内生真菌感染对高羊茅光合和形态特性的影响

通过对感染和未感染内生真菌Neotyphodium starrii高羊茅植株光合特性和形态变化的测定,研究了内生真菌感染对高羊茅的影响。结果表明:感染内生真菌的高羊茅植株净光合速率(Pn)、蒸腾速率(Tr)、水分利用效率(ρWUE)、细胞间CO2浓度(Ci)、气孔导度(Gs)都高于非感染高羊茅植株,高温下光合性能和抵抗高温的能力都优于非感染高羊茅植株。感染植株和非感染内生真菌植株形态变化表现出一定规律性,感染植株叶片厚,植株高大、叶色深、叶片宽;而非感染植株叶片薄,植株矮、叶色浅、叶片窄。具有良好抗性和适应性的新的草坪草种的选育,可为水资源短缺城市、干旱、半干旱地区及特殊立地条件地区的绿化提供解决问题的新思路。     

马占相思接种根瘤菌对根际微生物及其林下植被生物量的影响

采用前期筛选的6个优良的根瘤菌株接种到马占相思幼苗上,并应用于造林试验。4.5 a后,通过对其林下根际土壤微生物和林下植被生物量的测定,探讨根瘤菌对人工马占相思林根际土壤微生物和林下植被生物量的影响。结果表明:根际土壤微生物的数量总和差异极显著(FF0.01),大小依次为:HM08HM04HJ06HJ07ZG03ZG04CK;林下植被总生物量差异不显著(FF0.05),大小依次为:HM08HM04HJ06ZG04ZG03HJ07CK。2项测定表明:HM08、HM04、HJ06 3个菌株相对较优良,且根际微生物的数量与其林下植被的总生物量和草本生物量表现出显著的线性正相关(P0.05),与木本生物量表现出极显著的线性正相关(P0.01)。     

徐州市水资源承载力研究

结合徐州市经济发展的基本现状和多年统计资料,以工业、农业、生活和生态四个方面需水作为指标体系,采用灰色预测模型GM（1,1）模型,以1986年为规划基准年,以2010和2020年为目标年对上述社会经济发展的指标进行了预测。以最大可支撑人口单目标模型为基准,根据灰色预测模型计算出的徐州市目标年人口和对因水资源可承载下的最大人口比较。结果表明,2010年徐州市水资源量是可承载的;2020年,徐卅市水资源极其缺乏,无法负担预测人口的正常生活。最后,对徐州市水资源合理利用提出了建议。     

A radial basis function neural network based self adapting predictive decoupling control system for gas collector pressure in coke ovens

Pressure is measured at different levels in the loop layer because self adapting predictive decoupling control systems are strongly coupled, disturbed, and non linear and there is a long time delay for gas collector pressure systems in coke ovens. By combing the traditional neural network control and proportional integral differential(PID) controllers based on radial basis function(RBF) neural network identification, the gas collector pressure is ensured to reach the desired technology range. The prediction model of an RBF neural network is used for advanced prediction of the actual output pressure to overcome delays in general gas collection. The simulation results and application indicate that the method can obtain ideal control results.     

一株耐铀及伴生重金属纤维素降解菌株的分离鉴定

筛选出耐受一定浓度铀及其伴生重金属胁迫的纤维素降解菌株,以期达到重金属富集植物体减容减重的目的。通过重金属浓度梯度摇瓶筛选和羧甲基纤维素(CMC-Na)水解圈等方法筛选出一株有较强重金属抗性的纤维素降解菌株C1。经过形态学,菌株培养特征,16S rDNA序列和gyrB基因序列系统发育树对分离菌株进行鉴定和分析,鉴定为革兰氏阳性地衣芽孢杆菌(Bacillus licheniformis)。菌株C1的羧甲基纤维素酶活(CMCA)在第4天最高为99.16 U/mL;滤纸酶活(FPA)在第3天达到最高为85.89 U/mL;在10天时秸秆失重率为33.10%。筛得一株耐受一定浓度铀及伴生重金属胁迫的纤维素降解菌C1,对处置富集重金属植物体具有一定的指导意义。     

基于高通量测序的牡蛎冷藏过程中微生物群落分析

为揭示牡蛎冷藏过程中微生物群落结构的变化规律,采用高通量测序技术对冷藏0、4、8 d牡蛎的菌群进行分析。结果表明高通量测序可以全面反映牡蛎中菌群的物种组成及丰度信息。牡蛎体附着的细菌以变形菌门(Proteobacteria)、γ-变形菌纲(Gammaproteobacteria)、弧菌目(Vibrionales)为主。在科的分类水平上,主要是弧菌科(Vibrionaceae)、希瓦氏菌科(Shewanellaceae)和交替假单胞菌科(Pseudoalteromonadaceae),其中初始样品以Vibrionaceae为主,比例达36.8%;第4天样品Pseudoalteromonadaceae比例相对较高;第8天样品同样以Pseudoalteromonadaceae为主,而Shewanellaceae比例明显增加,达到19.5%。在属的分类水平上,在牡蛎初始菌群中比例前三位依次为弧菌属(Vibrio)、希瓦氏菌属(Shewanella)和交替假单胞菌属(Pseudoalteromonas),其中Vibrio在冷藏前期比例迅速下降;Shewanella和Pseudoalteromonas在系统进化关系上较为接近,在冷藏后期比例占优,可能在牡蛎腐败过程中起到重要作用。研究结果可以为牡蛎的贮运保鲜策略提供参考。     

Modeling vegetation pattern using digital terrain data

Using a geographic information system (GIS), digital maps of environmental variables including geology, topography and calculated clear-sky solar radiation, were weighted and overlaid to predict the distribution of coast live oak (Ouercus agrifolia) forest in a 72 km² region near Lompoc, California. The predicted distribution of oak forest was overlaid on a map of actual oak forest distribution produced from remotely sensed data, and residuals were analyzed to distinguish prediction errors due to alteration of the vegetation cover from those due to defects of the statistical predictive model and due to cartographic errors. Vegetation pattern in the study area was associated most strongly with geologic substrate. Vegetation pattern was also significantly associated with slope, exposure and calculated monthlysolar radiation. The proportion of observed oak forest occurring on predicted oak forest sites was 40% overall, but varied substantially between substrates and also depended strongly on forest patch size, with a much higher rate of success for larger forest patches. Only 21% of predicted oak forest sites supported oak forest, and proportions of observed vegetation on predicted oak forest sites varied significantly between substrates. The non-random patterns of disagreement between maps of predicted and observed forest indicated additional variables that could be included to improve the predictive model, as well as the possible magnitude of forest loss due to disturbances in different parts of the landscape.     

Salmonella enterica subsp. salamae serovar Sofia,a prevalent serovar in Australian broiler chickens,is also capable of transient colonisation in layers

1. Salmonella enterica subsp. salamae serovar sofia (S. sofia) is a prevalent strain of Salmonella in Australian broilers and has been isolated from broiler chickens, litter, dust, as well as pre- and post-processing carcasses, and retail chicken portions but has never been reported in commercial Australian layers or eggs.

2. To investigate whether a S. sofia isolate from a broiler could colonise layers, one-month-old Hyline brown layers were orally inoculated with S. sofia and colonisation was monitored for 2–4 weeks.

3. Overall, 30–40% of the chickens shed S. sofia from the cloaca between 6 and 14 d post-inoculation which then declined to 10% by d 21. Necropsy at 2 weeks post-inoculation revealed 80% of birds harboured S. sofia in the caecum, whilst, by 4 weeks post-infection, no chickens were colonised with S. sofia in the gastrointestinal tract, liver or spleen. Additionally, no aerosol ‘bird to bird’ transfer was evident.

4. This study demonstrated that laying hens can be colonised by broiler-derived S. sofia; however, this colonisation was transient, reaching a peak at 14 d post-inoculation, and was completely cleared by 28 d post-inoculation. The transience of colonisation of S. sofia in layers could be a factor explaining why S. sofia has never been detected when screening for Salmonella serotypes found in Australian laying hens or eggs.     

Effect of herbal feed additives on performance parameters,intestinal microbiota,intestinal morphology and meat lipid oxidation of broiler chickens

ABSTRACT

1. This feeding trial investigated the effects of herbal feed additives on performance of broiler chickens, jejunal and caecal microbiota, jejunal morphology, meat chemical composition and oxidative stability during refrigerated storage.

2. In a 42 days trial, 320 one-day-old broiler chickens were randomly allocated to 4 groups with 4 replicate pens each containing 20 chicks. The control group was fed maize–soybean-based diets. The diets of the other three groups were supplemented with herbal feed additives: HRB1 with Stresomix^TM (0.5 g/kg feed); HRB2 with Ayucee^TM (1.0 g/kg feed); HRB3 with Salcochek Pro^TM (1.0 g/kg feed). The GC/MS analysis of the feed additives showed that the major components of HRB1 were β-caryophyllene (14.4%) and menthol (9.8%); HRB2 were n-hexadecanoic acid (14.22%) and β-caryophyllene (14.4%); and HRB3 were menthol (69.6%) and clavicol methyl ether (13.9%).

3. Intestinal samples were taken at 42 day to determine bacterial populations (total aerobe counts, Lactobacilli, and Escherichia coli) and perform gut morphology analysis. Meat samples were analysed for chemical composition and oxidative stability under storage.

4. The HRB1 group had improved (P < 0.05) body weight gain and tended to have improved (0.05 ≤ P < 0.10) feed conversion ratio, compared to the control group. Jejunum lactic acid bacteria counts were increased (P < 0.001) in groups HRB1 and HRB3, compared to the control group, whereas caecal lactic acid bacteria counts tended to increase (0.05 ≤ P < 0.10) in group HRB1, compared to the control group. Breast meat fat content tended to be lower (0.05 ≤ P < 0.10) in group HRB1. Meat oxidative stability was improved (P < 0.001), and jejunum villus height, crypt depth and goblet cells numbers were increased (P < 0.001) in all three herbal supplemented groups, compared to the control.

5. In conclusion, herbal feed additives may be able to improve both growth performance and antioxidant activity of broiler chickens, based on their phenolic compound content.     

A Kind of Adaptive Generalized Predictive Control for a Nonlinear System

This paper,using Hammerstein model to express a kind of nonlinear system,presents a new kind of Adaptive Generalized Predictive control for Nonlinear systems(NAGPC). This method divides the whole system into two parts: linear subsystem and nonlinear one. In the first part,a new algorithm ,whose computation quantity is less and speed is faster,is developed according to the characteristics of gain controlling Matrix F in the Generalized Predictive Control (GPC). Mean while, the interpolation method is used to develop one step root solving procedure and the result can be used as the whole system input in the second part. Simulation studies show that the general algorithm NAGPC is strong in robustness,good in stability and fast in computation.