银杏落叶期叶片NDVI值2种拟合方法比较

【目的】对银杏Ginkgo biloba L.落叶期(9—12月)的叶片进行连续定期定点的高光谱测量,计算出能代表其生长状况和营养信息的高光谱参量NDVI值,通过选用两种不同的曲线拟合方法对其NDVI值进行宏观上的以时间为自变量的曲线拟合,选出最优拟合方法,更好地了解银杏落叶期叶片光谱特征参量NDVI值的变化趋势,从而更有效地对其进行决策和控制,为植被的大尺度遥感动态监测提供方法参考。【方法】利用SVC HR-1024I全波段地物光谱仪,选取三株健康、生长环境相同、长势相近的中龄银杏为叶片采集对象,对其落叶期冠层叶片进行定期定点定方位的高光谱观测。对获取的高光谱原始数据进行数据筛选与预处理后,通过计算得出叶片的NDVI值,分别采用二次函数拟合法和ARIMA时间序列拟合法对落叶期叶片的NDVI值进行曲线拟合,并对两种拟合方法的拟合结果进行比较,选出最适合银杏叶片落叶期NDVI值的拟合方法。【结果】二次函数拟合结果为NDVI=-0.0221T2+0.0547T+0.711,决定系数R2为0.926,但因拟合结果t值不显著,样本结果随机性大,不具广泛性;ARIMA时间序列拟合中ARIMA(2,1,2)模型估测结果与实际情况接近,R2为0.811,拟合效果较好。【结论】ARIMA时间序列拟合方法比二次行数拟合方法更适用于对银杏落叶期叶片的NDVI值进行拟合。     

基于角度指数的油菜叶片等效水厚度估算研究

叶片等效水厚度(EWT)是评估油菜生长状态的一个重要参数。为快速准确估算油菜叶片EWT,选择9个常用的植被水分指数(WI、PRI、NDVI、NDII、NDWI、MSI、PWI、GVMI、NDMI),在6个已有角度指数(β_SWIR1、SANI、SASI、ANIR、NANI、NASI)基础上,提出2种角度比值指数(SARI、NARI),并根据油菜叶片水吸收谷峰高光谱特征,提出基于水吸收谷1 450 nm和1 930 nm的8种改进型角度指数,利用以上25种角度指数估算不同施氮水平下苗期、蕾薹期以及不区分苗期、蕾薹期情况下的油菜叶片EWT。结果表明,苗期ANI₁₄₅₀、ASI₁₄₅₀、MSI、GVMI、NDII估算效果较好,R²均达到0.81以上;蕾薹期ANI₁₉₃₀、ASI₁₉₃₀、NASI、SANI、GVMI、SARI效果最好,R²均达到0.71以上;在不区分苗期、蕾薹期的情况下,改进型角度指数ANI₁₄₅₀、ASI₁₄₅₀效果最好,R²均达到0.832,可以在不区分苗期、蕾薹期情况下对油菜叶片EWT进行估算,适用性更广。本研究提出的改进型角度指数不仅丰富了已有角度指数,且提高了其反演油菜叶片EWT的精度,为快速精确估计油菜叶片EWT提供了新的研究思路。     

高光谱成像快速检测壳聚糖涂膜草莓可溶性固形物

为了对壳聚糖涂膜草莓可溶性固形物含量(soluble solids content, SSC)进行快速检测,该文采用高光谱成像仪(400～1 000 nm)对0,0.5%,1%浓度的壳聚糖(chitosan, CTS)涂膜草莓分别储藏1,2,4 d后进行成像,并测量样本SSC。通过分析SSC发现,0.5%和1%壳聚糖涂膜草莓,其SSC随着储藏天数的增加均高于0浓度壳聚糖涂膜草莓,说明了0.5%和1%壳聚糖涂层抑制了草莓中SSC的降低,能够延长草莓的新鲜口味。随后采用蒙特卡罗-偏最小二乘法(monte carlo-partial least squares, MCPLS)对异常样本进行剔除。对剔除异常样本后的光谱数据进行不同预处理,以确定最优的预处理方法。为提高运行速度和降低数据维数,采用竞争性自适应权重取样法(competitive adaptive reweighted sampling, CARS)和连续投影算法(successive projections algorithm, SPA)进行特征波段选择。最后,采用偏最小二乘回归(partial least square regression, PLSR)和支持向量回归(support vector regression, SVR)法建立回归模型。最终结果表明:SPA-SVR模型效果最佳,0浓度的壳聚糖涂膜的草莓,建模集精度Rc2为0.865,预测集精度Rv2为0.835;0.5%浓度的壳聚糖涂膜的草莓,建模集精度Rc2为0.808,预测集精度Rv2为0.799;1%浓度的壳聚糖涂膜的草莓,建模集精度Rc2为0.834,预测集精度Rv2为0.875。对储藏第4天的部分样本图像进行主成分分析(principal component analysis, PCA),结果显示除第二主成分图像(PC2)中有部分噪声影响外,PC1和PC3均能完整反映草莓信息,且PC3图像明显呈现出不同浓度壳聚糖涂膜草莓的褐变程度,说明不同浓度的壳聚糖涂膜也会对草莓货架期产生不同影响。综上说明利用高光谱成像技术可以实现壳聚糖涂膜草莓SSC快速检测,有效指导草莓保鲜处理。     

基于可见-近红外光谱预处理建模的土壤速效氮含量预测

以皖南地区采集的188份黄红壤样本为研究对象,利用地物非成像光谱仪获取原始光谱数据。首先,分析样本在350~1 657 nm波段经过预处理变换的平均光谱反射率曲线特征,再基于原始光谱,以及经29种预处理变换后的光谱,分别结合偏最小二乘回归(PLSR)和径向基核函数(RBF)-PLSR算法,建立60个针对土壤速效氮含量的预测模型,并进行模型优化;然后,以模型的决定系数(R²)和相对分析误差(RPD)来评价模型性能。结果显示,基于Savitaky-Golay卷积平滑和对数变换预处理的光谱,用PLSR建立的模型最适用于土壤速效氮含量的校正预测,其在建模集中R²=0.94、RPD=3.88,预测集中R²=0.91、RPD=3.38。该模型达到A类预测精度,可实现对土壤速效氮含量的定量估测。     

Relationships of Spectral Reflectance with Plant Tissue Mineral Elements of Common Bean (Phaseolus Vulgaris L.) Under Drought and Salinity Stresses

ABSTRACT

Salinity and drought stresses are critical for Phaseolus vulgaris L. growth and development. They affect plants in various ways, including tissue mineral element content. Micro- and macro-elements in leaves of Phaseolus vulgaris L. (cv. ‘Blue lake’ and cv. ‘Terli’) subjected to deficit irrigation and salinity treatments were investigated, both analytically and with regards to their effect on the leaves’ spectral reflectance. B (boron), K (potassium), Mn (manganese), Na (sodium), Si (silicon) and Zn (zinc) appeared to be influenced by stress factors, mainly responding to salinity increase. The leaf spectral reflectance of the plants appeared to be significantly correlated with most of the elements under investigation. Multivariate regression identified a relationship of the reflectance at particular regions of the spectrum with phosphorus and NDVI (normalized difference vegetation index) and indicated a significant correlation with B, Fe (iron), K, Mn, P (phosphorus) and Zn. Moreover, customized spectral indices, exhibiting significantly high correlation with B, Fe, K, Mg (magnesium), Mn, Na, P, Zn and N (nitrogen), were developed.     

基于高光谱成像技术识别水稻纹枯病

【目的】利用高光谱成像技术对水稻纹枯病进行早期的快速无损识别,结合判别分析方法建立相应的鉴别模型。【方法】以健康和感染纹枯病的水稻幼苗为研究对象,采集叶片和冠层各180个样本的380~1 030 nm波段的360条高光谱图像,剔除明显噪声部分后,以440~943 nm波段作为水稻样本的光谱范围,分别用不同的方法预处理获得水稻叶片的光谱曲线。采用偏最小二乘–判别分析(PLS-DA)对不同预处理的光谱建模。采用MNF算法对冠层的原始光谱数据进行特征信息提取,并基于特征信息建立线性判别分析(LDA)模型和误差反向传播神经网络(BPNN)判别模型。【结果】标准正态变量变换(SNV)预处理后建立的PLS-DA模型的预测集判别正确率最高,为92.1%。基于特征信息的LAD和BPNN模型的判别结果优于基于全波段的PLS-DA判别模型。基于最小噪声分离变换特征信息提取的BPNN模型取得了最优效果,建模集和预测集正确率分别达99.1%和98.4%。【结论】采用高光谱成像技术对水稻纹枯病生理特征进行无损鉴别是可行的,本研究为水稻纹枯病的识别提供了一种新方法。     

不同生育时期冬小麦叶片相对含水量高光谱监测

为实现冬小麦不同生育时期叶片水分含量的快速监测，以冬小麦冠层高光谱数据和红外热成像数据为基础，计算得到5种光谱参数，通过对不同生育时期叶片相对含水量与光谱参数拟合状况进行分析和筛选，分别构建了基于光谱参数的叶片相对含水量反演模型，并对模型进行检验。结果表明，不同生育时期叶片相对含水量与比值指数（RVI）、归一化差值植被指数（NDVI）、比值/归一化植被指数（R/ND）、优化土壤调整植被指数（OSAVI）、冠气温差（TDc-a）均呈极显著相关（P＜0.01）；拔节期、抽穗期、开花期、灌浆前期和灌浆后期叶片相对含水量分别与NDVI、OSAVI、R/ND、TDc-a和TDc-a拟合效果较好，决定系数分别为0.842、0.884、0.831、0.864和0.945；预测模型的均方根误差分别为0.019、0.016、0.027、0.032和0.024，相对误差分别为2.16%、1.80%、3.30%、3.81%和3.53%。因此，在拔节期、抽穗期、开花期、灌浆前期和灌浆后期，可以分别利用NDVI、OSAVI、R/ND、TDc-a和TDc-a估测冬小麦叶片相对含水量。     

面向从江香猪选育的肌内脂肪活体超声无损测定

为探索从江香猪肌内脂肪含量的超声活体预测方法,该文选取110头从江香猪育肥猪开展活体测定,以超声图像为研究对象,利用Matlab R2015b软件提取灰度-梯度共生矩阵(gray gradient cooccurrence matrix,GGCM)及4个角度灰度共生矩阵(gray level cooccurrence matrix,GLCM)图像纹理特征参数。通过逐步回归分析法构建肌内脂肪(intramuscular fat,IMF)含量预测模型,再将此模型应用于另外42头从江香猪,验证模型准确性。逐步回归分析结果表明,背膘厚、灰度平均和梯度熵3个参数指标达到显著水平(P0.05),回归预测模型决定系数R2=0.369。线性回归及相关分析得出,估测值与实测值间RMSE为0.686,皮尔逊积矩相关系数(pearson correlation coefficients)和斯皮尔曼相关系数(spearman correlation coefficients)分别为0.592和0.640(P0.001)。该研究所构建的拟合回归模型可应用于从江香猪肌内脂肪活体预测,为后期高肌内脂肪含量从江香猪的选育提供更为便捷有效的手段。     

Infection routes of Aeromonas salmonicida in rainbow trout monitored in vivo by real‐time bioluminescence imaging

Recent development of imaging tools has facilitated studies of pathogen infections in vivo in real time. This trend can be exemplified by advances in bioluminescence imaging (BLI), an approach that helps to visualize dissemination of pathogens within the same animal over several time points. Here, we employ bacterial BLI for examining routes of entry and spread of Aeromonas salmonicida susbp. salmonicida in rainbow trout. A virulent Danish A. salmonicida strain was tagged with pAKgfplux1, a dual‐labelled plasmid vector containing the mutated gfpmut3a gene from Aequorea victoria and the luxCDABE genes from the bacterium Photorhabdus luminescens. The resulting A. salmonicida transformant exhibited growth properties and virulence identical to the wild‐type A. salmonicida, which made it suitable for an experimental infection, mimicking natural conditions. Fish were infected with pAKgfplux1 tagged A. salmonicida via immersion bath. Colonization and subsequent tissue dissemination was followed over a 24‐h period using the IVIS spectrum imaging workstation. Results suggest the pathogen's colonization sites are the dorsal and pectoral fin and the gills, followed by a progression through the internal organs and an ensuing exit via the anal opening. This study provides a tool for visualizing colonization of A. salmonicida and other bacterial pathogens in fish.     

Three‐dimensional visualization of green fluorescence protein‐labelled Edwardsiella tarda in whole Medaka larvae

The invasive fish pathogen Edwardsiella tarda is common in aquatic environments and causes the environmentally and economically destructive emphysematous putrefactive disease called edwardsiellosis. In order to understand the organism's infection pathway, medaka larvae (Oryzias latipes) were immersion‐infected with E. tarda labelled with green fluorescence protein (GFP) and then visualized in three dimensions under confocal laser microscopy and light‐sheet fluorescence microscopy. Confocal microscopy revealed GFP‐labelled E. tarda in the mouth, head, gill bridges, gill cover, skin, membrane fin, gastrointestinal tract and air bladder, and in the caudal vein, somite veins, caudal artery and caudal capillaries. Light‐sheet microscopy additionally showed GFP‐labelled E. tarda in the pharyngeal cavity, muscle of the pectoral fin and cardiac atrium and ventricle. These findings suggest that during its infection of fish, E. tarda initially adheres to, and invades, the epithelial cells of the skin, gills and gastrointestinal tract (through the pharyngeal cavity); E. tarda then enters the blood vessels to access organs, including the air bladder and heart.