Design and Implementation of Declarative Crop Modeling Framework

Abstract

Crop modeling is a process of translating quantitative knowledge on crop growth into a computer program that simulates the growth in silico. From a software engineering perspective, crop modeling has suffered from a legacy built decades ago when early crop models appeared. Many crop models have been developed in imperative programming approaches striving for high performance, but frequently suffered from error-prone code and technical debts left behind. In this study, we propose a new declarative modeling framework named Cropbox written in Julia programming language to support developing crop models in a concise form equipped with useful abstractions commonly required in modeling. With an insight that a crop model is essentially an integrated network of generalized state variables, the framework provides various primitives for representing variables and systems as well as functions essential to modeling workflow. The modeling workflow based on Cropbox was used to create and illustrate its applications in crop modeling at different levels of organization and complexity. The first application was phenology modeling for building an ensemble model to predict flowering time based on various existing approaches. Extracting common patterns in the models and developing reusable interface for simulation, visualization, and calibration motivated an idea of a new modeling framework. The second application was a coupled gas-exchange model which combines two models for biochemical photosynthesis and empirical stomatal conductance with an additional link to an energy balance equation. The model implemented in Cropbox framework provided the same functionality as an existing model written in C++ with less code and a more flexible interface in terms of parameter management and output visualization. To demonstrate the capability of the model, we evaluated two stomatal conductance modeling approaches and applied them to replicate the observed behavior of transgenic plants from the literature. The last application was a whole-plant crop simulation model for garlic (Allium sativum) translated from an existing C++ model aimed at simulating leaf development and growth. The new model was expanded and improved to simulate biomass and yield with an emphasis on whole-plant carbon budget. The model was evaluated with three datasets for analyzing effective planting dates as a climate adaptation strategy in South Korea under future climate conditions projected by different greenhouse gas emission scenarios. The Cropbox framework can support development of conventional crop models but also show potential for incorporating other approaches like functional-structural plant modeling (FSPM) as briefly illustrated by a 3D root structure growth model for switchgrass (Panicum virgatum). With a domain-specific language and unified interface specifically designed for crop modeling, the Cropbox framework will become a useful tool for research and teaching in this field.