Abstract: • ICFAR-DB organises and stores data from 16 Italian long term agronomic experiments. • ICFAR-DB fulfils interoperability using system dynamics ontology and AgMIP nomenclature. • ICFAR information management system moves closer data to model and vice versa. The IC-FAR national project (Linking long term observatories with crop system modelling for better understanding of climate change impact, and adaptation strategies for Italian cropping systems) initiated in 2013 with the primary aim of implementing data from 16 long term Italian agronomic experiments in a common, interoperable structure. The building of a common database (DB) structure demands a harmonization process aimed at standardising concepts, language and data in order to make them clear, and has to produce a well-documented and easily available tool for the whole scientific community. The Agricultural Model Intercomparison and Improvement Project (AgMIP) has made a great effort in this sense, improving the vocabulary developed by the International Consortium for Agricultural Systems Applications (ICASA) and defining harmonization procedures. Nowadays, these ones have also to be addressed to facilitate the extraction of input files for crop model simulations. Substantially, two alternative directions can be pursued: adapting data to models, building a standard storage structure and using translators that convert DB information to model input files; or adapting models to data, using the same storage structure for feeding modelling solutions constituted by combining model components, re-implemented in the same model platform. The ICFAR information management system simplifies data entry, improves model input extraction (implementing System Dynamics ontology), and satisfies both the paradigms. This has required the development of different software tools: ICFAR-DB for data entry and storage; a model input extractor for feeding the crop models (MoLInEx); SEMoLa platform for building modelling solutions and performing via scripts the model intercomparison. The use of the standard AgMIP/ICASA nomenclature in the ICFAR-DB and the opportunity to create files with MoLInex for feeding AgMIP model translators allow full system interoperability.

Abstract: • Comparison of two methods for soil organic C quantification is presented. • Springer–Klee wet digestion and dry combustion with automated analyser were compared. • Soil samples were collected from three different sites in a Southern Italy area. • Recoveries close to one were observed for whole dataset and for data grouped per site. • The strong agreement between the methods would enable direct comparison of results. Abstract Soil organic carbon (SOC) is the largest carbon pool in the terrestrial biosphere and it is among the most important factors responsible for conservation of soil quality. Automated dry combustion techniques are gradually replacing traditional quantification methods based on wet digestion chemistry. Critical comparison of different methods is fundamental to reevaluate archives of SOC data and accurately assess and model long-term carbon stock variation and should be performed for different soil types and management conditions. Two analytical methods, the Springer–Klee wet digestion and the dry combustion using an automated analyser, were compared for soils typical of a Mediterranean environment in Southern Italy. Soil samples were collected from three sites, at two depths. Soils were fine textured (from clay–loam to clay) with total carbonate ranging from 6.6 to 16.7 g 100 g− 1. SOC content varied from 6.92 to 28.86 g kg− 1 (as average of the two methods), with values and ranges typical of Southern Europe. On average, Springer–Klee method gave slightly higher values and showed greater data variability. This behaviour, in agreement with other studies, can be attributed to the reaction of K2Cr2O7 with other soil constituents and to analytical constraints. Our results suggest high consistency between Springer–Klee and dry combustion techniques and show recoveries close to one both for the whole dataset and for data grouped per experimental site or soil depth. Linear regression equations between the two methods were slightly affected by different soil types (P = 0.0621). The best fitting of the relationship was a linear regression passing through the origin for the whole dataset (Radj2 = 0.965; RPD = 3.41). The strong overall agreement observed between the two methods would enable the direct comparison of new data set with those already existing in Southern Italy for soils with similar characteristics.

Abstract: A field experiment was conducted in Southern Italy to evaluate the effects of different water quality and fertilizers on yield performance of tomato crop. In mineral nitrogen (N) fertilizer and irrigation with fresh water (Electrical Conductivity, EC, = 0.9 dS m⁻¹) (FWF); mineral N fertilizer and irrigation with saline water (EC = 6.0 dS m⁻¹) (SWF); municipal solid waste (MSW) compost and irrigation with fresh water (EC = 0.9 dS m⁻¹) (FWC); MSW compost and irrigation with saline water (EC = 6.0 dS m⁻¹) (SWC). At harvest, weight and number of fruits and refractometric index (°Brix) were measured, total and marketable yield and dry matter of fruit were calculated. The results indicated that MSW compost, applied as amendment, could substitute the mineral fertilizer. In fact, in the treatments based on compost application, the tomato average marketable yield increased by 9% compared with treatments with mineral fertilizer. The marketable yield in the SWF and SWC treatments (with an average soil EC in two years to about 3.5 dS m⁻¹) decreased respectively of 20 and 10%, in respect to fresh water treatments. At the end of the experiment, application of compost significantly decreased the sodium absorption rate (SAR) of SWC treatment in respect of SWF (−29.9%). Significant differences were observed among the four treatments both on soil solution cations either exchangeable cations. In particular compost application increased the calcium (Ca) and potassium (K) contents in saturated soil paste respect to the SWF ones (31.4% and 59.5%, respectively). At the same time saturated soil paste sodium (Na) in SWC treatment recorded a decrease of 17.4% compared to SWF.