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External defects and severity level evaluation of potato using single and multispectral imaging in near infrared region Author links open overlay panel

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摘要 Non-invasive potato defects detection has been demanded for sorting and grading purpose.Researches on the classification of the defects has been available,however,investigation on the severity level calculation is limited.For the detection of the common scab,it has been found that imaging in the infrared region provide an interesting characteristic that could distinguish defected area to normal area.Thus,investigations on this wavelength range is interesting to add more knowledge and for applications.In this research,the multispectral image has been obtained and investigated especially at three wavelengths(950,1150,1600 nm).Image pre-processing and pseudo-color conversion techniques were explored to enhance the contrast between defects,normal background skin area and soil deposits.Results show that external defects,such as common scab and some mechanical damage types,appear brighter in the near infrared region,especially at 1600 nm against the normal skin background.It has been found that pseudo-color images conversion provides more information regarding type if surface characteristics compared to grayscale single imaging.Image segmentation using pseudo-color images after multiplication operation pre-processing could be used for common scab and mechanical damage detection excluding soil deposits with a Dice Sorensen coefficient of 0.64.In addition,image segmentation using single image at 1600 nm shown relatively better results with Dice Sorensen coefficient of 0.72 with note that thick soil deposits will also be segmented.Defect severity level evaluation had an R2 correlation of 0.84 against standard measurements of severity.
出处 《Information Processing in Agriculture》 EI CSCD 2024年第1期80-90,共11页 农业信息处理(英文)
基金 Japan Government Cross-Ministerial Strategic Innovation Promotion Program-Smart Bio Industry and Agricultural Fundamental Technology(SIP-2:Consortium,Smart Food Chain).
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  • 1谢建华.我国马铃薯生产现状及发展对策[J].中国农技推广,2007,23(5):4-7. 被引量:78
  • 2程国首,郭俊先,肉孜·阿木提,等.基于高光谱图像技术预测苹果大小[J].农机化研究,2012,34(6):108-112.
  • 3Peiris K It S, Dull G G, l.etfler R G, et :d. Spatial variability of sol- uble solids or dry-matter content within individual fruits, bulbs, or bubes: Implications for the development and use oi NtR spectro metric techniques[J] Hort Science,1999,34(1)= 114:118.
  • 4Angel D N, Arno F, Pilar C, et ah Common scab detection on potatoes using an in[rared hyperspectral imaging system[J]. Image Analysis and Processing, 2011,6 979(1) : 303:31Z.
  • 5Angel D N, Arno F, Pilaf C, et al. Non destructive detection of hollow heart in potatoes using hyperspectral imaging[J]. Image A nalysis and Processing, 2011,6 855( 1 ) : 1804 187.
  • 6Ray SS, Jain N, Arorar K, et al. Utility of hyperspectral data for potato late blight disease detection[J], Indian Soc Remote Sons, 2011,39(2) : 1614169.
  • 7N Nguyen Do Trong, M Tsuta, B M NicolaS, el al. Prediction of optinml cooking time for boiled potatoes by hyperspectral im aging[J]. Journal of Food Engineering, 2011,105(4): 617 624.
  • 8中华人民共和酬农业部.NY/T]0662006马铃薯等级规格[M].北京:中国农业出版社,2006.
  • 9赵杰文,刘剑华,陈全胜,Saritporn Vittayapadung.利用高光谱图像技术检测水果轻微损伤[J].农业机械学报,2008,39(1):106-109. 被引量:105
  • 10郭恩有,刘木华,赵杰文,陈全胜.脐橙糖度的高光谱图像无损检测技术[J].农业机械学报,2008,39(5):91-93. 被引量:55

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