Endocrine correlates of gender and throat coloration in the southern ground-hornbill (Bucorvus leadbeateri)

The southern ground-hornbill (SGH) is a cooperatively breeding bird endemic to eastern and southern Africa, but is endangered in its southern distributional range. The national conservation restoration program harvests redundant chicks for captive breeding and reintroduction; with sexing and social grouping of the species evaluated by throat-skin coloration, with adult males displaying a completely red color compared to dark blue within the red observed in adult females. However, recent findings indicate that dominant and subordinate adult males exhibit patches of blue throat-skin. To optimize SGH management practices, it is vital to determine the role of red and blue coloration, as well as the possible drivers thereof. As a prerequisite, an enzyme immunoassay for monitoring fecal androgen metabolite (fAM) concentrations in SGH was established. Following this, fresh fecal samples were collected from 78 SGH, of various demographics and origin, across 12 captive institutions, to determine whether fAM concentrations differ between blue (B), partially blue (sB), and fully red (R) throat-skin colored SGH. Furthermore, fAM concentrations were compared between males housed in different social groups of different age and sex classes. Individual median fAM concentrations of B, sB, and R adult males did not differ significantly but were considerably higher in B and sB males compared to R males. Social dynamics within captivity, for example, dominance, played no role as a driver of male gonadal activity or throat skin coloration. The results of the study indicate that androgens and apparent social dynamics are not primary determinants of throat coloration in male SGH.     

Model predicting dynamics of biomass, structure and digestibility of herbage in managed permanent pastures. 2. Model evaluation

A mechanistic model, simulating the dynamics of production, structure and digestibility of managed permanent pastures, was developed. Its evaluation consisted of (i) studying model response to a range of grassland communities, cutting frequencies and site characteristics, and (ii) testing the model against experimental data, focusing on biomass accumulation and digestibility during three different cutting cycles, herbage production under a frequent cutting regime, and sward dynamics during the winter. The model realistically predicted the dynamics of biomass, structure and digestibility of herbage for various communities of permanent pastures, in different sites and under different management conditions for upland areas of the Auvergne region in France. The predicted responses to environmental conditions and cutting regimes were close to field observations and experimental results. Although the model successfully predicted the dynamics of average herbage production, it lacked precision in predicting the low biomass production observed in relation to the weather conditions found in a few specific years. The model was able to predict the dynamics of the sward during winter and is, therefore, fit for producing multiple‐year simulations. To improve the prediction of variability of biomass production and to predict the medium‐ to long‐term dynamics of permanent pastures, the model could be refined by adding seasonal and multiple‐year variation in nitrogen availability and in the proportion of grass functional groups in the grassland community.     

Differentiating between analytical and diagnostic performance evaluation with a focus on the method comparison study and identification of bias

Prior to introduction of a new method to the diagnostic laboratory, analytical performance must be validated to ensure operation within the manufacturer's specifications and/or within predetermined quality requirements. In addition, the new method may require diagnostic performance assessment to ensure it differentiates between diseased and nondiseased individuals as intended. These 2 phases of assessment, while complementary, are not equivalent and require a different set of experiments, statistical analyses, and interpretation. Studies of analytical performance typically include a method comparison experiment, the purpose of which is to identify bias (inaccuracy) of the “test” (or “index”) method (new method) relative to a “comparative method” (established method). Analysis of method comparison data is facilitated by commercial software programs that present the statistical significance of identified bias; however, the clinical relevance of any bias also should be considered. Studies of diagnostic performance should not be pursued until analytical performance is fully characterized and may not be required for well‐established tests or for those for which results are nonspecific (ie, not referable to a specific disease or condition). Diagnostic performance assessment may include assessment of sensitivity, specificity, predictive values, odds ratios, and/or likelihood ratios. The purpose of this review is to clarify differences between the assessment of analytical and diagnostic performance, and to explore the method comparison study and bias assessment from a perspective not addressed in prior veterinary articles.     

Modelling genetic evaluation for dressage in Pura Raza Español horses with focus on the rider effect

The most popular use of the Pura Raza Español horse in sport is for dressage competitions. Tests on young sport horses were first established in 2004 in Spain to collect data for the genetic evaluation of this breed's suitability for dressage. The aim of this study was to compare eight different models to find out the most appropriate way to include the rider in the genetic evaluation of dressage. A progressive removal of systematic effects from model was also analysed. A total of 8867 performance records collected between 2004 and 2011 from 1234 horses aged between 4 and 6 years old were used. The final score in the dressage test was used as the performance trait. The pedigree matrix contained 8487 individuals. A BLUP animal model was applied using a Bayesian approach with TM software. The horse's age, gender, travelling time, training level, stud of birth and event were included as systematic effects in all the models. Apart from the animal and residual effects that were present in all models, different models were compared combining random effects such as the rider, match (i.e. rider–horse interaction) and permanent environmental effects. A cross‐validation approach was used to evaluate the models' prediction ability. The best model included the permanent environmental, rider and match random effects. As far as systematic effects are concerned, the event or the stud of birth was essential effects needed to fit the data.     

4U-1400型马铃薯联合收获机的设计

针对国内马铃薯收获依靠人工或小型挖掘机效率低、劳动强度大等问题,设计了4U-1400型马铃薯联合收获机。收获机主要由挖掘装置、土薯分离装置、茎秆分离装置、垂直提升装置、装袋装置、传动系统、机架以及行走装置等部分组成,结构紧凑。通过运动学分析和试验,确定了各装置的关键参数。运用Solidworks软件绘制虚拟样机,进行模型验证,各零部件之间不存在干涉现象。该机可一次性完成2行马铃薯的挖掘、土薯分离、薯秧、杂草和残膜分离、垂直提升以及装袋等工序,克服了马铃薯收获机装袋技术难题,提高了生产效率。     

CottonPlus模型在黄淮海棉区的验证--以河北曲周县为例

利用1996～1998年在河北曲周实验站进行的实验,对CottonPlus棉花模拟模型进行了全面的验证.结果表明,通过校正品种参数和土壤参数,CottonPlus模型基本上可以模拟黄淮海棉区中熟品种中棉所12、中早熟品种国试6号和早熟品种中棉所16的生长发育和产量形成过程,并针对有关问题提出了进一步修改的建议.     

Genome-wide indel markers shared by diverse Asian rice cultivars compared to Japanese rice cultivar ‘Koshihikari’

Insertion-deletion (indel) polymorphisms, such as simple sequence repeats, have been widely used as DNA markers to identify QTLs and genes and to facilitate rice breeding. Recently, next-generation sequencing has produced deep sequences that allow genome-wide detection of indels. These polymorphisms can potentially be used to develop high-accuracy polymerase chain reaction (PCR)-based markers. Here, re-sequencing of 5 indica, 2 aus, and 3 tropical japonica cultivars and Japanese elite cultivar ‘Koshihikari’ was performed to extract regions containing large indels (10–51 bp) shared by diverse cultivars. To design indel markers for the discrimination of genomic regions between ‘Koshihikari’ and other diverse cultivars, we subtracted the indel regions detected in ‘Koshihikari’ from those shared in other cultivars. Two sets of indel markers, KNJ8-indel (shared in eight or more cultivars, including ‘Khao Nam Jen’ as a representative tropical japonica cultivar) and C5-indel (shared in five to eight cultivars), were established, with 915 and 9,899 indel regions, respectively. Validation of the two marker sets by using 23 diverse cultivars showed a high PCR success rate (≥95%) for 83.3% of the KNJ8-indel markers and 73.9% of the C5-indel markers. The marker sets will therefore be useful for the effective breeding of Japanese rice cultivars.     

QTL analyses of complex traits with cross validation, bootstrapping and other biometric methods

With the development of molecular markers, dissection of complex quantitative traits by mapping the underlying genetic factors has become a major research area in plant breeding. Here, we report results from a vast QTL mapping experiment in maize with testcrosses of N= 976 F_4:5 lines evaluated in E= 16 environments. Although the number of detected QTL confirmed the infinitesimal model of quantitative genetics (e.g., 30 QTL detected with LOD ≥ 2.5 for plant height, explaining p= 61% of the genetic variance), cross validation (CV) still revealed an upward bias of about 10% in p. With smaller values of N (122, 244, 488) and E (2, 4), the number of detected QTL decreased, but the estimates of p remained almost the same due to a tremendous increase in the bias. This illustrates that QTL effects obtained from smaller sample sizes are usually highly inflated, leading to an overly optimistic assessment of the prospects of MAS. Moreover, inferences about the genetic architecture (number of QTL and their effects) of complex traits cannot be achieved reliably with smaller sample sizes. Based on simulations, we conclude that CV and one method of bootstrapping (BS) performed well with regard to yielding realistic estimates of p. In addition, we briefly review progress in new biometric methods and approaches to QTL mapping in plants including Bayesian methods that show great promise to overcome the present limitations of QTL mapping. This revised version was published online in July 2006 with corrections to the Cover Date.     

Linear and Poisson models for genetic evaluation of tick resistance in cross‐bred Hereford x Nellore cattle

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross‐bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick‐resistant animals.