Degree Course: Digital management of agriculture and mountain areas A.Y. 2022/2023

Expected learning outcomes Syllabus

AGRICOLTURA DIGITALE

FIRST YEAR

First semester

Course	Credits	Scientific Disciplinary Sector Code	Contact Hours	Exercise Hours	Laboratory Hours	Personal Study Hours	Type of Activity	Language
119413 - Fundamentals of digital engineering applied to agriculture
- Sensoristica (objectives) The objective of the "SENSOR" module of the Fundamentals of digital engineering applied to agriculture course is to provide the student with full knowledge of both the correct metrological language and the functioning of the main measuring instruments for digital agriculture applications. The sensors will be analyzed both considering the design process and the operating principle. The expected results according to the Dublin descriptors are the following: - Knowledge and understanding: Know the definitions of the static and dynamic meter characteristics, know the definitions of the units of measure, understand the meaning of probability distribution linked to the measure in order to be able to define the extended uncertainty, understand the concept of sampling and analog-digital conversion, includes the operation of a measuring instrument for the electrical evaluation of mechanical and thermal quantities and in digital agriculture applications. - Ability to apply correct knowledge and understanding: Having an understanding of the scientific approach in the field of measurements. Have the ability to independently carry out a calibration and associate the correct uncertainty in the function of the instruments used. Understanding the significance of the results through applied statistics. Have the ability to carry out a dynamic study of first and second order measuring instruments. - Judgment skills: The student will be able to evaluate the sensors most suitable for a given use and will be able to select the correct application in the world of agriculture. - Communication skills: The student will acquire the skills to be able to argue the metrological concepts and uncertainty in the exam, as well as the operating principle of sensors and the importance of the world of measurements in the agricultural field. - Ability to learn: The student will acquire the skills to be able to independently deepen the study of advanced sensors or the use of such as artificial intelligence, in addition to the basic ones seen above.	6	ING-IND/12	48	-	-	-	Related or supplementary learning activities	ITA
- Basi di meccatronica e IOT (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.	6	ING-IND/31	48	-	-	-	Related or supplementary learning activities	ITA
119466 - Innovation in the management of phytosanitary issues
- Entomologia (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.	3	AGR/11	24	-	-	-	Core compulsory activities	ITA
- Patologia (objectives) The course aims to provide students with the fundamental knowledge for a modern approach to the (eco)sustainable management of phytosanitary issues related to abiotic and biotic stress, the latter with specific reference to fungi, bacteria, and viruses in agricultural and natural ecosystems. At the end of the course the student will be able to choose the latest digital tools and biotechnological methodologies to be used in the different contexts in which plant diseases can occur in both agriculture and forestry to prevent and/or contain their detrimental effects.KNOWLEDGE AND ABILITY TO UNDERSTAND Acquisition of a comprehensive knowledge of the basics of plant protection in the context of digital agriculture: understanding of the ways of occurrence and spread of plant diseases and how to evaluate them with innovative tools; understanding of the main innovative diagnostic strategies and how to apply them correctly; solid knowledge of the latest technological innovations for preventive and containment defense from phytosanitary adversities. The course pursues the following educational objectives: KNOWLEDGE AND UNDERSTANDING Acquisition of a comprehensive knowledge of the basics of plant protection in the context of digital agriculture: understanding of the ways of occurrence and spread of plant diseases and how to evaluate them with innovative tools; understanding of the main innovative diagnostic strategies and how to apply them correctly; solid knowledge of the latest technological innovations for preventive and containment defense from phytosanitary adversities. APPLYING KNOWLEDGE AND UNDERSTANDING Application of the management of phytosanitary problems through digital and innovative approaches; awareness of pre- and post-onset strategies to be implemented to minimize phytopathological damage. MAKING JUDGMENTS Ability to face a phytosanitary problem with the methodologies discussed in class or similar to them, and to draw on the knowledge acquired in the course to manage it better. COMMUNICATION SKILLS Use of the correct technical-scientific terminology in the description of the course topics. Synthesis skills and communicative effectiveness in the description of the course topics. LEARNING SKILLS Knowledge of the topics of the course and critical ability to fully understand the crucial aspects of a phytosanitary problem and how to deal with it with the latest methods.	3	AGR/12	24	-	-	-	Core compulsory activities	ITA
119414 - Digital techniques in agriculture
- Tecniche agronomiche di precisione	Also available in another semester or year
- Applicazioni digitali in arboricoltura (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.	6	AGR/03	48	-	-	-	Core compulsory activities	ITA

Second semester

Course	Credits	Scientific Disciplinary Sector Code	Contact Hours	Exercise Hours	Laboratory Hours	Personal Study Hours	Type of Activity	Language
119414 - Digital techniques in agriculture
- Tecniche agronomiche di precisione (objectives) The objectives of the Precision Agronomic Techniques course are to provide students with the ability to use digital tools and technologies for the monitoring, analysis and management of cropping systems and for the application of precision agronomic techniques for open field applications with particular regard to herbaceous cropping systems. Attendance at lectures 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 which technologies are useful for monitoring cropping systems for precision agronomic applications such as multispectral and hyperspectral remote sensing to quantitatively estimate variables of agronomic interest of vegetation and soil; • to know and understand the techniques and technologies that can be used to analyze the spatial and temporal variability of cultivated plots, in particular by exploiting process-based agronomic modeling tools; • know and understand the methods of development and application of precision agronomic techniques such as seeding, fertilization and irrigation. Applied knowledge and understanding The course will allow students to apply knowledge and understanding, allowing for example to: • know and use the main multispectral satellite systems suitable for precision agriculture through the use of cloud-based platforms for the analysis of the temporal and spatial variability of cultivated plots; • know and use the techniques to estimate biophysical variables of vegetation and soil from satellite data for the purpose of monitoring agricultural crops; • know and use a proces-based agronomic model to analyze agronomic management scenarios; • know the techniques and technologies and equipment for precision seeding, irrigation and fertilization. Making judgements The course will allow students to develop autonomy of judgment at various levels, such as: • hypothesize which properties of the soil and atmosphere influence the spatial and temporal variability of agricultural production; • propose the most suitable precision management agrotechniques for efficient and sustainable management of herbaceous crops. 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 the application of precision agronomic techniques to herbaceous crops; • use an appropriate and up-to-date agronomic 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.	7	AGR/02	56	-	-	-	Core compulsory activities	ITA
- Applicazioni digitali in arboricoltura	Also available in another semester or year
119427 - Advanced English (C1) (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.	3	L-LIN/12	24	-	-	-	Other activities	ITA
119426 - Attività Formativa a Scelta	8		64	-	-	-	Elective activities	ITA
119411 - Informatic Systems (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.	8	INF/01	64	-	-	-	Core compulsory activities	ITA
119412 - Plant ecophysiology (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.	6	AGR/03	48	-	-	-	Core compulsory activities	ITA
119515 - Drones and land survey (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.	6	AGR/10	48	-	-	-	Core compulsory activities	ITA

SECOND YEAR

First semester

Course	Credits	Scientific Disciplinary Sector Code	Contact Hours	Exercise Hours	Laboratory Hours	Personal Study Hours	Type of Activity	Language
119416 - Digital technologies applied to genetics (objectives) Knowledge and understanding The course aims to provide the necessary knowledge for the evaluation of phenotypes and their genetic bases in order to learn the body's responses to different environmental situation and to be able to favor those most suited to specific needs. The basics of modern genetic analysis from sequencing to the evaluation of genomes and biodiversity will also be provided. Applied knowledge and understanding The course deals with genotypic and genomic characterization (morpho-bio-molecular markers; automation in field genotyping - NGS, DNA barcoding, genotyping by sequencing; population genetics; management of natural populations), phenotypic characterization (tolerance traits abiotic stress observation and parameterization; phenotyping of the individual, populations and communities; analysis of point and area data, from multispectral analysis to phenotype), from genotype to phenotype (gene regulation; phenotypic plasticity; epi-genetics), the exploitation of germplasm (characterization, enhancement and conservation of germplasm; general principles and application to case studies). Making judgments Know how to decide the best genetic evaluation and biodiversity conservation methodologies to use in different situations. Communication skills Acquire technical terminology to communicate information, ideas, problems and solutions clearly and in detail to the scientific and public community. Learning skills Develop learning skills necessary to undertake further studies with a high degree of autonomy.	6	AGR/07	48	-	-	-	Core compulsory activities	ITA
119485 - Digital mapping of soil and territory
- Analisi spaziali GIS e cartografia digitale (objectives) The main objective of the course is to provide knowledge of the methods and tools for observing and analyzing the territory, offering advanced insights into Geographic Information Systems (GIS), Remote Sensing, and spatial analysis of territorial data. Knowledge and understanding The student will acquire specific skills related to the acquisition of georeferenced data available from major databases (such as the National Geoportal, ISTAT database, Copernicus, Regional Web GIS, etc.), the analysis and processing of such data, and the production of georeferenced data through monitoring or derived from spatial analyses. Whenever possible, students will be involved in activities related to ongoing research projects. Applying knowledge and understanding By the end of the course, the student will be familiar with the fundamental elements of cartography and digital cartographic representation. They will be able to create thematic maps related to territorial elements, conduct spatial analyses of various phenomena, and develop a cartographic project. The student will have gained proficiency in using GIS software and employing remotely sensed images for territorial analyses. Making judgements The course aims to develop analytical skills at the territorial scale with the goal of proposing technical and practical solutions Communication skills The student will be required to produce an exam work by applying the acquired knowledge, conducting part of the work independently and part in a group to promote learning ability and work autonomy. Learning skills During the course, the student will be able to develop learning skills through active participation. Throughout the lessons, the student will have the opportunity to identify methods for acquiring and updating information, select and utilize the most useful sources, apply the acquired knowledge, and assess their own level of learning.	6	AGR/10	48	-	-	-	Core compulsory activities	ITA
- Cartografia e monitoraggio digitale dei suoli (objectives) The main objective of the teaching is to provide the knowledge required to understand the characteristics and spatial variability of soils, for proper site-specific soil management in agriculture and agro-ecosystem. Basic concepts of soil chemistry, physics and hydrology, pedogenetic factors and processes will be recalled. The student will learn to frame soil variability within an agro-ecosystem landscape, learn digital soil mapping techniques using GIS software and the use of innovative techniques for soil monitoring and mapping, in particular the use of proximal sensors such as electromagnetic induction and diffuse reflectance spectrometry. The student will also learn the applications of mapping products and soil data, such as land suitability maps, monitoring soil functionality, etc. Knowledge and ability to understand The student will have to demonstrate that he/she has learnt and understood the main aspects of soil mapping and monitoring, namely: • the main chemical, physical and hydrological characteristics of soils; • the principles of horizon and soil classification; • the principles of soil mapping, especially digital mapping, using methods of data spatialization and clustering of homogeneous units through GIS software; • the principles of soil science applied to agronomy with regard to soil suitability, water and nutrient availability, recognition of possible problems (e.g. waterlogging, erosion susceptibility, etc.). Applying knowledge and understanding The student will be able to use the acquired knowledge to: • describe the main characteristics of a soil profile and the associated pedogenetic processes, understanding the links between environmental characteristics and the chemical-physical and hydrological ones; • understand the location of a certain soil type within a landscape and its geographical limits related to variations in pedogenetic factors; • apply proximal soil sensing techniques using sensors and carry out the spatialization of soil data; • be able to identify any problems or risks related to soil functionality and circumscribe them. Making judgement The student must be able to independently recognise a certain soil type and the soil processes present. He/she must know how to set up a soil survey and a description of a soil profile or soil borehole, as well as interpret a soil map or a soil description and analysis. They must also know how to interpret data obtained from proximal geophysical sensors, how to spatialise them in the plot of interest and understand which soil characteristics are associated with the variability of these data. Communication skills The student should have the ability to explain in a simple and comprehensive manner the knowledge acquired, trying to connect the basic notions to the more complex topics related to soil mapping and applications of pedology. Learning ability The student will have to refer to the teaching program and to the lesson plan of the course, deepening the various topics addressed through the handouts provided by the lecturer, the consultation of recommended texts and publications of national and international relevance.	6	AGR/14	48	-	-	-	Core compulsory activities	ITA
119428 - Training	2		-	-	-	-	Other activities	ITA

Second semester

Course	Credits	Scientific Disciplinary Sector Code	Contact Hours	Exercise Hours	Laboratory Hours	Personal Study Hours	Type of Activity	Language
119424 - Machines and plants for precision farming (objectives) The students must acquire basic skills to develop the mechanization of operations in precision farming. In particular, they must be able to choose suitable machines for sustainable and high-quality work (knowing operational methods, safety aspects, etc.) while respecting mechanization constraints (economic, environmental, safety, etc.). Knowledge and understanding The student must acquire knowledge and understanding of the principles underlying the design and operation of machines and plants and be able to introduce them into agricultural sites, respecting various constraints. Applying knowledge and understanding The student must acquire the ability to apply theoretical knowledge of the topics covered in the course critically to identify individual machines, a fleet of machines, or systems for precision farming. Making judgements The student must be able to select specific machines and plants from the market suitable for various types of agricultural work sites where precision farming principles are applied. This should be done objectively, without being influenced by manufacturers, and respecting social, scientific, or ethical aspects related to each mechanization decision. Communication skills The student must be able to effectively communicate information about machines and plants and their technical-economic requirements to third parties (employers, clients such as agricultural companies, forestry enterprises, etc.), justifying their choices. Learning skills The course structure will be developed to first convey "cross-cutting" basic concepts relevant to any type of machine. Subsequently, individual types of machines (the most widespread in precision farming) will be covered. The topics will be presented to stimulate a desire for learning, logically developing knowledge gradually, from materials and mechanical principles to construction and safety aspects, to machine management. The same logic is required in creating a presentation (flipped classroom), which will be considered in the learning assessment.	6	AGR/09	48	-	-	-	Core compulsory activities	ITA
119417 - Digital management of water resources (objectives) The course covers the main aspects of digital water resource management at the catchment scale. The course aims to train the learner on the following topics: • regulatory aspects of water resources management; • the use of hydrological modelling software; • the use of hydraulic modelling software to assess the hydraulic characteristics of a free-flowing stream. Knowledge and understanding The course aims to develop students' knowledge and understanding skills, such as: • knowledge and understanding skills in a field of study at a level that is characterised by the use of advanced textbooks and also includes knowledge of some cutting-edge topics in the field of watershed managment; • ability to understand and hydrological data. Applied knowledge and understanding The course will enable them to apply knowledge by demonstrating adequate understanding, enabling them, for example: • to apply their knowledge and understanding in a way that demonstrates a professional approach to their work, as well as adequate skills to both devise and support arguments to solve problems in the field of watershed managment; • ability to collect and analyse hydrological data. Making judgements The course will allow the development of independent judgement at various levels, such as • hypothesising which causes most influence the occurrence of hydrogeological instability phenomena using one-dimensional hydraulic modelling software; • propose solutions for the mitigation of hydrogeological instability phenomena using one-dimensional hydraulic modelling software. Communication skills Attending lectures and/or making independent use of the material provided will facilitate the development and application of communication skills, such as: • ability to communicate information, ideas, problems and solutions, on the topics covered, to specialist and non-specialist people; • use an appropriate and up-to-date technical vocabulary in the field of hydrological-hydraulic modelling. Learning skills Attending lectures and/or making independent use of the material provided will facilitate the consolidation of one's learning skills, enabling one to, for example: • activate a programme of continuous updating of one's knowledge; • autonomously identify ways of acquiring information; • identify and use the most useful sources of information for personal updating. This learning capacity will be fundamental for undertaking subsequent studies with a high degree of autonomy.	6	AGR/08	48	-	-	-	Core compulsory activities	ITA
119425 - Precision livestock farming (objectives) In line with the educational objectives of the CdLM in 'Digital Management of Agriculture and Mountain Territory', the teaching provided has the general objective of providing the student with skills on the applications in the livestock sector of the main sensors and tools for precision farming aimed at improving productivity, health and animal welfare and environmental sustainability. Knowledge and understanding The student will develop basic and advanced knowledge relating to the possible automation solutions available for the management of animals (ruminants, pigs, poultry), for the control of the microclimate in breeding, for the management of food in breeding and preparation/distribution of the ration, depending on the species bred and the systems for monitoring animal performance and milking automation. Applying knowledge and understanding The knowledge acquired will give the student the ability to understand the main critical points related to the management of animals, animal nutrition, and the main digital technological approaches available to improve the production efficiency and sustainability of livestock farming. Making judgements The skills and knowledge acquired will allow the student to independently develop their own assessments regarding the resolution of practical problems related to the management of livestock using digital technologies available on the market. Communication skills The knowledge acquired by the student will allow him/her to communicate what he/she has learned using appropriate technical and scientific language. Learning skills The skills acquired by the student will allow him to develop a critical capacity that will allow him to face with great flexibility the different professional contexts in which he will have to operate.	6	AGR/18	48	-	-	-	Core compulsory activities	ITA
119429 - Final test	20		-	-	-	-	Final examination and foreign language test	ITA

TOTAL

120

Teachings extracurricular: (hide)

Info

119853 - Digital management of extensive animal husbandry and in mountain areas (objectives) In line with the educational objectives of the CdLM in 'Digital Management of Agriculture and Mountain Territory', the teaching provided has the general objective of providing the student with skills on the applications in the livestock sector of the main sensors and tools for precision farming aimed at improving productivity, health and animal welfare and environmental sustainability. Knowledge and understanding The student will develop basic and advanced knowledge relating to the possible automation solutions available for the management of animals (ruminants, pigs, poultry), for the control of the microclimate in breeding, for the management of food in breeding and preparation/distribution of the ration, depending on the species bred and the systems for monitoring animal performance and milking automation. Applying knowledge and understanding The knowledge acquired will give the student the ability to understand the main critical points related to the management of animals, animal nutrition, and the main digital technological approaches available to improve the production efficiency and sustainability of livestock farming. Making judgements The skills and knowledge acquired will allow the student to independently develop their own assessments regarding the resolution of practical problems related to the management of livestock using digital technologies available on the market. Communication skills The knowledge acquired by the student will allow him/her to communicate what he/she has learned using appropriate technical and scientific language. Learning skills The skills acquired by the student will allow him to develop a critical capacity that will allow him to face with great flexibility the different professional contexts in which he will have to operate.	4		32	-	-	-		ITA
119856 - Agronomic modelling, statistical methodology and artificial intelligence for digital agronomy (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.	4	AGR/02	32	-	-	-		ITA
119858 - Machines, tools and techniques for urban greenery (objectives) The students must acquire basic skills to develop the mechanization of operations in precision farming. In particular, they must be able to choose suitable machines for sustainable and high-quality work (knowing operational methods, safety aspects, etc.) while respecting mechanization constraints (economic, environmental, safety, etc.). Knowledge and understanding The student must acquire knowledge and understanding of the principles underlying the design and operation of machines and plants and be able to introduce them into agricultural sites, respecting various constraints. Applying knowledge and understanding The student must acquire the ability to apply theoretical knowledge of the topics covered in the course critically to identify individual machines, a fleet of machines, or systems for precision farming. Making judgements The student must be able to select specific machines and plants from the market suitable for various types of agricultural work sites where precision farming principles are applied. This should be done objectively, without being influenced by manufacturers, and respecting social, scientific, or ethical aspects related to each mechanization decision. Communication skills The student must be able to effectively communicate information about machines and plants and their technical-economic requirements to third parties (employers, clients such as agricultural companies, forestry enterprises, etc.), justifying their choices. Learning skills The course structure will be developed to first convey "cross-cutting" basic concepts relevant to any type of machine. Subsequently, individual types of machines (the most widespread in precision farming) will be covered. The topics will be presented to stimulate a desire for learning, logically developing knowledge gradually, from materials and mechanical principles to construction and safety aspects, to machine management. The same logic is required in creating a presentation (flipped classroom), which will be considered in the learning assessment.	3	AGR/09	24	-	-	-		ITA

Teachings extracurricular: (hide)

Info

120283 - Salute e sicurezza dei luoghi di lavoro (objectives)

4

AGR/09

32

-

-

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ITA

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