Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Swimming Performance and Oxygen Consumption as Non-lethal Indicators of Production Traits in Atlantic Salmon and Gilthead Seabream
    Palstra, Arjan P. ; Kals, Jeroen ; Böhm, Thijs ; Bastiaansen, John W.M. ; Komen, Hans - \ 2020
    Frontiers in Physiology 11 (2020). - ISSN 1664-042X
    aquaculture - feed conversion ratio - metabolic rate - selective breeding - starvation-refeeding - swim-tunnel respirometry

    The aim of this study was to investigate swimming performance and oxygen consumption as non−lethal indicator traits of production parameters in Atlantic salmon Salmo salar L. and Gilthead seabream Sparus aurata L. A total of 34 individual fish of each species were subjected to a series of experiments: (1) a critical swimming speed (Ucrit) test in a swim-gutter, followed by (2) two starvation-refeeding periods of 42 days, and (3) swimming performance experiments coupled to respirometry in swim-tunnels. Ucrit was assessed first to test it as a predictor trait. Starvation-refeeding traits included body weight; feed conversion ratio based on dry matter; residual feed intake; average daily weight gain and loss. Swim-tunnel respirometry provided oxygen consumption in rest and while swimming at the different speeds, optimal swim speed and minimal cost of transport (COT). After experiments, fish were dissected and measured for tissue weights and body composition in terms of dry matter, ash, fat, protein and moist, and energy content. The Ucrit test design was able to provide individual Ucrit values in high throughput manner. The residual Ucrit (RUcrit) should be considered in order to remove the size dependency of swimming performance. Most importantly, RUcrit predicted filet yield in both species. The minimal COT, the oxygen consumption when swimming at Uopt, added predictive value to the seabream model for feed intake.

    Optimizing design to estimate genetic correlations between environments with common environmental effects
    Lozano-Jaramillo, Maria ; Komen, Hans ; Wientjes, Yvonne C.J. ; Mulder, Han A. ; Bastiaansen, John W.M. - \ 2020
    Journal of Animal Science 98 (2020)2. - ISSN 0021-8812
    breeding programs - genetic correlation - genotype by environment interaction - population structure

    Breeding programs for different species aim to improve performance by testing members of full-sib (FS) and half-sib (HS) families in different environments. When genotypes respond differently to changes in the environment, this is defined as genotype by environment (G × E) interaction. The presence of common environmental effects within families generates covariance between siblings, and these effects should be taken into account when estimating a genetic correlation. Therefore, an optimal design should be established to accurately estimate the genetic correlation between environments in the presence of common environmental effects. We used stochastic simulation to find the optimal population structure using a combination of FS and HS groups with different levels of common environmental effects. Results show that in a population with a constant population size of 2,000 individuals per environment, ignoring common environmental effects when they are present in the population will lead to an upward bias in the estimated genetic correlation of on average 0.3 when the true genetic correlation is 0.5. When no common environmental effects are present in the population, the lowest standard error (SE) of the estimated genetic correlation was observed with a mating ratio of one dam per sire, and 10 offspring per sire per environment. When common environmental effects are present in the population and are included in the model, the lowest SE is obtained with mating ratios of at least 5 dams per sire and with a minimum number of 10 offspring per sire per environment. We recommend that studies that aim to estimate the magnitude of G × E in pigs, chicken, and fish should acknowledge the potential presence of common environmental effects and adjust the mating ratio accordingly.

    Modeling honey bee colonies in winter using a keller-segel model with a sign-changing chemotactic coefficient
    Bastiaansen, Robbin ; Doelman, Arjen ; Langevelde, Frank Van; Rottschafer, Vivi - \ 2020
    SIAM Journal on Applied Mathematics 80 (2020)2. - ISSN 0036-1399 - p. 839 - 863.
    Ecology - Spatial self-organization - Thermoregulation

    Thermoregulation in honey bee colonies during winter is thought to be self-organized. We added mortality of individual honey bees to an existing model of thermoregulation as an approach to model the elevated losses of bees that are reported worldwide. The aim of this analysis is to obtain a better fundamental understanding of the consequences of individual mortality during winter. This model resembles the well-known Keller-Segel model. In contrast to the often studied Keller-Segel models, our model includes a chemotactic coefficient of which the sign can change as honey bees have a preferred temperature: When the local temperature is too low, they move toward higher temperatures, whereas the opposite is true for too high temperatures. Our study shows that we can distinguish two states of the colony: One in which the colony size is above a certain critical number of bees in which the bees can keep the core temperature of the colony above the threshold temperature and one in which the core temperature drops below the critical threshold and the mortality of the bees increases dramatically, leading to a sudden death of the colony. This model behavior may help explain the globally observed honey bee colony losses during winter.

    Improving growth and survival of tilapia in brackish water
    Aththar, Farid ; Bastiaansen, J.W.M. ; Komen, J. - \ 2020
    In: Wias Annual Conference 2020 WIAS - p. 77 - 77.
    Global shrimp farming faces numerous problem related to environmental and climate change such as, disease outbreaks, rising of sea level and seawater intrusion. Those effects on shrimp farming are linked with livelihood security of small-scale shrimp farmers. In Indonesia,half a million households are involved directly in brackish water pond aquaculture producing mainly shrimp. Disease outbreaks in shrimp ponds have recurrently caused serious crop failures. As a result, many small-scale farmers face severe financial difficulties and are looking for alternative crops to secure their livelihoods. An economically promising alternative is to culture shrimp with tilapia in a so-called polyculture system. Salinity levels in shrimp ponds, however, vary greatly and cause large mortalities and poor growth in currently available strains of tilapia. What is needed is a strain of tilapia that has good growth and survival over a range of (fluctuating) salinities. For these traits, estimation of genetic parameters and accurate selection for salinity tolerance is needed. The starting material for research and breeding of salinity tolerance tilapia are available however the breeding program is needed. Objectives of the research are: 1) new fundamental knowledge about genetics of growth and survival under fluctuating salinities in tilapia, and 2) to develop an optimised breeding strategy to improve growth rate and survival of tilapia grown in brackish water ponds. There are several steps to reach the objectives: 1) obtain genetic parameters for growth rate and survival and calculate genotype by environment interaction of Nile tilapia in freshwater and brackish water, 2) obtain genetic parameter for tilapia reproduction, 3) identify physiological trait for salinity adaptation and 4) design an optimal breeding program for increased growth and survival in shrimp-tilapia systems. Results from the project are expected to allow the development of a sustainable breeding program for tilapia that supports an aquaculture production system that is accessible, affordable and applicable for farmers with brackish water ponds in Indonesia and elsewhere.
    Integrating selective breeding into commercial production of aquaculture species
    Gulzari, Benan ; Bastiaansen, J.W.M. ; Komen, J. - \ 2020
    In: Wias Annual Conference 2020 WIAS - p. 58 - 58.
    Family-based nucleus fish breeding programs are expensive operations. The cost of such fish breeding programs is not justified for many fish species cultured globally. An alternative to nucleus breeding programs is to integrate selective breeding into commercial aquaculture production. In integrated breeding programs the selection is performed on animals that are kept under commercial production circumstances using the data collected in the production environment.The objective of this PhD project is to understand the principles of and develop methods to optimise the design of integrated breeding programs for fish species.The first step is developing data collection strategies for economically important traitsdirectly from the commercial production environment to uniformly represent all individuals within the production system. Second step is developing precise and high-through put measurement techniques to phenotype large numbers of animals in the commercial environment in a fast and accurate way in combination with prediction of slaughter traits for alive fish (e.g. fillet yield) using computer vision. Third are methods for making a selection decision as soon as a fish is phenotyped by combining data collection, statistical analysis and selection of animals into one single step using computer vision and machine learning.Final step is designing and optimising an integrated breeding program, based on novel phenotyping and single-step selection techniques. Phenotypic data collection, imaging and genotyping of fish will be performed within the context of experiments in different EU projects. Throughout the PhD project, the analyses will be carried out and simulations will be performed based on commercial production data of gilthead seabream and parameters of various breeding companies.
    Using phenotypic distribution models to predict livestock performance
    Lozano Jaramillo, Maria ; Bastiaansen, J.W.M. ; Dessie, Tadelle ; Alemu, S.W. ; Komen, J. - \ 2019
    In: Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science. - Wageningen Academic Publishers (EAAP Book of Abstracts ) - ISBN 9789086863396 - p. 658 - 658.
    Genetic parameters for feed intake and growth curves in three-way crossbred pigs
    Mezencio Godinho, Rodrigo ; Bergsma, R. ; Guimarães, S.E.F. ; Silva, F.F. ; Knol, Egbert ; Milgen, J. van; Komen, J. ; Bastiaansen, J.W.M. - \ 2019
    In: Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science. - Wageningen Academic Publishers (EAAP Book of Abstracts ) - ISBN 9789086863396 - p. 488 - 488.

    Macauba pulp (Acrocomia aculeata) as alternative raw material for growing-pigs
    Dias, E.F. ; Moreira, V.E. ; Caetano, R.P. ; Veira, A.M. ; Lopes, Marcos S. ; Bergsma, R. ; Guimarães, S.E.F. ; Bastiaansen, J.W.M. ; Hauschild, L. ; Campos, P.H.R.F. - \ 2019
    In: Book of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science. - Wageningen Academic Publishers (Book of abstracts 25) - ISBN 9789086863396 - p. 248 - 248.

    Correction to: Use of genomic information to exploit genotype-by-environment interactions for body weight of broiler chicken in bio-secure and production environments
    Chu, Thinh T. ; Bastiaansen, John W.M. ; Berg, Peer ; Romé, Hélène ; Marois, Danye ; Henshall, John ; Jensen, Just - \ 2019
    Genetics, Selection, Evolution 51 (2019)1. - ISSN 0999-193X - 1 p.

    After publication of this work [1], we noticed that there was an error: the formula to calculate the standard error of the estimated correlation.

    Optimized grouping to increase accuracy of prediction of breeding values based on group records in genomic selection breeding programs
    Chu, Thinh T. ; Bastiaansen, John W.M. ; Berg, Peer ; Komen, Hans - \ 2019
    Genetics, Selection, Evolution 51 (2019)1. - ISSN 0999-193X - 12 p.

    Background: Phenotypic records of group means or group sums are a good alternative to individual records for some difficult to measure, but economically important traits such as feed efficiency or egg production. Accuracy of predicted breeding values based on group records increases with increasing relationships between group members. The classical way to form groups with more closely-related animals is based on pedigree information. When genotyping information is available before phenotyping, its use to form groups may further increase the accuracy of prediction from group records. This study analyzed two grouping methods based on genomic information: (1) unsupervised clustering implemented in the STRUCTURE software and (2) supervised clustering that models genomic relationships. Results: Using genomic best linear unbiased prediction (GBLUP) models, estimates of the genetic variance based on group records were consistent with those based on individual records. When genomic information was available to constitute the groups, genomic relationship coefficients between group members were higher than when random grouping of paternal half-sibs and of full-sibs was applied. Grouping methods that are based on genomic information resulted in higher accuracy of genomic estimated breeding values (GEBV) prediction compared to random grouping. The increase was ~ 1.5% for full-sibs and ~ 11.5% for paternal half-sibs. In addition, grouping methods that are based on genomic information led to lower coancestry coefficients between the top animals ranked by GEBV. Of the two proposed methods, supervised clustering was superior in terms of accuracy, computation requirements and applicability. By adding surplus genotyped offspring (more genotyped offspring than required to fill the groups), the advantage of supervised clustering increased by up to 4.5% compared to random grouping of full-sibs, and by 14.7% compared to random grouping of paternal half-sibs. This advantage also increased with increasing family sizes or decreasing genome sizes. Conclusions: The use of genotyping information for grouping animals increases the accuracy of selection when phenotypic group records are used in genomic selection breeding programs.

    Genotype by environment interactions in poultry breeding programs
    Thinh Tuan, Chu - \ 2019
    Wageningen University. Promotor(en): E. Norberg; H. Komen, co-promotor(en): J. Jensen; P. Berg; J.W.M. Bastiaansen. - Wageningen : Wageningen University - ISBN 9788793787803 - 199

    Environmental differences between the breeding (B) and commercial production (C) environments may lead to genotype-by-environment interactions (GxE) i.e. re-ranking of breeding values of animals in the two environments. A substantial re-ranking implies genetic progress achieved in breeding programs is not realized in performance of production animals. The issues of GxE are not new and several solutions exist, however, there has not been much focus on solutions for breeding programs for poultry. This PhD-project investigated GxE interactions in breeding programs for poultry and solutions to improve genetic progress in these breeding programs.

    A strong GxE interaction for body weight (BW) traits was found in broilers that were raised in B and C environments. Indications of GxE were significant re-ranking of breeding values, heterogeneous variances and different heritability for BW under B and C conditions. The genetic correlations between BW traits measured in B and C environments were in the range 0.48-0.54. Genetic variances of C traits were more than 2 times higher than those of B traits. Heritability of C traits (0.31-0.37) were higher than those of B traits (0.27-0.30).

    In this thesis, several approaches to improve genetic gains of the poultry breeding programs in the presence of GxE have been investigated: phenotyping strategies, optimal modelling of traits, use of group records, and the use of genomic information. Different phenotyping strategies were compared in a breeding program for broilers that used genomic selection. It was found that when the genetic correlations between traits measured in B and C were 0.5 and 0.7, allocation of 70% and 30% hatched birds to B and C environments, respectively, for phenotype testing led to the highest genetic gains among the compared phenotyping strategies. When the genetic correlation was 0.9, moving birds to C did not improve genetic gains of the breeding scheme due to reduced selection intensity. Increasing proportion of birds moved to C (from 15 to 45%) could reduce rate of inbreeding of the breeding program.

    Optimal modelling of traits was explored in a genetic analysis that was carried out for BW in broilers at different ages raised in a commercial environment. A statistical model was developed with the aim to increase predictive ability of the model for the traits affected by maternal effects. A criterion for the development of the statistical model was based on correlation between EBVs and corrected phenotypes of half-sib individuals. The statistical model also accounted for heterogeneous variances between sexes.

    In breeding programs for village chicken, where strong GxE interactions are expected, the use of group records was a good option to increase genetic gain of the breeding programs. The use of group records from villages significantly improved genetic gains compared to the scheme without birds tested in the village although group records led to a slightly lower genetic gain compared to individual records.

    In addition, the use of genomic information was exploited to improve genetic gain of poultry breeding programs in the presence of GxE. Compared to pedigree, genomic information increased accuracy of the prediction from individual records. The use of combined pedigree and genomic information in the ssGBLUP prediction from individual records substantially increased accuracy of EBVs of C traits by 31-37%, and reduced bias of prediction for genotyped selection candidates. Genomic information was also utilized to form groups, so that accuracy of the prediction from group records increased compared to the use of pedigree information.

    Overall, differences between the breeding and production environments can lead to substantial GxE interactions. In the presence of GxE interactions, a breeding program for poultry should establish recording systems under the production environments in either individual or group records in order to ensure maximum genetic gains and provide customers with genotypes well adapted to the production environments. In addition, an optimal cross-validation procedure for the choice of statistical models is needed for genetic evaluations in poultry breeding programs as better modelling of traits is a low-cost approach to improve accuracy of selection.

    Using phenotypic distribution models to predict livestock performance
    Lozano-Jaramillo, M. ; Alemu, S.W. ; Dessie, T. ; Komen, H. ; Bastiaansen, J.W.M. - \ 2019
    Scientific Reports 9 (2019)1. - ISSN 2045-2322

    Livestock production systems of the developing world use indigenous breeds that locally adapted to specific agro-ecologies. Introducing commercial breeds usually results in lower productivity than expected, as a result of unfavourable genotype by environment interaction. It is difficult to predict of how these commercial breeds will perform in different conditions encountered in e.g. sub-Saharan Africa. Here, we present a novel methodology to model performance, by using growth data from different chicken breeds that were tested in Ethiopia. The suitability of these commercial breeds was tested by predicting the response of body weight as a function of the environment across Ethiopia. Phenotype distribution models were built using machine learning algorithms to make predictions of weight in the local environmental conditions based on the productivity for the breed. Based on the predicted body weight, breeds were assigned as being most suitable in a given agro-ecology or region. We identified the most important environmental variables that explained the variation in body weight across agro-ecologies for each of the breeds. Our results highlight the importance of acknowledging the role of environment in predicting productivity in scavenging chicken production systems. The use of phenotype distribution models in livestock breeding is recommended to develop breeds that will better fit in their intended production environment.

    Predicting breed by environment interaction using ecological modelling
    Lozano-Jaramillo, María - \ 2019
    Wageningen University. Promotor(en): J. Komen, co-promotor(en): J.W.M. Bastiaansen; T. Dessie. - Wageningen : Wageningen University - ISBN 9789463950718 - 150

    In most of African countries, livestock production branches from an ancient tradition where nearly all rural and peri-urban families keep different indigenous breeds in scavenging systems. In sub-Saharan Africa, where these production systems are the most prominent, livestock mainly forages for resources that are highly dependent on the local environment and season. Even though these breeds are said to be adapted to the local conditions, their productivity is still low compared to commercial breeds. There have been several efforts from researchers, policy makers and livestock specialists to introduce commercial breeds to support the generation of food security and poverty alleviation. However, most of these attempts have failed because of the non-adaptability of introduced breeds to the local conditions. Typically there is no prior knowledge on the environmental sensitivity from these breeds to this new tropical environments. Throughout this thesis I use Geographic Information Systems (GIS) that describe the environment, and models used in ecology to investigate the match of animals with their environment. The aim of this thesis was to evaluate how the environment plays a role in shaping differences in breed performance across agro-ecological zones, and what implications this can have in genetic improvement of livestock.

    Several animal breeding studies tested breeds in different environments to evaluate whether genotypes respond differently to changes in the environment (i.e. G x E). To estimate if there is a re-ranking in breed/genotype performance between environments, a genetic correlation is estimated. To accurately estimate this correlation, an optimal mating design should be established. Breeding programs use full-sibs or half-sibs to perform testing in different environments. Within families, common environmental effects can be present generating a covariance between siblings, and should therefore be taken into account when estimating genetic correlations. In chapter 2, I used stochastic simulation to find the optimal population structure to accurately estimate the genetic correlation between environments using a combination of full-sibs and half-sibs groups under different levels of common environmental effects. Simulation results showed that when there are no common environmental effects present in the population, the mating ratio that gives the lowest standard error of the genetic correlation is of one female per male with 10 offspring per sire per environment. Not accounting for common environmental effects when these are present in the population will lead to an upward bias of the genetic correlation. Increasing the number of females per male to a minimum of 5, with 10 offspring per sire per environment will alleviate the impact of common environmental effects lowering the standard error of the genetic correlation. I suggest for studies that aim to estimate the magnitude of the G x E, to acknowledge the presence of common environmental effects and to take this into account when deciding the mating ratio.

    In chapter 3, using GIS and habitat distribution models a methodology to predict breed suitability for different agro-ecological zones was developed. The methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia. Results show that this methodology is effective in predicting breed suitability for specific environmental conditions. For both chicken breeds the model predicts suitable areas beyond their current extent, hence suggesting areas for breed introduction. The most significant variables that explain the current breed distribution were similar to the environmental conditions from which the breeds originate.

    In chapter 3, only information on the location of the breeds was taken into account. This was extended in chapter 4, leading to an approach that predicts the productivity of the breeds. I present a methodology to model breed performance by using growth data from five different introduced chicken breeds in Ethiopia part of the African Chicken Genetic Gains project (ACGG; https://africacgg.net/). The suitability of these breeds was tested by predicting the response of body weight as a function of the environment in Ethiopia. Across the Ethiopian landscape, predicted body weights varied for all of the breeds. The variation in body weight was explained by different environmental variables, highlighting the importance of understanding the role of the environment in predicting breed productivity.

    In chapter 4, breed performance was predicted within a single country. In chapter 5 breed performance was predicted across countries. Growth data was used from two chicken breeds that were introduced in Ethiopia, Nigeria and Tanzania by the ACGG project. The aim was to assess if the data from one country could be used to predict the performance of the same breed in the other two countries. The variation found in breed performance could be attributed to each breeds’ environmental sensitivity. The environmental variables responsible for shaping the variation in performance were different for each breed in each country. The accuracy of the prediction models projected from one country to the other show they can be used to identify areas for successful breed introduction.

    In chapter 6 I discussed how the tools developed in this thesis can be used in animal breeding for different approaches. I suggest for different disciplines such as landscape genomics and ecology to work together with animal breeding to understand the role that the environment plays in shaping the observed phenotypic differences. This knowledge has implications for the development of breeding programs for different agro-ecologies, taking into account the continuous environmental variation. Furthermore, I recommend the use of these tools to generate knowledge on the impact of climate change on livestock to help generate mitigation plans and policy frameworks that will help in enhancing food security and preserving the current biodiversity.

    Use of genomic information to exploit genotype-by-environment interactions for body weight of broiler chicken in bio-secure and production environments
    Chu, Thinh T. ; Bastiaansen, John W.M. ; Berg, Peer ; Romé, Hélène ; Marois, Danye ; Henshall, John ; Jensen, Just - \ 2019
    Genetics, Selection, Evolution 51 (2019)1. - ISSN 0999-193X

    Background: The increase in accuracy of prediction by using genomic information has been well-documented. However, benefits of the use of genomic information and methodology for genetic evaluations are missing when genotype-by-environment interactions (G × E) exist between bio-secure breeding (B) environments and commercial production (C) environments. In this study, we explored (1) G × E interactions for broiler body weight (BW) at weeks 5 and 6, and (2) the benefits of using genomic information for prediction of BW traits when selection candidates were raised and tested in a B environment and close relatives were tested in a C environment. Methods: A pedigree-based best linear unbiased prediction (BLUP) multivariate model was used to estimate variance components and predict breeding values (EBV) of BW traits at weeks 5 and 6 measured in B and C environments. A single-step genomic BLUP (ssGBLUP) model that combined pedigree and genomic information was used to predict EBV. Cross-validations were based on correlation, mean difference and regression slope statistics for EBV that were estimated from full and reduced datasets. These statistics are indicators of population accuracy, bias and dispersion of prediction for EBV of traits measured in B and C environments. Validation animals were genotyped and non-genotyped birds in the B environment only. Results: Several indications of G × E interactions due to environmental differences were found for BW traits including significant re-ranking, heterogeneous variances and different heritabilities for BW measured in environments B and C. The genetic correlations between BW traits measured in environments B and C ranged from 0.48 to 0.54. The use of combined pedigree and genomic information increased population accuracy of EBV, and reduced bias of EBV prediction for genotyped birds compared to the use of pedigree information only. A slight increase in accuracy of EBV was also observed for non-genotyped birds, but the bias of EBV prediction increased for non-genotyped birds. Conclusions: The G × E interaction was strong for BW traits of broilers measured in environments B and C. The use of combined pedigree and genomic information increased population accuracy of EBV substantially for genotyped birds in the B environment compared to the use of pedigree information only.

    Genetic correlations between growth performance and carcass traits of purebred and crossbred pigs raised in tropical and temperate climates1
    Godinho, Rodrigo M. ; Bergsma, Rob ; Silva, Fabyano F. ; Sevillano, Claudia A. ; Knol, Egbert F. ; Komen, Hans ; Guimarães, Simone Eliza F. ; Lopes, Marcos S. ; Bastiaansen, John W.M. - \ 2019
    Journal of Animal Science 97 (2019)9. - ISSN 0021-8812 - p. 3648 - 3657.
    breeding program - correlated response - crossbred pigs - genotype by environment interactions - growing-finishing pigs

    In pig breeding, selection commonly takes place in purebred (PB) pigs raised mainly in temperate climates (TEMP) under optimal environmental conditions in nucleus farms. However, pork production typically makes use of crossbred (CB) animals raised in nonstandardized commercial farms, which are located not only in TEMP regions but also in tropical and subtropical regions (TROP). Besides the differences in the genetic background of PB and CB, differences in climate conditions, and differences between nucleus and commercial farms can lower the genetic correlation between the performance of PB in the TEMP (PBTEMP) and CB in the TROP (CBTROP). Genetic correlations (rg) between the performance of PB and CB growing-finishing pigs in TROP and TEMP environments have not been reported yet, due to the scarcity of data in both CB and TROP. Therefore, the present study aimed 1) to verify the presence of genotype × environment interaction (G × E) and 2) to estimate the rg for carcass and growth performance traits when PB and 3-way CB pigs are raised in 2 different climatic environments (TROP and TEMP). Phenotypic records of 217,332 PB and 195,978 CB, representing 2 climatic environments: TROP (Brazil) and TEMP (Canada, France, and the Netherlands) were available for this study. The PB population consisted of 2 sire lines, and the CB population consisted of terminal 3-way cross progeny generated by crossing sires from one of the PB sire lines with commercially available 2-way maternal sow crosses. G × E appears to be present for average daily gain, protein deposition, and muscle depth given the rg estimates between PB in both environments (0.64 to 0.79). With the presence of G × E, phenotypes should be collected in TROP when the objective is to improve the performance of CB in the TROP. Also, based on the rg estimates between PBTEMP and CBTROP (0.22 to 0.25), and on the expected responses to selection, selecting based only on the performance of PBTEMP would give limited genetic progress in the CBTROP. The rg estimates between PBTROP and CBTROP are high (0.80 to 0.99), suggesting that combined crossbred-purebred selection schemes would probably not be necessary to increase genetic progress in CBTROP. However, the calculated responses to selection show that when the objective is the improvement of CBTROP, direct selection based on the performance of CBTROP has the potential to lead to the higher genetic progress compared with indirect selection on the performance of PBTROP.

    Randeffecten in vaste rijpaden : Verschillen in opbrengsten tussen binnen- en buitenrijen aanleiding voor onderzoek
    Balen, D.J.M. van; Bastiaansen, Lucas ; Janmaat, Leen - \ 2019
    Ekoland 39 (2019)6. - ISSN 0926-9142 - p. 35 - 35.
    Response to a selection index including environmental costs and risk preferences of producers
    Ali, Beshir M. ; Bastiaansen, John W.M. ; Mey, Yann de; Oude Lansink, Alfons G.J.M. - \ 2019
    Journal of Animal Science 97 (2019)1. - ISSN 0021-8812 - p. 156 - 171.

    Genetic improvement of animals plays an important role in improving the economic and environmental sustainability of livestock production systems. This paper proposes a method to incorporate mitigation of environmental impacts and risk preferences of producers into a breeding objective via economic values (EVs). The paper assesses the effects of using these alternative EVs of breeding goal traits on discounted economic response to selection and on environmental impacts at commercial farm level. The application focuses on a Brazilian pig production system. Separate dam- and sire-line breeding programs that supply parents in a 3-tier production system for producing crossbreds (fattening pigs) at commercial level were assumed. Using EVs that are derived from utility functions by incorporating risk aversion increases the cumulative discounted economic response to selection in sire-line selection (6%) while reducing response in dam-line selection (12%) compared with the use of traditional EVs. The use of EVs that include environmental costs increases the cumulative discounted social response to selection in both dam-line (5%) and sire-line (10%) selections. Emission of greenhouse gases, and excretion of nitrogen and phosphorus can be reduced more with genetic improvements of production traits than reproduction traits for the typical Brazilian farrow-to-finish pig farm. Reductions in environmental impacts do not, however, depend on the use of the different EVs (i.e., with and without taking into account environmental costs and risk). Both environmental costs and risk preferences of producers need to be considered in sire-line selection, and only environmental costs in dam-line selection to improve, at the same time, the economic and environmental sustainability of the Brazilian pig production system.

    Use of geographic information system tools to predict animal breed suitability for different agro-ecological zones
    Lozano-Jaramillo, M. ; Bastiaansen, J.W.M. ; Dessie, T. ; Komen, H. - \ 2019
    Animal 13 (2019)7. - ISSN 1751-7311 - p. 1536 - 1543.
    agro-ecology - breeding programs - distribution models - livestock - local adaptation

    Predicting breed-specific environmental suitability has been problematic in livestock production. Native breeds have low productivity but are thought to be more robust to perform under local conditions than exotic breeds. Attempts to introduce genetically improved exotic breeds are generally unsuccessful, mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to determine its suitability to different locations. Here, we present a methodology to predict the suitability of breeds for different agro-ecological zones using Geographic Information Systems tools and predictive habitat distribution models. This methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Cross-validation results show this methodology to be effective in predicting breed suitability for specific environmental conditions. Furthermore, the model predicts suitable areas of the country where the breeds could be introduced. The specific climatic parameters that explained the potential distribution of each of the breeds were similar to the environment from which the breeds originated. This novel methodology finds application in livestock programs, allowing for a more informed decision when designing breeding programs and introduction programs, and increases our understanding of the role of the environment in livestock productivity.

    Understanding the Effect of the Environmental Conditions on the Suitability of a Breed for Different Agro-Ecological Zones
    Lozano Jaramillo, Maria ; Bastiaansen, J.W.M. ; Dessie, Tadelle ; Komen, J. - \ 2018
    In: Proceedings of the World Congress on Genetics Applied to Livestock Production Auckland : IAVS / Massey University - 4 p.
    Predicting suitability of breeds for a production system can be challenging in livestock. Most attempts to introduce exotic breeds in low input systems were unsuccessful mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to elucidate their suitability to different locations. Predictive habitat distribution models use the current climatic conditions of a breed to make
    predictions of the potential distribution of the breed. A methodology was developed to predict breed suitability for different agro-ecological zones based on GIS tools and PHD models. This methodology was tested on distribution data of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Results from cross-validation based on the current distribution of the breeds showed this methodology to be effective in predicting breed specific environmental suitability. Furthermore, for both breeds the significant climatic factors that shape the breeds distribution
    were similar between the suggested distribution area, and the environment from which the breeds originated in South Africa and Egypt. This novel methodology applied to livestock research, allows for better decisions in introduction programs and the design of testing schemes, and increases our understanding of the role of the environment in livestock productivity.
    The impact of genome editing on the introduction of monogenic traits in livestock : Simulation program
    Bastiaansen, J.W.M. ; Bovenhuis, H. ; Groenen, M. ; Megens, H.J.W.C. ; Mulder, H.A. - \ 2018
    Wageningen University & Research
    genome editing - selection emphasis - monogenic trait - selection response - reduced editing efficiency - genomic selection - editing efficiency - polygenic trait - editing procedures - livestock
    Background Genome editing technologies provide new tools for genetic improvement and have the potential to become the next game changer in animal and plant breeding. The aim of this study was to investigate how genome editing in combination with genomic selection can accelerate the introduction of a monogenic trait in a livestock population as compared to genomic selection alone. Methods A breeding population was simulated under genomic selection for a polygenic trait. After reaching Bulmer equilibrium, the selection objective was to increase the allele frequency of a monogenic trait, with or without genome editing, in addition to improving the polygenic trait. Scenarios were compared for time to fixation of the desired allele, selection response for the polygenic trait, and level of inbreeding. The costs, in terms of number of editing procedures, were compared to the benefits of having more animals with the desired phenotype of the monogenic trait. Effects of reduced editing efficiency were investigated. Results In a population of 20,000 selection candidates per generation, the total number of edited zygotes needed to reach fixation of the desired allele was 22,118, 7072, or 3912 with, no, moderate, or high selection emphasis on the monogenic trait, respectively. Genome editing resulted in up to four-fold faster fixation of the desired allele when efficiency was 100%, while the loss in long-term selection response for the polygenic trait was up to seven-fold less compared to genomic selection alone. With moderate selection emphasis on the monogenic trait, introduction of genome editing led to a four-fold reduction in the total number of animals showing the undesired phenotype before fixation. However, with a currently realistic editing efficiency of 4%, the number of required editing procedures increased by 72% and loss in selection response increased eight-fold compared to 100% efficiency. With low efficiency, loss in selection response was 29% more compared to genomic selection alone. Conclusions Genome editing strongly decreased the time to fixation for a desired allele compared to genomic selection alone. Reduced editing efficiency had a major impact on the number of editing procedures and on the loss in selection response. In addition to ethical and welfare considerations of genome editing, a careful assessment of its technical costs and benefits is required.
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