Wayne Nathanson - Neolithics - Ep 41 — PostHarvest Technologies

In this episode of "Let's Talk Farm to Fork," we're joined by Wayne Nathanson from Neolithics, who we'll be talking to about how their AI software integrates seamlessly to detect, classify, and sort crops on conveyors to help increase yields.

www.neolithics.ai/

Transcript

[00:00:00] Mitchell Denton: Hi, and welcome to “Let's Talk Farm to Fork.” The PostHarvest podcast interviews people of interest across the food supply chain. Today on our show, I'm joined by Wayne Nathanson from Neolithics, who I'll be talking to about how their AI software integrates seamlessly to detect, classify, and sort crops on conveyors to help increase yields.

So with no further delays, let's get started.

Well, hi Wayne. Thanks for joining us today.

[00:00:26] Wayne Nathanson: Thank you for having me.

[00:00:28] Mitchell Denton: Before we get into it, could you tell us a little bit about your background and how you came to work in the FoodTech industry and maybe a fun fact about yourself?
[00:00:37] Wayne Nathanson: Okay, so, uh, my background's always been in business development and sales. I've been in the technology industry and software. And then I spent, um, a number of years in agriculture actually um, I worked in the Netherlands, what I would consider to be the centre of the agricultural world.
[00:01:00] Mitchell Denton: Mm-hmm.
[00:01:01] Wayne Nathanson: And now when I was there, I realised that, um, you know, the world needed to re-engineer the way that it produced and distributed food. And I was interested in getting into that as, um, no, not only a trend but as a very important area that we have to focus on. And, um, so I went looking for an opportunity in FoodTech. Uh, so a fun fact, um, I'm Canadian, although I worked the last five, six years in the Netherlands, uh, I live in Israel now, and so, um, you know, I'm a person who likes adventure.
[00:01:44] Mitchell Denton: Fantastic. Where, whereabouts from Canada do you hail from?
[00:01:48] Wayne Nathanson: I am from Toronto for most of my life, but originally from an island off the east coast called Newfoundland.
Most people have never heard of before, but it's very obvious island off the coast of North America.
[00:02:02] Mitchell Denton: Yeah. Well, believe it or not, I do because I, I lived in Toronto for a few years, not too long ago actually. Yeah. Yeah. So bit of a small world. We're, we're, we're just a couple of jet setters, aren't we?
[00:02:14] Wayne Nathanson: Newfoundland is the, uh, the brunt of the jokes in Canada.
[00:02:19] Mitchell Denton: Yeah, it's true. Yeah. No, it's a, it's a beautiful place though. But, um,
[00:02:24] Wayne Nathanson: Very beautiful.
[00:02:24] Mitchell Denton: Yeah. Yeah. Before we get bogged down in, in, in talking geography, uh, let's talk farm to fork. So, would you be able to tell us a little bit about the history of Neolithics and what solutions and technology they provide to the food industry?
[00:02:41] Wayne Nathanson: Well, the history is short. It's only about two and a half years. Most of that has been in the development of our solution that's focused on food waste. That was the motivation behind the company and the founders saw the need, uh, to improve the way the food was distributed in the supply chain. And, um, we have, as one of the founders, a food scientist, and I think that I could talk a bit about later, but that food science component of what we're doing, is our secret sauce. It's the differentiator that, uh, distinguishes Neolithics from anything that's in the industry currently.
[00:03:26] Mitchell Denton: And so what, what are these solutions and, and technology that Neolithics provides?
[00:03:33] Wayne Nathanson: So our technology is a software, uh, artificial intelligence solution called "Crystal.eye". Um, we do quality control inspection of fruits and vegetables, and we cater to companies who are in the fresh produce supply chain, anywhere from post harvest after it comes out of the field. All the way through food processors and distributors to, uh, the consumer.
So to a retail, uh, distributor.
[00:04:07] Mitchell Denton: And so. How does your Crystal.eye technology conduct internal and external inspections of fresh produce supplies?
[00:04:16] Wayne Nathanson: So we use sensors to take images of fresh produce and our sensors. Along with its illumination, uh, the way that we light up the fruit is able to see not only the exterior of the fruit, but we can see the interior of the fruit as well.
And that gives us the ability to provide information to food distributors, uh, that they wouldn't normally have. The fact that we can see inside with sensors means that we can give a food distributor information without destroying the fruit.
And 35% of the food waste in the supply chain comes from inspection and logistics. Just moving it around. So that is the area that we're focused on. And there's over, uh, in the United States, they waste over 50% of the fresh produce that is grown and it's a phenomenal number. So what we need to do is figure out how to reduce that waste in order to continue feeding the population, because the estimate today is that we're gonna run out of food by the year 2050. And I don't believe that's gonna happen because we see the dramatic change in the way that food is provided, the way it's grown, we're re-engineering the industry.
[00:05:50] Mitchell Denton: So you've talked about how it's a non-invasive form of sampling the fresh produce. I was just wondering if you could expand on that as to how Neolithics is more sustainable compared to more traditional quality control practices.
[00:06:07] Wayne Nathanson: So the main thing is that in fresh produce, quality control globally, it's mainly done by hand and by eye.
[00:06:17] Mitchell Denton: Mm-hmm.
[00:06:18] Wayne Nathanson: So what we're doing is we're automating a process that is still manual, which is hard to believe in today's world. I remember when I started in technology, I would go around and tell people what they could do with a computer and how to automate their business.
It was things like billing and inventory control. Um, so when we're talking to people about automating quality control, it's phenomenal that commercially quality control is done very similar way to the way we do it, when we go into a supermarket to buy fruits and vegetables, we pick it up, we feel it, we look at it, and we make a judgment call based on the feel and the look.
And a lot of the quality control commercially is done that way, but sometimes, Um, they have to see the inside of the fruit or vegetable, and the way that's done is by cutting it and doing certain types of you know, sometimes laboratory experiments or different types of analysis that destroy the fruit.
So if we can use our sensors to see inside the fruit and give information like sugar content, acidity. Uh, we can identify defects or bacteria that's inside the fruit that's going to impact its, let's say, maturity or ability to be sold. Then, you know, that's a major game changer because if you are curious, go to the back of any grocery store and you'll see most of the things in their garbage can are fresh fruit and vegetables that have been spoiled and can no longer be sold.
[00:08:06] Mitchell Denton: Yeah, absolutely, and I'd imagine being able to actually put the fresh produce under the, uh, microscope so to speak, would have a lot better results with forecasting as opposed to simply eyeballing a product. So that's really awesome. That's really exciting.
[00:08:23] Wayne Nathanson: Providing more information than they have today, and we're doing it in a higher volume and providing data that gives them the ability to make decisions that will ultimately improve the quality of the produce, it will improve the consistency of the quality and, um, give them more information to make decisions on how to utilise the fruit or vegetable better. So if a tomato's too soft to go to the supermarket, because it'll never be sold in time for it to spoil, then it should be going to a ketchup maker or a tomato sauce maker or something where it can still be utilised.
[00:09:08] Mitchell Denton: Yeah. Fantastic. So then, what are some of the challenges that the team at Neolithic has had to face when developing the Crystal.Eye technology?
[00:09:18] Wayne Nathanson: So the biggest challenge is the obvious question that most people ask. "Well, how do you do it?" And that, that's the secret sauce. We have food scientists on staff that have studied spatial recognition of produce, and they know based on the images that we see, what the colours and the, what the colours mean from a perspective of content.
And that is the, the secret sauce. So it's not just taking the images and feeding it into our AI engine. But it's what happens in between that. What does the AI engine know about what it sees? And that comes from our food science department.
[00:10:08] Mitchell Denton: That's great. So then would you be able to share any success stories or case studies from customers who have switched to using your technology for their produce inspections?
[00:10:19] Wayne Nathanson: Well, there's a number of them. One of the ones that I like is, um, a company in the grape vineyard business. They are one of the world's largest producers of wine. And what they need when the grapes come off the field, is they need to measure the sugar content in the grapes. And what the sugar content tells them is how much alcohol they can produce and therefore, What wine the different grapes should go into.
And they also pay their, uh, farmers based on the sugar content that's in the grapes. So in the past they used a method to measure the sugar content that would take them about, uh, 30 to 45 minutes per truck. So a truck would come in with the big bins filled with grapes.
[00:11:18] Mitchell Denton: Mm-hmm.
[00:11:18] Wayne Nathanson: What we do is we scan the grapes in the truck as the truck passes underneath our scanners, and in seconds we tell them the sugar content,
So they eliminated that half hour to 45 minutes that was creating a tremendous lineup and a delay.
And we're giving information in seconds and then feeding it directly into their billing system and their payment system so that they can handle it administratively as well.
[00:11:51] Mitchell Denton: Oh, that's fantastic.
[00:11:52] Wayne Nathanson: it's a, it's revolutionising the, the winery business, how they do quality control inspection.
[00:11:59] Mitchell Denton: Yeah. I mean, that's such a time saver and, uh, a weight off the shoulders. That's fantastic. So then what have you found to be the biggest surprise while working in AgTech?
[00:12:11] Wayne Nathanson: Well, that's easy. How much food is wasted. I don't think we realise, the biggest problem in the future with feeding people is that we waste a lot of food and so everybody knows how much food we waste in our kitchens or how much spoils in their fridges.
Um, but what happens on the supply chain is not very well known. And even though we see people in the supermarkets picking out the, the bad apples, so to speak, it doesn't really resonate in our minds what's happening. And what's happening is, as I said before, that uh, almost half of the produce produced goes to waste.
We don't even get a chance to eat, so we gotta change that.
[00:13:00] Mitchell Denton: Yeah, absolutely. Following on this thread and maybe taking a step away from the solution that Neolithics is providing, what in your opinion represents one of the main challenges or pain points in the fight against food loss and waste?
[00:13:16] Wayne Nathanson: Motivation. It means change. It means that people have to revisit what they're doing. And so in a lot of cases when I talk to companies, I see that they have a motivation. It might be cost, or it might be quality standards, but in a lot of places in the world, there isn't enough motivation yet. And one of the things that I heard one time at a FoodTech conference is we all appreciate what it's like when we're fighting over energy, uh, from one country to another.
Can you imagine in the future if we had to fight over food and water?
[00:13:55] Mitchell Denton: Hmm.
[00:13:55] Wayne Nathanson: That's a big risk and something that we've gotta, you know, make sure it doesn't happen.
[00:14:01] Mitchell Denton: So then how do you see the AgTech industry evolving in the next 5 to 10 years?
[00:14:08] Wayne Nathanson: Well, we're in the, uh, software business that has, um, an artificial intelligence engine. And it's not unique, but it's rare, and I think that in months or a few short years, artificial intelligence will be a predetermining factor for being in the software business. It'll, it's going to change our life and everybody hears more about.
AI and, you know, ChatGP T, which is, um, you know, available for free. Uh, Microsoft has made a heavy investment to provide algorithms for companies to build in, and we can make a lot better decisions and. Uh, analyse a lot more data that is meaningful and valuable, and I think that alone will change the way that agriculture is farmed and the way it's distributed around the world.
[00:15:14] Mitchell Denton: Yeah, I agree. On that note, is there a particular group or innovation within the industry that you're excitedly keeping a watchful eye on?
[00:15:24] Wayne Nathanson: Um, I have a, uh, small investment in an Israeli startup called Remilk that I've always been fascinated with. I don't know if you did an interview with them, but the fact that we can create milk from a cell.
Milk and we don't need cows. I mean, this whole FoodTech business of creating, uh, food, whether it be meat or fish or milk without using animals, is incredibly fascinating.
And it's a necessary requirement to revolutionise the way people eat, and hopefully, we'll, it'll be for the better, it'll be healthier, but I can't imagine not barbecuing a steak that came from a cow..
[00:16:13] Mitchell Denton: Yeah. Yeah. We've had a few different cell cultured product companies on the podcast, but I don't think we've had anyone in, in the area of milk before. That's interesting, I'll keep an eye out for that. So then, what advice would you give to entrepreneurs looking to start a company in the FoodTech space?
[00:16:33] Wayne Nathanson: Well, I think it's not just in the Food Tech space, but any entrepreneur that I would give advice to about any startup would be to make sure that there's a justification for their solution. There's lots of great ideas in this world, but if you can't justify why a company would use it, then it's wasted energy and, uh, and not really applied well.
So I think that's, that's a consideration that everybody has to make when they're deciding what business to get in and, and what's the reason for it.
[00:17:12] Mitchell Denton: Yeah. Agreed. Well, Wayne, we are coming to a close, but before we do, I just wanted to ask you, what is the major point you really want the listeners to take away from this episode?
[00:17:24] Wayne Nathanson: I guess the thing that we all have to consider is, uh, what impact can each of us have on reducing food waste?
That could be as simple as not buying as much, fresh produce or food that can't be eaten in time.
[00:17:46] Mitchell Denton: Mm-hmm.
[00:17:46] Wayne Nathanson: But um, it's going to be a much more exposed part of our life over the coming years and it's important for us to pay attention and be motivated to make a difference for the sake of our kids.
[00:18:04] Mitchell Denton: Couldn't agree more. Well, that's all for today's episode of Let's Talk Farm to Fork. Thanks for listening, and thank you, Wayne for joining me today.
[00:18:13] Wayne Nathanson: Thanks for having me and I'm excited to be here and to be part of your mission.
[00:18:17] Mitchell Denton: If you'd like to know more about Wayne and Neolithics, check out the link in the description of this episode. Make sure to subscribe to the podcast so that you never miss an episode, and don't forget to write a review and share with your friends. Until next time, you've been listening to "Let's Talk Farm to Fork," a PostHarvest podcast.