Department of Environmental Information and Bio Production Engineering, Kobe University, 1-1 Rokko-dai, cho, 657-8501, Japan.
Biochem Biophys Res Commun. 2010 Jul 9;397(4):685-90. doi: 10.1016/j.bbrc.2010.06.007. Epub 2010 Jun 4.
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.
利用水敏近红外光谱学（aquaphotomics）作为一种新方法，评估了在大豆花叶病毒（SMV）感染的大豆植株（Glycine max）处于无症状潜伏期时进行诊断的效果。使用了来自感染和未感染 SMV 的大豆植株的近红外（NIR）叶片光谱（范围为 730-1025nm）。所有植株的叶片样本均通过酶联免疫吸附测定（ELISA）进行分析，以确认感染。先前报道的 NIR 波段中 970nm 处的水和 NIR 中水区的两个新波段 910nm 和 936nm 被发现对感染叶片出现可见症状前 2 周的 SMV 感染非常敏感。当使用个体植株平均光谱的二阶导数时，基于软独立建模分类类比（SIMCA）的光谱校准模型预测疾病的灵敏度为 91.6%，特异性为 95.8%。该研究表明，近红外光谱学及其新方法具有阐明感染潜在生化和生物物理信息的潜力，因为它能够在疾病无症状早期成功区分 SMV 感染的植株和健康植株。
