Modular frameworks can be designed for crop modelling by decomposing models into reusable parts or sub-models. This allows key crop processes like phenology, light interception, biomass production, and partitioning to be assembled in different configurations depending on factors like crop type, limiting factors, scale, and objectives. Guidelines are needed for systematically selecting the appropriate modules to assemble a crop model tailored to the specific crop system and simulation question. Testing different model structures and comparing model performance can help identify the optimal modelling solution.
OPEN SOURCE GEOPROCESSING TOOLS AND METEOROLOGICAL SATELLITE DATA FOR CROP RISK ZONES MONITORING IN SUB-SAHARAN AFRICA
AUTHORS T. De Filippis, L. Rocchi, P. Vignaroli, M. Bacci, V. Tarchiani and E. Rapisardi National Research Council - Institute of Biometeorology (CNR –IBIMET), Florence, Italy
Presentazione OGRS Conference 2016
Slide Presentation Design: Elena Rapisarid
These slides are about how crop and weather are interlinked an d how their association can be an impressive tools in the hands of the creative minds of the scientific world.
OPEN SOURCE GEOPROCESSING TOOLS AND METEOROLOGICAL SATELLITE DATA FOR CROP RISK ZONES MONITORING IN SUB-SAHARAN AFRICA
AUTHORS T. De Filippis, L. Rocchi, P. Vignaroli, M. Bacci, V. Tarchiani and E. Rapisardi National Research Council - Institute of Biometeorology (CNR –IBIMET), Florence, Italy
Presentazione OGRS Conference 2016
Slide Presentation Design: Elena Rapisarid
These slides are about how crop and weather are interlinked an d how their association can be an impressive tools in the hands of the creative minds of the scientific world.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
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Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
2024.06.01 Introducing a competency framework for languag learning materials ...
Designing modular frameworks for crop modelling. Myriam Adam
1. Designing modular frameworks
for crop modelling
Implementation and guidelines for use
Myriam ADAM
Marc CORBEELS, Frank EWERT, Herman VAN KEULEN,
Peter LEFFELAAR, Jacques WERY
2. 2 /20
Why having modular frameworks?
• Large collection of crop models
• Increasing interest in model reuse
• Are they directly applicable? How to adapt them for the
specific application/objective?
Need of guidelines for model selection for
a given crop, in a given context and for a given
question (system studied)
3. 3 /20
Diversity of objectives diversity
of models and their structures
Photosynthesis of leaf canopies
1965 (de Wit 1965)
ELCROS
1970 (de Wit et al. 1970) Pedigree of models of
the ‘School of de Wit’
(Adapted from Bouman et al. 1996. Agric. Syst. 52:171-198)
MICROWEATHER
1975 ARID CROP (Goudriaan 1977)
(van Keulen 1975)
ARID CROP BACROS PHOTON
(SAHEL) (de Wit et al. 1978) (de Wit et al. 1978)
(van Keulen et al. 1986)
1980
PAPRAN
(Seligman & van Keulen 1981)
SUCROS
1985 (van Keulen et al. 1982)
SWHEAT SUCROS87 MACROS
WOFOST
1990 (van Keulen & Seligman 1987) (van Laar et al. 1992)
(van Diepen et al. 1988) (Penning de Vries et al. 1989)
(van Keulen & Wolf 1986)
SUCROS1
(Goudriaan & van Laar 1994) INTERCOM
(Kropff & van Laar 1993)
1995 SUCROS2 WOFOST 7.0
(van Laar et al. 1997) (Boogaard et al. 1998)
ORYZA
(Kropff et al. 1995)
2000 ORYZA2000
(Bouman et al. 2001)
GECROS
2005 (Yin & van Laar 2005)
4. 4 /20
Objective
• Develop framework to facilitate the assembly of crop
models depending on the crop system and on the
simulation objective (when to use which model?)
▫ IMPLEMENTATION
▫ Decompose the models into parts (different structures)
▫ Incorporate the different parts in a framework
▫ USE
▫ Develop criteria and approaches to select relevant parts to
assemble a crop model depending on the crop system and the
simulation objective
6. 6 /20
Diverse models = Diverse structures
Anything in common?
Structure of these models is based on the same basic crop
processes
Phenology
spring crop
winter crop
indeterminate
Light interception Production level
Homogenous Cascading
Water
limited Darcy
LAI expansion
Row Nitrogen Nitrogen fixation
limited
Biomass production
Partitioning
RUE
Allocation factor
Farquhar Source sink
strength
7. 7 /20
Applying new software techniques in crop
modelling
• Software engineers also decompose their models into
sub-models
• Applying object-oriented techniques enables to :
▫ Interchange of code among models
▫ Test of alternatives hypotheses
▫ Share expertise
Applying their techniques to more easily reuse parts of
code and build on the existing expertise
8. 8 /20
Design used
CROSPAL APES APSIM
Modules RUE Strategy design Strategy design Dynamic link
Basic crop processes pattern pattern libraries (dlls)
Component Abstract factory Composite Generic model
Crop and criteria with a strategy structure/ XML
Biomass GUI (IStrategy: configuration
production
interface)
Crop models Definition of new Components GCROP linked
Soil-crop concrete factories linked via to the APSIM
(i.e. crop simulator) wrapper engine
9. 9 /20
Implications for the users
Developers Crop modellers Model users
--- CROSPAL GUI
APES
APES APSIM
GUI
Composite
Flexi strategies Biomass
GUI
bility production
CROSPAL
factories
CROSPAL APES
strategies strategies
PLANT from APSIM
dlls and xml
+++ RUE
10. 10 /20
Implications for the users
• How to combine the different parts?
• How to deal with the flexibility?
• Need of criteria or systematic approaches to
define “the logic to assemble the appropriate
modules”
11. Select relevant parts to assemble a
crop model depending on the crop
system and the simulation
objective
Guidelines for use
12. 12 /20
CROSPAL
CROp Simulator: Picking and Assembling Libraries
Phenology:
Criteria
spring crop
Phenology:
winter crop
Phenology:
indeterminate
LAI expansion
Crop type
Limiting factors
Biomass production: (water, N, P,K…)
RUE
Biomass production:
Farquhar
Scale
Biomass
partitioning
Data availability
Management
Water
limited
Nitrogen Nitrogen fixation
limited
13. 13 /20
Test different model structures
winter crop indeterminate
spring crop
Objective of Picking the basic crop The “right”
simulation growth and modelling solution
development processes (crop model)
according to criteria
Models comparison
Sensitivity analysis
Expert elicitation Uncertainty matrix
Conceptual modelling Underlying the main
assumptions
14. 14 /20
Uncertainty matrix
Source of Nature Range Recognized
uncertainty The The “unknown ignorance
“known known” (to be) known” The “known
unknown”
Contextual: System definition
boundaries and
definitions
Input/data Data collection Data availability
uncertainties
Parameters Sensitivity analysis
Model Structure Scenario analysis Data availability/
research
▫ Study the system in a systematic way
▫ Test different modules
▫ Document uncertainties by explicitly formulating the
assumptions
15. 15 /20
Models comparison
North South Detailed Summarized Farq. RUE Farq. RUE
LAI LAI NORTH SOUTH
▫ Investigate the effect of modelling details on potential yield
▫ Identify which structure in which location
16. 16 /20
Participatory modelling
▫ Understand the initial model
▫ Integrate new knowledge
▫ Test the new model
18. 18 /20
Main conclusions
Definition of guidelines to facilitate exchange of
models (or parts of models)
Better documentation of modules but also of
modelling decision-making process (e.g.
use of uncertainty matrix)
Modular modelling is prone to error
seeking for scientific understanding vs. credible set of
outputs
Role of the crop modeller and conceptual models
19. 19 /20
Use of models for different purposes
Developers Crop modellers Model users
--- Software engineer Agronomist
CROSPAL GUI
Modeling Solution Soil-crop system
APES
APES APSIM
GUI
Composite
Flexi strategies
GUI
bility Uncertainty
CROSPAL
Component factories Basic crop processes
CROSPAL APES
strategies strategies
Underlying assumptions
PLANT from APSIM
dlls and xml
Underlying concept
Module
+++
Basic research Applied research
20. APES team
Funding: PRI, CIRAD, SEAMLESS
Thanks all for your attention
Acknowledgements
contact: m.adam@cgiar.org