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Greenhouse gas emissions (GHGs) into the atmosphere derived from the use of fertilisers is a serious issue for the sustainability of agricultural systems, also considering that the growing global demand for food requires an increasingly productive agriculture. Emissions dynamics are very variable and are determined by many factors and their reciprocal interactions. Among driving factors, soil type (mineral, organic and microbiological composition), fertilisation method, climate, and the cropping system. In the present experiment, the combined effect of soil organic matter (SOM) and fertilisation method on the emissions of GHGs and ammonia (NH3) was investigated. Liquid fraction of digestate from pig slurries, compost from organic fraction of municipal solid wastes, and urea were applied on bare soil with two levels of organic matter (OM1: 1.3% and OM2: 4.3%). Emissions were directly monitored by a static chamber system and a portable gas analyser. Results show that soil organic matter as well as the composition of the fertilisers affect greenhouse gasses emissions. Emissions of methane (CH4) produced by digestate and compost during experimental period were higher in correspondence of lower organic matter content (0.58 – 0.49 kg CH4 C/ha/ day and 0.37 – 0.32 kg CH4 C/ha/day for digestate and compost respectively), contrary to what was observed for urea. For all fertilisers, carbon dioxide (CO2) and nitrous oxide (N2O) emissions were higher in correspondence of higher organic matter level. In particular, CO2 emissions were 11.05%, 67.48% and 82.84% higher in OM2 than OM1 for digestate, urea and compost respectively. Likewise, N2O emissions were 87.45%, 68.97% and 92.11% higher in OM2 than OM1 for digestate, urea and compost respectively. The obtained results show that the content of organic matter in soils plays a key role on the emissions of GHGs, generally enhancing the levels of gas emissions.

Quinoa (Chenopodium quinoa Willd.) is capable of adapting to multiple environments and tolerating abiotic stresses including saline, drought and frost stress conditions. However, the introduction of quinoa into new environments has disclosed adaptation challenges. The principle factor affecting crop pollination is heat stress at flowering, which leads to sterile plants. To investigate the effect of high temperatures during the sensitive phenological phases, flowering and seed germination, a Danish-bred cultivar (cv. Titicaca) was grown in climatic chambers. Selection of the cv. Titicaca was based on the fact that it is the most extensively used cultivar in the Sahel and Middle East and North African region. The results of this research demonstrated that temperatures exceeding 38 °C hindered seed germination and pollination, and therefore, seed yield at harvest. At 38 °C, seed yield losses were 30%, whilst seed germination percentage declined below 50%. In addition, the results of the present research were compared with field observations from Burkina Faso in order to determine the spatiotemporal suitability of this crop with respect to temperature stress. Although many other abiotic stresses need to be considered when defining crop calendars (e.g. heavy precipitation in July and August), this research proposes the following growing periods to avoid heat-stress conditions at flowering: Sahel (July–September and November–February), Soudano–Sahel (June–February) and Soudanian zone (all year round).

The paper presents results from a study examining the relationship between large-scale modes of climate variability with the fluctuations in the yield of barley, durum wheat, olives and sunflower crops in Tuscany, Italy. In particular, the blocking circulation over the growing season, with associated hot and dry conditions, decreased yield for olive crops, barley and durum wheat. The teleconnections analysed in this study are the winter North Atlantic Oscillation (NAO) and the Summer North Atlantic Oscillation (SNAO); the West African Monsoon (WAM) and the Intertropical Front (ITF); and although NAO, SNAO, ITF and WAM are not strictly related to each other, the values of these indices are strongly related to the atmospheric circulation regimes and related weather types. Thus, they have an impact on precipitation and temperature patterns in Italy and on yields of important crops in Tuscany. Results show that the large-scale temperate and tropical variability directly influences the crop yield through three main circulation regimes. These patterns illustrate the importance of the large-scale modes, which, together with the associated weather types, have an impact directly on Tuscan crop yields; both barley and olive yields decline significantly when the ITF is further north with warmer and drier conditions in Italy.

In this paper a modern statistical technique of multivariate analysis is applied to an indoor radon concentration data base. Several parameters are more or less significant in determining the radon concentration inside a building. The elaboration of the information available on South Tyrol makes it possible both to identify the statistically significant variables and to build up a statistical model that allows us to forecast the radon concentration in dwellings, when the values of the same variables involved are given. The results confirm the complexity of the phenomenon.

Title pageSoil microbiome biomass, activity, composition and CO2 emissions in a long term organic and conventional farming systems.

Proximal optical sensors (POSs) are effective devices for monitoring the development of crops and the nitrogen (N) status of plants. POSs are both useful and necessary in facilitating the reduction of N losses into the environment and in attaining higher nitrogen use efficiency (NUE). To date, no comparison of these instruments has been made on quinoa. A field experiment conducted in Tuscany, Italy, with different POSs, has assessed the development of quinoa with respect to N status. Three sets of POSs were used (SPAD-502, GreenSeeker, and Canopeo App.) to monitor quinoa development and growth under different types of fertilizers (digestate and urea) and levels of N fertilization (100, 50, and 0 kg N ha−1). The present findings showed that in-season predictions of crop biomass at harvest by SPAD-502 and GreenSeeker optical sensors were successful in terms of the coefficient of determination (R2 = 0.68 and 0.82, respectively) and statistical significance (p < 0.05), while the Canopeo App. was suitable for monitoring the plant´s canopy expansion and senescence. The relative error (RE%) showed a remarkably high performance between observed and predicted values, 5.80% and 4.12% for GreenSeeker and SPAD-502, respectively. Overall, the POSs were effective devices for monitoring quinoa development during the growing season and for predicting dry biomass at harvest. However, abiotic stresses (e.g., heat-stress conditions at flowering) were shown to reduce POSs’ accuracy when estimating seed yields at harvest, and this problem will likely be overcome by advancing the sowing date.