Hyperspectral species mapping for automatic weed control in tomato under thermal environmental stress

This work studied the impacts of variations in environmental temperature on hyperspectral imaging features in the visible and near infrared regions for robust species identification for weed mapping in tomato production. Six major Californian processing tomato cultivars, black nightshade (Solanum nigrum L.) and redroot pigweed (Amaranthus retroflexus L.) were grown under a variety of diurnal temperature ranges simulating conditions common in the Californian springtime planting period and one additional treatment simulating greenhouse growing conditions. The principal change in canopy reflectance with varying temperature occurred in the 480-670 and 720-810 nm regions. The overall classification rate ranged from 62.5% to 91.6% when classifiers trained under single temperatures were applied to plants grown at different temperatures. Eliminating the 480-670 nm region from the classifier’s feature set mitigated the temperature effect by stabilizing the total crop vs. weed classification rate at 86.4% over the temperature ranges. A site-specific recalibration method was also successful in alleviating the bias created by calibrating the models on the extreme temperatures and increased the classification accuracy to 90.3%. A global calibration method, incorporating all four temperature conditions in the classifier feature space, provided the best average total classification accuracy of 92.2% out of the methods studied, and was fairly robust to the varying diurnal temperature conditions.     

基于支持向量机（SVM）的稻纵卷叶螟危害水稻高光谱遥感识别

 对健康水稻叶片以及受稻纵卷叶螟危害后的水稻叶片进行了室内光谱的测定及分析。对430~530 nm和560~730 nm波段采用连续统去除的方法,分别提取了波深、斜率参量作为径向基核函数支持向量机的输入变量,利用LIBSVM软件包构建叶片高光谱识别模型。当参数γ和惩罚系数C分别取0.25和1时构建的径向基支持向量机模型的分类性能最佳,识别精度达100%。研究结果为实时水稻病虫害的早期监测以及田间管理提供了一定的理论基础。     

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.     

脐橙糖度光谱图像检测技术研究

对采集到的不同波长的光谱图像灰度分布进行洛伦茨分布(LD)、高斯分布(GD)、指数分布(ED)函数拟合,通过比较发现洛伦茨分布为最优灰度分布拟合函数.将脐橙的糖度与洛伦茨分布函数拟合所得参数分别进行多元线性回归,建立最佳单波长、最佳双波长组合、最佳三波长组合和最佳四波长组合的校正方程.结果表明:利用光谱图像技术无损检测脐橙糖度是可行性的.     

Identification of a periorbital wooden foreign body as the cause of chronic ocular discharge in a horse

The clinical, diagnostic and therapeutic features of a horse with a wooden foreign body embedded in the deep portion of the right masseter muscle adjacent to the right orbit are presented. The purpose of this report is to describe the clinical presentation, magnetic resonance imaging findings and treatment of a penetrating wooden foreign body in a horse that had no history of trauma or evidence of a puncture wound. This report documents the usefulness of magnetic resonance imaging to detect a wooden foreign body embedded in the soft tissues of a horse with a chronic copious ocular discharge. Two surgical procedures were necessary, which is a frequent complication encountered with wooden foreign bodies.     

PET/CT today and tomorrow in veterinary cancer diagnosis and monitoring: fundamentals,early results and future perspectives

Functional imaging using positron emission tomography (PET) plays an important role in the diagnosis, staging, image‐guided treatment planning and monitoring of malignant diseases. PET imaging complements conventional anatomical imaging such as computed tomography (CT) and magnetic resonance imaging (MRI). The strength of CT scanning lies in its high spatial resolution, allowing for anatomical characterization of disease. PET imaging, however, moves beyond anatomy and characterizes tissue based on functions such as metabolic rate. Combined PET/CT scanners were introduced commercially in 2001 and a number of technological advancements have since occurred. Radiolabelled tracers such as ¹⁸F‐fluorodeoxyglucose (FDG) and ¹⁸F‐fluorothymidine (FLT) allow visualization of various metabolic processes within cancer cells. Many studies in human oncology evaluating the utility of PET/CT have demonstrated clinical benefits. Few veterinary studies have been performed, but initial studies show promise for improved detection of malignancy, more thorough staging of canine cancer and determination of early response and disease recrudescence.     

基于野外实测高光谱数据的干旱区耕作土壤含水量反演研究

利用2011年3月野外实地采集的不同含水量土壤的高光谱数据,研究了南疆地区耕作土壤草甸土含水量与高光谱反射率之间的定量关系,构建了一元线性回归与多元逐步回归的土壤含水量预测模型.结果表明,土壤含水量在380～ 1080 nm波段与反射率呈负相关关系;反射率经倒数(1/R)、对数(logR)、一阶微分(R’)变换后可提高其与含水量的相关性;以50个建模样本所建立模型的相关系数均达到极显著水平,所有模型通过对37验证样本进行预测,比较决定系数、均方根误差、相对误差后,表明多元逐步回归模型的预测能力要优于一元线性回归模型,从所有模型中优选出以698、702、703、746、747 nm波段反射率倒数(1/R)建立的多元逐步回归模型为最优模型,该模型实测值与预测值之间的R2为0.9199,RMSE为1.6026,RE为0.6517,可用于基于野外高光谱数据的土壤含水量的估测.     

基于稀疏非负最小二乘编码的高光谱遥感数据分类方法

为了提高高光谱遥感影像的分类精度,提出了一种基于稀疏非负最小二乘编码的高光谱数据分类方法。采用非负最小二乘方法,将待测样本表示为训练样本的线性组合,并将得到的系数作为待测样本的特征向量,通过最小误差方法对待测样本进行分类。提出的方法在AVIRIS Indian Pines和萨利纳斯山谷高光谱遥感数据集上进行分类实验,并和主成分分析(PCA)、支持向量机(SVM)和基于稀疏表示分类器(SRC)方法进行比较,在2个数据集上本文方法的总体识别精度分别达到85.31%和99.56%,Kappa系数分别为0.816 3和0.986 7。实验结果表明本文方法的总体识别精度和Kappa系数都优于另外3种方法,是一种较好的高光谱遥感数据分类方法。     

东亚飞蝗光谱特征波长筛选与龄期识别方法研究

利用高光谱图像采集系统在400~1 000 nm波段范围内采集东亚飞蝗成虫、5龄、4龄和3龄的前胸背甲光谱信息;每个龄期提取15像素×15像素目标区域平均反射率信息作为样本信息;提出了一种基于K均值聚类和主成分分析(K-PCA)相结合特征波段提取方法,对比分析K-PCA和SPA(投影连续变换)2种特征波长提取方法,采用Fisher判别分析方法分别对K-PCA和SPA筛选的特征波长建立东亚飞蝗龄期识别判别模型,实验结果表明K-PCA筛选出的特征波长数少且正确识别率为98.25%。K-PCA筛选的特征波长为468 nm、555 nm、635 nm、710 nm、729 nm、750 nm、786 nm和899 nm。本文提取的东亚飞蝗特征波长为东亚飞蝗的龄期识别奠定基础,进而对蝗灾的监测与预防提供了技术支持。