[Monitoring of Winter Wheat Aboveground Fresh Biomass Based on Multi-Information Fusion Technology].

The aim was to find a nondestructive way to improve the accuracy of detecting the winter wheat aboveground fresh biomass(AGFB). In this study, data fusion technology of the spectroscopy technology and the machine vision technology were used to analyze the AGFB and solve the problem that the accuracy of the prediction model of a single technology is not high. In this experiment, canopy spectra and canopy pictures of 93 samples at seeding stage were collected. Canopy spectra and side images of 200 samples at medium and later growth stage were collected. Spectral reflectance as the spectral absorption parameter was used to construct the AGFB prediction models based on the spectra technology at different stages; The wheat coverage were extracted from canopy pictures and side images by using image processing technology to build the AGFB prediction models. Multivariate regression analysis (MRA) and Partial least-squares regression analysis(PLS) were implemented on the feature variables from the spectral information and image information. The results showed that, compared with the individual image model and spectral model, the AGFB prediction models of PLS based on multi-information at different stages shows better performance. At the seeding stage, the determination coefficient (R2) of PLS models based on multi-information was 0.881，and the RMSE was 0.015 kg. The R2 of PLS models based on multi-information was 0.791, the RMSE was 0.059 kg at middle and final stages. It demonstrated that the precision of model based on multi-information fusion technology, which increased utilization of image and spectral information, was improved for AGFB detecting, which is than the individual image model and spectral model.

[Near-infrared spectra combining with CARS and SPA algorithms to screen the variables and samples for quantitatively determining the soluble solids content in strawberry].

In using spectroscopy to quantitatively or qualitatively analyze the quality of fruit, how to obtain a simple and effective correction model is very critical for the application and maintenance of the developed model. Strawberry as the research object, this research mainly focused on selecting the key variables and characteristic samples for quantitatively determining the soluble solids content. Competitive adaptive reweighted sampling (CARS) algorithm was firstly proposed to select the spectra variables. Then, Samples of correction set were selected by successive projections algorithm (SPA), and 98 characteristic samples were obtained. Next, based on the selected variables and characteristic samples, the second variable selection was performed by using SPA method. 25 key variables were obtained. In order to verify the performance of the proposed CARS algorithm, variable selection algorithms including Monte Carlo-uninformative variable elimination (MC-UVE) and SPA were used as the comparison algorithms. Results showed that CARS algorithm could eliminate uninformative variables and remove the collinearity information at the same time. Similarly, in order to assess the performance of the proposed SPA algorithm for selecting the characteristic samples, SPA algorithm was compared with classical Kennard-Stone algorithm Results showed that SPA algorithm could be used for selection of the characteristic samples in the calibration set. Finally, PLS and MLR model for quantitatively predicting the SSC (soluble solids content) in the strawberry were proposed based on the variables/samples subset (25/98), respectively. Results show that models built by using the 0.59% and 65.33% information of original variables and samples could obtain better performance than using the ones obtained by using all information of the original variables and samples. MLR model was the best with R(pre)2 = 0.9097, RMSEP=0.3484 and RPD = 3.3278.

[Characteristic wavelengths selection of soluble solids content of pear based on NIR spectral and LS-SVM].

To improve the precision and robustness of the NIR model of the soluble solid content (SSC) on pear. The total number of 160 pears was for the calibration (n=120) and prediction (n=40). Different spectral pretreatment methods, including standard normal variate (SNV) and multiplicative scatter correction (MSC) were used before further analysis. A combination of genetic algorithm (GA) and successive projections algorithm (SPA) was proposed to select most effective wavelengths after uninformative variable elimination (UVE) from original spectra, SNV pretreated spectra and MSC pretreated spectra respectively. The selected variables were used as the inputs of least squares-support vector machine (LS-SVM) model to build models for de- termining the SSC of pear. The results indicated that LS-SVM model built using SNVE-UVE-GA-SPA on 30 characteristic wavelengths selected from full-spectrum which had 3112 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.956, 0.271 for SSC. The model is reliable and the predicted result is effective. The method can meet the requirement of quick measuring SSC of pear and might be important for the development of portable instruments and online monitoring.

[Preliminary research on insect damage detection in pecans using terahertz spectroscopy].

Pecan is an important nut in US, however, the inner insect influences pecan's quality a lot. To realize the nondestructive detection of insect damage in American pecans rapidly and efficiently, preliminary research on insect damage detection in pecans was conducted based on terahertz spectroscopy. Firstly, a set of native pecan nuts were collected and were manually sliced with a thickness of about 1, 2 and 3 mm and with a size of about 2 cm(length) X 1 cm(width) for every pecan nutmeat; Pecan shell and inner separator were also cut into the same size. Secondly, the absorption spectra of the nutmeat slices, shell, and inner separator were collected using THz time-domain spectroscopy (THz-TDS) developed by a group of researchers at Oklahoma State University, and the spectral characteristic of the slices was analyzed. Thirdly, the absorption spectra of the alive manduca sexta and dry pecan weevil were collected, and due to the high contents in the insects, very obvious spectral characteristics were found. Finally, the transmission experiment was conducted with the whole pecans. The results from the preliminary study show a potential application of THz technology for insect damage detection. This research provides a reference for further understanding terahertz and exploring sample preparation methods, test methods, data acquisition and optical parameters calculation methods, and developing nondestructive detection system for insect damage in American pecans based on terahertz technology.

[Detection of slight bruises on apples based on hyperspectral imaging and MNF transform].

Bruising is one of the major defects occurring on apple surface inevitably during postharvest handling and processing stage. To detect slight bruises on apples fast and efficiently, a novel bruises detection algorithm based on hyperspectral imaging and minimum noise fraction transform is proposed. First, the hyperspectral images in the visible and near-infrared (400 approximately 1 000 nm) ranges are acquired, and MNF transform based on full ranges could obtain better detection performance compared to PCA transform; Second, five wavebands (560, 660, 720, 820 and 960 nm) are selected as the effective wavebands based on the coefficient curve of I-RELIEF method conducted on spectra extracted from intact and bruise surface; Third, the bruises detection algorithm is developed based on the effective wavebands and MNF transform method. For the investigated 40 sound samples and 40 different time stage bruise samples, the results with a 97. 1% overall detection rate are got. The recognition results indicate that the proposed methods and the effective wavelengths selected in this paper are feasible and efficient. This research lays a foundation for the development of multispectral imaging system based on MNF transform for slight bruises detection on apples.

[Surveillance of bacterial distribution and drug resistance in inpatients with surgical infections: a single center study].

OBJECTIVE: To investigate the bacterial distribution and drug resistance in patients with surgical infections, and provide the basis for the standardization treatment of the surgical infection. METHODS: Retrospectively analyzed from January 2008 to December 2011 surgical infection in our samples bacteria identification and drug sensitivity test results. RESULTS: A total of 3829 nonduplicate isolates from 3257 samples, Gram-negative bacteria accounted for 62.4% (the main microbes were P.aeruginosa, K. pneumonia and E.coli etc) and Gram-positive bacteria accounted for 37.6% (the main microbes were Enterococcus, Staphylococcus and coagulase negative Staphylococcus). Incidence of Staphylococcus aureus and Enterococcus faecalis were on an obvious increase. For the performance of the high level of sensitive to Imipenem, Amikacin, Piperacillin and Tazobactam by E. coli and K. pneumonia. The Pseudomonas aeruginosa and Acinetobacter baumannii to cephalosporins, Carbapenems and Fluoroqinolones were higher resistant with Multidrug resistance. No vancomycin and teicoplanin resistant Enterococcus faecium were found. The prevalence of ESBL E.coli was 45.6%-61.5% and ESBL K.pneumoniae isolates were fluctuated. The methicillin-resistant S.aureus (MRSA) isolates were relatively high (21.1%-55.8%), and methicillin-resistant Staphylococcus epidermidis was higher than the other Gram-positive cocci. Vancomycin for Staphylococcus performance was highly sensitive. CONCLUSIONS: The main composition of surgical clinical infection pathogens are Gram-negative bacillus, and the emergency of resistance of bacteria to antibacterial drugs is a common phenomenon. The resistant rate shows ascendant trend; Drug resistance is significantly higher in Pseudomonas aeruginosa and Acinetobacter baumannii. Antimicrobial resistance is a serious and challenging issue.

Clinical and microbiological features of community-acquired and nosocomial bloodstream infections in the surgical department of a tertiary-care hospital in Beijing.

BACKGROUND: Bloodstream infections (BSIs) remain a major cause of morbidity and mortality in patients undergoing surgery. This study aimed at elucidating the clinical characteristics of community-acquired BSIs (CABs) and nosocomial BSIs (nBSIs) in patients admitted to the surgical wards of a teaching hospital in Beijing, China. METHODS: This cross-sectional study compared 191 episodes of BSIs in 4074 patients admitted to the surgical wards between January 2008 and December 2011. Cases of BSIs were classified as CABs or nBSIs, and the characteristics, relevant treatments, and outcomes of CABs and nBSIs were compared. RESULTS: Of the 191 BSIs, 52 (27.2%) and 139 (72.8%) were CABs and nBSIs, respectively. Escherichia coli, coagulasenegative staphylococci, and Klebsiella spp, were the most frequently isolated microorganisms. There were significant differences between CABs and nBSIs with respect to the use of hormonal drugs, ventilation, acute physiology and chronic health evaluation (APACHE) II and American Society of Anesthesiologists scores, and prevalence of cancer (P < 0.05). Empirical antibacterial therapy did not decrease the crude mortality, but multivariate analysis showed that high APACHE II was independently associated with a risk of mortality (odds ratio = 0.97, 95% confidence interval: 0.93-1.02 for APACHE II). CONCLUSIONS: We found significant differences in the clinical characteristics of surgical patients with CABs and nBSIs. The outcome of patients seems to be related to high APACHE II scores.

[Antimicrobial resistance of Gram-negative bacilli isolated from 13 teaching hospitals across China].

OBJECTIVE: To explore the antimicrobial resistance of nosocomial Gram-negative bacilli across China. METHODS: A total of 1247 consecutive and non-repetitive Gram-negative bacilli were isolated from 13 Chinese teaching hospitals from March to August 2012. All isolates were sent to a central laboratory for reidentification and susceptibility testing. The minimal inhibitory concentration (MICs) of meropenem and other antibacterial agents were determined by agar dilution method. And the data were analyzed with WHONET-5.6 software. RESULTS: The activity of antimicrobial agents against Enterobacteriaceae was in the following descending order of susceptibility rate: meropenem (97.5%, 849/871) , amikacin (94.5%, 823/871) , imipenem (93.6%, 815/871) , ertapenem (92.9%, 809/871) , piperacillin/tazobactam (89.9%, 783/871) , cefoperazone/sulbactam (83.5%, 727/871) , cefepime (78.1%, 680/871) , polymyxin B (77.0%, 670/871) , cefiazidime (69.6%, 606/871) , levofloxacin (69.2%, 603/871) , ciprofloxacin (63.6%, 554/871) , minocyline (63.1%, 550/871) , ceftriaxone (55.7%, 485/871) , cefotaxime (54.2%, 472/871) and cefoxitin (51.4%, 448/871) . The prevalence of extended-spectrum beta-lactamase (ESBL) was 64.3% (117/182) in Escherichia coli (E. coli) and 32.1% (60/187) in Klebsiella pneumonia (K. pneumoniae) . The sensitivities of E. coli to meropenem and imipenem were 100%. And over 90% of E. coli was sensitive to ertapenem, amikacin, piperacillin/tazobactam and polymyxin B. However, over 60% of E. coli was resistant to ciprofloxacin, levofloxacin, ceftriaxone and cefotaxime. The susceptibility of K. pneumoniae to meropenem, imipenem, amikacin and polymyxin B maintained at over 90%. The activities of antimicrobial agents against E. cloacae, E. aerogenes and Citrobacter freundii were in the following descending order of susceptibility rate: meropenem (96.0%-100%) , imipenem (96.0%-100%) , polymyxin B (95.8%-100%) , amikacin (92.2%-100%) , ertapenem (85.6%-93.3%) , cefepime (77.8%-93.3%) , cefoperazone/sulbactam (78.4%-90.0%) and piperacillin/tazobactam (65.0%-89.8%) . The most susceptible agent against Acinetobacter baumannii (A. baumannii) was polymyxin B (100%) . The susceptibilities of A.baumannii to imipenem, meropenem and minocyline were 37.8% (65/172) , 36.0% (62/172) and 62.8% (108/172) respectively. The most active agents against Pseudomonas aeruginosa (P. aeruginosa) were polymyxin B (97.2%, 173/178) , followed by amikacin (89.3%, 159/178) and cefiazidime (83.7%, 149/178) . Clinical and Laboratory Standards Institute revised P.aeruginosa susceptibility standard in 2012. The sensitivity of piperacillin/tazobactam changed from 83.7% (149/178) to 77.5% (138/178) . The sensitivity of meropenem decreased from 78.1% ( 139/178 ) to 71.3% ( 127/178 ) while that of imipenem declined from 69.7% (124/178) to 59.6% (106/178) . The prevalence of multi-drug resistant A. baumannii and P. aeruginosa were 65.7% (113/172) and 9.0% (16/178) respectively. CONCLUSIONS: Carbapenems remain highly active against Enterobacteriaceae. Increasing resistance of A. baumannii to all antimicrobial agents is noted. New breakpoint to P.aeruginosa has obvious effects on antimicrobial sensitivity.

[A study of in vitro activity of daptomycin against 2679 Gram-positive cocci].

OBJECTIVE: To evaluate the in vitro activity of daptomycin against 2679 Gram-positive cocci. METHODS: A total of 2679 non-duplicate Gram-positive cocci isolates were collected from 17 teaching hospitals during January, 2010 and December, 2011. The minimal inhibitory concentrations (MICs) of daptomycin and other anti-microbial agents against 4 Gram-positive cocci were determined by micro-broth dilution method and agar dilution respectively. The data of drug susceptibility were analyzed by WHONET5.6 software. RESULTS: Methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococci (MRSCoN) detection rates were 45.8% and 84.2%, respectively. The susceptibility rates of sulfamethoxazole, chloramphenicol, erythromycin, tetracycline, clindamycin and rifampicin against MRSA were 93.1%, 85.5%, 13.8%, 26.6%, 63.2% and 50.0%, respectively. The susceptibility rates of daptomycin, vancomycin and linezolid against MRSA and MRSCoN were all 100.0%. The daptomycin MIC50 and MIC90 of MRSCoN and MRSA were 0.5 mg/L. The high level gentamicin resistance rate of 513 Enterococci isolates was 56.9%. The susceptibility rates of chloramphenicol and tetracycline were 76.0% and 44.1%, respectively. The susceptibility rates of tigecycline and daptomycin reached 100.0%. The MIC50 and MIC90 of daptomycin against 17 vancomycin-resistant Enterococci (VRE) were both 2 mg/L. The susceptibility rates of daptomycin against Streptococcus pneumoniae and ß-hemolytic Streptococcus were 100.0%. The prevalence of penicillin-nonsusceptible Streptococcus pneumoniae (PNSSP) was 63.1%. The MIC50 and MIC90 of daptomycin against PNSSP were 0.125 mg/L and 0.25 mg/L, respectively according to the breakpoint of oral penicillin. The MIC50 and MIC90 daptomycin against ß-hemolytic Streptococci were 0.008 mg/L and 0.032 mg/L. CONCLUSIONS: Daptomycin have excellent in vitro activity against common Gram-positive cocci, including multi-drug resistant bacteria. It may be a good choice for clinicians to treat drug-resistant Gram-positive cocci.

[Research on discrimination of cabbage and weeds based on visible and near-infrared spectrum analysis].

The automatic identification of weeds forms the basis for precision spraying of crops infest. The canopy spectral reflectance within the 350-2 500 nm band of two strains of cabbages and five kinds of weeds such as barnyard grass, setaria, crabgrass, goosegrass and pigweed was acquired by ASD spectrometer. According to the spectral curve characteristics, the data in different bands were compressed with different levels to improve the operation efficiency. Firstly, the spectrum was denoised in accordance with the different order of multiple scattering correction (MSC) method and Savitzky-Golay (SG) convolution smoothing method set by different parameters, then the model was built by combining the principal component analysis (PCA) method to extract principal components, finally all kinds of plants were classified by using the soft independent modeling of class analogy (SIMCA) taxonomy and the classification results were compared. The tests results indicate that after the pretreatment of the spectral data with the method of the combination of MSC and SG set with 3rd order, 5th degree polynomial, 21 smoothing points, and the top 10 principal components extraction using PCA as a classification model input variable, 100% correct classification rate was achieved, and it is able to identify cabbage and several kinds of common weeds quickly and nondestructively.

[An analysis of resistance of nosocomial infection pathogens isolated from 13 teaching hospitals in 2011].

OBJECTIVE: To investigate the pathogen profile of nosocomial infection in China, and to survey the susceptibility rates of these pathogens to the clinical common antibiotics. METHODS: The non-repetitive nosocomial pathogens isolated from bloodstream infection (BSI), hospital acquired pneumonia (HAP) and intra-abdominal infection (IAI) and the case data were collected from 13 teaching hospitals in different areas of China and sent to a central laboratory for re-identification and susceptibility testing. The levels of minimal inhibitory concentration (MIC) of the common antibiotics were determined by agar dilution method. The data were analyzed by WHONET 5.6 software. RESULTS: A total of 2103 clinical isolates were collected from January to December 2011, of which gram positive cocci and gram negative organisms accounted for 23.2% and 76.8% respectively. The top three pathogens of BSI were E. coli (31.0%, 243/784), K. pneumoniae (14.8%, 116/784) and S. aureus (10.6%, 83/784). The top three pathogens of HAP were A. baumannii (24.2%, 158/652), P. aeruginosa (23.0%, 150/652) and K. pneumoniae (16.4%, 107/652). The top three pathogens of IAI were E. coli (34.3%, 229/667), E. faecium (13.3%, 89/667) and K. pneumoniae (9.6%, 64/667). Methicillin-resistant S. aureus (MRSA) and coagulase negative Staphylococcus (MRCNS) accounted for 64.4% and 78.1% respectively. The susceptibility rates of Staphylococcus species to tigecycline, vancomycin, teicoplanin and linezolid were all 100%. The prevalence of MRSA in HAP was significantly higher than that in BSI or IAI. The susceptibility rates of Enterococcus species to tigecycline, teicoplanin and linezolid were all 100%. The prevalence of extended-spectrum ß-lactamases (ESBL) was 64.3% in E. coli and 38.3% in K. pneumonia. Against Enterobacteriaceae, the most active agents were as following in order: tigecycline (92.3% - 100%) [except P.mirabilis], meropenem (87.5% - 100%), imipenem (87.5% - 100%) [except M. morganii], amikacin (87.5% - 100%), polymyxin B (75% - 100%) [except S. marcescens, P. mirabilis and M morganii], cefepime (67.8% - 100%), cefoperazone-sulbactam (66.6% - 100%), piperacillin-tazobactam (61.5% - 100%). Carbapenem-resistance Enterobacteriaceae strains emerged. The susceptibility rates of P. aeruginosa to imipenem and meropenem were 66.2% and 72.2%, respectively. The susceptibility rates of A. baumannii to imipenem and meropenem were 27.7% and 25.9%, respectively. The most active agents against A. baumannii were polymyxin B (100%), followed by tigecycline (79.8%) and minocycline (50.4%). The susceptibility rates of P.aeruginosa to antibiotics in BSI were higher than those in HAP and IAI. Susceptibility rates of S. maltophilia to trimethoprim-sulfamethoxazole, minocycline and levofloxacin were about 90% or above. Susceptibility rates of B. cepacia to trimethoprim-sulfamethoxazole, ceftazidime and meropenem were all 100%. Several P.aeruginosa and A. baumannii strains were resistant to all tested antibiotics except polymyxin B. CONCLUSIONS: The pathogen profile is different in different types of infection. The prevalence of multi-drug resistant A. baumannii is high, which is still a key problem of nosocomial infection. Tigecycline remains relatively high activity against gram-positive cocci and gram-negative bacteria (except P. aeruginosa and P. mirabilis) in vitro.

[Determination of potassium in farmland soil using laser-induced breakdown spectroscopy].

The real-time measurement of potassium in farmland soil has great importance. A method to determine the potassium content in farmland soil based on laser-induced breakdown spectroscopy (LIBS) was studied using a LIBS equipment consisting of a 1,064 nm laser generator and a high resolution spectrometer. The farmland soil samples with potassium content in the range of 8.74-34.56 g.kg-1 were analyzed. The 766.49 nm was chosen as the analysis line, by comparing the potassium atom characteristic lines of 404.40, 404.72, 766.49 and 769.90 nm. The errors of characteristic line strength caused by the laser stability and random noise was analyzed. The silicon, which is nearly constant in farmland soil, was chosen as the standard element, and a calibration model between the ratio of potassium to silicon (K/Si) and the potassium content was established. The linear fitting degree of the calibration curve was 0.935, and the relative standard deviation of the calibration model for prediction set samples was 9.26%.

[Antimicrobial resistance and serotype distribution of Streptococcus pneumoniae isolated from multi-centers across China, 2010 - 2011].

OBJECTIVE: To investigate the trends of resistance of S. pneumoniae and to evaluate the potential coverage of pneumococcal conjugate vaccine. METHODS: The antibiotic susceptibility and serotype distribution of 471 pneumococcal strains isolated from pneumococcal diseases in 13 hospitals across China during 2010 to 2011 were studied. In vitro susceptibility to 15 antimicrobial agents was determined by agar dilution method. Serotyping of S. pneumoniae was performed by using latex and quelling reaction. Vaccine coverage by 7-, 10-, 13- and 23- valent conjugate vaccines was estimated by calculating the percentage of isolates that belonged to the serotypes included in the vaccines. RESULTS: Among all strains tested, 50.1% (236/471) was resistant to penicillin (Oral breakpoint, MIC ≥ 2 mg/L). Overall, 27.4% (129/471), 60.3% (284/471), 58.8% (277/471) and 18.5% (87/471) of S. pneumoniae were resistant to amoxicillin/clavulanate, cefaclor, cefuroxime and ceftriaxone, respectively.1.5% (7/471) of all stains were resistant to levofloxacin and 0.6% (3/471) of all strains were resistant to moxifloxacin. The resistance rates to other antibiotic agents, such as erythromycin, clindamycin, tetracycline, trimethoprim/sulfamethoxazole, and chloramphenicol, were 93.2% (439/471), 88.7% (417/471), 89.6% (422/471), 62.8% (296/471) and 22.1% (104/471), respectively. The most prevalent serotype was 19F (112, 23.8%), followed by 19A (63, 13.4%), 3 (48, 10.2%), 14 (43, 9.1%), 23F (29, 6.2%), 15 (25, 5.3%) and 6A (23, 4.9%). The potential coverage by 7- and 13-valent pneumococcal conjugate vaccines was 45.3% (213/471) and 76% (358/471), respectively. The potential coverage of PCV7 and PCV13 in children were 59.0% (72/122) and 86.9% (106/122), and the potential coverage of PCV7 and PCV13 in adult were 42.3% (94/222) and 73.4% (163/222). CONCLUSIONS: The antibiotic resistance of S. pneumoniae was serious in China, especially to tetracycline, erythromycin and clindamycin. The majority of serotypes 19A and 19F was penicillin-resistant. The potential coverage of PCV7 and PCV13 in children was higher than those in adult. PCV13 could cover most of the isolates, especially for penicillin-resistant S. pneumoniae.

[Research on spectra recognition method for cabbages and weeds based on PCA and SIMCA].

In order to improve the accuracy and efficiency of weed identification, the difference of spectral reflectance was employed to distinguish between crops and weeds. Firstly, the different combinations of Savitzky-Golay (SG) convolutional derivation and multiplicative scattering correction (MSC) method were applied to preprocess the raw spectral data. Then the clustering analysis of various types of plants was completed by using principal component analysis (PCA) method, and the feature wavelengths which were sensitive for classifying various types of plants were extracted according to the corresponding loading plots of the optimal principal components in PCA results. Finally, setting the feature wavelengths as the input variables, the soft independent modeling of class analogy (SIMCA) classification method was used to identify the various types of plants. The experimental results of classifying cabbages and weeds showed that on the basis of the optimal pretreatment by a synthetic application of MSC and SG convolutional derivation with SG's parameters set as 1rd order derivation, 3th degree polynomial and 51 smoothing points, 23 feature wavelengths were extracted in accordance with the top three principal components in PCA results. When SIMCA method was used for classification while the previously selected 23 feature wavelengths were set as the input variables, the classification rates of the modeling set and the prediction set were respectively up to 98.6% and 100%.

[Fluoroquinolone resistance determining region mutation in Streptococcus pneumonia isolates].

OBJECTIVE: To investigate the relationship between different fluoroquinolone (FQ) resistance of Streptococcus pneumoniae and the mutations of target genes. METHODS: A total of 232 Streptococcus pneumoniae isolates were collected from 12 teaching hospitals at 9 cities between June and December 2010. The antibacterial activities of 16 antimicrobial agents were determined by agar dilution method. The ciprofloxacin, levofloxacin and moxifloxacin MIC ≥ 1 mg/L isolates were selected to detect the mutations in QRDR (parC, parE, and gyrA genes) through PCR combined sequencing. RESULTS: The susceptible rates of ciprofloxacin, levofloxacin and moxifloxacin were 53.9% (125/232) , 98.7% (229/232) , 98.7% (229/232) .Forty-three strains were randomly selected to be analyzed, including 19 levofloxacin MIC ≥ 2 mg/L strains and 24 levofloxacin MIC = 1 mg/L strains. The MIC of levofloxacin were 1-2 mg/L, ciprofloxacin were 2 mg/L and moxifloxacin were 0.125-0.250 mg/L when a single mutation in parE occurred. The MIC of levofloxacin were 2 mg/L, ciprofloxacin were 4 mg/L and moxifloxacin were 0.25 mg/L or 0.50 mg/L when mutations in both parE and parC occurred. The MIC of levofloxacin were 16 mg/L, ciprofloxacin were ≥ 16 mg/L and moxifloxacin were 4 mg/L when mutations in both parE and gyrA occurred. CONCLUSION: The single mutation in parE/parC is associated with low level levofloxacin and ciprofloxacin resistance, while double mutations in both parC/parE and gyrA are associated with moxifloxacin resistance.

[Effect of spectral resolution on black soil organic matter content predicting model based on laboratory reflectance].

Laboratory reflectance of Black soil samples was re-sampled with different spectral resolution, and the correlation between soil organic matter (OM) and reflectance, spectral variables was analyzed to study the effect of spectral resolution on black soil OM predicting model. The results are as follows: the spectral response range of black soil OM is between 445 and 1 380 nm, high OM content shades the spectral effect of other soil properties. The precision of black soil OM predicting models increases and decreases with spectral resolution, and the maximum accuracy is at 50 nm, which is wider than hyperspectral resolution, and narrower than the bandwidth of multispectral sensors; with the derivative of logarithmic reflectance reciprocal as input variables, the optimal black soil organic matter predicting model shows high accuracy, with R2 = 0.799 and RMSE = 0.439; the results can provide the academic and technical support for soil organic matter remote sensing reversing and quick instrument developing.

[Study on relationship between new characteristic parameters of spectral curve and chlorophyll content for rice].

It is of significance to monitor chlorophyll content with hyperspectral data for crop growth diagnosis in field. In the study, with the point of view that spectral curve shapes display "tall, low, fat and thin" morphological changes, we proposed some new characteristic parameters from spectral curve such as the ascensive or degressive velocities of segments composing peak or valley shapes in spectral curve, and angles formed by the lines fitting the segments of two sides of peak or valley curves, and used the normalized spectra to analyze correlation between these parameters and rice chlorophyll content. The result shows that (1) there is a good negative correlation between rice chlorophyll content and normalized reflectance spectra from 520-740 nm; (2) characteristic parameters from green peak region of spectral curve display better correlation with rice chlorophyll content, which makes it possible to utilize the parameters to monitor crop chlorophyll content, and will provide new ideas and methods for carrying out crop growth diagnosis with hyperspectral data.

Spectral target-detecting system using sine-wave modulation.

Target detection is one of the key technology of precision chemical application. Previously the digital coding modulation technique was commonly used to emit and receive the optical signal in the target detection systems previously in China. It was difficult to adjust the output power, and the anti-interference ability was weak in these systems. In order to resolve these problems, the target detection method based on analog sine-wave modulation was studied. The spectral detecting system was set up in the aspects of working principle, electric circuit, and optical path. Lab testing was performed. The results showed that the reflected signal from the target varied inversely with detection distances. It indicated that it was feasible to establish the target detection system using analog sine-wave modulation technology. Furthermore, quantitative measurement of the reflected optical signal for near-infrared and visible light could be achieved by using this system. The research laid the foundation for the future development of the corresponding instrument.

[Study of serotype distribution, antimicrobial resistance patterns and molecular epidemiology in 148 isolates of invasive Streptococcus pneumoniae].

OBJECTIVE: To investigate the serotype distribution, antimicrobial resistance patterns and molecular epidemiology of Streptococcus pneumoniae (S. pneumoniae) isolated from invasive pneumococcal diseases in order to provide rationales for antibiotics application and immunity control of S. pneumoniae. METHODS: A total of 148 isolates of invasive S. pneumoniae were collected from blood, cerebrospinal fluid and other sterile body fluids from 15 regions between January 2005 and August 2008 nationwide. Agar dilution method was used to determine the minimal inhibitory concentrations (MICs) of penicillin and other antibiotics against these isolates. Simplified chessboard system and capsule swelling reaction were used for serotyping of S. pneumoniae. Multilocus sequence typing (MLST) was used to determine the genetic relationship of 53 strains of serogroup-19. RESULTS: Twenty serotypes/serogroups were identified in 148 strains. The prevalent serotypes (70.9%) were 19A, 19F, 3, 23F, 5, 6, 14 and 9 respectively. Serotypes 19A (22.3%, 33/148) and 19F (16.9%, 25/148) were the most frequent type observed. And serotypes 3 (7.4%, 11/148) and 23F (6.8%, 10/148) were less prevalent. Of all 36 strains isolated from infants under 2 years old, 33.3% (12/36) were covered by 7-valent pneumococcal conjugate vaccine (PCV7). The resistant rates to amoxicillin/clavulanic acid, erythromycin and other antibiotics in PCV7-related pneumococcal strains were significantly higher than those in PCV7-unrelated group (P < 0.05). Fifty-three strains of serogroup-19 were genotyped by MLST and 9 sequence types (STs) identified. ST320 (52.8%, 28/53) and ST271 (22.6%, 12/53) were the most frequent STs. CONCLUSIONS: The major serotypes of invasive S. pneumoniae are 19A, 19F, 3 and 23F. Antimicrobial-resistant S. pneumoniae has become a serious issue of public health.

[Study on spectral detection of green plant target].

Weeds grow scatteredly in fields, where many insentient objects exist, for example, withered grasses, dry twig and barriers. In order to improve the precision level of spraying, it is important to study green plant detecting technology. The present paper discussed detecting method of green plant by using spectral recognizing technology, because of the real-time feature of spectral recognition. By analyzing the reflectivity difference between each of the two sides of the "red edge" of the spectrum from plants and surrounding environment, green plant discriminat index (GPDI) is defined as the value which equals the reflectivity ratio at the wavelength of 850 nm divided by the reflectivity ratio at the wavelength of 650 nm. The original spectral data of green plants and the background were measured by using the handhold FieldSpec 3 Spectroradiometer manufactured by ASD Inc. in USA. The spectral data were processed to get the reflectivity of each measured objects and to work out the GPDI thereof as well. The classification model of green plant and its background was built up using decision tree method in order to obtain the threshold of GPDI to distinguish green plants and the background. The threshold of GPDI was chosen as 5.54. The detected object was recognized as green plant when it is GPDI>GPDITH, and vice versa. Through another test, the accuracy rate was verified which was 100% by using the threshold. The authors designed and developed the green plant detector based on single chip microcomputer (SCM) "AT89S51" and photodiode "OPT101" to realize detecting green plants from the background. After passing through two optical filters, the center wavelengths of which are 650 and 850 nm respectively, the reflected light from measured targets was detected by two photodiodes and converted into electrical signals. These analog signals were then converted to digital signals via an analog-to-digital converter (ADS7813) after being amplified by a signal amplifier (OP400). The converted digital signal of reflected light was eventually sent to the SCM (AT89S51) and was calculated and processed there. The processing results and the control signals were given out to actuate executive device to open or close the solenoid valve. The test results show that the level of detectivity of the designed detector was affected by the species, size, and density of weeds. The detectivity of broad-leaf species is higher than that of narrow-leaf species. Broad-leaf species are more easily detected than those narrow-leaf ones; the bigger the plants and the denser the leaves are, the higher the level of detectivity is.