In this study, phenological and meteorological data have been used to interpret variations in a time series of regional average yields and quality parameters of malting barley (Hordeum vulgare L). The analyses were focused mainly on the grain filling period. Duration and occurrence of this development stage showed remarkable differences from year to year, as heading varied over more than four weeks and yellow ripeness over two weeks in the investigation period from 1974 to 1996. Yields above average were achieved only in years when grain filling duration exceeded 42 d. Protein concentrations below 10.5 % and grading percentages over 90 % required at least 44 d of grain filling. Temperature had the strongest influence on the length of grain filling, even though the calculated Growing Degree Days (base temperature 3 °C) were not absolutely constant. Mean daily temperature and relative air humidity were the best estimators with respect to grain yield. An optimum temperature range was found between 14 and 18 °C. Assuming a linear relationship, yield reductions between 4.1 and 5.7 % have been calculated for every 1 °C increase of the mean daily temperature. Relative air humidity was the best single estimator for grain protein concentration. The results of this study suggest that relative humidity during grain filling can be a more suitable parameter to describe drought stress effects than precipitation amounts from heading to yellow ripeness or from January 1 to yellow ripeness. 相似文献
Data from surveys should be weighted using expansion weights to avoid biased estimates for the inference population. Calculation of expansion weights is a stepwise procedure that can be thought of as allowing respondents to represent all eligibles from the population. Design will have an impact on the variance of the estimates. Furthermore, the impact may be to inflate or deflate the variance and is often variable-dependent. Accounting for the design in estimating the variance will require specialized analysis procedures and often specialized software. 相似文献
AIMS: To identify network measures with relevance to disease spread in a network of movements derived from the Department of Conservation (DOC) translocation records from 1970 to mid-2014, and to identify conservation sites that should be prioritised for surveillance activities and improvements to data collection to make the best use of network analysis techniques in the future.
METHODS: Data included the source and destination of translocated specimens, the species and the dates the translocations were expected to occur. The data were used to construct a directed, non-weighted network in which a translocation event represented a tie in the network. Network density, in-degree (movements entering a node of interest) and out-degree (movements leaving a node of interest) and reciprocity were calculated.
RESULTS: The data analysed consisted of 692 unique translocations between 307 sites, with the majority (518; 73%) being for birds. The constructed network for bird, reptile and frog translocations comprised 260 nodes, with 34/260 (13%) having two-way movements and 47/260 (18%) non-reciprocal movements. The median degree score (sum of in- and out-degree) was two (min 0, max 36) with a mean of 3.5 in a right skewed distribution. Most sites acted as receivers or senders of consignments with only a few having both high in- and high out-degree, and thus had characteristics that made them sites of interest for surveillance activities. These included the National Wildlife Centre at Mount Bruce, Tiritiri Matangi Island and Te Kakahu (Chalky Island).
CONCLUSIONS: The presence of linking sites that join larger clusters within the network creates the potential for rapid disease spread if a pathogen were to be introduced. The important sites that supply or receive specimens for translocations are already well recognised by those performing translocations in New Zealand, and this paper provides further information by quantifying their role within the network. 相似文献
The aim of this paper was to develop statistical models to estimate individual breed composition based on the previously proposed idea of regressing discrete random variables corresponding to counts of reference alleles of biallelic molecular markers located across the genome on the allele frequencies of each marker in the pure (base) breeds. Some of the existing regression‐based methods do not guarantee that estimators of breed composition will lie in the appropriate parameter space, and none of them account for uncertainty about allele frequencies in the pure breeds, that is, uncertainty about the design matrix. To overcome these limitations, we proposed two Bayesian generalized linear models. For each individual, both models assume that the counts of the reference allele at each marker locus follow independent Binomial distributions, use the logit link and pose a Dirichlet prior over the vector of regression coefficients (which corresponds to breed composition). This prior guarantees that point estimators of breed composition such as the posterior mean pertain to the appropriate space. The difference between these models is that model termed BIBI does not account for uncertainty about the design matrix, while model termed BIBI2 accounts for such an uncertainty by assigning independent Beta priors to the entries of this matrix. We implemented these models in a data set from the University of Florida's multibreed Angus‐Brahman population. Posterior means were used as point estimators of breed composition. In addition, the ordinary least squares estimator proposed by Kuehn et al. ( 2011 ) (OLSK) was also computed. BIBI and BIBI2 estimated breed composition more accurately than OLSK, and BIBI2 had a 7.69% improvement in accuracy as compared to BIBI. 相似文献
