Selective Hydrodeoxygenation of 5-Hydroxymethylfurfural to 2,5-Dimethylfuran over Heterogeneous Iron Catalysts.

This work provided the first example of selective hydrodeoxygenation of 5-hydroxymethylfurfural (HMF) to 2,5-dimethylfuran (DMF) over heterogeneous Fe catalysts. A catalyst prepared by the pyrolysis of an Fe-phenanthroline complex on activated carbon at 800 °C was demonstrated to be the most active heterogeneous Fe catalyst. Under the optimal reaction conditions, complete conversion of HMF was achieved with 86.2 % selectivity to DMF. The reaction pathway was investigated thoroughly, and the hydrogenation of the C=O bond in HMF was demonstrated to be the rate-determining step during the hydrodeoxygenation, which could be accelerated greatly by using alcohol solvents as additional H-donors. The excellent stability of the Fe catalyst, which was probably a result of the well-preserved active species and the pore structure of the Fe catalyst in the presence of H2 , was demonstrated in batch and continuous flow fixed-bed reactors.

[Combining ability analysis for SP4 lines of maize from space flight].

Three maize (Zea mays L.) inbred lines 08-641, RP125, and 18-599 were carried into cosmic space by recoverable satellite "Shijian 8". Some mutant lines were selected from SP4 and combinations were made according to the NC II genetic design. The materials were planted in Sichuan and Yunnan separately to analyze combining ability based on the incomplete diallel cross design. The results showed that space flight affected the combining ability of mutant lines, and the GCA value of mutant lines were different in two kinds of environmental condition. The GCA of ear length, row per ear, kernel per row, and yield per plant for the mutant line C03 showed substantial increase compared with the control 08-641; the GCA of row per ear, kernel per row, and other yield component traits for the mutant lines C01 and C04 were significantly higher than those of the control. The SCA of yield and yield components for the combinations derived from the mutant lines C06, R18, and S22 were higher than others. These results laid a material foundation for maize breeding and provided some important references for improving and utilizing the mutant lines.

[Successive projections algorithm and its application to selecting the wheat near-infrared spectral variables].

Successive projections algorithm combined with partial least squares regression, termed as SPA-PLS approach, was implemented as a novel variable selection approach to multivariate calibration. The proposed approach was applied to near-infrared reflectance data for analyzing moisture in wheat. The number of variables selected from 701 spectral variables was reduced to 16 by SPA, and the root mean squared error of prediction set (RMSEP) of the corresponding partial least squares regression models was decreased to 0.205 5% as well. The result indicates that the SPA-PLS approach by performing SPA prior to calibration not only can improve the model accuracy, but also decreases the number of spectral variables, so its resulting model becomes more concise. Moreover, as compared with genetic algorithm for wavelength selection, SPA is a deterministic search technique whose results are reproducible and it is more robust with respect to the choice of the validation set.