Page 17 - Marieke Poppe
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1 General introduction

                      with a less severe negative energy balance (Sölkner and Fuchs, 1987; Dekkers et al.,
                      1998). Furthermore, data is becoming available on feed intake which is used for
                      selection for feed efficiency  (Berry  et al., 2014; Pryce  et  al., 2014; Martin et al.,
                      2021b). Automatic recording of e.g. body condition score is an emerging area of
                      study as well (e.g. Salau et al., 2014; Hansen et al., 2018; Song et al., 2019). These
                      new  sources  of  data  may  offer  an  opportunity  for  genetically  improving  energy
                      balance (Martin et al., 2021a).
                         A  third  method,  specifically  for  dairy  cattle,  was  to  select  for  more  robust
                      conformation (Hamoen et al., 2009). A cow with robust conformation is a cow with
                      intermediate body condition score, body depth, rump width and chest width. The
                      robustness score has been applied in The Netherlands in the overall conformation
                      score,  but  was  removed  again  due  to  lack  of  clarity  of  the  trait  for  farmers
                      (Veeteelt, 2015).
                         The  last  proposed  method  to  improve  robustness  was  selection  for  lower
                      environmental  sensitivity  (Knap,  2005;  Veerkamp  et  al.,  2013).  Two  types  of
                      environmental sensitivity exist: macro- and micro-environmental sensitivity (for a
                      review,  see  Iung  et  al.  (2020)).  Macro-environmental  sensitivity  refers  to  how
                      sensitive  performance  is  to  a  measurable  aspect  of  the  environment,  such  as
                      ambient temperature (Berghof et al., 2019b). Macro-environmental sensitivity can
                      be improved by applying reaction norm models. A reaction norm model is a genetic
                      model where the trait of interest is regressed on an environmental descriptor, such
                      as temperature-humidity index. With this model, animals receive a breeding value
                      for the level and the slope of the trait. A steeper slope means that the animal is
                      more environmentally sensitive. Many studies have been performed on selection
                      for  macro-environmental  sensitivity  (e.g.  Calus  et  al.,  2005;  Bohmanova  et  al.,
                      2008;  Mulder  et  al.,  2013a;  Rashidi  et  al.,  2014;  Herrero-Medrano  et  al.,  2015;
                      Carabaño et al., 2017; Nguyen et al., 2017b). Nevertheless, to my knowledge such a
                      model is in practice only being applied for heat tolerance in dairy cattle in Australia
                      (Nguyen et al., 2017b).
                         Micro-environmental  sensitivity  refers  to  how  sensitive  performance  is  to
                      temporary  changes  within  the  environment,  and  is  therefore  similar  to  the
                      definition  of  resilience  used  in  this  thesis.  Studies  that  focused  on  selection  for
                      micro-environmental sensitivity used advanced statistical models on variability of
                      available traits, within family groups or within animals. The hypothesis for family
                      groups, is that family groups with high variability in performance within them, have
                      high  micro-environmental  sensitivity  (or  low  uniformity).  The  hypothesis  for
                      individual animals, is that a trait measured multiple times on the same animal is
                      more variable for animals with high than with low micro-environmental sensitivity.

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