Fabrizio Mazzetto

MEACROS: a tool for multi-criteria evaluation of alternative cropping systems

A procedure aimed at identifying cropping systems suitable for environmentally sensitive areas has been developed within the framework of a coordinated Italian project. It has been implemented as a DSS software named Multi-criteria Evaluation of Alternative CRopping Systems (MEACROS) which makes it possible for decision-makers to compare different scenarios based on alternative cropping systems. A set of default technical—agronomic, economic, and environmental criteria have been included in MEACROS to allow for the different impacts induced by each scenario. Users can select between the proposed set of criteria and/or in-putting new ones. The software performs concordance analysis, providing preference rankings for the alternatives, based on computed indices and allowing a good sensitivity analysis of weighted values as well as displaying the results in graphic form. Indicative results are presented here in a case study concerning a farm in a flat, sensitive area in Northern Italy.

A PC model for selecting multicropping farm machinery systems

Abstract A model, Computed Farm Machinery System (ComFARMS), has been developed to analyse mechanisation problems of Italian arable farms (

Evaluation of a LiDAR-based 3D-stereoscopic vision system for crop-monitoring applications

Abstract When dealing with unmanned agricultural vehicles (remotely-controlled vehicles, robots), vision systems are a key-factor for implementing field-solutions having direct interactions with crops. Among all the possible information given by a vision system, the punctual estimation of the canopy volume is surely an interesting parameter: it is related to the crop vegetative status and, hence, it is fundamental for performing and setting-up properly some important field-operations (e.g., pruning/thinning, spraying). A system able to recognize the canopy volume can provide either the input-signals for implementing a robotic real-time site-specific farming system or relevant information for a proper crop management. However, there are many practical difficulties in the field implementation of such a system: complex canopy shapes, different colours, textures and illumination conditions with projected shadows. Terrestrial/aerial vision systems working on visible-light wavelengths and/or 2D-images of crops, although capable of excellent performances, have a computationally-heavy post-processing; therefore, they are unsuitable for implementing low-cost real-time servo-actuated cropping systems (e.g., robotised sprayers). Instead, a vision system composed by two LiDAR sensors aligned vertically, scanning the same targets, could give a sort of stereoscopic vision, here named “ lateral-linear-stereoscopic vision ”. The aim of this study is assessing the opportunity to use such a system on an automatic or autonomous/robotised implement by performing some preliminary tests in a controlled environment. The resulting system is independent of the lighting conditions (it works also in the dark), is highly reliable (no projected shadows) and data processing is very fast. Although further studies are required to overcome the issues that could arise in a future field implementation, this system has all the premises to be successfully embedded in an automatized monitoring system.

Development of a Dynamic Stability Simulator for Articulated and Conventionaltractors Useful for Real-Time Safety Devices

The safety of agricultural tractors drivers is a very actual topic, especially when tractors operate on side slopes, such as in terraced vineyards. This work approaches the stability problem of articulated tractors by modelling, simulating and quantifying the safety of the driver with respect to both roll and pitch overturns. First of all, an articulated tractor has been modelled and simplified, after that a stability index has been defined and calculatedin several simulated slope conditions when the tractor travels along a circular trajectory; then, the obtained results have beencompared with respect to a conventional tractor. This work is a preliminary studyfor a tilting test platform for real vehicles, capable to reproduce real field conditions (slope, obstacles, roughness). Finally, some directives on how exploiting the obtained results for real-time safety devices have been formulated.

Repair and Maintenance Costs of 4WD Tractors in Northern Italy

Abstract. Purchasing and maintaining tractors along with other machines are two of the most considerable costs for the agricultural sector, which includes farm equipment manufacturers, farm contractors, and farmers. Repair and maintenance costs (R&M costs) typically account for 10% to 15% of the total costs related to agricultural equipment and tend to increase with equipment age. Hence, an important decision in farm management is the optimal time for equipment replacement. Classical R&M cost estimation models, calculated as a function of accumulated working hours, have been primarily developed for U.S. operating conditions. However, R&M costs are strongly influenced by farming practices, operating conditions, crop and soil type, and climatic conditions, which can be specific for individual countries. In this study, R&M cost model parameters were recalculated for the current Italian situation. A complete dataset related to the R&M costs of 100 4WD tractors in northern Italy, including 43 tractors owned by farmers and 57 tractors owned by contractors, was collected. Based on these data, the classical R&M cost estimation model was refined with the purpose of assisting manufacturers in commercial assessment of the domestic market and supporting Italian farmers in their decisions about purchasing new tractors. The main model result indicated that the R&M cost incidence on the price of Italian tractors at 12,000 working hours (the estimated life of local tractors) was 48.6%, compared to a value of 43.2% obtained with the original model formulated for U.S. operating conditions. Further, R&M costs were higher for tractors owned by farmers compared to tractors owned by contractors, at 55.4% of the list price at 12,000 working hours compared to 45.7%.

Design, implementation and validation of a stability model for articulated autonomous robotic systems

The use of robots in agriculture and forestry is rapidly growing thanks to the progress in sensors, controllers and mechatronics devices. Especially in hilly and mountainous terrains, the development of (semi-)autonomous systems that could travel safely on uneven terrain and perform many operations is an open field of investigation. One of the most promising mobile robot architectures is the articulated 4-wheeled system that shows an optimal steering capacity, and the possibility to adapt to uneven terrains thanks to a central passive degree of freedom. In this paper, the kinematic and (quasi-)static model for evaluating the phase I instability presented in Baker and Guzzomi(2013) has been firstly extended to allow to threat a generic articulated robotic system and to forecast the instability conditions. Then, the model and the stability conditions have been implemented in a Matlabźźsimulator and validated by means of an experimental emulator. Finally, a first prototype for a mechatronic anti-overturning device is discussed. The articulated 4-wheeled system can be suitable in hilly and mountain terrains.A kinematic and (quasi-)static model for the articulated robotic platform is presented.The predicted phase I and II instabilities have been experimentally validated.A cheap mechatronic anti-overturning prototype is designed.

Design and First Tests of a Vision System on a Tele-operated Vehicle for Monitoring the Canopy Vigour Status in Orchards

A vision system able to give a punctual estimation of the canopy vigour (volume, leaves’ chlorophyll content) of an orchard is a key-system for implementing Precision Agriculture. Indeed, such a system, composed by Lidar and NDVI sensors, can give all the information necessary for performing some important field-operations (e.g., pruning, spraying) and, above all, for setting-up automatically and in real-time the relative machines. The first issues when implementing a vision system concern: which type and how many sensors using, how making this system move within an orchard. As proved in some preliminary lab trials, the use of two Lidar sensors, vertically-aligned to give a sort of lateral-linear-stereoscopic vision, manages to avoid the presence of the large “projected shadows” (or “blind spots”) originating when using a single sensor to scan a target. Then, this article presents a compact “mobile lab”, based on an electric tracked bins-carrier, able to move off-road within the orchards and equipped with an ad-hoc developed adjustable tubular frame, designed to carry two Lidar sensors in the individuated configuration, together with other six (NDVI) sensors. This frame allows placing the sensors at different heights to ensure the complete scan of the canopy (even with high fruit trees).

A tracked mobile robotic lab for monitoring the plants volume and health

Precision agriculture has been increasingly recognized for its potential ability to improve agricultural productivity, reduce production cost, and minimize damage to the environment. In this work, the current stage of our research in developing a mobile platform equipped with different sensors for orchard monitoring and sensing is presented. In particular, the mobile platform is conceived to monitor and assess both the geometric and volumetric conditions as well as the health state of the canopy. To do so, different sensors have been integrated and effective data-processing algorithms implemented for a reliable crop monitoring. Experimental tests have been performed allowing to obtain both a precise volume reconstruction of several plants and an NDVI mapping suitable for vegetation state evaluations.

Development and Preliminary Tests of a Crop Monitoring Mobile Lab Based on a Combined use of Optical Sensors

Background: Technology is constantly evolving with respect to production agriculture. Precision farming technologies have been increasingly recognized for their potential ability for improving agricultural productivity, reducing production cost, and minimizing damage to the environment. Methods: The combined use of different sensors and the following analysis of the recorded data allowed to define an efficient technique for crop monitoring. Results: We obtained the volume reconstruction of several plants and the NDVI mapping by exploiting the proposed technique. Conclusion: Crop monitoring and yield forecasting play a major role in the agricultural context. Future work will be devoted to develop and use a customized index structure to increase the efficiency and to integrate in our knowledge base some geo referential data.

Mission Planning for the Estimation of the Field Coverage of Unmanned Aerial Systems in Monitoring Mission in Precision Farming

In the recent years, Unmanned Aerial Systems (UAS) have been largely employed in civil applications, such as aerial photography and topographic mapping, environmental monitoring, search and rescue, prevent of fires and disasters, environmental research and general photography and videos. Nevertheless, according to (AUVSI, 2013), agriculture is the main application where UAS will be employed in the near future. Small Unmanned Aerial Vehicles (UAVs) are flexible, easy to use and relative low-cost; thus, they can be employed in monitoring activities in precision farming, ensuring a prompt reaction to plant disease, lack of plants nutrients and environmental changes that are the main focus for farm efficiency and productivity. Recent development in high-resolution remote sensing and image processing technology has yield to small- size sensors compatible with small UAV payload weight. Each kind of sensor needs a certain flight pattern over the fields. However, a Remotely Piloted Aircraft Systems (RPAS) used for specialized operations or experimental activities has to be compliant with National Civil Aviation Authority regulations. On 2015, the Italian Aviation Authority (ENAC) published the second edition of the regulatory issue for this kind of aircrafts. The aim of this paper is the management analysis of RPAS for their use in survey missions for precision faming, taking into account the Italian regulatory prescription and two different kind of commercial sensors. UAVs are considered similarly to any other farm machine, describing the operative workflow and analysing the elementary time procedures associated to the different ways of planning a flight mission of the UAS on the field to be monitored. Actual rates of works, Effective Field Capacity (EFC) and Field Efficiency (FE), field coverage and survey cost are finally provided. The analysis includes also in-field pre-flight calibration procedures.