[Estimation of organic matter content of north fluvo-aquic soil based on the coupling model of wavelet transform and partial least squares].

For improving the estimation accuracy of soil organic matter content of the north fluvo-aquic soil, wavelet transform technology is introduced. The soil samples were collected from Tongzhou district and Shunyi district in Beijing city. And the data source is from soil hyperspectral data obtained under laboratory condition. First, discrete wavelet transform efficiently decomposes hyperspectral into approximate coefficients and detail coefficients. Then, the correlation between approximate coefficients, detail coefficients and organic matter content was analyzed, and the sensitive bands of the organic matter were screened. Finally, models were established to estimate the soil organic content by using the partial least squares regression (PLSR). Results show that the NIR bands made more contributions than the visible band in estimating organic matter content models; the ability of approximate coefficients to estimate organic matter content is better than that of detail coefficients; The estimation precision of the detail coefficients fir soil organic matter content decreases with the spectral resolution being lower; Compared with the commonly used three types of soil spectral reflectance transforms, the wavelet transform can improve the estimation ability of soil spectral fir organic content; The accuracy of the best model established by the approximate coefficients or detail coefficients is higher, and the coefficient of determination (R2) and the root mean square error (RMSE) of the best model for approximate coefficients are 0.722 and 0.221, respectively. The R2 and RMSE of the best model for detail coefficients are 0.670 and 0.255, respectively.

[Inversion of organic matter content of the north fluvo-aquic soil based on hyperspectral and multi-spectra].

The present study aims to assess the feasibility of multi-spectral data in monitoring soil organic matter content. The data source comes from hyperspectral measured under laboratory condition, and simulated multi-spectral data from the hyperspectral. According to the reflectance response functions of Landsat TM and HJ-CCD (the Environment and Disaster Reduction Small Satellites, HJ), the hyperspectra were resampled for the corresponding bands of multi-spectral sensors. The correlation between hyperspectral, simulated reflectance spectra and organic matter content was calculated, and used to extract the sensitive bands of the organic matter in the north fluvo-aquic soil. The partial least square regression (PLSR) method was used to establish experiential models to estimate soil organic matter content. Both root mean squared error (RMSE) and coefficient of the determination (R2) were introduced to test the precision and stability of the modes. Results demonstrate that compared with the hyperspectral data, the best model established by simulated multi-spectral data gives a good result for organic matter content, with R2=0.586, and RMSE=0.280. Therefore, using multi-spectral data to predict tide soil organic matter content is feasible.

[Microbial Diversity and Influencing Factors in a Small Watershed in Winter].

The water quality of a small watershed will directly affect the water quality safety of the entire watershed. The Lidu small watershed of the Fulin District in Chongqing was selected for this study. The characteristics of runoff and the microbial community in the receiving water body were analyzed by high-throughput sequencing technology. The effects of the physical and chemical factors of the water body on the microbial diversity in the water body were also investigated. The results showed that the small watershed of Lidu was an important source of nitrite and dissolved organic carbon for the receiving water. There was no significant difference in the microbial richness and diversity of the water flowing through different pollution sources in the small watershed, and the microbial diversity index was negatively correlated with the total phosphorus (r -0.79--0.84, P ≤ 0.01) and phosphate (r -0.71--0.80, P ≤ 0.01) of the water. At the phylum level, Actinobacteria (37.33% ±14.69%) accounted for the largest proportion of runoff flowing through the agricultural area, followed by Proteobacteria (32.53% ±7.18%), Cyanobacteria (14.65% ±22.64%), Bacteroidetes (8.50% ±3.67%), and others. Proteobacteria (43.67% ±10.80%) accounted for the largest proportion of runoff flowing through the industrial area, followed by Bacteroidetes (25.33% ±11.97%), Actinobacteria (24.17% ±14.66%), Firmicutes (2.53% ±0.72%), and others. At the genus level, hgcI_clade (19.08% ±13.46%) accounted for the largest proportion of runoff flowing through the agricultural area, followed by CL 500-29 _marine_group (7.40% ±4.44%), Limnohabitans (7.05% ±3.14%), and others. Flavobacterium (20.40% ±12.37%) accounted for the largest proportion of runoff flowing through the industrial area, followed by hgcI_clade (15.30% ±11.11%), Acinetobacter (9.33% ±11.50%), and others. The Flavobacterium in the runoff water may be related to the input of industrial sources in the watershed. Nitrous nitrogen, total phosphorus, phosphate, pH, and Zn2+ were the main environmental factors that affected the microbial community in the small watershed. They can explain the variance of microbial community 0.26, 0.21, 0.20, 0.15, and 0.14, respectively. DOC, nitrate nitrogen, and heavy metal ions such as Cu2+, Zn2+, Mn2+, and As3+ were also related to the proportion of some microorganisms in the water.

[Diversity of the Microbial Community in Rice Paddy Soil with Biogas Slurry Irrigation Analyzed by Illumina Sequencing Technology].

In order to explore the variation in soil microbial community diversity in paddy fields with different irrigation periods, we collected in situ rice field soils during different biogas irrigation periods and analyzed the microbial community structures of these soils by high-throughput sequencing. The results showed that as the biogas irrigation period increased, the soil pH decreased gradually, while organic matter, nitrate nitrogen, phosphate, and other nutrients were accumulated. Years of continued biogas irrigation was not conducive to improving rice yields. The results showed that as the biogas irrigation period increased, the richness in microbial species in paddy soils decreased gradually, and the diversity in the microbial communities was also reduced. Proteobacteria accounts for the largest proportion in rice paddy soil with biogas slurry irrigation. With the increase of biogas irrigation years, the proportion of ß-Proteobacteria, Bacteroidia, Bacteroidales, Burkholderiales, Bacteroides, and Thiobacillus increased, while the proportion of Gemmatimonadetes and α-Proteobacteria decreased gradually. Dissolved organic carbon (F=2.67, P=0.09) had the greatest effect on microbial community structures in the studied paddy soils.

[Clinical observation on hailong juanxiao recipe combined with kechuanping mounting on yongquan acupoint in treating children' bronchial asthma in the stage of attack].

OBJECTIVE: To observe the effect of children' bronchial asthma in the stage of attack treated by Hailong Juanxiao Recipe combined with Kechuanping sticking on Yongquan acupoint (HKSYA). METHODS: One hundred and fifty children aging between 4-14 years old with bronchial asthma were randomly divided into HKSYA group (treated group, 75 cases) and Western medicine control group (control group, 75 cases). The clinical efficacy, eosinophilis (EOS) in peripheral blood and serum IgE of the patients were determined after 2 weeks of treatment. RESULTS: The clinical efficacy in the treated group was 89.3%, compared with the control group (64.0%), the difference was significant (P < 0.05). EOS and IgE in both groups after treatment were obviously lower with significant difference when compared with before treatment (P < 0.01 or P < 0.05). CONCLUSION: HKSYA could improve the clinical symptoms and the observation item, and enhance the clinical efficacy.