Articles
Development of a vision and image analysis system to evaluate the natural regulation of crop pests
Article number
1360_11
Pages
85 – 90
Language
English
Abstract
Natural pest regulation is still difficult to evaluate because of methodological difficulties, especially in quantifying predation.
The lack of an indicator for this ecosystem service leads to its underutilization for the reduction of plant protection products in all types of crops.
The Mirage project (2019-2023) aims to remove this methodological barrier by combining a macro camera and automatic image analysis.
A prototype camera, called Beecam®, has been designed to produce high-definition videos and photos (8 MPixels).The overall footage is dramatically reduced by using real-time in-image motion detection. Two synchronized sensors allow close observation of up to a few cm2. The sensitivity is very high so that sub-millimetre insect movements are detected.
To process all these data produced by this camera, a neural network was developed for automatic classification of insects on still photos, of 20 taxa of natural enemies from a database of 8000 photos, some of which were obtained with the prototype camera and others from partners database.
Improving the performance of the software, called Harmony, is ongoing as well as adding to the number of identifiable taxa.
The performance of this tool is currently being tested on different stages of the main pests of annual and perennial crops, which are filmed in the field during the immobile phase.
The first results show that it offers interesting perspectives to identify new trophic relationships and to better quantify them.
The transfer potential of this tool will be evaluated in teaching, in experimentation (effect of agroecological practices and developments on natural regulation) and in crop management.
The lack of an indicator for this ecosystem service leads to its underutilization for the reduction of plant protection products in all types of crops.
The Mirage project (2019-2023) aims to remove this methodological barrier by combining a macro camera and automatic image analysis.
A prototype camera, called Beecam®, has been designed to produce high-definition videos and photos (8 MPixels).The overall footage is dramatically reduced by using real-time in-image motion detection. Two synchronized sensors allow close observation of up to a few cm2. The sensitivity is very high so that sub-millimetre insect movements are detected.
To process all these data produced by this camera, a neural network was developed for automatic classification of insects on still photos, of 20 taxa of natural enemies from a database of 8000 photos, some of which were obtained with the prototype camera and others from partners database.
Improving the performance of the software, called Harmony, is ongoing as well as adding to the number of identifiable taxa.
The performance of this tool is currently being tested on different stages of the main pests of annual and perennial crops, which are filmed in the field during the immobile phase.
The first results show that it offers interesting perspectives to identify new trophic relationships and to better quantify them.
The transfer potential of this tool will be evaluated in teaching, in experimentation (effect of agroecological practices and developments on natural regulation) and in crop management.
Authors
J.-M. Ricard, G. Sentenac, A. Guerin, P. Masquin, A. Ferre, A. Fougère, V. Tosser, J. Marks-Perreau, T. Corbière, G. Duclos, A. Gardarin, L. Girerd
Keywords
natural regulation of crop pests, camera, video recording, automatic classification, neural network
Groups involved
- Division Precision Horticulture and Engineering
- Division Plant-Environment Interactions in Field Systems
- Division Vine and Berry Fruits
- Division Tropical and Subtropical Fruit and Nuts
- Division Plant Genetic Resources, Breeding and Biotechnology
- Division Temperate Tree Nuts
- Division Temperate Tree Fruits
- Division Vegetables, Roots and Tubers
- Division Sustaining Horticulture in a Changing World
- Working Group Mechanization, Digitization, Sensing and Robotics
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