Whilst simulating crop performance in different environments can help fill the knowledge gap and improve the adoption of crops that are currently neglected and underutilised in conventional agrifood systems, lack of experimental data remains a barrier to widespread modelling of these crops. To date, no attempt has been made to collate sub-species crop data that are specifically suited for modelling underutilised crops. This article describes the first attempt to develop a database for crop modelling data with a focus on European underutilised crops.
View Article and Find Full Text PDFCurrent agricultural production depends on very limited species grown as monocultures that are highly vulnerable to climate change, presenting a threat to the sustainability of agri-food systems. However, many hundreds of neglected crop species have the potential to cater to the challenges of climate change by means of resilience to adverse climate conditions. Proso millet (Panicum miliaceum L.
View Article and Find Full Text PDFAn evidence base was developed to facilitate adoption of hemp ( L.) in tropical environments (Wimalasiri et al. (2021)).
View Article and Find Full Text PDFEvidence 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.
View Article and Find Full Text PDFFollowing the development of a database that was specifically designed to store value chain information, particularly for underutilised crops, this article describes the data that are currently stored in the database and accessible through its web portal. The data includes various datasets on utilisation status, agro-ecological requirements and season lengths, potential yield and nutritional composition of crops. The data are stored in the form of tables with fixed data elements (column attributes).
View Article and Find Full Text PDFSoil data for Sri Lanka are available through semi-detailed series maps that were developed based on limited soil profile data combined with expert knowledge. This data plays a vital role in decisions at national and regional levels. However, the present format of this database does not allow for their wider use in crop simulation modelling and other related agricultural research that require finer scale data.
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