study between LWD at 30 cm over turfgrass and in the crops reinforce the idea that adopting physically based models to estimate LWD at height of 30 cm over turfgrass (e.g., Madeira et al., 2002) is a viable alternative to direct measurement. This procedure is a less complex modeling task than attempting to account for all the various characteristics of different crops, and we intend to pursue this idea with further analysis of our data.

5. Conclusions Flat plate LWD sensors, when properly treated with painting and heating, can give measurements that are as precise and accurate as the limits of spatial sampling reported by previous studies (e.g., Magarey, 1999). However, the position, height and angle of the LWD sensor have an effect on the measurements. At the highest positions, measured LWD was shorter than at 30 cm and at the smallest angles it was longer than at larger angles. As a standard for LWD measurements over turfgrass at a weather station, sensor deployment at 30 cm and angles of 308 to 458 is recommended. When LWD data from the reference sensor (30 cm over turfgrass and at 308) was correlated to LWD measured in the upper canopy of crops with very different physical characteristics, strong relationships were obtained, which suggests that crop LWD

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may be estimated well enough for many operational purposes from LWD measurements made under weather station conditions.

Acknowledgement The project was funded in part by a fellowship to Paulo C. Sentelhas from the CNPq, a Brazilian Government Institution (Proc. 202536/02-5), and by USDA.

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