DON content in oat grains in Norway related to weather conditions at different growth stages

High concentrations of the mycotoxin deoxynivalenol (DON), produced by Fusarium graminearum have occurred frequently in Norwegian oats recently. Early prediction of DON levels is important for farmers, authorities and the Cereal Industry. In this study, the main weather factors influencing mycotoxin accumulation were identified and two models to predict the risk of DON in oat grains in Norway were developed: (1) as a warning system for farmers to decide if and when to treat with fungicide, and (2) for authorities and industry to use at harvest to identify potential food safety problems. Oat grain samples from farmers’ fields were collected together with weather data (2004–2013). A mathematical model was developed and used to estimate phenology windows of growth stages in oats (tillering, flowering etc.). Weather summarisations were then calculated within these windows, and the Spearman rank correlation factor calculated between DON-contamination in oats at harvest and the weather summarisations for each phenological window. DON contamination was most clearly associated with the weather conditions around flowering and close to harvest. Warm, rainy and humid weather during and around flowering increased the risk of DON accumulation in oats, as did dry periods during germination/seedling growth and tillering. Prior to harvest, warm and humid weather conditions followed by cool and dry conditions were associated with a decreased risk of DON accumulation. A prediction model, including only pre-flowering weather conditions, adequately forecasted risk of DON contamination in oat, and can aid in decisions about fungicide treatments.     

Bull Selection in MOET Nucleus Breeding Schemes with Limited Testing Capacity

Centralized multiple ovulation and embryo transfer (MOET) nucleus breeding schemes with limited testing capacity were compared with a conventional artificial insemination (AI) scheme using a simulation. The donor cows were selected after their first lactation. In the hybrid MOET schemes, bulls were progeny tested in the AI population. In comparison, two other schemes used nucleus-born adult bulls only. The best hybrid scheme gave 77% or 40% better genetic response in milk protein yield than that estimated in the national AI scheme when the assumed genetic progress in the AI scheme was low or high, respectively. The best scheme had acceptable coefficients of variation of genetic response, although the rate of inbreeding was 2.5 times higher than in the national AI scheme. The schemes using adult bulls had lower responses and higher rates of inbreeding than the hybrid schemes. The outstanding performance of the hybrid schemes was due to more successful cow selection path than in a conventional AI scheme. A high accuracy of selection of bulls was also important.     

Change in genetic correlation due to selection using animal model evaluation

SUMMARY: Monte Carlo simulation and analytical calculations were used to study the effect of selection on genetic correlation between two traits. The simulated breeding program was based on a closed adult multiple ovulation and embryo transfer nucleus breeding scheme. Selection was on an index calculated using multi-trait animal model (AM). Analytical formulae applicable to any evaluation method were derived to predict change in genetic (co)variance due to selection under multi-trait selection using different evaluation methods. Two formulae were investigated, one assuming phenotypic selection and the other based on a recursive two-generation AM selection index. The recursive AM method approximated information due to relatives by a relationship matrix of two generations. Genetic correlation after selection was compared under different levels of initial genetic and environmental correlations with two different selection criteria. Changes in genetic correlation were similar in simulation and analytical predictions. After one round of selection the recursive AM method and the simulation gave similar predictions while the phenotypic selection predicted usually more change in genetic correlation. After several rounds of selection both analytical formulae predicted more change in genetic correlation than the simulation. ZUSAMMENFASSUNG: ?nderung der genetischen Korrelation bei Selektion mit einem Tiermodell Der Selektionseffekt auf die genetische Korrelation zwischen zwei Merkmalen wurde mit Hilfe von Monte Carlo-Simulation und analytischen Berechnungen untersucht. Ein geschlossener Adulter - MOET (Multiple Ovulation and Embryo Transfer) Zuchtplan wurde simuliert. Die Selektion gründete sich auf einen Index, der die Zuchtwertsch?tzung des Mehrmerkmals-Tiermodells benutzte. Analytische Formeln für die Voraussage der ?nderung der genetischen (Ko)varianz unter multivariate Selektion für verschiedene Zuchtwertsch?tzungsmethode wurden deduziert. Zwei Formeln wurden studiert, die erste nahm ph?notypische Auswahl an und die andere gründete sich auf ein wiederholte Mehrmerkmals-Tiermodell von zwei Generationen. Das wiederholte Mehrmerkmals-Tiermodell approximierte die Information aus den Verwandten mit Hilfe einer Verwandtschaftsmatrix der zwei Generationen. Die genetische Korrelation nach der Selektion aus der Simulation und den analytischen Formeln wurde mit verschiedenen reellen genetischen und umweltbedingten Korrelationen mit zwei Selektionskriterien verglichen. Sie ?nderte sich ?hnlich bei Simulation und analytischen Formeln. Nach einem Selektionszyklus kamen das wiederholte Mehrmerkmals-Tiermodell und die Simulation zu gleichen Voraussagen, aber die ph?notypische Selektion sagte mehr ?nderung voraus. Nach mehreren selektierten Generationen sagten die beiden analytischen Formeln mehr ?nderung in der genetischen Korrelation voraus als die Simulation. RéSUMé: Changement de corrélation génétique du à la sélection en utilisant une évaluation de type modèle animal Une simulation Monte Carlo et des calculs analytiques ont été utilisés pour étudier l'effet de la sélection sur la corrélation génétique entre deux caractères. Le programme de sélection simulé a été basé sur le schéma d'un noyau de sélection adulte et fermé avec superovulation et transfert embryonnaire. La sélection portait sur un indice calculé à partir d'un modèle animal multicaractères (AM). Des formules analytiques applicables à n'importe quelle méthode d'évaluation ont été développées pour prédire le changement de (co)variance génétique du à la sélection multicaractères en utilisant différentes méthodes d'évaluation. Deux formules ont été étudiées, l'une supposant une sélection phénotypique et l'autre basée sur un index de sélection de type AM sur deux générations. La méthode AM récurrente prenait en compte l'information des apparentés de manière approximative à travers la matrice de parenté sur deux générations. La corrélation génétique après sélection a été comparée à différents niveaux de corrélations génétique et environnementale pour deux critères de sélection différents. Les changements de corrélation génétique étaient similaires dans les simulations et les prédictions analytiques. Après un cycle de sélection, la méthode récurrente AM et la simulation donnaient les prédictions similaires alors que la sélection phénotypique prédisait habituellement des changements de corrélations génétiques plus importants. Après plusieurs cycles de sélection, les deux formules analytiques prédisaient des changements de corrélation plus importants que la simulation. RéSUMé: Cambio en la correlación genética debido a selección usando evaluaciones con modelo animal Se estudió el efecto de la selección sobre la correlación genética entre dos caracteres utilizando simulación de Monte Carlo y cálculos analíticos. El esquema de selección simulado estuvo basado en un núcleo adulto y cerrado de ovulación multiple y transferencia de embriones. El criterio de selección fue un indice calculado a partir de un modelo animal multicarácter (AM). Se derivaron fórmulas analíticas aplicables a cualquier método de evaluación para predecir cambios debidos a selección en las (co)varianzas genéticas bajo selección multicarácter usando distintos métodos de valoración. Se investigaron dos fórmulas, una que asumía selección fenotípica y la otra basada en un índice de selección AM recurrente con dos generaciones. El método AM recurrente aproximaba la información de parientes a través de una matriz de relaciones aditivas que contemplaba dos generaciones. La correlación genética tras la selección fue comparada bajo distintos niveles de correlación genética y ambiental iniciales con dos criterios de selección diferentes. Los cambios en correlatión genética fueron similares en las predicciones analíticas y con simulación. Tras un ciclo de selección, el método AM recurrente y la simulación produjeron predicciones similares mientras que la selección fenotípica predijo, generalmente, más cambio en la correlación genética. Después de varios ciclos de selección, las dos fórmulas analíticas predijeron más cambios en la correlación genética que la simulación.     

Breeding for better eye health in Finnish blue fox (Vulpes lagopus)

The frequency of eye infections in the Finnish blue fox population has increased during the past decade. Eye infection may incur economic losses to producers due to reduced selection intensity, but ethical aspects need to be considered as well because eye infection can be quite painful and reduce animal well‐being. The purpose of this study was to determine the potential for genetic selection against susceptibility to eye infection. The data were collected from 2076 blue foxes at the MTT fur animal research station. Genetic parameters were estimated using single‐ and multiple‐trait animal models. The heritability estimate for eye infection was analysed as a binary trait (EYE) and was moderate (0.24 ± 0.07). EYE had a moderate antagonistic genetic correlation (–0.49 ± 0.20) with grading density (thick underfur). The genetic correlation of EYE with grading size or body condition score was estimated without precision, but all size traits had a low antagonistic phenotypic correlation with EYE. Our results suggest that there is genetic variance in susceptibility to EYE, indicating that eye health can be improved through selection. The current recommendation is that the sick animals should be culled immediately. If more efficient selection is needed, the selection index and multiple‐trait animal models can be applied in breeding for better eye health.     

Effect of Estradiol and Progesterone on Metabolic Biomarkers in Healthy Bitches

The aim of this study was to evaluate the possible association between hormonal changes that occur during oestrus and biomarkers related with glucose metabolism (glucose and insulin), lipid metabolism (lipidic profile and BChE) and adipokines (adiponectin and ghrelin) in healthy bitches. For this purpose, we measured these analytes in serum of bitches, at two times: before (T1) and after (T2) the LH peak that were established according to progesterone concentrations. Increased levels of total cholesterol (p < 0.01), high density lipoprotein cholesterol (HDL‐C) (p < 0.01), low density lipoprotein cholesterol (LDL‐C) (p < 0.01), adiponectin (p < 0.01) and ghrelin (p < 0.05) were observed at T2 in comparison with T1. No statistically significant changes were observed in serum glucose, insulin, homoeostasis model assessment for insulin sensitivity (HOMA), triglycerides and BChE. When all data of T1 and T2 were pooled, serum adiponectin showed positive correlation with progesterone (r = 0.353; p = 0.022) and HDL‐C (r = 0.307; p = 0.048), and negative with insulin (r = ?0.429; p = 0.005), HOMA (r = ?0.446; p = 0.003) and BChE (r = ?0.522; p < 0.001). Ghrelin showed negative correlation with estradiol (r = ?0.701; p = 0.004). BChE was negatively correlated with estradiol (r = ?0.441; p = 0.018) and glucose (r = ?0.343; p = 0.028), and positively with insulin (r = 0.460; p = 0.003) and HOMA (r = 0.505; p < 0.001). In conclusion, changes in metabolic biomarkers occur in bitches after LH peak, characterized by increased lipids (total cholesterol, HDL cholesterol and LDL cholesterol) without changes in BChE activity, and increased adiponectin and ghrelin concentrations, without significant changes in glucose and insulin.     

A pulsar, the heliosphere, and pioneer 10: probable mimicking of a planet of PSR B1257+12 by solar rotation

Doppler data generated with the Pioneer 10 spacecraft's radio carrier wave between 1987 and 1995 show a 25.3-day periodicity which is related to the solar rotation. The timing data of the pulsar PSR B1257+12 also show a periodicity of 25.34 days, which has been explained as a signature of the pulsar's barycentric motion in response to the existence of a small moon-like object. However, because PSR B1257+12 is located close to the ecliptic and because the timing variations are in the range of microseconds, it is likely that the pulsar signal is affected by the same mechanism acting on the Pioneer 10 Doppler data. Hence, the hypothesized inner planet around PSR B1257+12 is probably an artifact of the heliosphere.     

A model strategy for the simulation of chlorinated hydrocarbon distributions in the global environment

A model strategy that can be used for the study of global distributions of chlorinated hydrocarbons in the environment is presented. In this first approach the number of compartments and processes are kept on a minimum level by only considering the atmosphere, ocean and soil. Important processes are simulated or replaced by simple parameterizations, while processes believed to be less important are temporally omitted. The transport in the atmosphere is simulated by a simple two-dimensional zonally averaged model with a rather coarse resolution of 6 equally spaced latitude zones and 4 vertical layers. The soil is included in the model by dividing the continents into the same latitude zones as the atmosphere, and the land area in each zone into an uncultivated part and a cultivated part where pesticides may be incorporated. A model for tracer transport in the ocean which combines the features of the box and box-diffusion models has been modified for use in this study. Material is exchanged between the compartments by the processes believed to be most important in the real environment. The model is tested by simulating the life cycle of the α and γ isomers of hexachlorocyclohexane in the environment. The emissions of the two isomers are estimated from the total world consumption of HCH, and it is assumed that a fraction of 50% is lost to the atmosphere for long range transport during application or during the first days therefore. Comparison with observations indicates that in spite of the many assumptions and uncertain parameters the model is able to reproduce the atmospheric and oceanic concentration levels of εHCH. The HCH simulation indicates that the presented model strategy is usable when the aim is to increase the understanding of chlorinated hydrocarbons in the global environment. For the prediction of concentration levels in specific areas on the other hand, the present model strategy does not apply. The resolution of the model is too coarse and the simplifications are too extensive for such estimates to be valid.