Soil organic carbon under conservation agriculture in Mediterranean and humid subtropical climates: Global meta‐analysis

Conservation agriculture (CA) is an agronomic system based on minimum soil disturbance (no-tillage, NT), permanent soil cover, and species diversification. The effects of NT on soil organic carbon (SOC) changes have been widely studied, showing somewhat inconsistent conclusions, especially in relation to the Mediterranean and humid subtropical climates. These areas are highly vulnerable and predicted climate change is expected to accentuate desertification and, for these reasons, there is a need for clear agricultural guidelines to preserve or increment SOC. We quantitively summarized the results of 47 studies all around the world in these climates investigating the sources of variation in SOC responses to CA, such as soil characteristics, agricultural management, climate, and geography. Within the climatic area considered, the overall effect of CA on SOC accumulation in the plough layer (0–0.3 m) was 12% greater in comparison to conventional agriculture. On average, this result corresponds to a carbon increase of 0.48 Mg C ha−1 year−1. However, the effect was variable depending on the SOC content under conventional agriculture: it was 20% in soils which had ≤ 40 Mg C ha−1, while it was only 7% in soils that had > 40 Mg C ha−1. We proved that 10 years of CA impact the most on soil with SOC ≤ 40 Mg C ha−1. For soils with less than 40 Mg C ha−1, increasing the proportion of crops with bigger residue biomasses in a CA rotation was a solution to increase SOC. The effect of CA on SOC depended on clay content only in soils with more than 40 Mg C ha−1 and become null with a SOC/clay index of 3.2. Annual rainfall (that ranged between 331–1850 mm y−1) and geography had specific effects on SOC depending on its content under conventional agriculture. In conclusion, SOC increments due to CA application can be achieved especially in agricultural soils with less than 40 Mg C ha−1 and located in the middle latitudes or in the dry conditions of Mediterranean and humid subtropical climates

Ethylene-auxin crosstalk regulates postharvest fruit ripening process in apple

The ripening of climacteric fruits, such as apple, is represented by a series of genetically programmed events orchestrated by the action of several hormones. In this study, we investigated the existence of a hormonal crosstalk between ethylene and auxin during the post-harvest ripening of three internationally known apple cultivars: 'Golden Delicious', 'Granny Smith' and 'Fuji'. The normal climacteric ripening was impaired by the exogenous application of 1-methylcyclopropene (1-MCP) that affected the production of ethylene and the physiological behaviour of specific ethylene-related quality traits, such as fruit texture and the production of volatile organic compounds. The application of 1-MCP induced, moreover, a de-novo accumulation of auxin. The RNA-Seq wide-transcriptome analysis evidenced as the competition at the level of the ethylene receptors induced a cultivar-dependent transcriptional re-programming. The DEGs annotation carried out through the KEGG database identified as most genes were assigned to the plant hormone signaling transduction category, and specifically related to auxin and ethylene. The interplay between these two hormones was further assessed through a candidate gene analysis that highlighted a specific activation of GH3 and ILL genes, encoding key steps in the process of the auxin homeostasis mechanism. Our results showed that a compromised ethylene metabolism at the onset of the climacteric ripening in apple can stimulate, in a cultivar-dependent fashion, an initial de-novo synthesis and de-conjugation of auxin as a tentative to restore a normal ripening progression

Reducing Topdressing N Fertilization with Variable Rates Does Not Reduce Maize Yield

Proximal sensing represents a growing avenue for precision fertilization and crop growth monitoring. In the last decade, precision agriculture technology has become affordable in many countries; Global Positioning Systems for automatic guidance instruments and proximal sensors can be used to guide the distribution of nutrients such as nitrogen (N) fertilization using real-time applications. A two-year field experiment (2017–2018) was carried out to quantify maize yield in response to variable rate (VR) N distribution, which was determined with a proximal vigour sensor, as an alternative to a fixed rate (FR) in a cereal-livestock farm located in the Po valley (northern Italy). The amount of N distributed for the FR (140 kg N ha−1) was calculated according to the crop requirement and the regional regulation: ±30% of the FR rate was applied in the VR treatment according to the Vigour S-index calculated on-the-go from the CropSpec sensor. The two treatments of N fertilization did not result in a significant difference in yield in both years. The findings suggest that the application of VR is more economically profitable than the FR application rate, especially under the hypothesis of VR application at a farm scale. The outcome of the experiment suggests that VR is a viable and profitable technique that can be easily applied at the farm level by adopting proximal sensors to detect the actual crop N requirement prior to stem elongation. Besides the economic benefits, the VR approach can be regarded as a sustainable practice that meets the current European Common Agricultural Policy

A Design Methodology of Multi-level Digital Twins

This paper proposes a design methodology of Digital Twins enabling multi-level simulation of equipment in a manufacturing plant. In this context, the Digital Twin covers a central role where it can perform analysis of the current state of the plant and, more importantly, prediction regarding its future state. This requires the use of complex models for all the nodes that compose the entire production, to obtain a more accurate estimation of future equipment states. Furthermore, most of the commercial tools provided by different vendors do not consider this dimension of the problem and allows to perform simulations of the plant with a very high level of abstraction, or with the use of statistical approximation. On the other hand, several physical process simulators allow to model and simulate single equipment, but without considering the production line perspective. Multi-Level modeling considers different levels of abstraction of the same model, allowing to switch from a model to another. This paper proposes a design flow methodology based on multi-level approach, that allows to obtain a unique environment where physical and production simulators are integrated automatically. The entire design flow is validated with a real use case scenario. The obtained results show different simulation strategies using multi-level approach with different synchronization granularity

Computation of total soil organic carbon stock and its standard deviation from layered soils

To assess carbon sequestration in the agricultural and natural systems, it is usually required to report soil organic carbon (SOC) as mass per unit area (Mg ha-1) for a single soil layer (e.g., the 0-0.3 m ploughing layer). However, if the SOC data are reported as relative concentration (g kg-1 or %), it is required to compute the SOC stock and its standard deviation (SD) for a given layer as the product of SOC concentration and bulk density (BD). For a proper computation, it is required to consider that these two variables are correlated. Moreover, if the data are already reported as SOC stock for multiple sub-layers (e.g., 0-0.15 m, 0.15-0.3 m) it is necessary to compute the SOC stock and its SD for a single soil layer (e.g., 0-0.3 m). The correlation between stocks values from adjacent and non-adjacent soil sub-layers must be accounted to compute the SD of the single soil layer. The present work illustrates the methodology to compute SOC stock and its SD for a single soil layer based on SOC concentration and BD also from multiple sub-layers. An Excel workbook automatically computes the means of stocks and SD saving the results in a ready-to-use database. - Computation of a carbon (SOC) stock and its standard deviation (SD) from the product between SOC concentration and bulk density (BD), being correlated variables. - Computation of a SOC stock and its SD from the sum of SOC stocks of multiple correlated sub-layers. - An Excel workbook automatically computes the means of SOC stocks and SD and saves the results in a ready-to-use database

Carotid artery stenting renaissance: is it safe and effective using new materials?

Data from randomized controlled trials (RCTs) demonstrated significant differences between carotid artery stenting (CAS) and carotid endarterectomy (CEA) in terms of early neurological outcomes (from 0 to 30 days), although mid- and long-term neurological results are indistinguishable. CAS in symptomatic standard risk patients is coupled with a higher risk of any stroke, and death or any stroke at 30 days, while the rates of disabling or major stroke do not vary remarkably between treatments. Since the micro-embolization through the stent struts is the primary suspected cause of suspected early postoperative neurological complications (i.e., non-disabling stroke), surgical technology has focused on the production of a new generation of stents with a double layer of mesh to reduce the "free area" of the cells, and on new cerebral protection devices. Another major determinant of early negative outcomes is believed to be the intraluminal manipulation occurring during carotid engagement from the aortic arch, the crossing maneuvers at the level of the culprit lesion and vessel trauma during angioplasty. To address these subject matters, new embolic protection devices and innovative strategies have been developed, consequently. This review is designed to furnish the current status of CAS results, to update the ongoing RCTs comparing CAS vs. CEA outcomes, and to recapitulate the features and clinical outcomes for a new carotid stent design, the so called "mesh-stents", and new embolic protection tools

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von S. E. Blog

Hybrid interface in sepiolite rubber nanocomposites: Role of self-assembled nanostructure in controlling dissipative phenomena

Sepiolite (Sep)-styrene butadiene rubber (SBR) nanocomposites were prepared by using nano-sized sepiolite (NS-SepS9) fibers, obtained by applying a controlled surface acid treatment, also in the presence of a silane coupling agent (NS-SilSepS9). Sep/SBR nanocomposites were used as a model to study the influence of the modified sepiolite filler on the formation of immobilized rubber at the clay-rubber interface and the role of a self-assembled nanostructure in tuning the mechanical properties. A detailed investigation at the macro and nanoscale of such self-assembled structures was performed in terms of the organization and networking of Sep fibers in the rubber matrix, the nature of both the filler-filler and filler-rubber interactions, and the impact of these features on the reduced dissipative phenomena. An integrated multi-technique approach, based on dynamic measurements, nuclear magnetic resonance analysis, and morphological investigation, assessed that the macroscopic mechanical properties of clay nanocomposites can be remarkably enhanced by self-assembled filler structures, whose formation can be favored by manipulating the chemistry at the hybrid interfaces between the clay particles and the polymers