General Info

Learning objectives

Knowledge and understanding
Students will gain a solid understanding of the fundamentals of programming in Python and the basics of mechatronics and the Internet of Things (IoT). They will be able to understand and explain the theoretical principles governing the integration of mechanical, electronic and software components for applications in agriculture and beyond.

Applying knowledge and understanding
Students will be able to apply their acquired skills in Python programming to develop practical mechatronics projects using Raspberry Pi. They will be able to design, implement and test digital solutions that combine sensors, actuators and communication modules, with a focus on agricultural applications.

Making judgements
Students will develop the ability to critically analyze proposed solutions to specific digital engineering problems applied to agriculture. They will be able to evaluate the effectiveness of their mechatronic and IoT solutions by considering various technical factors and make autonomous decisions regarding the most appropriate implementations.

Communication skills
Students will be able to effectively communicate the results of their projects, both orally and in writing, using appropriate technical language. They will be able to document and present their work clearly and coherently, making the technological solutions adopted and the results obtained understandable even to non-specialists.

Learning skills
Students will develop the ability to independently learn new techniques and tools in programming, mechatronics and IoT. They will be able to continuously update themselves, successfully tackling new technological and application challenges, thanks to a solid methodological and practical foundation.

Learning objectives

The aim of the course is to provide the basis for learning how to assess and monitor pest (entomology module) and pathogen (pathology module) risks using advanced techniques, including monitoring and forecasting systems, and innovative diagnostic tools. At the end of the course, students will be able to develop innovative and sustainable pest management strategies, integrating biological, chemical and cultural techniques. They will acquire skills in the use of advanced technologies to improve the effectiveness and efficiency of plant health practices and develop communication skills to effectively transfer knowledge and innovations in plant health to different stakeholders, including farmers, technicians and land managers.

Knowledge and understanding
Demonstrate a thorough knowledge of the theories and principles governing plant health issues and the innovative solutions available to manage them.

Applying knowledge and understanding
Apply theoretical and methodological knowledge to the diagnosis and management of concrete phytosanitary problems, using advanced technological tools.

Making judgements
Make autonomous and critical judgements regarding different options for the management of plant health problems, taking into account practical, economic and environmental implications.

Communication skills
Use the correct technical-scientific terminology when describing course topics. Ability to synthesize and communicate effectively to specialists and non-specialists.

Learning skills
Demonstrate the ability to learn independently and continuously, keeping abreast of the latest innovations and developments in the field of pest management.

Learning objectives

The learning objectives of teaching Digital Applications in foothill arboriculture are to provide the student with the ability to use digital tools and technologies for monitoring analysis and management of fruit tree systems and for the application of precision agronomic techniques in the field with regard to fruit trees from the foothill environment.
The course also intends to provide students with the ability to identify the most appropriate level of digitization applicable to the different types of orchard farms, together with an in-depth exploration of the different plant shapes used in fruit tree systems, with the aim of calibrating the applications of fruit farming 4.0 to the type of planting and plant shapes used in the orchard. The objectives described above are also pursued through the exploration of appropriate case studies.

Knowledge and understanding skills
The teaching aims to develop students' knowledge and understanding skills, such as:
• knowing and understanding what technologies are useful in monitoring tree systems for precision agronomic applications such as remote sensing and digital soil mapping to quantitatively estimate variables of agronomic interest in vegetation and soil;
• know and understand the digital techniques and technologies that can be used to analyze the spatial and temporal variability of the orchard;
• to know and understand the development and application of precision agronomic techniques and decision support systems for plant fruit systems.

Applied knowledge and understanding
The teaching will enable the application of knowledge and understanding, allowing the student to:
• know and use the main multispectral satellite systems suitable for precision agriculture through the use of cloud-based platforms for analyzing the temporal and spatial variability of fruit-growing plots;
• know and use techniques for estimating vegetation and soil biophysical variables from satellite data and through the use of proximal sensing for monitoring fruit crops;
• to know the techniques and technologies available for digital applications in the management of cultivation operations in the orchard, also exploring the opportunities for using drones and agribots for the automatic execution of cultivation operations.

Autonomy of judgement
Teaching will allow the development of autonomy of judgement at various levels, such as:
• hypothesize which soil and climate properties influence the spatial and temporal variability of fruit tree crops;
• propose the most suitable precision management agro-techniques for efficient and sustainable management of fruit tree crops.

Communication skills
Participation in the lectures and use of the teaching materials made available will facilitate the development and application of communication skills, such as:
• provide an exhaustive range of practical examples of the application of precision agronomic techniques to fruit tree crops;
• using an appropriate and up-to-date technical agronomic vocabulary in line with fruit growing 4.0.

Learning skills
Participating in lessons and making independent use of the material made available will facilitate the consolidation of one's learning skills, such as:
• activate a programme of continuous updating of one's knowledge;
• autonomously identify ways of acquiring information by consulting bibliographic databases at various levels (peer-reviewed journals, popular journals, conference proceedings, websites, etc.);
• identify and use the most useful sources of information for personal updating.

Learning objectives

The objectives of the Artificial Intelligence Applications course are to provide students with the ability to use advanced statistical tools such as machine learning to understand, design and solve problems concerning the estimation of quantitative or qualitative variables.
Attendance at lessons and exercises, although optional is strongly recommended.
Knowledge and understanding
The course aims to develop in students knowledge and understanding skills, such as:
• know and understand what a machine learning problem is and when to use machine learning to solve a problem;
• know and understand the logic behind machine learning and the most common machine learning techniques;
• know and understand how to develop simple machine learning models and their training.

Applied knowledge and understanding
The course will allow students to apply knowledge and understanding, allowing for example to:
• divide problems into general categories;
• match problems with the most suitable algorithms to solve them;
• design and train machine learning algorithms that can estimate qualitative or quantitative variables based on structured and non-structured datasets.

Making judgements
The course will allow students to develop autonomy of judgment at various levels, such as:
• identify possible sources of uncertainty in the estimation of variables by machine learning (underfitting, overfitting, etc.);
• propose critical solutions to correct trends that undermine the value of the estimate.

Communication skills
Participating in the lessons and/or using the material made available independently will facilitate the development and application of communication skills, such as:
• provide a sufficient range of practical examples of application of artificial intelligence;
• use a suitable and up-to-date computer science technical vocabulary.

Learning skills
Participating in the lessons and/or independently using the material made available will facilitate the consolidation of one's learning skills, allowing for example to:
• activate a program of continuous education updating of one's knowledge;
• independently identify the ways to acquire information;
• identify and use the sources of information most useful to staff updating.

• Luciano ORTENZI
• Luciano ORTENZI

Learning objectives

Learning objectives

The minimum educational objectives of the course are aimed at enabling the student to effectively read and understand (reading-comprehension) texts in English such as scientific and/or popular articles, book chapters, etc., as well as to communicate with foreigners and dialogue, with particular reference to the contents of the master's degree course, with foreign interlocutors.

Knowledge and understanding

The student must demonstrate that he/she has acquired a level of knowledge and understanding of linguistic contents (reading, understanding and analysis of scientific texts, dialogue) of C1 level.

Applied knowledge and understanding

The student must demonstrate that he/she is able to apply the knowledge acquired and the understanding of the educational contents provided by confidently passing the final assessment test.

Autonomy of judgment

The student must demonstrate that he/she is able to critically and independently analyze the available teaching material, and also propose autonomous self-learning activities.

Communication skills

During the course, students must demonstrate good oral communication skills in English.

Learning skills

The student must demonstrate an ability to learn the teaching content at a level at least equal to C1.

Learning objectives

Knowledge and Understanding
The course aims to provide students with the necessary knowledge to carry out a topographic survey using the most modern techniques: GPS/GNSS and Remotely Piloted Aircraft Systems (RPAS). The goal is to enable the acquisition of precise knowledge regarding both aerial and terrestrial unmanned surveying systems, applicable to individual and environmental surveying in the field of animal husbandry. Additionally, the course aims to ensure knowledge of the subject from the perspective of usage methods and directly applicable applications. Specifically, the satellite constellation, control systems, and ground user segments will be analyzed. The course will also cover the digital processing and representation of data acquired through surveying activities, with an in-depth focus on the software and processing techniques involved.

Applied Knowledge and Understanding
The course intends to help students acquire the knowledge and skills needed to implement and utilize aerial and terrestrial unmanned surveying systems in the agricultural sector and mountainous terrain. These systems have various applications, including individual and environmental surveying in animal husbandry.
Additionally, the course aims to promote the use of GIS tools and the application of global satellite positioning systems, satellite remote sensing, and the main types of ground receivers.

Autonomy in Judgment
The course also aims to ensure that students understand digital technologies and can apply them in various contexts, including business and regional levels, with particular reference to mountainous areas. It also fosters the acquisition of the necessary skills to communicate relevant information to other engineering professionals working in the field, aiding in the design of technologies related to surveying systems. This includes promoting the development of independent judgment through the cultivation of critical skills aimed at identifying technical and scientific issues related to the subject, evaluating complex surveying projects and flight plans, conducting bibliographic research on scientific, regulatory, and technical sources, and delving into social, professional, and ethical considerations associated with surveying activities. The course will thus address aspects related to the knowledge and use of surveying with RPAS (Remotely Piloted Aircraft Systems), focusing particularly on the regulatory framework, types of RPAS, and the planning of photogrammetric flights.

Communication Skills
The course also aims to enable students to develop specific skills through educational activities to ensure an adequate level of communication regarding ideas, problems, and solutions related to the technical and scientific training pertinent to digital surveying issues.

Learning skills
The course is also designed to help students develop the technological skills needed to ensure continuous updating of knowledge relevant to their professional or scientific activities. This involves consulting regulatory, legislative, technological, digital, methodological, and experimental innovation sources related to current surveying systems. After revisiting the basic concepts of topographic surveying, students will be provided with the necessary knowledge to ensure the correct use of the global positioning system, fostering an understanding of geostatistics, global satellite positioning systems, satellite remote sensing, and the main types of ground receivers.

• Stefano BIGIOTTI
• Stefano BIGIOTTI

Learning objectives

Knowledge and ability to understand
The course aims to consolidate and expand the knowledge of the biology of plant organisms, with regard to ecophysiological aspects. Students will learn, in class and with originality, multidisciplinary approaches more related to genetics, molecular biology, biochemistry and plant physiology.

Applying knowledge and understanding
Students will acquire the ability to independently solve problems related to crop resilience, critically analysing the biochemical and physiological mechanisms that plants put in place to adapt to unfavourable environmental conditions and to defend themselves from pathogens.

Making judgement
Students will develop the ability to synthesize and integrate knowledge by making solid judgments.

Communication skills
Conclusions and recommendations will be communicated by students through the argumentation of the knowledge gained during the course and the motivations behind it, both to a specialized and non-specialist audience, in a clear and unambiguous way.

Learning skills
The notions and concepts acquired during the course will provide students with greater responsibility for further professional development.

• Daniel Valentin Savatin
• Daniel Valentin Savatin

Learning objectives

The learning objectives of teaching Digital Applications in foothill arboriculture are to provide the student with the ability to use digital tools and technologies for monitoring analysis and management of fruit tree systems and for the application of precision agronomic techniques in the field with regard to fruit trees from the foothill environment.
The course also intends to provide students with the ability to identify the most appropriate level of digitization applicable to the different types of orchard farms, together with an in-depth exploration of the different plant shapes used in fruit tree systems, with the aim of calibrating the applications of fruit farming 4.0 to the type of planting and plant shapes used in the orchard. The objectives described above are also pursued through the exploration of appropriate case studies.

Knowledge and understanding skills
The teaching aims to develop students' knowledge and understanding skills, such as:
• knowing and understanding what technologies are useful in monitoring tree systems for precision agronomic applications such as remote sensing and digital soil mapping to quantitatively estimate variables of agronomic interest in vegetation and soil;
• know and understand the digital techniques and technologies that can be used to analyze the spatial and temporal variability of the orchard;
• to know and understand the development and application of precision agronomic techniques and decision support systems for plant fruit systems.

Applied knowledge and understanding
The teaching will enable the application of knowledge and understanding, allowing the student to:
• know and use the main multispectral satellite systems suitable for precision agriculture through the use of cloud-based platforms for analyzing the temporal and spatial variability of fruit-growing plots;
• know and use techniques for estimating vegetation and soil biophysical variables from satellite data and through the use of proximal sensing for monitoring fruit crops;
• to know the techniques and technologies available for digital applications in the management of cultivation operations in the orchard, also exploring the opportunities for using drones and agribots for the automatic execution of cultivation operations.

Autonomy of judgement
Teaching will allow the development of autonomy of judgement at various levels, such as:
• hypothesize which soil and climate properties influence the spatial and temporal variability of fruit tree crops;
• propose the most suitable precision management agro-techniques for efficient and sustainable management of fruit tree crops.

Communication skills
Participation in the lectures and use of the teaching materials made available will facilitate the development and application of communication skills, such as:
• provide an exhaustive range of practical examples of the application of precision agronomic techniques to fruit tree crops;
• using an appropriate and up-to-date technical agronomic vocabulary in line with fruit growing 4.0.

Learning skills
Participating in lessons and making independent use of the material made available will facilitate the consolidation of one's learning skills, such as:
• activate a programme of continuous updating of one's knowledge;
• autonomously identify ways of acquiring information by consulting bibliographic databases at various levels (peer-reviewed journals, popular journals, conference proceedings, websites, etc.);
• identify and use the most useful sources of information for personal updating.