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An evaluation of the effect of the conservation agriculture (CA) on agro-environmental aspects is needed at the farm scale in intensive production systems, which are likely prone to reduce soil fertility. Here, as part of the HelpSoil LIFE+ Project and involving 20 farms in the Po valley (Northern Italy), we have estimated the soil organic carbon (SOC) content, SOC stock, crop yield, biological fertility, soil biodiversity, and economic efficiency under different agricultural systems (CA and conventional, CvtA) at the beginning (March 2014) and end (October 2016) of the experimental period. CA was mostly represented by no-till practice (NT) coupled with the cultivation of winter cover crops. Minimum tillage (MT) was considered as CA or CvtA practice according to the farm design. The CA practices have been implemented on the monitored farms at different times (Long-term=before 2006, Medium-term=between 2006, Short-term=after 2013. A direct comparison between CA and CvtA of soil-related variables, yields, and costs was performed on 14 out of the 20 farms; data were statistically treated with a linear mixed model.Overall, CA resulted in significantly higher SOC content, SOC stock, biological fertility, QBS-ar, and earthworms for the Medium-term group. Considering the effect of tillage practices observed on the 20 farms, SOC content was the highest in NT for the Long-term group. The biological fertility index was higher in NT and MT compared to CvtA within the Long-term and Medium-term groups in 2016. QBS-ar was the higher in MT and NT than CvtA for the Long-term and Medium-Term groups. The number of earthworms was the highest under NT for the Long-term group. Maize, winter wheat, and soybeans yields were generally 1 t ha -1 higher in CvtA than in CA, but this did not reach statistical significance. The cost for herbicides was 18% more expensive in NT, whereas the fuel consumption and total costs for weeding operations did not differ between NT and CvtA.The overall outcome of the analysis was that CA is a viable solution for intensive farms in the monitored area, but further skills need still to be acquired in to enhance its economic feasibility. Highlights Conservation and conventional agriculture (CA, CvtA) evaluation on 20 farms in 3 years  Implementation_Year (IY) of CA differed among the farms  SOC and biological fertility index were higher in CA than in CvtA according to IY  CA of recent IY was found in higher SOC storage and lower yield than CvtA  CA may be more profitable than CvtA if cover crop and weed management improves IntroductionAgriculture is required to face major agro-environmental threats, such as the increasing carbon dioxide (CO2) concentration in the atmosphere, decreasing biodiversity, and limited water availability (Bouma and McBratney, 2013); these processes can be effectively mitigated by an adequate management of the soil (McBratney et al., 2014). Conservation agriculture (CA), originally aimed at reducing water and wind erosion in the United States (Faulkner, 1943), was recently pro...

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SUMMARYA reliable evaluation of crop nutritional status is crucial for supporting fertilization aiming at maximizing qualitative and quantitative aspects of production and reducing the environmental impact of cropping systems. Most of the available simulation models evaluate crop nutritional status according to the nitrogen (N) dilution law, which derives critical N concentration as a function of above-ground biomass. An alternative approach, developed during a project carried out with students of the Cropping Systems Masters course at the University of Milan, was tested and compared with existing models (N dilution law and approaches implemented in EPIC and DAISY models). The new model (MAZINGA) reproduces the effect of leaf self-shading in lowering plant N concentration (PNC) through an inverse of the fraction of radiation intercepted by the canopy. The models were tested using data collected in four rice (Oryza sativaL.) experiments carried out in Northern Italy under potential and N-limited conditions. MAZINGA was the most accurate in identifying the critical N concentration, and therefore in discriminating PNC of plants growing under N-limited and non-limited conditions, respectively. In addition, the present work proved the effectiveness of crop models when used as tools for supporting education.