 I would like to start addressing questions to you, whatever we've collected over the course of your talk. Priyanshu asks whether culinary fingerprints performed only using the flavor molecules or other parts of food as well. Culinary fingerprints entail using information of recipes, ingredients as well as the flavor molecules, not to mention even the functional group present in the flavor molecule. So it's a multi-layer information that was used for creating culinary fingerprints, Priyanshu. Thank you. Mr. Prasad asks, some doctors recently are speaking about human microbiomes and how post-COVID-19 world, they will be very significant. So how would computational astronomy help in building up, say, good gut microbiomes? Thanks for asking this question. I obviously hadn't touched upon many aspects of food that included gut microbiome, which happens to be one of the hot topics these days in the food sciences. Quite clearly, in fact, the Weizmann Institution research that I pointed out towards the end indeed uses gut microbiome as one of the factors which goes into the machine learning algorithm. So wherever you are compiling data and analyzing it, that becomes part of computational gastronomy. So as long as you are looking at gut microbiome data, plugging it with other data such as BMI, food diary, and what kind of diet that you are having, thereby making predictions of any kind of health indication, that way computational gastronomy can pitch in there. That was also a machine learning algorithm and similar kind of algorithms can be built for suggesting what kind of dietary interventions are beneficial against diseases such as inflammatory bowel diseases, cones disease, etc., which are diet-linked. Thank you, Professor Ganesh. One more question. How do you think that the field of psychology, Humeirah Fatima asks this, how do you think that the field of psychology and neuroscience add value to computational gastronomy? This is a tough one, though this has been thought about and very complex one. Food is a complex topic. So definitely psychology touches upon it, with whom you are having your food, the kind of music or ambience in which you are having your food may make a huge difference in your perceptual, how you pursue food. This has been studied incidentally in the field of psychology and somebody suggested me from Tripoli to Hyderabad that I should collaborate and work on it actually. So I believe that indeed computational gastronomy, which is a broader paradigm, wherever you use computation in the context of food, it can be called as a computational gastronomy, largely speaking. So I believe there is a much scope for working on questions which are derived from psychology, not to mention the neuroscience. In fact, only next week I have a meeting with an entrepreneur who is working on neuro gastronomy about how food elicits different reactions in different parts of the brain. And can we analyze this in the context of different food molecules that the food has? That's one of the broad question one is asking here. I personally believe there is a huge scope. How soon this is going to happen? I wonder. Will it take time? I believe it will take a little time before we can touch upon it. Among these I believe neuro gastronomy is something which will come up very fast, very soon. People would like to find out what are the neural correlates as they say of a certain perception. Thereby, if you would like to evoke that sensation, one of the immediate application that I can see here is this. Can you elicit somehow, quote unquote somehow, sweetness without having sugar in your food or your beverage? If you can do that, you have a million dollar or billion dollar solution problem. So this is a multi-billion dollar solution. Thank you. The next question is there is molecular gastronomy which is innovations used by chefs. How is computational gastronomy different from molecular gastronomy? And a second part of the question, if impairing the index is negative, does it mean that paired foods together are not healthy? Okay. Second question first, I'll take it right. So first of all, this positive and negative food pairing doesn't have anything to do with food being good or bad. It is simply a mathematical notion used on a vertical axis, something which is random, something which is on one side, the so called uniform side or positive side and something which is on the other side, which is contrasting side. That was the only reason the word negative food pairing was used in the research article that we wrote in, that is to put a contrast, to create a contrast with the positive food pairing. But after realizing that many people are misreading it to be having negative health consequences, we are now sticking to the terminology of uniform pairing and contrasting food pairing. So that was, that's the answer to the second question. I'm sorry, but I lost on the first one. Very quickly. Can you repeat that? So molecular gastronomy is primarily a chef's endeavor where a chef is trying to recreate a certain test using certain molecules like you would like to create a taste of a recipe using only a few molecules, for example, that is what molecular gastronomy largely entails with. That's a very, very physical endeavor where we are trying to come put together molecules, which will, for example, it doesn't have palak, it doesn't have paneer, but it tastes like palak paneer, right? By putting together some molecules together, you would like to do that. That's called molecular gastronomy, whereas computational gastronomy is far different. It basically creates a framework, data driven framework around food and food related attributes. The one I told you, recipes, ingredients, the flavors, nutrition and health, and thereby try to create applications out of it. Yeah? So it's very different from that. Mr. Hariharanasi asks, how would you advise using this research to develop new recipes for recipe developers? Okay. So there are two ways of doing it. Maybe you can talk about your, your favorite recipe, which is your Baigan Kavarta. Baigan Kavarta. Okay. So, okay, I have got a lot of feedback used, including, you know, Chef Garima, who is a Michelin star chef actually herself, saying that the food pairing parameter that we have identified, she finds it useful while designing her recipes. So that's a, that's a chimeric job. You are using intuition, but at the same time, you are also trying to use objective parameters given by food pairing index. So we have FlavorDB, the database, you go to FlavorDB, there is something called food pairing. And the food pairing index actually provides you, tells you that if I ask what is similar with mango, then it will tell you all the ingredients that are similar by virtue of shared flavor molecules. Similarly, it will give it to spinach or tomato or chocolate, whatever you want. Now you can use your intuition that, oh, let me create a uniform food pairing, similar one or contrasting one by choosing ingredients of your choice, taking ingredients of your choice, putting them together and figuring out whether it works or not. I have, of course, many chef friends and because I conduct a symposium every year. So we have already conducted three symposiums, chefs come to that, they learn from us, they go back and do experimentation. Many have got back to us, not all, but many have got back to us saying that this tool helps them in shortlisting ingredients that could be good for creating such recipes. So that's a very loose answer for the first part, where you can use your intuition. Second, you'll have to wait for it. We are in the middle of creating Nobel recipe generation algorithms, which for example would learn from all the biryanis and will come up with a new biryani or 10 templates of biryani. And then you can choose one of them, which can possibly be in your opinion, the best recipe, alternative biryani recipe, right? But that will take a while. It's a deep learning machine learning based algorithm that we're trying to design. It has to beat a human chef without which we can't say it is a really good one. So we are in the middle of doing that. So it's a futuristic work. So Mr. Hariyanand, you would have to wait for a while for this to come to reality. So Professor Ganesh, this is a lot like maybe building perfumes or maybe building very complex perfumes, right? You have a top note. You have a middle note. You have a bottom note. So if you're going to do like a template for biryani, you want to know what it smells like when you open the pot. You want to know what it tastes like, what immediately hits you, what kind of acidity hits you, and then the texture, the umami texture that you feel across the board. And yeah, we can't wait. The chefs that you were talking about who attend your symposium, what tools do they use when they attend your symposium and go back to their own to experiment? Most of them used positive food pairing principle that seems to be still a dominating principle incidentally. So they essentially went to FlavorDB. They, for example, looked at chocolate and what are the ingredients that pair or have most similarity with chocolate. And while creating a chocolate based recipe, they use those ingredients as possibility and wherever they found the exception, they actually got back to me and also told me that look, this is not working well, despite it being so much similar. It's not really working. My customers are not liking it just to give an example. Is this, um, is this database available to the general public? Correct. FlavorDB is available as a browser, browsable database for non-commercial purposes. As long as you use it for making some player playing around, et cetera, it is available for commercial purposes, purposes that is not available just like that. You will have to make a contract or something. Thank you. Now, Mr. Priyanshu asks on what lines the field of gastrophysics and professor Charles Spence's intersect with computational gastronomy? I didn't even know something like gastrophysics existed, but today I learned. Gastrophysics is more on lines with the molecular gastronomy, I would say pretty much, whereas computational gastronomy is heavy, very heavy duty on data and computation, right? I would rather collect data coming from Spencer's lab and use it for doing some analytics at my end. That's computational gastronomy. If I were to create a lab to put together ingredients, molecules to create a desirable recipe or a flavor, that would be Spencer's lab. That would be molecular gastronomy or gastrophysics. Gastronomy and gastrophysics are pretty much similar, except that physics principles are used a lot heavily when they are trying to design a new recipe, such as that they do in Spencer's lab. Okay, I'm going to put you on the spot again. You very cleverly avoided my question with regards to your favorite recipe and how you've played around with it. Trust me, I still remain a very novice cook. I fail a lot. And while my wife takes some intuition from what I do, you know, my mother hasn't done as much, but my wife has done it. But I am still playing and trying to figure out how do I change Bagan Kabhartha in a recipe which is more or at least equally likable by changing some of the ingredients by using food bearing principles. But so far I have not been able to change my liking. What it is, primary liking is with the basic, the classic Bagan Kabhartha that hasn't changed with any of the food bearing that I've done so far. So you think this is something to do with nostalgia as well because you've grown up eating it. And it is something that I know that we've touched upon when we spoke earlier with regards to the flavor molecules both our factory as well as the straight tree evoking nostalgia and that also being therapeutic in some aspect. It is eminently possible. As I said, it's a complex topic. You know, those who have grown up, there is a factor of nostalgia and more like, there is another word for it. Basically, you have been used to that particular taste and order and aroma. Like somebody who has grown up eating Bagan Kabhartha, Dhanin Chulha would not like it as much on a gas probably. It's that kind of a difference it makes actually. So it's a complex topic. Food is very complex. What we are trying to do is to take out the top layers only. That's why I mentioned that it is probably still 18th century physics or 17th century physics. Very early stages, very basic principles is what we are trying to figure out from whatever we have available with us. That's wonderful. Now, I have one more question. When the chefs come back to you saying that this didn't work, was there one particular example that stood out? I can't recall that particular example, but it was regarding chocolate. With chocolate, one of the ingredients that was coming on the top in the third or fourth number in terms of chocolate pairing with something else, that something else, I was told, I have a written record of that somewhere. The person wrote a message to me saying that this ingredient didn't really work well. So I do have that particular example, but I don't know the name of it right now. And then many more, sorry. And are you investigating why, despite it being so high up on the flavor or the food pairing index, it's just not working well? I looked at it. If there is an easy answer to it by looking at its flavor composition or some unusual molecule which might be present, which is giving an unpleasant odor or aroma, et cetera. But there was nothing so easy to come by. If you look at flavor DB, you will come to realize that it's a very, very complex database. It gives you molecules and molecules' order. What kind of order or a taste the ingredient molecule has. So it is very difficult to pin down in the absence of additional data such as concentration of the molecule, which is not available. So in chocolate, for example, this molecule, what concentration it is available in. Practically it is not available for every ingredient. We have around 1000 odd ingredients in our database. So in the absence of large amount of such data, it is impossible to investigate and pin down about what made that possible. Thank you. Mr. Hariharan has another question for you. I think this is similar or it's just writing off what you've just said right now. Do the flavor molecules of ingredients also change based on the method of cooking? If yes, how is it accounted for in the flavor DB? Good question. A very good question. So of course, flavor molecules change their composition, their nature when they are processed, depending on whether they are boiled or fried or sauteed or they are raw. They are obviously very different from each other. In flavor DB, flavor DB is not cooking related database. It's flavor molecules is repository. So natural molecules as available in raw ingredients is what is reported in flavor DB. If you ask me for boiled beef and fried beef, boiled chicken, for some of these ingredients, we do have their molecules available with us. But for most of them remaining 1000 odd ingredients, we don't have their transformed form. In fact, one of the major agenda, if one were to do some interesting gastronomical project, is to do this, is to take an ingredient, put it through some popular protocols that it goes through, boiling, frying, sauteing, roasting, etc. And look at the flavor composition using gas chromatographic kind of techniques. What was the original flavor? What are the flavors later? And make a list of those and create a database of that. That itself would do wonders to this area of computational gastronomy, propelling it towards the future, trying to create new recipes out of it actually. In the absence of that, we are heavily limited. So to answer the question of Mr. Hariharan, we don't have that data in flavor DB available with us. Not right now, but I'm sure you'll have in terms, very excited to put chicken or mutton or beef through, you know, the entire processes that you said, whether it's boiling or braising or sauteing or even sous vide for that matter or deep frying and then, you know, get the database, get the molecules that are required and then put them into the database. Yeah, we intend to do that. And one of the, you know, lackunas or shortcomings of being in an area such as computational gastronomy, as an active researcher, I can tell you, is that if you work on cancer or diabetes, you will get million of funders, whether it is from DST, Department of Science and Technology, Department of Biotechnology, et cetera. But when you're working on food and that, and you develop a new area as a pioneer of computational gastronomy, everybody claps, saying that, wonderful. You're done amazing thing. Nobody would have done this. You have spent five years so far working on this area, et cetera. But when it comes to funds, practically none. So this needs a lot of money to be able to do this characterization of flavor profile of different type of ingredient needs a lot of money. So we need funder. Funder either is coming from government agency which realizes the huge potential based on nutrition and health of the country or it should come from private industry, you know, private labs such as industry. They should be realizing its value and should be putting their money. It has not happened so far. So you're looking at exploring personalized nutrition and intersecting with computational gastronomy, correct? Yeah, very much. So Pranav is asking, what about the food pairing in sweets? Is it similar to food or different in regards to flavors? You mean sweet meats. Yeah, desserts, basically. Desserts, yes. And I guess he's talking about the Indian context which might be heavily dairy based and you know, half sugar. But I think actually you could maybe talk about the spices that are involved here and how different they can be, yeah. You know what, there are so many ideas that have been popped at me including, for example, dishes which are made as naivedams in temples, for example, right? The whole of all of them, can you investigate those itself, you know, as a repertoire of recipes? Apart from others, tribal recipes as a set of recipes and similar such subsets of recipes have been suggested including desserts, right? To answer your question, I have not done the analysis of this in the context of desserts, so I don't know the answer. We haven't done specifically for desserts what is the food pairing index and how different it is from other dishes. We haven't done that yet. Okay, thank you very much. I think we've run through our time. Professor Ganesh, would you like to leave us with any last thoughts? Hopefully to do with how we can maybe apply FlavorDB in our own everyday lives from today onwards. Sure, so one is FlavorDB, another is RecipeDB. Those of you who are interested more in practical applications of computational gastronomy, you may start investigating these databases to look at what are the flavor composition of different ingredients that go into our daily recipes. In my opinion, that will be an eye-opening exercise to begin with. Just to find for example that how sulfurous compounds are so much dominant in onion or similar ingredients which have pungent aroma that itself is a learning exercise in my opinion. Secondly, you should be able to do food pairing by using the food pairing app which is part of FlavorDB and thereby come up with some interesting pairing by which you can change your recipes and hopefully come up with some novel tweaks in the recipes that you like already probably. And if you do so, don't forget to write to me. I have my email ID written on the database, so do that. And of course, if things don't work, things are not working according to your intuition or the logic as I have proposed, don't hesitate to write back to me also. And if you have any other adventurous applications, remember this is a database that I have created primarily from academic endeavour and has ended up becoming of applied nature. And similarly, RecipeDB. So we have database of 118,000, 1,18,000 recipes with us which we have broken down into its elements, ingredients, quantity, units, blah, blah. So use it, find ways by which you can see, you can search recipes. Show me all recipes which have, let's say peanut in it from Brazilian cuisine, which have peanut in it but doesn't have chili in it from Brazilian cuisine or whatever cuisine that you would like to search for. You can make such queries by using RecipeDB and probably you might hit upon some interesting recipes. These are real recipes. So eventually you will reach a link which can take you to original database on allrecipes.com or geniuskitchen.com, et cetera, in addition to giving you insight into the recipe about what is the composition of the recipe. So those are the couple of things that I would suggest to you. And further, finally, final thoughts is this, two things, two forks. One is of academic nature. If you think of some interesting ideas which can be run on in computational gastronomy domain, feel free to write to me that this is an interesting thought that can be done. Can you please work on it? Like the deserts, for example, was one of the case. So can you look at food pairing index of deserts and compare it with dishes? You can come up with such thoughts. And finally, if you see there is an industry partner that you know of among the audiences who can be of value to me in terms of partnering, feel free to connect me so that we can take it forward. Apart from you yourself coming up with propositions, of course. I can be your partner over there. We run the Vodava. And we primarily work on nostalgia. One of the things that works very well for us, apart from the health aspects of the bar, is that we use jaggery. And we caramelize it in butter or ghee because we clarify the butter to make ghee. And it immediately sends everybody back home to Dadi's laddus or chickies. So yeah, I would love to collaborate with you. This is very exciting for me. And crowdsourcing flavor libraries will be fantastic, I think, for your research as well as for our enhanced knowledge with regards to flavors. From a nutritional aspect though, does FlavorDB have the nutritional aspect matched to it? RecipeDB has it. Some information of nutritional value that for example, there is a recipe. There are ingredients. What is the nutritional value of that particular ingredient has been estimated? There can be mistakes because this has been done using a machine learning algorithm because we had to do it for 118,000 recipes. So we did it for a few of them, trained it. So there is a protocol which has gone behind it. So using that, we have estimated the nutritional value. So they are available. One last thought before I end this session with you. NIN has a very comprehensive nutritional database, especially with regards to Indian foods and recipes. I advise people to also take a look at that and see if there's any discrepancies. Okay, thank you very much, Professor Ganesh. What a pleasure having you here. I really enjoyed your talk and I'm really looking forward to gastronomica and I'm really looking forward to hopefully yelling out to Alexa that this is what I have in my fridge. Tell me what I can make with the best food pairing index possible. Indeed, my pleasure too. Thank you. Thanks a lot.