NonDestructive Assay Of Vital Wheat Quality Parameters Using Spectroscopic Techniques

Abstract

Near InfraRed Spectroscopy (NIRS) techniques are being perfected over ages for the quantitative and qualitative analysis on a melange of biological systems. In this research, efforts are made to investigate various combinations of preprocessing, prediction and classification techniques used for the quality analysis and variety classification of wheat grains. This study focuses on the selection of optimum classification algorithms, as an automated variety identifier suitable for wheat grains based on the statistical performance indices. newline newline newlineNIRS techniques find immense applications in the field of pharmacy, medicine, agriculture and food. The evaluation of a biological substance in a non-destructive and rapid way is done by analysing a near infrared spectrum with chemometrics. The quality parameters of wheat grains also need to be analysed in a fast, cost effective way with dependable diagnostic quality. In order to achieve reduction of testing time and labour-intensive procedure, efficient prediction algorithms with good accuracy results are needed. newline newline newlineRecent developments in the other major branch of non- destructive studies has paved way to the usage of image analysis widely in the field of wheat grain analysis. Structural analysis focuses on the visualization aspect of the wheat grains such as the shape, size (learnt from the length, width, and height), colour and glossiness of the seed coat. The shape and size details of the grain cannot be obtained from spectral details, while the colour and texture can be studied from NIR spectra. A much clear idea of the mentioned parameters will help define the varietal newline newline newline newlinecharacteristics. In addition to the spectral information, the image derived characteristics are incorporated into the classification models to further enhance the variety identification. newline newline newlineIn this work, a hand-picked wheat database has been created with wheat varieties from different regions of India harvested in the year newline2015-16 and 2016-17. The samples from varied years, geographical locations and occupy