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Crop Modeling CoP
Pre-Convention
Update
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Dear
members,
We
are pleased to invite
you to the upcoming
CGIAR Convention on
Big Data in
Agriculture that
will take place next
week from 19 to 23
October 2020. It will be
a fully virtual,
#OneCGIAR convention,
engaging a wide audience
of more than 2,500
researchers, private
sector stakeholders,
donors and investors,
and entrepreneurs from
around the globe.
Under
the theme of Digital
Dynamism for Adaptive
Food Systems, the
convention will focus on
several subtopics,
including natural and
digital ecosystems, food
security in times of
crisis, inclusive
digital transformation,
agile digital
technologies, and
natural and digital
ecosystems. Don't miss
this unique opportunity
and register for free
TODAY to the convention!
In this
Convention, our
Crop Modeling
Community of Practice
will host different
sessions that can be of
your interest. Find all
the details below! We
are happy to welcome you
to our sessions!
Regards,
The Crop Modeling
Community of Practice Team
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Virtual
Convention: Digital
Dynamism for
Adaptive Food
Systems
19-23 OCTOBER 2020
ONLINE & GLOBAL
#BDPGLOBAL2020 #OneCGIAR
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CROP
MODELING CoP
INTERNAL SESSIONS
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Disease
Crop Modeling
Advances and
Challenges for
Large-Scale
Simulation Studies
19
OCTOBER, 2:00 - 4:00
PM CEST
Speakers: Diego
Pequeno, Timothy
Krupnik, Jose Mauricio
Fernandes, Simone
Bregaglio, Carlos Montes,
Jacob Smith &
Christopher Gilligan
In
this session we present
some aspects of crop
disease modeling including
minimum data requirements,
integration of disease and
crop growth models, and
successful applications of
crop disease modeling new
technologies.
Outline: Crop pests
and diseases assessing and
monitoring are important
aspects of agricultural
systems to consider for
assuring food security in
many parts of the world.
Multidisciplinary
approaches such as crop
growth modeling
integration with pests and
disease modeling have
advanced in this aspect to
develop warning systems
and crop damage
assessments tools. In this
session we present some
aspects of crop disease
modeling including minimum
data requirements,
integration of disease and
crop growth models, and
successful applications of
crop disease modeling new
technologies.
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Phenotyping
and Remote Sensing to
Facilitate Minimum
Data Set Requirements
for Crop Simulation
Modelling
19
OCTOBER, 4:30 PM -
6:30 PM CEST
Speakers: Matthew
Reynolds, Kai
Sonder, Davide Cammarano
& Heidi Webber
This
workshop will discuss
ideas on how the digital
technologies such as
remote sensing for high
throughput phenotyping can
supplement or potentially
serve as proxies for some
of the harder to phenotype
traits required, in
different modelling
contexts.
Outline: Crop
models can require
extensive and/or intensive
data sets to drive
simulations as well as for
calibration purposes.
While some of the
information is
straightforward, such as
agronomic performance
traits (e.g. yield,
phenology) as well as
weather data, other types
of data require
significant resources such
as green area index, light
interception and water and
nitrogen availability in
the soil. As a result, the
vast majority of field
data sets are not ‘model
friendly’, lacking key
inputs required for
simulation purposes. This
workshop will discuss
ideas on how the digital
technologies such as
remote sensing for high
throughput phenotyping can
supplement or potentially
serve as proxies for some
of the harder to phenotype
traits required, in
different modelling
contexts.
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CROP
MODELING
CoP SESSIONS DURING
THE CONVENTION
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Are
you a crop
modeler, a GIS
specialist or a
crop scientist
interested on how
Machine Learning
can be applied to
crop Models? Or
are you wondering
how to study crop
growth and
development at a
spatial level.
Then don’t miss
the two webinars
the Crop Modeling
Community of
Practice is
going to present
during the
Convention.
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Machine
Learning and Crop
Modeling. A Modern
Affair?
21
OCTOBER, 2:15 PM - 3:00
PM CEST
Speakers: Scott
Chapman &
Mark Cooper
Several efforts have been
developed recently to
integrate (deep) machine
learning (ML) algorithms
into crop models to result
in better predictions and
inform adaptation
strategies. In this session
our speakers will present
the current work they are
developing to link training
genetic data to crop models
to improve predictions and
facilitate genomic selection
for upstream crop management
support. Some examples of
image analysis and
phenotyping using ML linked
to crop models will be
presented. After the
presentation, our panelists
will open up a discussion
about the role of ML in crop
modeling.
Register
for the convention to
join this session.
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Gridded
Crop Modeling Advances
and Challenges for
Regional and Global
Simulation Studies
22
OCTOBER, 1:00 PM - 1:45
PM CEST
Speakers: Diego
Pequeno, Jawoo
Koo &
Christoph Müller
Several efforts have been
developed to integrate
point-based crop models with
Geographic Information
Systems (GIS) input data to
study crop growth and
development at a spatial
level. Due to the complexity
of data variability
representation and accuracy
over space and time, many
crop modeling groups have
developed tools to run
gridded crop simulation
models. In this session we
present some of those
approaches, including
concepts of GIS data
requirements, examples of
crop modeling studies using
spatial level data and
processing of simulation
outputs.
Register
for the convention to
join this session.
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If
you missed our
latest blog posts or one
of our previous
webinars, no worries!
We've added the most
recent here, as well
as a link to our website
page where you can
watch all previous
webinars.
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New
study on
measuring
efficiency in
potato
landraces: How
far are we from
the optimum?
A
new publication by
scientists from
the International
Potato Center
(CIP) highlights
the usefulness of
combining crop
growth model,
remote sensing,
and plant
ecophysiological
tools to assess
genetic
efficiencies in
potato
landraces...READ
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What are TPEs? What
are they useful for?
How can a breeding
program develop and
use them? In this
webinar organized by
the Crop Modeling
Community of Practice
these and more
questions are
addressed...WATCH
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This webinar
presents what
secondary data are
being used by CGIAR
crop modeling
researchers and
discuss when to (and
not to) use the
secondary data in
practice...
WATCH
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