An optimization method for the reduction of fertilization errors with centrifugal applicators

This paper discusses an optimization method for the spreading performed by centrifugal spreaders in order to minimize adverse environmental effects owing to application errors. A cost functional relying on a conventional simplified spread pattern model is proposed. In order to take into account the mechanical limits of the device, constraints are introduced. An augmented Lagrangian algorithm is implemented to compute an approximate solution. Numerical experiments show that application errors can be significantly reduced for parallel tracks within a main field body

Insights about the Choice of Pig Manure Processing System in Three Italian Regions: Piemonte, Friuli Venezia Giulia, and Veneto

The adoption of best available technologies (BATs) by the livestock sector has a fundamental role in developing a sustainable agricultural system. Italy is the EU member with the highest percentage of manure treated, but processing facilities are regionally scattered and the adoption of BATs is far from being scaled-up. The adoption is a matter of multicriteria decision-making and full knowledge on how to foster the transition is still lacking. The present research aims to deepen the available knowledge by analysing the perception of 40 pig farm managers about decision criteria behind the adopted manure management system across three different Italian regions. We assessed farms in Piemonte, Friuli Venezia Giulia, and Veneto. All farms have adequate storage facilities, but 82.5% adopt no processing technique. The two most important decision criteria are economic, i.e., the minimization of treatment and spreading costs. The emerging picture allows us to conclude that BAT adoption is still adopted as a mere consequence of legal obligation. Economic constraints prevail as there is a lack of information and uncertainty. Clear perspectives and recognition of virtuous behavior prevent farmers from making decisions based on environmental or social criteria. Therefore, effective policies oriented to fill these gaps are needed to accelerate the transition towards sustainability

Agricultural aviation research

A compilation of papers, comments, and results is provided during a workshop session. The purpose of the workshop was to review and evaluate the current state of the art of agricultural aviation, to identify and rank potentially productive short and long range research and development areas, and to strengthen communications between research scientists and engineers involved in agricultural research. Approximately 71 individuals actively engaged in agricultural aviation research were invited to participate in the workshop. These were persons familiar with problems related to agricultural aviation and processing expertise which are of value for identifying and proposing beneficial research

Sustainable Production in Food and Agriculture Engineering

This book is a collection of original research and review papers that report on the state of the art and recent advancements in food and agriculture engineering, such as sustainable production and food technology. Encompassed within are applications in food and agriculture engineering, biosystem engineering, plant and animal production engineering, food and agricultural processing engineering, storing industry, economics and production management and agricultural farms management, agricultural machines and devices, and IT for agricultural engineering and ergonomics in agriculture

Using a GIS technology to plan an agroforestry sustainable system in Sardinia

This study was conducted with the aim to quantify the spread of livestock agroforestry in a Mediterranean ecosystem (island of Sardinia, Italy) and evaluate its sustainability in terms of grazing impact. By using GIS software ArcMap 10.2.2, the map of Sardinia vegetal landscape, obtained by information of Sardinia nature map based on the classification of habitat according to CORINE-Biotopes system, have been overplayed with the map of livestock grazing impact map CAIA developed by INTREGA (spin-off ENEA), to obtain for Meriagos (local agro-silvo-pastoral systems; classified “Dehesa 84.6” according to CORINE-Biotopes system), bushlands and woodlands, the surfaces under grazing and evaluate the extension of overgrazing for each of them

Statistical Geocomputing: Spatial Outlier Detection in Precision Agriculture

The collection of crop yield data has become much easier with the introduction of technologies such as the Global Positioning System (GPS), ground-based yield sensors, and Geographic Information Systems (GIS). This explosive growth and widespread use of spatial data has challenged the ability to derive useful spatial knowledge. In addition, outlier detection as one important pre-processing step remains a challenge because the technique and the definition of spatial neighbourhood remain non-trivial, and the quantitative assessments of false positives, false negatives, and the concept of region outlier remain unexplored. The overall aim of this study is to evaluate different spatial outlier detection techniques in terms of their accuracy and computational efficiency, and examine the performance of these outlier removal techniques in a site-specific management context. In a simulation study, unconditional sequential Gaussian simulation is performed to generate crop yield as the response variable along with two explanatory variables. Point and region spatial outliers are added to the simulated datasets by randomly selecting observations and adding or subtracting a Gaussian error term. With simulated data which contains known spatial outliers in advance, the assessment of spatial outlier techniques can be conducted as a binary classification exercise, treating each spatial outlier detection technique as a classifier. Algorithm performance is evaluated with the area and partial area under the ROC curve up to different true positive and false positive rates. Outlier effects in on-farm research are assessed in terms of the influence of each spatial outlier technique on coefficient estimates from a spatial regression model that accounts for autocorrelation. Results indicate that for point outliers, spatial outlier techniques that account for spatial autocorrelation tend to be better than standard spatial outlier techniques in terms of higher sensitivity, lower false positive detection rate, and consistency in performance. They are also more resistant to changes in the neighbourhood definition. In terms of region outliers, standard techniques tend to be better than spatial autocorrelation techniques in all performance aspects because they are less affected by masking and swamping effects. In particular, one spatial autocorrelation technique, Averaged Difference, is superior to all other techniques in terms of both point and region outlier scenario because of its ability to incorporate spatial autocorrelation while at the same time, revealing the variation between nearest neighbours. In terms of decision-making, all algorithms led to slightly different coefficient estimates, and therefore, may result in distinct decisions for site-specific management. The results outlined here will allow an improved removal of crop yield data points that are potentially problematic. What has been determined here is the recommendation of using Averaged Difference algorithm for cleaning spatial outliers in yield dataset. Identifying the optimal nearest neighbour parameter for the neighbourhood aggregation function is still non-trivial. The recommendation is to specify a large number of nearest neighbours, large enough to capture the region size. Lastly, the unbiased coefficient estimates obtained with Average Difference suggest it is the better method for pre-processing spatial outliers in crop yield data, which underlines its suitability for detecting spatial outlier in the context of on-farm research

Determination of Time Dependent Stress Distribution on Potato Tubers at Mechanical Collision

This study focuses on determining internal stress progression and the realistic representation of time dependent deformation behaviour of potato tubers under a sample mechanical collision case. A reverse engineering approach, physical material tests and finite element method (FEM)-based explicit dynamics simulations were utilised to investigate the collision based deformation characteristics of the potato tubers. Useful numerical data and deformation visuals were obtained from the simulation results. The numerical results are presented in a format that can be used for the determination of bruise susceptibility magnitude on solid-like agricultural products. The modulus of elasticity was calculated from experimental data as 3.12 [MPa] and simulation results showed that the maximum equivalent stress was 1.40 [MPa] and 3.13 [MPa] on the impacting and impacted tubers respectively. These stress values indicate that bruising is likely on the tubers. This study contributes to further research on the usage of numerical-methods-based nonlinear explicit dynamics simulation techniques in complicated deformation and bruising investigations and industrial applications related to solid-like agricultural products

NASA and general aviation

General aviation remains the single most misunderstood sector of aeronautics in the United States. A detailed look at how general aviation functions and how NASA helps keep it on the cutting edge of technology in airfoils, airframes, commuter travel, environmental concerns, engines, propellers, air traffic control, agricultural development, electronics, and safety is given

Actions for Bioenergy and Biofuels: A Sustainable Shift

The topic of bioenergy is a multidisciplinary one, where the use of resources and skills can be optimized for the development of sustainable models. It is a time for green strategies, but also for action. It is, therefore, necessary to implement projects that address virtuous examples of the circular bioeconomy. All politicians are called on to contribute, because this global goal can only be achieved if a contribution is made by all countries