Automated Detection of <i>Tetranychus urticae</i> Koch in Citrus Leaves Based on Colour and VIS/NIR Hyperspectral Imaging

Abstract

Tetranychus urticae Koch is an important citrus pest that produces chlorotic spots on the leaves and scars on the fruit of affected trees. It is detected by visual inspection of the leaves. This work studies the potential of colour and hyperspectral imaging (400–1000 nm) under laboratory conditions as a fast and automatic method to detect the damage caused by this pest. The ability of a traditional vision system to differentiate this pest from others, such as Phyllocnistis citrella, and other leaf problems such as those caused by nutritional deficiencies, has been studied and compared with a more advanced hyperspectral system. To analyse the colour images, discriminant analysis has been used to classify the pixels as belonging to either a damaged or healthy leaves. In contrast, the hyperspectral images have been analysed using PLS DA. The rate of detection of the damage caused by T. urticae with colour images reached 92.5%, while leaves that did not present any damage were all correctly identified. Other problems such as damage by P. citrella were also correctly discriminated from T. urticae. Moreover, hyperspectral imaging allowed damage caused by T. urticae to be discriminated from healthy leaves and to distinguish between recent and mature leaves, which indicates whether it is a recent or an older infestation. Furthermore, good results were achieved in the discrimination between damage caused by T. urticae, P. citrella, and nutritional deficiencies.

Keywords

• two-spotted spider mite
• red spider mite
• integrated pest management
• citrus damage
• optical sensors
• image processing