Crop2ML: A multi-language crop modeling framework for the exchange and reuse of

crop model components

Cyrille Midingoyi

Christophe Pradal, Andreas Enders, Davide Fumagalli, Hélène Raynal, Ioannis Athanasiadis, Cheryl Porter, Gerrit Hoogenboom, Dean Holzworth,

Frédérick Garcia, Peter Thorburn, Marcello Donatelli, Pierre Martre

October, 10th 2019 - Montpellier, France

Atelier #DigitAg

Modélisation

Atelier #DigitAg Axe 6 Modélisation,Montpellier, 17 octobre 2019

Introduction Standard Crop model representation (Crop2ML) CyML: Common modelling language of crop model PyCrop2ML software Use cases Perspectives

Outline

Context

Soil (RU, Infiltration….)

Atmosphere

Organ, Plant, Crop…

Agricultural policy Research

Decision support Tool

use:

Importance:

Objectives - Crop yield - Nutrient content

- Bio-Energy - Erosion - Emissions - ….

Agricultural practices (Sowing date, irrigation,….)

1

- Climate - Soil - Management - Plant

Model

Yield Soil, Water dynamics…

Introduction: Context

+40 wheat models in use (AgMIP)

𝐶𝑟𝑜𝑝𝑀𝑜𝑑𝑒𝑙 = 𝐸 𝐸𝑐𝑜𝑝ℎ𝑦𝑠𝑖𝑜𝑙𝑜𝑔𝑖𝑐𝑎𝑙 𝑃𝑟𝑜𝑐𝑒𝑠𝑠𝑒𝑠 = 𝑓(𝑃𝑙𝑎𝑛𝑡, 𝑆𝑜𝑖𝑙, 𝐶𝑙𝑖𝑚𝑎𝑡𝑒,

𝑀𝑎𝑛𝑎𝑔𝑒𝑚𝑒𝑛𝑡, 𝑡𝑖𝑚𝑒, … )

Ecosystem Level

Crop Level

Plant Level

Organ Level

Cell Level

Molecular Level

Different Levels of organization

Different objectives

Gene regulation…

Metabolism…

Organ growth…

Phenology…

Biomass…

Carbon flux…

Pla

nt

and

Cro

p S

cien

ce

Cro

p m

od

ellin

g P

latf

orm

s

Syst

ems

Bio

logy

1 Chew et al, 2014

Process-based Crop Models

Introduction: Agricultural Models Exchange Initiative

AMEI

Exchange of model components (Process-level) and code reuse

Propose a solution to the crop modelling community for NexGen crop modeling tools

Realize the benefit of sharing and complementing different expertises

Reuse model parts to leverage the expertise of third parties

Vision Motivation

2

Comparison of biomass (AGBM) of 23 wheat models for AgMIP project (Martre et al., 2015)

Which hypothesis is due to the difference of model outputs?

Introduction: Challenges

RECORD

Crop2ML (Python, Fortran, C++, C#, Java,…)

Transparent Reproducible Less Time-consuming More Modular

Good level abstraction of crop model representation

From abstraction to target

platform (conversely)

3

Objectives Goals

White-box approach

Related work

Declarative modelling language (white-box approach)

Muetzelfeldt and Massheder, 2003

Visual modelling languages Multi-scale modelling and simulation Framework (black-box approach)

Marshall-Colon et al., 2017

Hucka et al., 2017

4

Standard model representation (Crop2ML)

I. Conceptual model independent-platform (XML-based description) II. Formal rules to describe ecophysiological processes (Algorithms) or functions

(CyML language)

Model Unit Structure Model Composition Structure 5

(Equation + control flow)

Models communicate through link elements (scientific workflow)

Standard model representation (Crop2ML)

6

From Crop2ML model specifications to model diagram flow (Eg. Energy balance of SiriusQuality)

Composite

Link

CyML is an extensible subset of Cython (Python + C types) to represent algorithms in crop models.

Control structures (if elif else, for, while) / finite difference equations

Provides standard functions (characteristics) supported by the target languages.

7 Fully automatized Language conversion workflow (Transpiler)

CyML : Common modelling language of crop model

Cpp F90 Java C# Py R

FWSi

mM

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els

Do

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lass

es

Stra

tegy

cla

sses

No

des

(F

acto

ry)

VLE

pac

kage

Sub

mo

du

les

Mo

du

les

Automatic Conversion frameworks

Crop2ML models Repository

Pyt

ho

n

Java

Fort

ran

C+

+

C#

Dat

a Fl

ow

Dis

cret

e-ev

ent

Pro

ced

ura

l

XM

L/ O

-O

PyCrop2ML software

O-O: object –oriented approach 8

XM

L/ O

-O

Phenology Energy Balance

Phenology Energy Balance

Phenology Energy Balance

Crop2ML Algo only in Cyml

Crop2ML Src/Test generated in F90, C#, Py

Transpiler Phenology Energy Balance

Crop2ML Package

Use Cases

9

(Pradal et al., 2008)

(Enders et al., 2010)

(Bergez et al., 2013)

(BioMA, 2012)

(Jones et al., 1998)

(Brisson et al., 1998)

(Holzworth and al., 1996) Semi-automatically

Automatically

CyM

L A

ST

Lan

guag

es

AST

From code to AST From AST to AST From AST to code

1 2 3

Perspectives

Figure 2: CyML transformation extensibility

• User-friendly JupyterLab environment to develop, edit, and

visualize Crop2ML components (in progress)

• Public model repositories (linking publications to models for

reproducibility)

• New functionalities:

Check validity of model units (equations) and model composition

Model annotation (CropML concepts, ontology)

Propose a plant structure representation (Multi-Scale Tree Graph)

• Link with other initiatives (Crops In Silico…) and plant and crop

modelling platforms

Perspectives

10

Follow and contribute to Crop2ML development on GitHub

https://github.com/AgriculturalModelExchangeInitiative/ 11

Thanks