4.7 Article

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

Journal

AGRONOMY-BASEL
Volume 11, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/agronomy11051002

Keywords

two-spotted spider mite; red spider mite; integrated pest management; citrus damage; optical sensors; image processing; automated monitoring pest

Funding

  1. Generalitat Valenciana-Instituto Valenciano de Investigaciones Agrarias (GVA-IVIA) project [51918]
  2. European Regional Development Funds (ERDF)
  3. INIA - European Social Funds (FSE) [CPD2016-0007]

Ask authors/readers for more resources

This study explores the potential of color and hyperspectral imaging techniques in detecting the damage caused by Tetranychus urticae Koch on citrus trees. Color images achieved a detection rate of 92.5% for damaged leaves, while hyperspectral imaging allowed discrimination between damaged and healthy leaves, as well as differentiating between recent and mature infestations. Additionally, good results were obtained in discriminating damage caused by T. urticae, P. citrella, and nutritional deficiencies.
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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available