2016
DOI: 10.1002/jsfa.7832
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Non‐destructive evaluation of bacteria‐infected watermelon seeds using visible/near‐infrared hyperspectral imaging

Abstract: The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds. © 2016 Society of Chemical Industry.

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Cited by 46 publications
(27 citation statements)
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“…Because of these advantages, HSI has been successfully applied in various tasks involving seeds, such as classication of seed varieties, detection of seed vigor, identication of seed diseases. [8][9][10] As far as we know, no research has reported the application of HSI on varieties identication of oat seeds.…”
Section: Introductionmentioning
confidence: 99%
“…Because of these advantages, HSI has been successfully applied in various tasks involving seeds, such as classication of seed varieties, detection of seed vigor, identication of seed diseases. [8][9][10] As far as we know, no research has reported the application of HSI on varieties identication of oat seeds.…”
Section: Introductionmentioning
confidence: 99%
“…The characteristics of batch detection extend its application in the modern seed industry. Recently, HSI has been used in quality assessment of agricultural seeds, such as for variety and geographical origin identification [ 14 , 15 ], viability and vigor prediction [ 16 ], bacterial and fungal infection [ 17 , 18 ], etc. As for variety discrimination, the number of seeds should be sufficient to contain a broad variation, which will consequently result in high computational cost.…”
Section: Introductionmentioning
confidence: 99%
“…SVM is a supervised machine learning method, which is efficient to deal with linear and nonlinear data for classification and regression. For classification issues, SVM maps the original data into new feature spaces [ 31 , 32 , 33 ]. According to linearly separable data, a simple linear classifier can be constructed.…”
Section: Methodsmentioning
confidence: 99%