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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Compartmentalization of New Released and Old Wheat Cultivars (Triticum Durum & Triticum Aestivum) of Gujarat Region of India by Employing Computer Vision
verfasst von : Mayur P. Raj, P. R. Swaminarayan, Jatinderkumar Saini
Erschienen in: Smart Trends in Information Technology and Computer Communications
Verlag: Springer Nature Singapore
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Abstract
Machine learning methods majorly comprise of image processing and soft computing methods and are mainly responsible for automation. Wheat production is influenced by assorted varying factors. Sorting or grading of agricultural products influenced by computer varies product wise and even product variety wise which itself changes region wise. Grading for new varieties released by the agricultural scientists is the major concern as new varieties are produced by crossing existing varieties. For these varieties, proven optimized machine learning algorithms may give an adverse result. This paper introduces machine learning algorithm capable of classifying major 5 wheat cultivars cultivated in Gujarat region of India. Experimental data consist of 11 traits comprising of shape, color and morphological characteristics. After applying feature selection algorithm, 5 traits were considered and Levenberg-Marquardt back propagation was employed to classify above wheat cultivars which ensued to more than 90% overall accuracy.