Variety Identification of Single Rice Seed Using Hyperspectral Imaging Combined with Convolutional Neural Network

Zhengjun Qiu,Yiying Zhao,Jian Chen,Chu Zhang,Yong He,Susu Zhu

doi:10.3390/app8020212

Zhengjun Qiu, Yiying Zhao + Show 4 more

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https://doi.org/10.3390/app8020212

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Abstract

The feasibility of using hyperspectral imaging with convolutional neural network (CNN) to identify rice seed varieties was studied. Hyperspectral images of 4 rice seed varieties at two different spectral ranges (380–1030 nm and 874–1734 nm) were acquired. The spectral data at the ranges of 441–948 nm (Spectral range 1) and 975–1646 nm (Spectral range 2) were extracted. K nearest neighbors (KNN), support vector machine (SVM) and CNN models were built using different number of training samples (100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500 and 3000). KNN, SVM and CNN models in the Spectral range 2 performed slightly better than those in the Spectral range 1. The model performances improved with the increase in the number of training samples. The improvements were not significant when the number of training samples was large. CNN model performed better than the corresponding KNN and SVM models in most cases, which indicated the effectiveness of using CNN to analyze spectral data. The results of this study showed that CNN could be adopted in spectral data analysis with promising results. More varieties of rice need to be studied in future research to extend the use of CNNs in spectral data analysis.

Highlights

Rice is one of the most common food crops planted in China and some other countries
Discriminant models were built by K-nearest neighbor (KNN), support vector machine (SVM) and convolutional neural network (CNN) models
200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500 and 3000 samples selected from the total training samples of each rice seed variety were used to build discriminant models, and the test set for training samples of each rice seed variety were used to build discriminant models, and the test set above-mentioned models were all the same (2664, 2394, 1933, and 1916 rice seeds of Xiushui 134, for above-mentioned models were all the same (2664, 2394, 1933, and 1916 rice seeds of Xiushui 134, Zhejing 99, Zhongjiazao 17 and Zhongzao 39) for different number of training samples

Summary

Introduction

Rice is one of the most common food crops planted in China and some other countries. Rice seeds are harvested as food to consumers and as seed for the following sowing season. Due to the vast planting areas across villages, towns, countries and continents, different varieties of rice seeds are developed to adapt to changes of growth environments (climates, soil, water, etc.) and improve nutrition and flavors. With the development of breeding techniques, more varieties of rice seeds are brought into the market, and the purity of rice seeds is critical for planters and consumers. Different varieties of rice seed vary in physical and chemical characteristics, growth performances and stress tolerance. Rice seed varieties can be identified by inspecting the appearance characteristics such as size, color, shape and texture, or by determining the quality attributes such as protein, starch and aroma. Traditional methods for rice variety identification, like High Performance Liquid

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