Schjonning P.,University of Aarhus |
Lamande M.,University of Aarhus |
Munkholm L.J.,University of Aarhus |
Lyngvig H.S.,SEGES |
Soil and Tillage Research | Year: 2016
Compaction of the subsoil due to heavy traffic in moist and wet soil is widespread in modern agriculture. The objective of this study was to quantify the effects from realistic field traffic on soil penetration resistance and barley crop yield for three Luvisols developed from glacial till. Undisturbed soil cores were used for quantifying the precompression stress (σpc) of non-compacted soil. Tractor-trailer combinations for slurry application with wheel loads of ∼3, ∼6 and ∼8 Mg (treatments M3, M6, M8) were used for the experimental traffic in the spring at field-capacity. For one additional treatment (labelled M8-1), the soil was loaded only in the first year. A tricycle-like machine with a single pass of wide tyres each carrying ∼12 Mg (treatment S12) was included at one site. Traffic treatments were applied in a randomized block design with four replicates and with treatments repeated in four consecutive years (2010–2013). After two years of repeated experimental traffic, penetration resistance (PR) was measured to a depth of 1 m. The yield of a spring barley crop (Hordeum vulgare L.) was recorded in all four years of the experiment. The results did not support our hypothesis of σpc as a soil strength measure predicting resistance to subsoil compaction. The tyre inflation pressure and/or the mean ground pressure were the main predictors of PR in the upper soil layers. For deeper soil layers, PR correlated better to the wheel load. The number of wheel passes (M-treatments vs the S12 treatment) modified this general pattern, indicating a very strong impact of repeated wheel passes. Our data indicate that a single traffic event may mechanically weaken the soil without inducing major compaction but with influence on the effect of subsequent traffic even after as long an interval as a year (treatments M8 vs M8-1). Crop yields were much influenced by compaction of the plough layer. Due to the repeated wheel passes for the M-treatments, significant yield penalties were observed, while the single-pass treatment with 12 Mg wheel load in S12 did not have significant effects on crop yield. Our hypothesis of 3 Mg wheel load as an upper threshold for not inducing subsoil compaction was confirmed for the tractor-trailer treatments with repeated wheel passes but not supported for the single-pass machinery. The results call for further studies of the potential for carrying high loads using wide, low-pressure tyres by crab steering/dog-walk machinery. © 2016 Elsevier B.V.
Ranjitkar S.,University of Aarhus |
Karlsson A.H.,Copenhagen University |
Petersen M.A.,Copenhagen University |
Bredie W.L.P.,Copenhagen University |
And 2 more authors.
British Poultry Science | Year: 2016
Abstract: Two experiments were carried out in parallel with male Ross 308 broilers over 37 d. An experiment with a total of 736 broilers was performed to study the effect of dietary inclusion of crimped kernel maize silage (CKMS) on broiler production and meat quality. Another study with 32 broilers was carried out from 21 to 25 d to investigate the inclusion of CKMS on nutrient digestibility. In both trials, 4 dietary treatments were used: wheat-based feed (WBF), maize-based feed (MBF), maize-based feed supplemented with 15% CKMS (CKMS-15) and maize-based feed supplemented with 30% CKMS (CKMS-30). Compared with MBF, the dry matter (DM) intakes of broilers receiving CKMS-15 and CKMS-30, respectively, were numerically 7.5 and 6.2% higher and feed conversion ratio 6 and 12% poorer (significant for 30% CKMS), although there were no significant differences in AME content between the three diets. At 37 d, the body weight of birds receiving 15% CKMS was similar to birds fed with MBF. However, the inclusion of 30% CKMS decreased broiler growth. Dietary supplementation with CKMS significantly reduced the apparent digestibility of phosphorus. The fat digestibility was significantly lower for CKMS-30 than for the other three diets. Broiler mortality decreased significantly when CKMS was added to the diet. The consumption of drinking water was significantly lower in all maize-based diets as compared to WBF and was lowest in broilers fed with CKMS-30. An improved litter quality in terms of DM content and a lower frequency of foot pad lesions was observed with broilers supplemented with both dietary levels of CKMS. The addition of CKMS to maize-based diets increased juiciness, tenderness and crumbliness of the meat. In conclusion, the dietary supplementation of 15% CKMS had no negative effect on broiler growth and positively influenced bird welfare in terms of mortality and foot pad health. Therefore, the addition of 15% CKMS to maize-based diets is considered an advantageous feeding strategy in broiler production. © 2016 British Poultry Science Ltd.
Ostergaard S.,University of Aarhus |
Ettema J.F.,University of Aarhus |
Hjorto L.,SEGES |
Pedersen J.,SEGES |
And 2 more authors.
Livestock Science | Year: 2016
It has been a challenge to avoid double counting when economic values (EV) of traits are derived for breeding goal traits when using stochastic herd simulation models. In this study multiple regression and model building with mediator variables representing other traits in the breeding goal were evaluated to avoid double counting. EV were derived from data simulated with the SimHerd dairy herd simulation model. Scenarios were simulated to represent dairy herds with low and high levels of metritis and cow mortality. The simulated data was analyzed statistically with the economic net return per cow-year as the dependent variable and either the incidences of metritis or the incidence of cow mortality as the independent variables. In the model with metritis we corrected for mediator variables representing the direct effects of metritis on milk yield, fertility and occurrence of other diseases. The EV was estimated as the marginal change in economic net return in response to a change in the trait of interest. To avoid the multiple regression models to correct the EV for structural herd effects (changes in distribution of parities and lactation stages) we used a single animal based indicator variable for each trait of interest, such as incidence rate of cow mortality 1-100 DIM in multiparous cows.The EV value of improving the trait 'incidence rate of metritis 1-100 DIM in multiparous cows' by 0.01 was estimated to be €0.93. The importance of avoiding double counting was demonstrated as the EV of metritis was overestimated by 82% when no mediator variables were included in the multiple regression analysis. And by ignoring structural herd effects for the EV of metritis we demonstrated an underestimation in the order of 9%. Further pitfall of underestimation was demonstrated for EV of cow mortality.The EV of improving the trait 'incidence rate of cow mortality 1-100 DIM in multiparous cows' by 0.01 was estimated to be €46.4. Correcting for the independent variation in mortality between simulation replicates within the individual scenarios was found to be important.The results of this study suggests a new method for designing simulation experiments and analyzing simulated herd effects for estimation of EV of traits in a breeding goal. This deals with a number of previous and new concerns of how to correct for double counting and at the same time still include the structural herd effects. © 2016 Elsevier B.V.
Kristensen T.,University of Aarhus |
Aaes O.,SEGES |
Weisbjerg M.R.,University of Aarhus
Livestock Science | Year: 2015
Cattle production during the last century has changed dramatically in Western Europe, including Denmark, with a steady increase in production per animal and in herd and farm size. The effect of these changes on total production, herd efficiency, surplus of nitrogen (N) at herd and farm level and emission of greenhouse gases (GHG) per kg product has been evaluated for the Danish dairy cattle sector based on historic information. Typical farms representing the average situation for Danish dairy cattle farms and land required for feed supply was modeled for the situation in: (A) 1920 - representing a local-based production, (B) 1950 - representing a period with emerging mechanization and introduction of new technologies and a more global market, (C) 1980 - representing a period with heavy use of external resources like fertilizer and feed protein and (D) 2010 - today with focus on balancing production and risk of environmental damage. In A, B and C, other livestock such as pigs and hens also played a role, while the dairy farm in 2010 only had cattle. In 1920 and 1950 the farm was based on 7-8 dairy cows producing typically 1800-3400kg energy-corrected milk (ECM) per cow annually and fed primarily on pasture and hay, only to a limited extent supplemented with imported protein. In 1980 the herd size had increased to 20 dairy cows producing 5000kg ECM each, and feeding was with silage instead of hay, but still included grazing and there was a larger proportion of imported feed. In 2010 the herd had increased to 134 dairy cows producing 9000kg ECM per cow and fed indoors all year. During this period net energy used for milk and meat in % of total intake and land use per 1000kg of milk has steadily decreased as a consequence of higher milk yield per cow and higher yields of forage per ha. In opposition, the utilization of N in the herd, while increasing from 1920 to 1950 and to 2010 showed a drop in the 1980 system, where also the environmental N surplus per ha farmland was highest (40; 65; 226; 148kg N per ha farmland in the respective periods). The lower N efficiency in 1980 also resulted in an increased GHG emission per kg milk than in the preceding and following periods (2.23; 1.38; 1.94; 1.20kg CO2-eq. per kg ECM in the respective periods). It is concluded that the biological and technical development has made it possible to reduce the environmental load of dairy production significantly, but that this requires a strong focus on nitrogen management at the farm level and production efficiency in the herd. © 2015 Elsevier B.V..
PubMed | NAV Nordic Cattle Genetic Evaluation, University of Aarhus and Seges
Type: Journal Article | Journal: Journal of dairy science | Year: 2015
A bias in the trend of genomic estimated breeding values (GEBV) was observed in the Danish Jersey population where the trend of GEBV was smaller than the deregressed proofs for individuals in the validation population. This study attempted to improve the prediction reliability and reduce the bias of predicted genetic trend in Danish Jersey. The data consisted of 1,238 Danish Jersey bulls and 611,695 cows. All bulls were genotyped with the 54K chip, and 1,744 cows were genotyped with either 7K chips (1,157 individuals) or 54K chips (587 individuals). The trait used in the analysis was protein yield. All cows with EBV were used in a single-step approach. Deregressed proofs were used as the response variable. Four alternative approaches were compared with genomic best linear unbiased prediction (GBLUP) model with bulls in the reference data (GBLUPBull): (1) GBLUP with both bulls and genotyped cows in the reference data; (2) GBLUP including a year of birth effect; (3) GEBV from a GBLUP model that accounted for the difference of EBV between dams and maternal grandsires; and (4) using a single-step approach. The results indicated all 4 alternatives could reduce the bias of predicted genetic trend and that the single-step approach performed best. However, not all these approaches improved reliability or reduced inflation of GEBV. The reliability was 0.30 and regression coefficients of deregressed proofs on GEBV were 0.69 in the scenario GBLUPBull. When genotyped cows were included in the reference population, the regression coefficients decreased to 0.59 but the reliability increased to 0.35. If a year effect was included in the model, the prediction reliability decreased to 0.29 and the regression coefficient improved to 0.75. The method in which GEBV were adjusted for the difference between dam EBV and maternal grandsire EBV led to much lower regression coefficients though the reliability increased to 0.4. The single-step approach improved both the reliability, to 0.38 and regression coefficient to 0.78. Therefore, the bias in genetic trend was reduced. The results suggest that implementing the single-step approach is an effective way to improve genomic prediction in Danish Jersey cattle.
PubMed | University of Aarhus, Seges and Nordic Cattle Genetic Evaluation
Type: Journal Article | Journal: Journal of dairy science | Year: 2015
Including genotyped females in a reference population (RP) is an obvious way to increase the RP in genomic selection, especially for dairy breeds of limited population size. However, the incorporation of these females must be conducted cautiously because of the potential preferential treatment of the genotyped cows and lower reliabilities of phenotypes compared with the proven pseudo-phenotypes of bulls. Breeding organizations in Denmark, Finland, and Sweden have implemented a female-genotyping project with the possibility of genotyping entire herds using the low-density (LD) chip. In the present study, 5 scenarios for building an RP were investigated in the Nordic Jersey population: (1) bulls only, (2) bulls with females from the LD project, (3) bulls with females from the LD project plus non-LD project females genotyped before their first calving, (4) bulls with females from the LD project plus non-LD project females genotyped after their first calving, and (5) bulls with all genotyped females. The genomically enhanced breeding value (GEBV) was predicted for 8 traits in the Nordic total merit index through a genomic BLUP model using deregressed proof (DRP) as the response variable in all scenarios. In addition, (daughter) yield deviation and raw phenotypic data were studied as response variables for comparison with the DRP, using stature as a model trait. The validation population was formed using a cut-off birth year of 2005 based on the genotyped Nordic Jersey bulls with DRP. The average increment in reliability of the GEBV across the 8 traits investigated was 1.9 to 4.5 percentage points compared with using only bulls in the RP (scenario 1). The addition of all the genotyped females to the RP resulted in the highest gain in reliability (scenario 5), followed by scenario 3, scenario 2, and scenario 4. All scenarios led to inflated GEBV because the regression coefficients are less than 1. However, scenario 2 and scenario 3 led to less bias of genomic predictions than scenario 5, with regression coefficients showing less deviation from scenario 1. For the study on stature, the daughter yield deviation/daughter yield deviation performed slightly better than the DRP as the response variable in the genomic BLUP (GBLUP) model. Therefore, adding unselected females in the RP could significantly improve the reliabilities and tended to reduce the prediction bias compared with adding selectively genotyped females. Although the DRP has performed robustly so far, the use of raw data is recommended with a single-step model as an optimal solution for future genomic evaluations.
News Article | September 22, 2016
An international consortium of researchers from INRA (France), University of Copenhagen and SEGES (Denmark), BGI-Shenzhen (China) and NIFES (Norway) has now established the first catalogue of bacterial genes in the gut of pigs. This achievement is published in the latest issue of Nature Microbiology.
Mathiasen H.,Copenhagen University |
Bligaard J.,SEGES |
Esbjerg P.,Copenhagen University
Entomologia Experimentalis et Applicata | Year: 2015
The cabbage stem flea beetle, Psylliodes chrysocephala (L.) (Coleoptera: Chrysomelidae), is a major pest of winter oilseed rape. The larvae live throughout winter in leaf petioles and stems. Winter temperatures might play an important role in survival during winter and hence population dynamics, yet to what degree is unknown. This study investigates the effect of exposure time, cold acclimation, and larval stage on survival at -5 and -10 °C. Exposure time at -5 °C was 1, 2, 4, 8, 12, 16, and 20 days and 6, 12, 24, 36, 48, 72, 96, 120, and 144 h at -10 °C. Mortality increased with increasing exposure time and was significantly lower for cold-acclimated larvae. Estimated time until an expected mortality of 50% (LT50) and 90% (LT90) of larvae exposed to -5 °C was 7.4 and 9.6 days (non-acclimated) and 11.0 and 15.1 days (acclimated), respectively. Estimated LT50 for non-acclimated and acclimated larvae exposed to -10 °C was 32.6 and 70.5 h, respectively, and estimated LT90 66.8 and 132.2 h. Significant differences in mortality between larval stages were observed only at -5 °C. When exposed to -5 °C for 8 days, mortality of first and second instars was 81.2 and 51.3%, respectively. When exposed to -10 °C for 2 days, mortality of first and second instars was 70.5 and 76.1%. Data on winter temperatures in Denmark from 1990 to 2013 showed that larvae were rarely exposed to a number of continuous days at -5 or -10 °C causing a potential larval mortality of 50-90%. © 2015 The Netherlands Entomological Society.
Jensen L.M.,Copenhagen University |
Nielsen N.I.,SEGES |
Nadeau E.,Swedish University of Agricultural Sciences |
Markussen B.,Copenhagen University |
Norgaard P.,Copenhagen University
Livestock Science | Year: 2015
The objective of this study was to evaluate the accuracy of five models predicting dry matter intake (DMI) in dairy cows fed total mixed ration (TMR). The five models were the North American model from NRC, and the Northern European models: NorFor (Denmark, Iceland, Norway, and Sweden), TDMI (Finland), Zom (the Netherlands), and Gruber (Austria, Germany, Switzerland).The evaluated models represent different approaches to predict DMI. One approach uses only animal characteristics; a second uses the interaction between animal and dietary characteristics, and a third uses no production characteristics, such as body weight or milk yield. These different modelling approaches results in very different substitution rates, where only two of the models demonstrate direct or indirect relation to concentrate allocation. Accuracy of DMI prediction was evaluated by mean square prediction error (MSPE), root mean square prediction error (RMSPE), together with the decomposition of error into error of central tendency (ECT), error of regression (ER), and error due to disturbance (ED). The evaluation was performed on data from 12 Scandinavian production experiments with a total of 917 lactating dairy cows in 94 treatment means. The NorFor model was evaluated on only 9 of the experiments as 3 experiments had been used in the development of this model.The five models predicted DMI in groups of dairy cows fed TMR with RMSPE ranging between 1.2. kg dry matter (DM) per day for the Gruber model to 3.2. kg DM per day for the Zom model. Evaluated across the experiment the ECT and the ER ranged between 0.3% and 65% and between 3% and 38% of MSPE, respectively. Error associated to ED ranged between 31% and 93% of MSPE. When all five models were evaluated for prediction of DMI both across and within experiments, results revealed that all five models predicted differences between diets within experiments better than differences across experiments. The Gruber model, which predicted DMI most accurately did so due to its negligible systematic error (ECT, ER) resulting in 93% of the error located in ED. © 2015 Elsevier B.V.
PubMed | SEGES, Copenhagen University and Technical University of Denmark
Type: | Journal: Frontiers in veterinary science | Year: 2016
We describe a new mechanistic bioeconomic model for simulating the spread of