Roger Boll

Secondary plants used in biological control: A review

In crop systems, different types of plant or secondary crop may be grown together with the primary crop for pest management purposes. These additional plants – henceforth called secondary plants – may increase the efficiency and sustainability of biological control of pests by natural enemies. Such plants fall into several categories: companion, repellent, barrier, indicator, trap, insectary, and banker. Despite their effectiveness and accepted function in biological control, to date the full potential of secondary plants in integrated pest management has not been put to good use. This may be partly attributed to a lack of detailed knowledge of the way the secondary plant–crop systems operate, including the effects of the secondary plants on tritrophic interactions. The biggest constraint upon progress, however, has been confusion over definitions and terminology. In this paper, we review the knowledge of the currently employed plant categories and provide clear definitions.

Dispersal strategies of phytophagous insects at a local scale: adaptive potential of aphids in an agricultural environment

BackgroundThe spread of agriculture greatly modified the selective pressures exerted by plants on phytophagous insects, by providing these insects with a high-level resource, structured in time and space. The life history, behavioural and physiological traits of some insect species may have evolved in response to these changes, allowing them to crowd on crops and to become agricultural pests. Dispersal, which is one of these traits, is a key concept in evolutionary biology but has been over-simplified in most theoretical studies. We evaluated the impact of the local-scale dispersal strategy of phytophagous insects on their fitness, using an individual-based model to simulate population dynamics and dispersal between leaves and plants, by walking and flying, of the aphid Aphis gossypii, a major agricultural pest, in a melon field. We compared the optimal values for dispersal parameters in the model with the corresponding observed values in experimental trials.ResultsWe show that the rates of walking and flying disperser production on leaves were the most important traits determining the fitness criteria, whereas dispersal distance and the clustering of flying dispersers on the target plant had no effect. We further show that the effect of dispersal parameters on aphid fitness depended strongly on plant characteristics.ConclusionParameters defining the dispersal strategies of aphids at a local scale are key components of the fitness of these insects and may thus be essential in the adaptation to agricultural environments that are structured in space and time. Moreover, the fact that the effect of dispersal parameters on aphid fitness depends strongly on plant characteristics suggests that traits defining aphid dispersal strategies may be a cornerstone of host-plant specialization.

Inter-strain competition and dispersal in aphids: evidence from a greenhouse study

1. Crops are often colonised by aphids having different life‐history traits, and the aphids and their offspring compete for the shared resource. The intraspecific competition and dispersal characteristics of two strains (A and B) of the cotton aphid Aphis gossypii on cucumber were examined in a greenhouse study. Strain A normally feeds on cucumber, whereas strain B originated from melon but develops on cucumber. Both strains reproduce exclusively via parthenogenesis and can be discriminated using molecular markers.

Rapid visual estimates of thrips (Thysanoptera: Thripidae) densities on cucumber and rose crops

Abstract Scouting techniques combining rapid counting methods must be developed to help growers with immediate decision making in integrated pest management programs. We evaluated a method for estimating densities of western flower thrips, Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), one of the most damaging insect pests of greenhouse cucumber, Cucumis sativus L., and rose, Rosa × hybrida crops in southeastern France. This method is based on abundance classes of thrips observed on sampling units of flowers and foliage during a period of <1 min. Classes were calibrated using actual counts, and precision was improved by introducing additional predictive variables into multivariate nonparametric regression models. Regression models using infestation variables with and without climatic variables significantly increased calibration precision and made possible the accurate description of population dynamics. Rapid visual scouting methods could be combined for surveys of different pests and diseases. When calibrated, they provide growers or technicians with accurate tools guiding crop protection decisions.

Realistic Global Scouting for Pests and Diseases on Cut Rose Crops

ABSTRACT 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 1U/ 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.

Projection Pursuit Nonparametric Regression Applied to Field Counts of the Aphid Macrosiphum euphorbiae (Homoptera: Aphididae) on Tomato Crops in Greenhouses

Abstract The number of plants that sampling requires in aphid population studies often exceeds one hundred. Thus, only quick and nondestructive methods can be used to sample this pest in a reasonable time interval. We propose a visual method for estimating the density of the aphid Macrosiphum euphorbiae (Thomas) on tomato plants reared in greenhouses. After approximately 1 min of visual observation plants can be assigned to abundance classes, the boundaries of which are roughly the powers of 10. Precise counts were collected simultaneously on sets of reference plants from the same greenhouse. Projection pursuit nonparametric regression was then used to provide unbiased estimates of aphid densities from the abundance classes and several easily gathered explanatory variables. The robustness of the method was evaluated by testing the models on the complementary data sets from plants in which the aphid densities were precisely counted. In both single and twin-row cultural conditions, for the reference and complementary data sets, the order of magnitude of the error was less than one class rank per plant. The investigation time was reduced by approximately 10-fold compared with the exact counting method. This easy-to-teach field method could be useful in large-scale population surveys and for optimizing integrated pest management strategies.

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

1 The present study aimed to propose a method that can improve our understanding of pest outbreaks and spatio‐temporal development in greenhouse crops. 2 The experiment was carried out in a greenhouse rose crop grown under integrated pest management (IPM) for 21 months. The main pests observed were powdery mildew, two‐spotted spider mites and western flower thrips. A quick visual sampling method was established to provide continuous monitoring of overall crop health. 3 A Bayesian inferential approach was then used to analyse temporal and spatial heterogeneity in the occurrence of pests. Interactions between pest dynamics and properties of spatial evolutions were exhibited revealing the influence of biotic and abiotic factors on crop health. 4 In the context of IPM, this information could be used to improve monitoring strategies by identifying periods or locations at risk. It could also facilitate the implementation of the whole IPM procedure through the identification of key factors that have a negative impact on overall crop health.

A Bayesian Network to Prevent Mite Infestations in Rose Greenhouses

Abstract Mite infestation is a big threat for rose greenhouses. It is much easier to halt and destroy them if their future development can be predicted. Taking into account temperature, humidity, cropping practices, plant vigour and some other influent parameters, an expert is able to predict the future development of the mites. Unfortunately, not all greenhouses can call on an expert permanently to help them in their fight against mites. To help them we have developed a novel model to assess and anticipate mite invasions in greenhouses in the short term. The model, based on a Bayesian network, takes into account the environment and the parameters defining invasion status with their interactions Data have been collected using knowledge from horticultural experts. The model has been validated in real situations emanating from the field. We obtained a good correlation between forecasts and expert predictions for the 18 cases used in this study. Thus, using this model should help the growers to protect against mite outbreaks. It constitutes a framework for studies of other harmful pest invasions.