Molecular and functional characterization of a c-type lysozyme from the Asian corn borer, Ostrinia furnacalis

Some lepidopteran lysozymes have been reported to display activity against Gram-positive and Gram-negative bacteria, in contrast to most lysozymes that are active only against Gram-positive bacteria. OstrinLysC, a c-type lysozyme, was purified from the As

Photosynthetic physiology and growth as a function of colony size in the cyanobacterium Nostoc sphaeroides

Algal size can affect the rate of metabolism and of growth. Different sized colonies of Nostoc sphaeroides were used with the aim of determining the effects of colony size on photosynthetic physiology and growth. Small colonies showed higher maximum photosynthetic rates per unit chlorophyll, higher light saturation point, and higher photosynthetic efficiency (a) than large colonies. Furthermore, small colonies had a higher affinity for DIC and higher DIC-saturated photosynthetic rates. In addition, small colonies showed higher photosynthetic rates from 5-45degreesC than large colonies. There was a greater decrease in Fv/Fm after exposure to high irradiance and less recovery in darkness for large colonies than for small colonies. Relative growth rate decreased with increasing colony size. Small colonies had less chl a and mass per unit surface area. The results indicate that small colonies can harvest light and acquire DIC more efficiently and have higher maximum photosynthetic rates and growth rates than large colonies.

Fast Discrimination of Commerical Corn Varieties Based on Near Infrared Spectra

The existing methods for the discrimination of varieties of commodity corn seed are unable to process batch data and speed up identification, and very time consuming and costly. The present paper developed a new approach to the fast discrimination of varieties of commodity corn by means of near infrared spectral data. Firstly, the experiment obtained spectral data of 37 varieties of commodity corn seed with the Fourier transform near infrared spectrometer in the wavenurnber range from 4 000 to 12 000 cm (1). Secondly, the original data were pretreated using statistics method of normalization in order to eliminate noise and improve the efficiency of models. Thirdly, a new way based on sample standard deviation was used to select the characteristic spectral regions, and it can search very different wavenumbers among all wavenumbers and reduce the amount of data in part. Fourthly, 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 99.98%. Finally, according to the first ten components, recognition models were established based on BPR. For 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 900 samples of the other varieties were used as the second testing set. Calculation results showed that the average correctness recognition rate of the 37 varieties of corn seed was 94.3%. Testing results indicate that the discrimination method had higher precision than the discrimination of various kinds of commodity corn seed. In short, it is feasible to discriminate various varieties of commodity corn seed based on near infrared spectroscopy and BPR.