Alastair McCartney

Early Disease Detection in Wheat Fields using Spectral Reflectance

The difference in spectral reflectance between healthy and diseased wheat plants infected with Puccinia striiformis (yellow rust) was investigated. In-field spectral images were taken with a spectrograph mounted at spray boom height. A normalisation method based on reflectance and illumination adjustments was applied. To consider the entire canopy reflection, a spatially moving average was introduced. A classification model based on quadratic discrimination was built on a selected group of wavebands obtained by stepwise variable selection. Through this method, confusion rates dropped from 12 to 4% error classification, based on four different wavebands. These results are very encouraging for the development of a cost-effective optical device for recognising diseases, such as yellow rust, in the field in early spring.

Field measurements of airborne concentration and deposition rate of maize pollen

In recent years there has been interest in the dispersal of maize (Zea mays) pollen from crops, particularly in relation to gene flow and seed quality. We report the results of experiments that measured maize pollen dispersal from a 20 m x 20 m experimental crop. The experiments were done in a commercial farm in France during the summer of 2000. Pollen production was estimated to range from 10(4) to 2 x 10(6) grains per day per plant. Pollen concentrations and deposition rates decreased rapidly with distance from the crop: concentrations decreased by about a factor of 3 between 3 and 10 m downwind of the source deposition rates at 30 m were < 10% of those at 1 m. Horizontal flux of pollen were estimated from pollen concentration and wind speed profiles using a mass balance approach, and ranged from 15 to 560 grains m-1 s-1 at 3 m from the source. Comparison of deposition rates estimated with the mass balance and direct measurement suggests that only a small proportion of the pollen released from the crop would have been still airborne at distances greater than 30 m downwind. Deposition velocity determined as the ratio of the deposition rate to the airborne concentration at 3 m from the source averaged 0.6 m s-1, which is twice as large as the settling velocity for maize pollen.

A polymerase chain reaction (PCR) assay for the detection of inoculum of Sclerotinia sclerotiorum

The development of a polymerase chain reaction (PCR) assay for the detection of inoculum of the plant pathogenic fungus Sclerotinia sclerotiorum is described. The PCR primers were designed using nuclear ribosomal DNA internal transcribed spacer sequences. Specific detection of DNA from S. sclerotiorum was possible even in the presence of a 40-fold excess of DNA from the closely related fungus Botrytis cinerea. PCR products were obtained from suspensions of untreated S. sclerotiorum ascospores alone, but DNA purification was required for detection in the presence of large numbers of B. cinerea conidiospores. Specific detection of inoculum of S. sclerotiorum was possible in field-based air-samples, using a Burkard spore trap, and from inoculated oilseed rape petals. The assay has potential for incorporation into a risk management system for S. sclerotiorum in oilseed rape crops.

Detection of airborne fungal spores sampled by rotating-arm and Hirst-type spore traps using polymerase chain reaction assays

AbstractConventional methods for detectingairborne fungal spores rely on either optical identication orculturingand can be time consumingor unreliable. A method for purifyingDNA from conventionalsporesamplersanddetectingitusingpolymerasechainreaction(PCR)assaysisdescribed.Experimentswere done using Penicillium roqueforti. As few as 10 spores could be detected in the PCR andP.roquefortisporesweredetectedinabackgroundofsporesofsixotherunrelatedspecies.Themethodsuccessfully detected P. roqueforti spores collected by rotatingarm and Hirst-type spore traps in windtunnel tests. The tests suggested that the detection limit was about 10 spores or less in the PCR. Fungalspores were also detected in air samples collected in Mexico City usingfungal consensus primers, witha detection limit of about 200 spores in the PCR. The potential for usingPCR-assays in conjunctionwith impactor samplers is discussed. c 2001 Elsevier Science Ltd. All rights reserved. 1. IntroductionBioaerosolsmaycausearangeofhealtheectsinhumansandanimals,dependingonthepre-dominant components present and their concentrations. Such eects include mucous membraneirritation, chronic bronchitis, allergic rhinitis and asthma, extrinsic allergic alveolitis (hyper-sensitivity pneumonitis), inhalation fever, humidier fever or organic dust toxic syndrome and

Simultaneous identification of plant stresses and diseases in arable crops using proximal optical sensing and self-organising maps

The objective of this research was to detect plant stress caused by disease infestation and to discriminate this type of stress from nutrient deficiency stress in field conditions using spectral reflectance information. Yellow Rust infected winter wheat plants were compared to nutrient stressed and healthy plants. In-field hyperspectral reflectance images were taken with an imaging spectrograph. A normalisation method based on reflectance and light intensity adjustments was applied. For achieving high performance stress identification, Self-Organising Maps (SOMs) and Quadratic Discriminant Analysis (QDA) were introduced. Winter wheat infected with Yellow Rust was successfully recognised from nutrient stressed and healthy plants. Overall performance using five wavebands was more than 99%.

First field evidence that parasitoids use upwind anemotaxis for host‐habitat location

The direction of flight of natural populations of Phradis interstitialis (Thomson), Tersilochus obscurator Aubert (both Hymenoptera: Ichneumonidae), and Platygaster subuliformis (Kieffer) (Hymenoptera: Platygastridae), parasitoids of three crucifer‐specialist herbivores, to and from their hosts’ host plant [oilseed rape, Brassica napus L. (Brassicaceae)] was studied in the field within a heterogeneous arable environment. Double‐sided Malaise traps encircling a plot of winter oilseed rape (cultivar Lutin) were used to sample the parasitoids as they flew towards and away from the plot during spring and summer. Daily trap catch of parasitoids and trap air flow were compared using Spearmans rank correlation. For all 14 insect days analysed, and for each species, the correlations between daily catch of parasitoids into distal halves of traps (relative to the plot) and wind direction were negative, significantly so on half the days analysed. This confirmed that flights towards the plot were by upwind anemotaxis. In contrast, the correlations between daily catch of parasitoids into proximal halves of traps (relative to the plot) and wind direction were most often crosswind; they were never strongly nor significantly either negative or positive. Implications of the results for integrated pest management strategies incorporating biological control with these parasitoids are discussed.

Migration to and dispersal from oilseed rape by the pollen beetle, Meligethes aeneus, in relation to wind direction

1 Host‐plant‐odour‐induced upwind anemotaxis is accepted as the main mechanism by which herbivorous insects find their host plant within an heterogenous environment, but field data supporting this hypothesis are scarce.

Detection of foliar disease in the field by the fusion of measurements made by optical sensors

The objective of this research was to detect and recognize plant stress caused by disease in field conditions by combining hyperspectral reflection information between 450 and 900nm and fluorescence imaging. The aim is to develop a tractor mounted cost-effective optical device for site-specific pesticide application in order to reduce and optimize pesticide use. The work reported here used yellow rust (Puccinia striiformis) disease of winter wheat as a model system. In the field hyperspectral reflection images of healthy and infected plants were taken with an imaging spectrograph mounted at spray boom height. Leaf recognition and spectral normalization procedures to account for differences in canopy architecture and spectral illumination were used. A model, based on quadratic discrimination, was built, using a selected group of wavebands to differentiate diseased from healthy plants. The model could discriminate diseased from healthy crop with an error of about 10% using measurements from only three wavebands. Multispectral fluorescence images were taken on the same plants using UV-blue excitation. Through comparison of the 550 and 690 nm fluorescence images, it was possible to clearly detect disease presence. The fraction of pixels in one image, recognized as diseased, was set as final fluorescence disease variable called the lesion index LI). The lesion index was added to the pool of normalized selected reflection wavebands. This pool of observations was used in a quadratic discrimination model. This model was further refined using a neural network approach. The combined model improved disease discrimination compared to either the spectral model or fluorescent model and had a classification error of between 1 and 2 %. The results suggest that there is potential for developing detection systems based on multisensor measurements that can be used to in precision disease control systems for use in arable crops.