A novel method for the quantitative assessment of the percolation of <Emphasis Type="Italic">Metarhizium anisopliae</Emphasis> conidia through horticultural growing media

Incorporation of fungal biological control agents (BCAs) into plant growing media has considerable ergonomic and economic benefits for growers. These agents usually give prophylactic control of target pests and diseases. However, their efficacy is dose dependent and loss of inoculum through leaching could influence the degree of protection they provide. At present there are no protocols to determine the loss of inoculum in the disparate growing media used in horticulture. We describe a method based on a nutrient leaching column to quantify leaching of conidia of the insect-pathogenic fungus Metarhizium anisopliae in a range of growing media. Conidia of this biocontrol agent were applied as a drench or premixed into the medium. Both the application method and growth medium influenced conidial leaching. Inoculum losses were greater following drench application than premixing (95% vs. 15%) irrespective of media type. Comparatively more inoculum was lost from bark and coir following drench application whereas losses were relatively high in peat following premixed application. The leaching column assay provided a simple and accurate method to quantify inoculum loss in real time. This assay could help determine leaching of other fungal BCAs in growing media. It could help in improving pest and disease control by optimizing the rate and frequency of conidial application as well in the design of more efficacious formulations.     

Research on WNN Greenhouse Temperature Prediction Method Based on GA

Temperature in agricultural production has a direct impact on the growth of crops. The emergence of greenhouses has improved the impact of the original unpredictable changes in temperature, but the temperature modeling of greenhouses is still the main direction at present. Neural network modeling relies on sufficient actual data to model greenhouses, but there is a widening gap in the application of different neural networks. This paper proposes a greenhouse temperature prediction model based on wavelet neural network with genetic algorithm (GA-WNN). With the simple network structure and the nonlinear adaptability of the wavelet basis function, wavelet neural network (WNN) improved model training speed and accuracy of prediction results compared with back propagation neural networks (BPNN), which was conducive to the prediction and control of short-term greenhouse temperature fluctuations. At the same time, the genetic algorithm (GA) was introduced to globally optimize the initial weights of the original model, which improved the insensitivity of the model to the initial weights and thresholds, and improved the training speed and stability of the model. Finally, simulation results for the greenhouse showed that the model training speed, prediction results accuracy and model stability of the GA-WNN in the greenhouse were improved in comparison to results obtained by the WNN and BPNN in the greenhouse.     

Diversity of Saxicolous Lichens along an Aridity Gradient in Central México

Lichens are symbiotic organisms that comprise a fungus and a photosynthetic partner wich are recognized as a good indicator of climate change. However, our understanding of how aridity affects the diversity of saxicolous lichens in drylands is still limited. To evaluate the relationship between saxicolous lichen diversity and aridity in a central México dryland, a geographical transect was established of 100 km to build an aridity gradient in the semiarid zone of the State of Querétaro, Mexico, comprising ten sampling sites with a 10 km separation. Species richness, abundance and diversity of soil lichen species were recorded using two sampling methods: the quadrat-intercept and the line-intercept method, to compare their performance in assessing soil lichen diversity in drylands. The number of species and Shannon diversity of saxicolous lichens were higher at intermediate values of the aridity index (AI = 0.10–0.34). Quadrat intercept and point intercept methods gave quite similar results, which means that the selected method does not influence the results in a significant way. This study confirms the role of saxicolous lichens as climate change indicators and reveals the importance of the sampling method selection in the evaluation of different parameters of soil lichen diversity in drylands.     

昼夜变温幅度对小菜蛾不同发育阶段生活史性状的影响

【目的】昼夜变温幅度对昆虫的发育、存活、寿命、繁殖等核心生命活动有非常重要的影响。以往研究主要以恒温为主,温度设置不符合自然界中昼夜温度波动变化,无法明确温度波动幅度与恒温之间的生物效应差别。【方法】本研究采用了二步变温,模拟了不同的昼夜温度波动幅度(25±2℃,25±4℃,25±6℃,25±8℃,25±10℃和25±12℃)与相应恒温25℃,研究了不同变温幅度对十字花科世界性害虫小菜蛾Plutella xylostella不同生活史阶段中发育、存活、寿命与繁殖的影响。【结果】结果表明,变温幅度对小菜蛾不同阶段的发育、存活、寿命与繁殖影响存在显著差异。25±2℃,25±4℃和25±6℃对小菜蛾生活史性状的影响与恒温(25℃)相似,但25±10℃和25±12℃却产生了显著的负面影响。【结论】我们发现,较大的昼夜变温幅度显著影响小菜蛾不同阶段的发育、存活、寿命与繁殖,而适宜夜低温在一定程度上修复了日高温胁迫对小菜蛾的不利影响;并且认为昼夜变温幅度作为影响昆虫核心生命活动一种重要决定因素,必需纳入到昆虫种群数量预测模型中,才能真实地反映自然界中复杂变温模式对昆虫生态学效应的影响,才能提高昆虫田间发生预测预报的准确性。     

Room temperature crystal structure of the fast switching M159T mutant of the fluorescent protein dronpa

The fluorescent protein Dronpa undergoes reversible photoswitching reactions between the bright “on” and dark “off” states via photoisomerization and proton transfer reactions. We report the room temperature crystal structure of the fast switching Met159Thr mutant of Dronpa at 2.0‐Å resolution in the bright on state. Structural differences with the wild type include shifted backbone positions of strand β8 containing Thr159 as well as an altered A‐C dimer interface involving strands β7, β8, β10, and β11. The Met159Thr mutation increases the cavity volume for the p‐hydroxybenzylidene‐imidazolinone chromophore as a result of both the side chain difference and the backbone positional differences. Proteins 2015; 83:397–402. © 2014 Wiley Periodicals, Inc.