Abstract
Skinning injury on potato tubers is a kind of superficial wound that is generally inflicted by mechanical forces during harvest and postharvest handling operations. Though skinning injury is pervasive and obstructive, its detection is very limited. This study attempted to identify injured skin using two CCD (Charge Coupled Device) sensor-based machine vision technologies, i.e., visible imaging and biospeckle imaging. The identification of skinning injury was realized via exploiting features extracted from varied ROIs (Region of Interests). The features extracted from visible images were pixel-wise color and texture features, while region-wise BA (Biospeckle Activity) was calculated from biospeckle imaging. In addition, the calculation of BA using varied numbers of speckle patterns were compared. Finally, extracted features were implemented into classifiers of LS-SVM (Least Square Support Vector Machine) and BLR (Binary Logistic Regression), respectively. Results showed that color features performed better than texture features in classifying sound skin and injured skin, especially for injured skin stored no less than 1 day, with the average classification accuracy of 90%. Image capturing and processing efficiency can be speeded up in biospeckle imaging, with captured 512 frames reduced to 125 frames. Classification results obtained based on the feature of BA were acceptable for early skinning injury stored within 1 day, with the accuracy of 88.10%. It is concluded that skinning injury can be recognized by visible and biospeckle imaging during different stages. Visible imaging has the aptitude in recognizing stale skinning injury, while fresh injury can be discriminated by biospeckle imaging.
Highlights
Potato is regarded as the fourth most important food crop around the world after wheat, rice and maize, due to its great yield production and high nutritive value [1]
Experiment Results Obtained from Biospeckle Imaging became more violent during this time
This paper presents the discrimination of sound skin (SS) and injured skin (IS) using CCD-based visible and biospeckle imaging techniques
Summary
Potato is regarded as the fourth most important food crop around the world after wheat, rice and maize (corn), due to its great yield production and high nutritive value [1]. Quality and nutrition of potato tubers can be adversely affected by mechanical damages, which happen frequently during the handling chain from harvest, storage, and transport to packaging. Skinning injury is related to excoriation of potato skin. Potato periderm is composed of three cell layers: phellem, phellogen and phelloderm [2]. Well-organized suberized cells constitute phellem, which is referred to as skin. According to Lulai [3], the resistance to skinning injury is determined by phellem (skin) tensile-related fractures and phellogen shear-related fractures, where the force required for fracture of the phellogen cell walls is dominant. Skinning injury is one kind of superficial damage on potatoes that can result in the fracture of phellogen cell walls of the native periderm and loss of Sensors 2016, 16, 1734; doi:10.3390/s16101734 www.mdpi.com/journal/sensors
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