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.

Scale study of direct synthesis of dimethyl ether from biomass synthesis gas

We investigated the synthesis of dimethyl ether (DME) from biomass synthesis gas using a kind of hybrid catalyst consisting of methanol and HZSM-5 zeolite in a fixed-bed reactor in a 100 ton/year pilot plant. The biomass synthesis gas was produced by oxygen-rich gasification of corn core in a two-stage fixed bed. The results showed that CO conversions reached 82.00% and 73.55%, the selectivities for DME were 73.95% and 69.73%, and the space-time yields were 124.28 kg m- 3 h- 1 and 203.80 kg m- 3 h- 1 when gas hourly space velocities were 650 h- 1 and 1200 h- 1, respectively. Deoxidation and tar removal from biomass synthesis gas was critical to the stable operation of the DME synthesis system. Using single-pass synthesis, the H2/CO ratio improved from 0.98-1.17 to 2.12-2.22. The yield of DME would be increased greatly if the exhaust was reused after removal of the CO2.