Impact of weather variables and season on sporulation of Phytophthora pluvialis and Phytophthora kernoviae

Phytophthora pluvialis and Phytophthora kernoviae are the causal agents of important needle diseases on Pinus radiata in New Zealand. Little is known about the epidemiology of the diseases, making the development of control strategies challenging. To investigate the seasonality and climatic drivers of sporulation, inoculum traps, consisting of pine fascicles floating on water in plastic containers, were exchanged fortnightly at five sites in P. radiata plantations between February 2012 and December 2014. Sections of needle baits were plated onto selective media and growth of Phytophthora pluvialis and P. kernoviae recorded. To explore the generalizability of these data, they were compared to detection data for both pathogens from the New Zealand Forest Health Database (NZFHDB). Further, equivalent analyses on infection of Rhododendron ponticum by P. kernoviae in Cornwall, UK allowed the comparison of the epidemiology of P. kernoviae across different host systems and environments. In New Zealand, inoculum of P. pluvialis and P. kernoviae was detected between January–December and March–November, respectively. Inoculum of both species peaked in abundance in late winter. The probability of detecting P. pluvialis and P. kernoviae was greater at lower temperatures, while the probability of detecting P. pluvialis also increased during periods of wet weather. Similar patterns were observed in NZFHDB data. However, the seasonal pattern of infection by P. kernoviae in the UK was the opposite of that seen for sporulation in New Zealand. Phytophthora kernoviae was likely limited by warmer and drier summers in New Zealand, but by colder winter weather in the UK. These results emphasize the importance of considering both environmental drivers and thresholds in improving our understanding of pathogen epidemiology.     

果园有机肥深施机分层变量排肥控制系统设计与试验

果园不同深度的土壤养分不同，果树根系分层吸肥能力不同，有机肥分层变量深施可以解决传统施肥存在的养分分布不均和肥料利用率低等问题。针对有机肥分层变量深施的排肥控制问题，本文设计了排肥控制系统，可以根据用户设置的各层理论排肥量和作业速度，实时计算液压马达的理论转速，并采用PID算法控制比例流量阀开度，调节马达转速驱动螺旋输送器排肥，实现分层变量排肥。将AMESim中建立的液压系统模型与在Matlab/Simulink中建立的控制模型进行联合仿真，整定PID参数。液压马达转速调节性能试验中最大超调量为14r/min，达到稳定转速的时间最大为6s，控制性能较好，表明通过AMESim-Matlab/Simulink联合仿真，能够快速便捷地整定PID参数，结果准确可靠。排肥控制性能试验中排肥量相对误差最大6.20%，变异系数最大8.69%，排肥量准确性和均匀性均达到要求。设计的控制系统具有较好的性能，能为果园有机肥分层变量深施提供技术支撑。     

竹花叶病毒浙江麻竹分离物全基因组序列及siRNA分析

正已知有3种病毒可在自然条件下侵染竹类植物,即竹花叶病毒(bamboo mosaic virus,BaMV)~[1]、樱桃坏死锈斑驳病毒(cherry necrotic rusty mottle virus,CNRMV)和苹果茎沟病毒(apple stem grooving virus,ASGV)~[2,3]。其中,BaMV是最早在巴西的金竹(Bambusa vulgaris Cv.)和孝顺竹     

Development of a linear mixed-effects individual-tree basal area increment model for masson pine in Hunan Province,South-central China

ABSTRACT

An individual-tree basal area increment model was developed for masson pine based on 26276 observations of 13,138 trees in 987 sample plots from the 7th (2004), 8th (2009), and 9th (2014) Chinese National Forest Inventory in Hunan Province, South-central China. The model was built using a linear mixed-effects approach with sample plots included as random effects since the data have a hierarchical stochastic structure and biased estimates of the standard error of parameter estimates could be a consequence of applying ordinary least square (OLS) for regression. In addition, within-plot heteroscedasticity and autocorrelation were also considered. The final mixed-effects model was determined according to the Akaike information criterion (AIC), Bayesian information criterion (BIC), log-likelihood (Loglik), and the likelihoodratio test (LRT). The results revealed that initial diameter (DBH), the sum of the basal area (m²/ha) in trees with DBHs larger than the DBH of the subject tree (BAL), number of trees per hectare (NT), and elevation (EL) had a significant impact on individual-tree basal area increment. The mixed-effects model performed much better than the basic model produced using OLS. Additionally, the variance structure of the model errors was successfully modeled using the power function. However, the autocorrelation structures were not defined because there was no autocorrelation amongst the data. It is believed that the final model will contribute to the scientific management of the masson pine.     

利用马尾松解析木对林地立地指数和立地形的研究

利用重庆市南川区马尾松解析木数据，选择合适的导向曲线方程，建立基于导向曲线的立地指数和立地形模型，并对立地形的适用性进行说明。根据散点图和三倍标准差对解析木数据进行了选择，排除了不符合要求的圆盘记录对。采用5种常用的经验生长方程对年龄-树高、胸径-树高进行拟合，根据决定系数R²,均方根误差RMES、 AIC、方程的参数变动系数以及拟合曲线对方程进行选择；根据选定的方程，求出其连续生长量方程和平均生长量方程，并采用matlab绘制出其曲线方程，根据连续生长量和平均生长量次相交后的下一个龄（径）阶，选择出基准年龄（胸径）；利用标准差调整法进行编表，编表后采用成对T检验方法对立地指数表和立地形表进行验证。结果表明，立地指数和立地形的表达精度在95%水平下显著，平均总相对误差和相对总误差都<5%，而预估精度分别达到了99.18%和99.22%，说明所编立地指数表和立地形表精度较高，能够满足编表需要。根据导向曲线绘制生长量曲线方程的方法确定基准年龄和基准胸径的方法准确可行；由于龄阶和径阶的选择差异，导致立地指数级不同，同时影响了立地形与立地指数的编表质量；由于树木的生长特性，立地形在表示立地质量时，在林木的早期将会低于立地指数，在树木生长的中后期将会高于立地指数；立地形的适用性取决于胸径与树高的相关性，相关性越强，立地形就越准确，在选择合适的优势木的情况下，立地形可以取代立地指数来表示林地质量。     

面向养殖水体分布差异的COD光谱法检测研究

面向养殖水体，传统光谱法对化学需氧量（Chemical Oxygen Demand，COD）检测模型构建的基础：源域（现有样本库）与目标域（检测地水体）间光谱数据独立同分布。但是当源域与目标域分布间存在差异时，由源域得到的低误差模型常在目标域上表现下滑。针对该问题，提出面向UV Vis光谱的域对抗训练网络（DAUVwpNet），将分布不同的源域和目标域数据映射至相同分布的特征空间中，使其在该空间的分布距离尽可能接近，从而在特征空间中对源域训练的目标函数也可以迁移至目标域上，以降低模型在目标域的误差。试验表明：面向同一批测试数据，DAUVwpNet的预测误差为0.78，要低于传统模型的预测误差（0.85）；DAUVwpNet预测值与实测值间相关系数为0.95，要高于传统模型的相关系数（0.89）。表明了该网络能够较好对齐两域特征空间数据分布，降低因分布差异带来的COD检测误差。     

草坪草屑的加工与利用

我国每年修剪草坪产生大量的草坪草屑,对草坪草屑的加工利用,可以对我国能源、饲料、肥料及蛋白资源的短缺起到一定的缓解作用,因此如何对草坪草屑进行合理利用已成为一项重要的研究课题。本文综述了草坪草屑能源化、饲料化、肥料化和深加工4种利用方式,详细介绍了草坪草屑在发酵生产能源、饲喂家畜、堆肥还坪以及加工叶蛋白等方面的研究进展,指出禾本科草坪草屑和豆科草坪草屑应采用不同的处理方式,对各加工方式的投入和产出也应进行进一步的量化核算,同时总结并展望了草坪草屑利用方式的发展前景。     

基于主成分和隶属函数分析的高粱品种耐深播性综合评价

采用盆栽试验,分别设置1、3、5、7 cm播深,对34个高粱品种在不同播深下的出苗率、幼苗形态和幼苗干物质量进行分析,筛选耐深播性鉴定指标,综合评价高粱品种的耐深播性。研究结果表明,随着播种深度的加大,出苗率、苗长、根长、根数和苗重均呈下降趋势,3、5、7 cm与1 cm播深上述指标测定值的比值分别为0.84～0.60、0.96～0.75、0.83～0.53、0.88～0.64和0.95～0.85;中胚轴长、根重和根冠比呈上升趋势,3、5、7 cm与1 cm播深上述指标测定值的比值为1.52～3.30、1.10～1.25和1.17～1.50;胚芽鞘长在播深间差异不显著。主成分分析结果表明,前4个主成分的累积方差贡献率为77.647%,相对根冠比、相对根长、相对中胚轴长和相对出苗率载荷量最大,将其作为高粱耐深播性筛选的主要指标并计算隶属函数值。根据隶属函数值对高粱品种进行聚类分析,结果显示,34个高粱品种可聚为3类,晋粱白2号等11个品种为耐深播品种,红青壳等14个品种为中等耐深播品种,吉品609等9个品种为深播敏感品种。品种间耐深播性差异明显,杂交种较常规种耐深播性强。     

基于大型渔业平台的深远海渔业发展现状与思考

基于渔业产业现状,分析国内外在大型渔业平台、深海网箱和养殖工船方面的发展现状,提出“游弋式”养殖工船及深远海渔业的基本概念。受限于投资成本、技术发展水平等客观因素,中国深远海养殖发展速度缓慢,但近年来取得了一定的发展成效。笔者针对现阶段渔业粗放型生产方式的现状,从国家战略、渔业改革和产业需求等角度分析深远海渔业发展的必要性,认为发展以养殖工船为代表的深远海大型渔业平台是实现渔业强国之路的有效途径之一,走出一条符合中国国情的深远海渔业平台的开发之路势在必行。     

基于非接触式的牛只身份识别研究进展与展望

快速精准确定牛个体身份对疾病防控、品种遗传改良、奶制品和肉制品质量溯源以及改善农业假保险索赔等方面具有重要意义。传统的牛个体识别使用诸如烙印、耳纹、耳标和无线射频识别等方法，易遭受设备损失/工作重复、标记欺诈、动物福利安全以及监测成本和距离等方面的挑战；而基于生物特征的非接触识别由于其独特性、不变性、低成本易操作以及动物福利高，成为牛身份识别的新趋势。主要介绍了几种基于非接触式的牛身份识别的研究进展，重点关注牛脸识别的最新成果，讨论当前牛脸识别在实际应用中面临的挑战，在此基础上对深度学习在牛脸身份识别研究中的应用进行了设计构思与展望。