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Near infrared spectroscopy and aquaphotomics: Novel approach for rapid in vivo diagnosis of virus infected soybean.

机译:近红外光谱法和水生照相术:用于体内快速诊断病毒感染大豆的新方法。

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Near infrared spectroscopy with aquaphotomics as a novel approach was assessed for the diagnosis of soybean plants (Glycine max) infected with soybean mosaic virus (SMV) at latent symptomless stage of the disease. Near infrared (NIR) leaf spectra (in the range of 730-1025nm) acquired from soybean plants with and without the inoculation of SMV were used. Leaf samples from all plants were assayed with enzyme-linked immunosorbent assay (ELISA) to confirm the infection. Previously reported NIR band for water at 970nm and two new bands at 910nm and 936nm in the water specific region of NIR were found to be markedly sensitive to the SMV infection 2weeks prior to the appearance of visual symptoms on infected leaves. The spectral calibration model soft independent modeling of class analogy (SIMCA), predicted the disease with 91.6% sensitivity and 95.8% specificity when the second order derivative of the individual plant averaged spectra were used. The study shows the potential of NIR spectroscopy with its novel approach to elucidate latent biochemical and biophysical information of an infection as it allowed successful discrimination of SMV infected plant from healthy at the early symptomless stage of the disease.
机译:评估了以水生植物学作为一种新方法的近红外光谱技术,用于诊断在疾病潜伏期无症状的大豆花叶病毒(SMV)感染的大豆植物(Glycine max)。使用从接种和未接种SMV的大豆植物获得的近红外(NIR)叶光谱(在730-1025nm范围内)。用酶联免疫吸附测定法(ELISA)测定所有植物的叶片样品,以确认感染。先前报道的在970nm处的水的NIR谱带以及在NIR特定水域的两个新的910nm和936nm谱带在感染叶片出现视觉症状之前两周对SMV感染非常敏感。光谱校准模型采用类比法(SIMCA)进行软独立建模,使用单个植物平均光谱的二阶导数预测该病的敏感性为91.6%,特异性为95.8%。这项研究显示了NIR光谱学以其新颖的方法阐明感染的潜在生化和生物物理信息的潜力,因为它可以在疾病的早期无症状阶段成功地将SMV感染植物与健康植物区分开。

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