•No tillage provided no benefits to wheat grain yield under rainfed conditions.•Durum wheat and sunflower yields were more stable under minimum tillage.•Maize yields were higher and more stable under ...conventional or minimum tillage.•NT was unsuitable for sunflower and maize under non-Vertisols heavy clayish soils.•Sunflower yields were constrained by water availability and soil status at sowing.
Long term investigations on the combined effects of tillage systems and other agronomic practices such as mineral N fertilization under Mediterranean conditions on durum wheat are very scanty and findings are often contradictory. Moreover, no studies are available on the long term effect of the adoption of conservation tillage on grain yield of maize and sunflower grown in rotation with durum wheat under rainfed Mediterranean conditions. This paper reports the results of a 20-years experiment on a durum wheat-sunflower (7 years) and durum wheat–maize (13 years) two-year rotation, whose main objective was to quantify the long term effects of different tillage practices (CT=conventional tillage; MT=minimum tillage; NT=no tillage) combined with different nitrogen fertilizer rates (N0, N1, N2 corresponding to 0, 45 and 90kgNha−1 for sunflower, and 0, 90 and 180kgNha−1 for wheat and maize) on grain yield, yield components and yield stability for the three crops. In addition, the influence of meteorological factors on the interannual variability of studied variables was also assessed. For durum wheat, NT did not allow substantial yield benefits leading to comparable yields with respect to CT in ten out of twenty years. For both sunflower and maize, NT under rainfed conditions was not a viable options, because of the unsuitable (i.e., too wet) soil conditions of the clayish soil at sowing. Both spring crops performed well with MT. No significant N×tillage interaction was found for the three crops. As expected, the response of durum wheat and maize grain yield to N was remarkable, while sunflower grain yield was not significantly influenced by N rate. Wheat yield was constrained by high temperatures in January during tillering and drought in April during heading. The interannual yield variability of sunflower was mainly associated to soil water deficit at flowering and air temperature during seed filling. Heavy rains during this latter phase strongly constrained sunflower grain yield. Maize grain yield was negatively affected by high temperatures in June and drought in July, this latter factor was particularly important in the fertilized maize. Considering both yield and yield stability, durum wheat and sunflower performed better under MT and N1 while maize performed better under both CT and MT and with N2 rates. The results of this long term study are suitable for supporting policies on sustainable Mediterranean rainfed cropping systems and also for cropping system modelling.
Agriculture can benefit from crop diversification to facilitate its transition to more sustainable agrifood systems. However, these practices remain rare in Europe. One major barrier is the existence ...of sociotechnical lock-ins. To clarify the dynamics at work, we analyzed the relationships between actors involved in 23 crop diversification experiences across 11 European countries. The novelty of this paper lies in the systemic analysis of the network of actors involved in crop diversification experiences. Using data from qualitative interviews and cognitive mapping approaches, we identify and describe the role of actors and the key relationships in crop diversification and detect relationships that are currently missing. Our study shows that in the different European countries, similar relationships act as levers or barriers to crop diversification, with farmers and researchers playing a crucial role. The most important cognitive factors that influence the choice of farmers to diversify are environmental and health concerns and the desire to make profit and innovate. We relate the cognitive factors to organizational, technical, economic, and political factors and suggest levers for crop diversification based on successful crop diversification experiences.
Background: Redesigning the agri-food system through agroecology represents a common ambition among practitioners, activists and scholars to achieve environmental and socioeconomic sustainability. ...Research can have a main role to support this path. Although it seems that there is a gradual increasing body of agroecology research, it clearly lacks good knowledge about this. The main objective of this study was therefore to map research projects related to agroecology in Europe with the aim to characterize European research in terms of implementation of agroecology elements, identify needs for future cross collaboration between countries and networks, and support the setting up of appropriate research agendas fostering agroecology research in Europe. Methods: A desktop research with different databases related to European and transnational funding programmes was carried out to identify funded research projects involved in agroecology. The obtained projects were used to perform a social network analysis. Furthermore, two surveys were conducted, one with coordinators of identified projects and a second one for researchers engaged in agroecology. Results: Our study highlighted a predominant trajectory of agroecology research prone to the transformation of the agri-food system. France, Germany, Italy, Netherlands, Portugal, Spain, and United Kingdom were the most active countries engaged in agroecology research. In all surveys, issues related to efficiency improvement, synergies strengthening, local economy development, and co-creation and sharing of knowledge were the most implemented to support agri-food transformation. Transdisciplinary approaches were mainly addressed by European projects. Surveys reported a limited participation of value chain actors, while researchers, farmers, and their associations were the most involved. Survey respondents suggested to increase project duration and introduce flexibility methods to modulate research actions according to dynamic of the contexts.Conclusion: On the basis of the results, some policy recommendations were provided to fostering agroecology research in Europe and its contribution for transformation of agri-foods systems.
This study assesses the ability of an ensemble of crop models (MME) to predict the impacts of fertilization and crop residue management on soil organic carbon (SOC) and aboveground biomass (AGB) in a ...long-term experiment (LTE) based on continuous maize cropping systems. Data from a LTE in Northern Italy were used. Treatments included continuous grain (MG) or silage (MS) maize, fertilized with mineral, cattle slurry, and farmyard manure. The MME median resulted the best predictor of the observed values. Models performance was better when simulating MG than MS, and for crops treated with mineral compared to organic fertilizers. The ability to predict the dynamics of SOC was affected by the model used and by the year × residues management and year × fertilizer interactions. The model and the residue × fertilizer interaction affected the ability to simulate AGB dynamics. Results showed that a MME can effectively predict the long-term dynamics of SOC and maize crop production under contrasting fertilization and crop residue management, and thus their potential for climate change mitigation. The uncertainty in the simulation of SOC is related to the model routines simulating SOC partitioning and to the complexity of the interactions between management factors over time. Highlights - A crop model ensemble was compiled to simulate soil organic carbon and maize aboveground biomass dynamics in a long-term experiment. - The performances of stand-alone models and their ensemble were assessed under contrasting fertilization and crop residue management. - The multi-model ensemble using the median value of simulation was the best predictor of the variables observed in the long-term experiment. - Improved performances in simulations were observed when crop residues were incorporated into the soil, regardless of the fertilization management. - The uncertainty in SOC simulation increased over time for cropping systems with silage maize and organic fertilization.
The agriculture sustainability assessment is a difficult issue for the coexistence of conflicting objectives and the multidimensionality of the performances. The environmental, economic and social ...pillars need to be simultaneously considered in an assessment to evaluate potential synergies and trade-offs of the agricultural processes within and among the attributes of the dimensions in both implemented systems (ex-post analysis) and potential options (ex-ante analysis). Among several sustainability assessment methods, tools based on multi-criteria analysis (MCA) are increasingly adopted in evaluating sustainability in agriculture. The aim of this work was to present the MCA tool developed in the framework of the BioDurum project for the sustainability assessment of organic farms located in southern Italy and characterised by durum wheat-based crop rotations. The tool was entirely designed through a participatory process and it was realised using the open-source DEXi software that have demonstrated to be particularly suitable for creating qualitative multi-criterial hierarchic models with the engage of stakeholders. The hierarchic structure of BioDurum_MCA tool was resulted composed by 64 indicators and 45 aggregated attributes articulated in three branches representing the agro-environment, economic, and social sustainability pillars. The articulated structure of the tool reflected the complexity and the sustainability issues and priorities expressed by the involved stakeholders. The tool was tested in four Italian organic farms presenting different agro-environmental and socio-economic patterns for their ex-post evaluations and in three different ex-ante production systems identified in compliance with the Italian regulation concerning the requirements of the rotations to be implemented in organic farming. The results highlighted the well discriminatory power of the tool. The best overall sustainability scores were reached in both ex-post and ex-ante analysis by the well diversified cereal farming systems with processed products sold through short supply chain mechanisms. BioDurum_MCA has proved to be a feasible tool to identify strengths and weaknesses of organic durum wheat-based production systems. Its adoption can support the definition of specific interventions for the sector in the Italian Strategic National Plan of the Common Agricultural Policy. Further improvements in the threshold classes of some indicators by using the tool in a wider number of Italian durum wheat based organic farms will increase model sensitivity and reliability of the results. Highlights - BioDurum_MCA is an effective tool for sustainability assessment of durum wheat organic Italian production systems. - Hierarchic structure of the tool reflects the sustainability issues and priorities expressed by involved stakeholders. - MCA tools can support a holistic evaluation of farm sustainability performances in the frame of post-2020 CAP.
Although hemp cultivation is increasingly perceived as a promising option in terms of crop diversification, especially in semi-arid conditions such as in the Mediterranean region, its adoption ...remains limited thus constraining the development of hemp value chains at a larger scale. Our objective was to explore suitable conditions, at farm and downstream levels, for organic hempseed oil production in Sicily, taking on an action-research perspective that involves local actors. Based on a preliminary characterisation of barriers to organic hemp development at different value chain levels, we carried out targeted complementary investigation: (i) assessment on agroenvironmental performances of integrating hemp in durum wheat-based rotations; (ii) chemical analysis of local hempseed oil; (iii) exploration of marketing opportunities and value chain development. Our results showed that the lack of technical and economic knowledge as well as the deficiencies of suitable cultivars and adequate machinery were the main barriers for the organic hemp value chain development in Sicily. The analysis of agroenvironmental performances also revealed both strengths and weaknesses of hemp introduction in durum-wheat based rotations. Despite the identified limitations, we demonstrated that the organic hemp value chains represent interesting perspectives for the Sicilian farming sector, particularly in case of substantial barriers removal or adaptation.
Bien que la culture de chanvre soit perçue de manière croissante comme une option prometteuse pour la diversification des cultures, en particulier en conditions semi-arides dans la zone méditerranéenne, le développement à large échelle de chaînes de valeur pour le chanvre est encore limité. Notre objectif était d’explorer les conditions adéquates pour l’exploitation de l’huile de chanvre biologique en Sicile au niveau de la ferme et de l’aval. Nous avons opté pour une perspective de recherche-action mobilisant des acteurs locaux. À partir d’une caractérisation préliminaire des freins au développement du chanvre biologique en Sicile à différents maillons de la chaîne de valeur, nous avons mené des recherches complémentaires ciblées : (i) évaluation des performances agroenvironnementales de l’intégration du chanvre dans des rotations à base de blé dur, (ii) analyse chimique de l’huile de chanvre locale, (iii) exploration des opportunités en termes de commercialisation et développement de chaîne de valeur. Nos résultats montrent des perspectives intéressantes pour les chaînes de valeur de chanvre biologique en Sicile avec une rentabilité prometteuse, en particulier si les freins les plus importants sont levés ou des adaptations trouvées. L’étude a également mis en lumière des points clés à considérer pour un développement futur du chanvre.
Biogeochemical simulation models are important tools for describing and quantifying the contribution of agricultural systems to C sequestration and GHG source/sink status. The abundance of simulation ...tools developed over recent decades, however, creates a difficulty because predictions from different models show large variability. Discrepancies between the conclusions of different modelling studies are often ascribed to differences in the physical and biogeochemical processes incorporated in equations of C and N cycles and their interactions. Here we review the literature to determine the state-of-the-art in modelling agricultural (crop and grassland) systems. In order to carry out this study, we selected the range of biogeochemical models used by the CN-MIP consortium of FACCE-JPI (http://www.faccejpi.com): APSIM, CERES-EGC, DayCent, DNDC, DSSAT, EPIC, PaSim, RothC and STICS. In our analysis, these models were assessed for the quality and comprehensiveness of underlying processes related to pedo-climatic conditions and management practices, but also with respect to time and space of application, and for their accuracy in multiple contexts. Overall, it emerged that there is a possible impact of ill-defined pedo-climatic conditions in the unsatisfactory performance of the models (46.2%), followed by limitations in the algorithms simulating the effects of management practices (33.1%). The multiplicity of scales in both time and space is a fundamental feature, which explains the remaining weaknesses (i.e. 20.7%). Innovative aspects have been identified for future development of C and N models. They include the explicit representation of soil microbial biomass to drive soil organic matter turnover, the effect of N shortage on SOM decomposition, the improvements related to the production and consumption of gases and an adequate simulations of gas transport in soil. On these bases, the assessment of trends and gaps in the modelling approaches currently employed to represent biogeochemical cycles in crop and grassland systems appears an essential step for future research.
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•We assess simulated C and N cycles in agricultural systems based on published modelling studies.•Biogeochemical models have limits in simulating pedo-climatic conditions and management effects.•We propose explicit modelling of soil microbial biomass to drive SOC turnover.•Improved approaches of gas transport in soil are required for future modelling ork.
This study evaluated the agro-environmental and economic effectiveness of strips introduced in a diversified organic vegetable system. Two experiments of three experimental years (2018, 2019, 2020) ...were carried out within the 4-year rotation of MOnsampolo VEgetable organic Long-Term Experiment (MOVE LTE) in Central Italy to test strip cropping vs pure stand. The crop combinations in the two experiments were faba bean (Vicia faba L.)–tomato (Solanum Lycopersicum L.) and common wheat (Triticum aestivum)–zucchini (Cucurbita pepo L.). We determined the productive and economic performances, disease and weed control, nutritional differences and effectiveness in returning carbon to the soil. The two strip cropping systems allowed a better use of resources, enhancing plant biomass and crop residues, particularly for tomato (+24%) and zucchini (+63%). However, the greater plant biomass did not always result in an increase in crop yields. For example, while the wheat–zucchini strip system showed a land equivalent ratio >1 in all three experimental years with a high yield performance in zucchini (+54% of yield), the faba bean–tomato system was more productive in strips only in 2018. On the contrary, this latter system contributed a carbon return >1 in all three experimental years. No significant differences between strip and pure stand systems were observed for fusarium (Fusarium oxysporum f. sp. lycopersici) and oidium (Oidium spp.) diseases on tomato and zucchini crops, respectively, and for weed control. Lastly, greater labor costs associated in both experiments did not affect their profitability (+21% and +319% in faba bean–tomato and wheat–zucchini experiments, respectively). Overall, our findings pointed out that farmers could increase sustainability of their cropping systems with the introduction of a well-designed strip cropping system, which can lead to the reduction of economic risks, greater potential soil carbon and more efficient use of resources on the same land.
Organic agriculture is perceived as environmentally sustainable, but, under its umbrella, different production systems exist ranging from simplified organic productions to well diversified systems ...with a full implementation of agro-ecological approaches. Among several developed tools for agriculture sustainability assessment, multi-criteria models are increasingly gaining importance. In this study, we evaluated the use of the multi-criteria DEXi-BIOrt tool, coupled with data from long-term experiments, for the sustainability assessment of different organic vegetable production scenarios. These scenarios were applied in two Italian areas: the Adriatic coast of Marche Region and the Metaponto plan of Basilicata Region. Despite the presence of some critical issues, DEXI-BIOrt proved to be a valid tool for the sustainability evaluation of organic vegetable productions. In both areas, the most sustainable scenarios resulted the well diversified organic systems characterized by proper rotations, inclusion of agro-ecological service crops, cultivation of local and different cultivars, and presence of short supply chain mechanisms. Conversely, the implementation of the simplified organic substitution scenarios does not guarantee a suitable level of sustainability. The findings of this study could support decision makers in the implementation of appropriate measures for enhancing organic production sustainability in the framework of post-2020 Common Agricultural Policy.
•We evaluated the response of 11 agro-ecosystem models to within-field variability of soil conditions.•The sensitivity of models to spatially variable site conditions differed considerably.•It was ...found that intensified calibration did not necessarily lead to improved model output.•The importance of quality-assured soil and yield information for model improvement was highlighted.
Process-oriented agro-ecosystem models are increasingly applied to assess crop management options or impacts of climate change on agricultural production, food security and ecosystem services. Thereby, the aggregation of initial soil and climate information is a widely used approach for performing simulations at larger scales such as regions, nations or even globally. In this context, the ability of models to respond to different site conditions is essential for high quality impact assessment through the use of modelling tools. As part of a model inter-comparison the present study investigated models’ yield response on variable site conditions using data sets from two well-documented fields, one located in Germany and one in Italy. The fields were sampled at 60 and 100 grid points, respectively, and soil and crop variables were recorded at varying intensity for the entire simulation period covering three growing seasons. The data was provided successively to the participating modelling groups in three calibration steps (a, b, and c) and the first growing season was considered for calibration. Model validation was based on these steps and each growing season as well as on the entire simulation period considering the soil state variables mineral nitrogen and water content (N, WC) as well as crop yield, biomass, and leaf area index (LAI). The WC was best depicted by the models, resulting in high correlation coefficients (r) up to 0.81 between simulated and observed values. The root mean square error (RMSE) of simulated N ranged from 20 kg ha−1 to 1072 kg ha−1 regarding all steps and growing seasons. The annual within-field variability of yields was better simulated by the models when observed subsoil information was provided. However, the RMSE ranged from 0.5 t ha−1 to 3.5 t ha−1 at the German field, and from 0.6 t ha−1 to 5.9 t ha−1 at the Italian field, respectively. It was found that intensified calibration did not necessarily lead to improved model output. Furthermore, single models showed specific inconsistencies in their algorithms when, for example, underestimated WC was associated with overestimated yields. In total, the sensitivity of models to spatially variable site conditions differed considerably. The importance of quality-assured soil and yield information for model improvement was highlighted.
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