[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.

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.

[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.

[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.