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.     

软基水闸底板脱空动力学反演模型构建与试验验证

软基水闸极易因地基不均匀沉降、渗透变形等发生底板脱空现象,传统的无损检测方法难以在水下探测底板脱空,且不具实时性,其应用还存在一定局限性。该研究基于软基水闸室内物理模型,提出了一种软基水闸底板脱空动力学反演方法。首先,基于多参数变量的底板脱空范围数学模型,改进了反映软基水闸底板脱空参数与水闸动力学参数（模态参数）之间非线性映射关系的数学代理模型;其次,以水闸多测点多阶频率和振型变化率组合作为动力学敏感特征量,建立了软基水闸底板脱空参数反演的目标函数,并基于遗传算法对目标函数进行求解。最后,建立了软基水闸室内物理模型,并在模型中设置3种不同的底板脱空工况,采用软基水闸底板脱空动力学反演方法对软基水闸底板的脱空进行反演识别与模型验证。结果表明：基于动力学参数反演识别的水闸底板脱空区域趋势和脱空面积与模型实际脱空情况吻合较好,3种工况下水闸底板脱空面积反演结果与模型实际脱空面积的相对误差分别为7.47%、6.78%、6.90%,验证了该方法的可靠性,可望为软基水闸实际工程底板脱空隐患检测提供一种新的思路。     

COMPARISON OF FLUID-ATTENUATED INVERSION RECOVERY AND T2-WEIGHTED MAGNETIC RESONANCE IMAGES IN DOGS AND CATS WITH SUSPECTED BRAIN DISEASE

To compare fluid-attenuated inversion recovery (FLAIR) and T2-weighted magnetic resonance (MR) imaging in small animal patients with suspected brain disease, paired sets of FLAIR and T2-weighted MR images of 116 dogs and cats were reviewed separately without any patient information. Images were rated as normal or abnormal using a five-point scale, and the distribution, signal intensity, and anatomic location of abnormalities were recorded. In 60 animals, both FLAIR and T2-weighted images were normal. In 50 animals, the same abnormalities were identified in both FLAIR and T2-weighted images. Overall, very good agreement was found between FLAIR and T2-weighted MR images (kappa = 0.88). FLAIR images had abnormalities that were not recognized in the corresponding T2-weighted images in six of 116 examinations (5%). In four of these, the abnormalities in FLAIR images were thought to represent pathology, including granulomatous meningoencephalitis in one dog, postictal edema in one dog, and undiagnosed lesions in two dogs. In the remaining two examinations, the abnormalities in FLAIR images were probably artifacts. No examples were found of intracranial abnormalities in T2-weighted images that were not visible in FLAIR images. In this study, acquiring FLAIR images in addition to T2-weighted images resulted in detection of otherwise occult abnormalities in relatively few patients.     

应用高光谱数据定量反演查干湖水质参数研究

湖泊水质下降和富营养化问题日益严重,传统监测方法已经日益不能满足水质监测的需要。该文通过野外高光谱仪器测定查干湖水体反射光谱,分析研究水体反射光谱特征与水质参数叶绿素a含量、透明度和浊度之间的关系,运用多种半经验算法建立反演模型。结果表明:单波段光谱反射率与叶绿素a和浊度的相关系数较小,但与透明度相关系数较高;光谱反射率通过对数、比值转换,可以有效的提高叶绿素a和浊度估测模型的精度,却对透明度作用不大。总体来说,叶绿素a和浊度估测模型效果较好,透明度高光谱估测模型相对较差,需进一步研究。     

Development of a spot plow providing complete inversion for effective weed control

Tillage for the "complete inversion" of soil, that is, overturning soil slices 180° was proposed, a "spot plow" was developed and tested to accomplish the task, and a simulation model was evaluated to demonstrate the efficacy of the plow on weed control. A 360 mm wide spot plow was designed to operate at a speed of 1.9 m s⁻¹ for the spot plowing with the least possible lateral displacement of the soil slice by utilizing the inertia of the soil slice and securely rotating it. In field experiments, complete spot inversion required an operating speed of at least 1.6 m s⁻¹; at lower speeds, a portion of the soil block was left half-inverted and further lowering led to considerable lateral displacement. The displacement in the forward and lateral directions was minimal, implying that spot plowing is suitable for potential application to and verification of the weed population dynamics model in the field. A simple linear matrix model of the population dynamics of annual weeds was proposed, whereby four layers of soil were set to describe tillage and other ecological events. The effect of tillage on weed control was evaluated by the equilibrium reproduction rate allowed to sustain a stable population of weeds. The simulation model showed that alternately changing the depth of spot plowing had a significant effect on controlling weeds of low-survival-rate seeds, even when some incomplete inversion of the soil slice was taken into account.     

基于多源遥感数据的高寒草地生物量反演模型精度——以夏河县桑科草原试验区为例

基于MODIS、Landsat-8 OLI和HJ-1A/1B CCD卫星遥感资料,结合2013-2014年甘南州夏河县桑科草原试验区野外实测数据,建立了高寒草地地上生物量遥感反演模型,筛选出基于不同遥感资料植被指数的生物量最优反演模型,比较分析了生物量最优模型的空间效应。同时,分析了2000-2013年基于MODIS植被指数估算的试验区产草量的年际变化特征。结果表明,草地生物量最优反演模型为基于Landsat-8 OLI NDVI数据的对数模型(y=727.54lnx1+495.23,R2=0.772,RMSE=31.333 kg DM·hm-2);在30和250 m空间分辨率下,基于MODIS NDVI及EVI、Landsat-8 OLI NDVI和HJ-1A/1B CCD NDVI最优模型估算的生物量均高于实测生物量,其中Landsat-8 OLI NDVI数据估算的草地生物量与实测生物量值最接近;2000-2013年试验区草地总生物量整体上具有显著增加的趋势(R2=0.590 7,P0.001),平均增加速率达50.57 kg DM·hm-2·a-1。     

基于群智能优化算法的土壤水动力参数反演

土壤水动力参数是模拟田间土壤物质传输过程的基本参数,准确确定土壤水动力参数对实现农田生境精准调控具有重要意义。基于一维垂直入渗试验数据,采用代数方法和数值方法,构造3个不同的目标函数,并分析鲸鱼优化算法和灰狼优化算法反演Brooks-Corey-Mualem模型参数的适用性。结果表明：通过选择合适的目标函数,两种群智能优化算法均可用于反演土壤水动力参数。在代数方法中,鲸鱼优化算法在目标函数2下(由累积入渗量、入渗时间、含水率构成的相对误差)固定参数θ_r、θ_s优化得到的土壤水动力参数误差最小,反演参数得到的累积入渗量、入渗率、含水率的相对误差都在9.74%以下,决定系数都在0.904 0以上,反演时间为70 s;在数值方法中,灰狼优化算法在目标函数3下(由累积入渗量、湿润锋深度、含水率构成的相对误差)固定参数θ_r、θ_s优化得到的参数误差最小,反演参数得到的累积入渗量、入渗率、含水率的相对误差都在2.53%以下,决定系数都在0.991 7以上,反演时间为115 s。因此,代数方法所用时间短、精度相对较低...     

基于无人机偏振遥感的水稻冠层氮素含量反演模型

受水稻冠层几何结构的影响,传统的无人机高光谱获取到的反射光谱信息中包含与水稻内部组成物质无关的镜面反射信息,从而影响水稻氮素含量的反演精度,因此在利用无人机获取水稻冠层反射光谱信息时,有必要考虑通过偏振测量技术去除反射光谱中的镜面反射分量,进而实现提升水稻氮素含量反演精度的目的。基于无人机偏振遥感测量得到的水稻分蘖期多角度偏振光谱数据和与之对应的氮素含量数据,采用植被指数方法分析二者之间的相关性,得到了水稻冠层偏振光谱数据与其对应氮素含量相关性最高时对应的角度,选取该观测角度下的偏振光谱数据,利用连续投影法(Successive projections algorithm, SPA)提取特征波段,在此基础上,基于数学变换的方法,提出了构建植被指数的新思路,构建了由2个波段组成的偏振光谱植被指数(Polarisation spectrum vegetation index, PSVI),并利用线性回归方法建立水稻冠层氮素含量的反演模型。结果表明,通过对不同观测天顶角下水稻冠层偏振光谱数据与氮素含量相关性分析,得到最佳观测角度为-15°(后向观测15°);利用连续投影法提取得到该角度下偏振...     

基于高光谱图谱融合技术的英德红茶等级快速无损判别

茶叶等级评价是检测茶叶品质的一项重要技术指标。通过提取红茶高光谱成像技术下的图像特征和光谱特征,构建一种基于图谱融合方法、适用于英德红茶等级评价的快速无损判别模型。首先制备3种不同等级的红茶样本,采用t分布-随机近邻嵌入和主成分分析对光谱数据进行降维可视化分析,然后从影响内在品质角度用连续投影法提取每种化学值的特征波长,通过多模型共识策略和竞争性自适应重加权算法-连续投影法筛选得出表征其内在品质的最佳特征波长组合,并建立基于遗传算法优化支持向量机的等级判别模型;其模型的训练集准确率为88%,预测集准确率为78.33%。为了融合外形纹理差异,先提取最佳特征波长组合对应的高光谱图像;采用图像掩膜消除背景的干扰和采用图像主成分分析消除多波长图像间的冗余信息,然后采用灰度共生矩阵和局部二值化算法提取主成分前三维主成分图像与特征光谱融合,并建立基于特征融合的遗传算法优化支持向量机等级判别模型,且基于第三主成分图像特征融合模型判别效果最佳,训练集准确率提升至98%,预测集准确率提升至96.67%。     

基于PROSAIL模型的山地草原叶面积指数高光谱反演

【目的】 研究基于PROSAIL模型监测天然草地的动态变化,掌握草地的质量与数量。【方法】 研究使用地物光谱仪连续3年在天山北坡中段的2个山地草原样区采集光谱数据和配套数据,基于PROSAIL模型进行冠层LAI的高光谱反演,重点研究应用不同代价函数、植被种类变化对反演精度的影响。【结果】 多数代价函数反演LAI的决定系数(R²)在0.54~0.55,均方根误差(RMSE)在0.23~0.25,归一化均方根误差(NRMSE)在17~19。在9个来自不同统计类型的代价函数中,常用的RMSE代价函数的反演精度相对不高。将获取的427个样方数据依据种类数分成组,然后用PROSAIL进行LAI反演。种类数越多,RMSE在增大,R²在减少,反演精度越差。但精度的下降幅度不是均匀的,种类数≤2的组和种类数≤3的组之间精度差异最大。【结论】 在利用物理模型反演天然草地的叶面积指数时,不同代价函数获得的反演精度差别比较大;随着植被种类数量的增多,反演的精度是下降的。