不同裂解温度的污泥生物质炭理化特性分析

研究裂解温度对污泥生物质炭基础理化性质的影响,为安全、合理、高效处置污泥提供理论依据。将干燥污泥分别在200、300、500、700℃下进行热裂解处理(SBC200、SBC300、SBC500、SBC700),获得污泥生物质炭,测定其基础理化特性。结果表明：不同温度制备的污泥生物质炭表面颗粒结构完好,孔径范围均集中在10~50 μm,其中低温生物质炭SBC200表面较光滑,最可几孔径和中值孔径最大,分别为20.1 μm和14.8 μm,高温生物质炭SBC700表面较粗糙,比表面积最大,为5.98 m²/g。随裂解温度的提高,污泥生物质炭的产率、含水量、电导率、挥发分、阳离子交换量显著下降,全碳、氧、全氮、氢含量、有效磷和铵态氮均逐渐降低,pH和灰分含量显著增加。将污泥制备成生物质炭,是安全处置污泥的有效途径,低温制得的污泥生物质炭具有更大的提高土壤肥力的潜力,而高温制得的生物质炭在改良土壤酸性的应用上具有更大的潜力。     

五常市杂种落叶松幼龄期变异分析

以5年生36个杂种落叶松家系为材料,测定其树高、胸径生长性状,估算变异系数、遗传力和遗传增益,筛选出优良家系。结果表明:各家系的树高、胸径存在较丰富变异,树高变异系数小于胸径,树高、胸径极显著相关(P<0.01),家系间树高、胸径差异均达极显著差异水平(P<0.01)。以10%的入选率,初选出家系1317、1324、1318、和1327为优良家系,树高平均增益为15.98%,胸径平均增益为29.46%。     

Genetic diversity and aggressiveness of Calonectria pteridis in Eucalyptus spp.

Calonectria leaf blight, caused by Calonectria pteridis, is currently one of the main foliar diseases in eucalypt plantations in Brazil. In warm and high rainfall regions, the disease can be a limiting factor for eucalypt production when planting susceptible genotypes. The most effective method for controlling this disease in the field is the use of resistant genotypes, which requires knowledge of the genetic variability and aggressiveness of the pathogen population for effective deployment of plant resistance. This work evaluated the genetic diversity and aggressiveness of C. pteridis populations obtained from infected eucalypt plants in Monte Dourado (Pará state) and Imperatriz (Maranhão state), Brazil. To study the genetic diversity, 16 ISSR primers were tested, five of which amplified polymorphic, reproducible and informative bands. Thirty-one closely related genotypes were identified from 84 isolates studied, indicating that the population has a low genetic diversity. The aggressiveness of seven isolates, selected according to geographic origin and their clustering in the ISSR-based dendogram, was determined by inoculation of a hybrid Eucalyptus grandis × E. urophylla clone under controlled conditions. Disease severity was assessed by both measuring the percentage of plant defoliation and assigning a score according to a diagrammatic scale of symptoms. A high correlation between the two evaluation methods was observed, which revealed significant differences in aggressiveness among the isolates. The diagrammatic scale is recommended for disease evaluation because results are obtained much faster, before the occurrence of severe defoliation. No correlation between clustering in the ISSR-based phylogenetic analysis and aggressiveness was observed.     

芦笋种植对冷凉沙化区土壤改良的效果研究

为探索芦笋种植对冷凉沙化区土壤的改良效果,在山西省朔州市右玉县,以未种植芦笋裸沙地为对照（CK）,设置种植芦笋1、2、3和4年共4个处理,通过田间试验测定不同种植年限芦笋田土壤理化特性和芦笋生长发育情况。结果表明,与CK相比,随种植年限增加,土壤黏粒和粉砂粒含量递增,砂粒含量递减,土壤容重递减,土壤田间持水量递增;土壤pH和可溶性盐浓度（EC）递减;土壤有机质、全氮、有效磷和速效钾含量逐年递增。种植芦笋3年的土壤粒级、土壤容重、田间持水量、pH、EC值、土壤肥力发生显著变化;连续种植芦笋4年的土壤黏粒含量较CK增加到29.8%,粉砂粒含量增加到12.6%,砂粒含量降低到57.6%,田间土壤持水量显著提高,土壤容重显著降低,土壤由砂质壤土向砂质黏土转变;土壤pH降低0.75,EC值降低0.08mS/cm;土壤有机质含量增加28.89%,全氮、有效磷和速效钾含量分别增加95.12%、94.92%和45.40%;芦笋产量达6 037.5kg/hm ²。综合分析,连续种植芦笋4年可改善沙化土壤的物理结构,提高土壤养分,降低盐碱程度。芦笋是冷凉沙化区土壤改良的先锋作物之一,可实现生态效益与经济效益并举。     

Variability in the performance of juvenile Chinook salmon is explained primarily by when and where they resided in estuarine habitats

Estuarine habitats provide rearing opportunities for the juvenile life stage of anadromous fishes. Because survival is positively correlated with juvenile performance, these estuarine habitats play an important role in population abundance and productivity. To provide information for the recovery of several depressed stocks of Chinook salmon in the Columbia River Basin, we sought to identify the factors that explain variability in performance. Using otolith‐derived estimates of juvenile somatic growth rate as an index of recent performance, we observed a negative nonlinear relationship between growth rate and day of year, and a decreasing and increasing trend of growth rate over the 8 years of this study and distance from the river mouth respectively. Using a generalised linear modelling approach, we found that variability in juvenile somatic growth rate was best explained by where and when individuals were collected, their body size, contaminant loads, stock of origin, and whether a fish was hatchery produced or unmarked. Lastly, we argue that a considerable improvement to the growth rate of juveniles in estuarine habitats is physiologically possible. The results of this 8‐year study provide a baseline of the performance of juvenile Chinook salmon to evaluate habitat restoration programs and to compare against future anthropogenic conditions.     

四川省不同地域的核盘菌遗传多样性分析

 核盘菌(Sclerotinia sclerotiorum)属于世界性分布的植物病原真菌,可以危害油菜等多种经济作物。研究不同地域核盘菌的遗传多样性对了解核盘菌的遗传演化过程和指导病害防控具有重要意义。实验采用序列相关扩增多态性(sequence-related amplified polymorphism,SRAP)标记对四川省17个不同地理来源的66株核盘菌菌株的遗传多样性进行了分析。10对检测引物共获得129个位点,其中123个为多态位点,占95.35%。UPGMA聚类结果显示,在相似性系数为0.7时,66个核盘菌菌株分为5类(Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ),分别包含60、2、2、1和1个菌株。在相似性系数为0.74时,第Ⅰ类又可分为3个亚类(Ⅰ-1、Ⅰ-2、Ⅰ-3),分别包含21、37和2个菌株。聚类及组成分分析结果显示,四川省各地区的核盘菌菌株具有较高的遗传多样性,但其遗传变异与菌株地理来源无明显相关性。     

中国地方绵羊群体TYRP1基因遗传变异研究

本研究旨在了解酪氨酸酶相关蛋白1（tyrosinase related protein 1，TYRP1）基因在中国地方绵羊群体内的遗传变异，以及TYRP1基因突变与不同毛色表型绵羊群体的相关性。通过直接测序法和PCR-RFLP技术对10个中国地方绵羊群体进行单核苷酸多态性（SNP）检测，利用Beagle、PLINK和POPGENE等软件对突变位点数据进行单倍型构建、连锁不平衡分析和遗传变异研究。突变位点检测结果表明，在绵羊TYRP1基因内识别了13个SNPs，其中位于TYRP1基因外显子上的10个SNPs位点，除个别位点在大尾寒羊、中国美利奴羊和岷县黑裘皮羊中没有发生突变外，其他突变位点在所有绵羊品种中均出现不同程度变异，说明中国地方绵羊群体具有较高的遗传多样性。单倍型分析结果表明，所有样本中共有42个单倍型，优势单倍型0000000000（245/918）、0100000001（91/918）在所有绵羊群体中均存在，除单倍型0101100000（93/918）在中国美利奴羊中没有出现，单倍型0001000001（69/918）在岷县黑裘皮羊、哈萨克羊群体中没有出现外，在其他群体中均存在。连锁分析结果表明，10个SNPs在所有样本中均存在2个连锁模块。群体遗传变异分析表明，中国地方绵羊群体具有较高水平的群体内遗传变异，各绵羊品种间存在明显的遗传分化模式，且各品种遗传关系与其品种传统分类结果基本一致。本研究为进一步研究TYRP1基因对绵羊毛色遗传性状的影响提供了参考依据。     

Precipitation forecasting by large-scale climate indices and machine learning techniques

Global warming is one of the most complicated challenges of our time causing considerable tension on our societies and on the environment. The impacts of global warming are felt unprecedentedly in a wide variety of ways from shifting weather patterns that threatens food production, to rising sea levels that deteriorates the risk of catastrophic flooding. Among all aspects related to global warming, there is a growing concern on water resource management. This field is targeted at preventing future water crisis threatening human beings. The very first stage in such management is to recognize the prospective climate parameters influencing the future water resource conditions. Numerous prediction models, methods and tools, in this case, have been developed and applied so far. In line with trend, the current study intends to compare three optimization algorithms on the platform of a multilayer perceptron (MLP) network to explore any meaningful connection between large-scale climate indices (LSCIs) and precipitation in the capital of Iran, a country which is located in an arid and semi-arid region and suffers from severe water scarcity caused by mismanagement over years and intensified by global warming. This situation has propelled a great deal of population to immigrate towards more developed cities within the country especially towards Tehran. Therefore, the current and future environmental conditions of this city especially its water supply conditions are of great importance. To tackle this complication an outlook for the future precipitation should be provided and appropriate forecasting trajectories compatible with this region's characteristics should be developed. To this end, the present study investigates three training methods namely backpropagation (BP), genetic algorithms (GAs), and particle swarm optimization (PSO) algorithms on a MLP platform. Two frameworks distinguished by their input compositions are denoted in this study: Concurrent Model Framework (CMF) and Integrated Model Framework (IMF). Through these two frameworks, 13 cases are generated: 12 cases within CMF, each of which contains all selected LSCIs in the same lead-times, and one case within IMF that is constituted from the combination of the most correlated LSCIs with Tehran precipitation in each lead-time. Following the evaluation of all model performances through related statistical tests, Taylor diagram is implemented to make comparison among the final selected models in all three optimization algorithms, the best of which is found to be MLP-PSO in IMF.     

基于粗糙遗传算法在打捆机齿轮箱故障诊断中的应用*

自走式连续作业打捆机是一款实现不停机连续打捆作业的新型秸秆收集装备,其关键功能部件齿轮箱发生故障会严重影响正常打捆工作。针对齿轮箱故障的防控和监测,提出一种结合粗糙集和遗传算法的故障诊断方法。该方法使用时域频域分析得到的多项故障特征参数作为条件属性,故障类型作为决策属性,并利用自适应遗传算法得到决策规则表,实现无需先验信息的属性约简和故障诊断。在齿轮箱故障诊断试验中,分别对不同故障类型进行信号采集和诊断分析,结果显示:该方法在无先验信息的条件下将12项故障特征参量约简为3项,根据决策规则表进行故障诊断的准确率为100%,结果表明该方法能准确判断故障的发生和故障类型,对实现故障监测和防控具有重要意义。     

巨菌草在动物饲养和生态改善领域的应用研究进展

巨菌草具有适应性广、抗逆性强、根系发达、营养含量丰富、产量高等特点,近年来在动物饲养和生态改善领域得到了广泛应用。本文综述了近年来巨菌草在动物饲养和生态改善领域的最新研究应用进展,对其存在的问题进行讨论,并对其发展前景提出了建议,以期为巨菌草的开发利用提供参考。