 Hello, everybody. I would like to welcome you to the seminar on the file inputs seminar on analytical data. And this time we are going to talk about fat and fatty acids. I would really like to welcome all those who are already connected. And as far as I can see, we have already more than 120 participants. I hope that this is a new series of webinars. And the idea is that we will talk about the analytical method, how to present the data and then to present the different techniques. So I'm looking forward to the presentation and the discussions that you will have. As the participants, you can enter your comment in the chat box and your questions as well. So I would like to introduce you to the first speaker, who is Srimulavi Sampan. And he's going to talk about analysis of fatty acid steps, critical steps and potential errors. Srimulavi, you have the floor. Can you please share your screen and unmute yourself? Hello. Yes, we can hear you. We are looking forward to a very nice presentation. So good morning all. Today I'm going to discuss, I'm going to give a talk on critical steps and potential errors in analysis of fatty acids. So my name is Srimulavi Sampan. I graduated from PhD and working here as a research associate in food chemistry division. Srimulavi, National Institute of Nutrition. Previously I worked as a scientific officer at SRM Research Institute, SRM Institute of Science and Technology. Thank you. So today I'm going to talk about, this is the outline of the topic that we are going to discuss. First, what is fatty acid? Second one is analytical techniques used for fatty acid. It puts samples, quality instruments and quality control. Sample preparation, like fame to fatty acid conversion. Then for the GC column selection criteria, and then peak integration. Challenging during fame conversion, doing fatty acid method analysis. How to work on the challenges, finally the conclusion. So first what is fatty acid? Fatty acids are based on the carbon chain, based on the carbon, based on the number of the carbon, it can be categorized short chain, medium chain and long chain. Where fatty acid are divided into two like saturated fatty acid or unsaturated fatty acids. Where saturated fatty acid without double bond in the carbon-carbon atom. Whereas in polyunsaturated fatty acid have double bond, unsaturated double bond in the fatty acids. Fatty acid or carboxylic acid with a long aliphatic chain whether it is saturated or unsaturated. Then there is a two like cis double bond and trans double bond in polyunsaturated fatty acid. So what are the techniques available for analysis of fatty acid? There are four techniques in nuclear magnetic resonance spectroscopy. Nuclear infrared ray spectroscopy, liquid chromatography and gas chromatography. Among the four techniques, gas chromatography is widely used for analysis of fatty acids in food samples. When compared with other three methods, they have its own disadvantage like low sensitivity and need a relevant model library for high and the cost of the model is high and the poor sensitivity. Like the repetitive brain is not that much good. So coming to the gas chromatography for flame analysis, there are two, two, two like gas chromatography equipped with the flame ionization director, which is high accuracy, high sensitivity, less natural consumption and easy to operate. Gas chromatography in mass spectrometry or another gas chromatography technique where quality and quantitative work we can do. But when compared to the GCFID, the GCMS has 20 fold higher sensitivity than GCFID. But for food composition analysis, especially fatty acid GCFID is essential. So this is the typical schematic representation of the GC gas chromatography, where consist of like five components. Number one is like carrier gas where this is the carrier gas where this gas, the carrier gas injector core, column over temperature, column over detector and the FID flame ionization. This is the FID. So exactly like one meal of a sample, once we injected into the column, the carrier gas will help to carry the injected sample which it is in volatile like that. The injector core, the temperature will be, temperature is high. It will volatile and it enter into the stationary phase of the stationary phase column. Then it get separated in the column and eluted in the detector or the detector get eluted. The compound will get eluted. Then the detector will ionize the, the flame ionization detector will ionize the separated fatty acid and you will get the chromatogram of the, chromatogram based on the response of the collected ions. So this is excellent in separation and computation of fatty acid. Especially like, especially like, especially like for fatty acid analysis, this is the most efficient technique for, most efficient technique. So next we will move on to the quality assurance and quality control where we, quality assurance by purchasing a standard mixture of, we can purchase the standard mixture from companies and then we can, we can do the, we can do the linearity, accuracy, precision and everything with the help of CRM. Why we need this internal standard hypertechnoic acid? For, during sample preparation process, whether any loss in the, any loss in the flame by using this C 17 as internal standard we can, and normalize the loss of the query and then also we can calculate the each individual fatty acid which is present in the sample. So, so mostly this SRM issued by National Institute of Standard and Technology. So this is the sample preparation steps for analysis of fatty acid. So this is like, we take the sample, saponification by a KOH and methanol, followed by the acid hydrolysis, then acid catalysis, then collect the sample, collect the X-ray layer and the cost nitrogen and inject into the FID of the sample. So next the GC column selection criteria. What are the column selection criteria available? Like we have to first look into the stationary phase where the compound will get separated based on the packed material which is present in the column. And column ID, column inner die off should be like, point if the column inner die off if it is less than point, point to, is point to by the peak shape and peak width and all it will be very accurate whereas in film thickness also like will help us to separate the compound. Column length will, if increasing the column length, the resolution of the peak separation also very good. So for fatty acid, for fatty acid methyl ester analysis, we need column like SP2560 and CPCL8820, especially in our lab we have observed like 37 effect film mixture by using SP2560. In that column we faced like, but we faced difficult to resolve the cis and trans C81, but other all the compound are eluted like more than 70 like other fatty acids we have except we have separated very well. Even in CPCL88 also resolved all cis and trans isomer is both column are very good for separation of 37 film mix of a standard. So here we can see this is the standard like promotogram of two different columns which we have performed in our lab. So here in 37 film mix we can see all are very well separated in this column. And CPCL also for, for titanium fatty acid this column is very efficient. But only thing is that that C80 is to one cis and like latic and vasinic very difficult to separate in this column. But for in CPCL88 the separation of like separation is very well separated of all the compounds, all the fatty acids which we have in the standard. So okay we are running the samples and we processed we get the results from the instrument. There are different types of peak integration techniques available peak identification technique available. Like we should first construct a baseline and then we have to identify the starting and ending peak of the compound and find the effects of the peak and measure the peak area. So the different types of base head construction are there base to base construction, base to value construction, value to base construction. So that whatever the process and the open result where we can by taking this single open icon we can open and do all the peak identification and peak integration all the things available in here. So here you can see like two different standards like the red highlighted or the 37 mixed standard and the blue highlighted are the sample where it is perfectly matching with the RP. So each compound we can find the area and everything. So this is the typical 37 mixed standard. This is the following parameters which we used for separating the 37 pane. This is the CPCL88 column. We can see how distinct how very very separated of this column. This standard the same in the same sample chromatogram using CPCL88. If we if this is the result of which we open from the GCMS like coconut oil. We can see the lower it has to see two of these two zeros the predominant and whereas in fish we can see the DHM DEPA and also the matrix of the sample. Here the number of peaks are very like number of peaks are number of the peaks are less. Whereas in the this matrix fish and milk are high. We can see how many number of patios are available in the fish and these are all the things we have to separate very well. So we need a suitable column so that we can separate. So this is the same sample chromatogram of a sample chromatogram of a plant put using S32560. Here you can see all the like all the patios that are similar in trend. Rai-ri-sil-lithium-so-roof-t-first all the patios are excellent. This is the sample chromatogram of fish and shellfish where here we can see in fish red squid crab all have this DHA DEPA. Whereas in oyster there is a linonica very it is a very like it is a different among the fish and shellfish. By using this column we have separated the patios. This is the sample chromatogram of boat organ using SP2560 where here we can see the results later. How the spleen and kidney where the erythritic acid or ecotrimic acid are more whereas the other like palmitra this C16 all the samples we have similar trend except in spleen and kidney specifically it is there in the sample. So what are the challenges during analysis of pain is like when peaks are merged we have to separate by changing the optimum parameters like column oven temperature and ramping everything. And routine like peak merging and retention time shift will be there. So we have to monitor and how to rectify that issue and we have to see this all the problem like peak trading, peak point and some unidentified peaks will be there how to check that point and then we have to look there. So for that how to overcome the challenges which we face during the sample preparation and analysis. So first we have to look this column and then second is like for separation of mill tripping by changing the oven temperature program. So we can separate here we can see the how the program temperature are ramping and this is the typical parameter setting images and whereas any continuous injection of more than 100 samples or more. So it will be this liner and inlet portion of the GC column and outlet portion of the GC column we have to routine we have to check and monitor and if any problem is there we have to fix it correctly. So overall like gas chromatography is well established analytical tool for fatty acid methyl ester analysis input sample and AYAC method 996.06 and that methylation are efficient for fatty acid to fatty acid methyl ester conversion. SP2560 and Cp688 column are very good separation of 37 pin mix and cis trans isomers in Cp688. So throughout the experiment procedure we have to follow the strict QA quality assurance and quality control. So that there will be a reduction in the gap and routine monitoring and maintenance of analytical instrument is needed to avoid the potential gap. Thank you for the very interesting presentation. I have learned a lot about analysis and what of fatty acids and what to take care of. I think we will have all the questions and answers at the end. So can you please stop sharing your screen? Yes. So thank you very much. All the speakers who will not speak may I ask to mute yourself? And I may ask now our Anatan to give us a presentation on how to present fatty and fatty acid data per percentage total fatty acid or per 100 gram total fat or per 100 gram edible portion on fresh made basis. Anatan you have the floor. Thank you Dr. Root. Is my screen is visible? Your screen is visible and you are visible as well. So we are very much looking forward to your presentation. Giving to Anandal because various participants from across the globe has participated in the webinar. Am I audible Dr. Root? Perfect. Okay. Thank you. Just for the confirmation before starting. So I am going to talk on this topic, the presentation of the fat and fatty acids in different forms like the percentage total fatty acid or per 100 gram total fat or per 100 gram of edible portion on fresh made basis. As my colleague explained how to estimate the fatty acid, what are the different techniques are available. So I am just going to touch upon the presentation of the fatty acid in different forms. You know the fatty acid is nothing but mainly three, four different forms are available especially the free fatty acids or the phospholipids. So if you look at all these fatty acids which have mostly the non-polar aliphatic chain with the little polar characters. But this kind of information, you know the polar and non-polar are very, very important for various biological functions especially for maintaining the component of cell membrane and some of the fat like the fat is used as an energy storage component. Also some of the fatty acids like a cholesterol used as a precursor for other components other molecules like the cholesterol used for precursor for the vitamin D. So as you seen in the previous presentation, this is a chromatogram which we get out of GC, this is a standard chromatogram and similarly when we inject the sample, we will get the sample chromatogram. So what we will do with this chromatogram? The end of the chromatogram, you know the post chromatogram play, we have to identify the peak as Dr. Murli said, we have to integrate the peak properly. Then after identifying the peaks then we will get, we can see in the last column the percentage of area depending upon the percentage of area then we will identify the peak, the fatty acids corresponding to the fatty acids. Then based on that, we will report this is the percentage of fatty acid fame in the total fatty acid fame. But if you look at various literatures as you see in the previous slides, the predominantly they are expressing in terms of total fat or the total lipid or per total fatty acids. Where we need essentially, it should be expressed in terms of per 100 gram of edible portion which is very important where we will use this denominator in terms of whenever we wanted to calculate the fatty acid intake from the fat without any error, without any mistake. So in order to get this kind of information, how to convert the fame fatty acid methyl ester to fatty acid. So we are going to see in detail, you know the converting fatty acid into fatty acid methyl ester is very very important step in the analysis of fatty acids. Particularly when we analyze the fatty acid by using gas chromatographic techniques because there are so many advantages are there that I don't want to explain now. But using the appropriate method for the conversion from fatty acid to fatty acid methyl ester, then after that appropriate method to convert the fame into fatty acid is very very important. Where I just draw the attention from the literatures initially where I have taken this conversion factor how we have to derive for the example here is egg lipid. So the egg lipid, its identified lipid fractions are essentially three that is tritleys rights, phospholipids and cholestidols. So among the three lipid profiles of fractions 65% is a tritleys rights, then the 29.6% is a phospholipids. Among the phospholipids, the lecithin and the cephalin is the majority of the phospholipids where 24% and 5.6% is reported and then finally is a polyspera. After identifying these fractions of the fatty acids then we have to look at the real estimation of fatty acid in gram lipid fractions. Where you can see 95.6% of the gram fatty acids you can see in the tritleys rights similarly 70.8% in the lecithin and 75.6 gram in the cephalin. So when we multiply the weight percentage of total lipids with the gram fatty acid in that particular lipid fraction we will get the gram fatty acid in that particular total lipid. So this is the conversion factor for each fraction. Then when you you know some of all these individual fractions the conversion factor where you can see here individually you just multiply the weight percentage of lipid fraction with the fatty acid and then we will get the fractions like this. And this particular factor will be used as a conversion factor where we have to where we can apply to get the fatty acid from the total fact. So similarly one more example where you can see for the beef and here also there are apart from apart from triglycerides there are many phosphoryl molecules have been fractionated and their respective percentage of total lipid fractions and estimated total the fatty acid in particular gram lipid fractions when you multiply both the characters you will get gram fatty acid which will be used as a factor for the conversion of this particular food you know the fatty acid from the total fact. So these kind of applications so these kind of conversion factors have been extensively worked and it has been reported in our Bible of our food composition you know the Greenfield Southgate book where you can see where different food groups with the conversion factors. But not only this later on you know FeOE in foods Navak et al they went in depth you know because in this in this table where the fish have been given only with the two different factors only with the lean mass and the fatty mass without mentioning the fat composition. So FeOE in foods further went in depth to analyzing to differentiate with the for depending upon the fat composition then they have come to the conclusion that so we can modify this factor where if we have the fat content more than 0.55 gram so this can be used for different fish like the fin fish using the 0.933 factor minus with the 0.143 with the total lipid. So that the derived value can be used as a conversion factor so similarly if it is less than 0.55 lipid content so are the fat content so again the Navak et al they have identified for the further investigation they made to find the different conversion factors so these are all the conversion factors where we can use exactly to find out the fat to fatty acid. But apart from that you can see the literature expressed with the different expressions like the fatty acid percentage of fatty acid or the percentage the total fat gram per 100 gram of total fat gram per 100 gram total lipids in fact the last three is almost similar but whatever it may be as we saw in the previous slide everything it needs to be converted into gram per 100 gram of edible portion that is one of the important Agenta or one of the important factors so we need not bother so it's very easy. A few input guidelines are available to convert these different factors or different expressions into gram per 100 gram of edible portion so I am going to I am going to explain some of the few examples because I cannot cover all the calculations in the presentation. I just wanted to take importantly the few calculations where I just wanted to explain the initially the conversion of the lipid fraction from percentage total fat to lipid fraction as a gram per 100 gram. For this the required data is we have to have the lipid fraction as a percentage of total fat with the fat in gram per 100 gram if we have these two data we can apply this formula where so in almost all the formulas we are going to convert the gram per 100 gram of edible portion unanimously okay well I have taken the formula few few few applications so here if you get listen may I interrupt you can you put off your calendar please because if not we cannot see the whole slide. So when we have these two different data lipid fraction and the fat data when we multiply with these two things and then we will get you know the end the gram per 100 gram of edible portion so this is an example for the chicken egg. I don't want to take much time where we wanted to look into the real the problem or where we wanted to have a little more time to convert the data we can go directly and this is another example where you have to convert the gram per 100 gram total lipid to a fatty acid as a gram per 100 gram of edible portion. Here also you need individual fatty acids as gram per 100 gram of fat and it's a fat content if you have these two different data we can use this formula for example in this pipe perch fish where the 16 is to 1 and 7 is a 0.4 gram in the particular fat and when you have the fat content as a 1.3 you just put it in the formula you will get a 0.0005 gram of this particular fatty acid. You can put it in 100 gram of edible portion then if you have other you know different factors like the you wanted to convert from percentage of total fatty acid to gram per 100 gram of edible portion in this case if you have the total fatty acid you know the fatty acid the total fatty acid fact I FACID then it is very easy and if you have both you just to multiply with both and then ultimately you will get the value but the problem is if you don't have the data FACID if you don't have the data there we have to apply the conversion factor you know initially we have to convert the fatty acid into total fat where for this also it is importantly required the individual fatty acid as percentage and then the fat content and conversion factor and this is a formula to convert and these are the example where we can take the meat chicken meat and the 18 is to 1 is 26 percent of total fatty acid and the fat content is 3.3 and the whole three conversion factor is 0.945. So, when we apply all these things using this formula then this particular C18 is to 1 will be converted into 0.811 gram per 100 gram of edible portion. So, as we saw in the previous slide so this XFVA can be obtained from our the food composition book readily and similarly if you have if you are not having the total fatty acid for fat or food again we can convert into the fat into convert into fatty acids that can be multiplied with the fat then ultimately you can you know you can estimate the individual fatty acid as a percentage of fatty acid into gram per 100 gram of edible portion. It's very easy so where we can take directly the fatty acid conversion, but so this is the exact the calculation where it will be continued from our GC analysis you know the previous presentation also we tell it to mostly with the fat gas chromatography analysis where we will estimate only the fatty acid methyl ester. So, once the fatty acid methyl ester we did we get from get out of GC this needs to be converted into fatty acid and that too it's a gram per 100 gram of edible portion. So, this involves three different steps the first thing is we have to convert the methyl the fatty acid methyl ester into the particular fatty acid by applying the Shefford factor. It's a Shefford factor is nothing but the molecular weight of the fame divided by the molecular weight of the particular fatty acid individual fatty acids divided by the molecular weight of fame. So, you will get Shefford factors. So, after converting this is a fact the fame to fatty acid then it goes to the another the formula where we have to apply the the fame with these to be converted into the fame into you know the individual fame individual fame with multiplying with the Shefford factor to get the next value. And this value always will be a lesser than 100 where I just to show you the excel sheet where generally we use to convert for our regular analysis and that will be very easy to understand for you. This is the first step we have to convert the fame into fatty acid using the Shefford factor essentially. The second step after converting this this individual fatty acids will be multiplied with the the sum of the individual fatty acids. And the third step is we have to use our the fat content estimated fat content and the conversion fat fat fatty acid to fat conversion factors XFPA in order to convert the complete the fatty acid total fatty acids into the fatty acid per 100 gram of edible portion. So, so these are essentially the three steps involved to convert our the fame to fatty acid in 100 gram. So, just I'll show you sorry. Yeah, this is the sheet where I just wanted to explain. This is our the individual fatty acid methyl methyl ester for particular samples where you can see the C 14 is to 0 like that is goes and as for our fatty acid composition all together it will give 100 as a percentage. So, when we convert this methyl ester using the Shefford factor and that will reduce it to as per the you know the factor and that total it's supposed to be lesser than 100 it generally it will be around 95. So, after that so the this sum needs to be used to convert this individual the fatty acids in the second step where we have to multiply this one in order to get this second you know if it is a this particular 2.68 in 95% or 90.058 what will be the concentration in 100 in 100% so this is for the total fatty acid. So, like this after converting if you look at again this will become 100 then by multiplying with the fat content with the fatty acid conversion factor ultimately you will get the fatty acid in milligram per 100 gram of edible portion. So, sometimes if you wanted to convert the dry matter to you know on the fresh white basis so you have to have your moisture content and then any particular the nutrient in this case the fatty acids. So, directly you just to take the dry matter by subtracting the 100 with the water content you will get the dry matter and if you check the value for that particular dry matter what could be the value for the fresh white basis it is a without water. So, ultimately you will convert the dry matter or whatever the expression express in terms of dry matter will be converted into the fresh white basis or the edible portion also. And there are some suggestions which is you know suggested from the inputs guidelines I have taken most of these conversion factors on the calculations from the inputs guidelines. The main suggestion would be when we express the data in terms of per 100 gram of edible portion always the quality of the data will be good and it easy for any kind of further studies like the fatty acid intake or similar kind of studies. Then the approximation if the value for the total fat is not available for the particular food or the conversion factor is not available for the particular food which can be taken from the similar foods. But it will be the approximate value but it can be recommended to take and always the final slide what we saw you know the conversion of whatever the expression given in the dry matter into the fresh white basis or the edible portion is always advisable for more applications are easy to understand by other food composition the followers. So, with this, I would like to thank FAO in foods for given this opportunity to present this particular topic in this today's webinar. I have acknowledged I would like to acknowledge especially Dr. Bruth and FAO in foods for the wonderful guidelines provided for you know the converting the data from different forms to uniform form. And I also have referred Bible of food composition data for this presentation and apart from there are some literature as well. Thank you so much one and all for your kind of attention given for this presentation. Over to Dr. Bruth. Thank you so much and that was a very nice presentation and I have even learned a lot more on how to do the fatty acid conversion conversion. Could you please stop sharing your screen so and again I would like to tell the participants. If you have any questions put it into the chat or in the question and answers. And after the presentation of Anna, we will we will come to all your questions and the presenters will will answer them. So, with this one, I would like to give the floor to Anna Vincent. And she will talk about the attribution of inputs tag names to find and better at it, the principles and challenges. Anna, you have the floor. Lovely. Thank you. Let me share my screen. Is that sharing for everybody? Not yet. Yes, we see the first slide. Excellent. And we can hear you perfectly well. Excellent. I'd like to say good morning, good afternoon and good evening to everybody depending on where you are in the world. I'm Anna Vincent and I'll be talking today about the attribution of inputs tag names to fat and fatty acids. Give me just one minute and I will work out how to move my presentation on to the next slide. Here we go. So just introduce myself. I'm Anna Vincent. I currently work at Food Standards Australia New Zealand in the food composition section team. We have a couple of food composition publications. Osnut, which is our tables for Australian nutrition intake surveys. And the Australian food composition database, which is our reference database. I've previously worked with FAO. I was a consultant with Ruth where the major piece of work that I worked on was the food composition table for Western Africa. So I'll start with an introduction to inputs tag names. What are inputs tag names? They're short combinations of letters and numbers. We use them to identify components in food and ambiguously. And the most important thing is they allow exchange of food composition data. So they're really specifically targeted for food composition purposes. And I know there's lots of naming systems for chemicals for fatty acids and for components for lots of different purposes. And so this is the one for food composition. I've picked out a couple of examples. First example is vitamin A definition of vitamin A is a tag name is calculated by the summation of the vitamin A activities of retinol and the active carotenoids. And so you can see that's definitely a food composition tag name because vitamin A doesn't exist as a single component as a single chemical entity. But obviously vitamin A is of interest to us as a component. We want to know the vitamin A content in a food. And the other example I've picked out is AAE8, which is the sum of the total essential amino acids, which I've picked to give you an example of a tag name with a number in it. You can find in foods tag names published at the input website. How to use tag names. So key thing to recognize when you're using tag names is that tag names differ if there are different analytical methods for the component that return a different result. So one tag name exists for a component if there's only one method of analysis or if different methods of analysis provides very similar values for the component. Several tag names exist for component if analytical results are method dependent. And so for us in this presentation, the most important one there is the difference between total fat and total fat derived by analysis in continuous extraction. So the tag name fat and the tag name fat CE. We also have tag names where that we can apply where we don't know the method was. And so in this instance, if we don't know whether it was fat total or it was fat total derived by analysis using continuous extraction, we can apply the tag name tag name, but we don't have to assign the incorrect one. So basically we can say we don't know what it is so we know in future when we come back to that data that we didn't know what the method was. Key point is that data of different tag names cannot be directly compared or combined. So if you go to the input website to have a look at the tag names. The website will include the following information for all of the different tag names. It will have the tag name itself. And so the example I've got up is F 18 D one. It will have the name or it will have a descriptive definition. So in this case fatty acid 18 one. It will have the synonyms, and it will tell you a selection of tables in which you can find that component. So I will point out something key. When you look at the input website the tag names will have a unit, but actually since 2003 the units are no longer part of the definition of the tag name. So when you're looking at tag names of fatty acids and when you're applying tag names of fatty acids, you'll need to define and clearly state the units that you're using. And when you're looking at data tagged by somebody else, you'll need to double check the units that they have assigned to the data. And so there are two key groups of tag names that are of interest to us. One is the tag names for total fat. So that's including triglycerides, phospholipids, sterols and all the other related compounds. And then we have a selection of tag names for fatty acids only. And so they can be for individual fatty acids or they can be groups of fatty acids or they can even be total fatty acids in a food. I'm going to talk about total fat today because total fat is quite a common component, quite an important component. The big composition is one that you will come across quite often. It's included in most food composition tables and databases. It's on most food labels and it's used in calculating the energy contents of food. So as I said earlier, the analysis of total fat, the results from the analysis of total fat is method dependent. So the two most common are used to find tag names for fat and fat CE and one where the method is unknown. There are a range of other less common methods and expressions of fat. For example, one I've got there, fat and LEA. So you can have a website for that. I just wanted to put it in so that you knew that fat, fat CE and fat weren't the only tag names. They're just the most common ones, the total fat. So I've got a summary here of the key tag names for total fat. Fat, the tag name FAT, fat is the highest quality or preferred one. So it's total lipid in the food. The method is extraction is using a mixed solvent extraction. And so that is the one, that's the data, there's the highest quality. Fat CE is total fat derived using continuous extraction. And so the comments for that in the tag names are the SOC method has often been used to analyze for total fat using continuous extraction. And this method tends to underestimate the total value of a food. You often see it reported in scientific literature as crude fat and the general understandings that it underestimates fat and cereal products. Depending on the application, this data is okay to use. It might be acceptable for non-serial products or where fat is not available. In various in-foods food composition tables, we have used fat CE where that's the data that's been available. And I have a slide later on to show how we market in our food composition tables when we publish it. And fat, where the method is unknown or it's variable is obviously the lowest quality because they're not sure of the source of the data. So publishing total fat. When you're publishing total fat data, it's important to make it clear to your users which total fat tag name is being used and has been applied to your data. So I've looked at some recent publications from FAO includes recent food composition tables. And each of them we've had a combination of fat and fat CE data. And we've highlighted in different ways. So for the West Africa table, we used fat CE where we didn't have any access to data that was have the tag name fat. And we've highlighted that fat CE data in the square brackets. In you pulses, the majority of the data were fat CE. And so in that case where fat data was available with a high quality data was available, it was included and indicated with an asterisk. And in you fish fat data was preferred, but fat CE data was used when there wasn't any fat data and that was indicated as an asterisk. So that's the other total fat tag names. And so we'll move on to the tag names for individual fatty acids and total fatty acids. So the key one is fatty acids total, which can be calculated from fat and from the fatty acid conversion factor as explained in the last presentation. And we have a tag name X F A and that's for the fatty acid conversion factor. I don't actually think it's published yet at the infoods website, but we have used it in FAO infoods publications. So it's a commonly used one. The fatty acid conversion factor is the proportion of total fat that is fatty acids and varies by food. The published fatty acid conversion factors are available as as discussed at the Bible, the food composition Bible Greenfield and Southgate. So then we move on to different tag names for groups of fatty acids. And so these are the most common ones that you can probably come across in food composition. And they are the sum of total polyunsaturated fatty acids, the sum of total monounsaturated fatty acids and the sum of total saturated fatty acids. There's also two minor ones, fatty acids, other non specified, which is usually a very small amount of fatty acids where fatty acids are present, but they can't be identified and they're used to get the sum of fatty acids up to the value that it should be. And fat RN, which is the total trans fats in the food. And then we move on down to individual fatty acids. So there are tag names for each of the individual fatty acids. These tag names are of the form F N D M, where N is the number of carbon atoms in the fatty acid, and M is the number of double bonds in the fatty acid molecule. The easiest and most straightforward of these is the saturated fatty acids as they have no double bonds, so M is zero. So for saturated fatty acid, the tag names will be of the form F number of carbon D zero. The example I've got here is F 16 D zero, which is polyunsaturated acid. And for monoun polyunsaturated fatty acids, the tag names include the number of carbon atoms and the number of double bonds. And they also go into more depth and they may include the double bond position and they may specify whether the fatty acid is the cis or the transform. So what we have is effectively a hierarchy of tag names with the most general one being of the form F N D M, the first one in that table, where the bond position is unspecified. And this is the minimum description required. So we don't know what the bond is, where the bond is, but we know where, how many carbons there are. The second one, more detailed, indicates the double bond position in the methyl end, but doesn't indicate whether the fatty acid is cis or trans. And so then the most detailed tag names include double bond position, the number of carbon atoms and whether it's the cis form or whether it's the transform. So monounsaturated fatty acids have a single double bond, so they're always of the form F N D one. So I just pulled some out for examples. The most general form then the tag name will be F 18 D one is the fatty acid 18 one. And then a more specific tag name for a subset of those fatty acids would be fatty acid 18 D one and nine, which means we've got a double bond, the in nine position. And then more specific than that is 18 one and nine trans. So that's the trans form of that fatty acid. What I haven't probably put in the slide but should emphasize is that that F N D M the most general form includes the more specific forms if that makes sense so that will be that will include those specific forms. And polyunsaturated fatty acids can have two or more double bonds. And again, bond position and whether the cis or trans form of the fatty acid mat, whether we have the cis or trans form of the fatty acid may also be specified. And so the example I've got there is F 18 D two, we can then specify that down to where the one position is, and then whether it's the trans or cis form. So as you can imagine, there's quite a lot of individual fatty acid tag names. And I've just pulled out some other common fatty acid tag names that you likely to come across. So they're of interest, especially nutrition. And one of them is the total omega three polyunsaturated fatty acids, and the other one is the total omega six polyunsaturated fatty acids. And they're, they're sums are normally calculated by summation of the individual fatty individual omega three or omega six fatty acids. And then there are two individual fatty acids that are often of interest and they're alpha linolenic acid and linoleic acid. So I just wanted to include them so you have them for reference difficulties in attributing tag names. And there's a couple of key issues, I guess, that I've come across in my work trying to attribute fatty acid and fatty acid tag names to data. And the first one that people often come across is determining whether total fat data should be assigned to tag name fat or fat C. And the way to check, I guess, is to look at the method and include an extraction process. And so go back to those earlier slides where we have the methods in the extraction process is spelled out for fat and fat C. There's also some decisions to make. I included in the earlier slide about the different publications about whether you have, if you have only fat C data, well, that's the only data that you can use. If you have both fat and fat C, you can compare your fat C data, check if it looks similar to your fat data. If so, then maybe it can be included those sorts of things. And individual fatty acids can be just a little bit complicated just because there are so many of them. There's also lots of different names. There's lots of differing nomenclature for fatty acids. And so you'll see them with trivial names. There are, there's the IUPAC names, the Delta naming convention, the Omega N number, the carbon numbers. I don't have any secrets there other than just be aware that there's lots of different ways that the fatty acid might be referred to. It's always good to check and look up and to keep your own list of the fatty acids that you're interested in and the various names or nomenclature that you might see them under when you're trying to assign fatty acid tag names. And with individual fatty acid, there's often some uncertainty over the inclusion of the transform. So if you're looking at data for a particular fatty acid, whether you should be applying a quite specific tag name that indicates cis data only, or whether you should be applying a general one. Again, depends on where your data comes from and what you're using it for. The best thing to do is apply the most specific tag name you can. You might not know, you might make a practical decision that the foods you're looking at are going to be low in trans fats, like I've got there in naturally appearing foods. Sorry, naturally appearing trans fats. So non hydrogenated foods, they only ever make up about 5% of total fatty acids. And so you might make a decision that it doesn't matter that you'll use data that has both the data that you don't know. Basically, you can apply quite a general, the general tag name that doesn't specify whether it's cis or trans. And I've just popped in some important considerations for dealing with fatty acid tag names, but I guess also key things for dealing with food composition data in general. First up, what are the units of the other fatty acid data that you're looking at? And as the previous presentation went through, there are lots of different ways to present fatty acid data. It can be presented in grams and milligrams. It can be given as a percentage of total fatty acids. So it's really important to know and understand what the units of the data that you're looking at and using. That goes for all food composition data, not just fatty acids. It's also important to know what the denominator of your data is. So when you're looking at data that's per 100 grams edible portion, whether you're looking at data that's per 100 grams dry matter, or whether you're looking at one per 100 grams fatty acid, which is the same as the percentage of total fatty acids. And again, important to know if you can, whether the data you're looking at includes the transform. So use the most specific tag name possible, but if you're not sure, then you can use the general tag names that don't specify the cis or the transform. And I've just included some references and further resources. This presentation drew quite heavily on FAO in foods, e-learning course and food composition data, which is excellent and I recommend to everybody. There's also lots of resources at the infoods website, including the list of tag names. And the last link there is the food composition Bible by Greenfield and Southgate. And so that's me. And I think that marks the end of our presentations. Okay, thank you so much for this wonderful presentation on inputs tag names on patent fatty acids, as well as for the for usage and to difficulties in using it. I would like now to go to the different questions that we have received. One of them is if we will get the PowerPoints. So no, you will not get the PowerPoints, but this webinar is recorded and we will publish it on the input website. There is a new category, which is called webinars, and this is where it will be published in Utah. And let us now go to the more specific questions. So I think the first one is for three moolari. Can we use in-house material for quality assurance rather than reference material? I had calculated the fatty acids from peak heights. It's come in high range, but when I use factor to converting fatty acids to 100 gram, then the result seems accurate. Is there is any special thing which needs to calculate fatty acid from its percentage to gram to gram per 100 gram? So I think we already noticed from the presentation of Anatan that gram per 100 gram does not have any meaning, so it would need to be more specific. But probably we can have the answer to the first part of the question for the in-house reference material. Can you unmute yourself, three moolari? Can I answer that too? Yes, you can. Yes, of course we can use the in-house quality control as a quality assurance. When we establish properly, so we have to use regularly until we get repeated analysis, reproducibility, it's a good reproducibility. Once if you develop up to maximum 99% reproducibility, of course we can use. Even we use in our regular batch-to-batch sample preparation one quality assurance which we established in-house because every time we cannot use CRM or SRM samples because it's very expensive. Yes, as a conclusion, yes of course we can use but we have to establish with good reproducibility. Okay, so the answer to Dr. Saman Somro is that yes, you can, you need to calibrate it with certified reference material. Then there is another question for Anatan. So the shepherd factor, is it different for different food or is it constant? No, this is a food factor essentially not for the food, but this is for the fatty acid methyl ester-2 fatty acid. So except the one methyl group, the methylated fatty acid will be having additionally one CH2 where only the 14 molecular weight will be increased in the fatty acid methyl ester. It's not for food-to-food, but the SHF will vary fatty acid to fatty acid. Okay, thank you. Then we have another question also on the method in from Kunshit June Prason from Thailand. In AOSC it is recommended to use C111 as internal standard. Why did you select the C17 as internal standard? The C17 double point zero found in fish and fish product which may affect the calculation of each fatty acid. So this is for 3 mulari on the presentation that you gave. Can you please unmute yourself and answer the question? Murli, can I answer? Well, you know, you are working in the same institute. Yeah, we are working together. Yes. So that's why he's my colleague only. So I can answer for this question also. Yes, of course, Dr. Kunshit, it's AOSC recommended C11. But we are using C17 for all the planned samples. Even WHO also recommends C21 for some of the analysis. So C17 and C21 generally we use as internal standard. When the fish sample analysis, so we use C21. The next question is would you recommend using external standard calibration for quantification of absolute fatty acid? And this is a question from Michael Bellagio. One second. The question is would you recommend using external standard calibration for quantification of absolute fatty acid? Yeah, we can do quantification. Calibration we can do. So the answer is yes, you would recommend the calibration. Yeah. Okay. Thank you. Please comment on a method that allows to distinguish between natural and industrial trans isomers. This is the question from Hannah Moiska. Yeah, this is a question because you know the separating the trans fat which is definitely available in the natural source from the necessarily produced partially dehydrogenated vegetable oil. So it's a big challenge except you know the different source what they used. Without that we cannot really, it's very difficult job to identify, eventually send the trans fats with industrially produced trans fats. So if I understand correctly there is no method which is distinguishing with chemically between natural and industrial trans isomers. Let me add that. Can you hear me? Yes. Yeah. We can do the differentiation but the thing here is the industrially produced trans fats is a lactic acid. A lactic acid. But where is the naturally occurring ones at the conjugate linoleic acid? For which if we use 668 column we can differentiate those. So thank you and I would like to introduce you. I did not do it at the beginning. I'm sorry for that. So who just spoke is Chi Longba from also from the National Institute of Nutrition in Hyderabad. So thank you so much Longba for the answer. Then there is another question. There is a fairly limited number of fatty acid conversion factor in Greenfield and Southgate compared to the large number of foods available with mixed sources of fat such as cake that includes fat from butter, egg, cacao and flour. How should we deal with this if we want to express our data as gram fatty acids per 100 gram edible portion on fresh weight basis? As recommended by Info, FAO Info, it's similar food groups we can adopt. Yes, of course I do agree. There is no complete XFA for all the food groups are different foods are available but the similar food groups can be adopted. That's what FAO Info's guidance also is recommended. Okay, so then what would you suggest to do to have a weighted average of the conversion factors or to use the one of the highest proportion of the fat? What would be the recommendations? Let's say for the egg, let me have the report on the average of all the individual samples. Yes, so if we analyze cake and have the fatty acids are coming out. So I think the solution would be the most precise would be to use an average, a weighted average according to the fat content of the ingredients. If you want to make a more cross estimation, you take the fatty fatty acid conversion factor from the food which is giving the highest proportion of fatty acids. Then we have another question. Do you have any plan to include in format, in formation on the methods? So this is a question then to Srimu Larry, but I think... Can you repeat the question again? Sorry? Can you repeat the question again? Yes, do you have any plan to include information on the methods? So more information on the methods. So I thought that the information giving in the presentation were very detailed. So probably Takashi Yasui would like to specify the question in a new question. So I can... And then Takashi has also a question to Anna. Do you have any plan to include the information on the methods used for fat determination in tag names? Because there are several different mixed solvent extraction methods. I'll give my answer, but then I might turn over to Longvair and Anatan to double check. My understanding is that with a tag name, we only had different tag names where the different methods result in different results. And so for the mixed solvent extraction, I assume that even if there are different mixed solvent extraction methods, they all supply a similar result. Does that sound correct? Yes, that would be my understanding as well. So if our analysts can confirm that the different mixed solvent methods would give the same results. Well, it is not actually that different method will give the same result. Because the extraction will also depend on the material. Food metrics are very different from each other. So for example, if we are looking at the cereals and pulses, you need to take out the fat that is within the cell layers, which normally the solvent extraction cannot do. So we need to use an assist extraction after which you will use the solvent to take out the fat. Now, when we use only the solvent extraction without the acidification in the beginning of the material, you will get a different result. So normally for the fat estimation of cereals, it is recommended that the use of acid to bring down the cell walls, so that the cell will find the acid, which is normally the phospholipids. So the thing is to do the acid hydrolysis before the analysis. And you will get more fat out of the matrix than compared to not doing it. Yeah, but you know the items for food items need sample, just chloroform mechanical extraction is enough. You don't need to acidify. Just chloroform mechanical. So the solvent extraction is enough for meat, meat and meat fish levels. Okay. Thank you very much. So, and the last question comes from Nuhar Tzara. When we borrow data for fatty acids, do we need to do a water adjustment? And this is, I think, more for Anna. Thank you for the question. And it depends on how you are borrowing the data. So if you're borrowing from an FCT that is giving you data in grams or milligrams per 100 grams edible portion, then yes, you will need to do a water adjustment. So if you have a fatty acid profile, so you have a profile that is proportional to total fatty acids for each fatty acid, then you can just take that profile and apply it to the total fat in your food multiplied by the fat factor. So it depends on what the data looks like. Yeah. Thank you so much. Thank you so much for the questions. I don't see any more questions nor in the chat nor in the question answers. So I think with this one, we have answered all the questions. And I hope that every participant was getting the answers that they were looking for. And I would really like to thank all the presenters and also Longva to jump in for answering some questions. And I think that was a very useful seminar and I truly hope that we will have more seminars in the future on analytical methods together with the tag names and on how to present the data. Because it is very obvious for some parts of the like the chemists on the chemical part, but they are not that familiar with the other part on how to use it and what are the difficulties in using it. And very often and we also saw it in one of the questions. The data which are presented in even in scientific journals are not specific enough in terms of units or denominators. So that we can use the data or that we don't have the fat content or that we don't have the water content in order to convert the data which has been analyzed and a lot of funds has been and time has been going into the analysis. And then at the end for food composition purposes we cannot use that because of ambiguity in the unit or denominator or that we have some missing data. So, and therefore it was really very important or so when Anatan presented to say, you know, what data do we always use and this are the data that we would like every journal to publish always at the same time when they are publishing the fatty acid data. Because if not, it is really it's a pity that we are not able to use the published data to its full potential. So, and if anybody would like to add something to the discussion, so please feel free Anna or Anatan Lombar or Simulari, please if you want to say something before we close the seminar. Let me thank you for organizing this great webinar. I think this is the first step to take toward the techniques in analysis of foods. And I think this is a very good activity that inputs us, especially at a time like this. It will be very good. We can continue this with some other techniques so that people can understand more about the food analysis and in three cases that are involved in it. Thank you all for attending this webinar. I would like to thank Dr. Root for arranging this wonderful webinar on this particular topic. I'm very happy to present my presentation. But unfortunately we could not present it in detail because of the construction of the time limit, I hope and the future presentations. More clarity but at the maximum we have clarified all the notes raised by the participants also. If they have more doubts they can personally also they can conduct more clarification. Thank you so much for all the participants. Also thank you as well to Root and to FAO for organizing and thank you to everybody who came along to listen. Yes and I see a lot of messages coming in thanking for this wonderful seminar and the content and to the panelists. So probably we can end this seminar by clapping to the wonderful presentations. Thank you so much and with this one I would like to close and hope that this is only the beginning of a series of webinars on analytical methods. Thank you so much. Thank you. Have a good day to all. Good night. Good evening.