Experimental analysis on concrete blocks reinforced with Arundo donax fibers

Over the last decades, there has been a growing attention in research and development on non-conventional building materials, such as vegetable fibers (e.g., flax; hemp; jute; etc.), to be used as eco-friendly materials in a wide range of applications in civil construction. The main reasons of this interest are related to the specific properties, price and sustainability of natural fibers, which can be considered as “green” building materials. In this article, the tensile strength of a new type of fibers extracted from stem of the Giant Reed Arundo donax L., has been investigated. These fibers, which widely grow in Mediterranean areas, but that are diffused all around the world as well, have been extracted from the outer part of the plant stem. Then, in order to have an initial idea of their influence on the mechanical properties of concrete, some experimental bricks have been prepared, with the addition of different weight percentages of this vegetal fiber. To assess the mechanical properties of these bricks, compression and tensile tests on the whole block has been performed. Hence, the differences between concrete bricks without any fiber and those reinforced with different weight percentages of natural fiber have been analyzed, then assessing their potential applications in bio-architecture.

Cropping pattern simulation-optimization model for water use efficiency and economic return

Sustainable agricultural development is one of the most important tools for the economic growth of a country. Therefore, water and land use management is considered a priority. This research aimed to develop a framework to optimize crops’ spatial and temporal distribution in an irrigation district. The AquaCrop- OS (FAO) water productivity model was integrated with a nonlinear optimization model to maximize the annual net profitability and minimize the water consumption of three crops (rice, corn, and forage). It was applied at a regional level to 905 simulation sub-units in the Zulia irrigation district (Colombia), in three typical climatic years’ scenarios, and at a multi-period level (monthly). The results indicated that: i) crop simulation for the study area was applicable and feasible; ii) rice can be combined with forage and corn; iii) corn is a viable option under dry year conditions; iv) under a wet year, forage production is the best option. On average, in the dry year, profitability decreased by 14.5% compared to the normal year in half of the study area, and in some areas, economic losses of up to 53% were obtained. In the wet year, profitability remained at the same level as the normal year in 43.8% of the area. However, there were significant decreases in profitability in 23.1% of the district. In the normal year, the water demand of the crops in each simulated period allows savings of up to 50% of water compared to the current concession amount, which is 1000 mm. This study is useful for making decisions on sustainable resources management and optimal irrigation water and land use under different biophysical and economic conditions.

Effects of controlled burn rice husk ash on geotechnical properties of the soil

Pozzolanic reactions of RHA entirely depends on controlled burning condition. The current study illustrates the effects of controlled burn rice husk ash (RHA) on the geotechnical properties of A-2-4 type soil. The compactibility, bearing capacity, compressive strength, and shear strength were investigated as the important geotechnical properties on soil with 0%, 5%, 10%, and 15% of RHA admixtures. Considering the 7-day moist curing, standard Proctor compaction tests, California Bearing Ratio (CBR) tests, Unconfined Compressive Strength (UCS) tests, Consolidated-Drained (CD) Triaxial Compression tests, and Scanning Electron Microscopy (SEM) tests were conducted on soil-RHA combinations. The test results showed that the optimum moisture content increased, but MDD reduced with the increment of RHA content. Soil with 5% RHA showed the increase of CBR (39.5%), UCS (6.0%), modulus of deformation (56.3%), cohesion (11.8%), and angle of internal friction (6.3%) compared to control specimen which indicated that the application of burnt RHA at a controlled temperature significantly enhanced the geotechnical properties of soil. SEM image on soil with 5% RHA also observed the best microstructural development.

Image analysis of real-time classification of cherry fruit from colour features

An image analysis algorithm for the classification of cherries in real time by processing their digitalized colour images was developed, and tested. A set of five digitalized images of colour pattern, corresponding to five colour classes defined for commercial cherries, was characterized. The algorithm performs the segmentation of the cheery image by rejecting the pixels of the background and keeping the image features corresponding to the coloured area of the fruit. A histogram analysis was carried out for the RGB and HSV colour spaces, where the Red and Hue components showed differences between each of the specified colour patterns of the exporting reference system. This information led to the development of a hybrid Bayesian classification algorithm based on the components R and H. Its accuracy was tested with a set of cherry samples within the colour range of interest. The algorithm was implemented by means of a real time C++ code in Microsoft Visual Studio environment. When testing, the algorithm showed a 100% effectiveness in classifying a sample set of cherries into the five standardized cherry classes. The components of the hardware-software system for implementing the methodology are low cost, thus ensuring an affordable commercial deployment.

Technological innovation in the winery addressing oenology 4.0: Testing of an automated system for the alcoholic fermentation management

In recent years, the use of automated machine tools in the wine industry has increasingly gained ground to simplify and optimize winemaking, complying with Industry 4.0 requirements. This work aimed to analyse a system for the automatic management of yeast nutrition in alcoholic fermentation in terms of environmental, management, and economic performance in comparison with traditional fermentation management. The automated system is a transportable and easily installable place and start system, equipped with a control unit and rods for the dosage of nutrients, and it works with a memory unit in which fermentative kinetics curves are loaded. The curves are predefined or customized according to oenologists’ needs. Hence, fermentation time, manpower, nutrients, oxygen, water, and energy consumption were evaluated concerning the alcoholic fermentation process. The analysis was carried out considering two different Italian wineries with different working capacities. Furthermore, life cycle assessment methodology and variable costs analysis was performed. Overall, the automated system reveals to be a promising investment, especially if applied to wineries characterized by high-volume tanks, where scale factor played a crucial role. Nutrients used by the automated system are more expensive but more environmentally sustainable than traditional ones.

Comparing Sentinel-1, Sentinel-2, and Landsat-8 data in the early recognition of irrigated areas in central Italy

This study evaluated the effectiveness of various remote sensing (RS) data (Sentinel-1, Sentinel-2, and Landsat 8) in the early recognition of irrigated areas in a densely cultivated area of central Italy. The study was based on crop data collected on more than 2000 plots in 2016 and 2017, characterized by quite different climatic conditions. The different RS data sources were used both alone and combined and with precipitation to define corresponding random forest (RF) classifiers whose overall accuracy (OA) was assessed by gradually increasing the number of available features from the beginning of the irrigation season. All tested RF classifiers reach stable OAs (OA 0.9) after 7-8 weeks from the start of the irrigation season. The performance of the radar indexes slightly improves when used in combination with precipitation data, but three weeks of features are required to obtain OA above 80%. The optical indices alone (Sentinel-2 and Landsat 8) reach OA ≈85% in the first week of observation. However, they are ineffective in cloudy conditions or when rainfed and irrigated fields have similar vigour. The most effective and robust indices are those based on combined sources (radar, optical, and meteorological), allowing OAs of about 92% and 96% at the beginning and in the middle of the irrigation season, respectively.

Diagnostic method and device for evaluating and forecasting the technical condition of farm machinery in operation

The paper discusses methods and ways to diagnose the technical condition of agricultural machines and harvesters, existing practices, and approaches to get reliable data on the current health of the machinery used. The device for assessing and predicting machines’ technical condition includes software and technical means developed with virtual technologies to measure diagnostic parameters of the machinery. The main device elements are digital sensors with physical modifiers (pressure, temperature, medium composition and motion sensors, a-d converters with signal amplifiers), software to configure data gathering, and output to conduct analyses and produce recommendations. The core of the present approach is the technology of virtual prediction of breakdowns by changes in the technical condition parameters. It is based on modular devices, software with an interface that collects and processes data and provides a complete set of failure diagnostics and forecasting. The given method based on a device operating in the information and communication network increases farm machinery’s performance. Furthermore, it reduces operating costs due to the prevention of expensive breakdowns, individual forecasting, and scheduled maintenance of machines in operation. The approach under consideration was applied in the laboratory of digital engineering technologies of the Bashkir State Agrarian University Republic of Bashkortostan of the Russian Federation. The given work is aimed to boost the efficiency of the farm machinery diagnostics and maintenance system by applying a virtual breakdown prediction technology to conduct an automated evaluation, registration, and analysis of a machine’s condition. It can be achieved by developing software and technical means to register data and their structure systematization.

Long-term monitoring of deficit irrigation regimes on citrus orchards in Sicily

The study aims to identify the responses of citrus orchards (C. sinensis (L.) Osbeck), grown under typical Mediterranean climatic conditions, to deficit irrigation (DI) regimes applied over more than a decade (2010-2020). In particular, the DI regimes were declined at the study site in terms of sustained deficit irrigation, regulated deficit irrigation, partial drying of the root-zone, with increasing severity of the water deficit, from 25% to 50% of the crop evapotranspiration, using surface and sub-surface micro-irrigation techniques. Long-term monitoring was set up for identifying the main processes acting at the soil-plant-atmosphere continuum (SPAC) level through direct in situ measurements of mass and energy fluxes (i.e., via micrometeorological technique) and the estimation of ETc and transpiration fluxes (i.e., via sap flow method), and the soil-plant-water processes (via geoelectrical techniques). In addition, the main physiological, qualitative, and quantitative parameters were evaluated since the beginning of the experiment. The results of the long-term experiment demonstrated the great adaptability of the crop species to sustain even the highest water reductions without substantial alterations of the main marketable productive and qualitative characteristics, evidencing the importance of controlling the SPAC dynamics for correctly applying the water restriction regimes.

Assessing the effect of barns structures and environmental conditions in dairy cattle farms monitored in Northern Italy

Animal welfare is a fundamental pillar for livestock farming, and it can be endangered by a series of aspects, among which is the presence of undesired microclimates. This condition can be monitored by measuring the temperature-humidity index (THI), an index able to inform about the emergence of heat-stressing conditions in the barns. The THI can be influenced by the external environmental conditions and the barn structure, orientation, thermal buoyancy, and roof insulating materials. In order to evaluate these structural aspects of buildings and the consequent microclimate, in this study, a survey was carried out in 8 dairy cattle barns located in the northern part of Italy that were monitored continuously during thermoneutral, warm, and cold periods. Experts observed the structural aspects ,and the environmental parameters were measured with sensors. From the results emerged that the barns had structural characteristics that considerably affect the internal microclimate, with openings, roof height, forced ventilation, and building orientation playing a significant role in estimating of the THI in the barn. The more critical period was the warm one when the structures could not mitigate the external conditions, and THI exceeded the threshold of 72 for a big share of the period in all monitored farms (range between 50-80% of observations). In the best situation, the cooling systems were able to maintain the external conditions. The results confirm the importance of the barn design and of an appropriate ventilation to improve air exchanges.

Evaluation of ammonia emissions from filtration of digestate used for fertigation

Fertigation can be a suitable technique for utilizing digestate, minimizing nitrogen losses, and contributing to circularity within a farming system. For this purpose, digestate usually is first processed with a screw-press separator. However, further filtration is required to remove particles that could clog the nozzles of drip or sprinkling irrigation systems. Advanced filtration can be obtained using mechanical separation with screens having openings of 100- 300 μm. This operation can be another source of ammonia emission, but this aspect has not been adequately investigated. This study aimed to address this knowledge gap by evaluating the emissions from three different filtration systems for digestate. The study was conducted in three different farms located in Lombardy (Italy) using digestate to fertigate maize by drip irrigation (two farms) and pivot irrigation (one farm). Ammonia emissions were measured with passive samplers and the fluxes were examined using an inverse dispersion model implemented in Windtrax software. The emissions were measured both when the filtration systems were in operation and when they were switched off. Ammonia emissions (mean values between 375 and 876 μg NH3/m2/s) tended to increase during operation of the filtration systems. However, no significant differences were found in the emissions from active and inactive equipment on any of the farms. The emissions from the filtration systems were higher than from a storage tank (22-67 μg NH3/m2/s). However, the mean emissions amounted to only 0.3% of the nitrogen content of the digestate. These emissions can be considered irrelevant in the context of the whole management scheme for digestate. This work provides a first insight on ammonia emissions arising from advanced filtration of digestate, with specific reference to Po Valley farming systems. Further studies are required to improve knowledge about emissions from the entire digestate management process, including the treatments required for specific application techniques.