Analysis of Influencing Factors of Pine Wood Nematode Disease in Lu an City Based on GIS

[Objectives]The paper was to figure out the distribution of Monochamus alternatus in the stumps of pine wood nematode infected wood in Lu'an City and to provide a theoretical and practical basis for differentiated prevention and control of pine wood nematode disease in the future.[Methods]The factors influencing the number of epidemic small classes and infected plants in all counties and districts of Lu'an City were analyzed by GIS method,and the number of worms and wormholes of M.alternatus inside and outside the stumps of pine wood nematode infected wood in Lu'an City were investigated on the spot.[Results]There were 98,40,54,781,193,268 and 34 epidemic small classes of pine wood nematode disease,and 7241,6099,9532,39161,11079,49876 and 4853 infected plants in Yu'an District,Jin'an District,Yeji District,Shucheng County,Huoshan County,Jinzhai County and Huoqiu County,respectively.Pine wood nematode disease in Lu'an City mostly occurred in Huoshan County,Shucheng County and Jinzhai County,with relatively high altitude,paddy soil,the annual precipitation higher than 2062 mm,and the annual average temperature lower than 16.2℃.The number of diseased plants of pine wood nematode disease was positively correlated with altitude and annual precipitation,and was negatively correlated with annual average temperature.The number of worms and wormholes in pine wood nematode infected wood was very small at different altitudes,stump heights and stump diameters.[Conclusions]The pine wood nematode infected wood can be differentially processed after stump treatment,and stumps can be peeled.The results will provide a theoretical and practical basis for differentiated prevention and control of pine wood nematode disease in the future.

Pine wilt disease: a short review of worldwide research

This article summarizes the results of the research papers presented at the International Symposium on pine wilt disease （IUFRO Working Party Meeting 4.04.03） held in July 2009, at Nanjing, China. The general topics covered were on pine wilt disease （PWD）, its causal organism, the pinewood nematode （PWN） Bursaphelenchus xylophilus, plus other PWN-associated microorganisms that play a significant role in PWD such as bacteria （e.g. Pseudomonasfluorescens）. Most of the papers that are reviewed are based on work on PWD-PWN in East Asia and Russia. Specific topics covered include： 1） the fundamental conceptions of PWD development, 2） pathogenicity, 3） host-parasite relationships including the histopathology of diseased conifers and the role of toxins from bacteria-nematode ecto-symbionts, 4） PWN life cycle and transmission, 5） B. xylophilus dissemination models, 6） associations （with other nematodes）, 7） diagnostics, 8） quarantine and control of the PWN and 9） biocontrol of the PWN.

Investigation of beetle species that carry the pine wood nematode,Bursaphelenchus xylophilus(Steiner and Buhrer)Nickle,in China

In order to found new carriers of pine wood nematode(PWN),Bursaphelenchus xylophilus,beetles were collected from pine wilt disease-affected areas in six provinces in China.A total of 8830 beetles of 29 species was collected and examined to determine whether they were PWN carriers.Eight species were identified as carriers.Results included the first worldwide report of Monochamus uigromaculatus,Semanotus siuoauster,and Uraecha angusta being carriers of PWN,and the first report from China of A rhopalus rusticus carrying PWN.Monochamus alternatus was commonly collected in all six provinces and was the dominant species in four inland affected areas and A.rusticus was dominant in two coastal affected areas.The species varied between different neighboring regions in the same province.The distribution of the same species varied considerably over different regions.

Theory and Practice of Controlling and Extinguishing Pine Wilt Disease

[Objective] This study was aimed to review the controlling experience of pine wilt disease in the past 25 years, explore the theories and methods of controlling pine wilt disease, and improve the scientific level of controlling techniques and the protection capacity of healthy pine trees. [Method] Eleven items of effects were used to refine the theory of clearing dead pine trees affected by pine wilt disease, namely, ＂1 priority＂, ＂2 objections＂, ＂3 principles＂, ＂4 measures＂, and ＂5 manage- ments＂. On the basis of comprehensive control and complete removal of the infect- ed pine trees, a variety of comprehensive and efficient controlling methods were developed to carry out targeted chemical ecology trapping, bionic pesticide killing and releasing natural enemies of Sclerodermus guani, Dastarcus helophoroides. High ef- ficient emamectin benzoate immune injection was developed to inject the healthy pine trees for prevention, so as to extinguish the pine wilt disease. [Result] The pine wilt disease dropped from the peak of 3.5 million dead trees with an infecting area of 28 273 hectares in 1999 to 0.068 million with an area of 4 333 hectares in 2012 gradually, reducing by 98.06% in number and 84.84% in area, respectively. On the basis of removal, Dastarcus helophoroides was also released, which could make the number of dead pines decrease more significantly than the control, and af- ter releasing for 5 consecutive years, the dead pine trees dropped to 0.511 plant/hm2 in 2012, with a mortality rate of 0.022 7%, which achieved the control effect, reaching extremely significant level. ＂Forest land removal＋infected trees isolation＋natural enemy release＂ could extinguish the pine wilt disease. The test of isolating 24 heaps of infected pine trees showed that there were 9 heaps of pine trees extinguished the pine wilt disease, which controlled the occurrence of pine wilt disease for 100%, accounting for 37.5% of the total, in which the number of those isolated using iron netting and nylon net were 4 for each, accounting for 88.9%, and there was one heap using polypropylene net, accounting for 11.1%. The invention of em- amectin benzoate immune injection laid the foundation for extinguishing pine wilt disease. The follow checking of the effects of emamectin benzoate immune injection on pine wilt disease found that the number of dead trees caused by pine wilt dis- ease decreased significantly after injecting, and became very small in October of the next year, and the disease was completely extinguished in the third year. [Conclusionl Pine wilt disease could be controlled and extinguished with positive control by using ＂comprehensive cleaning＋industrialized removal＂, ＂comprehensive cleaning＋ natural enemy release＂, ＂comprehensive cleaning＋infected trees isolation＋natural ene- my release＂ and ＂comprehensive cleaning＋emamectin benzoate immune＂.

A spatio-temporal multi-scale fusion algorithm for pine wood nematode disease tree detection

Pine wood nematode infection is a devastating disease.Unmanned aerial vehicle(UAV)remote sensing enables timely and precise monitoring.However,UAV aerial images are challenged by small target size and complex sur-face backgrounds which hinder their effectiveness in moni-toring.To address these challenges,based on the analysis and optimization of UAV remote sensing images,this study developed a spatio-temporal multi-scale fusion algorithm for disease detection.The multi-head,self-attention mechanism is incorporated to address the issue of excessive features generated by complex surface backgrounds in UAV images.This enables adaptive feature control to suppress redundant information and boost the model’s feature extraction capa-bilities.The SPD-Conv module was introduced to address the problem of loss of small target feature information dur-ing feature extraction,enhancing the preservation of key features.Additionally,the gather-and-distribute mechanism was implemented to augment the model’s multi-scale feature fusion capacity,preventing the loss of local details during fusion and enriching small target feature information.This study established a dataset of pine wood nematode disease in the Huangshan area using DJI(DJ-Innovations)UAVs.The results show that the accuracy of the proposed model with spatio-temporal multi-scale fusion reached 78.5%,6.6%higher than that of the benchmark model.Building upon the timeliness and flexibility of UAV remote sensing,the pro-posed model effectively addressed the challenges of detect-ing small and medium-size targets in complex backgrounds,thereby enhancing the detection efficiency for pine wood nematode disease.This facilitates early preemptive preser-vation of diseased trees,augments the overall monitoring proficiency of pine wood nematode diseases,and supplies technical aid for proficient monitoring.

2%甲维盐乳油对松材线虫病的防效测定

[目的]为测试2%甲维盐乳油(商品名:松高飞)对松材线虫病的防治效果。[方法]首先通过室内浸渍法比较了2%甲维盐乳油和2%甲维盐微乳剂(商品名:林源松韵)的杀线活性,然后在温室和林间通过树干注射测试了2%甲维盐乳油对松材线虫病的防治效果,最后通过高效液相色谱法测定了不同时间、不同松树体内甲维盐的含量变化。[结果]室内浸渍法结果显示,2%甲维盐乳油具有更强的杀线活性,LC_(50)为41.808 mg·L^(-1),显著低于2%甲维盐微乳剂的75.959 mg·L^(-1)(p<0.05)。温室预防组结果显示,2%甲维盐乳油的预防效果显著,2 a后松树无死亡。温室治疗组结果显示,2%甲维盐乳油治疗时间越早,治疗效果越好;2 a后,接种线虫后7 d注药治疗组,松树无死亡;而30 d后注药治疗组,白皮松、无死亡,油松死亡率为20%,华山松死亡率为40%。林间的试验显示2%甲维盐乳油在两块林地的防治效果显著,其试验组马尾松林2 a累计死亡率分别为2%和5%,远低于对照组马尾松死亡率20%和25%。随着时间变化,不同松树体内甲维盐变化有所差异,华山松体内平均甲维盐含量最高(36.59 mg·kg^(-1)),油松最低(27.11 mg·kg^(-1))。注射后15 d内,所有松树体内甲维盐含量均上升;15 d后,华山松树干中部甲维盐含量逐渐升高,60 d的含量最高;而油松、白皮松树干内甲维盐含量逐渐降低并趋平。[结论]2%甲维盐乳油对松材线虫具有显著的杀线活性,温室和林间防治效果显著,在不同松树体内传输和存留效果良好,无明显药害,可以进一步推广使用。

基于无人机高光谱的川南疫木林区早期监测研究

为探明马尾松感染松材线虫病早期地理位置及发病率。2021年7月上旬,利用无人机搭载高光谱成像仪采集遥感影像,选用支持向量机进行监督分类,在早期感病反演模型基础上,顺利提取了感病早期的马尾松地理位置及相关信息。结果表明:(1)利用460 nm、525 nm和635 nm的3波段组合真彩色影像进行ROI勾绘,马尾松与其他地被物分离度较高;(2)基于支持向量机的监督分类,顺利获取741株马尾松地理位置及高光谱反射率数据;(3)结合监测模型提取64株疑似感病马尾松,通过随机采样及镜检,马尾松聚类范围感病植株提取准确率86.67%,即马尾松林间发病率7.49%。综上,初步揭示川南地区马尾松林自然状态下松材线虫发病率,有利于今后指导松材线虫病早期精准防治。

Review of Pathogen Identification and Diagnosis Technology of Pinewood Nematode Disease

This article briefly introduced the disease incidence and disservice situation in China. The disease is regarded as cancer in pines for its higher spread and death speed and the difficulty in prevention. Strict quarantine is the main measure on countrol of the disease, for there are many difficulties in the prevention. The most important part of the disease study is the early diagnosis and detection.

松材线虫病防治措施分析

本文从清理病死松树、媒介昆虫药物防治、健康松树打孔注药和林分改造4个方面对松材线虫病防治措施进行了分析。从保护松木资源、形成综合防治体系和积累防控工作经验3个方面对其防治效果进行了评价。提出从优化防治措施、强化检疫管理、完善防治方式、加强精准监测和促进联防联治等方面强化松材线虫病防治策略。目的在于为松材线虫病防治工作提供参考。

抗松材线虫病马尾松种源的抗性相关基因分析

为了从转录组水平探讨抗病马尾松种源对松材线虫的响应机制。以抗病马尾松GD5种源为试验材料,普通马尾松SX1种源为对照,利用RNA-seq技术通过Illumina高通量测序平台对松材线虫诱导前后的试验材料进行转录组测序和差异基因表达分析。试验共获得65889条unigenes,平均长度为906.85 bp,其中40478条(61.43%)unigenes基于Nr、GO、COG、KEGG等多个公共数据库获得了功能注释。抗病马尾松GD5种源在接种松材线虫后差异表达基因数量为3247条,包括2308条基因表达显著上调,939条基因表达显著下调。其中有1961条(60.39%)差异表达基因被注释到GO数据库中,有504条(15.52%)差异表达基因被注释到233条pathway。普通马尾松SX1种源在松材线虫诱导过程中产生了更多的差异表达基因。两个马尾松种源富集的GO条目和pathway差异也较大。抗病马尾松GD5种源体内编码醛脱氢酶的5条基因和编码超氧化物歧化酶、过氧化物酶体原蛋白以及细胞色素b2的基因表达均显著上调,醛脱氢酶基因不仅富集于抗坏血酸和醛酸代谢途径中,还参与β-丙氨酸、赖氨酸、色氨酸、缬氨酸、亮氨酸、异亮氨酸、组氨酸、精氨酸和脯氨酸等氨基酸的代谢途径;参与氨基糖和核苷酸糖代谢途径的6条几丁质酶基因表达均显著上调;参与单萜生物合成的短链脱氢酶/还原酶2b及参与倍半萜和三萜生物合成的长叶烯合酶基因表达均显著上调,而参与二萜类生物合成的1(10),5-格玛吖啶-4-醇合酶、萜烯合酶、α-松油醇合酶、异丙二烯合酶以及2-甲基-3-丁烯-2-醇合酶等表达均显著下调。抗病马尾松GD5种源对松材线虫的胁迫响应是多基因和多信号途径共同参与调控的复杂防御反应,是全局性系统性的响应模式。与抗性相关的醛脱氢酶、几丁质酶等编码基因为后期相关抗性基因的研究提供了参考。

基于无人机高光谱技术的松材线虫病监测技术研究

本文基于无人机高光谱技术,对松材线虫病的高效、准确监测进行了研究。以山东省威海市河东村为试验区域进行了高光谱数据采集,分析了松树不同染病时期的光谱曲线,并基于此提取了松材线虫病疑似树木。通过对提取结果进行实地检核,发现利用高光谱技术进行松材线虫病疫木提取的精度可达90%,说明利用无人机高光谱技术进行松材线虫病监测是可行的。

基于多色彩空间的YOLOv5松枯死树检测方法

【目的】针对在松枯死树监测实践中,从无人机航拍RGB影像中自动识别松枯死树漏检率高的问题,提出了一种生产应用场景下基于多色彩空间的YOLOv5松枯死树高精度自动识别新方法。【方法】利用无人机采集大面积松材线虫病发生林分的RGB图像,用Pix4Dmapper软件拼接,用LabelImg开源软件建立VOC格式的松枯死树数据集,分别用Faster R-CNN、YOLOv3、YOLOv4、YOLOv5、SSD和EfficientDet等6种基于深度学习的目标检测算法对数据集进行训练和测试,以精确率、召回率、平均准确率以及F 1分数作为评价指标筛选出最优目标检测算法;然后将采集的RGB图像转换成LAB和HSV色彩空间图像,再将这3个色彩空间的图像分别用最优目标检测算法进行训练,得到目标在每个色彩空间的边界框,使用非极大值抑制算法对这些边界框进行处理,得到最优边界框实现松枯死树自动识别。【结果】6种算法均取得良好效果,其中YOLOv5模型为最优算法,其精准率、平均查准率和F 1分数在6种算法中均最高,分别达到97.58%、82.40%和0.85。通过3个色彩空间融合后,反映漏检情况的召回率由74.54%提高到98.99%,平均准确率提升至98.39%。【结论】基于多色彩空间的YOLOv5模型能够显著提高从无人机航拍RGB影像中检测松枯死树的精度,为松枯死树监测提供了有力工具,也有助于松材线虫病的防治。

基于多光谱卫星影像与机器学习算法的松材线虫病受害林分识别研究

松材线虫病(Pine Wilt Disease,PWD)被称为“松树癌症”,具有高传染率和高死亡率,对我国森林资源构成了严重的威胁,对我国的经济、社会和生态造成了重大损失。及时发现并清理疫木是遏制松材线虫病蔓延的有效手段,精准监测疫木是防控松材线虫病的前提,但是现阶段缺少大面积识别松材线虫病疫木的技术方法。本文旨在探索哨兵-2号与Landsat-8遥感卫星影像对受害松林的识别能力,采用随机森林(Random Forest,RF)、支持向量机(Support Vector Machine,SVM)、决策树(Decision Tree,DT)和极端梯度提升(Extreme Gradient Boosting,XGBoost)等4种机器学习算法建立了松材线虫病监测模型。结果表明:基于哨兵-2号影像数据建立的监测模型对受害松林的识别准确率高于Landsat-8遥感卫星影像,其中基于10 m分辨率的影像数据建立的监测模型识别准确率最高,随机森林、决策树、支持向量机和极端梯度提升等算法建立模型的准确率分别达到了79.3%、76.2%、78.7%和78.9%。在3种不同的影像数据集中,RF、SVM和XGBoost的准确率、Kappa系数和ROC值接近,均明显优于决策树算法。光谱特征中的绿波段、红波段、短波近红外波段和长波近红外以及植被指数中的NBRI、NGRDI、TVI、NDVI和PSSR等对松材线虫病监测模型的贡献值最高。递归消除法对特征参数的筛选效果最好,特征数量由原来50个减少至35个。本研究建立的松材线虫病受害林分监测模型为科学防控松材线虫病提供了技术支撑。

生物质疫木热处理炉热处理过程仿真模型的构建

以自制的生物质疫木热处理炉(SLYF-21)为疫木热处理设备(疫木采伐粉碎剩余物为燃料)、以疫木为试验材料,借鉴控制方程、湍流模型、混合(Mixture)模型、离散坐标(DO)辐射模型,构建疫木处理炉内多物理场耦合的热处理过程仿真模型,模拟遴选适宜的疫木热处理工艺参数。2022年7月14日,在山东省威海市荣成市,应用生物质疫木热处理炉对黑松(Pinus thunbergii)疫木进行热处理试验(热处理7 h),测定不同热处理时间时的各监测点温度,并与模拟结果进行对比,检验模型可靠性。采用试验与数值模拟相结合的方法,分析疫木直径、含水率、热处理环境温度对热处理时间的影响,遴选适宜的疫木热处理工艺参数。结果表明:炉内不同位置,疫木与环境的传热强度差异明显;木堆下部疫木温度高于上部、木堆内部疫木温度低于外围,木堆中心位置是传热的不利位置,应作为疫木中心温度监测的重点区域。疫木直径增加、环境温度降低、含水率增大,均会导致疫木热处理所需热量的增加和所需时间的延长,而且环境温度对热处理时间的影响最为显著;寒地环境时,可通过调整风机频率、增加炉体保温材料等措施提高炉体内升温速度,弥补低温环境对热处理时间的影响。结合试验结果,推荐6种典型工况下彻底杀灭疫木中松材线虫及媒介昆虫所需的热处理时间。

松材线虫病防控策略研究

松材线虫病严重危害松树健康,已成为全球性的森林生态问题,该病害的发生和扩散不仅直接危害松树的生长和生命力,而且对森林生态环境造成了不可逆转的影响。为了保护森林资源,推进可持续森林管理,该文对松材线虫病及其防治思路加以阐述,并提出相应的防控措施,以有效预防和控制松材线虫病的发生和扩散。

基于无人机多光谱遥感技术监测松材线虫病的实验研究

松材线虫病是目前对我国各省区松树林区危害最大的病害类型之一,被称为松林的癌症,一旦发生病害,如不及时治理,将对林业生态安全造成巨大的威胁。对染病和病死树木的准确监测和定位是开展治理工作的首要环节,但目前尚未有成熟高效的监测方法。为此,本文探讨基于无人机多光谱遥感手段,研究适用于山地松林松材线虫病染病树木和病死树木的监测方法。以青岛城阳区毛公山松林为研究区,利用无人机载多光谱遥感影像数据,通过图像处理、分类识别和定位等方法,开展了染病、病死松树的高精度监测。结果表明无人机遥感是开展松材线虫病监测的有效手段,多光谱遥感数据可实现对病害和病死树木的识别提取,无人机多光谱遥感监测方法可为松材线虫病的早期治理和治理后效评估提供方法支撑。

林业常见病虫害松材线虫病的防治技术解析

松材线虫病有较多的传染途径,且扩散速度极快,会在一定程度上致使松树规模不断缩小,严重影响松林的可持续发展和生产,同时还会对当地生态系统造成严重破坏。因此,为了更好地保护松林和生态系统,围绕松材线虫病的传播方式和发生特征,对其致病机理进行科学探讨,积极探索松材线虫病害的防治策略,以供参考。

无人机高光谱影像分层分类的松材线虫病监测

松材线虫病在秦岭以南传播广、蔓延快,利用遥感技术提取病害松可为疫情防控提供数据支撑。以无人机获取的高分辨率、高光谱数据为基础,捕捉区分病害松与健康松的特征波段,提出一种结合植被指数与小波神经网络的林地分层分类新方法,用于提取病害松树冠图斑。病害松识别结果与实地核查数据对比表明,分层分类结果与实地核查情况基本一致,病害松识别总精度达到89.87%,优于单一使用支持向量机、小波神经网络的分类结果。林地分层分类新方法与传统分类方法相比,分类精度更高,所需的样本更少。无人机高光谱数据信息丰富,病害松、健康松在可见光、近红外范围内均有光谱敏感特征,后续应进行病害松时序光谱监测,进一步研究松材线虫病害影响因子。

基于改进RetinaNet算法和无人机影像的松材线虫病疫木检测

松材线虫病是一种传播速度快的毁灭性森林病害,及时识别、处置染病变色疫木是控制该病扩散蔓延的主要手段。该文研究了利用RetinaNet算法自动识别无人机遥感影像上的松材线虫病变色疫木,并将注意力机制引入到主干特征提取网络以减少背景对检测效果的影响,提高特征提取能力。结果表明,改进后的RetinaNet算法平均精度为97.2%,单张影像测试时间为17 ms,表现优于Fasterr R-CNN、SSD和RetinaNet。基于研究成果,对崂山区林地进行疫木航拍图像检测,实地抽检准确率达到98%。

松材线虫病病原线虫鉴定研究进展

松材线虫病是一种林业危害性流行病,传播迅速、危害巨大,对中国在内的多个国家造成了严重的生态和经济损失。松材线虫和拟松材线虫作为中国松材线虫病的病原线虫,依靠媒介昆虫在松科植物传播,目前其防治仍存在困难。鉴别该病的病原线虫松材线虫与拟松材线虫一直是研究的热点,目前主流的鉴定方法分为形态检测、生化检测与分子检测3大方向。绝大多数传统的松材线虫检测技术存在一些局限性,如特异性较差、灵敏度不高、基层推广难度较大等;而基于核酸的分子检测技术以其简单,快捷,灵敏,可靠的优点逐渐成为检测研究的主流方向。从形态、生化分子、核酸检测3方面综述了3类松材线虫鉴定方法,并比较了各鉴定方法的优缺点,旨在为探索新的松材线虫病的鉴定方法提供理论依据,为研究松材线虫病提供新的方向。