Globally,
agricultural
systems
face
the
complex
challenges
of
producing
enough
food,
fiber,
and
fuel
to
sustain
a
growing
population
while
mitigating
negative
environmental
consequences
intensive
management.
To
that
end,
optimizing
nitrogen
(N)
fertilizer
management
has
become
major
focus,
as
it
is
commonly
most
limiting
nutrient
maximizing
cereal
crop
growth,
over-application
increases
potential
for
reactive
N
leach
into
groundwater
be
emitted
potent
greenhouse
gas.
The
goals
this
dissertation
were
1)
quantify
interannual
changes
economic
optimum
rate
enhancing
our
understanding
tradeoff
between
production
degradation;
2)
improve
capacity
process-based
model
simulate
yield
response
rate;
3)
rank
sensitivity
individual
environmental,
management,
genetic
factors.
meet
goals,
we
used
modeling
measured
grain
yields
from
14
long-term
maize
experiments
across
Iowa
Illinois,
USA,
thereby
allowing
us
temporal
trends
rates
provide
systems-level
analysis
using
modeling.
Analysis
these
data
revealed
have
been
increasing
over
time
by
2.06
2.80
kg
ha-1
yr-1
continuous
following
soybean
rotation
reducing
below
mitigate
effects
application
will
more
severe
on
than
reductions
in
losses.
Moreover,
solution
models
reproduce
penalty
identify
bias
associated
with
fitting
simulated
curves
leading
lower
predict
relative
(RRMSE
=
33
19%).
Further
complicating
prediction
rate,
determined
genetics,
environment
similar
contributions
annual
rate.
This
serves
benchmark
guide
future
research
priorities
toward
inform
recommendations,
research,
policy
decisions.
Field Crops Research,
Journal Year:
2023,
Volume and Issue:
299, P. 108987 - 108987
Published: June 3, 2023
Quantification
of
nutrient
concentrations
in
rice
grain
is
essential
for
evaluating
uptake,
use
efficiency,
and
balance
to
develop
fertilizer
recommendation
guidelines.
Accurate
estimation
without
relying
on
plant
laboratory
analysis
needed
sub-Saharan
Africa
(SSA),
where
farmers
do
not
generally
have
access
laboratories.The
objectives
are
1)
examine
if
the
macro-
(N,
P,
K,
Ca,
Mg,
S)
micronutrients
(Fe,
Mn,
B,
Cu)
can
be
estimated
using
agro-ecological
zones
(AEZ),
production
systems,
soil
properties,
mineral
application
K)
rates
as
predictor
variables,
2)
identify
uptakes
by
best-fitted
models
with
above
variables
provide
improved
prediction
actual
(predicted
x
yield)
compared
average-based
(average
SSA
yield).Cross-sectional
data
from
998
farmers'
fields
across
20
countries
4
AEZs
(arid/semi-arid,
humid,
sub-humid,
highlands)
3
different
systems:
irrigated
lowland,
rainfed
upland
were
used
test
hypotheses
concentration
being
estimable
a
set
among
above-cited
factors
linear
mixed-effects
regression
models.All
10
nutrients
reasonably
predicted
[Nakagawa's
R2
ranging
0.27
(Ca)
0.79
(B),
modeling
efficiency
0.178
0.584
(B)].
However,
only
K
B
was
satisfactory
superior
0.5.
The
country
variable
contributed
more
variation
these
than
AEZ
systems
our
best
predictive
models.
There
greater
positive
relationships
(up
0.18
difference
correlation
coefficient
R)
between
model
estimation-based
those
uptakes.
Nevertheless,
uptake
had
significant
improvement
all
investigated.Our
findings
suggest
that
exception
associated
high
EF
an
over
estimates
macronutrient
micronutrient
obtained
simply
average
each
at
regional
scale
SSA.Further
investigation
other
such
timing
applications,
variety,
occurrence
drought
periods,
atmospheric
CO2
warranted
accuracy
concentrations.
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 13, 2024
Abstract
Near-term
commitments
to
net-zero
greenhouse
gas
emissions
(GHG)
require
the
agriculture
sector
reduce
and
sequester
CO2.
Harvesting
of
crop
residues
can
contribute
these
goals;
however,
uncertainties
about
effects
on
grain
yield,
non-CO2
GHGs,
soil
health
have
led
questions
potential
benefits
residue
harvest.
Here,
we
show
that
harvest
are
underestimated
growing
because
they
do
not
account
for
increasing
rates
production
attendant
agronomic
environmental
partial
In
North
America,
maize
is
by
>
100
kg
ha-1y-1.
Partial
increase
yield
6%
N2O
30%.
These
greatest
when
paired
with
conservation
tillage
grow
production.
A
systems
approach
integrates
practices
mitigate
GHG
promote
farmer
adoption.
Plants,
Journal Year:
2023,
Volume and Issue:
12(11), P. 2135 - 2135
Published: May 28, 2023
Nitrogen
is
crucial
for
plant
growth
and
development,
improving
nitrogen
use
efficiency
(NUE)
a
viable
strategy
reducing
dependence
on
inputs
promoting
sustainability.
While
the
benefits
of
heterosis
in
corn
are
well
known,
physiological
mechanisms
underlying
this
phenomenon
popcorn
less
understood.
We
aimed
to
investigate
effects
traits
four
lines
their
hybrids
under
two
contrasting
conditions.
evaluated
morpho-agronomic
such
as
leaf
pigments,
maximum
photochemical
PSII,
gas
exchange.
Components
associated
with
NUE
were
also
evaluated.
N
deprivation
caused
reductions
up
65%
terms
architecture,
37%
42%
photosynthesis-related
traits.
Heterosis
had
significant
traits,
NUE,
foliar
particularly
low
soil
N-utilization
was
found
be
mechanism
favoring
superior
hybrid
performance
NUE.
Non-additive
genetic
predominant
controlling
studied
indicating
that
exploring
most
effective
obtaining
promote
The
findings
relevant
beneficial
agro
farmers
seeking
sustainable
agricultural
practices
improved
crop
productivity
through
optimization
utilization.
Nutrient Cycling in Agroecosystems,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 20, 2024
Abstract
Estimates
of
cropland
nutrient
budgets
at
national
to
global
scale
generally
rely
on
regional
or
mean
coefficients
for
quantifying
nutrients
removed
in
crop
yield
and
by-products.
Use
such
values
masks
the
variability
these
coefficients.
Using
maize
wheat
as
examples,
we
assessed
variation
removal
coefficients,
namely
harvest
index
(HI),
nitrogen
(N),
phosphorus
(P)
potassium
(K)
concentrations
products
(Grain
N,
Grain
P
K
respectively)
residues
(Residue
Residue
P,
respectively).
Variation
was
by
three
categories
(Tiers)
estimation.
Statistical
(mixed-effects)
machine
learning
(random
forest
regression)
models
(Tier
3)
were
used
predict
using
available
predictor
variables
a
level.
Mean
prediction
accuracies
(R
2
)
mixed-effects
random
0.32
0.45
when
based
sub-selection
mainly
replicated
field
experiment
data.
When
predictions
applied
on-farm
data
only,
lower
(mean
R
0.08
0.36
in,
dearth
contributed
poor
accuracies.
Until
limitations
are
overcome,
it
is
recommended
use
Tier
(regional)
coefficient
estimates
country
balance
efficiency
estimates.
Where
not
available,
then
average
1)
can
be
used.
Authorea (Authorea),
Journal Year:
2023,
Volume and Issue:
unknown
Published: July 9, 2023
Estimates
of
cropland
nutrient
budgets
and
use
efficiencies
at
national
to
global
scales
generally
rely
on
average
concentrations
for
quantifying
nutrients
removed
in
crop
yield
by-products.
Given
the
relevance
removal
budgets,
it
is
important
that
more
locally
relevant
coefficients
or
models
are
developed.
However,
many
countries
do
not
have
sufficient
data
from
farm
surveys
field
experiments.
Using
maize
as
an
example,
we
assessed
how
much
a
country’s
estimated
affected
when
using
either
(Tier
1),
regional
2)
national/sub-national
3)
estimates
harvest
index
concentration
products
residues.
nitrogen,
phosphorus
potassium
varied
substantially
(up
52%),
depending
which
Tier
approach
was
used.
This
had
substantial
influence
efficiencies.
Our
study
shows
large
uncertainty
associated
with
current
offtake
estimates.
If
available,
3
offers
methodology
overcome
such
limitations
through
application
models,
trained
localized
but
widely
available
countries.
We
recommend
2
approaches
once
they
been
evaluated
against
real
on-farm
data.
The
presented
can
be
applied
other
crops
improve
Abstract.
Nutrient
budgets
help
to
identify
excess
or
insufficient
use
of
fertilizers
and
other
nutrient
sources
in
agriculture.
They
allow
calculation
indicators
such
as
the
balance
(surplus
deficit)
efficiency
that
monitoring
agricultural
productivity
sustainability
across
world.
We
present
a
global
database
country-level
budget
estimates
for
nitrogen
(N),
phosphorus
(P)
potassium
(K)
cropland.
The
database,
disseminated
FAOSTAT,
is
meant
provide
reference,
synthesizing
continuously
updating
state-of-the-art
on
this
topic.
covers
205
countries
territories,
well
regional
aggregates,
period
1961
2020.
Results
highlight
wide
range
efficiencies
geographic
regions,
nutrients,
time.
For
year
2020,
data
show
average
N
surpluses
from
about
10
kg
ha-1
year-1
Africa
more
than
90
Asia.
Furthermore,
they
P
K
deficits
2020
Americas.
This
study
introduces
improvements
over
previous
work
relation
key
coefficients
affecting
estimates,
especially
removal
crop
products,
manure
content,
atmospheric
deposition
biological
fixation
rates.
conclude
by
discussing
future
research
directions,
highlighting
need
align
statistical
definitions
groups,
further
refine
plant
livestock
expand
all
land,
including
flows
meadows
pastures.
Abstract.
Nutrient
budgets
help
to
identify
excess
or
insufficient
use
of
fertilizers
and
other
nutrient
sources
in
agriculture.
They
allow
calculation
indicators
such
as
the
balance
(surplus
deficit)
efficiency
that
monitoring
agricultural
productivity
sustainability
across
world.
We
present
a
global
database
country-level
budget
estimates
for
nitrogen
(N),
phosphorus
(P)
potassium
(K)
cropland.
The
database,
disseminated
FAOSTAT,
is
meant
provide
reference,
synthesizing
continuously
updating
state-of-the-art
on
this
topic.
covers
205
countries
territories,
well
regional
aggregates,
period
1961
2020.
Results
highlight
wide
range
efficiencies
geographic
regions,
nutrients,
time.
For
year
2020,
data
show
average
N
surpluses
from
about
10
kg
ha-1
year-1
Africa
more
than
90
Asia.
Furthermore,
they
P
K
deficits
2020
Americas.
This
study
introduces
improvements
over
previous
work
relation
key
coefficients
affecting
estimates,
especially
removal
crop
products,
manure
content,
atmospheric
deposition
biological
fixation
rates.
conclude
by
discussing
future
research
directions,
highlighting
need
align
statistical
definitions
groups,
further
refine
plant
livestock
expand
all
land,
including
flows
meadows
pastures.