Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model     

Hooten  Mevin B.  Larsen  David R.  Wikle  Christopher K. 《Landscape Ecology》2003,18(5):487-502

Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.This revised version was published online in May 2005 with corrections to the Cover Date.  相似文献   

基于MCMC模拟的MGPD模型及其在地质灾害风险度量中的应用     

欧阳迪飞  杨扬  甘柳  李应求 《湖南农业大学学报(自然科学版)》2015,(2):101-106

基于马尔科夫链蒙特卡洛(简记为MCMC)模拟的参数贝叶斯估计,对改进的广义帕累托分布(简记为MGPD)模型进行了优化,并利用该模型得到了地质灾害损失的在险损失值(简记为VaR)和条件损失值(简记为CVaR).以湖南娄底市地质灾害损失数据进行实证分析及模型适应性检验,结果表明:优化后的模型不仅具有很好的极值数据描述能力,而且具有较强的适用性.  相似文献   

基于信号博弈的阳澄湖大闸蟹绿色标签市场应用分析   总被引：2，自引：0，他引：2  

吴昊 《黑龙江农业科学》2011,(6):108-111

水产品绿色标签对消费者来说是高质量的信号,对卖家来说则是卖出高价的资本.但是欺诈行为的存在损害了消费者和其他卖家的利益,扰乱了市场秩序.以阳澄湖大闸蟹为例,通过信号博彝理论,对螃蟹市场中关卖双方的消费行为进行博彝分析,得到了精炼贝叶斯Nash均衡.  相似文献   

Identification of potential genomic regions for egg weight by a haplotype-based genome-wide association study using Bayesian methods     

A. H. Khaltabadi Farahani  H. Mohammadi  M. H. Moradi  H. A. Ghasemi 《British poultry science》2020,61(3):251-257

ABSTRACT

1. Theoretically, haplotype blocks might be a more suitable alternative to SNP genotypes as they are usually better at capturing multi-allelic QTL effects, compared to individual SNP genotypes in genome-wide association studies. The objectives of this study were to identify genomic regions related to egg weight traits by Bayesian methods (BayesA, BayesB, and BayesN) that fit fixed-length haplotypes using GenSel software.

2. Genotypes at 294,705 SNPs, that were common on a 600K Affymetrix chip, were phased for an egg-laying hen population of 1,063 birds. Recorded traits included first egg weight (FEW) and average egg weight at 28, 36, 56, 66, 72 and 80 weeks of age.

2. Fitting 1Mb haplotypes from BayesB resulted in the highest proportion of genetic variance explained for the egg weight traits. Based on the trait, the genetic variance explained by each marker ranged from 27% to 76%.

3. Different haplotype windows associated with egg weight traits only explained a small percentage of the genetic variance.

4. The top one 1-Mb window on GGA1 explained approximately 4.05% of total genetic variance for the FEW. Candidate genes, including PRKAR2B, HMGA2, LEMD3, GRIP1, EHBP1, MAP3K7, and MYH were identified for egg weight traits.

5. Several genomic regions, potentially associated with egg weight traits, were identified, some of which overlapped with known genes and previously reported QTL regions for egg production traits.  相似文献   

基于模糊神经网络的智能温室环境控制方案     

彭辉  曾碧 《农机化研究》2017,(6):43-49

针对农业温室环境的精确建模和控制问题,提出了一种基于模糊神经网络的智能控制方案。首先,在考虑室内外环境因素下,构建一个有效的温室环境数学模型,获得通风量、喷雾量和加热量的微分表达式;然后,利用一种自适应模糊神经推理系统(ANFIS),以温度和湿度差作为输入,通过神经网络自学习和模糊推理获得控制输出;最后,通过遗传算法优化控制器的输出比例因子,提高控制响应速度和稳定性。实验结果表明:该方案能够快速且稳定地追踪环境设置值,具有很好的控制效果。  相似文献   

New Approaches to Modeling Methyl Jasmonate Effects on Pomegranate Quality during Postharvest Storage     

Mohammad Sayyari  Daniel Valero 《International Journal of Fruit Science》2017,17(4):374-390

Adaptive neuro fuzzy inference system (ANFIS) and genetic algorithm–artificial neural network (GA-ANN) models were used to predict the effect of methyl jasmonate (at three levels 0, 0.01, and 0.1 mM) and storage time (0, 14, 28, 42, 56, 70, and 84 days) on quality parameters and physiological changes of pomegranate fruits during storage. Methyl jasmonate reduced chilling injury and improved quality characteristics of pomegranates during postharvest storage. The GA-ANN and ANFIS were fed with two inputs of methyl jasmonate and storage time. The results showed that GA-ANN predictions agreed with experimental data and the GA-ANN with 14 neurons in one hidden layer can predict physiological changes and quality parameters of pomegranate (weight loss, pH, chilling injury index, ion leakage, ethylene, respiration, polyphenols, anthocyanins, and total antioxidant activity) with correlation coefficients equal to 0.87. The ANFIS model was trained by a hybrid method and agreement between experimental data and ANFIS predictions was significant (r = 0.90).  相似文献   

Bayesian estimation of diagnostic accuracy of a new bead-based antibody detection test to reveal Toxoplasma gondii infections in pig populations     

《Veterinary parasitology》2015,207(1-2):1-6

The success of a Toxoplasma gondii surveillance program in European pig production systems depends partly on the quality of the test to detect infection in the population. The test accuracy of a recently developed serological bead-based assay (BBA) was investigated earlier using sera from experimentally infected animals. In this study, the accuracy of the BBA was determined by the use of sera from animals from two field subpopulations. As no T. gondii infection information of these animals was available, test accuracy was determined through a Bayesian approach allowing for conditional dependency between BBA and an ELISA test. The priors for prevalence were based on available information from literature, whereas for specificity vague non-informative priors were used. Priors for sensitivity were based either on available information or specified as non-informative. Posterior estimates for BBA sensitivity and specificity were (mode) 0.855 (Bayesian 95% credibility interval (bCI) 0.702–0.960) and 0.913 (bCI 0.893–0.931), respectively. Comparing the results of BBA and ELISA, sensitivity was higher for the BBA while specificity was higher for ELISA. Alternative priors for the sensitivity affected posterior estimates for sensitivity of both BBA and ELISA, but not for specificity. Because the difference in prevalence between the two subpopulations is small, and the number of infected animals is small as well, the precision of the posterior estimates for sensitivity may be less accurate in comparison to the estimates for specificity. The estimated value for specificity of BBA is at least optimally defined for testing pigs from conventional and organic Dutch farms.  相似文献   

金融时间序列指标判别框架：以特质波动率为例     

汤胤  毛景慧 《湖南农业大学学报(自然科学版)》2016,(3):35-39

基于拐点集合判别的TBUD方法主要思路是分析拐点集合间的关系，并在高维空间进行划分，从而搭建判别模型，并将分析框架应用在特质波动率等若干指标上，利用实证数据得到结论。应用TBUD判别框架可以发现，特质波动率等指标无法对拐点集合进行清晰划分，因而并不具有预测能力。  相似文献   

A global sensitivity analysis of cultivar trait parameters in a sugarcane growth model for contrasting production environments in Queensland,Australia     

《European Journal of Agronomy》2017

New sugarcane cultivars are continuously developed to improve sugar industry productivity. Despite this sugarcane crop models such as the ‘Sugar’ module in the Agricultural Productions System sIMulator (APSIM-Sugar) have not been updated to reflect the most recent cultivars. The implications of misrepresenting cultivar parameters in APSIM-Sugar is difficult to judge as little research has been published on the likely values of these parameters and how uncertainty in parameter values may affect model outputs. A global sensitivity analysis can be used to better understand how cultivar parameters influence simulated yields. A Gaussian emulator was used to perform a global sensitivity analysis on simulated biomass and sucrose yield at harvest for two contrasting sugarcane-growing regions in Queensland, Australia. Biomass and sucrose yields were simulated for 42 years to identify inter-annual variability in output sensitivities to 10 parameters that represent physiological traits and can be used to simulated differences between sugarcane cultivars. Parameter main effect (S_i) and total effect (ST_i) sensitivity indices and emulator accuracy were calculated for all year-region-output combinations. When both regions were considered together parameters representing radiation use efficiency (rue), number of green leaves (green_leaf_no) and a conductance surrogate parameter (k_L) were the most influential parameters for simulated biomass in APSIM-Sugar. Simulated sucrose yield was most sensitive to rue, sucrose_fraction (representing the fraction of biomass partitioned as sucrose in the stem) and green_leaf_no. However, climate and soil differences between regions changed the level of influence cultivar parameters had on simulation outputs. Specifically, model outputs were more sensitive to changes in the transp_eff_cf and k_L parameters in the Burdekin region due to lower rainfall and poor simulated soil conditions. Collecting data on influential traits that are relatively simple to measure (e.g. number of green leaves) during cultivar development would greatly contribute to the simulation of new cultivars in crop models. Influential parameters that are difficult to measure directly such as transp_eff_cf and sucrose_fraction are ideal candidates for statistical calibration. Calibrating crop models either through direct observation or statistical calibration would allow crop modellers to better test how new cultivars will perform in a range of production environments.  相似文献   

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm     

Fernando Brito Lopes  Fernando Baldi  Ludmilla Costa Brunes  Marcos Fernando Oliveira e Costa  Eduardo da Costa Eifert  Guilherme Jordão Magalhães Rosa  Raysildo Barbosa Lobo  Cláudio Ulhoa Magnabosco 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2023,140(1):1-12

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.  相似文献