Course
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Credits
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Scientific Disciplinary Sector Code
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Contact Hours
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Exercise Hours
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Laboratory Hours
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Personal Study Hours
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Type of Activity
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Optional materials and exam in a foreign language
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Language
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119413 -
Fondamenti di ingegneria digitale applicata all'agricoltura
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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.
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TABORRI JURI
( syllabus)
The detailed program is as follows: - Topic 1 Metrology, calibration and statistics (8 hours): Measurement process, Systems of measurement units, Transducer, Static metrological characteristics, IInfluencing variables, Design criteria of measurement chains, Dynamic metrological characteristics, Gauss curve and deviation mean value standard, Student's t-distribution, Statistical tests, Confidence interval, Uncertainty of type A, Uncertainty of type B, Propagation of uncertainties; - Topic 2 Amplifiers and filters (4 hours): Inverting configuration, Non-inverting configuration, Instrumentation amplifier, First order low pass filters, First order high pass filters; - Topic 3 Acquisition and analog-digital conversion (4 hours): sampling theorem, quantization, A/D converters; - Topic 4 Temperature and humidity measurements (6 hours): Resistance thermometers, Thermistors, Thermocouples, Integrated circuit thermometers, Chemical thermometers, Moisture meters; - Topic 5 Pressure measurements (4 hours): Liquid column pressure gauge, Bourdon gauge, Diaphragm pressure gauge, Mc Leod vacuum gauge, Thermal conductivity vacuum gauge; - Topic 6 Flow and viscosity measurements (4 hours): Capillary viscometers, Spherical viscometers, Rotational viscometers, Differential pressure flow meters, Turbine meters, Hot wire anemometer; - Topic 7 Air quality measurements (2 hours): pollution sensors, CO2 sensors; - Topic 8 Non-destructive measurements (4 hours): infrared spectroscopy and NIR technology, colorimetry, agricultural applications;
In addition, laboratory/seminar activities are planned:
- Measurement laboratory (2 hours): first and second order instruments, amplifiers, thermometers; - The world of measurements and digital agriculture (4 hours); - Artificial intelligence (4 hours): basics and use in the field of precision agriculture.
( reference books)
For the achievement of the exam, it is sufficient the materials provided by the teacher and uploaded on moodle. For further details, it is suggested to consult the following books: VALLASCAS Fondamenti di misure meccaniche e termiche, Hoepli VALLASCAS, PATANÈ Misure meccaniche e termiche, Hoepli E. O. DOEBELIN Strumenti e metodi di misura, Mac Graw Hill (some chapters)
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6
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ING-IND/12
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48
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Related or supplementary learning activities
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ITA |
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Basi di meccatronica e IOT
(objectives)
The objective of the "Fundamentals of Mechatronics and IOT" module of the Fundamentals of digital engineering applied to agriculture course is to provide the student with full knowledge of the mechatronics fundamental components: automation and electronics with application to digital agriculture. The expected learning results are: (i) the knowledge of the theoretical contents of the course (Dublin descriptor n°1), (ii) the competence in presenting technical argumentation skills (Dublin descriptor n°2), (iii) autonomy of judgment (Dublin descriptor n°3) in proposing the most appropriate approach to argue the request and (iv) the students' ability to express the answers to the questions proposed by the Commission with language properties, to support a dialectical relationship during discussion and to demonstrate logical-deductive and summary abilities in the exposition (Dublin descriptor n°4).
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MINUCCI Simone
( syllabus)
Fundamentals of circuit theory and electronics: principal components of electronic circuits and methods of analysis od steady-state circuits. Fundamentals of industrial automation: microcontrollers and PLC for digital agriculture. Fundamentals of Arduino: programming an Arduino controller for digital agriculture applications.
( reference books)
Lecture notes Giulio Fabricatore, Elettrotecnica e applicazioni, Liguori Editori, 1994 Arduino starter kit
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6
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ING-IND/31
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48
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Related or supplementary learning activities
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ITA |
119466 -
Innovazione nella gestione delle problematiche fitosanitarie
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Entomologia
(objectives)
The aim of the course is to give students the core information needed to handle entomological problems in agricultural and natural environments using a contemporary, digital approach. At the end of the course the student will have to know the latest digital tools and biotechnological methodologies for the management of insect pests in both agriculture and forestry to prevent and/or contain their detrimental effects. The course pursues the following learning objectives: KNOWLEDGE AND UNDERSTANDING Knowledge of the main methods of crop pest management, traditional pest monitoring and control strategies and application methodologies. Knowledge of potential innovations in pest monitoring: proximal and remote sensing and machine learning. Knowledge of case studies for the extension of the principles acquired in the course to other cases. Knowledge and application of mathematical and statistical models for the description and prediction of insect populations. Examples of software used and their application to other case studies. APPLIED KNOWLEDGE AND UNDERSTANDING Understanding of innovative entomological approaches discussed in lectures and their application to specific cases in agricultural and forestry environments. MAKING JUDGEMENT Application of knowledge acquired in the course to case studies. Application of the acquired knowledge to the identification of innovative strategies discussed for sustainable management of phytosanitary problems. 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 course topics and critical ability to understand the crucial aspects of a phytosanitary problem, how to apply the currently available technological innovations and how to carry out the necessary investigations.
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CONTARINI Mario
( syllabus)
1. Importance of integrated insect management 2. Traditional monitoring strategies and potential innovations 3. Decision support systems (DSS) Mathematical models for the description and prediction of insect populations Statistical and mathematical models for the study of species distribution (MAXENT, Random Forest etc) Measurement and estimation of insect populations Case studies
4. Proximal sensing in monitoring of main insects in agriculture and forestry Monitoring with automated traps YOLO technology and machine learning for pests detection and recognition Case studies
5. Remote sensing in monitoring of main insects in agriculture and forestry UAVs and sensors, data collection and processing The use of satellite-collected data for assessing the activity of phytophagous insects Case studies
6. Apps for insect species recognition (citizen science)
( reference books)
Students will be provided with ppt slides. The study will be integrated with scientific papers provided by the teacher
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3
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AGR/11
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24
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Core compulsory activities
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ITA |
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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.
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MAZZAGLIA Angelo
( syllabus)
Importance of digital approach and technological innovations in plant disease management. Detection and monitoring of diseases and pathogens: • Critical approach to diagnosis: when traditional techniques are enough and when not • Advanced diagnostic methods: o immunological techniques (ELISA, DBTIA, Lateral flow, etc.) o molecular (standard PCR, Real-Time PCR (qPCR), loop-mediated isothermal amplification (LAMP), digital droplet PCR (ddPCR). o biosensors Assessment of the incidence of the disease and the damage caused by remote sensing: satellite images, ultralight aircrafts and drones. Assessment of structural damages to trees and risk related to plant stability in urban environments and control: VTA, instrumental diagnosis (resistograph, tomograph, pulse hammer, Pressler’s pacifier, fracking meter, use of infrasound, Ground Probing Radar (GPR), Compressed Air Digging Systems (Air-Spade®, Dendrotherapy). Bioinformatics approach to understanding pathogen biology through omics sciences (genomics, transcriptomics, proteomics, etc.); Strategies for disease prevention and management in precision agriculture: • forecast models • monitoring networks • decision support systems (DSS) for plant protection. Optimization of the distribution of active ingredients: advantages and problems Latest tools in plant protection: • the genome editing • nanotechnologies in plant protection Disease control and improvement of their resilience to stress through biological agents: • antagonistic micro-organisms, • natural microbial communities (endophytes and epiphytes), • supporting micro-organisms: PGPR and mycorrhizae
( reference books)
On the MOODLE portal the PowerPoint presentations of the lessons are made available, with graphic illustrations, photographs, videos and animations. It also offers in-depth studies and examples related to some lessons, selection of scientific bibliography on the subject, and a forum for the exchange of views and information with the teacher.
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3
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AGR/12
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24
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-
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Core compulsory activities
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ITA |
119414 -
Tecniche digitali in agricoltura
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Applicazioni digitali in arboricoltura
(objectives)
At the end of the course, the student acquires knowledge on precise and sustainable cultivation techniques for orchard management according to the type of cultivation, planting layout and the chosen plant training. Acquires knowledge on the use and installation of SMART technological tools, including artificial intelligence, for the management of orchard cultivation techniques. The student acquires knowledge on prescription models for managing nutrition, irrigation, canopy management, fruit load and fruit quality. The student possesses skills to organise cultivation strategies for fruit species based on sensors, models and artificial intelligence applications, and acquires knowledge to correct anomalies in orchard production performance related to plant-climate-soil interaction.
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Cristofori Valerio
( syllabus)
Part 1. Suitability of the orchard for Precision Farming applications and ecophysiological monitoring of the fruit plant The course deals with fruit tree water relations and interaction with soil and environment. Relationships of fruit trees with light: effects of cultivation practices on plant-light interactions. Gas exchange of fruit trees: photosynthesis/transpiration parameters; effects of environment and soil on photosynthesis and tree productivity. Fruit tree architecture and orchard design for precision farming applications. Fruit development and ripening: effects of cultivation technique and environment on fruit growth and ripening. fruit growth models and measurement methods using field sensors.
Part 2. Forecasting models and sensor technology for monitoring the state of the orchard The course covers the type and use of traditional and innovative tools and sensor technology to measure crop, environmental and soil variables. Analytical approaches to orchard monitoring and management and artificial intelligence models. Data processing and integration of derived information into farm management and decision support information systems (DSS). Definition of prescription maps and use of UAV (unmanned aerial vehicle) and UGV (unmanned ground vehicle) in the orchard system.
Part 3: Case studies Field experiments and case studies with the aim of gaining first-hand experience of current precision orchard management technologies available on the market.
( reference books)
- Casa Raffaele (editore) 2016. Agricoltura di precisione: metodi e tecnologie per migliorare l’efficienza e la sostenibilità dei sistemi colturali. Edagricole New Business Media
- Gentile Alessandra, Inglese Paolo, Tagliavini Massimo (editori) 2022. Arboricoltura Speciale. Edagricole New Business Media
Lecture notes, handouts and articles provided by the instructor through internet services managed by UNITUS
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6
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AGR/03
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48
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Core compulsory activities
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ITA |