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。     

大型渡槽槽身施工技术进展

阐述我国大型渡槽槽身施工技术的若干最新进展，并探讨了大型梁式渡槽槽身施工中的支撑浇筑系统、伸缩缝止水、预应力张拉等问题，提出大型渡槽槽身施工中支撑系统、施工方法、预应力张拉次序的选择，可供实际工程施工借鉴。     

基于烟叶致香成分建立烤烟香型分类模型方法研究

为筛选出基于烟叶致香成分数据建立烤烟香型分类的最优模型,以便于较好地对烤烟的香型进行正确分类。首先对142 个烤烟烟叶样品中的45 个指标采用行业标准进行检测,然后采用逐步回归法筛选出14 个烟叶致香成分,依据这14 个指标采用判别分析法、Logistic 回归、高斯混合模型、分类树、K最邻近法、人工神经网络和支持向量机7种方法进行建模。通过对不同方法建立的模型采用100次随机抽取训练集样本和测试样本计算错误分类率,选择错误分类率较低的模型作为优选模型。结果表明,线性判别法和高斯混和模型建立的2 种香型函数能较好地对未知样品的香型进行正确分类,且效果较好（正确率可达90%以上）。研究筛选出的2种优选模型对于烤烟香型分类研究具有一定的应用价值。     

运用数量化方法估测普洱县森林蓄积量

根据普洱县森林遥感调查资料 ,利用卫星影像特征判读数据与地面实测数据建立数学类型 ,估测森林蓄积量。首先将 2 0 0块有、疏林地数据输入数据本中 ,然后分析其与优势树种、龄组、郁闭度、海拔、坡向、坡度的关系 ,结果把样地分为针叶林、阔叶林、针阔混交林三个类型分别建立数学模型 ,以估测每公顷蓄积量。数学模型的建立是根据数量化模型的原理来编程 ,并通过计算机的不断调试 ,直到可行为止。蓄积量比较精度达到 90 3%。     

Accounting for unknown foster dams in the genetic evaluation of embryo transfer progeny

Animals born by embryo transfer (ET) are usually not included in the genetic evaluation of beef cattle for preweaning growth if the recipient dam is unknown. This is primarily to avoid potential bias in the estimation of the unknown age of dam. We present a method that allows including records of calves with unknown age of dam. Assumptions are as follows: (i) foster cows belong to the same breed being evaluated, (ii) there is no correlation between the breeding value (BV) of the calf and the maternal BV of the recipient cow, and (iii) cows of all ages are used as recipients. We examine the issue of bias for the fixed level of unknown age of dam (AOD) and propose an estimator of the effect based on classical measurement error theory (MEM) and a Bayesian approach. Using stochastic simulation under random mating or selection, the MEM estimating equations were compared with BLUP in two situations as follows: (i) full information (FI); (ii) missing AOD information on some dams. Predictions of breeding value (PBV) from the FI situation had the smallest empirical average bias followed by PBV obtained without taking measurement error into account. In turn, MEM displayed the highest bias, although the differences were small. On the other hand, MEM showed the smallest MSEP, for either random mating or selection, followed by FI, whereas ignoring measurement error produced the largest MSEP. As a consequence from the smallest MSEP with a relatively small bias, empirical accuracies of PBV were larger for MEM than those for full information, which in turn showed larger accuracies than the situation ignoring measurement error. It is concluded that MEM equations are a useful alternative for analysing weaning weight data when recipient cows are unknown, as it mitigates the effects of bias in AOD by decreasing MSEP.     

Preparation of Atherosclerosis Model Using Guangxi Bama Mini-pig

The atherosclerosis (AS) model was prepared in Guangxi Bama mini-pig,and the atherosclerosis index (AI) was preliminarily identified in occurrence of AS to provide the basis for the preparation of related models.20 Guangxi Bama mini-pigs were randomly divided into control group and experimental group which were fed with high fat and cholesterol diet to prepare the AS model.Blood biochemical indexes were detected in the process of model preparation and the correlation between AI and the results of vascular slices was analyzed to initially draw up AI of AS.The results of vascular slices showed that the incidence rates of AS of Guangxi Bama mini-pigs in experimental group and control group were 20% and 0,respectively.The association analysis between the results of vascular slices and AI in the pathogenic Guangxi Bama mini-pigs preliminarily suggested that AI was above 3.8 and lasted for more than 3 months during the attack.     

近53年青海省气候变化与粮食产量及气候生产潜力特征

利用青海省1961-2013年年平均气温、年降水量等资料,分析了青海省气候变化的特征,应用Thornthwaite Memorial 模型估算了青海省气候生产潜力,探讨了气候生产潜力与粮食产量的关系。分析结果表明,1961-2013年青海省年平均气温显著升高,年平均气温升温率达0.40 ℃10a-1;降水量也呈现增加趋势,增幅为6.0 mm10a-1;日照时数和相对湿度呈现减少趋势。自2002年以来的近10年期间,粮食总产量和气候生产潜力变化趋势有一定相关性且气候生产潜力从2002年开始有突变（r=0.29,P＜0.05）。近53年青海省气候生产潜力在323.39～478.48 gm-2a-1之间,年际间变化波动较大,呈现较弱的增加趋势,增加率为0.914 gm-2a-1。     

基于TM NDVI的库尔勒市域植被覆盖动态变化

以库尔勒市域为研究区,基于1990、1998、2006和2011共4期TM遥感影像提取归一化植被指数（NDVI）,将NDVI结果输入到像元二分模型中计算得到研究区各时期植被覆盖度,然后根据研究需要将植被覆盖度划分为4个等级,最后计算覆盖度差值并结合各级覆盖度转移矩阵和土地利用情况分析了库尔勒市域植被覆盖度动态变化特征。结果表明,在1990、1998、2006和2011年间,库尔勒市域总体植被覆盖情况有所改善,植被恢复改善面积比退化面积多23.8%,其中东南部的扇形绿洲平原植被状况改善明显,北部和南部区域植被有所退化。     

A comparison between multivariate Slash, Student's t and probit threshold models for analysis of clinical mastitis in first lactation cows

Robust threshold models with multivariate Student's t or multivariate Slash link functions were employed to infer genetic parameters of clinical mastitis at different stages of lactation, with each cow defining a cluster of records. The robust fits were compared with that from a multivariate probit model via a pseudo‐Bayes factor and an analysis of residuals. Clinical mastitis records on 36 178 first‐lactation Norwegian Red cows from 5286 herds, daughters of 245 sires, were analysed. The opportunity for infection interval, going from 30 days pre‐calving to 300 days postpartum, was divided into four periods: (i) ?30 to 0 days pre‐calving; (ii) 1–30 days; (iii) 31–120 days; and (iv) 121–300 days of lactation. Within each period, absence or presence of clinical mastitis was scored as 0 or 1 respectively. Markov chain Monte Carlo methods were used to draw samples from posterior distributions of interest. Pseudo‐Bayes factors strongly favoured the multivariate Slash and Student's t models over the probit model. The posterior mean of the degrees of freedom parameter for the Slash model was 2.2, indicating heavy tails of the liability distribution. The posterior mean of the degrees of freedom for the Student's t model was 8.5, also pointing away from a normal liability for clinical mastitis. A residual was the observed phenotype (0 or 1) minus the posterior mean of the probability of mastitis. The Slash and Student's t models tended to have smaller residuals than the probit model in cows that contracted mastitis. Heritability of liability to clinical mastitis was 0.13–0.14 before calving, and ranged from 0.05 to 0.08 after calving in the robust models. Genetic correlations were between 0.50 and 0.73, suggesting that clinical mastitis resistance is not the same trait across periods, corroborating earlier findings with probit models.