ORGANISING YOUR RECORDING SYSTEM TO OPTIMISE MANAGEMENT DECISIONS

Transcription

1 ORGANISING YOUR RECORDING SYSTEM TO OPTIMISE MANAGEMENT DECISIONS Keith Hammnd 1. WHAT IS PERFORMANCE RECORDING? The systematic measuring and recrding f perfrmance r indicatrs f perfrmance traits. These recrds may be taken n- and ff-farm at central test r slaughter pints. They can be cmbined with ther whle herd prductin, ecnmic and marketing data int a data bank. Upn prper manipulatin and analysis this infrmatin is used t aid the many breeding and ther management decisins invlving individual animals, grups f animals and the herd as a whle. We use the term "breeding" t mean all genetic imprvement peratins. Hence, the fundamental reasn fr perfrmance recrding is t (enable!) imprve decisin-making, i.e. it prvides a Decisin Supprt System fr the herd. Perfrmance recrding is als variusly called perfrmance testing, recrd f perfrmance, herd testing, herd recrding, r whle herd recrding. It frms the herd's infrmatin system. Maximising the infrmatin cntent per unit f investment in perfrmance recrding peratins shuld be emphasised. This means addressing: Which animals t identify? What identificatin system? What measurements (including visual scres) t take, hw t take them (e.g., weight r scre birth weight), hw frequently? What ther data shuld be recrded (e.g., birth date, management grups, mating data)? Hw shuld all data be managed (data management cvers a range f peratins frm measurement, thrugh checking, transferring, string, retrieving, and again editing data; input/utput reprt design and use; and arranging fr regular analyses fr presenting the results f these timely and in frms which simplify yur regular decisin prcesses. Hw shuld management grups be structured? What are randm and systematic errrs, and hw t minimise these? AGBU Pigblup Clinic - August

2 2. REMEMBER IDA - INFORMATION, DECISIONS, ACTIONS! That's what recrding, breeding and management is all abut! What infrmatin, and hw is infrmatin cntent maximised? What actins? What decisins? Ideally, the decisin supprt system fr the herd shuld be designed t aid all decisins, breeding and ther management and marketing decisins. Classically, perfrmance recrding has been assciated with breeding peratins nly. Increasingly the recrds themselves will becme part f the infrmatin system fr the herd, invlving animal perfrmance, feeding, financial, marketing and ther farm infrmatin, t be used in the range f day-t-day decisin-making prcesses and fr ther purpses (e.g., advertising == fr decisins by buyers). Autmatin will becme increasingly imprtant t perfrmance recrding, fr generating n- and ff- (e.g., carcase) farm infrmatin. Autmatin includes cmputing, cmmunicatins, identifying animals, cntrlling animal and envirnment, feeding, measuring, recrding and advanced analyses t summarise the infrmatin ready fr use in decisins. Ntice als in the pening definitin f perfrmance recrding the use f the wrd "systematic". Careful planning up frnt is critical t maximising the infrmatin cntent f recrds fr bth breeding and ther management decisins. Recgnise that these large data sets f herd recrds are highly unbalanced in their structure (e.g., unequal representatin f sires, f dams, f age grups, f animals within particular feeding r ther treatment grups, unequal representatin acrss years, nly sme animals being measured fr sme traits, etc). Rule: As data sets becme mre unbalanced 'infrmatin cntent' is increasingly reduced, smetimes dramatically! Message: Endeavur t achieve as much representatin within and acrss grups as practical management and ecnmic cnstraints permit. The final recrding system used must be tailred t the individual prperty and herd management prcedure. AGBU Pigblup Clinic - August

3 Watch fr the false ecnmies! Be realistic when evaluating the csts and benefits f changes t the recrding system. Sme small investments have the ptential t achieve appreciable savings/returns frm the breeding herd. Recrding is nt a spare time jb! It is vital that time be allcated in the daily and weekly wrk schedule fr recrding purpses. GIGO perates! Remember: Garbage In, Garbage Out! Accurate recrding f animal identificatin, management grups, and accurate measurement and recrding f each trait is necessary fr btaining the best summary decisin aids. Remember als: the PIGBLUP prcedure simultaneusly utilises the majrity f the infrmatin cntained in the cmplete data set f individual animal measurements, i.e. all years f recrds, all animals and measurements are analysed simultaneusly. Errrs in pedigree and in ther parts f the animal's recrd unintentinal r therwise, will impact thrughut the analysis, year after year, the extent f this depending upn the amunt f use made f the animal whse recrd is incrrect. Of curse, as this recrd becmes ancient it will have less influence. Labur requirements are a significant variable cst in recrding and breeding peratins, and f curse these place additinal demands n the nature r type and quality f this labur, its management and the amunt required. A number f peratins assciated with yur breeding prgram may well be capable f being varied t reduce demands n labur withut reducing the effectiveness f the prgram. Is whle herd recrding justified fr breeding/management decisins? Fr effective evaluatin f traits such as female reprductin and survival, whle herd recrding is essential, as is the need t recrd the fate f all animals, e.g., animals sld fr slaughter r fr breeding. The pwer f PIGBLUP is based particularly n using infrmatin frm all measurements and all relatives and ther animals in the herd simultaneusly - the mre recrds, the mre infrmatin at the same level f recrding efficiency. Decisins are based n infrmatin; the better the infrmatin the better the decisins prviding the infrmatin is crrectly used. Nw t breeding. Perfrmance recrding is the central peratin t the breeding prgram. The planning and cnduct f perfrmance recrding is ften disregarded as trivial when this is definitely nt s. AGBU Pigblup Clinic - August

4 3. WHAT ARE THE KEY DECISION AREAS? The nine key decisin areas applying t seed-stck prducers are: (ii) T breed r buy replacement stck? Which breeding enterprise t pursue? (iii) What is imprvement? (iv) What recrding system? (v) What t cull? (vi) What t select? (vii) What t mate? (viii) Hw effective is the whle breeding prgram? (ix) Hw t merchandise the results? Fr example, straightbreeding and/r prductin f crssbred bars r sws. In terms f maximising prfit? (This is the breeding bjective fr the herd). A cmplex f questins/ decisins, as already mentined. T maximise gains frm the current herd. T maximise genetic gains in prgeny, grand prgeny, etc. Including age at first mating, mating structure and the use t be made f artificial breeding technlgies. In terms f maintaining cash flw and maximising lng- term return n investment. These decisins are nt independent, and they need t be addressed repeatedly initially, and thrughut the life f the breeding peratin. The imperative fr the seed-stck buyers differs smewhat. The abve decisin areas, 1, 3 t 7 and 9 still apply, with sme changes in emphasis, and areas 2 and 8 cmbined int a new questin: Where t buy? Seed-stck buyers may place different levels f emphasis n sme traits t seed-stck breeders. A breeding infrmatin service needs t recgnise the different imperatives f the seedstck prducer and buyer. Of curse, the seed-stck prducer s lng- term breeding directin, r breeding bjective, shuld be based primarily n his clients cst structures. AGBU Pigblup Clinic - August

5 The decisin aids btained frm yur data bank f perfrmance recrds fr breeding can be gruped int three cmpnents, viz. the breeding directin (breeding bjective), genetic evaluatin (the EBVs), and the verall structure f the breeding prgram (design). We will cme back t these in discussing "Putting it all tgether", later. Fr gd breeding decisins, management grup structure is very imprtant in perfrmance recrding. There are three critical areas: Fair treatment Always try t identify animals separately that have been treated differently, therwise n frm f analyses t prduce EBVs will be able t remve the treatment different bias amngst the measurements. (ii) Large grup size Maximise the number f equally treated animals within each grup t maximise accuracy f the EBVs. (iii) Strng linkage The better the balance f sires and dams acrss equally treated grups the mre accurate will be the EBVs. 4. MAXIMISING INFORMATION CONTENT PER $ INVESTED Recrding systems must evlve. This is ften nt appreciated. Careful planning frm the utset will simplify system evlutin. Fllwing is an extended list f matters t cnsider in maximising infrmatin cntent per unit f investment in yur decisin supprt system. 4.1 What animal identificatin? When is it needed? T cllect infrmatin ver time and space. What are the prs and cns f each system? Shuld there be ne system? When t identify? Which animals t identify? Whle herd? AGBU Pigblup Clinic - August

6 4.2 What measurements? T aid: Management? Breeding? Marketing? decisins - Nte the special place f reprductin in breeding fr genetic imprvement. Cmpare: Mental, Manual and Autmated measurement prcedures. Visual scring systems need greater than 4 stable and mutually exclusive categries, and all categries must be then used prperly. Understand the different requirements f measurements when used fr pricing slaughter stck (price decisin is based n measure f each trait taken n the animal itself) vs breeding decisins based n PIGBLUP (each measure n the same and ther animals cntributes t each EBV f all animals and ranking f EBVs is nw the key cncern). Understand the desirable characteristics f measurements used fr breeding decisins. Variable, heritable and assciated with ne r mre f the ecnmic traits, taken early in life and in bth sexes. Develp fr yurself standard prtcls fr making and recrding each measure, and ensure that all staff are aware f and use these. What place has "marker" traits fr indirect selectin? Fr example, liveweight fr carcase weight, and p2 backfat fr carcase lean. Measuring sme versus all animals. Fr example, live animal vs direct carcase measures, reduced numbers t measure at each stage f multi-stage selectin, sex limited traits. 4.3 What ther data t recrd? Management grups. Dates f birth and pst-birth measures. Age and perfrmance are related fr many measurements! Mating data fr bars, gilts and sws. 4.4 What data management system? Measurement and entering. Checking - incrprate simple checks at each pint remember GIGO! AGBU Pigblup Clinic - August

7 Transferring String Retrieving Editing Analysing Reprting Interpreting Operatinal plans fr abve, particularly timing and n- farm vs. central data banks. 4.5 What design fr the Input/Output system? Establish hw the reprts are t be used and by whm. Then establish the necessary design cnventins fr I/O: - What infrmatin is really required - mre is nt necessarily better? - Hw is it best presented - many issues. 4.6 Hw t best arrange management grups? Think abut the management grups fr each different type f measurement, i.e. the gruping that will result in fair cmparisn f a large number f animals and in strng links between grups, fr each trait measured. We recgnise that measurements are used t create infrmatin fr use in the decisins and actins fr: (ii) Breeding decisins and actins. Management peratins n and ff the farm. (iii) Transactin purpses, i.e., fr marketing breeding stck and slaughter stck. What makes a measurement useful? The criteria fr a measure t be useful fr decisins abut genetic imprvement t a seed-stck prducer are: Variable (the mre the better). (ii) Heritable (the higher the heritability the better, but remember PIGBLUP has greatest impact fr measurements that are less heritable). Nte: smetimes several measures are taken and averaged t increase precisin, althugh nw the heritability f the average shuld be used r preferably each separate measure culd be used in analyses as a repeated measure. AGBU Pigblup Clinic - August

8 (iii) Crrelated with the ecnmic traits (the higher the assciatin the better). (iv) Able t be taken early in life (preferably prir t reprductive age, r even t any culling/castratin), and (v) It is preferable that the measurement can be taken n bth sexes. These are the criteria that cntrl the cntributin f a particular measure t the rate f genetic prgress in ecnmic perfrmance. N measurement is perfect and many different cmbinatins f the abve criteria exist in practise and will prve useful. Of curse, taking the measurement is mre palatable if this can be dne easily and cheaply, but beware f false ecnmics as already mentined. The criteria fr a measurement t be ecnmically valuable t a seed-stck buyer are: (ii) Variable (the mre the differences between animals the mre imprtant the measure). High bserved crrelatin with prfit in the current crp f piglets (even if lwly heritable). (iii) Repeatable (fr traits that are expressed repeatedly such as farrwing success). (iv) Measurable prir t reprductive age. (v) Measurable in the sex f direct interest. (vi) Lw cst f measuring. As yu can see the criteria differ frm the seed-stck breeders and the seed-stck buyers perspective. Intrducing new measurements t perfrmance recrding and genetic evaluatin peratins invlves: Develpment f n- and ff-farm prtcls fr all aspects f: Measuring. Entering, transferring, editing and string. Reprting. AGBU Pigblup Clinic - August

9 (ii) Analyses t: Establishing the analytical mdels t be used in summarising the data - what are the systematic (biases) and randm effects. Estimating adjustment factrs fr standardising the measurements prir t analysis - there is a range f methds fr adjusting data. Estimating the (c)variances - heritabilities, genetic crrelatins etc., which describe the bilgy f the difference between the animals measured. Designing and running the EBV (predictin) system - in this case PIGBLUP. (iii) Training/Educatin: On the riginal system and n the upgrades. 5. ACROSS-HERD PERFORMANCE RECORDING AND GENETIC EVALUATION In graduating frm within- t acrss-herd recrding, either within the same cmpany r amng peratins what are the issues? (ii) (iii) (iv) (v) (vi) Genetic linkages - hw strng and hw t strengthen these where several AB and central testing peratins may be invlved. What are the imprtant traits and where can these be measured, centrally r n-farm (there is a strng trend internatinally t emphasize n-farm recrding). Des linkage exist fr all traits measured? Des a suitable identificatin system exist, i.e. can each AI sire always be identified as the same in all herds invlved, and des much transfer f breeding stck ccur between the herds invlved? Is there an rganisatin capable f implementing/maintaining the additinal lgistical cmplexities in the field and at the central data prcessing facility? What is the (perceived) imprtance f gentype by envirnment interactins (e.g. changes in sire ranking between herds) fr each f the traits measured? Hw t accmmdate crssbred/grade/intrduced animals in the analyses? AGBU Pigblup Clinic - August

10 NOTES AGBU Pigblup Clinic - August