基于卷积神经网络的拖拉机工况识别

农机工况识别在细化农机作业状态和帮助掌握区域污染物排放趋势方面有着重要的研究价值。基于拖拉机不同运行状态下的行驶速度、发动机转速以及实时油耗等时间序列,首次提出将图像识别方法引入到拖拉机工况识别中的思路,并分别应用参数优化的支持向量机与卷积神经网络对实际作业拖拉机工况进行研究。结果表明:(1)基于参数优化的支持向量机可以较好地实现样本点的工况识别且识别准确度达到99.851 9%,但无法实现农机工况的连续性识别,同时无法对农机工况转换阶段进行有效识别。(2)以拖拉机运行速度与发动机转速等信息构建样本图像来描述农机工况变化的数据表达,并在此基础上应用卷积神经网络可以有效实现农机工况的连续性识别,且识别准确率可以达到93.3%。本研究在农机工况识别方面具有一定参考价值,并为后续农机不同工况下区域污染物排放研究提供技术支持。     

基于GF-1和Sentinel-2时序数据的茶园识别

由于茶园大多分布在地形复杂的山区,地块破碎,分布零散,形状差异大、植被混杂且茶园所处环境长期受到云雨的影响,增加了茶园遥感识别的难度与不确定性,针对这一问题,该研究提出了利用高分1号(GF-1)和哨兵2号(Sentinel-2)时序数据提取茶园的方法,以浙江省武义县王宅镇为研究区,采用GF-1号为主要数据源,并利用MODIS地表反射率产品和Sentinel-2反射率数据,基于时空融合算法得到时间分辨率5 d的10 m Sentinel-2完整的时序数据。综合利用GF-1在空间细节方面的优势和重建的Sentinel-2高观测频率时序数据在反映茶树生长过程方面的优势,分别基于GF-1的光谱和纹理特征及GF-1的光谱、纹理特征和Sentinel-2时序特征两种特征组合方式,采用随机森林算法提取茶园。结果表明,GF-1光谱、纹理信息结合Sentinel-2时序信息分类结果的准确率、错误率、精确率、召回率和F1分数分别为96.91%、3.09%、89.00%、83.09%和0.86,仅基于GF-1光谱和纹理信息的分类准确率、错误率、精确率、召回率和F1分数分别为94.72%、5.28%、73.09%、84.61%和0.78,添加时序信息分类结果总体优于未添加时序信息的分类结果。表明高空间分辨率结合高频率时序遥感数据是提高茶园分类精度的有效手段。     

辣椒细菌性果实条斑病菌生物学特性及抑菌药剂筛选

研究辣椒细菌性果实条斑病菌的生物学特性,对病原菌进行室内药剂筛选,旨在为田间病害规律研究和病害防治提供依据。采用紫外分光光度计测定病原菌在不同温度、pH、NaCl浓度下的生长速率。采用滤纸片抑菌圈法对病原菌进行室内药剂筛选试验。结果表明,辣椒细菌性果实条斑病菌最适生长温度为28℃,最适pH 7.0,病原菌的耐盐性为12%。18种供试药剂在药剂推荐使用剂量范围内,四霉素、乙蒜素、77%志信、氯溴异氰尿酸4种药剂对病原菌有抑菌效果,对这4种药剂进行毒力测定,结果表明四霉素的毒力较强,EC₅₀值为11.75 mg/L,毒力强于其他3种试剂,四霉素可作为田间防治药剂的首选。     

基于高通量测序及分离培养初步研究美国大豆中真菌多样性

中国是全球最大的大豆进口国,进境大豆所携带的病原真菌传入我国的风险极高。基于高通量测序技术对6批美国大豆真菌多样性进行分析,同时采用分离培养获得单一菌株,依据菌落形态、显微结构及分子技术进行鉴定。高通量测序结果显示,大豆中所有真菌共计5门15纲35目63科112属155种,主要为链格孢属(Alternaria)、球腔菌科(Mycosphaerellaceae)、小戴卫霉科(Davidiellaceae)、小囊菌科(Plectosphaerellaceae)、赤霉属(Gibberella)、附球霉属(Epicoccum)、间座壳属(Diaporthe)、隐球菌属(Cryptococcus)。分离培养结果显示,得到真菌共计40株10种,分别是大豆北方茎溃疡病菌(Diaporthe phaseolorum var.caulivora)、大豆南方茎溃疡病菌(Diaporthe phaseolorum var.meridionalis)、大豆拟茎点种腐病菌(Diaporthe longicolla/Phomopsis longicolla)、大豆炭腐病菌(Macrophomina phaseolina)、尖孢镰刀菌(Fusarium oxysporum)、菌核菌(Sclerotinia sclerotiorum)、镰刀菌(Fusarium sp.)、附球菌(Epicoccum sp.)、交链孢菌(Alternaria sp.)、小双胞腔菌(Didymella sp.)。     

菊花绿变病植原体在中国的发生及分子鉴定

对内蒙古农业大学校园内表现花器绿变症状的菊花样品进行采集和DNA提取,应用植原体16S rRNA基因和rp基因的引物进行巢式PCR扩增,从感病样品中分别扩增得到了长度均约为1.2 kb的片段。序列一致性分析表明,菊花绿变植原体16S rRNA基因与翠菊黄化植原体匈牙利风信子株系(GenBank登录号MN080271)、印度玉米株系(KY565571)、印度繁缕株系(KC623537)和印度马铃薯株系(KC312703)的核酸一致性最高,为99.9%,rp基因序列与翠菊黄化植原体立陶宛洋葱株系(GU228514)的核酸一致性最高,为99.8%。基于16S rRNA基因和rp基因构建系统进化树时发现,菊花绿变植原体均与16SrI-B亚组成员聚为一起。16S rRNA基因相似性系数分析表明,菊花绿变植原体与洋葱黄化植原体(AP006628)的相似性系数最高为1.00,洋葱黄化植原体(AP006628)在分类上属于16SrI-B亚组。因此,我们可以确定该菊花绿变植原体属于16SrI-B亚组。这是我国首次报道菊花绿变病的发生。     

拟康宁木霉Tk1的分离鉴定、拮抗作用及其生物学特性

为了分离利用高效植物病害生物防治菌株，从广东药用植物金丝皇菊根部分离获得一株木霉菌株Tk1。经过形态观察、rDNA-ITS和EF-1α序列分析明确其为拟康宁木霉Trichoderma koningiopsis。用平板对峙培养法测定，该菌株对金丝皇菊枯萎病菌（尖孢镰刀菌Fusarium oxysporum）和柑橘炭疽病菌（胶胞炭疽菌Colletotrichum gloeosporioides）的抑制率分别为68.5%和77.1%，且在后期能完全覆盖或部分覆盖病原真菌。其无菌发酵液对金丝皇菊枯萎病菌的抑制率为45.55%。该菌株营养生长和产孢的最适碳源分别为乳糖和葡萄糖，最适氮源是酵母膏；在pH 4~11的培养基上均可生长、产孢，最适pH为7；12 h交替光照条件下菌丝的生长速度最快，全光照条件下产孢数量最大；该菌株的致死温度为73℃处理10 min。     

油茶内生拮抗细菌的筛选、鉴定及防效

为筛选出对油茶炭疽菌有拮抗效果的生防菌株，以油茶健康叶为对象，平板对峙法筛选，利用形态和生理生化特征以及16S rDNA基因和gyrA基因序列对菌株进行鉴定，测定其抑菌活性，并将该菌株与枯草芽胞杆菌Y13复配进行林间防效试验。结果表明，对油茶炭疽病菌拮抗作用效果较强的内生菌株为HBMC—B05；菌落为乳白色，不透明，边缘不整齐，中间有凸起；分子鉴定结果显示菌株HBMC—B05为贝莱斯芽胞杆菌Bacillus velezensis，其对果生炭疽菌Collectotrichum fructicola，抑菌率可达到81.31%，对另外3种油茶炭疽病病原菌抑菌率可达到70%以上，对其他4种致病菌也有抑制作用；复合菌剂对油茶病害的田间防治效果达到59%以上。该菌株的抑菌具有广谱性，可为油茶病害的生物防治扩充菌种资源，具有广泛的应用前景。     

马尾松叶表微生物多样性

为发掘对林木生长发育有利的优良微生物资源,并筛选适合叶表微生物的收集方法,以马尾松针叶为试验材料,分别用悬摇法和超声波法收集马尾松叶表微生物,用扩增子高通量测序技术、MUSCLE和Qiime软件研究马尾松叶表微生物的多样性。结果表明:扫描电镜观测结果显示,马尾松针叶表面定殖有大量微生物,包括真菌(菌丝及孢子)和细菌。扩增子高通量测序结果表明,马尾松叶表微生物物种丰富,包含细菌运算分类单位(OTUs)490个,真菌OTUs 1273个。马尾松叶表细菌以未分类的蓝细菌属(unidentified_Cyanobacteria)(36.53%)、未分类的拜叶林克氏菌属(unidentified_Beijerinckia)(28.60%)、鞘氨醇单胞菌属(Sphingomonas)(2.35%)为优势属;叶表真菌以枝孢属(Cladosporium)(2.45%)、拟盘多毛孢属(Pestalotiopsis)(0.92%)、无头孢菌属(Capnobotryella)(0.91%)为优势属。针对叶表细菌多样性的研究表明,悬摇法和超声波法均有较高的物种检出度;在叶表真菌多样性的研究中超声波法优于悬摇法,但超声波法样品间数据变异性较大,测定结果不稳定。     

The first survey and molecular identification of Entamoeba spp. in farm animals on Qinghai-Tibetan Plateau of China

Protozoans of Entamoeba spp. are globally distributed zoonotic parasites that infect diverse animal hosts and humans. Prevalence and species/genotypes distribution of Entamoeba spp. in domestic animals are not fully investigated on Qinghai-Tibetan Plateau (QTP), an animal husbandry and agriculture region of China. In a survey, 528 fecal samples were collected from 7 species of domestic animals on multiple locations across QTP region and analyzed by PCR and sequencing analysis. The overall prevalence of Entamoeba spp. infection in all examined animals was 97.9 %. Four Entamoeba species, E. bovis, E. moshkovskii, E. ecuadoriensis and E. histolytica were found, and majority (94.2 %) of Entamoeba-infected animals harbored E. bovis. Six Entamoeba genotypes, Entamoeba ribosomal lineages (RL) 1, 2, 3, 4, 8 and 9 were identified by sequencing analysis. Two zoonotic species, E. moshkovskii and E. histolytica, were present in horses, while E. ecuadoriensis and E. bovis were found in horses and all species of seven farm animals, respectively. It was also observed that six Entamoeba genotypes were distributed in animals in specific pattern. The results revealed high prevalence of Entamoeba spp. infection in livestock, broad range of hosts as well as diversity and species/genotype distribution of Entamoeba spp. in farm animals inhabiting on the high altitude QTP region.     

Improvement,identification, and target prediction for miRNAs in the porcine genome by using massive,public high-throughput sequencing data

Despite the broad variety of available microRNA (miRNA) research tools and methods, their application to the identification, annotation, and target prediction of miRNAs in nonmodel organisms is still limited. In this study, we collected nearly all public sRNA-seq data to improve the annotation for known miRNAs and identify novel miRNAs that have not been annotated in pigs (Sus scrofa). We newly annotated 210 mature sequences in known miRNAs and found that 43 of the known miRNA precursors were problematic due to redundant/missing annotations or incorrect sequences. We also predicted 811 novel miRNAs with high confidence, which was twice the current number of known miRNAs for pigs in miRBase. In addition, we proposed a correlation-based strategy to predict target genes for miRNAs by using a large amount of sRNA-seq and RNA-seq data. We found that the correlation-based strategy provided additional evidence of expression compared with traditional target prediction methods. The correlation-based strategy also identified the regulatory pairs that were controlled by nonbinding sites with a particular pattern, which provided abundant complementarity for studying the mechanism of miRNAs that regulate gene expression. In summary, our study improved the annotation of known miRNAs, identified a large number of novel miRNAs, and predicted target genes for all pig miRNAs by using massive public data. This large data-based strategy is also applicable for other nonmodel organisms with incomplete annotation information.