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Rapeseed is one of the most important sources of vegetable oils, and its cultivation in Europe is expanding due to the economic incentives to grow energy crops. Given the unique characteristics of this crop, simulation studies targeting yield predictions and scenario analysis should be performed using specific models rather than using generic crop simulators adapted to rapeseed via calibration. This study presents a new model – WOFOST-GTC – which implements a dynamic representation of the rapeseed canopy architecture and includes modelling approaches to simulate oil content and composition. We reduced the number of model parameters to 35, compared to the 97 parameters of the original WOFOST model, from which it derives. WOFOST-GTC was developed using data collected in dedicated field experiments carried out in northern Italy in 2012–2013. The model ability to reproduce the underlying processes was evaluated using data collected in Europe between 1993 and 2013. In particular, dynamics involved with production and oil quality were evaluated on 7 and 18 datasets, respectively. The aboveground biomass and photosynthetic area index at different depths in the canopy were accurately simulated (R 2 = 0.86 and 0.78, respectively). Despite the lower complexity, WOFOST-GTC proved to be as accurate as the original WOFOST model. The simulation of the seed oil content (R 2 = 0.76) and of the oleic (R 2 = 0.95), linoleic (R 2 = 0.88) and α-linolenic acid (R 2 = 0.95) fractions was accurate. Hence, we propose WOFOST-GTC as a suitable simulation model to analyse the rapeseed production and oil quality under different weather and management scenarios. [ABSTRACT FROM AUTHOR]

Highlights: [•] An attempt to compile a validation guideline for in vivo field methods is presented. [•] The guideline is derived by adapting norms from chemistry. [•] A case study for indirect determination of rice nutritional status is presented. [•] The applicability and effectiveness of the proposed procedure is discussed. [ABSTRACT FROM AUTHOR]