RESUMO
We introduce an integrative process-based crop model for garlic (Allium sativum). Building on our previous model that simulated key phenological, morphological, and physiological features of a garlic plant, the new garlic model provides comprehensive and integrative estimations of biomass accumulation and yield formation under diverse environmental conditions. This model also showcases an application of Cropbox to develop a comprehensive crop model. Cropbox is a crop modeling framework featuring declarative modeling language and a unified simulation interface for building and improving crop models. Using Cropbox, we first evaluated the model performance against three datasets with an emphasis on biomass and yield measured under different environmental conditions and growing seasons. We then applied the model to simulate optimal planting dates under future climate conditions for assessing climate adaptation strategies between two contrasting locations in South Korea: the current growing region (Gosan, Jeju) and an unfavorable cold winter region (Chuncheon, Gangwon). The model simulated the growth and development of a southern-type cultivar (Namdo, ND) reasonably well. Under Representative Concentration Pathway (RCP) scenarios, an overall delay in optimal planting date from a week to a month, and a slight increase in potential yield were expected in Gosan. Expansion of growing region to northern area including Chuncheon was expected due to mild winter temperatures in the future and may allow ND cultivar production in more regions. The predicted optimal planting date in the new region was similar to the current growing region that favors early fall planting. Our new integrative garlic model provides mechanistic, process-based crop responses to environmental cues and can be useful for assessing climate impacts and identifying crop specific climate adaptation strategies for the future.
RESUMO
BACKGROUND AND AIMS: Phenology and morphology are two major aspects of crop growth models. A new process-based model built for hardneck garlic (Allium sativum) is presented, focusing on phenology and morphology processes and how they translate to whole-plant growth. The tight coupling between the two processes and their dynamic changes throughout the growing season were captured while incorporating storage effects and reproductive aspects unique to bulbous crops. METHODS: Non-linear temperature dependences of leaf development were integrated into the model and dynamically coupled with changes in leaf growth throughout the growing season. Bulb storage effects on leaf development and photoperiod effects on the vegetative-to-reproductive transition were also incorporated. The model was parameterized with data from a set of experiments and the literature, while its performance was tested with additional observations that had not been used for parameterization under a range of environmental conditions, management practices and cultivar choices. KEY RESULTS: The model successfully captured the dynamic nature of leaf development and growth in garlic plants throughout the growing season. It simulated with reasonable accuracy the timing of leaf initiation, maturation and senescence, as well as changes in green leaf area over time. Most parameters were relatively stable across cultivars, and parameter sensitivity tests revealed the importance of bulb storage effects. CONCLUSIONS: The model embodies a novel approach to capture the phenology and morphology of garlic under a range of environments, genotypes and management practices. The process-oriented nature of the model and inclusion of storage effects set the foundation for bulbous crop growth simulations, allowing the understanding and discovery of key processes that coordinate and integrate the dynamics of growth and development from organ to whole plant, with implications for crop improvement programmes while opening opportunities for modelling other bulbous crops.