Identifying Wheat Breed Genotype using CNN & LSTM

Author(s)	Ms. Pavithra U, Ms. Shireesha S, Obulesh G, Mr. Pavan Kumar S, R. Sreenivasulu
Country	India
Abstract	Image processing has been applied to various process of agriculture industry in order to achieve fast and accurate operation. applying image processing techniques to classify wheat seeds based on their varieties is also objective method in real time applications can provide additional knowledge in their production, seeds quality control and in impurities identification. Also, it is very important to confirm the variety of the wheat before planting. Because each variety needs its own condition for taking good yield. In this study, a method is proposed to identify the varieties grown by using image analysis techniques, with the motivation of developing a fully automatic grain type and variety identification system. the sun pest is a major threat to agriculture, as it damages some of the most important crop varieties. this distinctive characteristic makes the datasets especially suitable for application such as sun pest damage detection and grain segmentation. Since the dataset includes various cultivars, it is also appropriate for segmentation.
Keywords	deep learning, convolutional neural networks, long short term memory, wheat, genotype identification.
Field	Engineering
Published In	Volume 16, Issue 4, October-December 2025
Published On	2025-12-06

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