HortResearch, Mt. Albert Research Centre, PB 92-169, Auckland, New Zealand

Background and objectives
The importance of free water on plant surfaces for infection by fungal pathogens means that leaf wetness is often used as an input into disease prediction models. In New Zealand, the SpotCheck program, part of Orchard 2000 decision support software, is used for monitoring apple scab infection periods[l]. Surface wetness in this application is measured by a flat plate electronic sensor, mounted with other instruments within orchard shelter but outside the canopy to avoid spray deposits. This study aims to develop sensors which more accurately measure canopy wetness by comparing observed leaf and flower wetness in an apple canopy with outputs of two types of sensor, located inside and outside the canopy.

Materials and methods
The two wetness sensors used were a flat fibreglass plate with interleaved gold-plated copper strips[2] (Campbell Scientific Instruments, Utah, type 237) as used on Orchard 2000 weather stations, and a perspex cylinder with interleaved nichrome wire helices[3]. Sensors were mounted 1.5m above ground, either on a mast approximately 10m from an experimental block of apple trees, or on a branch of a tree within the block. Flat plate sensors were inclined 10o to the horizontal, facing North. All sensors were wired to a Campbell Scientific CR10 data logger with outputs scaled 0-100, where 0 was the driest and 100 the wettest reading. Sensors were scanned every minute and means were logged every 15 minutes when at least one sensor exceeded 5% wetness, or hourly if all sensors read below 5%. Most comparisons used averaged data from two replicate sensors. Wetness of leaves and flower buds was visually recorded in experimental orchards at Mt Albert Research Centre. In March 1995 eight apple extension shoots were tagged, and all leaves on each tagged shoot were observed during drying after daytime rain or morning dew at 1-2 hour intervals. Leaves were scored in seven categories: 0) no surface water, 1) up to 5% of total leaf surface wet, 2) 5-25% wet, 3) 25-50% wet, 4) 50-75% wet, 5) 75-100% wet, 6) all leaves completely wet. Upper and lower leaf surfaces were recorded separately. Average percentage wetness for analysis was taken to be the mid point of each category. In October 1996 twenty extension shoots on five apple trees (2 cv. Gravenstein, 1 cv. Royal Gala, 2 cv. Granny Smith) were tagged and leaves observed as above. Most observations were made at night during dew formation. In October 1997 flower buds were observed in a block of 15 apple trees (cv. Royal Gala). Growth stages green tip/centimetre green, cluster, pink/bloom, and petal fall/fruit set were identified and 20-30 buds from each category were scored for wetness as above. Observations were made after daytime rain or morning dew. In practical use in the Orchard 2000 SpotCheck program, electronic sensor output is interpreted as being either wet or dry using a 50% threshold. Data analysis therefore included a table of mean observed leaf or bud wetness according to whether a given sensor output was wet or dry, as well as regression analysis.

Results and conclusions
The relationship between observed wetness and sensor output was nonlinear. For example, when flat plate sensors mounted outside the canopy read from 0 to 50%, leaves and buds were generally dry. When these sensors read over 50%, observed wetness ranged from 0 to 100%. Flat plate sensors mounted in the canopy gave the most accurate prediction of leaf upper surface wetness, but cylindrical sensors mounted outside the canopy were almost as good. Cylindrical sensors mounted outside the canopy gave consistently good results for both leaves and flower buds. Mounting cylindrical sensors inside the canopy did not improve their performance markedly. Detection of apple scab infection periods may be improved by the use of cylindrical sensors in situations where deployment of sensors outside the canopy is necessary to avoid agrichemical spray deposits.

1. Beresford RM, Spink M, 1992. Acta Horticulturae 313, 285-96.
2. Gillespie TJ, Kidd GE, 1978. Canadian Journal of Plant Science 58, 179-87.
3.Young K, Galbreath NH, Hewitt EW, 1979. Journal of Agricultural Engineering Research 24, 20913.