Analysis on Spectral Matching of Biochemical Component for Rice

The protein, starch and amylose are three important indexes to characterize rice quality. The starch, crude protein and amylose of rice were extracted by experiments. The hyperspectral reflectance of starch, crude protein and amylose, their mixed samples and rice samples were determined by a ASD FieldSpec Pro FR™ The spectral characteristics of starch, crude protein, amylose and their correlation with component content were analyzed by using spectral matching technique and multivariate statistical method. The results showed that the spectra of three biochemical components were significantly different, and the spectral peaks and valleys of the mixed samples showed “red shift” or “blue shift”. The contents (%) of crude protein, starch and amylose in rice flour were significantly related to the absorption area S between 2020nm and 2235nm on their spectral curve. The results showed that the hyperspectral method could be used to estimate the contents of crude protein, starch and amylose content in rice, and then to detect rice quality.

Gene Validation and Remodelling Using Proteogenomics of Phytophthora cinnamomi, the Causal Agent of Dieback

Phytophthora cinnamomi is a pathogenic oomycete that causes plant dieback disease across a range of natural ecosystems and in many agriculturally important crops on a global scale. An annotated draught genome sequence is publicly available (JGI Mycocosm) and suggests 26,131 gene models. In this study, soluble mycelial, extracellular (secretome), and zoospore proteins of P. cinnamomi were exploited to refine the genome by correcting gene annotations and discovering novel genes. By implementing the diverse set of sub-proteomes into a generated proteogenomics pipeline, we were able to improve the P. cinnamomi genome annotation. Liquid chromatography mass spectrometry was used to obtain high confidence peptides with spectral matching to both the annotated genome and a generated 6-frame translation. Two thousand seven hundred sixty-four annotations from the draught genome were confirmed by spectral matching. Using a proteogenomic pipeline, mass spectra were used to edit the P. cinnamomi genome and allowed identification of 23 new gene models and 60 edited gene features using high confidence peptides obtained by mass spectrometry, suggesting a rate of incorrect annotations of 3% of the detectable proteome. The novel features were further validated by total peptide support, alongside functional analysis including the use of Gene Ontology and functional domain identification. We demonstrated the use of spectral data in combination with our proteogenomics pipeline can be used to improve the genome annotation of important plant diseases and identify missed genes. This study presents the first use of spectral data to edit and manually annotate an oomycete pathogen.

Spectral Matching of Three-Component Seismic Ground Accelerations for Nuclear Power Plants

The aim of the paper is to introduce a new procedure of three-component spectral matching of seismic ground acceleration records. The procedure is straightforward, yet it is general. In principle, the procedure involves varying of both the Fourier amplitude and the phase spectra so that the modified records’ spectra agree with a target. The matching can be performed against either a target Fourier or response spectra. In the former the solution is exact, while in the latter it becomes approximate. A target spectrum representative of three directions should be provided. In the example several three-component records were matched against two target spectra. Good convergence was achieved in velocity and displacement records so that no baseline correction was necessary. The couplings among the components were preserved.