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our next speaker is dr. Albert de Reese dr. Therese is currently a professor at the department of animal sciences at the University of Florida he grew up on a dairy and swine swine farm in the Netherlands and he went to vagon Hagan University where he received a bachelor's and master's in animal science with a minor in agricultural economics in 1991 in 1995 he came to the u.s. to pursue a PhD in animal sciences at the University of Minnesota in st. Paul with a focus on dairy science Applied Economics operations research and statistics after graduation in 2001 Albert accepted a faculty position at the University of Florida in Gainesville he currently teaches two undergraduate degree courses and advises undergraduate Theory students and graduate students his research interests are an optimization of culling and replacement strategies statistical process control economics of reproduction and genetics and precision dairy farming in his extension role he works with the Allied dairy industry and dairy farmers on farm financial management to apply the results of dairy systems management research albert is married to Kim who was a small animal veterinarian and together they have twin daughters Grace and Karen and four cats they live near Newberry Florida once again it is our honor to be able to have dr. de Brees with us this morning to give his presentation and I will hand the reins over to you okay okay well thank you for that introduction um he asked me to talk about the cooling strategies and economic impacts and I'm not sure I really have a lot of concrete on strategies but I want to walk people through some ideas that may affect you know how we shall we go caps so what I want to do today don't give you a little bit about the cooling statistics and some risk factors then show a little model on the economics of productive life and sometimes used breath of life and longevity simultaneously with with with going a few slides perhaps moving the use of the trade productive life intellectually next I think we have some ideas on how to make that better and then I want to say something about collating decisions to force alright and hopefully through thoughts is enough material that people feel it was worth a dime and well this data that is to animal kill rates it's from deer measured eh-eh-eh data um this is the two years old but it's just fairly similar as of now to and then we find it about 38% of cows are replaced every it's but there's about four percentage points of that or our animals that are moved to other farms and so we take 4% off with 38 you get to 34 percent go rate and if you do one over 34 percent then that leaves gives us a productive life of two years 11 months old not quite three years after first a B then that's our stay in virgin we see some variation quite a bit of variation right so the shirts that are below 30% and our what's up aged first caffeine in this data there's almost more than 9-thousand a little over two years twenty five point four months so you put it all together and longevity how long is the couch stay you desert is a little over five years but not much now how does this thirty four percent compared to the best I found the paper from 1939 there again an enhancer remark that it's known that replacement rates in there to here it's a Robert hi and I'm not sure what they compare this with but they found that back then it was necessary to replace approximately 21 to 28 percent to looking your dad so it seems go racing that would be a straight line from the 932 now have not increased but gone up some I'll say a few words about risk factors here this is some data we did ten years ago now with Pablo Benito and we looked at risk of going per day these the graph looking at our public house and so at the bottom is days after calving and we see an increase in Koh risk mostly met about problems probably the pharmacist ethical cows and then it flattens it slows down the daily risk and then you see there was the right end of the curve the tail goes up again because those were cows that failed to get threatened long time and farmers started killing those as well all right and we see clearly an increase in the day of the daily risk of the cow gets old right firstly patient house at lower risk also stayed flat or longer than older gaps they all the cows of the universe increases area we looked at these are all the cows will eat the pregnant cows as well you need this was also need data that was about 25% of the risk of all the caps so clearly you know pregnancy as we probably all know is birth and it prohibits cooling to largest now this data cool risk that we saw go up with age we see that back into the agenda Israel this is percent of cows not reaching the next location lactation 1% are lowered about 20 percent not reaching exploitation you got to really all the cows and it's more than half that started to lactation did not finish that location but sort of surprising here perhaps or at least not worth II is that simplifications not complete in 2016 slightly greater than 2007 okay and you haven't looked at the latest data that's available it maybe just follow your worth of data but clearly not decrease in go rate now I you some of my pharmacy in Forsyth you know which guy will survive they tell me well it's it's house it don't stand out basically don't noticed right and it scouted survived they have maybe four events publications they CAF obviously one calving they just stayed one breeding to get pregnant so no repeat meetings we may do a pregnancy diagnosis and then we find a pregnant and there's no abortion and then we dry them off the calf again right and addition we just know this couch now we could fill a lecture here about risk factors for killing we already briefly talked about parity and pregnancy but it's clear that if you look at the literature and if the cow is keep doses for example is a higher risk of or mastitis those lots of these factors documented you know cover of shake they're laying there not pregnant that is poor confirmation of all these factors awfully are risk factors to go and that means cows that have those are increased risk for coming now I will not talk about how all these factors affect cooling exactly here we did review them recently for the animal paper so if anybody's interested I'd be happy to see about that paper now I want to spend quite a bit of time about genetics actually in this talk because perhaps because I'm interested in it I'm also intrigued by the fact that our cool rates don't are what they are I also say this because I be talking to Europe several times and there's a there's a movement to really extend productive life Heath cows longer in hurt which also means therefore that but the core rates come down right now stay long in to hurt if the herd size is fixed and always have to come down they're really strong thought is there on how do we manage that well here we have data from council dear Carrie D and this is productive life data that's expressed in months and we basically seen from the 1960 to 2070 that the breeding value for productive life basically the ability to stay in the herd has increased perhaps a little oof left in the 20 years ago most it's linked reached all right and if I compare 2017 to about 1960 so that's close to 60 years but means in terms of the breeding value for productive life okay we've increased the breeding value by 20 months about or if you just take the breeding value divided by 2 you get the PTA that the PTA has decreased by 10 months right so 20 months breeding value if this have been expressed in herbs at Leeds cows we breed them they are much better to resist going because animals get positive a be developed for active life if they don't built but the hurt mates do then we would have reduced if we started say 33% in 1960 we would have been at 21% but clearly we're not a 21 percent we're stuck at the belt at 34 35 percent all right and I think in part we can just explain this through some simple basically closed loop going mathematics writes over national urge size is constant and it basically has been for a long time a little over 9 million cows we have one calves born per cow per year that is obviously not every cow has one put one cap but if you count the number of cows dairy you count the number of gametes you get to a number like all right if we then assume that all female calves are raised to become milking cows and I exclude here sexy men and beef segment for simplicity although I know hopefully that is a hot item all right then it has to be that the national and auto rate is about thirty five percent because these female calves that we raise them they have to enter Hertz and birds have to go cows and make room for these efforts right so to some extent and question is - how much extent you know yes is the fact that we have these heifers in the pipeline the driver then of national tours because clearly genetically our cows if they were to compete compared to 1960 cows the 1960 cows none of them would stay in her salon they'd all be gone because our house all right regarding productive life a little more here I sometimes hear we really want a lifetime profit per cow to eat ago a some cows live long it makes sense them that a life that profit goes up right because you replace them less often for example but I would argue that this is not really a goal for commercial therefore if you look at just basic economics then the rule would be to optimize your profit per unit of most limiting factor all right now if the number of cows you know you're stuck with say 100 cows and that's all you have you will never ever replace one yes then extending their life would be cents but often we see here for example I have least dollars per kg of milk or this would be in the quota system per cow per year if the number of places is limiting per milky cow per year this a better rule if say pilot capacity is limiting we could just milk you know X number looking's to eat per day there's also your per kilograms of phosphate because in Europe in the Netherlands that is the rule that they have phosphate quotas so there's a trade-off between more young stock and fewer cows because collectively the total amount of phosphate manure drives and the phosphate quota you can see there that since that implemented that productive life really increased by several percentage points maybe five or so because then farms could reduce their number of youngster and have more milking cows alright so clearly there was some there's possibility for movement there in New Zealand you talk about per hectare okay maybe labor is pretty here alright but I think in the u.s. context it's probably for a milky cow per year or per company here which is often the right goal here so not the length account because maybe I want to replace my cow with a better Cup so the next couple slides so when I walk everybody through a simple model on some key factors that determine how long how should remain in the verge and I'm aware that I will show you is far from reality but I think it really illustrates some PE principles that drive these skill decisions and maybe we can set some of the preconceived notions correct those as well all right so in what I'm going to show you I will I will change my co rates from 55% down to 20% so heiko rates so productive lives to 20% local rates high productive lives and when I do that I basically have an underlying distribution okay so for example if I were to look at this porridge launder 30% less the most clearly one then I have about 30% of my animals or the first lactation about 20 percent in the second 1718 and the third some in the fourth and so on right so 2030 percent and we'll go rate means that on average try to place 30% of my couch every year but I still have a distribution of certain number of animals in the first location and other lower number in the second again a lower number in the third and actually I extended this math all the way to the 20th like they should number known for well that there's hardly any doubt that we found on the theory that lives that long and but on the other hand there's very few cows even in this model that make it that far right we see the vast majority of animals regardless of call rates being in the first up to the fifth sixth guarantee so a little bit of the math and the rest still keeps simpler in the cell all right so one thing obviously that has to do with go rates is called appreciation right so have first lose value from Oh Chester or we have invested in raising up to the moment we cover including you know some some of the dye awfully so there's a depreciation there's a logic value of these ads and here I have this depreciation from high depreciation $2,000 from heifer cuckooing probably don't find it today all the way to 500 that's much lower depreciation right so for example if my heifer was $1500 my goal right it was 500 I have an appreciation of $1000 and now I want to spread out this depreciation over the number of years that this animal stays in the herd and clearly you know the longer and will stay in hurt the lower my depreciation cost per cow per gearing's right so just this graph would favor lower kill rates and therefore longer productive lives because my annual cost of keeping that cow a cow in the verge is is lower than the fish so I'm going to build I have like 400 or five of these figures here so let me set it setting up a little bit at the bottom i varied my animal throw rate as you can see from 50% down to 10% and then in in yellow here is my heart replacement cost okay here assuming cow depreciation of $1,000 all right so if I have Nano to rate 50% that's 2 years depreciation is $1,000 and I divided I'll spread it out over 2 years that would be $500 per here just for the hurt to make up for the replacement cost right so we've seen this is these yellow numbers on the previous slide now I've also had some blue numbers here that I pick the lowest of the bars here I set that to zero and then you then the other then if you go to the left in this case because all the total costs are higher I show what the opportunity from optimal is most of them are off the chart but if I went from 10% to 15% tolerate alright then that is a difference of $50 so this little yellow bar here at 15% is $50 higher then the yellow orange bar here at 10% so clearly this would if this was the only fact that we want to have low go rates but this is like from zoetis and I like this slide because it illustrates another important concept here and I'm looking here at the blue bar so this is milk per day all right at the bottom here we have parity group and clearly cows that are second or third or fourth or fifth lactation they make more milk than first lactation cows these first patient calbro eat the girl song still but they produce less look per day okay and so mature cows these are here fourth fifth lactation would be likely more profit comes right so would we not want to know a lot of fourth fifth lactation caps well if that's the case then clearly we don't want to have a very high cure rate because that would reduce the number of patients and perhaps we also don't want to have a lot of very old cops okay now I realize that the song songs going going on I mean the cows that we see these blue bars for are survivors of previous lactation so they're going in there but nevertheless two important factors in yeah one that again young cows are not mature and maybe second week when cows get to all their knob is efficiently either and I put some numbers to that missus I could with a lot of uncertainty really okay and here I put at zero my first lactation animal and then I did some income over feed cars calculations and I found that for example a fifth of six lactation animal might make us five hundred dollars per cow per year now we can argue about that whether that's the right number or not but for the principle perhaps that's not all right I also have the best the beat how a head of an aged cow cost here all right and clearly I really don't know how much this each cow cost is how really old cow become less efficient in my assumption here I assumed there is no really prior going happening this is truly just the fact of maturity so not just surviving animals we just going because that would create some bias right so I can also convert this graph into an opportunity cost okay in other words the first rotation animal compared to a fifth lactation animal maturity would be five hundred dollars less profitable so I can call that a five hundred dollar opportunity lost similarly you're very old now here the implication here to the best mature animal this would be a two hundred dollar age scout cost okay opportunity lost because I'm milking an old cow that is not mature right now clearly I understand that you cannot just look for a thief of cows just you know in this model here where I assume this heifer strong and cows get gradually over time but I'm converting now this each cow [ __ ] it is like a maturity cost for younger animals on top of my crafty right and I think this is correct here so I'm looking at the cost of third structure already has hurt replacement cost and if I have a very pretty high call rate so low average numbers productive life here I would have a lot of first second lactation animals and I have a high lack of maturity cops okay you know if I drop my cool rate then clearly my lack of maturity cost decreases and but it's not zero because even here or I still have animals even with a 10% Doreen's if I could get that I still have first lactation animals I've second location animals and I have animals fast the invitation and but I do see that my age now cost increased as well alright so and I'm interested now in the lowest of these bars here putting them all together okay and so in this case this would be a 15% tolerate all right that would be the lowest and then you can see the top of the bars are 20% and 10% how much they differ on the blue scale compared to 50% now maybe I forgot to mention this but I assumed that in this lack of maturity cop stand is a stylist we even know what the fact that there's genetic progress right so we're really looking at the same animals that are young then get mature and maybe get off all right I'll get to genetics perhaps in two ways a little bit here this one is quick just to illustrate that if we had local rates we would need fewer replacement heifers and we would have more opportunity in the herd to make higher valued caps perhaps for example with beef on there all right so another factor then of the local rate would be needing fewer dairy heifer gas perhaps I can capture more premium from perfect gas that I don't need so gas that I don't need surplus caps and I got some math there Jim oh and I had it that in here the cat value opportunity cost and again a local or a high flow rate means pretty much I need all the dairy heifers that I can make there to replace my old cows and I would have opportunity loss compared to a local rate where I can make more money on these caps okay but it's not this little blue line here it's not a lot of that doesn't really drive the maximum tolerate to the left or to the right all right let's look at the genetic certain thing because that's a major factor we haven't talked about and I think a lot of producers not sure how many but would say well I need to bring in all my effort is heard because they're my best genetics all right so that's will incorporate next so the question is you know she is greater longevity or brought to life always better right this cows would stay in the herd forever is that what we want it well this is 1956 champion cow she produced 150 four thousand pounds of milk and 13 lactation syrup literally an old cow you know great longevity productive life but she made only twelve thousand pounds per lactation all right so today who wants to milk this cow right would you like to have a whole herd of these 1950 Scouts that's refused to die but transportation well this is genetic trend for net mare net merit as selection index profitability index right several traits many traits and this is from 1980 to 2015 this is by birth year and we can see clearly that the line goes up and animals are genetically better for profitability in each we also see that the genetic lag is growing now the genetic lag is the difference between the genetic package CP Rail of the bulls you can buy and the cows in the verge okay and so because since genomics that widely used we see an increase in genetic progress even admits it's just doubled that rate of progress here that also means that the genetic lack with the couch becomes greater but eventually the slope of the cows will be the same slope as the slope for the bull so the cows are going to catch up all right but although these cows are going to catch up if I had older cows compared to younger cows I you know I don't really have the latest machinery all right and so I'm not going to walk you through this graph but if you just look at asset replacement theory and really calculate is a form of asset placement theory then we would replace sooner if the Challenger that would be replacement heifers technically better than he comments that's the cow all right so let's include that in the graphs that we've had so far so I looked at the genetic progress in that marriage and I'm used $50 per year that the net merit selection index is improving increasing per year now if I look at the net merit today is maybe $70 where it was $30 picked perhaps a conservative number here and so now I can include genetic opportunity cost okay so really if I have this is genetic opportunity compared to both breeding bulls available all right and so my genetic achieve cost increases with older animals all right because I'm basically milking an old cow the the distance genetically between the cows in the herd and the best available genetics is it's greater than when I turn over my work quickly and bring in the latest genetics all the time all right so if I glued it in here and I'm still I think it's still valid that I can add up all these different cost factors and I'm looking at the lowest total here and I get to twenty twenty percent okay although it's pretty close to 25 percent all right so even if I included the genetics in here again it's a simple model there is really any disease filling happening although you know every every lactation there's X percent leave in order to get to these animal Co rates I don't end up with a very high kill rate okay the pool of improved genetic progress from my heifers it doesn't weigh out there's all these other factors in the bird for example lower placing cost more mature animals okay I did a little bit of sensitivity analysis here Mike our depreciation is only five hundred dollars before and I increased my sire PTA and out seventy-five dollars okay so both these factors would favor higher animal go race and I end up with about thirty percent but I am still poor ways off from 45 to 50 percent alright so when I look at this analysis although simple I cannot find any evidence that raising all these efforts and bringing them into the herd would be the right thing to do from a genetics yes it helps and progeny ryx does increase flow rates tom but not very much also did some literature review on this all right published literature review about four or five studies here and then this increased genetic progress and I think I looked at home with doubling today progress today's world compared to what it was before 2010 should increase our fill rates by just a few percent most okay so this conclusion from this paper can also be seen then in his previous analysis all right I want to switch gears here and point to two different topics here I looked at my clock here all right so my grad student Michael Schmitt tonight with the help of Paul Raven that's USDA we wondered about the use of the trait productive life in our selection indexes all right let me illustrate you briefly and this is truly to get you thinking about some things too rough what we thought was the problem and so here this is actually the net merits these are the traits from the 2017 index index but the principle is still the same here and I have a number of traits here many of these traits repeat every lactation milk fat protein if I have high PTAs well every longer lactation that the level stays in hurt I would presumably repeat you know that the genetic diffic benefit the blue ones would be traits that repeat only once in the life of a net all right so only once I have two bulls here the bottom really doesn't matter here but the one is 609 bull another 177 bull and we'll just looking at fats and productive life and so this bull a makes a lot of fat all right time 12 pounds but doesn't live long okay - 3 months compared to the average now the average is about 2.8 like patients so about 2.5 lactation 2 or 3 months left all right where it will be is poor in fact although it's deposited but refuses to die take pleasure live in print and the net merit includes the value of that product of life in its counter fish just let man but what it does not do it does not give these different Bulls credit for how long they stay in the herds okay so as far as this fad go 612 first is 19 both Bulls get credit for this difference in fat for only two point eight locations even though this animal produces this plus one of 12 pounds of fat not for two more locations but made for 2.5 and this animal loses 19 pounds of fat not for 2.8 locations for eight months but for 11 months more all right so now that doesn't sound quite right we felt you need to give animals credit for these differences in these lactation traits for as long as all right we calculate if two indexes I won't go into the math here this one is P and V analyze the present value it seems like that or placement and this is annualized value with opportunity cost okay so this assumes it proof replacement this is next indexing this index showing that was longer than will stay in her refused to die I nominate this genetically heifer all right and I won't get too into that the math here but we did give credit for animals that are say high-protein or lactation we gave them the credit for as many locations not just all right and so what is rebuilt you next would do it would actually read rank both some not amazing ranking but summary ranking alright and so this is August 2009 teen evaluation here we have Bull City this was the top ranking at that time and we saw actually the dumb bull for net merit would within our indexes would not be the top and if we looked at the AVA with improved genetic opportunity cost it would actually drop three places all right so these balls would drop or change the couple positions and if you go down the list you can get to same over hundreds and sometimes he changes 40 or 50 positions all right so clearly I hope eventually that we get to a better improved way of putting productive life into these indexes because it does changed hold on up majorly how we should look at productive life therefore going as far as when it comes to selecting Bulls for profitability all right I want to go through a few slides here on cooling still and I'm looking at my clock close to 40 minutes here all right so it is there something to decide neither Disney meeting question is filling all well or stuffed with it it's just we can't play we can't do anything where's there's something to decide petrol in a review would say that most filling is for economic reasons I do that criteria for cooling vary between farmers study here but these farmers looked at the same cows in two different rankings from different ideas vehicles and farm advisors and farmers don't agree which Scout should be killed Boulder economic models would say that less than 30 percent and replacement is economically optimal knowing that this is farm dependent farmers also find that going decisions are not a priority now it's all to be shirts here and yes this weekend calls for grilling decision support I probably get an email every two or three weeks somebody says do you have something to decorate and I know how to do how to rank house we have to basically calculate cash flows for the keep the cow into some optimal time into the future we can basically calculate that versus go in the car now or place in there with a heifer right that takes cash flow predictions and it takes about five six years into the future for the animal that I have including her placements and also for if I were to fill this out and replace er right now and we can think the difference of these cash flows and in the literature that's called retention payoff future value keep value I think that cows value and Erica is a similar concept alright so this is this principle that we just talked about here let's just keep decision on top the black is the current cow the current cow gets replaced over time with the cash flows from placement animals different colors or I can replace my goal my current cow now and even over time my replacement heifer gets replaced and gets replaced and so on and if I I need to do this for five five six years into the future for certain slot then my values have been stabilized and I take the difference of both calculations and I get to my p-value kavaalen reps now the algorithms behind the successful predictions can be quite different it's not like they're all coming up with the same answer at all I think I have maybe three or so much less so if I calculate this with my own machinery here then I have these retention values of deep values here at the bottom here is Station scattering if I take the top ones this is a high producing cow the blue closed dots would be the value of keeping the Scout compared to replacement so as long as it's positive I want to keep this cow even though she's dog all right if I look at the green one close that's a noble cow it's a low producing cow and she dropped below zero clicker so when she drops below zero that would be the right time to replace the open dots here are these values for when animals get pregnant all right so here are some pregnancy about them starting in the third month and there's a little bit of loss because perhaps an abortion happening for example in the future but the pregnant cows are worth more than the overcomes yes so drop below zero replace so ideally this is the best rule if we can get these cash flow predictions correctly done and there's work to be done I compare this rpu rule with another rule just for illustration this would be income over variable costs my other rule for example no sales minus feed costs all right let's say milk sales minus the cost and I look at my RP over time and we can see that the RPO drops below zero time to replace when the income of feed cost as far as I could estimate this for his animal would still be positive 250 per day all right so I would if I hang on to this value until milk sales equals about feed cops then I'm hanging on too long three cents I basically I have days weeks for that make very little money with this animal and I deny more profitable animal into that work so the RPO would be a much better ranking of for animals for going decisions I do a little bit of that here this is a PC dart graph that I work with on a farm for development and so we do have to keep values keep percents all right so this is a trial this is experimental but this producer likes it he values those through song hurt this is after DHEA test making killing right off decisions and this is an animal that is now beef its goal and she had a low RPO allow people truly a driver of their decision all right now if you were to just go all negative RP owes you call those more positive up you keep that would also drive your government all right let me turn right this lot of material here so I think Everett's full rate has three slow over time seems most cows are broken when they're gold at least that's what we're being told but it's really all driven by economic chief and broken cows they may be obviously hard physicals once but really there's economic principle behind it I really didn't talk about much about consumer consumer perception I don't think in the US it's a big deal but Europe a lot of people believe that cows need to live law alright so there there's a strong push to reduce low rates we thought it faster genetic progress reduces often operative life span or increases fully but just a little bit I think that our current go rates compared to what much of the math SAS would be ideal I suggest that we should reduce alright son and I think we're starting to ask that questions more now that we're doing a lot of beef semen in their ear it's not how much Hector did we really needed some through the glass was fantastic question and then to really make improve these decisions I think we still need some better tools to support his decision placement seasons and were actually very fast working on this and hopefully this V market rage soon alright so thank you for the attention all right thank you dr. Therese a lot of stuff there for us to think about um again if you're if you're listening we do have time for a couple questions so you can leave them in the chat box on YouTube there to get us started looking for some clarification I guess do you don't you think amortization per liter of melt that is produced is more indicative than depreciation so the point is here that the producer gets paid by milk and not by the number of years at the cow stays in the herd so can you can you comment on that oh you know if you limit if I think that goes back to the idea that were limited by the amount of you we make okay so in a Canadian system I think it's still time I assumed that the number of cows in my version basically so then I would not necessarily as we want extent birth of life very long for cows and I think we forget the opportunity cost thank you um I know in a lot of your examples you were using $19 100 wait so so the way milk prices are looking currently does that does that change and I guess kind of a question along the same lines we see a lot of producers that are having to make some short-term decisions on on rapid culling or drying off cows sooner you know some of these harder economic decisions along these lines how does what you've talked about today relate to this hopefully hopefully unique situation that we're seeing right now yeah correct yeah good question we went through there's just exercise our own University for the hurt go up we have to cut look 10 percent so we said well what do we do and we did not know how laughs so it's at least it was in April is it since in May and we're looking at milk prices there like $3 for show of their weights their March prices we decided to dry off cows we killed a few but clearly we coat too many you know the question is and this is white box thinking almost like what will you price would be four or five months or not right if they get up you didn't have these animals of the urge you know that's scarce so we and this is all sort of risk we decided we want to have the capacity to make more milk quickly if prices worth it so we went through drying off we called a few but not much I would not make by seasons all oh my god I have to go couch now obviously you've got a look at cows anyways you know they have a future there but I don't think that these changes the last couple months really impacts going a lot okay and I'll just ask this one we have about a minute um if I didn't get a chance to get to your question this morning you can feel to feel free to reach out dr. dabree female is here on the slide or you can email us and we can pass the question on but we have a question could this analysis be extended to evaluation of extended lactation so greater than 14 months as a way to increase productive life by reducing the number of cat you know hold on a little bit here because we have something better - yeah because that's sort of a that's a question yeah I realize that and I hate to give you answers based on the two simple analysis okay but clearly in Europe that is also a big big topic all right thank you