Spatio‐temporal analysis of plant pests in a greenhouse using a Bayesian approach

Poncet, C.; Lemesle, Valérie; Mailleret, Ludovic; Bout, Alexandre; Boll, Roger; Vaglio, Joelle

doi:10.1111/j.1461-9563.2010.00483.x

Cited by 3 publications

(6 citation statements)

References 27 publications

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“…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.…”

Section: Thrips Monitoring Methodsmentioning

confidence: 99%

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Comparison of two methods of monitoring thrips populations in a greenhouse rose crop

Pizzol¹,

Nammour²,

Hervouet³

et al. 2010

J Pest Sci

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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.

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Section: Thrips Monitoring Methodsmentioning

confidence: 99%

“…A previous study conducted in the greenhouse (with these three cultivars) demonstrated no cultivar type effect on thrips populations (Poncet et al 2010). For thrips control, releases were conducted of Neoseiulus (Amblyseius) cucumeris (Oudemans) and occasionally of Franklinothrips vespiformis (Crawford).…”

Section: Greenhouse and Cropping Conditionsmentioning

confidence: 96%

Comparison of two methods of monitoring thrips populations in a greenhouse rose crop

Pizzol¹,

Nammour²,

Hervouet³

et al. 2010

J Pest Sci

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“…Information on the locations of temporary or recurring clusters of pests observed in the previous week or over a 3-yr period in the greenhouse (Poncet et al 2008(Poncet et al , 2010 did not help optimize sampling plans. Zones of foci infection, as identiÞed by stem observations, do not seem to remain in a Þxed position from 1 wk to the next, particularly for powdery mildew.…”

Section: Discussionmentioning

confidence: 93%

“…If there were more foci than grid points, foci were selected at random. Conversely, we also constructed grids with foci identiÞed as recurring foci over a 3-yr period in this crop (Poncet et al 2008(Poncet et al , 2010. We completed the sampling grid with a random selection of sampling units.…”

Section: Methodsmentioning

confidence: 99%

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Realistic Global Scouting for Pests and Diseases on Cut Rose Crops

Bout¹,

Boll²,

Mailleret³

et al. 2010

jnl. econ. entom.

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Scouting is considered an essential component of integrated pest management strategies, but most of the techniques, which involve visual assessment, remain too time-consuming for application on a commercial scale. The global scouting method proposed here for greenhouse rose (Rosa spp.) crops combines several rapid visual methods for common pests and diseases, in a single sampling process. A 2-min observation time per sampling unit is required, with two observers. The sampling unit consists of a single stem with its flower and the corresponding basal foliage. A 90-unit regular grid (1 U/6.4 m2) was used, with weekly assessments, including a spatial distribution approach, for pest monitoring. Different grid sizes were simulated and tested with reference data, to determine whether to decrease the number of sampling units. A grid size of 1 U/21 m2 was found to be acceptable, with no significant loss of information. A more realistic and cheaper sampling strategy of this type is more likely to be accepted by growers, increasing the efficiency of crop monitoring and leading to more rational decisions.

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A Four Dimensional Spatio-Temporal Analysis of an Agricultural Dataset

Donald¹,

Mengersen²,

Young³

2015

PLoS ONE

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While a variety of statistical models now exist for the spatio-temporal analysis of two-dimensional (surface) data collected over time, there are few published examples of analogous models for the spatial analysis of data taken over four dimensions: latitude, longitude, height or depth, and time. When taking account of the autocorrelation of data within and between dimensions, the notion of closeness often differs for each of the dimensions. Here, we consider a number of approaches to the analysis of such a dataset, which arises from an agricultural experiment exploring the impact of different cropping systems on soil moisture. The proposed models vary in their representation of the spatial correlation in the data, the assumed temporal pattern and choice of conditional autoregressive (CAR) and other priors. In terms of the substantive question, we find that response cropping is generally more effective than long fallow cropping in reducing soil moisture at the depths considered (100 cm to 220 cm). Thus, if we wish to reduce the possibility of deep drainage and increased groundwater salinity, the recommended cropping system is response cropping.

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Spatio‐temporal analysis of plant pests in a greenhouse using a Bayesian approach

Cited by 3 publications

References 27 publications

Comparison of two methods of monitoring thrips populations in a greenhouse rose crop

Comparison of two methods of monitoring thrips populations in a greenhouse rose crop

Realistic Global Scouting for Pests and Diseases on Cut Rose Crops

A Four Dimensional Spatio-Temporal Analysis of an Agricultural Dataset

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