Narrator: The following presentation
is part of the Agronomy and Horticulture Seminar Series
at the University of Nebraska Lincoln.
-: Right, good afternoon, everyone.
And it is my pleasure today to introduce my colleague
and associate professor Romulo Lollato
from Kansas State University.
Romulo is originally from Brazil.
Actually, he was raised in a farm
where he grow since he was a child.
He grew wheat, sorghum and other crops,
but later on he decided that there was no
so much excitement going on in the farm
so he decided to move on to Paraná State,
for his education at Londrina State University,
where he got his BS degree.
And after that, it seems like Sao Paulo
was not funny enough for him.
So he decided to go to Oklahoma State to get first
his master degree in plant and soil sciences.
And later on his PHD in crop sciences
with a specialization mostly on wheat,
and later on Romulo got this position as an
assistant professor in Kansas State University.
And later on, he was promoted to associate professor.
He has an 80/20 extension research appointment
and he is one of the most and recognized
national-wide experts on wheat production and physiology.
So it's a great pleasure to have you today
with us Romulo and the floor is yours.
-: Thanks you Patricio,
thanks for the introduction and good afternoon, everyone.
It is my pleasure to be here today.
To me, it's very exciting
to be presenting for the Department of Seminar here in UNL.
Very humbling as well,
because as you're gonna see a lot of the work
that we are doing actually is much of it is inspired
by some of the work on yield gaps that has been done
in soybeans and corn here in Nebraska as well,
and other parts of the globe.
So it's very inspiring to me.
So the wheat we grow versus the wheat we could grow,
I'm going to start off this presentation here
showing you a photo of farmer field
that I work with quite often in Western Kansas.
And that's also part of the inspiration
for most of the focus on our project.
So look at this wheat field here.
This field is placed about 30 miles
from the Colorado border.
So definitely one of the driest spots
in Kansas gets pretty hot as well during grain filling,
but still look at the potential of these wheat crop, right?
Very easily here, somebody can say,
well, it's gonna hit at least 100 bushel per acre there
based on that populational heads, right?
And in fact, 121 bushel per acre
in this specific field here close to it
or 8.1 tons per hectare,
they were the 2016
National Wheat Yield Contest winner there.
And very consistently they tend to be winners
on that yield contest,
that takes a lot of management, right?
Definitely that takes the potential of the varieties
to reach that yield level,
but not only that management as well,
not only in season management,
but across seasonal management,
they're managing their fertility
not only for that single crop, but across crops,
they're trying to improve their soil organic matter.
So then you have perhaps more water available
for that crop in these dry land regions
that can even improve your yield potential
just by having more water available to the crop.
So a lot of inspiration there coming
from working with some of these growers as well,
that are being able to push their
wheat yields as high as these examples.
I'm not gonna spend much time on this framework here,
probably very familiar to many of you,
but what we're gonna work with in most of this
presentation is the concept of water-limited yield
which is how far we can push
under optimal conditions in dry land environments, right?
We're not talking about irrigated wheat.
We're talking about rain-fed wheat
as most of our focus are placed in Kansas
94 and 95% of the crop is grown under rain-fed
or dry land conditions.
And we use that as a benchmark to compare
to our actual yields or the yields that are then
in farmer fields that are reduced by diseases,
by sub-optimal perhaps planting date or pest
and so on, and that originates that you'd get, right?
So very briefly here, just a framework
that we're gonna work with in this presentation,
before I go into some of the research
that we're doing.
With this mind, right?
Water-limited yield and the yield gap,
we can look at the assessment that we've done here
in collaboration with Patricio
and this is in the Global Yield Gap Atlas
where we use crop models that were calibrated
for the potential of our current varieties
to simulate what is that water-limited yield potential,
which is what we're looking at here, right?
And the region that we're studying over here
probably ranging between that five, two to six
or even seven tons per hectare
in terms of a long-term yield potential.
And the question now is how does
this compare to our actual yields, right?
Then when we look at that the relative yield
which is the actual yield divided by the potential,
we are probably around 40 to 50% of where we could be.
So the potential of the varieties are there, right?
We definitely have a variety that
are reaching that 120 or more bushels per acre
if the environmental conditions are there.
And especially if the management practices
are there as well.
So that's what we're gonna
focus most of the presentation here, moving forward.
So we know that there is a large gap.
I mean, we use these based on 30 years
of simulations there compared to growers actual yields.
And so now we move on and try
to understand how can we narrow that gap.
So I'm gonna start off here with some data
that we collected from actual growers, right?
We went out there and we interviewed growers
trying to get data from their commercial fields,
how they are managing their own fields
and what's the yield level on those commercial fields.
And essentially this is a map showing
each one of the fields that we were
able to collect data from.
So close to 700 commercial fields
spread all over Kansas perhaps are not
representing the Southwest part of the state as well.
But we do have a pretty well distributed number
of fields and a good number of fields
that we collected management data from.
So each one of these fields, we had the students
sit down with the grower and go
over a series of questions, right?
So each column here would represent
a different field that we were collecting data from.
So you can see there, dry land fields,
those are previous crop,
previous crop two years before that,
planting date, variety, nitrogen rate
and all the management practices
that were performed in that field, right?
Tillage practice all the way to fungicide applications,
harvest date, and grain yield.
So again, in each one of those individual fields,
we had all of the data that was into producing that crop.
Whenever we're looking at these
and try to understand
what are some of the driving factors, right?
There's quite a bit of variability
in weather in Kansas, just like here in Nebraska as well.
We have a very steep rainfall gradient
going from about 1000 millimeters
in the Eastern part of the state to about 400 millimeters
in the west there in terms of annual rainfall,
there's also a temperature gradient, right?
So we need it to kind of stratify these fields.
So we can actually try to learn a little bit more
in terms of what wheat growers are doing in each region.
And how does that relate to yield?
And essentially we divided these
in three main regions based on
long-term weather conditions, right?
The Western region in purple here,
it's a dry region.
And that has a relatively cool temperature regime
as compared to for example, North Central,
which has the same temperature regime,
but it has more rainfall,
in North Central which has about
the same amount of rainfall that we have in North Central,
but a warmer temperature conditions, right?
So three very distinct growing environments
based on long-term weather data here,
dry and cool, warm, moist and cool
and warm, moist and warm.
For each one of these fields as well
we went ahead and we collected soil data
and daily weather data
and we did a simulation or the potential
conditions on each one of those fields again,
to try to understand how far our growers are
from the potential in their own fields.
This is a distribution of those 700 yield levels
that we collected from growers, right?
You can see that we arrange it from as low as about
five bushels per acre, or 300 kilos per hectare
all the way to about seven tons per hectare there
with an average of 3.8 tons per hectare.
If we compare to the statewide yield level,
that 57 bushel per acre in this period,
average statewide is 53 to 54.
So we're pretty close,
maybe our growers were a little bit higher
than the state average, but very, very close, right?
So this is the distribution of the yield levels
from this commercial fields that we got.
Now, when you compare those, again
to those crop simulation
models that are calibrated
for current cultivar under potential conditions,
will have an yield gap of about 44%.
So, aligning really well with some of the longer-term
simulations that we had for the Global Yield Gap Atlas.
Now, one of the things that
I like about this on-farm surveys,
the first you get a snapshot
of how growers are managing their crop today, right?
And that's what we're looking at here.
How are our growers managing their crop
based on region within the state,
North Central, South Central and West.
And very clearly we can see
some obvious differences there for example,
sowing dates and seeding rates
in terms of the central regions,
being more similar to each other
as compared to earlier planting
and lower seeding rates out in the west,
but we can characterize many of the other things, right?
What's the average nitrogen rate
that they are applying,
fractional growers applying sulfur,
flag leaf fungicides and I apologize,
but it seems like it's a little bit off here,
but I think they're asking for example,
only 40, 50% of the growers using sulfur.
Again, only 40, 50% of the growers
using foliar fungicides as well.
Many of these factors that we can speculate
that are going to be impacting yield
and we can also characterize previous crops.
So here about 75% of the growers in Western Kansas,
they were in a follow-up period
and 50/50, more or less soybean
and wheat in the central part of the state,
very different rotations, very different crop management
on each one of these regions here.
And the next thing that we can do
that is of interest as well is try to see
how these management practices are associated
with yield in this commercial fields.
This is an example here for the Western part of the state.
We're looking at sowing date,
and this is days after September 1st.
So day 30 here will be September 30th, right?
And we don't see much relationship
across the entire data set,
but if we look at how far the growers
are being able to push through
that boundary function approach,
we can actually see a very steep decrease in yields there,
first we can actually identify
more or less what is the peak?
So if I'm a grower in that region
and I can plant all my crops
in one day where I would like to be,
but then second one can actually see that
very quickly here after October 5th or October 10th,
more or less yields are,
the yield potential is actually going down
in a pretty steep way.
Remember, Western part of the state
is a colder region, right?
If we do the same comparison
for a warmer region in south central here,
first thing, it's a later planting date.
So our optimal is more around that October 14th.
And it's not nearly as steep, right?
Actually, there's quite a bit of room here
for growers to plant as late as sometime in November,
November 1st, November 5th here
and still have a pretty decent yield potential.
So again, more temperature accumulation
in the fall allows their crop to tiller better
and it's more forgiving in terms
of if you're planting late,
there's some critique in terms of use
of on farm data like these,
'cause it's not replicated in so on.
So for you should test
the same hypothesis here using replicated data,
what we've done,
is we've looked back in 20 years,
a variety trial data in the region
and so it included Oklahoma, Kansas, and Colorado
based on the weather again,
we divided into these several 11 regions here, right?
In the regional one being a colder and drier region,
region 11 here, warmer and more moist region.
The size of those points are how many observations
we've had in each one of those variety of trials.
And this project we're working
with near 100,000 yield observations.
So it's quite a few yield observations.
We can't really say that
we don't have replications here anymore.
And if we do the very same exercise, right?
Of just looking at that boundary function,
and I'm gonna focus on the same regions.
So Northwest Kansas there
and south central Kansas here, right?
That's what we're seeing there.
Very, very similar.
Remember that I had mentioned September 28th
as the peak from the grower data.
And I had mentioned October 14th from the farmer data.
So very similar peak and also can see much steeper
yield losses here as compared to here.
So the data they're talking really well,
even though they're coming
from completely different sources.
And one interesting thing about these
is that we can now kind of still go
for this entire region.
Again, if I had one day to plant my wheat crop,
when should I be focusing, right?
That's not realistic, but at least growers
can be some somewhat surrounding that date.
And it's earlier in the Northwest region.
And later as we go south,
very well, it was just to
kind of like a ground proof here
of some of the concepts in our grower data.
But going back to that grower data,
another thing that we can start learning
is how our growers in the low yielding fields
managing their crop as compared to
which are in the light purple bars
as compared to growers in the high yielding fields
on the dark purple bars, managing their crop.
And here, we're just looking at the nitrogen rate example,
and we can see that for north central, south central
there is a significant difference
in adoption in terms of nitrogen rates
between low yielding growers and high-yielding growers.
In the west, not as much,
we're not able to detect that difference,
perhaps because out in the west,
they can rely more on soil nitrate at planting as compared
to some of these other regions,
because it's a drier region,
but we we're not able to find
significant differences in the west.
Adoption of foliar fungicide
it was pretty consistent across regions here
that was much more frequently
adopted in high-yielding fields as compared
to those low yielding fields.
And here each bar here has about 30%
of the observations that we have.
So these look at individual management practices, right?
We can actually try and put it all together,
management practices with weather data
and with soil data and use some sort of more,
a machine learning approach
or a conditional inference tree is here.
I'm not gonna give you many details here,
but the main points that we need to look at,
these for North Central Kansas,
Total nitrogen rates being
number one driving factor there,
and the highest yields were a thing then when
there was more than about 500 millimeters
growing season rainfall.
Now, flag leaf fungicide is also an important factor.
Previous crop was affecting grain yields there as well.
Again, total nitrogen rate being important,
even in lower yielding environments here.
And then a couple of things
that were probably more negatively
if you have a very dry growing season, right?
Related to lower yields, or if you have
a very hot grain field period,
that was also associated with lower yields.
Now, this is for north central Kansas.
If we look at this and again,
we're not going to go in detail,
but if we look at the other regions again,
have nitrogen related strategies here,
either the source or the stage of application
or the rate, foliar fungicide appearing again,
a maximum temperature being related to lower yields again.
In Western Kansas, very similar pattern, right?
We have nitrogen related management practices
appearing as important in these condition inference trees.
We also have the presence of sulfur there
and I'm gonna focus a little bit on sulfur here too,
'cause we've see more and more sulfur deficiency
around the state,
flag leaf fungicides appearing again.
So from these on-farm survey
that we collected from these
700 commercial wheat fields here, right?
We ground through our yield gap about 44%.
So a large yield gap there
that we can probably help fulfill that through management.
Sowing date, as an important determinant
of the yield potential of the crop,
maybe not necessarily related to the average yield
but to the yield potential of the crop
and then many improvements for many opportunities
to improve yield through nitrogen management.
So for adoption, fungicide adoption as well
as some other smaller things
that didn't appear as frequently, right?
Well, at this point though I wanna give a short,
I wanna tell you a short story here, right?
And this story is a story about two farmers from Brazil.
They love to fish, but they just that's their hobby.
They live to fish.
Any chance that they have, they will take
a vacation and go fish.
So during these vacation specifically here,
they actually took a weekend and went to the Amazon, right?
So they rented one of those small single engine airplanes,
hoped in, the both of them and the pilot,
went to the Amazons, spent a week fishing there,
and one of them caught about
150 pound catfish, huge catfish.
And he wanted to bring it back, right?
He wanted to, I mean, bragging rights.
He wanted to bring that fish back.
And the pilot he was saying,
"well, we can't really bring that fish back.
"It's a small single engine airplane,
"if it's both of you, myself and the fish,
"it's not gonna handle."
And they were discussing back and forth
and discussing back and forth.
And suddenly the other farmer said,
"well, but last year we were very similar airplane,
"same size I caught a fish about this size
"and the pilot allowed us to take it on
"the airplane we us."
So this pilot was like, "okay,
"are you sure everything was the same,
"the airplane size and everything?"
"Yep, we're good."
"All right, so let's do it."
And so they hop in the airplane, the catfish
go there with them and as soon as
this plane has taken off, it just goes down, right?
Just crashes, too heavy, right?
The plane couldn't handle all their
weight as the pilot had mentioned.
Now, everybody's okay.
Nobody got hurt, right?
But one of these farmers starts getting
out of the airplane and he's cleaning himself,
cleaning himself from all the dirt.
He starts looking around, looking around and he goes,
"isn't this the very same spot where we crashed last year?"
So, there was precedent there, right?
They did it again and had the same results, right?
So if we continue keeping, in the message
and the reason I always the story is that,
business as usual might not take us where we need to go.
We need to look at opportunities to narrow
that yield gap and perhaps doing things
a little bit differently,
which is the example of that on-farm survey.
And also the example that we're gonna
move on now and switch gears to some
of our small plot research
that we are also focusing on these narrowing yield gaps.
This is the example of some of our trials,
how they look like, about five by 30 plots,
very standard, and small plot research here
we run about five or 6,000 of these every year
in several locations across Kansas
and that's what we're gonna be focusing on,
in the remainder of the presentation here.
Very well.
First thing that we want to develop was
information on how do we improve yields
but now perhaps using a more physiological approach, right?
How do we make our recommendations?
How do wheat respond to management intensification
using a yield component type of approach?
So we had this trial for a couple of years,
a couple of environments in Kansas,
where we're testing different management intensives,
and the interaction with wheat varieties.
So from a variety that is a more stable variety
to a variety that is variety that is more considered
kind of like a race horse variety.
And we're wanting to see, okay,
how is wheat responding to management intensification?
So what we have here,
the six management intensifications, right?
On the first one that we're calling farmer practice here,
we were putting enough nitrogen
for the long-term average of that county.
So the county was about 2.4 tons per hectare in yields
that was our yield goal.
That's how much nitrogen we put out in that treatment.
Then we wanted to know the effect of fertility.
So we added in-furrow fertility,
place a higher yield goal as well of 6.7.
So we were well above the potential.
So that's in theory, not limited by fertility,
next, we're keeping the high fertility and
improving the foliar fungicide, right?
So next we're just adding foliar fungicide
and by doing this in a stairway like this,
we can actually fail which management is increasing,
which yield component,
next we added an early foliar fungicide.
Oops, next we added here an early foliar fungicide
to see if there's any value
on that early control of diseases,
following up here we had what we call
a water-limited yield, we're also adding sulfur,
we're adding micronutrients as well.
In theory, we shouldn't have much limitation there.
And then finally, we're dropping down population
and here we're interested in
seeing the tillering potential of these varieties
in a very high input scenario,
can we afford to have less plants out there
and still maintain our yields.
And the inspiration for these treatment
and in specific here
is actually coming from, again, working with those growers.
And you can see these are side-by-side,
one mile long strips that they do
in terms of strip trials there,
whereas you would have half
of the population here as compared to here.
Now, can we really tell that it's planted that?
I mean, half of the population, right?
But a million seeds per acre compared to 2.2,
which is about our recommendation right there.
So, very high fertility scenario
is very high input availability scenarios.
Can we afford to decrease population like these
and still maintain yields?
There's a rationale behind these last treatment.
Across these study, right?
If we just look at
the different yield impacts that we had
from our different management strategies here,
from our farmer practice in the bottom,
going up to our higher fertility treatment,
we were gaining about half a ton per hectare,
going up with a fungicide
we were gaining about another 900 kilos per hectare there.
And from there on that, not really statistical
differences there between adding that early fungicide
or even adding all those other micronutrients
to our management.
However, we did see a small
reduction in yield from reducing the plant population,
which was not true in all environments,
but across all environments like this,
we could detect about half ton per hectare less yield.
Now, again, we were interestingly knowing here,
how is wheat responding to the yield components
that we have and how can we improve
our management recommendations if you have
a yield component framework in mind?
So here's the relationship with each yield of wheat yield
and above ground biomass at maturity
on the left panel, on the right banner,
we have the relationship of yield and harvest index.
And the message here is that
above ground biomass (indistinct)
was highly related to grain yields
so perhaps management that will improve
that above ground biomass and maturity
are management practices of interest or varieties,
varieties that produce more biomass as well
would be of interest here,
whereas harvest index.
I don't know that I can really explain this negative
relationship here,
I think is really just a trend there,
but across all sources of variation here,
not much relationship there.
Same thing if we look at Kernels per meter,
as compared to 1000 Kernel weight,
so a lot more relationship there
across all sources of variation
by number of grains that we have per area
as compared to our Kernel weight.
That was in terms of factors
that are important determining yields.
We're trying to build that information here.
And it was interesting this next one from our side as well,
because we're looking at heads per meter square
versus Kernels per head.
So essentially had size and we found a greater
explanatory power of head size
in overall yields as compared to two heads per meter
which was a little bit counter-intuitive here,
but some of these varieties,
they were varying considerably
in terms of head size.
So probably that's what is driving some of these
relationship here as well?
Very well, here we have a general picture
across all sources of variation, right?
Of how yield is related to yield components
in wheat, now from our different management practices,
what can we learn which management practice is affecting,
which yield component,
and what we're looking at here folks
is the trait responsiveness, right?
In this first slide
we're looking just to responsiveness through fertility.
So essentially the way it's calculated
is just that the trait value
on the high fertility over to farmer practice, right?
So if that trait responsiveness
is associated with yield responsiveness,
so in the Y-axis, we have yield
and on the X-axis we have these different yield components.
It means that modulation of one
of these use components was actually resulting
in changes in yield.
So whenever we added that extra fertility,
we were increasing the number of heads per plant,
which was associated with increased yields as well.
Likewise, heads per meter square,
Kernels per meter square, as well,
as well as biomass, right?
So these are the main yield components
that through fertility we're able to modify,
and they are associated with yield.
And interesting here, grain protein as well, right?
So through fertility, we're able
to improve yield and grain protein simultaneously,
which is a goal that is, I mean,
for many wheat growers are goal,
especially if they can get paid for protein, right?
How do you yield high yields and high protein
concentration as well?
This is the fertility.
Now, if we'll look at fungicide,
and now we're just looking at that fungicide treatment
on top of the high fertility.
So the only effect that we have here is fungicide.
We're also having some increases in biomass.
So fungicide is resulting in more biomass
at maturity that is associated with yield
more heads per meter square and more Kernel weight.
So it was interesting because
when we're changing Kernel weight
through fungicide that was associated
with changes in yield
but across the whole population
of trials that we have here,
Kernel weight was not a trait
that was too associated with you.
I'm focusing only on these two here
because they were the most important,
but when we think of fungicides as well,
very important is that we look at light intersection,
how much radiation we're actually intercepting
and what we're looking at here.
Just comparing that fertility treatment
with the fungicide treatment
and here we have this slope,
how fast are we losing canopy cover after anthesis.
3% means that we're losing 3% per day
of green canopy cover after anthesis, right?
So the more canopy, so the faster we're losing
green canopy over during grain filling
the last yield we had in the end that was associated
with last radiation receptors as well.
So again, there's an effect there
of radiation reception and its effect on yield
from the fungicide.
We're also interested
in understanding how the plant population,
why we're losing some yield in plant population,
seemed like we had last canopy cover
at anthesis on that with the reduced plant population.
Even though we had a very high input system,
just reducing the population was reducing
the amount of green canopy cover and anthesis
and then reducing the amount of radiation
intercepted after and anthesis
and that was associated with yield.
So there's some indication there.
They probably just don't have enough
canopy on those low populations
to sustain the yield levels that we had
in the high population.
And out of interest here, especially
we've a couple of breeders in the room here, right?
We're interested in seeing
how much can these varieties tiller.
And if that depends on the environment
that index for tillering potential here, right?
So while we have there, each color
is a different variety
and here environmental index low
means that you produce very few heads per plant.
So very few productive tillers per plant,
and here very high number of tillers per plant.
We get our race, horse variety,
it was only producing 2.7 tillers per plant,
and you can see that
it's not really responsible
when you're bringing the population down,
it's not really responding
in terms of producing more tillers.
We've got our work horse variety.
The one that doesn't respond
as much to the fertility or to inputs,
the other way around, it was the highest tillering variety.
And as with the reduced population
it produced even more tillers.
We did the same analysis here
just looking at management.
And just for us brief comparison here,
our farmer practice across the board
about two tillers per plant.
And we've our low population here on average,
about 4.4 tillers per plant,
and very responsive to environmental potential as well.
So you can really modulate
the number of tillers per plant there
through population, through fertility as well.
Just a few take homes here from this short study
that we've done, but essentially,
probably don't need to go full intensive,
you can manage most of those (indistinct) regulators
of yield, biomass, trumping, harvest index,
and Kernel number, trumping Kernel weight
in terms of importance for yield determination.
And then you have fertility impacting the Kernel number
and also impacting biomass,
whereas fungicide impacting biomass,
but impacting Kernel weight.
So again, we can reach those high yield levels,
but through different yield components here.
So this was a project one on management intensification.
Trying to look what yield components
we're managing at a time here.
But if you remember from that on-farm survey, right?
Nitrogen was something that came up
very frequently in terms of important
and associated with yield
and sulfur came up as well.
So this is a field trial that, well,
several field trials that we were doing
in that interaction of variety with nitrogen rate
or sulfur management with nitrogen as well.
So a lot of these lights are green
that you see up there have sulfur deficiency here.
Here we're more looking at the different levels
of nitrogen deficiency here.
I'm gonna go ahead and summarize some of the nitrogen
and sulfur data that we have had,
nitrogen is too complex we're not going to,
we could spend a full seminar
just on the nitrogen piece, but very briefly here,
we reviewed about 130 experiments
that were conducted looking at nitrogen rates in wheat.
And here, we're looking at the yield difference
between applying 45 kilos
of nitrogen versus not applying, right?
And what we see here is that these difference there was on
average here about half ton per hectare,
it depended on yield environment, right?
We have different use environments here
and I apologize, 'cause I don't see the axis label here,
but (indistinct) yield environment in tons per hectare,
the higher yield environment that we had,
the greatest the response of the crop
to those 45 kilos of nitrogen per hectare.
On the bottom we're looking at the same graph,
but at 90 kilos per hectare
just notice the difference in scale there, right?
So much greater yield gains,
but again, yield gains associated with
higher yielding environments.
Another thing that we found from this research here
is some interaction with water nutrients,
here we had a (indistinct) and response curve
across I mean, hundreds of environments there,
but without applying any phosphorous versus applying
phosphorous to the crop as well.
So some interaction there
a little bit higher yield levels
when we were having that core application of nutrients.
Now the penalty here was actually
coming from grain protein concentration, right?
We have that same nitrogen rate
with the two phosphorous management levels,
just we're analyzing grain protein concentration.
We're able to, the crop is able
to produce higher yields from there.
And in terms of,
we've got a lot of questions in terms
of how do we manage nitrogen for yield
or nitrogen for protein as well.
And if we would summarize that in terms of
some of the research that has been done in Kansas so far,
I don't have all the points here,
but these lines, they're linear plot
or regressions over several experiments that we've done,
essentially if we have total nitrogen
in the season and this is
including the amount of nitrogen available at sowing,
at time of crop sowing.
Plus whatever was applied as fertility
in our own treatments,
yield in red, protein in blue,
and we're looking at relative values, right?
Being 100% over there
is the highest yielding treatment
or the highest protein treatment in that experiment.
And here we're summarizing about that experiments.
Essentially what we have here is that
there is a deficient range right below
which both in protein increase
with additional of more nitrogen, right?
That's where adding more nitrogen
will yield in protein increase,
yield increases at a much steeper rate than protein does.
Now, we reach a sufficiency level for yields, right?
Or at least a point for that environment
where putting more nitrogen,
doesn't really increase your levels anymore.
Our protein continues going up, right?
So there's a point there where yield is maximized
and as a diagnostic we can look back
at our protein content.
That's about 11 and a half.
So, if you have less than 11 and a half protein content
in a high yield environment, right?
In a good environment,
that means your yield is likely limited by lack of nitrogen.
So you are missing yield because of nitrogen there.
So, add a protein of about 11 and a half
are reaching this sufficient point here,
but then protein kind of continues increasing, right?
And then you have just a point where is excessive.
And if we look across all of these data here, right?
In our recommendations today are 2.4 pounds of nitrogen
for every bushel per acre
of yield goal that we have.
For yield we're reaching a very close number there,
slightly greater for maximizing protein in these
higher yielding environments here.
By higher yield environments, I mean 70 bushels average,
more or less of these experiments here.
So this kind of summarizes that relationship
of yield and protein in terms of rate.
There's quite a bit
that goes on in terms of timing as well.
And I just have the single slide here on timing
which, what we're looking at here
is the nitrogen uptake and nitrogen partitioning
of the wheat crop as effected by nitrogen timing,
same variety, same nitrogen rate,
the only difference here is that on the left hand,
100% of the nitrogen was applied in the fall.
On the right hand side here,
we were splitting about 40% in the fall,
50% early in the spring,
and about 10% is late out there at anthesis.
And look at the magnitude in difference in uptake here,
the 100% applied in the fall, the crop
is up taking maybe 80 pounds of nitrogen total
at the peak, right?
Even less than that.
Whereas just by managing our nitrogen timing
and we're putting more closer to where the crop
actually uses it in these experiment here
we're actually,
the crops are taking to 120 units.
Now I need you to say that these were experiments
planted soybeans, very little fall development.
So, probably a lot of losses from these fall applied here.
These will be probably different
if you're talking about the crop that is planted early,
especially a crop that is planted for grazing
or dual purpose, right?
But in these conditions that seem
to be predominant in Central Kansas now,
wheat planted after soybeans,
again, the magnitude that we have
in improving our nitrogen use efficiency
just through nitrogen timing it's quite amazing to me here.
We're also doing some, as I mentioned,
some variety directions of nitrogen here, right?
And while we're looking at here is
two different variety.
Well, the same variety of different nitrogen rates,
short variety, very high yielding variety,
kind of lower on protein versus a taller variety,
much better protein content here in this example,
and these varieties they seem to differ quite a bit
in terms of yield potential
especially in high yielding environments,
which is what we're looking at this figure here, right?
As we increase our environmental yield potential,
it seems like the difference
between these varieties increase,
and these environments they are combinations
of different nitrogen rates and different actual locations.
Now, what is interesting here
is look at these data from all different perspectives,
looking at, let's see,
where these varieties plateau
in terms of amount of nitrogen available
and do they different plateau in terms of yield
and plateau in terms of nitrogen.
So this is a compilation of some of the low yielding
environments that we had, right?
And we see for those varieties,
they don't differ a whole lot in yield
or in terms of nitrogen,
where they are reaching that yield plateau,
look at higher yielding environments here.
The more they will tell us that there
is a larger difference here in the amount
of nitrogen where they are plateaued.
But actually if you look,
I mean, those two points are actually
probably plateaued already, right?
So this a function of the model here.
So what I was interested here is to know, okay,
across all of these varieties that we're interested,
are they requiring more nitrogen
to reach their plateau, right?
And does it depend on the level where that plateau is?
So this is just a couple
of examples here where we're looking at is,
where that variety plateau in terms of yield
and how much nitrogen you took
to get there in high yielding environments
and low yielding environments.
And the message here if you look
at these two things together, again,
the breakpoint of nitrogen here where increases
in nitrogen were not increasing yield anymore,
or the yield plateau, they were completely unrelated,
either in low yielding environments
or high yielding environments, meaning that,
the different varieties were reaching their yield
plateaus at different nitrogen levels
and at different levels,
but those two things were not related.
So, some things here, right?
We do have some varieties with higher nitrogen
use efficiency, but based on these
very preliminary data here, it seems like
that's probably a protein, it may
be a protein penalty, right?
It's just like higher nitrogen use efficiency
because perhaps some of these varieties
might be producing less protein
because they were not related here
between the break point and what plateau we have.
So, nitrogen doesn't really tell the whole story,
more and more we have situations like this across Kansas.
I would think that maybe in Nebraska,
we might see some fields
that look like these in early spring as well.
And these are symptoms of sulfur deficiency.
So very common to see this type
of a sulfur deficiency here across the state.
And this is around spring green up
or before jointing as we move towards closer to anthesis,
you can actually see that
they can get pretty deficient, right?
I mean, it's very severely deficient
in sulfur in the back there.
So try to understand a little bit more of the
dynamics of the crop is affected by nitrogen
and sulfur in that interaction for three years now,
we've been running an experiment
just with interaction of varieties,
different sulfur rates and different nitrogen rates.
We have a total about eight environments
in several, across three years in Kansas.
And these photos here,
they're showing you just the effect
of 20 units of sulfur per acre,
only difference that we have between left and right,
same variety, same nitrogen rate,
20 units of sulfur per acre here, nothing over there.
You can see the difference in biomass,
the difference in crop development here,
and these translates into maturity, right?
Or as we're approaching, we're doing,
the green fielding period, you can see just
fewer heads out there and much less biomass as well, right?
Just from that sulfur deficiency.
Very well, what can we learn in terms of yield so far?
And I'm going to divide these
into two different categories, the first one,
low organic matter, sandier soils
and in these conditions, very.
I mean, all times that we ran the trial
under these conditions,
we were actually having an interaction
of nitrogen and sulfur rate on yield.
So we're looking at grain yield over there.
Here we have our tree nitrogen rates
that we were exploring and the different line colors
they are the different sulfur rates.
So let's focus on the black line first
'cause that's our zero sulfur, right?
Regardless if you're adding 50, 100
or 150 units of nitrogen flat, no response,
because the crop is deficient for sulfur, right?
So it doesn't matter how much nitrogen put out there
simply the response in yield is not there.
Now, if we look at the red line
which is just 10 pounds of sulfur per acre,
first thing you look at the size of the gap, right?
We're talking about yield gaps.
And so I mean, in these conditions,
we're able to put as much as about
20 bushels per acre just from that sulfur application.
Do I expect these in every field?
I don't, but in very severely deficient conditions,
this is the level of,
this is the gap we're looking due to that sulfur.
Now, not only that, the sulfur also allowed
the crop to respond to nitrogen.
Right, now as we're improving our nitrogen
or increasing our nitrogen rate
we're also seeing a response in crop yield as well.
So two things, first we're kind of narrowing,
closing, or narrowing that we have to do to sulfur
and then we're also allowing
the crop to be responsive to nitrogen.
Now, if you look at these very same graph
in a higher organic matter soils,
perhaps silt loam soils, and this case
was a silty clay loam,
then simply we didn't see as much response to sulfur.
So it's very soil specific, right?
It depends on the amount of organic matter that we have.
We tend to see more response to sulfur,
low organic matter, sandier soils.
Now let's try to understand
this from a plant perspective, right?
Here we're looking at the yield,
but what is happening within the plant?
We can look at these using boundary functional analysis.
What we're looking at here
is the nitrogen uptake at maturity,
how much nitrogen is taken up by the plant
and the grain yield.
And the blue line is a boundary functions,
is just over the most efficient points, right?
So that's why it doesn't feed the data
really well is because we're just
doing over the most efficient points.
What we see there is that about 120 units
of nitrogen uptake at maturity
was the minimum necessary to maximize yields
which was about 5.7 tons per hectare
in these environments that we've done,
and these across all those eight environments
in three years here.
And if we look at the yield gap
as function off nitrogen stress, right?
That yield gap increases as function
of S that nitrogen stress increases.
Same thing from a sulfur perspective,
but then we're maximizing,
I mean, the minimal amount of sulfur uptake
to reach their maximum yield was about seven kilos
of sulfur per hectare, reaching
that yield level about 5.7 tons per hectare.
And again, if we look at the size
of the size of the yield gap
as function of this sulfur deficiency here
also that yield gap increases
as our sulfur deficiency is sulfur and stress index,
which is sulfur deficiency increases here.
We get crop yield
and crop limitation based on sulfur
and nitrogen uptake here.
Another thing that's interesting
for us to look at is the use efficiency of these nutrients.
So how we use, for example,
sulfur deficiency impacting
the use efficiency of our nitrogen,
and that's what we're looking at in this figure here,
the three different colors
are simply three different nitrogen rates.
And as we expect higher nitrogen rates here,
you have lower nitrogen use efficiency.
So the results were pre expected,
but the more sulfur stress index
that these crops had,
the lower deficiency to use nitrogen as well.
And if we break down this efficiency
into uptake efficiency or utilization efficiency,
it seems like the uptake efficiency
is actually the one that is being affected the most
based on the slopes of those curves.
So the crop is able to,
is up taking less efficiently as
compared to the use efficiency,
very similar story to sulfur here,
increasing nitrogen stress, reducing sulfur use efficiency,
mostly driven by sulfur uptake efficiency,
and not necessarily by sulfur utilization efficiency.
So these wraps up what I had in terms
of the nutrients and management
and some of the crop intensity management as well.
Maybe the last slide here is that ratio
of about 16 to one
in terms of nitrogen to sulfur,
seems to be about the optimum to minimize
both deficiencies there, right?
So if you look at the crop or the stover
the amount of nitrogen to sulfur
that we have there 16 to one seems to
be a sweet spot there in terms
of minimizing either deficiency.
In terms of conclusions here, right?
We have a few of the reference
that I use for this presentation here,
we didn't touch much on the first one
because that was the fungicide one,
but again, large gap existing
in these commercial wheat fields in Kansas about 44%.
So the potential is there, but how do we get there, right?
And we're trying to figure that out
through these field experimentation
looking at not only the nitrogen management,
but sulfur management as well and fungicide management,
that seem to be some of the most important factors
impacting yield from our own farm survey.
In terms of management recommendation
if we were thinking of physiologically
managing the crop, right?
That fertility,
able to modulate the Kernels per meter square
and biomass, that's how we're reaching the yields.
Whereas fungicide is more
a management of kernel, weight and biomass as well.
So I think that the wraps up,
I'll be happy to take any questions
that you guys might have or any questions
that might come up online as well.
-: Yeah, thank you very much, Romulo,
excellent presentation and a very nice example
of all how physiological farmers
can help also guide the practical applications
in (indistinct),
so thank you very much for your presentation.
So any question, okay, Steve.
-: Have you ever overlapped your weather
maps with your yield maps?
Or did you do that already and I missed it.
I'm just curious to see, like,
you have ecological zones,
which historically would show up
in our (indistinct) grass distributions also.
So in Nebraska we have three ecological zones,
are the tall grass, the intermediate and the short grass.
And I wonder if the same thing held up with Kansas
as well as can you explain
the yields by those that historic weather data cleanly,
or is that weather plus soils?
-: Yeah, that's a really good question
in our own subdivision of the data there,
we didn't consider soils necessarily,
well as a first step we did,
but there's so much variability
in soils that we end up with too many regions
and too few observational per region.
So we ended up just using long-term weather
to make that subdivision.
So maybe, there's some confounding factors
of the soil, different soils being evaluated there,
but I never tried to overlap it
with these other maps that you are mentioning
on the tall grass,
immediate or short grass there.
But we've tried to do, especially on that work
that we had the 100,000 observations of variety trials.
We tried to compare those zones
with some of the zones developed based
on cultivar performance, right?
And I think they are more widely used perhaps on breeding.
And while we found those that those
cultivar performance once, they were
relatively larger than the ones
that we developed based on long-term weather.
And we were missing a few of the important management
practices that are region specific.
So for example, it was large enough
that maybe we had the row spacing
of 12 inches in the west,
10 inches in the middle
and seven and a half inches.
So, they were too large for us
to get that management information there.
So, but we did that exercise
as we were going through, how do we subdivide our data?
And then we compare it to that approach
of cultivar performance.
The main difference there, again, was
the regions were too broad or (indistinct)
practices adopted in each region.
Great question.
-: Any other question, there is one...
Woman: So this is from Tony Fisher in Kabbalah,
a very clear and comprehensive study
of wheat in Kansas at last, congratulations.
I noticed there were some negative responses to nitrogen,
how much relates to field history,
nitrogen timing and rainfall,
all things the farmer can include
in the decision-making except for water supply,
but maybe you now have seasonal rainfall
forecasts of some reliability.
-: Yeah, that's a great question.
And thanks Tony for participating in it.
Thanks Patricio for sending out the invitation there.
Yeah, that's really good to hear from you there Tony,
and he just had a very nice paper on field crops
come out these week.
So we all know minimal temperatures on Mexico there.
So we did have some negative response
to nitrogen in that 130 site year analysis
that we were doing,
they were related to a very low yielding environments.
So perhaps, maybe too much early growth,
too much vegetative growth
early on because of that nitrogen again,
in that study all the nitrogen was applied pre-plant
in that study that I mentioned, and the one that we have,
and I'll go back there maybe,
but where we actually had 130 environments,
all that nitrogen was applied pre-plant
and perhaps there was too much growth.
So we did have some negative
yield responses over here, right?
In kind of like lower yielding environments
for both of the nitrogen rates there.
So yeah, my initial hypothesis here Tony
will be that probably too much early growth
from that fall application of nitrogen
who will have resulted in maybe unproductive water
use early on the season.
-: Go, so (indistinct).
-: Yes, because he is in Australia, yes.
Woman: So I wanted to follow up with Ken Kasman.
He agrees with Tony, so nice to see a solid,
a Grammy presentation on nutrient management
on wheat in Kansas.
Nathan Mueller, great presentation,
shared date with (indistinct) yes,
but 7% of wheat fields N equals 30 in Southeast, Nebraska
were low in sulfur in 2021
based on flag leaf survey at Feakes 10,
it would be higher, but some farmers had applied sulfur,
question, is the area of wheat was solid sulfur
deficiency expanding, or is it a well contained
small area that is not increasing?
-: Yeah, so first thanks Ken for the comment there.
And Nathan for the question,
what I'm seeing, so from our farmer data
that showed up more in the west,
which was kind of surprising to me.
I was expecting more to sulfur association
with yield to happen in central Kansas
where we have more leaching,
but a lot of the fields that we see year after year,
at least that I see are more
in the central part of the state there.
I don't know Nathan.
I honestly I don't know a good answer for that question.
I think that farmers are
not taking care of that on,
because now we have much more crops in the rotation, right?
It's not only wheat.
We have soybeans that are also removing sulfur.
We have corn also removing sulfur
or many other crops,
the main, okay, so (indistinct) come back will be
the main reason for the sulfur deficiency
to be increasing is that we have less sulfur
coming down with the atmosphere, right?
We actually have that data
for Kansas quantified in their natural conditions.
We went down considerably in 30 years
in amount of sulfur coming down
because of the Clean Air Act.
And with that,
I think we see more widespread deficiencies.
Now, the hard part to answer your question there
is that I think the growers are more and more aware.
So we're putting out these information
more and it is a relatively easy fix, right?
As I was showing there,
I mean 20 pounds of sulfur per acre
or even 10 pounds of sulfur per acre
applied together with the nitrogen
in the case of wheat at green-up,
just will take care of most of the problems.
And so being such an easy fix,
maybe we will see less expansion in the future
if we can do our work on extension.
Well, down there.
-: I have a question for you Romulo,
when we did the analysis of yield gap the US
we found that in the case of soybean and corn,
the yield gap was a small 20 to 40%,
even less in the case of (indistinct) corn in Nebraska.
But in the case of wheat
we were both surprised
when we found out that the yield gap was up to 50%.
So can you talk a little bit about
why the yield gaps are so large
for a wheat compared with corn and soybeans?
-: Yeah, that's a really good question.
I think that farmers are usually seen wheat,
perhaps they're well,
first they're not managing as intensively as they are
their corn crop,
and that wheat is also grown in more,
well in riskier environments.
So more harsh environments
where maybe the response to that nutrient
might not be there year after year.
And so maybe slightly more challenging
to manage the nutrient in wheat
because it's grown in those harsher environments,
recent years, I mean, today the wheat price is good,
but for the last five years or so,
they have been very low as well.
And so I think the lack of investment
on the farmers plays a very important role there,
we see, I mean, on the fungicide data,
we are seeing some of this (indistinct)
varieties on average, yield difference
of about 17% by just spraying fungicide
versus not spraying fungicide,
we look back in 12 years of bird
fungicide versus no fungicide work
and (indistinct) varieties up to,
I mean, on average, 17% up to 80, 90% yield difference
because of the fungicide.
So I think that is a matter of starting
to treat wheat more like we treat corn
and we already have some of these growers
who are doing these as I showed
in a few of the photos there,
and they're doing their own research
on seeding rates and things like these
under their conditions.
So, the more we move that way,
wheat prices being high now,
maybe we can see some moving that way.
Although fertilizer prices are really high as well.
So I don't know what's going to
be the final outcome if we improve yields
because wheat yield is high and guys will invest more,
or if the fertilizer prices are really
going to bring the investments down again, so.
But I think (indistinct) the crop and managing it.
Woman: So this one is from Andrew Hopkins,
the nitrogen response data on the screen
now show that about half of the nitrogen applications
would have been profitable,
that doesn't help risk adverse farmers.
You have to think tactical nitrogen.
So I guess that was more of a comment.
-: Yeah, completely agree and again,
these is just a compilation
of long-term data that we were
going back and see, okay, well,
what's the average response that we have
and how it depends on environment,
but for sure, I mean, moving forward
I think that future,
I mean, work like what Lily's doing
in terms of procedural nitrogen management
and addressing the current weather conditions
and yield potential it's the way to go
in terms of nitrogen management, yeah.
Woman: And I apologize, that was from Tony,
he had another comment.
This is from Andrew.
My more equal distance planting, narrow rows,
lower seeding rates equal more tillering
and thus more heads per acre and more yield.
-: The answer there for the first part is, yes, right?
So if we are reducing your population
and you're having it more equidistant, right?
you're having the plants better distributed
in that row,
they will have more resources and increased tillers.
And so in the end increased heads per plant.
Now, whether that turns out
to increase heads per meter or not,
I think it's very environmental dependent.
So the effects on yield as well,
what we see usually in these very low population trials
that we do, the crop rely so much on the tillers
and if you think of the tillers
they are going to develop later then that main,
well, the secondary tertiary tillers will be later.
So we have a slight delay in maturity,
but we also tend to see less lodging.
And I think that's where some
of the growers were coming after
with these hypothesis that they were going
with very low populations, like, okay, well,
I have so much fertility out there,
what can we do to reduce the chances of lodging beyond
selecting a variety of a good (indistinct) right?
And that's where population is kind of coming in,
but it changes the phonology a little bit too,
is gonna delay overall,
average flowering date there
and so depending on the growing season weather
or so grain filling whether that can be beneficial or not.
So it's gonna depend on the year.
For these to work, for these low populations to work,
family planting is essential, right?
Because some of these trials,
whenever we're doing a late planting,
that the crop doesn't have enough
time to tiller in the fall,
then we have the largest yield losses are coming from there.
And if you're planting the optimal
or even though is lightly before
that optimal, right?
I mean that optimal window,
but in the early side of it,
good moisture and fertility are essential
to ensure that we have enough tillers out there
as well as temperature in the fall.
Woman: I do have one last question from Olam Muhadji,
sulfur application showed positive
interaction with nitrogen efficiency in study.
Did you find any significant effect
of sulfur application on wheat protein contents?
-: Yeah, that's a really good
and that's a really good question.
And so all of that sulfur study that I showed here,
we are processing all that data
for the full million baking characteristics of the crop.
Well, I haven't looked at that data yet,
but it's being processed.
I would expect so,
I would expect that we will have,
well, first I don't think it's gonna
increase protein because of the
size of the yield benefit that we're gonna have.
So just based on dilution effect,
maybe the protein amount might even go down.
But I think that the quality of that protein
in terms of functionality
is probably going to improve because of sulfur,
in sulfur deficient environments.
So I think is a tricky question because
the amount of protein might actually go down,
but the functionality might improve.
-: We are running a bit late here,
but I'm gonna still gonna ask you the last question,
because I'm the chair and I have the privilege to
ask you the last question.
So, Romulo has an 80% extension appointment,
so you spend a lot of time with farmers.
So I wanted to know what was
the reaction of farmers in general
when you show them that they have such a large yield gap
which means a larger opportunity to increase yield,
and that in most of the cases,
the measures that you need to take to close
that gap in more cost effective agronomy
that already exists such as fungicide
or better for the likes of an input,
or simply
better management of the fertilizer
in terms of placement and timing.
So tell us a little bit about that reaction
and then how,
what do they do about that?
I mean, are they proactive?
And then they try to close that gap
or they kind of keep blaming the risk
and the climate and they just say,
well, all that but I prefer to hear.
-: Yeah, another really good one there.
So it's interesting
from the extension appointment there,
pre-COVID right?
Things changed it quite a bit,
but before COVID we were doing about 100
talks a year where we were
with growers on the field showing us
demonstrations of varieties
or inside in crop schools, right.
So there's a lot of chances
for interaction with growers there.
So first they're very interested
in the new and upcoming varieties, right?
It seems to be the main interest that they have,
but then we show, okay, well,
but the potential is there, right?
So we need to manage and close that gap.
In terms of the grower response to that type of information.
I think that we can almost characterize growers
into like a top 5% of the guys
that are gonna already be doing that, right?
And then you have a good 20%, maybe they're
watching and they get this information
and they're going to try in a part of their field
and see how it goes
and once it works,
then they will maybe go ahead in
adopting in their farm.
The majority of them they're gonna
take some time to change what they're doing
even though we might be showing here.
I think that the mentality of managing wheat
more as a almost a secondary crop
or in a very high risky region,
the majority of them
they will take some time to make that move.
And some of them are probably
just gonna continue doing what they're doing.
So I guess to answer your question there,
I work with many growers
who I'm learning a lot from them, right?
And a good number of them will adopt this practices.
I can give an example here.
I remember very well
and I'm just gonna say it
because it aligns really well with your question,
but right after in in a field day
one of the growers came for me and said,
"your data, it doesn't represent what we do,
"your yield are too high and this type of thing."
"So, well, what are you doing different
"from our plots or from our research?"
And he said, "you're putting much more nitrogen."
So i turned him "so well, why don't you do that?"
Do that, try and try to see,
I mean, in a season where you think the potential is there,
let's try and increase the rates a little bit.
And about three years later, I met that grower again.
And he said, yep, I mean, now
our data are aligned really well
because he started managing
his crop a little bit closer and the potential is there.
So when we first met, he was saying,
well, he's a, dual-purpose grower
his average were about 40 bushels
or so per acre after grazing.
So not too bad,
but more recently after a little bit
more close management of the nitrogen
and variety selection and other tools that he had,
he's probably on the 60 range in recent years.
So if they give it a try, many times
they are able to move to the next step.
-: Right, right.
Great message for funding agencies
and community boards to try to make sure
that they are more Romulus out there who
can help with growers to at least narrow
that existing large yield gap.
But thank you very much Romulo for your presentation
and let's thank Romulo with a round of applause.
(audience applauds)