珠江口重金属变化特征与生态评价

根据2002年5月和8月珠江口生态环境调查的数据,对水体和沉积物中重金属元素Cu、Pb、Zn、Cd的含量与变化特征进行分析讨论,并对研究海域的生态环境进行质量评价和生态危害性评价。结果表明,珠江口水体和表层沉积物中-6、48.9×10-6、153.3×Cu、Pb、Zn、Cd的平均含量分别是6.53μg/L、2.22μg/L、48.3μg/L、0.16μg/L和43.8×1010-6、0.82×10-6;沉积物对Cu、Pb、Zn、Cd的富集倍数平均在1.5～3.3。水体中Cu、Pb、Cd的含量在河口不同区段(上、下游)季节变化特征不同,这种变化与水体中Cu、Pb、Cd的存在形态、迁移转化过程有关;受水动力条件及冲淤特性的影响,表层沉积物中8月份Cu、Pb、Zn、Cd的含量高于5月份的含量。生态环境质量评价的结果表明,5月份珠江口水体处于中污染状况、沉积物属轻污染状况,8月份水体和沉积物分别为较清洁和中污染;对沉积物的生态危害评价显示,8月份沉积物重金属的潜在生态危害性高于5月份,Cd的潜在危害性高于Cu、Pb、Zn。     

赤水河中华倒刺鲃的形态分化及Cytb 基因序列比较研究

2013年9月调查发现,在赤水河干流中的雌性中华倒刺鲃（ Spinibarbus sinensis）群体中存在2种形态类型,按照体长比体高的形态学性状区分,分别为高背型（2.68～2.92）和低背型（3.19～3.58）。形态学分析表明,高背型和低背型在可数性状上并无显著性差异,在体长/体高等7个可比性状上二者存在极显著性差异,另外在体长/1-4等4个比例性状上也存在显著性差异,高背型比低背型具有明显的体型优势。生长特性分析表明,在相同体长或年龄的雌性群体中,高背型的平均体质量约为低背型的1.1～1.4倍,而表现出更为优越的生长性能。线粒体cytb基因序列分析表明,高背型和低背型群体各自独享1个单倍型（分别为HD和LD）,为2个不同的遗传谱系类群,遗传分化仅为0.005,远低于属内种间的0.020～0.045,两者尚属群体内变异;在分子系统关系中,高背型和低背型与长江干流泸州江段的单倍型（ LZ）共享并聚为单系,推测赤水河中华倒刺鲃源自长江干流。与国内其他地方群体或品种比较表明,赤水河2种类型雌性中华倒刺鲃,特别是高背型具有更为突出的生长优势,可作为优良的开发养殖品种和更具潜力的鱼类育种材料。     

基于质构和感官评价方法构建绿葡萄干干燥标准及快速检测技术

绿葡萄干较高的经济价值是维持新疆葡萄产业优势地位的重要支撑,葡萄干含水率对葡萄干的色泽、营养品质、质构特性和感官品尝体验具有较大的影响,但相关研究较少。本研究通过对不同含水率绿葡萄干品质、质构特性和感官品尝结果进行关联性分析,将定量检测技术应用到葡萄干的生产中。结果表明,不同含水率葡萄干的营养品质具有一定的差异,色泽分析中绿色色泽的差异最为显著;11.9%~19.2%含水率区间内葡萄干的质构特性呈现出较好的线性上升或下降趋势;不同人群对不同含水率葡萄干的感官品尝结果具有较大差异,含水率高的葡萄干在不同年龄段人群中的感官评分较高,根据感官评价结果和葡萄干的贮藏特性综合评价,生产中葡萄干含水率应控制在14%~17%;对葡萄干含水率与质构指标进行拟合,预测值与实测值的相对误差较小,弹性的相对误差最小为2.91%,粘附性的相对误差最大为13.33%;含水率14%~17%的葡萄干硬度预测值分别为1349.86、1191.75、1033.64、875.53 g;以硬度为快速检测指标,快速计算葡萄干含水率、弹性、咀嚼性等指标,拟合度较高,硬度与含水率的拟合方程为y=(-0.00006x+0.2191)×100,R²值为0.9171。综上,不同含水率葡萄干的色泽品质具有较大的差异,不同人群均喜欢较高含水率的葡萄干,采用硬度值快速计算葡萄干含水率及其他质构特性指标具有一定的可行性。研究结果可为绿葡萄干的标准化生产提供数据支撑和理论依据。     

Understanding the mechanism of change in morphological structures,visualization features,and physicochemical characteristics of adlay seeds (Coix lacryma-jobi L.): The role of heat soaking

Heat soaking is an essential factor deciding the final quality of hard-to-cook grains. In this study, the morphological structures, visualization features, and physicochemical characteristics of adlay seeds soaked at 30–70 °C were investigated compared with waxy rice (easy to cook). The morphology of macromolecules and section cracks were observed by scanning electron microscopy and light microscopy as these are the crucial factors for penetrate water penetration, which showed that starch granules were slightly eroded when adlay seeds were soaked at 70 °C. The MRI images showed that at higher soaking temperatures, the moisture of soaked adlay seeds was distributed more evenly across a gradient. Meanwhile, heat soaking has a minor effect on starch and protein content of adlay seeds, and the proportion of bound water of adlay seeds slightly declined after heat soaking. Moreover, hardness analysis and pasting measurements exhibited structural changes and viscosity transition in the grains. However, the contribution of heat soaking to the infrared spectrogram and relative crystallinity of adlay seeds was insignificant. This study provides effective methods to evaluate changes in adlay seeds during heat soaking and explains why it is hard to cook.     

Nondestructive evaluation of fish meat using ultrasound signals and machine learning methods

In this study, we propose a new method for the nondestructive measurement of the fat content and texture of fish meat using machine learning and the bag of features approach. We employed two machine learning methods, that is, a self-organizing map (SOM) and radial basis function (RBF) network. The SOM was applied to symbolize the pattern of the frequency spectrum extracted from ultrasound signals and to generate key features for the bag of features technique. The RBF network was applied to estimate the fat content and texture of fish meat from the bag of features histogram. We verified the accuracy of the fat content and texture estimations given by the proposed method through a series of experiments. The results showed that the fat content and texture of fish meat was estimated more accurately using the proposed method than by the conventional approach.     

Prediction of soil saturated water content using evolutionary polynomial regression (EPR)

The measurement of saturated water content (SWC) is necessary in the estimation of soil water retention and unsaturated hydraulic conductivity curves. In several studies, pedotransfer functions (PTFs) were developed to predict SWC. Among them, evolutionary polynomial regression (EPR) is one that can operate on large quantities of data in order to capture nonlinear and complex interactions between the variables of the system. In this study, the evolutionary data-mining technique was used to derive new PTFs and different methods were evaluated, such as the soil porosity method, Rosetta method, and others, for the estimation of SWC. For this purpose, 270 soil samples (3:1 ratio for development and validation) from three data sets were used. Among 190 PTFs provided by EPR, one equation with the highest accuracy and the least number of inputs was selected. The EPR predictions were compared with the experimental results as well as the PTFs proposed in previous studies. Comparison of the statistical indicators showed that the ‘proposed PTF’ and ‘porosity method’ are the best and worst methods for the prediction of SWC, respectively. Also, good predictions were achieved from the proposed approaches by the groups of Scheinost, Vereecken, and Williams.     

结合植被指数与纹理特征的玉米冠层FAPAR遥感估算研究

光合有效辐射吸收比率（fraction of absorbed photosynthetically active radiation,FAPAR）是反映作物产量的重要参数之一。无人机遥感能够快速无损地获取高分辨率植被冠层光谱信息,已成为进行物理化参数反演的重要手段。以不同播期玉米为研究对象,基于无人机搭载多光谱传感器,提取植被指数与植被纹理特征,使用偏最小二乘（partial least squares regression,PLSR）方法将二者结合反演玉米FAPAR,并与传统单独使用植被指数或植被纹理特征反演植被FAPAR的方法进行比较。结果表明：使用传统方法单独利用植被指数反演FAPAR（验证RMSE最低为7.33×10^-2,rRMSE最低为8.66%）的效果比单独利用纹理特征反演FAPAR（验证RMSE最低为9.50×10^-2,rRMSE最低为11.23%）的精度更高;使用PLSR方法单独利用植被指数或纹理特征估算FAPAR的效果比传统方法精度更高（植被指数与纹理特征的验证RMSE最低分别为6.77×10^-2和5.24×10^-2,rRMSE最低分别为8.01%和6.19%）;使用PLSR方法将植被指数与纹理特征相结合估算FAPAR（验证RMSE最低为4.72×10^-2,rRMSE最低为5.57%）的效果比单独使用植被指数或纹理特征估算FAPAR的精度更高。综上,使用PLSR方法将植被指数和植被纹理特征相结合来反演玉米冠层FAPAR可行,为作物FAPAR遥感反演研究提供了新的思路。     

基于小波变换与卷积神经网络的羊脸识别模型

为解决养殖场条件下羊只的个体识别问题,本文基于小波变换与卷积神经网络,提出一种融合频域特征与空间域特征的羊脸识别模型DWT-GoatNet。首先采集总计30只高相似度西农萨能奶山羊日间、夜间两种不同光照环境下的面部图像,基于SSIM指标剔除其中相似度过高的样本,接着进行图像裁剪,并通过模糊、调整亮度、平移、旋转、加入噪声、缩放等方法完成数据增强;然后,设计基于二维离散小波变换(2D-DWT)与卷积运算的羊脸特征提取模块,完成特征融合;之后,以前述羊脸特征提取模块为基础,添加分类模块,进行卷积神经网络搭建;最后,进行超参数组合寻优,形成羊脸识别模型。试验结果表明,本文所构建的羊脸识别模型在日间、夜间两种不同光照环境下测试集上识别准确率分别可达99.74%和99.89%,高于AlexNet、VGGNet-16、GoogLeNet、ResNet-50、DenseNet-121等经典卷积神经网络模型,说明所构建模型适用于羊只的个体识别,为精准养殖、农险理赔领域相关工作提供了有效解决方案。     

西双版纳机场2011年6月27-28日暴雨天气过程分析

2011年6月27-28日云南省西双版纳机场出现大到暴雨天气过程,通过对中高空天气形势及物理量特征等分析得出,此次降水过程是云南西部、南部地区受到切变线影响,而孟加拉湾低压有提供了充足的水汽条件。     

质地改良剂对北太平洋鱿鱼肌肉蛋白凝胶特性的影响

以北太平洋鱿鱼Ommastrephes bartrami的外套膜肌肉为原料,采用二次旋转组合实验设计方法,研究了3种品质改良剂（转谷氨酰胺酶、柠檬酸钠和多磷酸盐）对鱿鱼外套膜肌肉蛋白凝胶的凝胶强度、感官质量（咀嚼感、指压触感）和持水性的影响,并分别建立3种品质改良剂与感官质量、持水性和凝胶强度的回归拟合方程。结果表明：转谷氨酰胺酶、柠檬酸钠和多磷酸盐对鱿鱼肌肉蛋白凝胶的感官质量和凝胶强度均显示出不同的影响趋势,3种品质改良剂与感官质量（咀嚼感和指压触感）、凝胶强度和持水性的回归拟合方程的R2分别为0.8946、0.8980、0.9471、0.9106,拟合方程的显著性均很高,表明凝胶强度、感官评价和持水性均与转谷氨酰胺酶、柠檬酸钠、多磷酸盐的添加量存在着显著的相关关系,得到的拟合统计模型具有较高的可信度。