From Event: SPIE Commercial + Scientific Sensing and Imaging, 2018
Despite the complexity of the factors that lead to loss of seed viability, conventional methods like germination tests, tetrazolium tests are commonly employed to determine it. However, these methods have downsides like being destructive, time consuming and non-representative. Therefore, there is a need to develop a fast, non-destructive and real-time measurement and sorting system of seeds based on viability for industrial purpose. In this study, we seek to utilize HSI and multivariate data analysis techniques to classify viable seeds from non-viable ones and later use it basis to develop an online real-time detection system for sorting these seeds based on viability. For this cause, Data from melon and watermelon seeds were collected using a SWIR HSI system. The performance of the classification models achieved both during calibration and real-time tests were quite impressive and a proof that HSI can be effectively applied to an industrial real-time sorting system.
Collins Wakholi, Hoonsoo Lee, Insuck Baek, Eunsoo Park, Moon S. Kim, Hyungjin Bae, and Byoungkwan Cho, "Real-time sorting of melon seed using hyperspectral shortwave infrared imaging (Conference Presentation)," Proc. SPIE 10665, Sensing for Agriculture and Food Quality and Safety X, 106650I (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 18, 2018; Published: 15 May 2018); https://doi.org/10.1117/12.2307699.5783315377001.
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Study of self-shadowing effect as a simple means to realize nanostructured thin films and layers with special attentions to birefringent obliquely deposited thin films and photo-luminescent porous silicon