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Summary This work aims to develop an automatic system capable of providing objective information about the bloom charge in an apple orchard in order to manage flower-thinning activities. The article presents and discusses the use of a mobile lab (ByeLab) equipped with several optical sensors to carry out a site-specific bloom charge assessment in apple trees. The data collected by the sensors were processed by a specific algorithm implemented in MatLab®. Investigations of the flower reflectance signature indicated that the Normalized Difference Vegetation Index (NDVI) is the most suitable parameter to distinguish leaves from flowers. Pure flowers produce NDVI values slightly negative or at least very near to 0. Despite the homogeneous behavior of the NDVI flower response, OptRx™ sensors, which provide an average assessment of an area, were not able to highlight a significant correlation between the number of flowers and the NDVI values. In the future, further studies will be conducted to assess if other techniques based on image analyses can provide better and more sensitive results regarding the bloom charge assessment. Such results could then be used as a reference in automating machines for thinning operations according to a site-specific approach.

Summary The aim of WEQUAL project (WEb service centre for QUALity multidimensional design and tele-operated monitoring of Green Infrastructures) is the development of a system that is able to support a quick environmental monitoring of riparian areas subjected to the realization of new green infrastructures (GI). The Wequal’s idea is to organize a service center able to manage both the Web Platform and the whole data collection and analysis processes. Through a personal account, the final user (designer, technician, researcher) can get access to the service and requires the evaluation of alternatives GI projects. On the Web Platform, a set of algorithms runs in order to calculate, through automatic procedures, all the ecological criteria required to evaluate a quality environmental index that describes the eco-morphological value of the monitored riparian areas. For this aim, the WEQUI index was developed, which uses 15 indicators that are easy to monitor. In this paper, the approach for environmental data collection and the procedures to perform the automatic assessment of two of the ecological criteria are described. For the computation, the implemented algorithms use data including the vegetation indexes, Digital Terrain Model (DTM), Digital Surface Model (DSM) and a 3D point cloud classification. All the raw data are collected by UAVs (Unmanned Aircraft Vehicle) equipped with a 3D Lidar, multispectral camera and RGB camera. Interpreting all the raw data collected by these sensors, using a multi-attribute approach, the WEQUI index is assessed. The computed ecological index is then used to assess the riparian environmental quality at ex-ante and ex-post river stabilization works. This index, integrated with additional not-technical or not-ecological indicators such as investment required, maintenance costs or social acceptance, can be used in multicriteria analyses in order to evaluate the intervention from a wider point of view. The platform is expected to be attractive for GI designers and policy makers by providing a shared environment, which is able to integrate the method of detection and evaluation of complex indexes and a multidimensional evaluation supported by an expert guide.

This work presents a new survey system for the assessment of diseases and missing plant in vineyards. The data analysis is based on LiDAR and NDVI data classification, collected by sensors mounted on a tracked all-terrain vehicle. After this classification, a thematic map representing the vegetative status of the whole row is accomplished. The first results obtained from preliminary tests, carried out on portions of row (transepts), are shown in this work.

The aim of the project in which this work was conceived is the design of a climbing robot for pruning spruce trees without damaging the bark. According to the requirements and pruning methods for avoiding the flaws of the finished timber, guidelines and constraints for the mechatronic design of a new climbing robot for spruce-pruning activities were deduced. A 3-wheeled-driven system able to cope with the tree bark thanks to compression springs is chosen for the first functional design; a force-balance analysis is performed for understanding the climbing and equilibrium requirements also considering the additional weight of a pruning system installed on a cart moving on a guide placed on the robot main structure. The quasi-static model, the mechanical design and the related electronic and driver systems are here presented. The preliminary scaled mechatronic prototype is experimentally evaluated on poles with diameters in the range of the young spruces, i.e. 100–200 mm, in its main climbing features. These results will serve as basis for the further development of the system .

Viticulture is one of the most important productive sectors of agriculture. The vineyards can be subject to a large production of losses, mainly due to vegetative stress or diseases. Esca disease (ED) is one of the most widespread diseases in the vineyards and it is difficult to be predicted. The main symptoms appear at level of wood and leave starting to the end of showing yellow spots which turn to red—brown before their complete drying. This research aims to develop and validate a fast and reliable system able to recognize diseased plants in the vineyard through remote sensing applications. This experiment was carried out in a vineyard in the North–West of Italy on rows of V. vinifera plants cv. Dolcetto and Barbera using a multirotor-UAV (Unmanned Aerial Vehicle) equipped with a multispectral camera. A ground survey was performed in order to assess the plant’s health status and georeference their position. During the field test, the UAV flew at three different flying altitude: 30–50–70 m. The collected images were elaborated using Pix4Dmapper software in order to: (i) extract the vineyard rows, (ii) identify their surface covered by a plant, and (ii) calculate a NDVI map for each plant.

A remarkable area of the cultivable land in South Tyrol has an inclination above 30%, which precludes the use of conventional machines for its cultivation. The project “Brotweg” is facing this problem by developing technologies for grain cultivation in a steep mountain environment up to an inclination of 70%. Furthermore, a technical solution for the whole grain processing after harvesting up to the production of bread is evolved. With the help of an entire facility the grain processing can be performed directly at the farm, which allows the farmer to act more independent while increasing his profitability. The aim of this project is to offer farmers an alternative or a supplement to livestock and dairy farming. It will improve and facilitate the working condition for farmers. To reach these goals many issues must be solved: (a) Mechanical solutions for grain seeding and harvesting in steep slopes must be developed. One of the main challenges thereby is to prevent erosion. (b) A solution for grain processing and conservation on the farm must be found. The existing structures of a farm are limiting the size of the facility. (c) The grain is processed to bread directly on the farm and distributed in a further step. The whole processing path must satisfy all safety restrictions, environmental terms and consider all possible geological problems of a steep mountain slope. We present the implementation of a grain processing facility in an existing farm structure and the development of the seeding and harvesting machines for steep slopes.

This paper describes the approach followed to perform an automatic load monitoring during yarding activities. The goal of this methodology is the weight assessment of the loaded biomass during the inhaul phase in cable logging operations. The approach is based on the development of dedicated mathematical models that assessing the skyline deflection, tension, and slope permit to estimate the hauled load through an indirect approach. To carry out this experience an in-scale standing skyline system with single-span was set-up. The experiment was conducted at 0%, 10% and 20% of slope, respectively, and the skyline deflection was measured during travels with 0, 5, 10, 20, 30 and 40 kg of fully suspend loads. Besides these, the assessment was performed at mounting tensions of 10 and 100 kg. According to the different estimative models and the operative context, the collected results showed a difference between the estimated load and the reference one lower than 20% in terms of mass. In conclusion is possible to affirm that the proposed approach can be a suitable compromise for the indirect estimation of timber during fully suspended yarding operations.

Remote Sensing tools in Precision Viticulture to detect disease levels of plants implies big data-sets and time-consuming analysis of data. In this study, we used remote images collected by an Unmanned Aerial Vehicle equipped with a Micasense RedEdge.MXTM multispectral camera and a Terrestrial Laser Scanner (TLS). These tools gave us large amounts of data in a short period. The aim of this research was to develop a methodology that shortens the post-processing phase of data. The data sets were taken from a vineyard during two crop monitoring surveys in June and August 2018. The monitored vineyard is situated in the Piedmont region (Italy). As a first step in the data analysis procedures, we used photogrammetry approaches, as well as the Digital Terrestrial Model and the Digital Surface Model to detect the shape of single plants. The achieved results were then validated with the analysis obtained through the TLS. We then analyzed the reflectance of the canopy using open source software, to detect changes in the pixels about the reflectance curve between healthy plants and plants with disease. We expect that the proposed methodology will help us to be time-efficient and to detect condition of vegetative changes.

Cable logging is a common harvesting technique for steep slope conditions, despite the safety hazard for the operators, which is mainly related to failure of cables or anchor trees. The multiple fa...

This paper describes the theoretical approach followed to perform an indirect load mass assessment during yarding activities. The goal of this methodology is the mass assessment of the loaded biomass during the inhaul phase in cable logging operations.The theoretical approach proposed is based on the development and the use of mathematical model which, thanks to the measurement of the skyline deflection, slope and tensions permit to estimate the hauled mass. Indeed, as reported in literature, these parameters, together with the mass of the load, are strongly related each other. For this experiment an in-scale yarding line has been developed in order to control and monitor all these parameters. The precision and accuracy of the obtained results related to the mass estimations have been then compared with similar results obtained through manual surveys using tools commonly used by the forestry community.In conclusion the proposed methodology has shown to be reliable for an indirect mass assessment of loads during yarding operations. Indeed, if the line is adequately installed this monitoring system ensures better accuracy if compared with the common tools employed for timber assessment.

The authors describe a study conducted under controlled conditions, with the goal of analysing the dynamic tension in the skyline of a yarder resulting from hauling known loads. The rigging was a classic three-cable configuration common to European yarder operations; with a single-span standing skyline and the mainline and haulback used to move the carriage back and forth along the span. Two carriage types were used to gauge tension differences between clamped (Hochleitner BW4000) and unclamped (SEIK Skybull 30/60) carriages. Tension was recorded at 0.5-s intervals through a measuring device with a nominal measuring range of 200 kN. Results showed that: (1) The recommended safe working load (safety factor = 3) was often exceeded by peak loads during lateral skidding and inhaul; (2) the endurance limit of the skyline was never reached; and (3) the Skyline XL software used for payload calculation grossly overestimated payload potential. Since study conditions could be considered representative of some commercial yarding operations in the European Alps, this finding suggests that local loggers may operate within safe limits considering the engineering properties of wire rope, while formally exceeding legal requirements.

The present study aims to quantify the main biomass resources in South Tyrol (Northern Italy) and estimate the potential contribution for the energy sector. Moreover, four representative feedstocks have been tested in a domestic pellet boiler under standard conditions in order to assess its performance and pollutant emissions. The unexploited biomass potential for energy conversion applications, expressed as dry weight, has been estimated to be 135 000 t y −1 from forest, 14 950 t y −1 for apple pruning residues and 12 000 t y −1 from the industrial sector. The scenario of utilizing the unexploited local biomass resources – in energy systems such as the ones deployed in South Tyrol – would contribute with an annual bioenergy production contribution of 130–270 TJ of electricity and 1700–2100 TJ of heat. Finally, the tested feedstocks can be used in domestic boilers, however, some modifications are required when using agricultural residues.

Summary An innovative approach for the automation of operational monitoring activities in agricultural and forestry tasks is described and discussed in this article. This approach can be considered as a solution for Precision Agriculture and Precision Forestry applications and can be used as an information and communication technology (ICT) tool for the management aims by a variety of agricultural and forestry companies. The aim of the proposed concept is to develop a system, composed of both hardware and software units, with the ability to collect and manage operative raw data and then to translate them into operational information that will be used in decision-making processes. All the procedures will be carried out automatically, in order to ensure an objective compilation of the field activity register. Thus, the entrepreneur will have all the operative information automatically updated in a dedicated database system. All the obtained documents can then be used for certification and traceability processes, if required by the procedural guideline, as well as to satisfy any other management tasks, including the estimation of the actual operative costs of the farm.

Each application of Precision Agriculture or Forestry should be supported by a technological platform able to perform, in an integrated way, the following data-information cycle functions: 1) data collection; 2) data processing; 3) data analysis and evaluation; 4) use of information. In accordance to this view, information are data that are usefully used in a decision making process or within a reporting protocol destined to users external to the enterprise (certification tasks). In order to manage the platform in a complete and efficient manner an adequate information system is needed. Firstly, the paper shows a classification of the possible monitoring solutions based on the different enterprise typologies, highlighting the main technological and interpretative requirements. Secondly, some case studies related to the application of operational monitoring in orchards and forestry are introduced, mainly focusing on some peculiar aspects of the algorithms developed for the implementation of the inference engines.

After a comparative evaluation around the concepts of Industry 4.0, Precision Agriculture and Smart Farming, the paper discusses the necessity of identifying solutions able to apply the methods of the so-called Knowledge Management 4.0 in the agri-environmental enterprises. To this aim, an ontology based on a conceptual map derived from the data-to-information transformation is here proposed to support the design of a new generation of Farm Information Systems (FIS) able to fit the production needs of agri-environmental enterprises. The data-to-information cycle is split into four phases: A) Data collection, B) Data processing, C) Data analysis and evaluation, and D) Use of information. Phases A and D comprise tools of “light digitization” typically referring to OLTP components (On Line Transactional Processes). On their turn, phases B and C are typically formed by “heavy digitization” components (On Line Analytical Processes), generally more complicated to be managed by the farmers directly. The conceptual map defined by the ontology is firstly useful to plan the composition of the FIS according to a modular approach, possibly following a strategy that starts to consider the introduction of OLTP components, for then evolving gradually towards more articulated solutions that include also OLAP component and related functions. In this way, decision makers can manage practical planning instrument able to show clearly the level of complexity a FIS can reach, thus evaluating its sustainability with respect to the financial, cultural and professional resources available at the farm. Finally, after having underlined the opportunities offered by Cloud Computing and widespread connectivity, that provide an easier adoption of OLAP tools, some application cases are presented and discussed.

The paper presents and discusses the use of a mobile lab (ByeLab) equipped with optical sensors (OptRx™ and LiDAR), GNSS- RTK system and an Inertial Measurement Unit (IMU), to carry out a site-specific bloom charge assessment in apple trees. The collected data are firstly synchronized by a LabView software and then processed by dedicated algorithms in MatLab®. Preliminary investigations were performed in order to evaluate the features of the flower and leaves reflectance signature. It was observed that low NDVI values corresponded to the flowers while higher values to the leaves. It was expected that NDVI show a negative correlation with the bloom charge. Using Terrestrial Laser Scanner it was possible to validate the information about the canopy thickness collected by the LiDARs mounted on the ByeLab. The OptRx™ do not seem suitable to be applied to perform an estimation of the flower charge but, merging the data collected by the two types of sensors it is possible to build descriptive maps, which provide information about canopy thickness and vegetation index values. These can be used as reference for automating machines to be applied in thinning operations according to a site-specific approach.

A new tractor prototype suitable to be used in extreme slope conditions of hilly and mountain areas is here proposed and described. It was primarily designed to address the problem of working in vineyards trained with the so-called “ pergola ” system, that has a long tradition in South Tyrol and it is still very common in the mountain sides of this Province, being the most suitable training system required by the typical vine varieties here cultivated ( Lagrein and “ uva schiava ”). “ Pergola ” is even well suited to the terrains cultivated through terracing methods, that permit to extend farming practices until 130% of slopes. Anyhow, its use involves many mechanization problems mainly due to need to face with limited transit widths and heights (

The authors describe a study conducted under controlled conditions, with the goal of determining the eventual benefits of replacing the conventional clamped carriage with an unclamped motorized dropline carriage. The rigging was a classic three-cable configuration common to European yarder operations, with a single span standing skyline. The mainline and haulback line were used to move the carriage back and forth along the span. Two carriage types were used to gauge productivity and extraction cost differences between clamped (Hochleitner BW4000) and unclamped motorized dropline (SEIK Skybull 30/60) carriages. The authors conducted a classic time study, recoding work time, delay time and load size individually for 83 cycles. Replacing the standard clamped carriage with the unclamped motorized dropline carriage resulted in a productivity increase equal or larger than 30%. Extraction and processing cost decreased between 10% and 17%, depending on extraction distance. These results are valid for the specific set-up considered with the study, and may not be generalized without repeating the experiment under more varied conditions: however, they are very encouraging and may justify further investigations aimed at determining the effect of carriage type on fuel consumption and machine wear.

At today, available mechatronics technology allows exploiting smart and precise sensors as well as embedded and effective mechatronic systems for developing (semi-)autonomous robotic platforms able to both navigate in different outdoor environments and implementing Precision Farming techniques. In this work, the experimental outdoor assessment of the performance of a mobile robotic lab, the ByeLab — Bionic eYe Laboratory — is presented and discussed. The ByeLab, developed at the Faculty of Science and Technology of the Free University of Bolzano (I), has been conceived with the aim of creating a (semi-)autonomous robotic system able to sense and monitor the health status of orchards and vineyards. For assessing and measuring the shape and the volume of the canopy, LIDAR technology coupled with ad-hoc developed algorithms have been exploited. To validate the ByeLab different experimental tests have been carried out. In addition to the in-lab and structured environments experimental tests that allowed to tune the algorithms, in this work the assessment of its capabilities — in particular the sensoric system — has been made outdoor controlled environment tests.

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.

The first results of a new approach for implementing operational monitoring tool to control the performance of forest mechanisation chains are proposed and discussed. The solution is based on Global Navigation Satellite System (GNSS) tools that are the core of a datalogging system that, in combination with a specific inference-engine, is able to analyse process times, work distances, forward speeds, vehicle tracking and number of working cycles in forest operations. As a consequence the operational monitoring control methods could provide an evaluation of the efficiency of the investigated forest operations. The study has monitored the performance of a tower yarder with crane and processor-head, during logging operations. The field surveys consisted on the installation of the GNSS device directly on the forest equipment for monitoring its movements. Simultaneously the field survey considered the integration of the GNSS information with a time study of work elements based on the continuous time methods supported by a time study board. Additionally, where possible, the onboard computer of the forest machine was also used in order to obtain additional information to be integrated to the GNSS data and the time study. All the recorded GNSS data integrated with the work elements study were thus post-processed through GIS analysis. The preliminary overview about the application of this approach on harvesting operations has permitted to assess a good feasibility of the use of GNSS in the relief of operative times in high mechanised forest chains. Results showed an easy and complete identification of the different operative cycles and elementary operations phases, with a maximum difference between the two methodologies of 10.32%. The use of GNSS installed on forest equipment, integrated with the inferenceengine and also with an interface for data communication or data storage, will permit an automatic or semi-automatic operational monitoring, improving the quantity of data and reducing the engagement of the surveyor.