A novel putative betapartitivirus isolated from the plant-pathogenic fungus Rhizoctonia solani.

In this study, we describe the genome sequence of a novel double-stranded RNA (dsRNA) mycovirus, designated as "Rhizoctonia solani partitivirus 15" (RsPV15), from the phytopathogenic fungus Rhizoctonia solani. RsPV15 consists of two genomic double-stranded RNA segments, dsRNA-1 and dsRNA-2, which are 2433 bp and 2350 bp long, respectively. Each of the dsRNA segments contains a single open reading frame, encoding the putative RNA-dependent RNA polymerase and coat protein, respectively. Homology searches and phylogenetic analysis suggested that RsPV15 is a new member of the genus Betapartitivirus within the family Partitiviridae.

[Influence of spectrometer scanning requirements in homemade grating diffuse NIR instrument on NIR veracity].

The influence of instrument parameters, such as scan internal, length of instrument run, frequency of scan background etc, on NIR veracity was studied with a homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that scan interval, such as 8 nm or 16 nm, had no evident influence on NIR quantitative analysis. To improve scan speed, the scan interval the authors decided to use was 16 nm. NIR model was set up which could revise the influence of the length of instrument run. This instrument can clue on baseline shift to decide the frequency of background scanning, which can deduce NIR analysis error and improve NIR veracity.

[New technology for sample preprocessing in NIR analysis].

Sample's moisture content and granularity would have an important influence on NIR veracity. Preprocesssing methods have been used for NIR analysis to achieve better NIR veracity. With Yunnan flue-cured tobacco as study materials, the authors innovatively applied microwave fast drying technology and home pulverizer to tobacco preprocessing, which could finish the preprocessing in 5 min, faster than the traditional methods such as oven drying and sifting. Results showed that: microwave fast drying technology could improve NIR analysis veracity when samples' moisture content had a wide range; influence of samples' granularity on NIR veracity could be eliminated after 25 s home pulverizer shatter. This study can offer a new method for NIR analysis workers to simplify NIR preprocessing.

[Influence of LPLS algorithm parameters on NIR veracity].

The theory of local partial least square (LPLS) algorithm was described based on locally weighted regression algorithm (LWR). The influence of data processing parameters, such as principal component numbers and local set-up sample number in LPLS mode, on the NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that for nicotine model, the principal component number decided by cross validation was not the best choice, and better results could be achieved by reducing the principal component number; using 30-50 samples to set up NIR model, the veracity of total sugar, total nitrogen, and nicotine could be improved by 7%, 14% and 10%, respectively. So, LPLS algorithm can effectively improve NIR model's veracity, and is a good method to set up robust NIR models.

[Influence of sample loading and test conditions on NIR veracity and study of analysis error source].

The influence of sample test conditions on the NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Deducing analysis error was achieved by model self-emendation when a global NIR model was set up. Without regarding the influence of loading samples and test conditions, the test repetition error, re-loading error and samples tightness error, which were brought by instrument S/N, accounted for 50%, 30% and 20% of the total error, respectively. Depressing sample could reduce errors brought by sample tightness. Changes in test conditions could bring more analysis error, which was larger than the total of repetition error. These results theoretically explain the influence of sample test conditions on the NIR analysis veracity, which can provide basic theory data for farther improvement of homemade instrument and offer a new idea for resolving this problem.

[Influence of sample annum and distribution of chemical values on NIR veracity].

The influence of sample annum and the distribution of sample component on NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that sample annum had an obvious influence on the total sugar and nicotine models, but had an unconspicuous influence on the total-nitrogen model. Models set up by samples, whose component content distribution was normal school, was better than those set up by even distribution. The conclusion in this study has a significant referenced value for the method and principle to select representative samples to modeling from a large amount of specimens.