Determination of Principal Components for Characterizing the Drying of Sea Cucumbers (Stichopus japonicus Selenka) Using Far Infrared Radiation Drying and Hot Air Drying

Principal component analysis (PCA) and multiple linear regression (MLR) were conducted to characterize the drying of sea cucumber (SC). Far infrared radiation drying (FIRD) and hot air drying (AD) were used to dehydrate SC. Thirteen variables—including the morphological, color, and textural properties of dried SC—were selected for statistical analysis. The analysis of these 13 variables yielded three principal components showing significant correlations. PCA showed that the first three components represented 86.2% of the total variation. The first principal component was primarily related to the morphological properties of SC. The principal components determined by the PCA were more strongly influenced by the morphological variables than by the drying method. Of the morphological variables, the weight of SC had the strongest influence on the drying time and rehydration ratio of FIRD and AD.     

玉米大斑病菌和小斑病菌交配型多重PCR 检测方法的建立与应用

【目的】由大斑突脐蠕孢（Exserohilum turcicum）和玉蜀黍平脐蠕孢（Bipolaris maydis）引起的玉米大斑病和小斑病是玉米生产上重要的叶部真菌病害,本研究旨在建立玉米大斑病菌和小斑病菌交配型多重PCR检测方法,为玉米大斑病菌和小斑病菌的交配型田间分布和有性生殖研究提供技术方法。【方法】根据GenBank中已登录的玉米大斑病菌（登录号MAT1-1：GU997138和MAT1-2：GU997137）和小斑病菌（登录号MAT1-1：X68399和MAT1-2：X68398）交配型基因序列,利用Primer Premier 5.0软件设计2种病原菌交配型多重PCR检测特异性引物,采用单因素法对引物的退火温度以及扩增程序中延伸时间和循环数等重要参数进行优化,建立玉米大斑病菌和小斑病菌交配型多重PCR检测方法,并对2种病原菌的交配型多重PCR检测灵敏度和特异性进行检验。同时,对田间采集的129株玉米大斑病菌和194株玉米小斑病菌单孢菌株的交配型进行多重PCR检测,以明确建立的交配型多重PCR检测方法的适用性。【结果】建立的多重PCR方法和设计的交配型特异引物StMAT01-2F/R、StMAT02-3F/R、ChMAT01-3F/R和ChMAT02-2F/R可分别扩增出MAT1-1、MAT1-2型菌株大小为816、132 bp（大病斑菌）与490、136 bp（小病斑菌）的特异性目的条带。25 μL多重PCR扩增体系：2×Multiplex PCR Mix 12.5 μL,引物各10 pmol,DNA模板100 ng,退火温度为57.2℃（大病斑菌）和55.0℃（小斑病菌）,35个循环。该多重PCR对玉米大斑病菌MAT1-1、MAT1-2型单孢菌株的检测灵敏度分别为0.1、0.01 ng基因组DNA,而对玉米小斑病菌MAT1-1、MAT1-2交配型的检测灵敏度均为0.1 ng基因组DNA。该交配型多重PCR检测方法对玉米大斑病菌和小斑病菌特异性很强,能够很好地区分玉米大斑病菌和小斑病菌相应的近缘种和14株其他真菌菌株。不同地理来源的玉米大斑病菌和小斑病菌交配型检测结果表明,该多重PCR能够准确地检出129株玉米大斑病菌和194株玉米小斑病菌的交配型,且检测结果与随机抽取的菌株杂交验证结果完全吻合。【结论】构建的玉米大斑病菌和小斑病菌交配型多重PCR检测方法灵敏度高、特异性好、操作简便,能够准确、快速地检测出玉米大斑病菌和小斑病菌的交配型,为玉米大斑病菌和小斑病菌的交配型田间分布和监测及有性生殖研究提供了可靠的技术方法。     

不同增稠剂对农药可分散油悬浮剂稳定性的影响

为明确不同增稠剂对以矿物油为分散介质的油悬浮体系稳定性的影响,以12.5%丙炔·吡嘧(丙炔噁草酮·吡嘧磺隆)可分散油悬浮剂为对象,通过流变学和多重光散射方法,研究了有机膨润土、有机高分子和气相二氧化硅3类增稠剂单独使用及有机膨润土和其他两类增稠剂分别搭配使用对可分散油悬浮剂物理稳定性的影响。结果表明:所有样品的流动特性指数(n)均小于1,为假塑性流体,具有触变性。除有机膨润土和高分子增稠剂Atlox Rheostrux100组合使用时体系更符合Casson方程外,其余样品均更符合Herschel-Bulkley方程。单独使用时,有机膨润土对保证体系稳定的效果相对较好;Atlox Rheostrux 100和Atlox Rheostrux200两种高分子增稠剂的效果差别较大,其中Atlox Rheostrux 100效果更好,这可能是由分子结构差异造成;两种气相二氧化硅类增稠剂由于不能有效形成氢键,效果较差。将有机膨润土和有机高分子增稠剂组合使用时,体系的稳定性有所提升,其中有机膨润土869和Atlox Rheostrux 100组合使用效果更好,体系具有较高的黏度,且具有良好的触变性,物理稳定性优异;有机膨润土869和疏水气相二氧化硅R974组合使用时则效果没有明显的提升。研究表明,流变学和多重光散射两种方法均能较好地表征可分散油悬浮剂的物理稳定性;新型高分子增稠剂和有机膨润土具有协同作用,将二者合理组合添加能大幅提升可分散油悬浮剂的稳定性。     

Cause and Consequence in Maize Planting Dates in Germany

An important part of agricultural adaptation is the timing of crop sowing dates, affecting yields and the level of risk incurred during a particular season. Cold stress is especially relevant in maize, Zea mays L., so that the timing of planting in the spring is a tactical response to short‐term weather, but is also subject to strategic planning with regard to longer‐term climate. Both factors compare the potential implications of cold stress to the additional yield obtainable through earlier planting. New cultivars suited to growing conditions in Europe and generally increasing spring temperatures have enabled earlier planting, but it is still dependent on short‐term weather during the planting period. In the context of field‐level decision‐making, a panel regression is used to estimate the relationship between weekly local temperature and precipitation and planting dates at specific sites throughout Germany. Next, localised weather data and planting behaviour are linked to yields at the district (Landkreis) level to show the effects of planting date on yield. Based on these relationships optimal planting dates are explored with some associated costs and benefits. Results show a trend towards earlier planting that follows observed increasing spring temperatures and the availability of more cold‐tolerant cultivars but this advance is buffered by the increasing severity of minimum temperatures during a critical period. Earlier planting potentially increases yield but this is offset by additional management costs and risk. A robust and simple depiction of farmer behaviour in climatic, technological and economic context can help to understand trends in crop management and productivity that effect agricultural landscapes.     

基于PCA-SVR-ARMA的狮头鹅养殖禽舍气温组合预测模型

为提高狮头鹅养殖禽舍气温预测精度,提出了基于主成分分析(Principal Component Analysis,PCA)、支持向量回归机(Support Vector Regression,SVR)融合自回归滑动平均(Autoregressive Moving Average,ARMA)模型的狮头鹅养殖禽舍气温组合预测模型。在建模过程中,运用主成分分析法筛选狮头鹅养殖禽舍气温的关键影响因子,消除变量之间冗余信息,约简预测模型结构;采用SVR-ARMA构建狮头鹅禽养殖舍气温组合预测模型,先通过SVR对气温进行预测,再由基于ARMA模型的残差预测值修正气温预测结果。利用该模型对广东省汕尾市2018年7月21日至2018年7月30日期间的狮头鹅养殖禽舍气温进行预测。结果表明,该组合预测模型取得了良好的预测性能,与标准BP神经网络、标准SVR、PCA-BPNN(反向传播神经网络,BackPropagationNeuralNetwork)、PCA-SVR和PCA-BPNN-ARMA等模型对比分析,其评价指标平均绝对误差、均方根误差和平均绝对百分比误差分别为0.183 2℃、0.454 0℃和0.005 9,均表明所提出的组合模型具有更高的预测效果,不仅能够满足狮头鹅养殖禽舍气温实际精准调控的需要,还为狮头鹅健康养殖和种苗繁育环境精细化管理提供决策。     

北京松山自然保护区主要树种冠幅预测模型研究

冠幅作为林业研究的关键因子，开展冠幅的研究对于精准林业发展具有重要意义。为了更好地利用冠幅对树木其他因子进行预测，选取了北京市松山自然保护区油松、白蜡、蒙古栎等14个常见树种作为研究对象，基于6种回归方程，借助样地实测数据分别建立每个树种的胸径 冠幅和树高 冠幅模型，并针对每个树种筛选出的最优方程进行了精度检验。结果表明，研建的14个树种的模型具有较好的拟合精度，决定系数R2绝大多数都大于0.5，其中，核桃的胸径 冠幅模型最高，R2=0.951，树高-冠幅模型R2=0.887，蒙古栎树高-冠幅模型最低，R2=0.506，也超过了0.5。所建模型的精度评价指标具有一定的统计学意义，对北京市松山地区大面积林分参数的预测预估有重要的参考价值。     

Multiple resistance of Papaver rhoeas L. to 2,4‐D and acetolactate synthase inhibitors in four European countries

The issue of cross‐ or multiple resistance to acetolactate synthase (ALS) inhibitors and the auxinic herbicide 2,4‐D was investigated in Papaver rhoeas L., a common and troublesome weed in winter cereals, in a broad‐scale study across four European countries. A combination of herbicide sensitivity bioassays and molecular assays targeting mutations involved in resistance was conducted on 27 populations of P. rhoeas originating from Greece (9), Italy (5), France (10) and Spain (3). Plants resistant to the field rate of 2,4‐D were observed in 25 of the 27 populations assayed, in frequencies ranging from 5% to 85%. Plants resistant to ALS‐inhibiting herbicides (sulfonylureas) were present in 24 of the 27 populations, in frequencies ranging from 4% to 100%. Plants resistant to 2,4‐D co‐occurred with plants resistant to sulfonylureas in 23 populations. In four of these, the probability of presence of plants with cross‐ or multiple resistance to 2,4‐D and sulfonylureas was higher than 0.5. ALS genotyping of plants from the field populations or of their progenies, identified ALS alleles carrying a mutation at codon Pro197 or Trp574 in 2,4‐D‐sensitive and in 2,4‐D‐resistant plants. The latter case confirmed multiple resistance to 2,4‐D and ALS inhibitors at the level of individual plants in all four countries investigated. This study is the first to identify individual plants with multiple resistance in P. rhoeas, an attribute rarely assessed in other weed species, but one with significant implications in designing chemical control strategies.     

土壤外源钴对大麦根伸长的毒害及其预测模型

选取我国11种不同性质的农田土壤，通过外源添加重金属钴（Co），研究其对大麦（Hordeum vulgare L.）根伸长的毒性阈值及土壤性质对Co毒性的影响。结果发现，Co对大麦根伸长10%抑制效应（EC₁₀）在11种土壤中的变化范围为37.1~3 914 mg·kg^-1土（105.5倍），50%抑制效应（EC₅₀）的变化范围为166.1~6 030 mg·kg^-1土（36.3倍）。建立土壤性质与毒性阈值的回归方程，结果表明土壤pH是影响土壤Co毒性阈值最重要的因子，作为单因子时分别可以解释77.6%、72%的EC₁₀和EC₅₀的变异（P≤0.001）。当在EC₁₀预测模型中引入土壤pH和土壤黏粒（Clay）双因子时，可以解释83.9%的EC₁₀的变异（P<0.001），EC₅₀预测模型中引入土壤pH和总碳（TC）双因子时，可以解释86.1%的EC₅₀的变异（P<0.001）。将我国土壤中得到的Co毒性阈值预测模型和欧洲北美10种土壤的预测模型进行比较验证，结果发现基于我国土壤得到的预测模型可以较为准确地预测欧洲北美土壤中Co的大麦根伸长毒性阈值，但基于欧洲北美土壤的预测模型不能准确预测我国土壤中Co的毒性阈值。研究表明，我国土壤性质对Co毒性有显著的影响，基于土壤性质建立的预测模型可为土壤中Co生态风险评价提供参考依据。     

Analysis of green total factor productivity trend and its determinants for the countries along silk roads

In coping with increasing energy consumption and the consequential environmental pollution, green development is becoming an important part of social development. Since the inauguration of China’s Silk Road Economic Belt Initiative (BRI), economic cooperation between China and other countries along BRI has seen much growth. Therefore, it is of great significance to study the levels of green total factor productivity (GTFP) of the countries in the Silk Roads Economic Belt (B&R) and examine how these levels vary spatially and evolve temporally. In this paper, a panel regression analysis with DEA windows is used to study the spatiotemporal trends of the levels of GTFP. The results are: (1) The B&R countries have seen an increase in their overall levels of GTFP over time; (2) There are regional differences in the levels of GTFP, with higher efficiency in Western Asia and Central and Eastern Europe, and lower efficiency in Southeast and Central Asia; (3) The analysis of GTFP for countries in these regions shows that the efficiencies of most countries have been improving, with that of only a few countries have been decreasing; (4) By using regression analysis, we find that variables such as import, export, industrial structure, and urban affect the B&R countries with growing GTFP.     

农业分区框架下Hargreaves-Samani公式的逐月回归修正

为验证中国农业综合分区框架下Hargreaves-Samani(HS)公式线性回归修正方案的适用性,利用中国气象数据网发布的124个站点1957—2016年的逐月有效日平均气压、平均最低气温、平均最高气温、平均风速、平均水汽压、月总太阳辐射数据及站点经纬度数据,首先,分别基于Penman-Monteith(PM)公式和HS公式计算了各站点多年逐月的参考作物需水量ET_(0-PM)和ET_(0-HS)。然后,以ET_(0-PM)为真值,基于1957—2010年的逐月ET_(0-PM)和ET_(0-HS),利用线性回归分析方法获取了中国38个农业管理子区的HS公式校正系数a、b,并以2011—2016年为验证年份,通过比较ET_(0-HS)校正前后的相对误差变化,验证了HS公式线性回归校正方法在中国农业区的适用性,并结合验证年份的具体误差结果,确定了各农业区HS公式校正系数a、b的逐月最优取值。结果表明:大部分农业区的大部分月份ET_(0-PM)与ET_(0-HS)的相关系数超过0. 6,可以进行ET_(0-HS)的回归校正;回归校正得到的系数a存在显著的季节变化规律,系数b则表现较为平稳;系数a、b的大小及变化说明了ET_(0-PM)和ET_(0-HS)彼此之间存在差异,且季节性明显;校正前后的ET_(0-HS)均存在不同程度的相对误差,但校正后的ET_(0-HS)的误差范围已经显著缩小;在具体的验证应用中,校正后的ET_(0-HS)并不完全是最优结果,实践中系数a、b的优选使用才是最佳方案。本研究验证的HS公式线性回归校正方法是实践中简便、可行的方案,对大尺度区域快速获得较高精度的参考作物需水量具有实际意义和推广价值。