Validating a Time Series of Annual Grass Percent Cover in the Sagebrush Ecosystem

We mapped yearly (2000–2016) estimates of annual grass percent cover for much of the sagebrush ecosystem of the western United States using remotely sensed, climate, and geophysical data in regression-tree models. Annual grasses senesce and cure by early summer and then become beds of fine fuel that easily ignite and spread fire through rangeland systems. Our annual maps estimate the extent of these fuels and can serve as a tool to assist land managers and scientists in understanding the ecosystem’s response to weather variations, disturbances, and management. Validating the time series of annual maps is important for determining the usefulness of the data. To validate these maps, we compare Bureau of Land Management Assessment Inventory and Monitoring (AIM) data to mapped estimates and use a leave-one-out spatial assessment technique that is effective for validating maps that cover broad geographical extents. We hypothesize that the time series of annual maps exhibits high spatiotemporal variability because precipitation is highly variable in arid and semiarid environments where sagebrush is native, and invasive annual grasses respond to precipitation. The remotely sensed data that help drive our regression-tree model effectively measures annual grasses’ response to precipitation. The mean absolute error (MAE) rate varied depending on the validation data and technique used for comparison. The AIM plot data and our maps had substantial spatial incongruence, but despite this, the MAE rate for the assessment equaled 12.62%. The leave-one-out accuracy assessment had an MAE of 8.43%. We quantified bias, and bias was more substantial at higher percent cover. These annual maps can help management identify actions that may alleviate the current cycle of invasive grasses because it enables the assessment of the variability of annual grass ? percent cover distribution through space and time, as part of dynamic systems rather than static systems.     

西部少数民族贫困山区扶贫模式研究——以四川省昭觉县为例

西部民族贫困山区是我国扶贫攻坚的重点和难点地区,其扶贫工作的好坏直接关系：我国民族团结、全面建设小康社会目标的实现。在分析西部民族贫困山区县——四川省昭觉县农村贫困与扶贫工作现状的基础上,总结了适合民族贫困山区县的扶贫模式——“三集中”扶贫模式,提出通过发展县域循环经济和建立健全生态环境补偿机制来推广发展“三集中”扶贫模式的对策建议。     

猪饲料有效能值预测模型的构建

为探索饲料常规成分及碳水化合物组分与饲料有效能值之间的关系方程,本研究以NRC第11版《猪营养需要量》中发布的122套饲料营养成分表为基础,将饲料中11种基础成分[6项常规成分:干物质、粗蛋白质(CP)、粗纤维(CF)、粗脂肪(EE)、酸性醚提取物、粗灰分(ash);5项碳水化合物组分:淀粉(ST)、中性洗涤纤维(NDF)、酸性洗涤纤维(ADF)、半纤维素、酸性洗涤木质素]作为自变量,将饲料中的消化能(DE)、代谢能(ME)及净能(NE)作为因变量,采用SAS软件中的REG过程,分别建立不同性质饲料、自变量的不同组合与DE、ME及NE之间的回归关系方程,并以相关系数(R2)及变异系数(CV)作为评价回归模型的优劣。研究表明,有效能值与CP、ST及纤维类指标显著或极显著相关(P0.05或P0.01)。将所有饲料作为研究对象时,饲料的DE、ME及NE与上述11种基础成分之间建立的普适性回归模型预测效果较差。当将14种玉米及其加工产品形成子集时,建立饲料基础营养成分与DE、ME及NE的关系方程分别为7、6和7套(P0.05),且3组回归模型R2分别为0.632 8~0.772 3、0.646 9~0.684 9和0.670 5~0.822 1,CV分别为6.61%~8.40%、6.58%~7.34%和6.21%~8.27%;当将13种大豆及其加工产品形成子集时,共建立饲料基础成分与DE、ME关系方程分别有3和4套,回归模型R2分别为0.907 1~0.926 9、0.890 7~0.922 3,CV分别为5.40%~6.09%、5.79%~6.78%,NE与基础营养成分指标之间无法建立具有营养学意义的有效回归方程。对于同类饲料中具有相同自变量组合的DE及ME预测模型而言,两者之间的差异主要是自变量CP的系数上,且CP部分对ME的正效应低于DE,这保证模型预测的ME低于DE。同时选用本研究构建的适宜模型,补充了NRC第11版成分表中第97(去皮大豆粕,低寡糖,浸提)、101(全脂大豆,高蛋白质)及102号(全脂大豆,低寡糖)饲料的DE值分别为15.99、17.35、17.27 MJ/kg,ME值分别为14.53、16.15和16.14 MJ/kg。综上,以NRC(2012)饲料营养成分表为基础,建立的普适性有效能值回归模型预测效果较差。按照玉米类和大豆类进行分类,可建立DE、ME和NE与饲料化学成分之间的多元回归方程,其中最优的预测因子为CP、EE、ST、ash、NDF、ADF。具有相同自变量的同类饲料DE和ME预测模型之间的差异是CP系数,CP影响DE转化为ME的效率。     

高分辨四极杆飞行时间质谱仪判别复原乳和超高温灭菌乳

采用高分辨四极杆飞行时间质谱仪,结合化学计量学方法,利用非靶向代谢组学方法,对超高温灭菌乳和复原乳进行检测。牛乳样品经过前处理后,经过C18色谱柱分离,采用FullScan模式进行一级全扫描,扫描结果通过数据预处理后,导入SIMCA-P14.1软件中进行主成分分析和偏最小二乘方差判别分析。结果表明:正、负离子模式下共找到14种判别超高温灭菌乳和复原乳的表征因子,进一步通过这14种表征因子建立区分2种乳的判别模型,通过该判别模型能够准确地区分超高温灭菌乳和复原乳,为复原乳的判别提供理论依据。     

不同生长模型估计籽鹅早期体重发育规律及遗传参数

运用Logistic,Gompertz,VonBertalanfy和Cubic4种非线性生长模型对籽鹅1～1周龄的平均体重进行拟合,并分析生长发育规律及遗传参数。结果表明:虽然4个模型都能描述籽鹅的生长过程,拟合度均超过额0.99;但Logistic模型更符合实际饲养情况,能更好地预测体重,为最佳模型,其相应的体重极限参数A为2267.63g,调节参数B为16.27,瞬时相对生长率C为0.47,生长的拐点时间为6.48周龄,拐点体重为1136.81g。     

利用广义线性模型预测家畜离散性状育种值

将广义线性混合模型(GLMM)引入动物离散性状的遗传分析及个体的遗传评定,初步比较了GLMM方法与一般线性方法(LM)的估计效果。模拟研究的性状为单阈值二项分类性状,选用的连接函数为对数连接μi=eη/(1+eη),方差函数为V(μi)=μ(i1-μi)/n,试验设计为全同胞-半同胞混合家系,参数估计采用Fisher迹法。结果表明:GLMM方法能较准确地估计公畜的个体育种值,在个体的遗传评定效果方面要明显优于常规的线性方法,其预测的育种值排序结果与真实育种值的排序之间存在极显著的相关性(P<0.001)。     

An Adjustable Nutrient Margin of Safety Comparison Using Linear and Stochastic Programming in an Excel Spreadsheet

A stochastic-linear program Excel workbook was developed that consisted of 2 worksheets illustrating linear and stochastic program approaches. Both approaches used the Excel Solver add-in. A published linear program problem served as an example for the ingredients, nutrients, and costs and as a benchmark in the development of the linear and stochastic programs. Standard deviations for ME and nutrients were taken or calculated from CV, and from a commercial publication of sources for amino acids. The Excel spreadsheet was set up so that the calculated margin of safety (MOS) value, according to the requested probability, was the same for both the linear and stochastic programs. As an example, the probability for meeting the nutrient value for protein was compared at 50% (MOS = 0) and 69% (MOS = 0.5) by using both linear and stochastic programming. Spreadsheet results illustrated the flexibility, accuracy, and precision of the stochastic program over the linear program in meeting the requested nutrient probability.     

家兔临床型乳腺炎病理模型的血液学检验

本试验选取16只3~4 kg健康泌乳家兔,通过人工造模的方法诱发其乳腺发炎,建立临床型乳腺炎模型。然后分别在造模前1 h和造模后4、12、24、36、487、2 h采集血液0.5 mL、血清1 mL,进行血常规、血生化检测和炎性细胞因子测定(ELISA)。结果显示:①外周血白细胞总数在造模后4 h显著高于造模前水平(P0.05),12~72 h内极显著高于造模前水平(P0.01);红细胞总数、红细胞压积、血红蛋白含量在造模前至造模后72 h内无显著差异(P0.05)。②血清磷离子含量、血清总胆红素含量、血清直接胆红素含量在造模前至造模后72 h内无显著差异(P0.05);血清钙离子含量在造模后4 h显著低于造模前水平(P0.05),12~72 h内极显著低于造模前水平(P0.01)。③血清TNF-α和IL-6含量造模后开始升高,12~72 h内极显著高于造模前水平(P0.01)。结果证明白细胞总数、血清钙离子含量、血清TNF-α和IL-6含量的变化可作为急性乳房炎炎症发展情况的指标。     

基于VG-PENG收缩特征曲线与收缩各向异性的裂隙率估算模型

为量化农田裂隙发育程度,考虑脱湿过程中土壤孔隙在基质域、沉降域和裂隙域间转化,该研究提出基于土壤收缩特征和收缩各向异性的裂隙体积比率(裂隙率)关于含水率的预测模型.该模型包括3个子模型:改进VG型式的基质域收缩特征VG-PENG模型,描述收缩各向异性的几何因子Logistic模型,基于上述VG-PENG收缩特征模型和几...     

ArcGIS Server支持下农产品质量安全追溯模型的实现

近年来农产品质量安全事件频繁发生,利用农产品质量安全追溯信息进行质量安全应急管理已成为处理农产品质量安全事件的重要手段,但是这些信息仅能以文本表格的形式表现出来,在地图服务端存在一定的限制。模型借助于ArcGISServer,把传统的质量安全追溯与GIS功能相结合,实现追溯信息在地理空间中的形象化展示,并可对地图服务任意进行配置。该模型不仅能够图形化地模拟出农产品在不同主体之间的流通路径,而且能在发生农产品质量安全事件时快速定位到责任主体。