Development and evaluation of a model for prediction of fecal and urinary nitrogen excretions in cattle

The reduction of nitrogen (N) excretion in animal production is crucial in intensive farming systems particularly in the developed countries. In this study, a model to predict N excretion in cattle was developed based on existing feeding standards and evaluated using independent N balance experiments for Holstein steers and lactating cows and Japanese Black (JB) steers. Although model predictions for fecal and urinary N excretions appeared to be close to observed values in plot figures, statistical analysis showed that the model tended to over-predict both fecal and urinary N excretions, especially in Holstein lactating cows. This was because body weight changes of cows during lactation period were not considered in the model due to the lack of information (i.e., body weight gain or loss) available in the experimental data for evaluation. There were large mean bias and small line bias for urinary N prediction, but reverse results were obtained for fecal N prediction. The largest mean square prediction errors for both N excretions were due to random variation in all cases. When all data were pooled (combined), the accuracy for predictions for fecal N excretion was considerably high (r² = 0.94), indicating that the model may predict fecal N excretion beyond breeds, sexes and physiological states (growing and lactating). More information and accumulated data will be required to predict urinary N excretion under a wide range of genotype and environmental situation.     

Comparison of the Sensitivity of Landscape-fire-succession Models to Variation in Terrain, Fuel Pattern, Climate and Weather

The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer & wetter, and warmer & drier) and weather (year-to-year variability) was determined for four existing landscape-fire-succession models (EMBYR, FIRESCAPE, LANDSUM and SEM-LAND) and a new model implemented in the LAMOS modelling shell (LAMOS(DS)). Sensitivity was measured as the variance in area burned explained by each of the four factors, and all of the interactions amongst them, in a standard generalised linear modelling analysis. Modelled area burned was most sensitive to climate and variation in weather, with four models sensitive to each of these factors and three models sensitive to their interaction. Models generally exhibited a trend of increasing area burned from observed, through warmer and wetter, to warmer and drier climates with a 23-fold increase in area burned, on average, from the observed to the warmer, drier climate. Area burned was sensitive to terrain for FIRESCAPE and fuel pattern for EMBYR. These results demonstrate that the models are generally more sensitive to variation in climate and weather as compared with terrain complexity and fuel pattern, although the sensitivity to these latter factors in a small number of models demonstrates the importance of representing key processes. The models that represented fire ignition and spread in a relatively complex fashion were more sensitive to changes in all four factors because they explicitly simulate the processes that link these factors to area burned. The US Government's and the Canadian Government's right to retain a non-exclusive, royalty-free license is acknowledged     

A simple diffusion model of the effect of droplet size and spread area on foliar uptake of hydrophilic compounds

The uptake of a hydrophilic active ingredient through the leaves of plants is mathematically modelled as a simple diffusion process. A three layer model is considered consisting of the droplet, the cuticle and the subcuticle. Translocation of the active ingredient from the subcuticle is allowed for as is depletion of the active ingredient from the droplet. Both the effect of the size of the droplets on the leaf surface and surfactant enhanced spreading of the droplet is examined. It is found that decreasing the size of the droplet leads to an increase in the percentage uptake of the active ingredient. Increasing the spread area of the droplet is found to increase the percentage uptake with the effect greatest in larger droplets.     

Development of <Emphasis Type="Italic">Peronospora parasitica</Emphasis> epidemics on radish as modelled by the effects of water vapour saturation deficit and temperature

Epidemics of Peronospora parasitica are strongly affected by temperature and air moisture, and the interaction of these factors. Because a significant percentage of radish plants are grown in greenhouses, it may be possible to influence epidemics by altering the greenhouse climate. The objective of this study was to test the hypothesis that epidemics of P. parasitica can be modelled by the effects of air temperature and moisture in the greenhouse. Such a model could then be used to analyse greenhouse climate control strategies with regard to managing downy mildew. Five radish crops were grown under greenhouse conditions with set-points for heating and ventilation intended to obtain favourable conditions for disease development during the first part of the growing cycle. Subsequent to this first phase, unfavourable conditions were set until harvest. Disease incidence was measured once a week until the radishes reached marketable size. In addition, experiments were carried out in growth chambers in which inoculated plants were subjected to air temperatures between 8 and 27°C, and disease incidence and sporulation intensity were measured. Data from these two experiments were then used to estimate model parameters. In this model, the interactions of air temperature (T) and water vapour saturation deficit (SD) were adequately described by a multiplicative relationship. The simulated epidemics by the fitted model were highly correlated with the observed epidemics (r = 0.91, R ² = 0.83, n = 29). Parameter estimates indicated that T of ca. 20°C and SD < 0.03 hPa resulted in the highest rates of disease development and that the rate was zero when SD > 2.0 hPa. Both experimental data and simulations showed that epidemics of P. parasitica can be effectively controlled by managing the greenhouse climate.     

Density estimates of rural dog populations and an assessment of marking methods during a rabies vaccination campaign in the Philippines

We estimated the population density of dogs by distance sampling and assessed the potential utility of two marking methods for capture-mark-recapture applications following a mass canine rabies-vaccination campaign in Sorsogon Province, the Republic of the Philippines. Thirty villages selected to assess vaccine coverage and for dog surveys were visited 1 to 11 days after the vaccinating team. Measurements of the distance of dogs or groups of dogs from transect lines were obtained in 1088 instances (N = 1278 dogs; mean group SIZE = 1.2). Various functions modelling the probability of detection were fitted to a truncated distribution of distances of dogs from transect lines. A hazard rate model provided the best fit and an overall estimate of dog-population density of 468/km² (95% confidence interval, 359 to 611). At vaccination, most dogs were marked with either a paint stick or a black plastic collar. Overall, 34.8% of 2167 and 28.5% of 2115 dogs could be accurately identified as wearing a collar or showing a paint mark; 49.1% of the dogs had either mark. Increasing time interval between vaccination-team visit and dog survey and increasing distance from transect line were inversely associated with the probability of observing a paint mark. Probability of observing a collar was positively associated with increasing estimated density of the dog population in a given village and with animals not associated with a house. The data indicate that distance sampling is a relatively simple and adaptable method for estimating dog-population density and is not prone to problems associated with meeting some model assumptions inherent to mark-recapture estimators.     

家蚕一代杂交种成品卵微粒子病检疫抽样检查存在问题及解决方案

利用近年来集团抽样检查接收概率函数的研究成果,分析了家蚕一代杂交种成品卵微粒子病检疫抽样检查在信赖度的估算、集团检出率的考虑和样本量大小等方面存在的问题,提出了成品卵微粒子病检疫抽样检查方案制定的基本原则和相应的改进方案。新方案考虑了集团检出率、样本的代表性等问题,通过增加检验集团内的个体数减少了检验工作量,使消费者风险和生产者风险都得到有效控制。     

基于有限元及试验技术的制动盘模态分析

针对制动噪声,基于有限元理论和方法,利用有限元分析软件MSC.NASTRAN对某盘式制动器制动盘进行模态分析,得到其固有频率和振型。同时,运用模态试验技术的锤击法对该制动盘进行模态试验,得到了试验模态参数,验证了有限元分析结果的准确性。研究表明,该制动盘前8阶固有频率主要集中在1~10 kHz范围内,对盘式制动器中高频制动噪声具有较大的影响。     

森林采伐限额与林业企业生产经营优化的探讨

简述了实施森林采伐限额制度的意义，以及实施限量采伐对林业企业经济的影响。利用投入产出与线性规划最优化模型对林业企业生产经营进行优化设计，提出了解决林业企业民限量采伐矛盾的方法和途径。     

Lederer粘度模型适用范围

基于140组北疆—吐哈、胜利—阿曼混合原油的粘度测量数据,对Lederer模型(经验常数α使用印度Shu关系式)的适用范围进行了研究,发现应用该模型计算高粘度比混合原油粘度时,存在一个临界温度,当混合原油温度在临界温度以上时,Lederer粘度模型具有很高的预测精度,其最小平均绝对相对偏差为3.97%,最大平均绝对相对偏差为9.15%;当在临界温度范围以下时,Lederer粘度模型的预测精度明显变差,其最小平均绝对相对偏差为13.57%,最大平均绝对相对偏差为109.8%,无法满足工程需要。这个临界温度随混合原油组分、混合比例不同而不同,一般低于高含蜡组分油的反常点。另外,还发现Lederer粘度模型预测值的平均相对偏差几乎全部为负偏差,即大部分预测值小于实测值,表明经验常数α引用Shu关系式还有待于修正。