Predicting armoured scale insect (Homoptera: Diaspididae) phenology on kiwifruit (Actinidia sp.)

New Zealand Journal of Crop and Horticultural Science ISSN: 0114-0671 (Print) 1175-8783 (Online) Journal homepage: http://www.tandfonline.com/loi/tnzc20 Predicting armoured scale insect (Homoptera: Diaspididae) phenology on kiwifruit (Actinidia sp.) M. G. Hill, N. A. Mauchline & K. A. Stannard To cite this article: M. G. Hill, N. A. Mauchline & K. A. Stannard (2008) Predicting armoured scale insect (Homoptera: Diaspididae) phenology on kiwifruit (Actinidia sp.), New Zealand Journal of Crop and Horticultural Science, 36:4, 253-262, DOI: 10.1080/01140670809510242 To link to this article: http://dx.doi.org/10.1080/01140670809510242 Published online: 19 Feb 2010. Submit your article to this journal Article views: 280 View related articles Citing articles: 3 View citing articles Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalinformation?journalcode=tnzc20 Download by: [148.251.235.206] Date: 04 February 2016, At: 10:58

New Zealand Journal of Crop and Horticultural Science, 2008, Vol. 36: 253-262 0014-0671/08/3604-0253 The Royal Society of New Zealand 2008 253 Predicting armoured scale insect (Homoptera: Diaspididae) phenology on kiwifruit (Actinidia sp.) M. G. HILL N. A. MAUCHLINE K. A. STANNARD The Horticulture and Food Research Institute of New Zealand Te Puke Research Centre 412 No 1 Rd, RD2 Te Puke, New Zealand email: ghill@hortresearch.co.nz Abstract Five years of greedy scale (Hemiberlesia rapax) phenology data from a kiwifruit (Actinidia deliciosa '') orchard in Whangarei, New Zealand have been used to develop and partially validate a predictive equation for forecasting the timing of seasonal emergence of first generation crawlers using heat unit (day-degree) summation above a 10 C threshold from 1 August. This was further validated against five armoured scale insect phenology data sets collected from Northland, Coromandel Peninsula, and Bay of Plenty, New Zealand. The armoured scale phenology data were similar at all sites notwithstanding measurements being taken from both '' and 'Hort16A' commercial cultivars and there being large differences in armoured scale insect species composition among sites. The model provided predictions of the 50% crawler emergence date for the first generation of armoured scale within 1 week of observed date at four of the five sites, but was less accurate in predicting the date of 10% and 90% generational emergence. The use of this method as a tool for forecasting insecticide spray applications for the kiwifruit industry is discussed. Keywords greedy scale; latania scale; Hemiberlesia lataniae; Hemiberlesia rapax; phenology; models; kiwifruit H08063; Online publication date 1 December 2008 Received 30 June 2008; accepted 16 October 2008 INTRODUCTION A pre-requisite for certification in good agricultural practice (e.g., GLOBALGAP (www.globalgap. org)), required by many fruit-importing countries, is that chemicals are only applied to fruit crops in response to a demonstrated need. This implies that insecticides are to be sprayed at a time that would achieve optimal control of the target pest. The two armoured scale insect species (Homoptera: Diaspididae), latania scale {Hemiberlesia lataniae Signoret) and greedy scale {Hemiberlesia rapax Comstock) are the dominant pests of kiwifruit {Actinidia sp.) in New Zealand. Both insect species are parthenogenetic and release their mobile first instar (crawler) life stage in two broad peaks over an extended period between October and May, with peaks of crawler production usually occurring in January and March/April (Blank et al. 1996). Various studies of these pests have demonstrated that the immature life-stages are more vulnerable to insecticides (Blank et al. 1985, 1991, 1995); therefore, targeting insecticide applications during periods of the year when the mobile and vulnerable crawler stage is most active should maximise the impact of insecticide sprays on armoured scale insect populations. The crawler stage is the dispersal phase of the insect. It lasts for usually less than one day immediately following the eclosión of the first instar. The crawler is laid by the armoured scale insect and emerges from a gap between the hard test covering the adult and the host plant substrate. The crawler wanders around for a few hours and may be blown around by the wind looking for a suitable place to settle. On locating a suitable place to settle, it inserts its stylet into the host plant and spins a waxy test over itself after which it becomes permanently settled. The crawler stage and the settled first instar are the most susceptible to being killed by topical insecticide application as they are not protected by a hard waxy test which is developed in the late nymphal and adult stages. A key element in optimising insecticide sprays for the control of horticultural pests in integrated pest management (IPM) systems is the use of forecasting

254 New Zealand Journal of crop and Horticultural Science, 2008, Vol. 36 to predict insect phenology (dent 2000). Because of the strong relationship between insect development rate and temperature, a function relating these two variables is the basis for most insect phenology models. Such models have been successful in predicting the timing of insect life history events for a wide range of insects in many diverse habitats. Temperature-driven phenology models have been widely used in research and practice to predict the occurrence of populations of armoured scale insects and to optimise the timing of insecticide applications (Potter et al. 1989; Mazzoni & cravedi 1995,1999; Nestel et al. 1995; Blank et al. 1996; Ortu & Acciaro 1999; Schaub et al. 1999). Previous research on spray application timing for export kiwifruit produced a leaf monitoring system and scale infestation threshold for determining the need to apply sprays against the second generation of armoured scales (Steven et al. 1994). This system is currently used by all export kiwifruit growers to justify insecticide applications between January and March (Anon. 2001), but cannot be used earlier in the season, from November to January, as the numbers of insects on leaves are too low to monitor accurately (Steven et al. 1994). There have been two previous attempts to model greedy scale populations on kiwifruit. Greaves et al. (1994) developed a deterministic population dynamics model based upon laboratory-generated temperaturedevelopment data for greedy scale. its accuracy was tested using first instar phenology data from kiwifruit leaf samples collected in Paeroa and Rukuhia, but it was never validated (Greaves et al. 1994). By running their model on historical meteorological data collected in the 1970s to 1990s from Kerikeri, Te Puke, and Riwaka, Greaves et al. (1994) were able to show that greedy scale phenology was likely to vary significantly both between sites and between years. A second study carried out on greedy scale phenology by Blank and colleagues in Whangarei during the 1980s used Bayesian modelling to predict the peaks of scale insect life stage relative abundance on kiwifruit (Blank et al. 1996). This analysis does not allow the modelling of stage specific phenology, as it is based upon relative life stage abundance only, not absolute insect densities, but Blank et al. (1996) claimed that crawler phenology (i.e., actual crawler densities) could be modelled by comparing the abundance of settled first instars ("white cap" stage) with that of other life stages. This paper re-analyses the greedy scale crawler phenology data of Blank et al. (1996) to predict the phenology of the first generation of the armoured scale insect crawler life stage on kiwifruit between November and February; and makes preliminary validations of phenology predictions, using scale insect phenology data on kiwifruit vines from several sites within the main kiwifruit growing regions of New Zealand. The outputs from this analysis are used to discuss the merits of developing sprayforecasting predictions for armoured scale insect control in commercial kiwifruit production, targeting the crawler and first instar stages of the first (summer) generation. MATERIALS AND METHODS Developing an armoured scale crawler phenology model Between 1984 and 1990, Blank et al. (1996) collected data on the phenology of scale insect crawler emergence on unsprayed kiwifruit (Actinidia deliciosa (A.chev.) c.f. liang et A.R. Ferguson '') bark at a site near Whangarei. Crawlers were trapped on sixteen 20-mm-wide sticky white tape bands wound around kiwifruit wood, sticky side to the wood, within 40 mm of mature scale insects. The two ends of the tape were joined to make a flap for ease of handling during removal and a petroleum grease was applied in a thin band over the tape. The bands were replaced at the same position at intervals between 13 and 23 days during the summer and greedy scale crawlers, identified by their oval shape and yellow colour, were counted on both sides of the tape using a binocular microscope (Blank et al. 1996). Ninety-nine percent of the scale insects on the vines were greedy scale (Blank et al. 1996). The original crawler phenology data set collected by Blank et al. (1996) was obtained from the HortResearch archives and re-analysed to develop a predictive equation of crawler release in the first generation. crawler production stops or is very low during winter, and the first generation was judged to start from 1 August. A cut-off point for the end of the first generation of crawlers was determined as the date on which crawler catches on sticky bands began to rise again, following a period of several weeks of declining numbers through January and February (Blank et al. 1996, fig. 7). Three years (1985-86 to 1987-88) of cumulative catches of first generation crawlers on sticky traps were plotted against calendar dates and day-degrees above a base of 10 c starting from 1 August. Mean daily temperatures were calculated as (max. + min.)/2) using New Zealand

Hill et al. Predicting armoured scale insect phenology 255 Kerikeri Research Centre fapiro, abandoned orchard Reren$a, abandoned orchard Fig. 1 Map of the North island of New Zealand showing the location of sites. Meteorological Service Whangarei site data. The start date of 1 August and base temperature of 10 c were chosen after a preliminary analysis showed that the results were insensitive to a range of start dates in August and September, and base temperatures from 7-10 c. A 3-parameter logistic equation of form y = a/(1+(x/b) c ) was fitted to the data using Sigma Plot 8.02. Proportion of first generation crawler emergence was the dependent variable and day-degrees above 10 c from 1 August was the independent variable. Monitoring armoured scale insect crawler phenology for predictive purposes in 2005/06 Scale insect phenology monitoring sites, consisting of bands of all-weather tape (Hill et al. 1986) were set up in mature blocks of unsprayed kiwifruit at the HortResearch Research centre orchards at Kerikeri and Te Puke, and at abandoned orchards in Northland (Kapiro) and coromandel (Te Rerenga) (Table 1; Fig. 1). Banding sites were 2- to 3-year-old wood near to the vine leader. One site per vine was selected where preliminary observations had shown crawler activity. Two sites per vine were used on 'Hort16A' vines at Te Puke to increase sampling accuracy where crawler populations were low. crawler trapping at these five locations was carried out over a 12-month period from July 2005 to July 2006. Bands were changed every 2 weeks, and replaced in the same positions on the canes. crawler numbers on bands were counted using a binocular microscope, and the band length (cane or branch circumference) was measured. On two occasions, the generic composition of the crawlers was estimated on the bands from each site by counting crawlers in the genus Hemiberlesia (greedy or latania scale) or Aspidiotus (oleander scale), by determining the pygidial lobe configuration under a compound microscope (Morales 1988). Greedy scale and latania scale crawlers are morphologically indistinguishable. The armoured scale species composition at each site was estimated by examining a minimum of 100 adult scale insects on 10-15 canes close to the crawler trap bands on one occasion half way through the phenology data-gathering period. One sampling time was judged to be adequate for this as scale insect population dynamics characteristically change relatively slowly and the species composition would not be expected to alter significantly over the Table 1 Site details for scale insect monitoring in 2005/06. (a.s.l. = above sea level (in metres).) Site location and elevation (a.s.l.) Kiwifruit cultivar Mean cane diam. (mm) ± SE No. of crawler trap sites Te Puke Research centre Te Rerenga, coromandel Kerikeri Research centre Kapiro, Northland S 37 49 : e 176 19 100 m S 36 45.26 : e175 36.27 5m S 35 10.66 : e 173 5.69 75 m S 35 10.63 : e 173 53.99 115 m Hort16A 103 ± 5.5 100±5.6 76.5±6.2 76.7 ± 3.9 59.1 ±3.4 20 10 11 9 12

256 New Zealand Journal of crop and Horticultural Science, 2008, Vol. 36 3 g U 1U0-80 - 60-40 - 20-0 - r 7 /' / / / 1985/86 o 1986/87 --r 1987/88 100 150 200 Fig. 2 A, Cumulative first generation armoured scale insect (Hemiberlesia) mobile first instar (crawler) trap catches over time from 1 August for the 3 years 1985-86,1986-87, and 1987-88. B, cumulative first generation crawler trap catches over physiological time (day degrees above 10 c from 1 August) for the 3 years 1984-85, 1985-86, and 1986-87, and fitted logistic regression. Days from 1 Aug C 00 3.a g S 3 p3 B feiss-â-t- 1985-86 o 1986-87 r 1987-88 fitted logistic curve 1000 1200 1400 Day-degrees above 10 C from 1 Aug Table 2 Proportion of the adult scale that were latania scale (Hemiberlesia lataniae) and the proportion of trapped crawlers that were in the genus Hemiberlesia (i.e., greedy or latania scale). Site Te Puke Te Puke Kerikeri Kapiro Te Rerenga cultivar Hort16A % latania scale 93 54 0 97 100 N 200 50 150 150 200 % of crawlers from genus Hemiberlesia 98 95 100 100 99 N 800 160 100 150 400 duration of the study (Steven 1990). Species were determined by the visual appearance of the adult scale caps (Morales 1988). Temperature in each block was recorded hourly with a Tinytag temperature logger inside a "stacked plate" screen (Henshall & Snelgar 1989) and suspended beneath the vine canopy at a height of c. 1.6 m. Hourly temperature records from the standard NIWA (National Institute of Water and Atmospheric Research) meteorological sites at HortResearch Te Puke and Kerikeri were also obtained. RESULTS Predicting first generation crawler phenology from the Whangarei data set There is a variation of c. 2 weeks in the cumulative emergence of crawlers between 1985/86 and 1987/88 (Fig. 2A). Plotting the data as physiological time leads to a much closer alignment of curves for the 3 years of data (Fig. 2B), and a logistic equation provides a good description of the data for all 3 years (r 2 = 0.991):

Hill et al. Predicting armoured scale insect phenology 257 Proportion of first generational crawler emergence = 1.0381/(1 +(x/481.5) 3. 139 ) (1) where x = day-degrees from 1 August above a base of 10 c. Additional crawler phenology data collected by Blank et al. (1996) in 1988/89 and 1989/90 were used to validate the predictions from equation 1. equation 1 provides a good prediction of crawler emergence in both seasons, although data for only half the season were collected in 1988/89 (Fig. 3). Scale phenology estimates The five sites where crawler phenology was measured in 2005-06 were all on the eastern side of the North island and several hundred kilometres apart (Fig. 1). latania scale was the dominant scale insect on '' vines except at Kerikeri, where greedy scale was dominant (Table 2). Greedy and latania scale were present in equal numbers on 'Hort16A' at the Te Puke site. Nearly all scale insect crawlers were either greedy or latania (they are indistinguishable as crawlers), with up to 5% being oleander scale (Aspidiotus nerii Bouché) at Te Puke and Te Rerenga. The phenology of scale insect crawler release on the vines was estimated by plotting crawler abundance, expressed as crawlers/cm of bark circumference/day, against the date the bands were removed from the kiwifruit vines (Fig. 4). errors associated with the mean scale crawler populations used to estimate crawler phenology are shown in Table 3. The phenology of crawler activity followed a pattern of two broad peaks in a year, corresponding roughly to two annual generations of scale insects (Greaves et al. 1994; Blank et al. 1996). The first generation of crawlers occurred from approximately November to January and the second from February to May. The overall pattern was similar at all sites (Fig. 4), but there appeared to be differences. For '' sites, the spring peak of crawler abundance occurred 2-4 weeks earlier at the Northland sites (November/december) than at Te Rerenga and Te Puke (december/january). crawler numbers on 'Hort16A' vines at Te Puke were low compared with numbers on an adjacent '' block, and first generation peak crawler abundance was 3-4 weeks earlier (Fig. 4). The cumulative emergence of the first generation of crawlers on kiwifruit at four sites in 2005-06 (Table 1) was plotted against calendar dates and compared at each site with the crawler emergence predictions using the logistic equation (equation 1) (Fig. 5; Table 4). Observed dates of 50% crawler 200 400 600 800 1000 1200 1400 1600 Day-degrees > 10 C from 1 Aug 30Sep 5Nov 5 Dec 31 Dec 21 Jan 8 Feb 26 Feb 200 400 600 800 1000 1200 1400 Day-degrees > 10 C from 1 Aug 12Sep 30 Oct 20 Nov 11 Dec 5 Jan 26 Jan 1989/90 Fig. 3 Predicted (dashed line) versus observed (solid line) first generation greedy scale (Hemiberlesia rapax) crawler phenology on kiwifruit (Actinida deliciosa) wood at Whangarei, A, in 1988-89, and B, in 1989-90, using predictions from equation 1 and data from Blank et al. (1996). emergence ranged from 13 November 2005 (Kerikeri '') to 11 December 2005 (Te Rerenga). The predicted 50% crawler release date was within one week of the observed date at Te Puke, Te Rerenga, and Kapiro (Table 4), but was 15 days late for the Kerikeri '' site. The 10% and 90% cumulative crawler emergence dates were less accurately predicted, being later than observed at all sites, and ranging from nought to 31 days late. The predicted mean (±SE) dates of peak first generation first instar (white cap (Blank et al. 1996)) "incidence", based upon the analysis in Blank et al. (1996) (which calculates the dates on which first instars peaked calculated as a proportion of all life stages) were also calculated and compared with the actual 50% cumulative crawler emergence dates at each of the four sites (Table 5). The predictions ranged from 13 to 26 december 2005. They were

258 New Zealand Journal of crop and Horticultural Science, 2008, Vol. 36 OH T3 T3 «S" S X U 2.5-2.0-1.5-1.0-0.5 -, Te Puke HortlóA, Te Püke AW \A 3 & O- "O - 0.04 ^ ja x tj Fig. 4 Scale insect (Hemiberlesia sp.) crawler phenology for 'Hort16A' and '' kiwifruit (Actinidia sp.) vines at Te Puke, and '' vines at Te Rerenga, Kerikeri, and Kapiro. 10 -» _ -< i Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul 2005 2006 Table 3 Errors associated with mean scale (Hemiberlesia sp.) crawler population estimates for the phenology estimations in Fig. 4 expressed as the median and upper and lower quartile ranges for the standard error of the mean crawlers/cm per day trapped on the sticky bands expressed as a percentage of the mean over the duration of the sampling period. Median lower quartile upper quartile Kapiro Kerikeri Te Puke Hort16A Te Puke Te Rerenga 26% 21% 33% 40% 30% 51% 57% 50% 25% 19% 29% 24% 35% Table 4 Observed dates of 10%, 50%, and 90% emergence of the first armoured scale (Hemiberlesia sp.) crawler generation in 2005-06 at Kerikeri, Northland, coromandel, and Te Puke sites based upon the cumulative scale crawler emergence graphs in Fig. 5. Numbers in parentheses are the number of days that predictions from a fitted logistic equation of day-degree accumulation from 1 August above 10 C against cumulative first generation greedy scale (Hemiberlesia rapax) crawler emergence at Whangarei (Blank et al. 1996) (Equation 1) are ahead of (+) or behind (-) the observed percentage cumulative emergence data. Temperature estimates are all from orchard-based temperature data loggers. Site 10% emergence 50% emergence 90% emergence Te Puke Hort16A Te Puke Te Rerenga Kerikeri Kapiro 29 October 2005 (0) 20 October 2005 (-11) 17 October 2005 (-4) 19 September 2005 (-25) 21 September 2005 (-29) 6 december 2005 (-6) 8 december 2005 (-4) 11 december 2005 (+6) 13 November 2005 (-15) 24 November 2005 (+6) 29 december 2005 (-31) 10 January 2006 (-20) 19 January 2006 (-2) 30 december 2005 (-17) 15 January 2006 (0)

Hill et al. Predicting armoured scale insect phenology 259 Fig. 5 Observed cumulative armoured scale (Hemiberlesia sp.) first (summer) generation crawler emergence at each site during 2005-06 compared with estimates predicted using the logistic equation fitted to historical Whangarei data (Blank et al. 1996). Predictions of cumulative emergence using temperatures recorded by data loggers ("logger") in orchards are compared with those recorded at NIWA weather stations ("screen"). (KHRc, Kerikeri Horticultural Research centre.), Kapiro Kerikeri model Met screen temps model - Kapiro logger temps model - KHRC logger temps U I 3 3 U O0 40 - HortlóA, TePuke Te Puke model - Met screen temps model - data logger temps Table 5 Predicted dates of mean (±SE) peaks of first generation armoured scale (Hemiberlesia) "white cap" emergence from the Bayesian analysis of Blank et al. (1996) based upon 679±43 Se day-degree accumulations from 1 August 2005 above a threshold of 9.3 c. Numbers in parentheses are the number of days that predictions are ahead of (+) or behind (-) the observed cumulative crawler emergence curve. Site Mean -Se +Se Te Puke Hort16A Te Puke Te Rerenga Kerikeri Kapiro 26 december 2005 (-20) 26 december 2005 (-18) 16 december 2005 (-5) 13 december 2005 (-30) 14 december 2005 (-20) 20 december 2005 20 december 2005 13 december 2005 9 december 2005 9 december 2005 30 december 2006 30 december 2006 22 december 2005 18 december 2005 18 december 2005 18-30 days late compared with the date of 50% crawler emergence at Te Puke, Kerikeri, and Kapiro, and their standard error estimations, which were within 6 days of the mean, were also 14-25 days late (Table 5). Predictions from the Bayesian analysis agreed only with the Te Rerenga data, where the predicted mean first instar peak incidence date was 5 days later than the observed 50% crawler release date of 11 december (Table 5). Predictions from equation 1 using temperature data from the withinorchard-block Tinytag data loggers and local NIWA meteorological sites at Te Puke and Kerikeri were essentially identical (Fig. 5). DISCUSSION The results from the crawler phenology studies confirm earlier work (Greaves et al. 1994; Blank et al. 1996) showing that armoured scale insect phenology on kiwifruit follows two broad peaks of abundance in early summer (december-january)

260 New Zealand Journal of crop and Horticultural Science, 2008, Vol. 36 and autumn (March-April), representing the two annual, though clearly overlapping, armoured scale population generations. A minimally-parameterised (three) logistic equation describing cumulative crawler emergence in relation to heat unit accumulation developed in this study provides a good predictor of first generation (summer) crawler emergence. it proved to be reasonably accurate for describing the five armoured scale phenology data sets differing in space and time from the original data used to generate the equation (Fig. 5). in the original analysis of these data, Blank et al. (1996) calculated the dates of "peaks" and 'troughs" of the relative abundance of the sessile life stages (i.e., not the crawler stage) by fitting a smoothed line through the data using Bayesian probability (upsdell 1994), but never validated the model. The analysis presented here is a more accurate predictor of the phenology of crawler release over the duration of the first generation, and provides a more useful interpretation of the data for forecasting purposes compared with one based upon the relative abundance of life stages. The generally good agreement between the phenology predictions and the actual data across all sites in this study (Fig. 5; Table 4) is surprising, given that the predictions are based on greedy scale phenology on '' in Whangarei, but were successfully applied to predominantly latania scale populations on '', and greedy scale populations on'hort16a', several hundred kilometres further south (Table 2). This may be a function of the widely overlapping generations and the broad and irregular shape of the crawler emergence curves for both generations across all sites (Fig. 4). in New Zealand, there are only two published examples of phenology prediction modelling aiding pesticide application timing for horticultural crops; both relate to european red mite control. This pest diapauses and emerges from over-wintering eggs in a short pulse in spring, providing a well defined spraying target of young active stages that lasts only 1-2 weeks. Forc. 12 years in the 1980s and 1990s, a mite predator-prey population dynamics simulation model was used successfully to forecast organo-tin miticide applications for the control of european red mite on apples (Hayes 1987; Hayes et al. 1993). An empirical phenology model using a similar method to that used in the current example was also developed for accurately predicting miticide applications for the control of european red mite on stonefruit in central Otago (Hill & Mclaren 1988, 1989). Heat unit summation has been used as a means of predicting armoured scale insect phenology and for timing insecticide applications in numerous studies overseas, either from a fixed starting date (Jorgensen et al. 1981; Rice et al. 1982; Helsen et al. 1996) or more commonly since the advent of pheromone traps, by using male trap catches as a "biofix" (Phillips 1987; Rice & Jones 1988; Ortu & Acciaro 1999; Schaub et al. 1999). in addition to having bi-parental populations with more discrete generations, these studies are also from regions with continental climates, where rapid spring warming aids in the development of accurate predictions. The broad phenology peaks observed here for the uni-parental armoured scale insect populations on kiwifruit in New Zealand contrast strongly with the narrow and discrete crawler emergence curves observed for the bi-parental Pseudaulacaspis pentagona Targioni and Tozzetti on kiwifruit in italy (Hill et al. 2007) and for a variety of other bi-parental armoured scale insect populations on other crops (Potter et al. 1989; Mazzoni & cravedi 1999; Ortu & Acciaro 1999; Schaub et al. 1999). This is presumably because of the synchronising effect of a winter diapause, the mass emergence of males in spring and the requirement to mate prior to oviposition (Mazzoni & cravedi 1999). Recent studies of P. pentagona in italy have shown that insecticides targeted to kill crawlers at the peak of release of the first of the three armoured scale insect generations can provide season-long control of the scale insect populations on kiwifruit (Hill et al. 2007). Such well-targeted single insecticide applications are not possible against the broad phenology profiles of the uni-parental armoured scale insect species on kiwifruit in New Zealand (Fig. 4). Nevertheless, targeting spray applications against armoured scale phenology forecasts may still be of assistance to kiwifruit growers, given the observed potential for year-to-year variations of 20-30 days in armoured scale phenology (Greaves et al. 1994). Precise forecasting of phenology events is clearly not necessary in this instance, given the somewhat slowly changing phenology of armoured scale populations on kiwifruit in New Zealand (Fig. 4). Being able to predict the main period of first generation crawler emergence to within ± 1 week (Table 5) is likely to be sufficiently accurate to provide useful forecasts of spraying windows in spring. Yearly variation in climate affects kiwifruit vine phenology (Hall & McPherson 1995; Seleznyova & Greer 2001) as well as pest phenology. Thus it is possible that vine phenology may be an adequate and easily measured predictor of armoured scale insect

Hill et al. Predicting armoured scale insect phenology 261 phenology. Vine phenology is itself a strong driver for armoured scale insect control interventions, as insecticide sprays cannot be applied during pollination, and mineral oil spray applications are limited to a 2-5-week window (depending on kiwifruit cultivar) after flowering, because of phytotoxic effects on fruit (McKenna et al. 1997; Allison & McKenna 2002). However, most kiwifruit orchardists use a chemical bud-break enhancer which over-rides the natural phenology rhythm of the plant to the point of budbreak (Hall & McPherson 1995). Further studies will investigate the correlation between plant and insect phenology with and without bud-break enhancers. Temperature data collected from standard New Zealand Meteorological Service weather stations in the vicinity of two orchards (HortResearch Centres at Te Puke and Kerikeri) in this study gave similar predictions to those using temperature data collected by loggers within the kiwifruit block from which the insect phenology data were collected. This suggests that temperature data from standard Meteorological Service weather stations could be used to drive phenology models used for local or even regional scale crawler phenology prediction. The equation developed and validated in this study combined with appropriate synoptic or local temperature forecasts can be used to predict scale insect crawler phenology from October to January with sufficient accuracy to provide growers within the main kiwifruit growing regions of the Bay of Plenty, Auckland, and Northland with forecasts of periods of major crawler release for the first scale insect generation in summer. ACKNOWLEDGMENTS We are grateful to Mrs Coral Parr and Mr F Burgoyne for allowing us to use their properties for gathering phenology data and to Coral Parr and Ted Dawson for data collection. This work was supported by ZESPRI Group Ltd and the Foundation for Research, Science and Technology (contract C06X0306 "Biodigital: Technology for Sustainable Horticultural Production"). Thanks to David Logan for Fig. 1 and John Charles for comments on an earlier draft. REFERENCES Allison PA, McKenna C 2002. Effects of a C21 narrowrange petroleum spray oil on kiwifruit fruit gas exchange. In: Beattie GAC, Watson DM ed. Spray oils beyond 2000: sustainable pest and disease management. Pp. 193-194. Anonymous 2001. ZESPRI Kiwi Green Manual. Blank RH, Olson MH, Waller JE 1985. Screening pesticides for control of greedy scale on kiwifruit leaves. Proceedings, New Zealand Weed and Pest Control Conference No. 38: 219-222. Blank RH, Gill GSC, Upsdell MP 1996. Greedy scale, Hemiberlesia rapax (Hemiptera: Diaspididae), phenology on kiwifruit leaves and wood. New Zealand Journal of Crop and Horticultural Science 24(3): 239-248. Blank RH, Olson MH, Waller JE, Popay AJ 1991. Relative efficacy of chemicals for dormant season control of armoured scale on kiwifruit. Proceedings of the Forty-fourth New Zealand Weed and Pest Control Conference: 75-79. Blank RH, Holland PT, Gill GSC, Olson MH, Malcolm CP 1995. Efficacy and persistence of insecticide residues on fruit of kiwifruit to prevent greedy scale (Hemiptera: Diaspididae) crawler settlement. New Zealand Journal of Crop and Horticultural Science 23(1): 13-23. Dent D 2000. Insect Pest Management. Wallingford, United Kingdom, CABI Publishing. 424 p. Greaves AJ, Davys JW, Dow B W, Tomkins AR, Thomson C, Wilson DJ 1994. Seasonal temperatures and the phenology of greedy scale populations (Homoptera: Diaspididae) on kiwifruit vines in New Zealand. New Zealand Journal of Crop and Horticultural Science 22(1): 7-16. Hall AJ, McPherson HG 1995. Modelling the influence of temperature on the timing of bud break. Acta Horticulturae 444(1): 401-406. Hayes AJ 1987. of phenology model of European and red mite fall timing miticides. 40th Conference New Zealand Weed and Pest Control. Pp. 90-93. Hayes AJ, Walker JTS, Shaw PW, White V 1993. A decision model for miticide use in apple orchards. New Zealand Plant Protection Conference Proceedings 46: 162-165. Helsen HHM, Blommers LHM, Trapman MC, Polesny F, Muller W, Olszak RW 1996. Timing observation and control of mussel scale Lepidosaphes ulmi. International conference on integrated fruit production, Cedzyna, Poland, 28 August-2 September 1995 19(4): 145-149. Henshall WR, Snelgar WP 1989. A small unaspirated screen for air temperature measurement. New Zealand Journal of Crop and Horticultural Science 17: 103-107. Hill MG, McLaren GF 1988. predicting European red might hatch on apricots 1. A day-degree model. Proceedings of the 40th New Zealand Weed and Pest Control Conference. Pp. 90-93.

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