Determinination of Efects of Sunn Pest on Wheat Grain by Artificial Neural Networks
Wheat is a very strategic crop for Turkey as well as many other countries and sunn pest is a major constraint to the production of wheat. Sunn pest negatively affects wheat crops during their vegetative growth, heading and maturity stages. This effect causes two types of damage on wheat grain by lead...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Trakya University
2015-08-01
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| Series: | Trakya University Journal of Natural Sciences |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/en/pub/trkjnat/issue/25382/267873 |
| Summary: | Wheat is a very strategic crop for Turkey as well as many other countries and sunn pest is a major constraint to the production of wheat. Sunn pest negatively affects wheat crops during their vegetative growth, heading and maturity stages. This effect causes two types of damage on wheat grain by leading to wheat yield loss and grain quality decrease. The decrease in the quality leads in turn to production losses in many products which depends on wheat. Wheat crops therefore should be examined before the production processes in order to separate the sunn pest affected ones from non-affected ones. Such a discrimination task in Turkey is performed by experts. However, the damage can sometimes be visible but also sometimes it migth be hard to notice the damage. So, the damaged grains may not be distinguished among undamaged ones with simple eye observation. In this study, an automatic system which uses Artificial Neural Networks (ANN) to determine the wheat grains damaged by sunn pest is proposed |
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| ISSN: | 2147-0294 2528-9691 |