Sampling and monitoring disease in winter wheat
About this project
In a three year study some of the factors likely to affect the reliability of disease monitoring in winter wheat crops were investigated.
A novel large-scale sampling procedure using randomly positioned transects and based on the theory of autocorrelation analysis is described. The great attraction of the technique is that it allows valid tests of significance to be made on the autocorrelation coefficients calculated. The sample data obtained are also suitable for use in mapping analysis and the production of semivariograms.
Over a period of three crop seasons the spatial pattern of some common diseases of winter wheat were investigated at growth stages 31/33 and 59/61 using the techniques outlined above.
The most complete data obtained were for Septoria tritici which was found to have an essentially random pattern at the growth stages investigated. Spatial pattern of the disease was detected on a small scale in some fields which were patchy as a probable consequence of low nutrient status.
With the exception of powdery mildew at GS31/33 and yellow rust at GS59/61 the other diseases also generally exhibited a random disease pattern. For this reason random (not haphazard) sampling paths can be recommended to be an adequate method of obtaining samples for monitoring purposes. A survey of observers employed in various areas of the agricultural industry indicated that such sampling patterns are already commonly used in disease monitoring despite the advice of ADAS to sample along two diagonal transects of the field.
The reliability of visual disease severity estimates was investigated. Observers were shown to be inaccurate, inconsistent and often imprecise in their estimates of disease severity. In a comparison of the efficacy of three seed treatments on the disease severity of powdery mildew the errors described above were shown to cause the wrong conclusions to be drawn about the efficacy of the treatments relative to one another.
The use of model leaves highlighted the possibility that the precision and consistency with which assessments were made was reduced with increasing speed of assessment. It is therefore suggested that the proficiency of observers may be adversely affected by having to make large-scale disease assessments. There was also evidence that the design of disease assessment keys, being reliant on high contrast between the 'diseased' and 'healthy' areas, is fundamentally flawed.
A new key is proposed which aims to avoid some of the drawbacks of conventional disease assessment keys, but as yet the efficacy of the key is untested.
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