J Pest Sci (2010) 83:191–196 DOI 10.1007/s10340-010-0286-5
ORIGINAL PAPER
Comparison of two methods of monitoring thrips populations in a greenhouse rose crop Jeannine Pizzol • Doummar Nammour Pierre Hervouet • Alexandre Bout • Nicolas Desneux • Ludovic Mailleret
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Received: 19 September 2009 / Accepted: 7 January 2010 / Published online: 30 January 2010 Ó Springer-Verlag 2010
Abstract The thrips, Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae) is among the most important pests of greenhouse crops in Europe and causes considerable damage to commercial rose crops. The usage of pesticides is associated with major problems, and thus the interest of implementing integrated pest management (IPM) for rose crops is increasing. One essential component of IPM is field monitoring/scouting. Growers use information gathered from scouting to select and schedule appropriate control tactics. Thrips populations were surveyed in 2005 and 2006 in a greenhouse planted with roses, Rosa x Hybrida in Southern of France. From April to August, thrips were counted using yellow sticky traps (YST), knock-down techniques [i.e., tapping flower heads (FT)] and actual counts of entire plants. Thrips abundance recorded using YST correlated well with abundance levels determined through FT or actual counts (whole plant). Our results demonstrate that it is accurate to estimate thrips populations using YST in rose crops in greenhouse. Because YST takes at least twice less time than other monitoring methods, it could be used as a valid and easy monitoring technique in further development of IPM programs on roses. The possibility of setting a damage threshold using the data from the YST in the greenhouse is discussed. Keywords Integrated pest management Population dynamics Frankliniella occidentalis Yellow sticky traps Greenhouse Rose
Communicated by M. Traugott. J. Pizzol (&) D. Nammour P. Hervouet A. Bout N. Desneux L. Mailleret Unite´ de Recherches Inte´gre´es en Horticulture, INRA, 400 route des chappes, 06903 Sophia-Antipolis, France e-mail:
[email protected]
Introduction Thrips are important pests of greenhouse vegetable and ornamental crops around the world (Yudin et al. 1986; Lewis 1997; Moritz 2002; Morse and Hoddle 2006). More specifically, Frankliniella occidentalis (Pergande) is among the most important pests of greenhouse crops in Europe (van Lenteren and Loomans 1998). Thrips cause considerable damage to commercial flower crops, through direct feeding on marketable produce (i.e., flowers or flower buds) or as occasional vectors of plant pathogens (Brodsgaard 2004; Jones 2005). There are major problems associated with usage of insecticides: resistant strains are appearing (Esponisa et al. 2002; Humeres and Morse 2006; Bielza et al. 2007), and it is now well known that they have considerable impacts on human health and non-target organisms (Weisenburger 1993; Desneux et al. 2007). Theses concerns are leading to legal restrictions on the insecticides allowed. In addition, the thrips live mainly in the rose flowers where they are difficult to reach by nonsystemic insecticides. Therefore, environmentally sound alternatives to pesticides are needed and increase the interest of using Integrated Pest Management (IPM). IPM is an approach that aims to reduce pest status to tolerable levels by using methods that are effective, economically sound while minimizing environmental impact (Stern et al. 1959). One essential component of IPM is field monitoring/ scouting and growers use information gathered from scouting to select and schedule appropriate control tactics. Among other monitoring methods, sticky traps have been demonstrated to be helpful for evaluating the degree of infestation of various greenhouse crops (Allen 1995; Boone 1999; Casey and Parrella 2002; Parella et al. 2003). Additionally, sticky traps can also provide a way to control pest insects on various crops (notably the thrips
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F. occidentalis) (Heinz et al. 1992; Brodsgaard 1993; Hazarika et al. 2009, but see Trdan et al. 2005). In France, IPM is only adopted in 2% of greenhouse ornamental crops (Astredhor 2004) whereas, for example, releases of natural enemies against thrips are widely used on greenhouse vegetable crops (Gillespie 1989; Jacobson et al. 2001; Shipp and Wang 2003). This difference may be ascribed to the variation in natural enemy efficacy against thrips among crops and also primarily on the extremely low economic thresholds adopted in ornamental flower industry (see van Driesche et al. 2005). Another reason for poor adoption of IPM in greenhouse ornamental crops in France is because current monitoring practices in several crops are highly inefficient and time consuming. More widespread use of IPM will therefore depend on the development of quick, accurate monitoring procedures that are also easy to learn and use by growers. Fast sampling methods on the plant (notably for thrips) have been assessed (Boll et al. 2007; Poncet et al. 2008; Bout et al. 2009), but some other authors have promoted yellow sticky traps (YST) as predictor of thrips in roses (both in flowers and buds) (Parrella et al. 2003). In this article, we aimed initially to compare two monitoring tactics: (i) sampling thrips using a traditionally adopted method which consists in tapping the rose flowers onto a white sheet of paper and counting individuals (i.e. tapping flower head, FT) (Pizzol et al. 2005), and (ii) counting individuals captured on YST. We also used actual count of thrips on whole plants (Boll et al. 2007; Poncet et al. 2008). It allowed the assessment of accuracy of the YST and FT monitoring tactics.
Materials and methods Greenhouse and cropping conditions Research was conducted during spring and summer of 2005 and 2006, periods during which thrips infestations commonly occur in southern France (Pizzol et al. 2006). Experiments were conducted in a North–South oriented, 576 m2 plastic greenhouse with rosebushes, at INRA in Sophia Antipolis, France (438360 N–78040 E). The greenhouse was equipped with 400 9 700 lm mesh screens, shade screens, and a mist system. Climate and fertilization were computer managed and climate data continuously recorded. Temperatures were 14–35°C during the sampling period (week 15–31). Three cultivars of roses, MagnumÒ, MilvaÒ, and SuelaÒ, were grown on Grodan rock-wool substrate on 50-cm high tables. A previous study conducted in the greenhouse (with these three cultivars) demonstrated no cultivar type effect on thrips populations (Poncet et al.
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2010). For thrips control, releases were conducted of Neoseiulus (Amblyseius) cucumeris (Oudemans) and occasionally of Franklinothrips vespiformis (Crawford). To control Tetranychus urticae (Koch), the predatory mite Neoseiulus (Amblyseius) californicus (McGregor) was used. In the event of heavy infestation, insecticides (abamectin and lunefuron) were used. Thrips monitoring methods Depending on the year, two or three methods were used simultaneously to monitor thrips: (i) direct sampling using FT (2005 and 2006), (ii) counts of individuals captured on YST (2005 and 2006), and (iii) actual counts made on plants (2006). Monitoring was conducted during periods of high crop susceptibility to thrips attack (i.e., week 15–31, Brun et al. 2004). Frankliniella occidentalis was identified as the main thysanopterous species. Thrips tabaci Lindeman was also in a lesser extent present and was pooled with F. occidentalis for counting purposes. For FT, the following protocol was adopted: rose flowers were lightly tapped three times onto a white sheet of paper. If any thrips were detected on the paper, the rose was tapped again for as long as thrips continued to fall on the paper. Pilot experiments showed that this method allowed counting more than 95% of thrips present in the flower (Pizzol J., unpublished data). Each week, 150 randomly selected rose flowers were revised. This FT method has been shown to give similar results to those of stereo microscope precise counts (Duraimurugan and Jagadish 2004; Pizzol et al. 2005). It is also non-destructive and less time consuming than stereo counts. For YST, the following protocol was adopted: a total of 40 traps (10 x 25 cm, Bug-ScanÒ) were deployed on the greenhouse sides: 15 each on the north and south sides, above the crop, 5 each on the east and west sides (1.5 m from ground level). This disposition of traps was chosen (i) accordingly to a previous study that demonstrated an important homogeneity in spatial distribution of thrips in the greenhouse (Poncet et al. 2010), and (ii) because placing traps this way could provide an easiest access to the YST (and thus easiest adoption of the method by growers). Traps were replaced and the trapped thrips counted on a weekly basis. In 2006, thrips survey was also conducted in the greenhouse using actual counts made on whole plants carried out on a weekly basis. Sampling units consisted of one stem with a flower as close as possible to the harvesting stage and the corresponding basal foliage. 90 plants were labeled on a 3 9 3 m regular grid in the greenhouse. Depending on the level of thrips infestation, FT, YST and actual counts methods took 35–70 min, 20–35 min, and 90–120 min weekly, respectively.
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Data analysis Simple linear regressions were used to determine relationships between thrips counts made using the YST and FT methods, as the actual counts. In addition, in order to relate a previously established threshold based on FT results (0.5 thrips per flower [tpf], Brun et al. 2004) to the results gained using the YST method, we computed the best linear relationship (according to least square error minimization) between the YST and FT datasets. For statistical analyses, we used SPSS software.
damage threshold of 0.5 tpf (Brun et al. 2004) during week 25. In 2006, thrips population dynamics obtained through FT, YST, and actual counts were similar (Fig. 1b). The mean numbers of thrips trapped (YST) or counted (FT and actual counts) increased slowly from week 15 to week 19 but were higher than in 2005. By week 21, thrips population reached the damage threshold of 0.5 tpf, and thrips numbers reached a peak during week 23. Then thrips population decreased sharply. Comparison among monitoring methods
Results Thrips population dynamics During 2005, thrips population dynamics recorded through the different methods showed similar trends (Fig. 1a). The mean numbers of thrips were low up to week 22, (for both YST and FT methods) and then there was a clear increase in the numbers of individuals counted or trapped. It remained at these higher levels until the end of the survey. Based on our FT results, infestation levels reached the
For both 2005 and 2006, thrips population counts from FT and YST showed significant positive relationships (2005: R2 = 0.65, F = 27.60, df = 15, P \ 0.001; 2006: R2 = 0.88, F = 113.40, df = 15, P \ 0.001; 2005 and 2006 datasets pooled: R2 = 0.85, F = 176.91, df = 32, P \ 0.001) (Fig. 2). In addition, population counts from both monitoring methods were significantly correlated with actual counts undergone in 2006 (YST: R2 = 0.84, F = 87.91, df = 15, P \ 0.001; FT: R2 = 0.92, F = 200.10, df = 15, P \ 0.001). Computation of a damage threshold for the YST monitoring method
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The following relationship: tpt = 9.78 tpf ? 1.8 provided the best linear relationship (according to least square error minimization) between the YST and FT datasets (2005 and 2006 datasets pooled) (Fig. 2). Using this formula and the 25
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tpt = 9.78 tpf + 1.8 R² = 0.85
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Fig. 1 Mean number (±SEM) of thrips per yellow sticky trap, per flower, and per plant in the greenhouse in (a) 2005 from week 12 to week 31, and in (b) 2006 from week 15 to week 31. Actual counts on whole plants were undergone only in 2006
Fig. 2 Relationship between the mean number of thrips per flower (FT method) and the mean number of thrips per trap (YST method) in the greenhouse (2005 and 2006 datasets pooled)
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damage/action threshold estimated at 0.5 tpf (Brun et al. 2004), we estimated a damage/action threshold of 6.7 thrips per trap (tpt). This value of 6.7 tpt for YST dataset showed to provide the same week for thrips populations reaching the threshold as what was observed with the FT method (2005: week 24–25; 2006: week 21).
2002) can influence the captures. In instance, even though our results showed a clear linear relationship between the numbers of trapped thrips (YST) and the level of crop infestation as estimated by FT, further studies should be performed to optimize the use of YST in terms of location and height above ground, among other factors.
Discussion
Computation of a damage threshold for the YST monitoring method
Our results demonstrate that it is accurate to estimate thrips populations on the plants using YST in rose crops in greenhouse because the data so obtained correlated well with the numbers of thrips in the flowers (FT method) and numbers of thrips from actual counts made on plants. YST method is quicker (time required by YST and FT methods differs by a factor 2) to use than FT method. The YST method is also easier for a ‘‘non-expert’’ to learn (Parrella et al. 2003). It gives the YST method two main advantages over the FT method. In addition, it appears that using a threshold value based on YST dataset is possible and accurate. Relationship between YST and FT monitoring methods Our results showed that monitoring population levels of thrips can be done accurately using the YST method. On cucumber, Hassan (1983) described a simple method using YST to monitor populations of pests, including thrips. However, the method’s efficiency depends on the location and color of the traps (Brodsgaard 1989; Gillespie and Vernon 1990; Vernon and Gillespie 1990). Robb (1989) observed a significant correlation between trapped F. occidentalis on YST and larval and female populations on carnation crops. In addition, Robb (1989) found that YST located near greenhouse openings helped to predict thrips invasion in rose crops. However, our results contradict other studies. Boone (1999) showed that the linear correlation between thrips captured on sticky traps and the population on the roses was of low significance. In a study by Allen (1995), the number of thrips per sticky trap was not (linearly) correlated to the level of the thrips population on the plants around the trap: the traps merely indicated that thrips were present in the crop. However, in these studies some factors could have set differently than in our study. For example, the distribution of thrips on various parts of the plant or the distribution of the adults between the traps and the plant depends on the density of flowers in the greenhouse. Also, crop composition can affect the relationship between the numbers of F. occidentalis on sticky traps and in flowers in greenhouses (Robb 1989). Finally, the number, the disposition and the color of the traps (Yudin et al. 1987; Brodsgaard 1989; Vernon and Gillespie 1990; Hoddle et al.
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On the basis of the YST damage threshold, the decision as to whether action is required to deal with a thrips infestation or not would be obtained more quickly and easily by comparing the mean number of trapped individuals per week and per YST with the 6.7 tpt threshold rather than using the FT method. An examination of the literature shows that authors vary widely in the action thresholds they recommend in terms of numbers of trapped individuals. This threshold does strongly depend on the crop (thrips damage and crop tolerance differ between crops), but it may also depend on the traps’ spatial density, location, geometry, or color. Considering YST only, Shipp et al. (2000) estimate this threshold at between 20 and 50 thrips per day on a cucumber crop with 13 9 8 cm traps at a density of roughly 1 trap per 35 m2. For Steiner and Goodwin (2005) it ranges between 20 and 30 trapped individuals per week on a hydroponic strawberry crop with 10 9 15 cm yellow traps, though trap density was not specified. On a carnation crop, Cloyd and Sadof (2003) recommend to use a threshold of 20 trapped thrips per week on sticky traps (dimensions not given) at a density of roughly 1 trap per 100 m2. To our knowledge, very few data are available for rose crops. Kobb et al. (2004) recommend a threshold of 25 to 50 thrips per week on rose crops using sticky cards (dimensions not specified) at a density of roughly 1 trap per 1,000 m2. Also Casey and Parrella (2002), Parrella et al., (2003) predict a mean trap capture between 20 and 50 adults western flower thrips per trap per week (on YST 15 9 15 cm) corresponded to one to two thrips per flower per week. From this brief survey it seems quite difficult to make a sound comparison between the different recommended thresholds. In instance, our computed threshold is at least three times lower than the other recommendations and thus further studies research would aim optimizing the use of YST in rose greenhouses.
Conclusion The aim of this study was to perform a quantitative comparison among various methods for monitoring thrips population dynamics in a greenhouse rose crop. It was
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motivated by the need to provide professional growers with a simple, fast and reliable method for monitoring thrips population levels and so facilitate the use of IPM to protect greenhouse rose crops. We compared the FT method, an accurate but time consuming one, with the YST method, which is much easier and faster but whose accuracy was not precisely known (and also to results from actual counts made on whole plants). Our results showed a strong relationship between the two methods. From this and the known damage threshold for the FT method, we derived a corresponding damage threshold for the YST method, estimated at about 6.7 trapped thrips individuals per trap and per week. Further research will aim to optimize the use of YST for thrips population monitoring in terms of trap density and location, and so promote their use in an IPM program. Contrary to FT, the YST method can constitute a method easily usable by the growers and that could be optimized by video detection techniques (Boissard et al. 2008). Acknowledgments We thank Jean-Michel Rabasse and Kris Wyckhuys for comments on an earlier version of the manuscript. This work was funded by REGION PACA Projects No 2005_20372 and No 2006_13517. We thank Michel Ziegler and Sophie Voisin for technical assistance during the experimentations.
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