[Music] at adesayo we cherish the work we carry out with animals and thanks to us chickens and pigs grow with less feed and in a healthier way cows produce milk in greater quantity and quality for a longer period and fish and shrimp now have fewer diseases and grow faster these animals contribute to feed 8 billion people and have enabled us to become a global leader in the production of nutritional solutions for animal feed one of the leaders in methionine an essential amino acid and protected methionine for ruminants one of the key players in the vitamins and specialty products designed to foster animal health and welfare our story began in france with alimothers in 1939 then in 1971 the company is acquired by hon pulank becoming its animal feed division in 2002 acquired by an investment fund and renamed adesayo the company regains its independence and in 2006 we joined the blue star group thus asserting opposition in asia and china especially adeseo is a unique company in many aspects our roots are in france but our products come from europe and china and 95 of them are exported to over 110 countries and have more than 3 900 customers worldwide we are a medium-sized company with around 1.5 billion euros turnover and almost 2 200 people working for adeseo our uniqueness also comes from our investments in both industry and research guaranteeing a competitive and innovative product and service offering 1.7 billion euros have been invested since 2007. our success is also due to our dedication to essential values team spirit creativity integrity commitment and results over the years our company has changed developed and grown putting safety and sustainability as top priorities safety of our employees safety of our plants and of our research centers safety of our products we never do any compromise with safety aware of present and future economic environmental and social issues adesayo has developed a growth strategy that is clearly in line with the un's sustainable development goals building on its strengths and successes adesayo strives to be a partner of choice in animal nutrition with women and men who make the difference every day to feed the planet in a high quality affordable safe and sustainable way in the name of fadicio i want to welcome you to the webinar presenting nasam 2021 protein and amino acid requirements in dairy cow i am dr christophe polos remnant business director emea together with my colleague dr sean richards women and senior technical advisor we will be sharing this webinar it is my pleasure that you all can listen to this very new information on dairy cow's requirements from the u.s national academies of sciences engineering and medicine nasem previously known as nrc this webinar will be presented by dr ellen lapierre a famous prominent researcher at the sherbrooke research and development center quebec canada from agriculture and agri-food canada before i am introducing her please let me explain the rules of today the presentation will last 45 to 15 minutes followed by 5 to 10 minutes of question how to ask the questions you will not be able to ask them live but you can post question at any time just use the questions tab and type in sean richards will ensure that we answer as many of them as possible after the presentation the webinar is recorded so that you or other can watch it later on but enough housekeeping messages let me introduce dr helen lapierre even if i'm guessing that she's well known to many of you her research aims to improve the efficiency of nitrogen utilization through a better knowledge of intermediary metabolism of dairy cows to achieve this goal dr lapierre has developed an integrated approach to determine both supply from the diet and utilization of nutrients with a focus on nitrogen metabolites at the whole body and tissue level this fundamental knowledge permits a lower overall protein input but with a better balance of individual amino acids to support milk protein output such an approach has the added benefit of decreasing feed costs and decreasing excretion of nitrogen into the environment as a consequence and as recognition of her contribution dr lapierre is a co-author of the nasam committee focusing on the protein and amino acid requirements today she will speak to you about nasa in 2021 protein and amino acid requirements in dairy cows it is my pleasure to leave the floor to dr lapierre welcome ellen it's up to you i leave you the floor so uh thank you again dr paulus and thanks to disabled for their very kind invitation and what i will be doing will be to present you what we can call the novelties in the estimation of the protein and amino acid supply and recommendation i'll go a little bit further than just the recommendation or the requirements uh just to describe basically the thinking that we had on the mileage that should be inputted into the new model so uh christoph already mentioned that nrc changed for nassem and just briefly some abbreviations here um that will go through your family with those but that will help so essential amino acid deficiency of utilization of amino acid uh efficiency of intelligence of mp microbial cryptine metabolic fecal protein metabolizable protein milky yield the true coutinho uh requirement roman and degraded protein and the true protein so when we well the novelties that we'll be talking about basically first covering both the prediction of the supply and the estimation of the requirement is the thinking that we had about the amino acid composition of the proteins then what other principle on which we base the prediction of the supply of np and essential amino acid on the prediction of nipatine yield and now we came to a new estimation of recommendations of np and essential amino acids so first the amino acid composition of proteins so basically in most of the model that are dealing with individual amino acid photosupply and all the requirements except milk we use amino acid compositions that are obtained from protein hydrolysis whereas for milk we use an amino acid composition which is based on dna sequence of milk protein fractions and basically we put all that together which is the same thing as adding bananas and apple so what we were thinking of is that this is not something which is being new we know that when we do an hydrolysis of 24 hours to obtain a minoxid composition this standard time actually is a compromise and basically is that it does not allow an accurate quantification of any of the amino acids it's like okay for all the minorizes but it is not right for each individual of mine was it and very simple examples here is that if you look at the vanilla availing sorry in cannola meal we have different time of hydrolyzes here you know we've been for extended period of time and here we have the veiling relative to the grams of crude protein and we can see here in the solid triangle that at 24 hours we haven't reached yet the total release of the valine in the protein and this is fairly well known for all the branched chain minor acid whereas form another minority like serene and we get the same thing for throning well actually at 24 hours we already began to have some degradation of the amino acid that was almost totally released after 12 to 18 hours so taking the 24 hour period actually we underestimate here in the case of serine because it's degraded and in the case of veining because it's not totally released so we went on utilization of correction factors that do account for incomplete recovery of amino acid when we use a 24 hour by 24 hour hydrolysis and this is a paper we published in 2019 we have different correction factors for each amino acids but we could not detect an effect of the protein matrix we checked you know if this correction factor would be different for example if we're sampling juvenile digester or feed ingredients we couldn't find any difference so for now we propose the same adjustment to use for each amino acid for all types of proteins but in the future there is more work than that we might come to another um to to another conclusion but for now at least it is helping to merge things together and make sure that we have we are accounting for the total amino acid composition of each type of proteins that we're dealing with in the model the other point that we have to think as well is that when we obtain a minor acid from hydrolysis actually each time that we cut a peptide peptide bond we do add one molecule of water which is not new but what it means basically is that if we hydrolyze one kilo of true protein that will yield 1.15 kilo of amino acid so when we want to determine the ratio of true protein on crude protein we should not sum the free amino acid but we should sum the free nitrous amino acid to remove this molecule of water and in some models like in norfolk being acknowledged i know that the indra they're also making some summation to yield 100 percent but many in many of the models actually this fact is not taken into account so what we've done for the amino acid or obtained from hydrolysis we use these correction factors to account for incomplete a recovery however the tables in sm do report amino acids analyzed to avoid confusion because otherwise it would become very confusing but the digestible flows of the mino acid that are predicted by the model do include these correction factors and the true protein and the croupin cryptine ratio is estimated from corrected anhydrous amino acids the second point is the prediction the supply of np and essential amino acid so we're being we are using a factorial approach so when we estimate the general flow of property and essential amino acid this is the sum of microbial protein rup and judenal endogenous protein whereas when we look or when we calculate the sum the supply of mp or the digestible flow of essential amino acid this will be the sum of the digestible true protein but only from microbial and rup why we do not consider endogenous protein in the digestible flow well first what are those juvenile endogenous threatening these are like slav cells enzyme mucus and bile that are secreted in the saliva and along the gastric compartment and that will contribute from 15 10 to 15 percent of the crude protein to the mold flow if we look at this crude protein flow it's going to be the sum of microbial protein rup and juvenile endogenous it's there we have to acknowledge and to account for this contribution so when we look at the juvenile flow for essential amino acid we have what is derived from microbial protein which is going to be the microbial cryptine the ratio of tr protein on crew protein times the amino acid composition of the true protein of the microbial and for that we used a paper that we published recently success in 2019 for the rup again this is the rdp fraction times the amino acid composition of the feed ingredient and for the judeon endogenous this is due the null engineers flow times the amino acid composition on a crude protein basis that is detailed in oscapetol but when we come to the digestible flow of np and essential amino acid why we do not take into account the general endogenous flow is that if we have here all the flows of the different fractions actually the general endogenous flow mainly originates from the arterial supply so basically it is not something that is a net supply from the diet it is taken from the arterial blood which is irrigating the gut and this is being used actually to make those love cells to make those enzymes and as such it is not a net supply it has been absorbed previously recycled and put back into the lumen gut into the gut room and sorry so actually we do not occur we do not consider it as a net supply so for the digestible flow of npn essential amino acid then we we have the essential amino acid flow from mcp times the intestinal digestibility that we kept at 80 because we didn't have better numbers and it's like the numbers which which was used before and the intestinal digestibility of our up has been revised is and is in the table so for the prediction of the supply of mp and essential amino acid a factorial approach where we have for the dental flow of cpn essential amino acid the sum of mcp rup endothermal engine endogenous protein and for that actually we were quite happy because in many models actually there is kind of a regression which is applied to the prediction to the initial prediction to fit what's being observed whereas with the model that was developed actually we could just go straight forward with a factorial approach which is meaning that we have somewhat cut better the biology of the digestion across the rumen and for the supply of mp and the digestible flow of essential amino acid again this is the digestible trypatine but only from microbial and rup endogenous is not considered as a new or net supply for the prediction of meal protein yield actually we do acknowledge that this is a non-linear response to supply before in many models there is a fixed efficiency we wanted to go away from that fixed efficiency that we might observe the response to individual amino acid supply and also that the energy supply and the type of energy might have an impact on deficiency of utilization of essential amino acids so we came out with a multivariate equation where initially we tried all the amino acids but we only kept those the supply the predicted supply and at the end we came with this equation which includes an intercept acidity isoleucine leucine lysine and methane the sum of all the other amino acids essential pleasant and essential then we have a square term here which is the sum of those amino acids which are into the model we see a negative term so we have a 8-bit plateau which has been achieved the digestible energy but excluding the protein so the non-protein digestible energy digestible ndf and body weight actually for arginine leucine and turning an essential there was a trend for those coefficients to be significant but that was not really improving the model and these were not significant just trends so we decided not to include them and for phenylalanine chapter fine and veiling uh we considered the data that we had that we had were not adequate so if we look at the result of that actually we can see that compared to nrc 2001 we have gotten rid of the slow bias bias which was fairly important because of this fixed efficiency and here you can see on the observers as predicted and here the residual actually one thing we had to deal with was that we had to work with the data that we had right that were published and with that the equation that was derived we reach a plateau at 3 000 grams of mp which is like 42 kilos of milk 1250 grams of male protein yield and we know that a lot of herds actually have reached a higher uh productivity than that so what we did was developed a term to scale um which is based on what we call the rolling herd average and as you can see this is the initial and then there is a place in the model where you can put the rolling herd average which is the average milk protein yield on kilogram of protein per one 305 days and this will if you want bring the plateau at a higher level to account for the fact that the genetic the management and the environment actually might be different between the herds and actually again we're working with cows of the past but we want to predict things for cows of the future and finally for the protein and amino acid recommendation most of that is being based on a paper that we publish in animal in 2020 so i really want to thank the co-authors of that paper and actually most amount in most of the models we do have mp requirement based on factorial approach which would include curve endogenous urinary mfp sometimes to level endogenous milk proteinal gestation and growth and for the essential amino acid requirements basically is based on a proportional approach which means that we define especially for methionine and lysine as a percentage of the np supply what we wanted to develop in dynasty was a factorial approach and we'll see together how we define protein secretions and accretion the amino acid composition of the protein that or that we deal here with all these or this supply are being used with switch efficiency to yield the recommendations so secretions and accretion so first a question that i've i'm often being asked is why should we only account for secretions and accretion the cow is making much more protein in the day than it's being secreted or gained we'll discuss that the secretions which are the what do they mean and how do we quantify those and accretions so why only secretions and acquisition well to answer that question again we looked at the biology of utilization of essential one rising so if we have to pull a free amino acid into the body it will be used actually to support protein synthesis and part of the amino acid will also leave that pool through an obligate loss or oxidation of excess once the amino acid orange proteins actually might type in two things or these proteins will be secreted out of the animal or they will be on an accretion on a net basis i agree that this is a dynamic process but on a net basis this is the demand which is the gain in body weight or degestation and part of these amino acids actually of this protein sorry are degraded and basically those amino acids are flowing back to the pool of free amino acid intact not degraded and the difference between the protein synthesis and the protein degradation actually we yield here this protein secretion and accretion and we have the net digestible flow which is the net supply that will also be feeding this pool of free amino acid and basically what we want to do when we balance the diet is to provide here a net digestible essential amino acid flow that will balance the protein secretion and accretion and the loss here this protein degradation is important but it is not creating a net demand on the amino acid that we have to provide here because this is just a movement back and forth between the free pool and the essential amino acid into the protein it does cost energy but it doesn't cost protein and if we look at numbers just to have an idea how this is quantified within a cow if we look at the protein synthesis here that we have for an average cow we're gonna have in the muscle in the skin in the liver in the gut and in the mammary gland so all together the cow will be making about five kilos of proteins per day but if we look at how much of that is being secreted and let's say that the cow is not growing is not in gestation well there will be no accumulation in the muscle very little lust through the skin there will be some proteins that will leave the liver again but they will not leave the whole the body of the cow the gut part of that will be recirculated what we will find into the feces actually will be lost and we'll discuss that later and out of what happens in the married gland part of that obviously will be excreted as milk protein so basically the whole body protein secretion will be roughly two kilos compared to five kilo of protein synthesis and basically this is the demand that we want to meet when we balance the diet so we have this curve here we have the metabolic fecal protein we'll discuss that a little bit later as well and milk protein yield and in this nasim actually version we do not consider as a requirement the general flow of endogenous protein and the reason for that again if we come back to the schemes that the scheme that we've seen before we have our little i just put in the miner i said but we have a lot of the mine was it actually derived from the general endogenous flow and actually if it is not digested it will just be um yes or if it's not if it is digested the protein will just be cleaved and individual amino acid will go back into the circulation into the portal vein so this is not a real requirement what is the requirement actually is that if it is not digested and if it goes out into the feces then this is a real loss and this is what we will acknowledge in the term metabolic fico protein so again the net essential amino acid that we want demand that we want to meet it's going to be protein secretions curve mfp mercutio accretion and gestation we'll have to cover as well for the endogenous urinary loss which we can consider as an obligate class and there will be an extension of the excess which will relate as the inefficiency other functions for essential amino acid yes there is plenty of other function for central amino acid and if we talk about methionine for example we know it is involved in more than 100 metabolic different pathways but actually we do not have numbers to adequately quantify this demand especially that in many of those um doubling reaction there is a recycling of the methionine so what is the net demand we don't know really but we have built the model in such a way that if we gain this knowledge it would be possible just to include that into because we work in a factorial way to include that new demand into the requirement to get the recommendations so quickly if we go through the secretions um scarf and scarf is as it's very limited so it is just as presented before milk it is as measured and we have revisited androgenous urinary and metabolic fecal output endogenous urinary we've been through what actually is secreted in this endogenous urinary we're going to have angiogenesteria purine derivatives creatinine and creatine thromotylistine and hypric acid we'll come back to that later what is important to notice that none of these compounds actually is a protein and through the lip review we came to the equation that the androgenous urinary plus actually will be 0.53 um gram of tricotting per kilo by the way which is point zero five three gram of nitrogen per kilogram by the weight metabolic fecal protein we've been talking a lot of the endogenous secretions and the reason for that you'll see later is that the metabolic fecal protein is probably the output which has the highest discrepancy between the different models so with the work that we've done with danielle wallet we label the animal with n15 to track exactly the endogenous secretion along the digestive tract and actually it can contribute to between 20 to 35 percent of the fecal nitrogen and what we wanted to consider in the metabolic fecal loss is that we didn't want to include microbial protein that was synthesized from urea but we want to because it's not a net demand on amino acid but we wanted to include the undigested german microbial protein which was synthesized from indigenous secretion because this is in a demand an essential amino acid so it's always like the pattern is that output creating a demand on the essential amino acid that had been absorbed digested and absorbed and we were calling it mfp but really it's um measured at the ileal level and we had also the ungut contribution so we came with this estimation actually which is related to dry matter intake plus a small effect of the percentage of fiber into the diet based on the work of the ofuelet sendai kettle and navigator what is interesting is how do these updates compare to what's being currently in the field so if we have a cncps an american model the gve oeb system the dutch system in 2018 french system north 4 nrc 2001 and the current revision actually it's a paper that we presented it well three years ago and um we i just updated adding the nsn and we're working to have a larger um measurement you know with more cows but this is just like with an example car just to have a quick glance at how would that compare with the different models and actually if we look at the net protein secretion we have the endogenous urinary here and the metabolic fecal theory all of the models actually are using the swanson except inra which has revised which is very similar to the proposition of the nsm i was saying the metabolic fecal output was something that was very different between the models so you can see here that cncps was really high the dutch system in north four nrc and the nasam proposition and if we put things in perspective again for our example car we can see that mirpatinil still remains the major demand scarf is very limited but metabolic fecal can be still quite important relative to the other losses accretion uh for growth we went to something which is very simple especially that basically this is not a large number for the cows that are being in lactation so it would vary between 13 and 18 grams per day depending you know if if it's uh first cow first heifer sorry first calf effort or if it is second or more per parity and the gestation here any question that was derived which is really giving fairly similar result in terms of net output to note 4 and but up to 150 days of lactation this is not a large demand as well so the net np demand is true protein demand and but then this is for true protein if we want to look for the amino acid then obviously we need to have the amino acid composition of those different proteins so we went through a fairly substantial lit review because the amino acid composition of the output is not needed with the proportional approach that is usually um used in different models again it's relative to true protein as discussed previously for the amino acid that were obtained from materializers we used a correction factor and it's all detailed in nsm so i won't go through too many details but just uh for the androgenous urinary what is interesting actually is the majority of the output in the endogenous urinary is based on non-essential output here we have the current derivative arginine creatinine and creatine arginine cancerous is semi-essential um euphyric acid which is glycine so basically for the net demand and essential amino acid we have to use rather the endogenous urea to give it the whole empty body composition for metabolic fecal protein what we had again it's fairly limited we used what is proposed by oscar which is just gastric we combine that with what has been published by jansmen at all but it is in pigs but it is not that different in is the best that we had and best of the work of willett we assumed that 70 was from undigested juvenile and 30 was arising from the intestine formula protein yield actually again we also went with the dna sequence of the different protein fractions as described in fahren and uh using 15 manuscript we came to this distribution with 82 percent of casein and 70 percent of weight if we look at the essential amino acid composition through these different proteins secretion or accretion what is interesting and it is why we need really to deal with individual amino acid for example if you look at threonine we had a much higher concentration in the metabolic fecal output than in milk protein yield slightly higher for histidine whereas for leucine we had totally the opposite and we also add the opposite for lysine and also the same thing for histine so we can see that the pattern actually of the composition of each amino acid in the different protein differs between uh the different secretions so that's why it's important really to deal with individual amino acids and the different fractions so the net essential amino acid demand is going to be what we've seen in the first section secretion and accretion times the essential amino acid composition of each type of protein that will yield the net essential amino acid demand now which is really the heart of the estimation of the requirements or the recommendation is the efficiency of utilization with which efficiency will these amino acids are being absorbed this mp which is being digested actually will be used to support those different uh functions initially in some most effectual models there was a fixed efficiency for maintenance and for lactation and they were different right so the requirement was the secretion for maintenance divided by deficiency secretion for male divided by deficiency of neon but actually again if you look at biology it might suggest something else so if you look here at the specific amino acid estidine this is a paper that we recently published so we had lowest bean supply an adequate distance supply so the amount that was digested actually really increased when we increase the supply which is what we'd expect mere protein yield here did increase slightly as well when we increased the supply if we looked at the difference between what was digested and what was absorbed in the portal vein there was some room here actually that basically supported the amino acid that the histidine that was needed to synthesize those endogenous protein that will be secreted in the thesis which is mfp metabolic fecal protein which is making sense then if we look at the pulsed liver supply memory uptake and milk output what we can see is that at the lowest edem or adequate std they were roughly identical here pulse liver supply memory uptake milk output the same thing here what it means basically is that there was no plastidine that was catabolized in peripheral tissues which is the difference between post liver supply and memory optic and there was basically no presiding that was catabolized within the memory glance it was all of what was taken on a net basis was secreted into milk what has happened is that all of the histidine that was catabolized was catabolized in the liver there was a large increment here when the level of esteem was adequate so what is telling us is that even if there is a large protein secretion in the mammary gland there is no catabolism of this in the memory gland even if there is a large secretion of nfp metabolic fecal protein into the gut basically all the difference here we could account for what was secreted in the feces there was no room for catabolism there was no room for catabolism here neither so it doesn't matter really where the protein is being synthesized for exportation all of what was oxidized or was removed the next one in excess actually or obviously here might be more it was across the labor so from that we proposed to use a combined efficiency because we might change our mind later but with the knowledge that we have now what should i give a different efficiency if everything does happen across the level for this amino acid and it's the same for the group on the mind was it i took a simple example so basically what we propose to do is to calculate an efficiency which is based on the net demand divided by the supply adjusted what is the net demand scarf mfp bill protein yield and growth and actually i'll show you i did not include gestation because in the database that we had we didn't have this information and the supply adjusted we call it the supply minus endogenous urinary because you remember endogenous urinary those are all nitrogen compounds that are not protein that they are derived from a myosite catabolism but they are not protein so we give to that output an efficiency of one so we had one 920 treatment means in more than 200 studies and if we looked at the mean of utilization of essential amino acid nmp those are numbers that we get and we can see that there was a fairly large variation between the different studies which is making sense because we had some that were feeling pretty nexus no there was not enough protein but what is interesting is to look at the distribution you know we can see that as we've seen the efficiency of hybrid efficiency of the steam was slightly higher than it was for the efficiency of phenylalanine but we can see or we can see that there was a large variation it varied within an amino acid it did vary between amino acid so we do need a reference value to have like a target efficiency that this is what we're going to try to reach to fulfill the requirement or the demand of a minor acid for that for that level of production so we define the target deficiency based on the relationship between the protein secretion and accretion and deficiency what we did basically we made a graph where we had all the the sum of protein secretion and accretion and then on the x-axis we had the efficiency and then it was a quadratic equation so with the first derivative we could calculate the optimal efficient uh the optimal deficiency and um we are just we had i had to see that we adjusted like some that were really low like vanilla aluminium training with the very limited deletion studies that were conducted with these studies and we had for now to assume that the energy supply was adequate so these are the target efficiencies that we propose to use for the different essential amino acids so we can see that again we slightly increase what we observed from the relationship for vanilla enemy this is a bit low for now we didn't want to raise it too much but there will be some options actually in the nasam software where these numbers could be changed so this is the first shot that we have at this type of approach so we might need to fine-tune it in the future as well so basically if you look at the recommendations for essential amino acid well we have the protein secretion and accretion times the essential amino acid composition of these proteins divided by deficiency all that together is leading to recommendations so if we look more specifically for amino acid endogenous memory we said that we have an efficiency of one we apply the target efficiency to scurv mfp mp1 and criterion growth and gestation we give an efficiency of 33. for np we've seen that the target efficiency is 69 so this is the same equation and we just put the target efficiency here i'm sorry [Music] so again if we compare with the the ampere combination from the different models as we've seen before because before it was the net output now if you look at the mp recommendation we can see that the difference between different models and in nsm is not that high because in the same as in the efficiency for utilization of the amino acid for the endogenous scenario is one whereas it was 67 for the other so when we look at the recommendation difference is not as large the same thing the difference is not as large as well between still important but not as big because cncps and an rc have an efficiency of one for mfp whereas we have different efficiencies here for the uh of the models but still the american models do have a fairly high recommendation for mfp and just to finish if we want to look at why actually we do believe that it is more appropriate to go with a factorial approach than a proportional approach for essential amino acid i'm gonna use extremes right but let's say that cow is making like 20 40 or 60 kilos of milk at 3.1 percent of sorry true protein eating 25 kilos of of genetic intake ndf uh the cow is not just eating and is not um growing either so if we calculate as we've seen before before the recommendation for methionine we have here the secretion true protein for the essential amino acid endogenous urinaries curve and mfp the methane concentration in each of this fraction endogenous generates curve so if we multiply that with that we obtain the secretion of methionine and then if we use the target efficiency which is one for endogenous urinary 73 for scurv and mfp so this is the methane recommendation for the non-productive function of endogenous curve and mfp now if you look at our car which will make like 20 40 or 60 kilos of milk this is meal pretty meal here 620 1200 1800 times the amino acid or the methane concentration in milk that will be the secretion of my fine in milk here target efficiency 73 so that's going to be like the secreted the recommendation to support sorry the milk protein yield with those different um level of production if we add the non-productive function that we've seen in the previous slide this is the total methane recommendation but if we continue that and if we estimate based on the same principle the mp recommendation here for milk we add what's going to be needed for the non-productive function then if we look at what would be the percentage of methionine relative to mp we can see here that this percentage does increase from 2.2 to 2.5 and this is making sense because mfp actually doesn't have as much methionine into its protein as those milk so when we increase the ratio of mfp well here i assume that the cows were eating the same amount as well it's simplified example but this is showing that we might have some misleading information when we only use a proportional approach we also propose other usage for the efficiency of insulation of essential amino acid if we have a predicted supply and an expected mid protein meal you know we have our herd and this is what we want to do we can calculate a theoretical efficiency of utilization which is going to be again the sum of this of the um scurv mfp networking of growth divided by the adjusted supply and if we had gestation we would just add here with 0.33 of efficiency actually if this theoretical efficiency of essential amino acid is much higher than the target efficiency for specific amino acid that might indicate that there is a short supply for this amino acid we've seen for example in the previous slide the target efficiency of methane was 73 percent right if i have a diet x and i have a new protein expected y and i calculate what is the efficiency and if i get the efficiency of my finding that i would need to support that level of protein with that diet at this intake if the efficiency is 80 or 85 i might just think probably that might be fine here won't be high enough or if it's like 63 you might say well if i name really don't have a problem with that i need to look at other mine why is it so we can really look at individual and mindlessly like that and relative to the target deficiency determine if we think when there might be a shortage or if there is like plenty and we might target something else so recommendations for essential amino acid and mp again true protein secretions in accretion times the essential amino acid composition of the protein divided by deficiency and utilization of essential amino acid rnp this is yielding the recommendations that we do have in sm so in conclusion we really worked hard to develop a factorial biology biology-based model because having it that way it should be easy to add new knowledge it is it is for all the essential and mind-wise it the target efficiency might evolve especially with energy supply actually the only thing we could do was with was with a adequate supply of energy but you know this might evolve in in the time and also we have a multivariate equation to predict milk protein meal with a scaling for the herd production on that i do thank you for your attention and i'll be really happy sean to answer the questions that you will have put together thank you very much thank you very much dr lapierre um superb presentation really really good and um glad to see lots of questions um let me um ask the first one you know looking at i mean you did some comparisons on um um sort of metabolic fetal between the systems etc have you compared the impact of um the total supply of metabolizable protein and an amino acid um requirement between nrc 2001 and nasa and 2021 and what what's the overall outcome and differences actually i must say that we are working on that we we have not completed that study yet but so far uh in terms of the prediction of the supply of essential amino acids these are fairly similar so we were as i was saying we're quite happy because we went with the totally factorial approach so it's just the sum of and cp plus rep plus student loan indigenous for the juvenile flow of essential amino acid and having just that without any adjustment a regression adjustment we came to fairly similar result as as we did with uh 2001 actually we are working to see how these changes that we've made might affect the prediction of mrt neil for example and but we haven't done any so far thank you i think it answers that question another question here if you're working with um supplemented essential amino acids i guess lysine and methionine um does that impact your your net efficiency number for that you know i'm is are we bringing the net efficiency down by supplementing with um supplemental amino acids well when you will be doing the calculations actually with the supply of essential amino acids um would the supply be from feed intake or just by room and protect the mine sorry would be by the diet would it be by rumen protected amino acid actually this will be considered as the same so maybe it is when romantic amino acid might be really useful is that if you check all of your diet and you're really below or right on for the efficiency of your diet compared to target efficiency but you see you see that deficiency of istidine for example is 95 or you see that the deficiency of methionine is 82 or you see that lysine is uh i don't know like 85 then you might think yeah might be then if i'm using iron protected amino acid then i add that to the diet i redo the calculation of the efficiency and because i have increased the supply that will decrease the calculated periodical efficiency down and then having this efficiency closer to the target efficiency will should improve the diet but it might work the other way around right for example if you have a diet which has a lot of um corn for example then you might calculate that you have a very high efficiency of lysine so you might decide well okay let's add some soybean meal or you know so it can help also to play with ingredients it works for all different sources of amino acids thank you i think that answers that one another question here do you um and i guess you may have answered this previously but have you compared this the requirements and supply against some of the other systems i know you published a paper a couple of years ago but have you compared against the european systems actually besides what we have published uh we have not done anything which is being published but actually we have a student which is finishing his phd thesis and he did compare different models which was very interesting is that it was using on-farm data so data that were collected from commercial forms and we're it's just um something is this is now so we should have those published uh fairly soon as well well we did compare different uh systems including some of the european systems uh inroad and dve etc yeah actually we did use and um and not four as with dve the problem that we had actually is that we faced in also in this paper that we published in 2018 is that there are some ingredients actually that are not in the dve and we try to substitute and really we couldn't make it work with some of the american north american ingredients so it was a little bit complicated yeah thank you uh so someone must be sharper someone's asked a question here uh i note no efficiency for arginine use um is there a reason for that yeah actually arginine is very special that we call it an essential often but it's more like a semi essential in that the cow is making some but we don't have a clue of how much decal is making so it's very tough to determine what would be a target efficiency when you know what will be the exogenous supply but you don't have a clue of what is the indigenous and another point also which is interesting with arginine is that it is very much required to synthesize the the proline into the milk so we're finishing some studies currently where we're looking at that because for like if i'm looking at the the need for leucine right so i'm looking at the leucine into milk but if i'm looking at the need for arginine i cannot just only look at the arginine into milk because there is a large portion of the proline in the milk which is made from arginine so how much of that is supplicate you know other other minerals that can be used for so we didn't have really a good clue on the output we didn't have really a good clue on the input so we decided that we were better off not to um put any numbers on arginine so far i know that some companies actually they are really keen on arginine but uh we pre we prefer not to put our head uh our fingers and uh to be tapped on we need more information and actually it's true that that's maybe i should put that on if there are people working on different one through a minority is that we we have a fair bit of studies where all of the amino acids will move together we have a fair bit after this where we have one of mine wise it or not you know i did but we're really lacking some those study effect where we have the same amino acid at different doses being supplied and we thought that actually it's very tough to have a through inference if the effect that we see is a combination of all the amino acids if it's only one amino acid and when would you reach you know when would you reach a plateau when you have one point here and one point here it might not be a straight line it might be something which goes that way but as long as we only have two points you know we don't know really where is the inflection point so we we really really like those type of studies where we have graded levels of different uh also not only lysine and methionine but it's been a little bit more but other mine was it actually might be interesting it all depends also what is the the basil diet right it's uh and this is different between europe and uh america it's different between canada and united states as well you know we have some areas in the northern part of quebec where we can't grow corn for example but there are so many studies that are using corn that uh we have to face that and maybe the breed as well this is one thing that you know we're also facing is that a lot of the studies are conducted with holstein but we don't know that much about small debris different breeds so that might be something interesting as well to get more information to be more accurate i guess this will be the last the last point of the day yeah we are reaching the end of this uh conference uh i understand dr lapierre that you are already volunteering to come again in 10 years to explain uh i don't know what will be the acronym at that time and he's 31 or 20 41 well hopefully hopefully it will not take 20 years like the last time but thanks very much i think sean we we can really thank dr lapierre a lot for her contribution for a first explanation of this new system [Music] we had a lot of people from europe who were listening to you and are really keen about understanding more and digesting more what you have said so uh it will be available as a um how do you call this um well we will we have recorded this webinar so we you can listen to it again and in the meantime i would like to thank everyone thank uh dr la piller sanctioned richards for his sharp questions and thank the audience for his participation so i wish you all a very good day thank you thank you very much