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。     

典型草原枯落物分解过程中官能团的动态特征

选择锡林浩特东部国家气候观象台的生态监测研究样地,对大针茅(Stipa grandis)、羊草(Leymus chinensis)、糙隐子草(Cleistogenes squarrosa)、知母(Anemarrhena asphodeloides)枯落物的化学结构特征进行阐释。结果表明:(1)枯落物分解速率呈先增大后减小的变化趋势,且知母枯落物分解速率高于大针茅、羊草和糙隐子草;枯落物总碳(TC)含量为富集-释放模式,在第120d时,知母枯落物TC含量高于其他3种植物。(2)大针茅、羊草、知母、糙隐子草枯落物所含的主要官能团为-OH;=C-H、-CH 2、-CH 3;C=O;C=O、C=C;C-O。(3)不同植物枯落物官能团含量在分解初期迅速减少,在分解后期减少趋势较为缓慢,与分解过程中枯落物的分解速率变化趋势一致;知母的含碳官能团含量在分解结束后最低,而羊草的则最大,且知母和糙隐子草损失量最大,与分解过程中枯落物TC含量的特征一致。(4)大针茅的支链化指数最大,羊草的最小;糙隐子草的芳香性指数最大,知母的最小。不同植物芳香性指数在分解初期迅速减少,在分解后期减少趋势较为缓慢,与分解速率变化趋势一致。     

马铃薯组培苗时期不同LED光源处理对温室移栽后植株生长和微型薯结薯的影响

不同LED光源下培养的马铃薯组培苗在形态特征上差异明显,为探索这种差异是否会对其移栽后产生进一步影响,试验研究了100%红光(R)、100%蓝光(B)、100%绿光(G)、75%红光+25%蓝光(RB)、45%红光+35%蓝光+20%绿光(RBG)和100%白光(CK)6种光谱下培养4周的马铃薯组培苗温室移栽后植株的生长和结薯情况。试验结果表明,B处理的马铃薯组培苗移栽后缓苗期叶绿素荧光参数Fv/Fm和qP、结薯前期SPAD值及结薯期各器官生物量均始终高于CK和其他处理,且该处理下最大薯的干鲜重和有效微型薯占比分别较CK提高45.66%、45.09%和10.93%。R处理的组培苗移栽后结薯期地上部生物量显著高于CK,单株结薯数目提高29.60%,但有效微型薯占比较CK降低63.97%。G处理的组培苗移栽后生长和结薯指标均表现最差。组合光谱RB和RBG处理的组培苗移栽后的生长指标和微型薯产量及产量构成指标均与CK无显著差异。因此,单色红、蓝、绿光谱处理对马铃薯组培苗的影响会持续至其移栽后植株幼苗生长,甚至结薯期,组合光谱RB和RBG则不会。在马铃薯组培苗生产上,单色蓝光和单色红光作为照明光源具有潜在的应用价值,组合光谱RB和RBG可作为白色光源的替代光源。     

The use of infrared spectroscopy and machine learning tools for detection of Meloidogyne infestations

Plant parasitic nematodes are generally soilborne pathogens that attack plants and cause economic losses in many crops. The infested plants show nonspecific symptoms or, often, are symptomless; therefore, diagnosis is performed by taking soil and root tissue samples. Here, we show that a combination of different infrared spectra analysis and machine learning algorithms can be used to detect plant parasitic nematode infestations before symptoms become visible, using leaves instead of roots and soil as samples. We found that tomato and guava plants infested with Meloidogyne enterorlobii produced different spectral patterns compared to uninfested plants. Using partial spectra from 1,450 to 900/cm as the "fingerprint region", principal component analyses indicated that after 5 (tomatoes) or 8 weeks (guava), plants with no visible symptoms of infestations were positively diagnosed. To improve the early detection response, we used machine learning modelling. A support vector machine (SVM) was used to obtain more robust, accurate models. The SVM model contained 34 support vectors, 17 for each level. The overall performance of the model was >97% and the total accuracy was significantly higher, demonstrating the absence of chance prediction. The best prediction of infestation was obtained at the second and fourth weeks for tomatoes and guavas, respectively, reducing the diagnostic time by half. The combined application of these techniques reduces the processing time from field to laboratory and shows enormous advantages by avoiding root and soil sampling.     

副车架疲劳载荷分析方法

结合LMSTWR软件,详细介绍了基于混合路面的轮心位移反求法求取副车架载荷谱的方法。通过在某MPV上布置合适传感器,在试验场测得道路载荷谱信号。根据实测的数据,建立整车多体动力学模型。基于处理后的道路载荷谱与多体动力学模型进行虚拟迭代,并进行副车架载荷分解。结果表明,迭代仿真得到的信号与试验值吻合度较好。     

Using vibrational molecular spectroscopy to detect moist heating induced carbohydrates structure changes in cool-climate adapted barley grain

There is limited research to study how moist heating affects internal structure of barley grain on a molecular basis. The objectives of this study were to use vibrational molecular spectroscopy: 1) to determine the moist heating induced changes of barley carbohydrate (CHO) structure on a molecular basis, 2) to study the effects of moist heating on CHO chemical profiles, Cornell Net Carbohydrate and Protein System (CNCPS) subfractions, in situ rumen degradation, and predicted intestinal carbohydrate supply of barley grain; and 3) to reveal the association between molecular structure spectral features and CHO related metabolic characteristics. Barley samples (CDC cowboy) were collected from Kernen Crop Research Farm (Saskatoon, Canada) during two consecutive years. Half of each sample was kept as raw barley and the other half underwent moist heating (autoclaving at 120 °C for 60 min). The molecular spectroscopy (attenuated total reflectance-fourier transform infrared, ATR-FTIR) was used to detect the barley CHO related molecular structure spectral features. Moist heating did not affect carbohydrate related chemical profiles and CNCPS subfractions but it decreased rumen degradable carbohydrate. Rumen undegradable and intestinal digestion of CHO subfractions were not affected by moist heating. The advanced vibrational molecular spectroscopy can be used to detect carbohydrate molecular spectral features. Nutrient utilization prediction using molecular spectral characteristics is warranted and further investigation is encouraged.     

水稻抗性基因Pi对福建省稻瘟病菌优势菌群的抗性分析

【目的】抗病品种的合理利用和布局是实现水稻抗瘟持久化的关键因子之一。为明确水稻24个抗性基因在福建省的抗病性及其应用前景,【方法】首先分别采用全国稻瘟病菌生理小种鉴别品种和CO39近等基因系来鉴定2012-2015年间从福建省各稻区种植的普感品种丽江新团黑谷上采集的347株稻瘟病菌单孢菌株的生理小种类型和致病型,再测定24个抗性基因对福建省稻瘟病菌的抗性。【结果】根据全国稻瘟病菌生理小种鉴别品种对菌株的抗感反应,可将供试稻瘟病菌的生理小种划分为6个群36个生理小种,其中ZA、ZB和ZC为主要种群,ZC15、ZD7和ZB15为优势生理小种。根据CO39近等基因系的接种结果,将供试稻瘟病菌划分为17个致病类型,其中I34.1为优势致病型。供试的24个抗性基因对347株福建省稻瘟病菌菌株的抗性频率不同,抗谱为9.80%~89.91%。其中,Pi-k~m、Pi-7(t)、Pi-9(t)、Pi-k~p、Pi-k、Pi-k~h、Pi-z~5和Pi-ta(1)等8个抗性基因的抗病性较强,抗谱均高于70.00%。【结论】说明这8个抗性基因在福建省具有较好的应用前景,育种时可以考虑联合利用这些抗性基因。同时,实验结果表明,这8个抗性基因对主要生理小种的抗谱和主要致病型的抗谱均值高于69.00%,与其对所有测试菌株的抗谱吻合。说明利用稻瘟病菌的优势种群或优势致病型来鉴定水稻品种的抗病性是可靠的。     

基于道路载荷特征的整车试验场耐久性评价方法

为了获得整车试验场各路况对底盘各零部件的对应考核情况,以国内某整车大型试验场为研究对象,通过将采集到的试验场载荷分解,获得试验场各子路况的载荷时间历程。通过分别以底盘零部件各测点为基准和以试验场各路况为基准对比分析各路况对应各测点的损伤,可得到试验场路况考核表。针对考核表中不同路况考核部件的相似性,对比分析其各路况考核各部件的极值、变程、RMS、损伤,根据分析结果优化此前得到的试验场各路况考核表。此方法可为整车试验场耐久性评价提供一定参考。     

高温干旱复合胁迫对花生幼苗生理指标的影响

为探讨高温和干旱复合胁迫下的花生幼苗对逆境的响应机制，以抗逆性存在差异的花生品种豫花9719和豫花9326为试验材料，对其幼苗进行昼夜温度为45℃/25℃、土壤含水量为35%~40%左右的高温和干旱复合胁迫处理，研究复合胁迫对花生幼苗生长及生理特性的影响。结果表明：胁迫条件下，豫花9719的株高和干重分别比对照组低44.3%和30.2%，差异达极显著水平；含水量、叶绿素a、叶绿素b、类胡萝卜素、花青素的含量均低于对照，其中叶绿素a的含量低4.88%，差异达显著水平，花青素含量低18.14%，差异达极显著水平；PRI、PI、Gs、Pn值分别比其对照组低12%、50.31%、75.2%、72.3%，差异均达极显著水平；MDA含量和相对电导率分别比对照组高93.1%和29.93%，差异均达显著水平；可溶性蛋白和类黄酮含量分别比对照组高104.5%和41.00%，差异均达显著水平；SOD和CAT活性分别比对照组低0.91%和3.29%，差异不显著。豫花9326的株高比其对照组低33.6%，差异达极显著水平，干重降幅不显著；含水量、类胡萝卜素、花青素的含量均比对照组低，但差异均不显著；叶绿素a和叶绿素b的含量分别比对照组高19.44%和3.39%，其中叶绿素a差异达极显著水平； PRI、PI、Gs、Pn值均比对照低，差异均不显著；MDA含量和相对电导率均比对照组高，但差异均不显著；可溶性蛋白和类黄酮含量分别比对照组高271.33%和48.96%，差异均达极显著水平；SOD和CAT活性分别比对照组高70.11%和68.8%，增幅均达显著水平。推测豫花9326对高温和干旱复合胁迫的抗性较高，主要与其较为强大的抗氧化防御系统及光合系统有关。