Nondestructive Classification of Viable and Non-viable Radish (Raphanus sativus L) Seeds using Hyperspectral Reflectance Imaging

Abstract

Purpose: Nondestructive evaluation of seed viability is a highly demanded technique in the seed industry. In this study, hyperspectral imaging system was used for discrimination of viable and non-viable radish seeds. Method: The spectral data with the range from 400 to 1000 nm measured by hyperspectral reflectance imaging system were used. A calibration and a test models were developed by partial least square discrimination analysis (PLS-DA) for classification of viable and non-viable radish seeds. Either each data set of visible (400~750 nm) and NIR (750~1000 nm) spectra and the spectra of the combined spectral ranges were used for developing models. Results: The discrimination accuracy of calibration was 84% for visible range and 76.3% for NIR range. The discrimination accuracy of test was 84.2% for visible range and 75.8% for NIR range. The discrimination accuracies of calibration and test with full range were 92.2% and 92.5%, respectively. The resultant images based on the optimal PLS-DA model showed high performance for the discrimination of the nonviable seeds from the viable seeds with the accuracy of 95%. Conclusions: The results showed that hyperspectral reflectance imaging has good potential for discriminating nonviable radish seeds from massive amounts of viable seeds.

Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with Multivariate Data Analysis

“…With the improvement of the available instrumentation and analytical techniques in the last decade, some researchers have dedicated themselves to detecting seed viability and vigor by using NIR spectroscopy [ 18 ]. Viability detection studies of the seeds of grains [ 19 , 20 , 21 , 22 , 23 , 24 ], vegetables [ 11 , 25 , 26 , 27 , 28 , 29 , 30 ], and fruit [ 31 , 32 , 33 ] have successfully used NIR spectroscopy or a related technique to discriminate nonviable from viable seeds with high prediction accuracies. To the best of our knowledge, no research has been published to date regarding the use of NIR spectroscopy for supersweet corn seed viability detection.…”

Hyperspectral Reflectance Imaging Technique for Visualization of Moisture Distribution in Cooked Chicken Breast

“…Hyperspectral imaging (HSI) is a three-dimensional technique, consisting of both images and spectra, which yields physical and chemical information. These hyperspectral techniques are the best potential tool for measuring the water content and distribution in the meat samples [ 9 ]. This information cannot be obtained using any other conventional technique.…”

Assessment of seed quality using non-destructive measurement techniques: a review

“…Most of these studies have reported accuracies of more than 90% in viable seed identification. Hyperspectral imaging systems have also been used for accurate and reliable discrimination of viable and non-viable seeds of corn (Ambrose et al ., 2016), radish (Ahn et al ., 2012), watermelon (Bae et al ., 2016) and pepper (Mo et al ., 2014) with accuracies of 95.6, 95, 84.2 and 99.4%, respectively. Recently, a hyperspectral fluorescence imaging technique was used to extract the fluorescence spectra of cucumber seeds in the 425–700 nm range to discriminate between viable and non-viable cucumber seeds using four types of algorithms.…”