Investing in a robotic milking system: a Monte Carlo simulation analysis

This paper uses Monte Carlo simulation methods to estimate the breakeven value for a robotic milking system (RMS) on a dairy farm in the United States. The breakeven value indicates the maximum amount that could be paid for the robots given the costs of alternative milking equipment and other important factors (e.g., milk yields, prices, length of useful life of technologies). The analysis simulates several scenarios under three herd sizes, 60, 120, and 180 cows. The base-case results indicate that the mean breakeven values are $192,056, $374,538, and $553,671 for each of the three progressively larger herd sizes. These must be compared to the per-unit RMS cost (about $125,000 to $150,000) and the cost of any construction or installation of other equipment that accompanies the RMS. Sensitivity analysis shows that each additional dollar spent on milking labor in the parlor increases the breakeven value by $4.10 to $4.30. Each dollar increase in parlor costs increases the breakeven value by $0.45 to $0.56. Also, each additional kilogram of initial milk production (under a 2x system in the parlor) decreases the breakeven by $9.91 to $10.64. Finally, each additional year of useful life for the RMS increases the per-unit breakeven by about $16,000 while increasing the life of the parlor by 1 yr decreases the breakeven value by between $5,000 and $6,000.     

蒙特卡罗模拟在微米木纤维热磨中的应用

分析总结了木纤维热磨加工中功耗较大的原因,提出了微米级纤维切削的新方法,并提出用蒙特卡罗统计分析纤维热磨过程中的相关参数变化,从而得出合理参数估计值的设想。     

蒙特卡洛法在甘蔗种质资源研究中的应用展望

甘蔗种质资源是甘蔗育种的物质基础,也是研究甘蔗及其近缘属植物起源、进化和遗传多样性的物质基础。蒙特卡洛法是一种有效的统计试验方法,本文通过分析总结其在大豆、野生利马豆、马铃薯、明党参等植物种质资源研究中的应用,对蒙特卡洛法在甘蔗种质资源研究中的应用作了展望。     

Prediction of time to growth of Listeria monocytogenes using Monte Carlo simulation or regression analysis,influenced by sublethal heat and recovery conditions

Stochastic models, including the variability in extent and probability of microbial growth, are useful for estimating the risk of foodborne illness (i.e. Nauta, 2000). Risk assessment typically has to embrace all sources of variability. In this paper, a stochastic approach to evaluate growth of heat damaged Listeria monocytogenes cells influenced by different stresses (pH and presence of eugenol) was performed, using an individual-based approach of growth through OD measurements. Both the lag phase duration and the “work to be done” (h₀ parameter) were derived from the growth curves obtained. From results obtained histograms of the lag phase were generated and distributions were fitted. Histograms showed a shift to longer lag phases and an increase in variability with high stress levels. Using the distributions fitted, predictions of time to unacceptable growth (10² cfu/g) of L. monocytogenes were established by Monte Carlo simulation and they were compared with results from statistical methods. It was evidenced that both methods (Monte Carlo and regression analysis) gave a good indication of the probability of a certain level of growth other than the average. Tornado plots were obtained to establish a sensitivity analysis of the influence of the conditions tested (heat, pH, eugenol) applied to the microorganism and their combinations.     

The variable nature of Biot numbers in food drying

Biot numbers (Bi) relate internal and external resistances to mass or heat fluxes and are useful to identify controlling mechanisms. Their variation during drying received little attention despite its importance in model selection. Therefore, variable Bi were analysed in drying of wheat, a low-moisture product, and in the formation of a low-calorie, dehydrated apple-leather (LCAL), a high moisture product. Wheat drying was predicted with a numerical solution from a m.c. of 0.35 kg water/kg dry matter, to find a variable mass transfer Bi that shifted the controlling mechanism from internal-external to internal. From a lower m.c. of 0.205 kg water/kg dry matter, the entire process was internally controlled. Drying of shrinking LCAL was solved with the energy balance. The mass transfer Bi varied from 0.5 to 1600, while the heat transfer Bi, only from 0.25 to 0.5, and a modified version, from 0.25 to 0.     

蒙特卡洛方法及在二维随机游动问题中的应用初探

概述蒙特卡洛方法的产生与发展,并结合射击问题的求解阐述了蒙特卡洛方法的基本特点,最后就蒙特卡洛方法在二维随机游动问题中的应用进行讨论,指出可将此用在油墨印刷牢度的评价上。     

Power density control in microwave assisted air drying to improve quality of food

Currently, the new trend is the development of microwave hot air drying control in order to solve the problem of hot spots on the product. So in this study, a microwave/hot air drying system with the ability of automatic power density control was developed for tomato drying. Three power densities (3, 5 and 7 W/g) at 40 °C air temperature were applied and the output, reflected microwave power and the mass of the sample were registered online. Two different drying strategies were implemented. The first consisted of a microwave drying without specific power control. The second one introduced power control. A feedback control based on specific power related to the actual sample mass resulted in the best power control and the improvement of product quality compared to the dry sample without power control.     

计算机数值模拟在食品干燥过程中的应用进展

由于食品干燥过程牵涉到相变、传热、传质、收缩等诸多变化,为预见食品真实的干燥情况,为生产应用提供参考,一种直观、快速、经济的研究方法——计算机数值模拟应运而出。从数值模拟常用的数学解析方法、模拟分析语言和软件三个方面介绍了计算机数值模拟的工具,并阐明了其一般流程,概述了该方法在食品干燥过程中的应用和发展前景。     

数值模拟方法在食品微波干燥机理与过程研究中的应用

在对微波干燥原理及特点进行分析的基础上,对农产品、食品的微波干燥机理与工艺研究中采用的数值模拟方法进行了归纳,重点分析说明了数值模拟方法在微波干燥过程中物料吸收微波能大小、水分扩散、物料收缩等方面的研究现状,并对该方法在微波干燥中的进一步研究进行了展望。     

Monte Carlo Simulation to establish the effect of pH, temperature and heating time on the final load of Bacillus stearothermophilus spores

Bacillus stearothermophilus heat treatment studies at different pH levels were carried out in order to predict the final microbiological load as affected by the temperature and pH treatment. For that, distribution functions were obtained for the initial number of microorganisms, the decimal reduction coefficient, the z _T and the z _pH parameters, and Monte Carlo Simulation was used as a tool to determine this microbial load after a heat treatment introducing in this way the variability and uncertainty. The mean value of the predictions made by Monte Carlo Simulation, when compared with independent data, rendered Accuracy Factors close to 1, values close to 1 indicated good predictions. Bias values were close to 1, but some values were below 1 and others above 1. The tornado graphs indicated that the main factor contributing to the final load after the heat treatment was the initial number of microorganisms followed by the temperature and pH.     

Assessing economic consequences of foot disorders in dairy cattle using a dynamic stochastic simulation model

Foot disorders are an important health problem in dairy cattle, in terms of economics and animal welfare. The incidence, severity, and duration of foot disorders account for their importance. Prevalence of both subclinical and clinical foot disorders is high. More insight into the economic consequences could increase awareness among dairy farmers and could be an incentive for them to take action on this problem of animal welfare. The objective of this research was to estimate the economic consequences of different types of foot disorders, both clinical and subclinical. A dynamic stochastic Monte Carlo simulation model was used, taking into account the different types of foot disorders. The economic consequences of the foot disorders modeled were costs due to milk production losses, culling, prolonged calving interval, labor of the dairy farmer and the foot trimmer, visits of a veterinarian, treatment, and discarded milk. Under the milk quota system in the Netherlands, costs due to foot disorders for a default farm with 65 cows averaged $4,899 per year (ranging from $3,217 to $7,001), an annual loss of $75 per cow. This calculation implies that the costs due to foot disorders are more substantial than farmers might think. The costs of subclinical foot disorders account for 32% of all costs due to foot disorders. The costs due to foot disorders that are present without treatment or detection by the farmer are considerable. This finding implies that farmers might underestimate the benefits of taking action earlier and more thoroughly. A clinical foot disorder costs, on average, $95, and a subclinical foot disorder $18. The highest costs classified by foot disorder were those due to digital dermatitis, which has a high incidence and relatively high clinical prevalence. The highest costs classified by cost factor were those due to milk production losses and culling. Sensitivity analysis showed that variables regarding milk production were important for economic costs due to foot disorders. Furthermore, the probability of getting a foot disorder and probability of cure were important for estimating the costs due to foot disorders. Farmer awareness concerning dairy cow foot health and taking action more thoroughly, therefore, could reduce the economic consequences and improve welfare simultaneously.     

Estimation of confidence interval of pasteurizing values of conduction-heated Sous Vide food in a combination oven

The thermal diffusivity of potato and the apparent heat transfer coefficients (h) in a conduction chiller and in a combination oven at 85, 90 and 95°C and vario-steaming mode were determined experimentally. Based on K-S tests and assumption, the variabilities of all six parameters (thermal diffusivity, h values for heating and cooling, initial food temperature, process medium temperatures and z value) were represented by normal distribution only (model A) or by both normal and gamma distributions (model B). The mean P₇₀ values and their 95% confidence intervals for three oven temperatures, estimated from experimental temperature histories, were 1510 ± 101, 1590 ± 131 and 1590 ± 170 min (for each oven temperature, n = 100) respectively. Good agreement was obtained between these estimations and those predicted using the Monte Carlo procedure and models A and B.     

Drying rate control in the middle stage of microwave drying

Microwave drying of apples at constant temperatures follows typical drying curves. The middle stage of the drying process shows a faster drying rate and accelerated moisture evaporation. Meanwhile, more flavors are lost, surface color is degraded, and charring often occurs in this stage. To improve the drying effects, drying curves were controlled and changed in this study. The drying curve was linearized by automatically varying drying temperatures in the middle stages. The controlled drying process therefore led to an optimized temperature profile. To simplify the drying methods, apples were further dried with the obtained temperature profile, while drying curves were online monitored but not controlled. It was proved that slowing down the drying rate in the middle stage could improve the product quality in terms of color, flavor, and overall appearance, while the drying time and energy consumption were still acceptable (within 200 min and 22 kJ/g, respectively).     

Exposure of the Irish population to PBDEs in food: consideration of parameter uncertainty and variability for risk assessment

Polybrominated diphenyl ethers (PBDEs) are brominated flame retardants used to retard the ignition and/or spread of fire. PBDEs are used in various consumer products, such as textiles, mattresses and TV screens. This study presents a chemical risk assessment for the Irish population based on exposure to PBDEs from food. Special regard is given to the influence of parameter uncertainty and variability on the margins of safety. To quantitatively model uncertainty and variability in concentration data and variability in consumer behavior, a hierarchical probabilistic model was constructed. This model was evaluated using a two-dimensional Monte Carlo simulation (2D-MCS) approach. By considering uncertainty and variability in concentration data, margins of safety (MOS) were derived that are lower by a factor of ～2 compared to MOS based on dose estimates that only consider variability. The lowest MOS is 7.5?×?10⁴ for BDE-99, with impaired spermatogenesis as toxic endpoint. Assuming an MOS of 10⁴ as acceptable, we conclude that there is no significant risk for human health through intake of contaminated food. To investigate whether additional measurements could improve the quality of dose estimates, the statistic “uncertainty-to-variability (UVR)” was developed. By applying the UVR to our dose estimates, we show that, in our case, the datasets contain little uncertainty and additional measurements would not significantly improve the quality of dose estimates.     

A comparison of imputation techniques for internal preference mapping, using Monte Carlo simulation

The usual algorithm for internal preference mapping requires a complete set of observations, meaning the technique cannot be used to analyse trials based on incomplete block designs.

A simulation study was carried out to compare techniques for imputing missing values under various conditions. Sets of simulated preference data with different characteristics were constructed. Monte Carlo simulation was used to create missing observations in these sets; the imputation techniques were applied to the data; and the results of preference mapping based on the imputed data compared to those from the complete data set.

Convergence problems were found with two techniques. Analysis of variance revealed that effects on performance were dominated by the proportion of data missing, the level of noise in the data, and the size of the data set. Differences in performance among the three convergent imputation techniques were small; mean substitution is recommended, as it performed as well as more complex iterative techniques.

The results were broadly confirmed by a similar study on a genuine set of preference data.     

Study of the drying behaviour in peeled and unpeeled whole figs

Aim of this study was to estimate the effect of peeling on drying kinetics and effective diffusivity D_eff of figs (Ficus carica L. var. tsapela) during air-drying. For this purpose three temperatures (45, 55 and 65 °C) were tested. The Logarithmic model was chosen to describe the drying curves among seven drying models. The estimated drying constants were associated with the drying temperature by an Arrhenius type equation. The ratio of peeled to unpeeled relaxation times was found to be 0.54 ± 0.16. The D_eff of figs (peeled and unpeeled) was estimated by the method of slopes. The D_eff of the peeled figs was higher than this of the unpeeled figs presenting smaller differences as drying temperature was increased. This behaviour was attributed to the case hardening effect which is faster developed as the drying rate increases during high temperature drying.     

A fundamental approach and its experimental validation to simulate density as a function of moisture content during drying processes

Although several empirical models are available in the literature to predict density in solid matrices, only a very limited number of theoretical models have been reported. So far, no model considered the possible variation in the initial air volume existing at the beginning of the drying process. In this contribution, a theoretical model to predict bulk density of dried materials was built by considering two mechanisms that might occur during drying processes. These mechanisms are represented by collapse and shrinkage functions. The predictions obtained by this theoretical model were extensively validated with experimental data published by several independent groups for different food products dried with different technologies. In all these cases, the model gave excellent agreement with the experimental data regardless the topology of the curve bulk density versus moisture content. The model was also compared with other published models. The result of this comparison revealed that the errors resulting from the predictions obtained by the present model are among the smallest. Shrinkage and collapse functions were used to analyze the mechanisms by which bulk density varies during air-drying and freeze-drying. The model showed that both shrinkage and collapse phenomena are dramatically involved during air-drying. However, in the case of freeze-drying, no collapse is observed and only partial shrinkage is taking place. Hence, the present model can be used as a tool to predict the bulk density with excellent accuracy, to understand the dynamic mechanisms involved during drying. Moreover, this model can be incorporated to other models involving the variation of density as a function of moisture.