Detection of cucumber green mottle mosaic virus-infected watermelon seeds using a near-infrared (NIR) hyperspectral imaging system: Application to seeds of the “Sambok Honey” cultivar

Abstract

The cucurbit diseases caused by cucumber green mottle mosaic virus (CGMMV) have led to a serious problem to growers and seed producers because it is difficult to prevent spreading through pathogen-infected seeds. Conventional detection methods for infected seeds such as biological, serological, and molecular measurements are not practical for measuring entire samples due to their destructive nature, and time, and cost issues. For this reason, it is necessary to develop a rapid and non-destructive novel technique for detecting seeds infestation. A near-infrared (NIR) hyperspectral imaging system was used to discriminate virus-infected seeds from healthy seeds with partial least square discriminant analysis (PLS-DA) and least square support vector machine (LS-SVM). The classification accuracy for virus-infected watermelon seeds were 83.3% with the best model, demonstrating the potential of NIR hyperspectral imaging for detection of virus-infected watermelon seeds.

Plant phenotyping relevance

NIRハイパースペクトル画像と分類モデルを用いて、スイカ種子のウイルス感染状態を非破壊推定する手法が研究の中心であり、植物の病害状態を直接評価している。

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