Crop model ideotyping for agricultural diversification

Evidence based crop diversification requires modelling for crops that are currently neglected or underutilised. Crop model calibration is a lengthy and resource consuming effort that is typically done for a particular variety or a set of varieties of a crop. Whilst calibration data are widely available for major crops, such data are rarely available for underutilised crops due to limited funding for detailed field data collection and model calibration. Subsequently, the lack of evidence on their performance will lead to the lack of interest from the policy and regulatory communities to include these crops in the agricultural development plans. In order to motivate further research into the use of state of the art techniques in modelling for less known crops, we have developed and validated an ideotyping technique that approximates the crop modelling parameters based on already calibrated crops of different lineage. The method has been successfully tested for hemp (Cannabis sativa L.) based on a well-known crop model. In this paper we present the method and provide an impetus on the way forward to further develop such methods for modelling the performance of minor crops and their varieties. The approach works based on modelling the performance of hemp using the knowledge from an existing model that was developed for sugar cane. The customisation uses one of the most prominent models (AquaCrop) to approximate growth coefficients for hemp (Cannabis sativa L.). A sequential procedure was used to approximate the phenological stages in the growth model that performs well in the calibration and validation steps. (C) 2021 The Author(s). Published by Elsevier B.V.