• Energy Research
• natural sciences close
• 2. Zero hunger close
• FR close
• IT close

In the transition from linear production systems, unsustainable from the point of view of resources, to a model that finds strength in environmental, social and economic sustainability, the circular economy paradigm is the foundation that facilitates the planetary agro-ecological transition. The European Union has taken a number of steps (including the Circular Economy Package of Directives) shaping circularity as a wide-ranging driver measure involving many sectors. The paper intends to provide a regulatory framework on the current general situation regarding circularity in European Union, in order to extrapolate and give evidence to the aspects that intersect the agri-food sector. This is not only because they are poorly addressed in the literature, but also because there is a lack of regulatory instruments on the circular economy specifically addressing this area of interest. For this purpose, the analysis focuses on waste and residue/scrap management issues, recognized by law as by-products and end-of-waste status, as they are covered by circular economy legislation and as they can be applied to the agri-food sector. The latter allow the implementation of circularity strategies in the agri-food sector and, given the numerousness of production chains and the peculiarities of each of them, various regeneration and/or reuse processes of specific resources may be depicted. The intent is to provide useful knowledge on how to implement sustainable waste management, also proposing a concrete case on a by-product of olive oil processing, through which it is possible to highlight how the correct application of regulations favors the adoption of circular economic and management models in the firms involved, as well as informing the relevant economic operators on the possible profiles of legal liability that may arise from insufficient knowledge. Furthermore, this paper delves into the European Green Deal’s Strategy as it enriches the circular economy paradigm with new facets. NextGenerationEU and the National Recovery and Resilience Plan financially support this strategy in the aftermath of the socioeconomic crisis from COVID-19 in the EU Member States. This is in order to achieve the objective of achieving the agro-ecological transition.

Urea is the most common nitrogen (N) fertilizer in agriculture, due to its cheaper price and high N content. Although the reciprocal influence between NO3- and NH4+ nutrition are well known, urea (U) interactions with these N-inorganic forms are poorly studied. Here, the responses of two tomato genotypes to ammonium nitrate (AN), U alone or in combination were investigated. Significant differences in root and shoot biomass between genotypes were observed. Under AN+U supply, Linosa showed higher biomass compared to UC82, exhibiting also higher values for many root architectural traits. Linosa showed higher Nitrogen Uptake (NUpE) and Utilization Efficiency (NUtE) compared to UC82, under AN+U nutrition. Interestingly, Linosa exhibited also a significantly higher DUR3 transcript abundance. These results underline the beneficial effect of AN+U nutrition, highlighting new molecular and physiological strategies for selecting crops that can be used for more sustainable agriculture. The data suggest that translocation and utilization (NUtE) might be a more important component of NUE than uptake (NUpE) in tomato. Genetic variation could be a source for useful NUE traits in tomato; further experiments are needed to dissect the NUtE components that confer a higher ability to utilize N in Linosa.

SUMMARYThis article discusses how decentralisation policies are enacted in the planning and implementation of natural resource management interventions in rural Ethiopia. A key element of decentralisation policy is the emphasis on greater participation by local communities. Drawing on qualitative research conducted with government staff and farmers, this paper illustrates how different actors perceive and implement national policy and how these actions affect the longer‐term sustainability of land management interventions. Copyright © 2014 John Wiley & Sons, Ltd.

With an approach combining crop modelling and biotechnology to assess the performance of three durum wheat cultivars (Creso, Duilio, Simeto) in a climate change context, weather and agronomic datasets over the period 1973–2004 from two sites, Benatzu and Ussana (Southern Sardinia, Itay), were used and the model responses were interpreted considering the role of DREB genes in the genotype performance with a focus on drought conditions. The CERES-Wheat crop model was calibrated and validated for grain yield, earliness and kernel weight. Forty-eight synthetic scenarios were used: 6 scenarios with increasing maximum air temperature; 6 scenarios with decreasing rainfall; 36 scenarios combining increasing temperature and decreasing rainfall. The simulated effects on yields, anthesis and kernel weights resulted in yield reduction, increasing kernel weight, and shortened growth duration in both sites. Creso (late cultivar) was the most sensitive to simulated climate conditions. Simeto and Duilio (early cultivars) showed lower simulated yield reductions and a larger anticipation of anthesis date. Observed data showed the same responses for the three cultivars in both sites. The CERES-Wheat model proved to be effective in representing reality and can be used in crop breeding programs with a molecular approach aiming at developing molecular markers for the resistance to drought stress.

The basins of the Indus and Ganges rivers cover 2.20 million km2 and are inhabited by more than a billion people. The region is under extreme pressures of population and poverty, unregulated utilization of the resources and low levels of productivity. The needs are: (1) development policies that are regionally differentiated to ensure resource sustainability and high productivity; (2) immediate development and implementation of policies for sound groundwater management and energy use; (3) improvement of the fragile food security and to broaden its base; and (4) policy changes to address land fragmentation and improved infrastructure. Meeting these needs will help to improve productivity, reduce rural poverty and improve overall human development.

AbstractBACKGROUND: Inappropriate utilisation of biosolids may adversely impact agrosystem productivity. Here, we address the response of wheat (Triticum durum) to different doses (0, 40, 100, 200 and 300 t ha−1) of either municipal solid waste (MSW) compost or sewage sludge in a greenhouse pot experiment. Plant growth, heavy metal uptake, and antioxidant activity were considered.RESULTS: Biomass production of treated plants was significantly enhanced at 40 t ha−1 and 100 t ha−1 of MSW compost (+48% and +78% relative to the control, respectively). At the same doses of sewage sludge, the increase was only 18%. Higher doses of both biosolids restricted significantly the plant growth, in concomitance with the significant accumulation of heavy metals (Ni2+, Pb2+, Cu2+ and Zn2+), especially in leaves. Leaf activities of antioxidant enzymes (ascorbate peroxidase, glutathione reductase, catalase and superoxide dismutase) were unchanged at 40 t ha−1 MSW compost or sewage sludge, but were significantly stimulated at higher doses (200–300 t ha−1), together with higher leaf concentration of reduced glutathione.CONCLUSION: This preliminary study suggests that a MSW supply at moderate doses (100 t ha−1) could be highly beneficial for wheat productivity. Copyright © 2010 Society of Chemical Industry

Life Cycle Assessment (the systematic analysis of the environmental impact of products during their entire life cycle), Carbon Footprint and Water Footprint assessments play an important role in decision-making processes. These assessments can help guide land management decisions and will likely play a larger role in the future, especially in natural areas with high biodiversity. Agriculture is a substantial consumer of fresh water, so it is important to identify causes and possible solutions to optimize agricultural water use. Water footprint assessments consider water consumption from several points of view and aid in reaching Sustainable Development Goals. Olive trees are a widespread agricultural crop growing in the Mediterranean Basin and are particularly important in the Umbria region in Italy. This paper estimates the water footprint impact related to the production of 1 kg of olives in a rainfed olive orchard managed using low environmental impact techniques. Eleven years of data collection (meteorological data, olives yield data, processes data) are analyzed for typical rural conditions. The results show that local management techniques have lower water requirements than standard international usages. These results can be used to improve and to further explore agricultural water use.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.