Development of a process-based simulation model of camelina seed and oil production: A case study in Northern Italy

Abstract

Camelina (Camelina sativa L. Crantz) is an oilseed crop gaining interest due to its potential portfolio of derived bio-based products. The inclusion of camelina in traditional crop rotations is fostered by the possibility of growing it either as spring or autumn crop, the latter being of particular interest in the Mediterranean region. Here we present a process-based simulation model for camelina, CAMEL, and we evaluate its performances in predicting yield, oil production and principal fatty acid accumulation. CAMEL integrates a crop simulator with a model of soil water balance and with models to reproduce main seed qualitative traits. It was calibrated and validated using ten camelina field experiments performed in Northern Italy in non-limiting conditions for soil water availability and nitrogen fertilization during 2015–2017. The results for phenology (average error of 6.7 days), and biomass and yield accumulation (RRMSE = 23% for aboveground biomass and 9% for yield) denoted the ability of CAMEL to reproduce field observations of crop development and growth across growing seasons and sowing periods. The large correlation between simulated and measured oil fractions highlights the correct reproduction of the main camelina fatty acids. This work lays the basis for the use of CAMEL as a support tool to assess seed yield and quality in Northern Italy, besides further work is still needed to add the impact of management practices on yield and qualitative traits, before adopting CAMEL for in-season farmer support.