Jackson: Welcome to the FarmBits podcast, a product of Nebraska Extension Digital
Agriculture, I'm Jackson Stansell.
Sam: And I'm Samantha Teten, and we come to you each week to discuss the trends,
the realities, and the value of digital agriculture.
Jackson: Through interviews and panels with experts,
producers and innovators from all sectors of digital technology, we hope that you
step away from each episode with new practical knowledge of digital agriculture technology.
Jack: Hello and welcome to the FarmBits podcast, this episode marks the beginning
of our precision crop protection series in which we will investigate the technologies
that are starting to revolutionize the way that we approach crop protection.
It is also the first time that we will have a new co-host joining me here on the FarmBits podcast.
Zach Rystrom is a doctor of plant health student here at the University of Nebraska
and is interning with the on-farm research network for the summer. Welcome Zach and we're really glad
to have you here on the podcast. Zach: Thanks, glad to be here.
Jack: On this episode of the podcast we are welcoming Dr. Erik Christian,
agronomic services manager at Trace Genomics. Zach: Trace Genomics is enabling greater insights
about the biology and chemistry that interacts within soil to drive forward
management decisions tailored to the particular potential and risk within a given field.
Jack: Dr. Christian discusses Trace Genomics, how they're revolutionizing the way that
growers approach crop protection, and how they're seeking to be enabling data set for
advanced analytics and insights in agriculture. Zach: There's a lot of interesting content in
this episode so let's get right to our interview. Erik: I'm actually, so I mentioned I'm in Ames,
Iowa. I'm at our lab which used to be called Solum. (okay oh yeah I've heard of Solum) So,
Solum was another startup it started in Mountain View, California and eventually they they sort of
started a brick and mortar lab here in Iowa. When they realized you know sending soil samples to San
Francisco is a little bit of a risky thing to do. Jack: Absolutely so, did Trace Genomics then
develop out of the old Solum labs or is it a totally new venture or some of the same
people crossed over what was the deal there? Erik: Yeah, so I was based in this lab, so
before Trace Genomics I work for Winfield united, and I was based out of this this
lab and got the opportunity to go to Trace Genomics, and at the time in 2019 our main
offices and labs were in San Francisco, and again so we're here we are sending
thousands and thousands of pounds of Iowa you know Nebraska, Minnesota soil
to San Francisco and it's maybe not the greatest idea in any way. We got the opportunity
to to purchase Solum in March of 2020, and so we did really merged the two together, ended up
closing our office and labs down in San Francisco moved all of the lab processing here. Most of the
folks that worked in our facilities in California just went remote, so they're all working from home
and now. We send California samples to Iowa instead of sending Iowa soil to California.
Zach: So, what exactly is Trace Genomics and what products and
services does it offer to its customers? Erik: Yeah, so Trace Genomics is an ag
tech startup, it was founded in 2015 by two Stanford graduates
and really the initially the company was focused on
taking soil samples and extracting the DNA of organisms like fungi and bacteria
and then sequencing all that DNA and giving those results back to to growers and agronomists really
to help drive more sustainable management. And so that's really the fundamental
or foundational technology for Trace Genomics, but over time we've really expanded. I can talk
about that here a little bit more in a minute, but what do you do with that fungi and bacteria
quantification and so one of the main things we do is as you can imagine we quantify pathogens.
So, what we're doing is take your favorite fungi our bacterial pathogen and what we're doing is
quantifying the inoculum level in the soil. One thing we also do is, if you think about nutrient
cycling think about nitrogen cycling for example, a fair bit of that is biologically driven. So,
if we're going to quantify the fungi and bacteria we're also going to quantify those organisms
involved in let's say the process of nitrification for example and quantify those organisms and again
we're not one distinction we're quantifying the inoculum level. We're quantifying the organisms
involved in nutrient cycling, but we're not quantifying activity necessarily. That's certainly
something that we're moving toward but we want to be very clear that we're quantifying the
amount of organisms in that soil sample and then finally something that we've added more recently
is the quantification of a lot of the standard fertility parameters, Ph buffer Ph, CEC, organic
matter and so on so forth. So, one of the things I think really differentiates us from traditional
soil testing is not only the fact that we extract that DNA and sequence those organisms, but that we
also have a data set that includes those chemical parameters as we call Ph and things like that,
and we have a really fantastic data science group, and we'll take all that data and we'll work with
our customers to really understand the situation and to look at the interactions the best we can
with the data we have today. So, again traditional soil testing lab you take
the samples you drop them off there, and at the end of the processing they give you some data.
Our interaction with the customer starts much earlier than that, and this is actually one of the
things that I do at Trace Genomics. I work with our customers to really design and appropriate
sampling plan to help them collect the samples to get them shipped to our lab here in Ames, Iowa
and then when the results are ready, I work with them to help interpret that data
to help understand what it means. You know, if you get a phosphorus value back let's say an Olson
phosphorus or brave phosphorus value back you can lean on 50-60-70 years of you know university
research and correlation calibration data to say okay I know exactly how much map or gap I need to
put on. When I give you a quantification of let's say Goss's will you can't go to any researcher and
say well what do I do with this value? So, we have to work really closely with our customer to help
interpret these values and to help drive those management decisions.
One interesting thing this is a bit anecdotal, but when we take a soil sample and we extract the DNA,
the fungi and bacteria from that soil sample and we run it against our bioinformatics database,
so it's got all the genome assemblies and everything that we check for. Typically,
we're only able to classify about 10 of the DNA in the soil sample.
So, that means 90% of the DNA, just the fungi and bacteria that we extract from a soil sample
at this point maybe it's not unknown but it hasn't been sequenced and genome has been made available.
So, there's a tremendous amount we still don't know, think about that 90 percent of the organisms
in that soil sample for at the very least haven't had there, haven't been sequenced and probably
haven't been cultured and identified so and they're doing something. They wouldn't be there,
I've taken enough biology and ecology to know that they're serving some function,
and they're probably interacting with all those organisms that we are interested in. They're
probably interacting with all those biological products that we put on and infer or soil applied.
They're probably interacting with the seed treatments, fungicide seed treatments that
we're putting out there. So, the more we start to know about these be able to very least quantify,
know and quantify these organisms the more we'll be able to start learning about the soil
and all the interactions. But, well I tell you we're at the I mean there's been a lot of soil
microbiologists have been working diligently for a long time over probably over 100 plus
years but using molecular techniques in soil microbiology at this scale is a really new thing.
Jack: And one thing that you mentioned there which I think is where we should probably start
because that's where everything starts right is the soil sampling, and so when you talk about
putting together one of these soil sampling plans, and I guess coming at this from a precision ag
point of view I mean we know there's a lot of spatial variability within a field, and
I assume that there's a decent amount of spatial variability in terms of maybe different fungi or
bacteria in the soil, and so how exactly do you design those soil sampling plants in terms of
you know spatial locations depths and all that sort of stuff to provide you the information
that you want to have to work with the grower? Erik: Well yeah, you're exactly right Jackson
there is a lot of variability in a lot of soil parameters not just the biological ones but folks
are not as used to sampling for the biological parameters. So, really we're just starting in
this journey to understand what's going on in the soil biology there's only a few companies that
have this technology and that it's commercially available. So, we're really all writing the book
on this, and so one of the things that I like to start off with saying is like any company,
in any startup, we want to be disruptive but we don't want to disrupt everything. So,
when it comes to sampling I like to align sampling the best I can with what folks are already doing.
I would say you know so, I came in and said okay I want you to sample in august in a
corn field in Nebraska. I want you to take 80 cores per sample, and I want them to be to exact
depth of two inches and you know you know nobody's going to want to do this right. We first start off
the conversation with what do you do what do you do today how's your standard fertility sampling
and start to get an understanding of what folks are doing today and then make sure we align
or modify that sampling to what they're looking for in the soil biology, if it's
purely exploratory well then we sort of have to be you know we have to sort of aim for the middle. If
we know we want to look for a specific organism, or we're trying to solve a specific problem,
well then we align it. But, sort of one of the big things that doesn't change between what folks are
used to now and what we're trying to do is the fact that when we get a sample, we want it to be
a composite soil sample, so it has multiple cores that are distributed in an area, and we want that
soil sample to be roughly one pound four to five hundred grams. So, that that looks no different,
our bags we get in our lab here look no different than the bag of soil that you collect today.
Now, the strategy of how we collect that as you mentioned the depth you know how many cores where
we're going to get that sample certainly can vary from what folks are used to. So,
even the depth you start looking into soil testing and soil fertility the depth that we soil sample
in Iowa is a different depth than the soil sample in Indiana (interesting ), and you know it really
has to do with that correlation/calibration. It has to do with historically what folks
you know deemed was the depth of incorporation of nutrients and lime and things like that.
So, you know talking to folks in Nebraska you know most often we're going to be collecting a
sample that's probably zero to six inches, which is pretty common, probably when you're talking
about a six inch sample you're probably looking at 10 to 12 cores would make a nice a nice sample.
You know folks that are really in a hurry and have thousands and thousands of acres do typically will
do less than ten cores, but that's what we like to do. You know, then you get into the grid versus
zone right that's a bit of a religious question in my opinion. I have a lot of opinions and
feelings about that and both are work well in in different scenarios but zone is where we can
really dial it in for sampling for biology. If we know again what organism we're really
interested in, we can design those zones to really capture that variability that spatial variability
and make sure we find that organism. So, for example if we're out hunting for a pathogen let's
say Goss's because it's something that certainly a lot of folks in Nebraska have been battling for
a long time, what decision are we going to be enabling you know? We probably variety,
selection, rotation things like that tillage you know that's obviously a way to to combat that. So,
what information do we need to find from a soil sample that can help drive those decisions? Should
I plant continuous corn do I need to you know as hybrids become more tolerant to disease do I need
to consider that as a management tactic and so, if we took let's say one soil sample per field,
we run the risk of not finding the problem. So, if they have two, three, four samples available to us
where can we strategically place those samples to make sure that we find maybe the levels of
high inoculum that can help drive the decisions. I think that we're a bit out from really being
implemented at grid scale let's say as fine as 2.5 acre resolution, we've done plenty of fields at
that resolution. It's extremely cool to see that data, but we've got to get to a point where that's
a cost effective and really zone's a nice way. Zach: So, some of the applications that you've
mentioned already or you know testing for pathogens, testing for nutrient cycling microbes,
what are some of like the potential other applications because I know microbes are involved
in a lot of processes such as microbial breakdown of pesticides, pest control as well such as BT
and then also what about maybe like the environment that the microbes are living in
is there anything that you're working with to maybe alter the environment based on management
practices to favor some microbes or maybe harm others that are negative like a pathogen?
Erik: Yeah it's a great question Zach, and really today where Trace is at is we're
really in an enabling data set or our technology to go down the road that you just mentioned. Now,
we don't specifically work in those areas where we're actually recommending approaches or even
sometimes digging into some of the questions that you've asked. But, we work very closely with a lot
of folks who do that ask the same questions that you just asked, how now that we can quantify and
perhaps get a baseline of what's going on in soil biology, how can we start to understand
that better and to use that to really be better managers right, and so one of the things we do
along that line. We really have a few main areas of customers of course the the logical one is we
work closely with agronomists and growers right, working to drive better management decisions. But,
another thing we also do we work a lot with product manufacturers of biological manufacturers
helping them understand how two things how their product impacts the soil microbiome and also on
the other side how does the soil microbiome impact the efficacy of their products. So, two ways you
can look at that because we have this amazing technology. It allows us to really to do that,
so that's one of the things that we're really working on. When you start going down the road and
some of these really interesting questions about you know suppressed disease-suppressive soils
and all these really cool things, a lot of that research right now is coming out of academia and
they're really focused on various tiny and very specific questions, and so we also hope to enable
that sort of research as well. But, really today where we're at Zach is really a tool to help
enable a lot of that, a lot of our internal r&d is very much collaborative with folks like as I
mentioned agronomists with product manufacturers and really goes to the level of we've done some
modeling work looking at pathogens. So, if you think about what I mentioned earlier
we quantify the inoculum level. Well, if I recall back to my plant pathology courses
and Zach, you're you're a dph student what do we really got to consider what are the three
things we got to consider? Well, there's a disease triangle that includes the environment, the host
and the pathogen yeah so Trace we know that we do a pretty good job on one of those. I'm not the
world's greatest agronomist, but I can know what the crop is when I walk into a field, so there's
an environmental piece, and so that's really a big part of it is if you have a high inoculum level
that doesn't mean you have imminent infection and you have yield loss right it's not,
and so we know that, and we're working on various efforts to model out certain pathogens
in certain situations to better understand using our technology. What's going on now,
I also like to think that even this step of quantifying the inoculum levels is I always ask
people you know what do you do today if you have soybean sudden death syndrome for example? What
if you took a soil sample where would you send that to to get the quantification of the inoculum
level and you can't there's nowhere to send it. So, already that first step is a big step
in just being able to to quantify the organisms in a soil sample and we know we can do better
by creating models and helping drive very specific recommendations, but it takes time.
Jack: Now, that's I think that opens a whole new field of questions for this interview
just thinking about kind of the data aspect and thing about Trace Genomics is kind of an enabling
technology how exactly are y'all leveraging the data that comes out of individual fields and kind
of what you know about that field alongside, and I don't even know I guess kind of to start are
you even aggregating data and bringing it all together in kind of a way that machine
learning or something along those lines could be leveraged to figure out okay these environmental
conditions this Ph, this soil temperature is is related to this certain inoculum level and
actually the presence of disease once we get to say R2 and corn I mean are those
things that you're working towards right now? Erik: Yeah, you know that's a great question
Jackson, and so that's why I wanted to make a point that we do have a data science group at
Trace Genomics, and we're not just a traditional lab in the sense of we're just a data generator,
we're a partner all the way through, and we're also an R&D organization at the same time, and so
I mean our folks in our data science group they can do things I can't even imagine. Like, my end
of my statistical ability like ends with the last day in anova right I mean I'm done after that,
and they're using these really fancy machine learning techniques
and applying that to really look at our data set and try to understand what's going on
because if you think about every soil sample that we capture, if we're going to extract the
DNA of the fungi and bacteria and sequence that, that's a massive amount of data right
there and then you add in you know the chemical parameters and we do a very comprehensive panel of
chemical parameters in the soil and then you start in adding other layers productivity.
You know, whether it's yield or imagery, as applied layers you name it and it becomes
a fairly hefty data set that really needs some good statistical techniques to tackle.
Now, what do we do today from the customer standpoint that you get with every sample
we do aggregate the data anonymously at the national level and what we do is what we call
benchmarking and basically we'll take all that data let's say for corn or soybeans,
so that when samples come to us the folks collecting the samples have identified the
past crop and the current crop. They identify if they're sampling in season or out of season
they typically we're supplied the GPS coordinates of the center probably of the composite sample
and we have all this information, so what we might do is take all the corn samples
and we'll aggregate that data and we'll create benchmarks, and so what the benchmarks are
is as Zac mentioned we have good IPM principles such as the disease triangle, but we also have
economic thresholds, economic injury levels and things like that
currently. We're always working on capturing that data but until that time
why don't we tell folks where you where your samples lay in relation to everybody else's.
So, what we do is actually we fix a benchmark that you can compare the data from your samples to
all the corn samples that we've received now to take that to another level. We work with folks
from the Gulf of Mexico, all the way up into Canada, and let's say they're soybean producers.
So, here I am in Arkansas one day talking to a soybean producer then I'm in southern Illinois,
I'm in Iowa, I'm in North Dakota, and I'm comparing the amount of
soybean sudden death syndrome or phytophthora or white mold from one day to the next,
to the next across those geographies. The folks in Arkansas are going to say other than work the fact
that we're both growing soybeans, there's a lot of difference to North Dakota to Arkansas right,
so why are you comparing my pathogen levels to theirs and so what we've done over time as we've
really collected a lot of samples from a wide variety of areas is we've created what we call
smart benchmarks. So, smart benchmarks are still an aggregation of data across
numerous farms and growers but what we're doing is aggregating at the level of like soil
properties so apparent material environment and cropping systems so you could say well you're
not necessarily comparing to the field next year but you're comparing it apples to apples
right. I'm comparing all the soil samples that are collected in southeast North Dakota.
Well, I'm comparing all the soil samples that are collected in northeast Arkansas, but I'm not
comparing the two right and so you know that that was one of the lessons I learned a long
time ago when I was in the seed industry, talk about this idea of yield stability and hybrids
and varieties right. This hybrid did great across five states and you know it just kicked everything
you know and inevitably the grower would say well I really want plot results from the nearest plot
you know in the county whatever, I don't care if this hybrid did well over five states in three
years. I want to know what it did right next door right. So, it's no different than pathogens you
don't want to compare what's going on northeast Arkansas to what's going on in North Dakota.
Jack: Sure, I think that makes a lot of sense, I mean it's the smart benchmarking
it's just kind of a crazy concept. I know farmers really like to get a lot of feedback, I mean have
you had any farmers that ask you if the data can be used negatively against them I'm just
gonna play devil's advocate and say like you know in this data security you know place that we are
in digital agriculture, farmers worry that okay if I know that I have this disease is this going
to be something that you know crop insurance or somebody else my banker is going to know about
and it could potentially adversely affect me. Erik: I don't know just how secure is that data
I guess that Trace Genomics is generating so sort of a similar scenario if I send my DNA
off to 23 and me and the next day they give it to my health insurance company.
Yeah, I mean that's a viable concern, but we have a lot of folks in the company that
have spent a lot of time in ag tech and have have really been very observant of that, and so our
guidelines for sharing and for technology are very strict in that we don't share any data.
We aggregate anonymously obviously in some certain things like that, so we're not, we're not sharing.
Being a startup you know people worry well okay today you're a startup and you say okay
we're not sharing your data but what happens if a large company or somebody buys you out
then all of a sudden they're they have your data yeah, and certainly that's a concern
as well and so that's a great point Jackson and we do our best to to keep people's data safe,
and we don't share with anyone. Jack: Sure, and I think that's the
right standpoint it's just something we always I don't know I feel like we
ask a lot when people are collecting a lot of data because it is such a
big deal and something I hear from a lot of farmers here that they're concerned about
in this new digital age that we're in. Erik: Yeah, well I mean this is probably
something you've covered on other podcasts with people that are much more astute than I am in this
area but who paid for the data who literally gave you the money that then that's that person's data.
There's a lot of nuances to that, but I believe that that's really the way it is. I'm a farmer
I've you know worked with a lot of different programs and different platforms and you
know I pay for that service. That's my data and I don't want it to be sold to anybody.
Now am I naive enough to think that those companies aren't using it to learn more to create
you know aggregated you know anonymous insights, but for them to sell it off that's not something
that a lot of growers would be excited about. Jack: What it does it look like for a customer
on the who's receiving a Trace Genomics report what are they able to go in and see
what do those recommendations or measurements look like to them and how
actionable is that really for them in the field? Erik: Yeah so, today if you you collect a soil
sample we'll enter as I mentioned we asked for a bit more information than your standard soil
testing lab would. We want to know a bit about the cropping history, we want to know the depth
of the soil sample the data was collected also the GPS coordinates for that soil sample
and then you're able to upload a shapefile boundary and also zone boundaries if you have
them into our customer portal and when the results ready, whether it's you know the quantification of
pithium or the quantification, nitrification or ph all that information is geospatially rendered in
our online customer portal and so people are able to manipulate that. We do a bit of sorting and
surfacing of issues there as well. For example, for a pathogen our quantification of pathogens
that inoculum level is in parts per billion, so folks that are used to traditional soil testing,
you know you might get your brave phosphorus in parts per million or your potassium value.
When we report our pathogens, we report those as an absolute quantification in parts per billion,
and so you can see geospatially rendered that map and then we also do a bit of rolling up to
the field level to be able to, like I mentioned surface issues like okay you have a field that
has really a hot spot for goss's as well okay you need to take a look at this first
versus fields where we have less inoculum or you may not need to focus on it right away. All that
data is available all the time it's just that there's a lot of parameters. We want people to
sort of help, we want to help folks through that. As I mentioned, we have a lot of ways to get
the data out whether it's a pdf report or a csv file. If folks want to take that data and put it
into their favorite fmis, but we also have a view where you can do some sorting and filtering. It's
our legacy portal and it's a bar chart, you're able to sort by farms and fields and different
parameters in order to manipulate the data. Now, one thing you asked about were recommendations and
we actually we don't produce any recommendations today. The closest thing would be the benchmarks
we talked about earlier, you know creating fertility wrecks or you know creating very
boring prescriptions and things like that is not something we do. We're happy to work with folks,
we do have apis with a few of the major softwares that folks can grab our data
and run them into those programs and to create wrecks, but we don't do that today. Obviously
it's something that we're extremely interested in and we're working on it and you know we
cover a fair bit of the United States from apples and lettuce to corn soybeans, cotton.
You know, we really rely on that local expertise to take it that last mile and but we'll work with
those folks. We may not write recs, but we work with folks who do and enable them to use our
information to really drive those decisions. It's awesome and so it's not that we don't we don't
want to do that and that we couldn't, I mean we have a really beautiful platform to allow us to
do that, we really want to put the data in the hands of the experts and help them go that last
bit. Jack: Have you heard any stories or been part of any stories that are particularly successful
outcomes that growers have had out there from using what Trace Genomics offers to them?
Erik: Yeah, there's a couple of ones that get me really excited and a while back we were working
closely with a grower who had basically more or less quit growing soybeans had a terrible time
with soybean sudden death syndrome and just you know was gonna sort of wait it out and
mostly just focus on corn. We were able to sample a field that had been in corn for quite some time
and to really get an idea of what the inoculum level was at that point in time, in that field.
For soybeans sudden death syndrome we were able to get some soil samples, compare some
fields that had been rotated corn/soybeans every year and sort of had known levels of
SDS and really give the growers peace of mind that the levels have been reduced in that field
and that perhaps it was okay to reincorporate soybeans into that rotation. You know, we all know
as good agronomists continuously growing a single crop can certainly be done and there
are no laws against it. But, it's certainly you know every once in a while you gotta break that
rotation and add something back in. There's another example that got thinking about
and as a few years ago I was working with a grower actually agronomist excuse me and we were going
over the results for the first time, and I was really trying to help the agronomist understand
how to interpret our results. So, I went through a few fields and interpreted the results,
and I pulled up at the time it was still bar charts but pulled up a bar chart of another field
and happened to be charcoal rot in soybeans and I said you know looking at the data from this field,
what what would be your interpretation and the agronomist directly looked at
one of the quantifications which is in the thousands of percent of our our benchmark
value. So, it was pretty high value for charcoal rot and proceeded to pull out his phone and showed
me a picture of a plant, a soybean plant that had some extreme charcoal rot issues
and it was exactly in that area where we had found really high levels of inoculum,
and so that was that was really exciting and of course then people are really buying into your
technology and and what what you're doing when you can really confirm their knowledge of the
field and what they've seen. It really makes you feel good when when a farmer can say yeah that's
exactly what I've been seeing point to it on the map and that that's my problem and yeah it just
makes it so much more tangible. I know you're the you're the one asking the questions, but I might
skip to one of your questions you asked about how can people perform trials to test efficacy or
the what we do and I tell you what people do that every day, and I think it's great. I mean we want
to be as open and transparent with folks about our technology as we can to build that level of trust
and so we often get blind samples abc123 you know and folks send them in and they know
this came from a a level area of the field of high infestation or low infestation or whatever
and they send them to us to see if it tracks. I mean we I was just talking with one of our
scientists today on some development work. We're working closely with a group of agronomists and
they want to test our capabilities out by sending us samples, and they're not going to tell us is
it high or low or in between to see I've even had some agronomists and I love this I have no
problem with this. You know, they name samples high medium and low and they send them to us.
We get results back, and I'm just sitting there going oh well high, medium, low
results are you know completely the opposite of what I'd see and you go you I'm a scientist.
Scientific integrity is of most importance to me the data is what the data is, and I believe in
our process so we take the data to the customer and they go you know, let's reverse what you
know high, medium and low labels and they go oh yeah don't worry about that we flip the labels.
(That's pretty awesome) It's interesting now you don't expect that every time,
most people don't do that, but I've had a few instances where they've done that. I
say, you know test us out. I mean we're you know if you think about the technology adoption
curve we're really in that the innovators, early adopters we're talking with the folks that are
trying all the new technologies and want to try it out and typically
they really enjoy these new technologies. They have a hefty skepticism, but they also give
you a lot of room to run. They know you're not perfect by the time you get to the average grower,
the average agronomist you got to be bulletproof right you got to be a technology that's really
tried and proven, but we work a lot with the innovators and it's a lot of fun to
see how we match up to their expectations. Those people help you get there, they're almost
like partners in the development when they push you like that and make sure that everything is
I guess performing up to their standards in a way. Jack: So, exactly where can our listeners go
to learn more about Trace Genomics, I mean obviously there's a website but
are there other resources you would point them to? Erik: Yeah, certainly the website is a great place
to start and actually that through that you can filter to our sales folks or our customer service
people. I'm always happy to ask answer any questions that folks have,
we also have a few sales folks out in the field, but a lot of the work that we're doing as I
mentioned is really going through agronomists, through to retailers and I'd be happy to help
folks find their nearest retailer that they may be able to buy our testing through and that's
probably the easiest way to get a hold of us. Jack: The last question that we always ask in
these interviews is for some advice, and I guess what is some advice that you might have for
individuals that are trying to stay ahead of disease and other problems that might be
occurring in their field and looking for that way to get their next edge over
their problems they're facing in their crops? Erik: Sure yeah, we're always, everyone's always
trying to do a better job whether it's financially or agronomically, environmentally and so you know
these tools like what we have at Trace Genomics to be able to take that first step as I mentioned
earlier you know if I want to send in a sample today to get quantified for soybean sudden death
syndrome you can't send it anywhere or gases will right. So, we're enabling that capability and that
first step, but it's got a long way to go and here here's something interesting to think about
if we're geospatially rendering the amount of pythium or if I top there in your field think
about the different management tactics that we've just enabled I think we just enabled
you to be able to place varieties for let's say phytophthora and soybeans
in a field and you may be able to place a a variety that has low-fi top-third tolerance
in one area and in areas where we find a lot of phytoplay you may want to put a
a resistant variety same with pithium. So for example, seed treatments really
have gained a lot of popularity not just in soybeans but also corn you start to think about if
you geospatially knew where there were differing amount of pithium in that field and you could have
the ability to potentially variate where you put different seed treatments, now what I would say
is our technology is a bit out front of people's appetite maybe ability to do those sort of things,
but if you look at ag tech and some of these things it's a back and forth right. We have
equipment gets out in front of the data and then the data gets out in front of equipment, so it's
very interesting that we have a technology. If you were able to soil sample you could actually enable
some of these decisions that maybe people aren't ready to to enact yet, and so I think that's
really cool because you'll see treatments on one hand have been pretty cost effective, and it's
pretty decent ROI there, but I think maybe one of the things will be the environmental aspects of
some of these things won't be necessarily that we're enabling you know folks to real really save
large large amounts of money but maybe to be a little bit more environmentally conscious of where
they're they're doing some of these tactics. Jack: Sure I think that's super interesting
especially about the interplay between the machinery and kind of these decisions and
recommendations because I remember an episode we had about multi-hybrid planters and it seemed like
those never seem to really catch on in many places and maybe aren't even really being produced by
some companies anymore, but if you think about what you just talked about where you can have
you know treated versus untreated seed and put those in the right places maybe you've
got two different hybrids that respond differently to different disease. I mean
all of a sudden that data that you've now provided makes that multi-hybrid planter worth having.
Thank you very much to Dr. Erik Christian of Trace Genomics for taking the time to join us
on the FarmBits podcast, I really enjoyed getting to hear some of his expertise has been gathered
over many years spent in the industry with a lot of different facets of crop production.
One of the things that I thought was super interesting about the episode is
number one how they're leveraging data to basically create better insights for farmers
through anonymized data, and they're also providing like these specific benchmarks
for farmers but really I thought it was great when he got to at the very end of the episode exactly
how some of these insights can be turned into management decisions to make better use of the
precision equipment that we have out in the field. Zach: Yes definitely, and a lot of the
agronomists, growers and other companies that Erik is working with are definitely early adopters
of this technology, and they're driving agriculture forward into the future.
Jack: Absolutely yeah it's there's a lot of cool stuff I'm sure we'll see a lot of cool stuff from
Trace Genomics here in the next few years. We hope that you enjoyed that interview as much as we did
and we look forward to you joining us next time here on the FarmBits podcast thanks.
Sam: Thank you for taking the time to join us today on the FarmBits podcast,
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to members of the agricultural community in Nebraska and beyond.
Jack: The opinions expressed by the hosts and guests on this podcast are solely
their own and do not reflect reviews of Nebraska extension or the university of Nebraska-Lincoln.
Sam: We look forward to joining us next week on FarmBits.