Early on-site detection of strawberry anthracnose using portable Raman spectroscopy.

Abstract

We developed a method for the early on-site detection of strawberry anthracnose using a portable Raman system with multivariate statistical analysis algorithms. By using molecular markers based on Raman spectra, the proposed method can detect anthracnose in strawberry stems 3 days after exposure to Colletotrichum gloeosporioides. A fiber-optic probe was applied for the portable Raman system, and the acquisition time was 10 s. We found that the molecular markers were closely related to the following subjects: i) an increase in amide III and fatty acids of C. gloeosporioides invading strawberry stems (Raman bands at 1180-1310 cm -1 ) and ii) a decrease in metabolites in strawberry plants, such as phenolic compounds and terpenoids (Raman bands at 760, 800, and 1523 cm -1 ). We also found that the increased fluorescence background caused by various chromophores within the invading C. gloeosporioides could serve as a marker. A two-dimensional cluster plot obtained by principal component analysis (PCA) showed that the three groups (control, fungal infection, and pathogen) were distinguishable. The linear discriminant analysis (LDA)-based prediction algorithm could identify C. gloeosporioides infection with a posterior probability of over 40%, even when no symptoms were visible on the inoculated strawberry plants.

Plant phenotyping relevance

携帯型ラマン分光と統計解析を用いて、症状出現前のイチゴ茎における炭疽病感染状態を検出する手法の開発が研究の中心であり、植物病害状態のフェノタイピングに該当する。

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