[A new discrimination method of maize seed varieties based on near-infrared spectroscopy].

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12000-4000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91.8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.

[Fast discrimination of varieties of transgene wheat based on biomimetic pattern recognition and near infrared spectra].

A new method for the fast discrimination of varieties of transgene wheat by means of near infrared spectroscopy and biomimetic pattern recognition (BPR) was proposed and the recognition models of seven varieties of transgene wheat and two varieties of acceptor wheat were built. The experiment adopted 225 samples, which were acquired from nine varieties of wheat. Firstly, a field spectroradiometer was used for collecting spectra in the wave number range from 4 000 to 12 000 cm(-1). Secondly, the original spectral data were pretreated in order to eliminate noise and improve the efficiency of models. Thirdly, principal component analysis (PCA) was used to compress spectral data into several variables, and the cumulate reliabilities of the first ten components were more than 97.28%. Finally, the recognition models were established based on BPR For the every 25 samples in each variety, 15 samples were randomly selected as the training set. The remaining 10 samples of the same variety were used as the first testing set, and all the 200 samples of the other varieties were used as the second testing set. As the 96.7% samples in the second set were correctly rejected, the average correct recognition rate of first testing set was 94.3%. The experimental results demonstrated that the recognition models were effective and efficient. In short, it is feasible to discriminate varieties of transgene wheat based on near infrared spectroscopy and BPR.

ZincExplorer: an accurate hybrid method to improve the prediction of zinc-binding sites from protein sequences.

As one of the most important trace elements within an organism, zinc has been shown to be involved in numerous biological processes and closely implicated in various diseases. The zinc ion is important for proteins to perform their functional roles. To provide in-depth functional annotation of zinc-binding proteins, an initial but crucial step is the accurate recognition of zinc-binding sites. Motivated by the biological importance of zinc, we propose a new method called ZincExplorer to predict zinc-binding sites from protein sequences. ZincExplorer is a hybrid method that can accurately predict zinc-binding sites from protein sequences. It integrates the outputs of three different types of predictors, namely, SVM-, cluster- and template-based predictors. Four types of zinc-binding amino acids CHEDs (i.e. CYS, HIS, ASP and GLU) could be predicted using ZincExplorer. It achieved a high AURPC (Area Under Recall-Precision Curve) of 0.851, and a precision of 85.6% (specificity = 98.4%, MCC = 0.747) at the 70.0% recall for the CHEDs on the 5-fold cross-validation test. When tested on an independent dataset containing 2023 zinc-binding CHEDs and 14,493 non-zinc-binding CHEDs, it achieved about 3-8% higher AURPC in comparison to two other sequence-based predictors. Moreover, ZincExplorer could also identify the interdependent relationships (IRs) of the predicted zinc-binding sites bound to the same zinc ion, which makes it a useful tool for providing in-depth zinc-binding site annotation.

Analysis of nucleotide sequences and multimeric forms of a novel satellite RNA associated with beet black scorch virus.

The full-length sequence of a satellite RNA (sat-RNA) of Beet black scorch virus isolate X (BBSV-X) was determined. This agent is 615 nucleotides long and lacks extensive sequence homology with its helper virus or with other reported viruses. Purified virus particles contained abundant single-stranded plus-sense monomers and smaller amounts of dimers. Single-stranded RNAs from total plant RNA extracts also included primarily monomers and smaller amounts of dimers that could be revealed by hybridization, and preparations of purified double-stranded RNAs also contained monomers and dimers. Coinoculation of in vitro transcripts of sat-RNA to Chenopodium amaranticolor with BBSV RNAs was used to assess the replication and accumulation of various forms of sat-RNA, including monomers, dimers, and tetramers. Dimeric sat-RNAs with 5- or 10-base deletions or 15-base insertions within the junction regions accumulated preferentially. In contrast, the replication of monomeric sat-RNA was severely inhibited by five-nucleotide deletions in either the 5' or the 3' termini. Therefore, sequences at both the 5' and the 3' ends of the monomers or the presence of intact juxtaposed multimers is essential for the replication of sat-RNA and for the predomination of monomeric progeny. Comparisons of the time courses of replication initiated by in vitro-synthesized monomeric or multimeric sat-RNAs raised the possibility that the dimeric form has an intermediate role in replication. We propose that replication primarily involves multimers, possibly as dimeric forms. These forms may revert to monomers by a termination of replication at 5' end sequences and/or by internal initiation at the 3' ends of multimeric junctions.