Degree Course: Digital management of agriculture and mountain areas
A.Y. 2022/2023 
Conoscenza e capacità di comprensione
I laureati al termine del corso di studi possiedono capacità di analisi approfondita e sono in grado di affrontare problemi e tematiche complesse in contesti interdisciplinari, utilizzando anche metodologie innovative.
I laureati sono capaci di identificare problemi, definirne i contorni e proporre adeguate soluzioni nel settore dell’applicazione delle tecnologie digitali in agricoltura e nel territorio montano, nell’ottica della sostenibilità.
Sono in grado di scegliere e utilizzare strumenti e metodologie appropriate conoscendone caratteristiche, possibilità applicative e scala di applicazione (aziendale, territoriale, ecc.).
I laureati possiedono una visione sistemica della realtà agricola e del territorio montano e sono in grado di proporre interventi e soluzioni, basate soprattutto su tecnologie digitali, con elevato grado di competenza e autonomia sia nella gestione delle produzioni agricole e zootecniche sia in quella del territorio, con particolare riferimento a quello montano.
Capacità di applicare conoscenza e comprensione
I laureati pertanto sono in grado di:
- partecipare alla progettazione e gestione dell'innovazione digitale applicata alle produzioni agricole e zootecniche con particolare riguardo alla sostenibilità delle stesse;
- partecipare alla progettazione e gestione dell'innovazione digitale applicata al territorio montano con particolare riguardo alla sostenibilità delle attività che vi si svolgono;
- svolgere indagini utili alla definizione di soluzioni a problemi complessi propri dei sistemi agrari e dell’ambiente montano e di quelli inerenti la ricerca e la sperimentazione dei suddetti ambiti;
- svolgere attività di assistenza tecnica e consulenza specialistica nel campo agrario e territoriale-ambientale;
- svolgere attività di assistenza tecnica e consulenza specialistica nel campo nel campo delle tecnologie digitali e meccatroniche applicate all’agricoltura e al territorio montano.
Le suddette capacità e potenzialità di applicazione delle conoscenze acquisite sono sviluppate anche con esercitazioni di laboratorio e di campo, esercitazioni interdisciplinari effettuate fuori sede, attività seminariali, tirocini presso aziende del settore, promozione della discussione critica su specifici problemi.
Le competenze sono valutate nelle verifiche di profitto (esoneri, prove scritte e/o orali), attraverso la relazione di tirocinio e nella Tesi nella quale lo studente sperimenta le sue capacità progettuali e di elaborazione e le capacità di applicare le conoscenze acquisite.
Nel caso di insegnamenti integrati le commissioni di verifica saranno composte dai docenti titolari dei rispettivi moduli di insegnamento.
Il CdS favorirà l'accessibilità ai materiali didattici, e utilizzerà specifiche modalità di verifica dell’apprendimento per gli studenti disabili secondo quanto previsto dalla Commissione Inclusione ed Equità di Ateneo.
Autonomia di giudizio
Il laureato magistrale in Gestione digitale dell’agricoltura e del territorio montano è in grado di comprendere ed utilizzare gli strumenti basati su tecnologie digitali, applicandoli nei diversi contesti in cui opera, sia a livello aziendale, che territoriale, con particolare riferimento al territorio montano.
È in grado, inoltre, di trasmettere a figure professionali ingegneristiche specializzate le informazioni utili alla progettazione, realizzazione e collaudo di nuove tecnologie per l’agricoltura ed il territorio.
Durante il corso di studio gli studenti maturano una capacità di giudizio in occasione di tutte le attività didattiche, sperimentali e di laboratorio impartite.
Tra queste capacità si evidenziano l’identificazione dei problemi tecnico-scientifici nelle aree di competenza e le diverse soluzioni attuabili valutandone anche i rispettivi pro e contro.
Maturano inoltre la capacità di progettazione e di valutazione critica dei risultati ottenuti.
I laureati in GEDAM sono in grado di comprendere la necessità di integrare le loro conoscenze per gestire la complessità, il cambiamento e di formulare giudizi ed acquisire decisioni sulla base di dati disponibili (es.
big data), includendo la riflessione sulle responsabilità sociali ed etiche collegate all'applicazione delle loro conoscenze e giudizi.
Durante il corso di studio, inoltre, acquisiscono:
- la capacità di condurre ricerche bibliografiche su fonti scientifiche e tecniche, anche tramite accesso a banche dati elettroniche;
- la capacità di valutare progetti e piani complessi;
- la capacità di approfondire considerazioni di natura sociale, politica e etica con riferimento particolare alla teoria e alla pratica della sostenibilità dei sistemi agricoli e della conservazione delle risorse ambientali;
- la capacità di operare in autonomia assumendo la responsabilità di progetti o di strutture;
- la conoscenza dei loro ambiti di intervento nella attività professionale e degli aspetti normativi e deontologici;
- l'autonomia di giudizio viene sviluppata mediante attività autonome o di gruppo, richiedenti allo studente uno sforzo personale individuale (per es.
preparazione di elaborati e relazioni nell'ambito dei corsi, valutazione della didattica e delle altre attività formative) e il confronto con i colleghi durante le esercitazioni di laboratorio e in campo.
La verifica dell'autonomia di giudizio è intrinseca alle valutazioni periodiche del profitto dello studente, sia in sede di esame che nella valutazione associata alle attività esercitative o di tirocinio.
Infine, l'avvenuto raggiungimento di questo obiettivo formativo è dimostrato in modo particolare dalle attività autonomamente condotte nella preparazione della tesi finale.
Abilità comunicative
Il laureato magistrale in 'Gestione digitale dell’agricoltura e del territorio montano' è in grado di comunicare in modo chiaro e non ambiguo informazioni, idee, problemi e soluzioni relativi alla formazione tecnico-scientifica acquisita.
È in grado di interagire adeguatamente con interlocutori specialisti e non e di utilizzare i principali mezzi di comunicazione, soprattutto quelli informatici.
E’ in grado di utilizzare, in forma scritta e orale la lingua italiana e quella inglese, con riferimento al lessico tecnico-scientifico acquisito durante il corso di laurea magistrale.
L'abilità comunicativa si esercita e si consegue durante le attività didattiche (lezioni, esercitazioni, laboratori, lavori di gruppo o individuali), durante lo svolgimento del tirocinio e della tesi e durante l’eventuale periodo di studio all’estero nell’ambito del progetto Erasmus.
L’abilità comunicativa si valuta mediante le verifiche del profitto conseguito dallo studente nelle diverse prove di esame, gli elaborati scritti individuali, le presentazioni, anche multimediali, di progetti o di argomenti specifici assegnati, le discussioni e relazioni di gruppo, e soprattutto mediante la presentazione dell'elaborato di tirocinio e di tesi dinanzi alla Commissione di laurea.Capacità di apprendimento
Il laureato magistrale in “Gestione digitale dell’agricoltura e del territorio montano” possiede la capacità necessaria per l’utilizzo delle tecnologie informatiche in grado di garantirgli il continuo aggiornamento delle conoscenze necessarie allo svolgimento della sua attività professionale o scientifica.
In particolare, il laureato magistrale è in grado di:
- mantenersi aggiornato su metodi, tecniche, strumenti e norme inerenti la professione, anche mediante la consultazione di banche dati;
- consultare fonti normative o reperire informazioni in autonomia, su tutte le innovazioni tecnologiche, digitali, metodologiche, sperimentali di settore;
- accedere, con le conoscenze e le competenze specialistiche acquisite, ai livelli formativi superiori universitari (Dottorato di Ricerca, Master, corsi di perfezionamento, ecc.).
Tali capacità sono acquisite durante il curriculum studiorum (lezioni, esercitazioni, tirocinio, preparazione della tesi).
La verifica del raggiungimento dell'obiettivo è legata ai risultati di profitto nell'ambito dei singoli insegnamenti e della valutazione finale.
Requisiti di ammissione
L'iscrizione al Corso di Laurea Magistrale in Gestione digitale dell’agricoltura e del territorio montano è possibile a tutti coloro che siano in possesso di laurea o di titolo equipollente conseguito all'estero.
Il Corso di Laurea Magistrale è ad accesso non programmato.
I requisiti curriculari minimi richiesti sono il possesso di almeno 24 CFU così ripartiti:
• 12 CFU nei SSD:
o da FIS/01 a FIS/07
o da MAT/01 a MAT/09
o INF/01 - Informatica
o SECS-S/01 - Statistica
• 12 CFU nei SSD:
o AGR/02 - Agronomia e coltivazioni erbacee
o AGR/03 - Arboricoltura generale e coltivazioni arboree
o AGR/04 - Orticoltura e floricoltura
o AGR/05 - Assestamento forestale e selvicoltura
o AGR/07 - Genetica agraria
o AGR/08 - Idraulica agraria e sistemazioni idraulico-forestali
o AGR/09 - Meccanica agraria
o AGR/10 - Costruzioni rurali e territorio agroforestale
o AGR/11 - Entomologia generale e applicata
o AGR/12 - Patologia vegetale
o AGR/13 - Chimica agraria
o AGR/15 - Scienze e tecnologie alimentari
o AGR/16 - Microbiologia agraria
o AGR/17 - Zootecnica generale e miglioramento genetico
o AGR/18 - Nutrizione e alimentazione animale
o AGR/19 - Zootecnica speciale
o AGR/20 - Zoocolture
o BIO/01 - Botanica generale
o BIO/02 - Botanica sistematica
o BIO/03 - Botanica ambientale e applicata
o BIO/10 - Biochimica
o BIO/19 - Microbiologia generale
o ING-IND/12 - Misure meccaniche e termiche
o ING-IND/13 - Meccanica applicata alle macchine
o ING-IND/14 - Progettazione meccanica e costruzione di macchine
L'ammissione al corso di studio sarà comunque subordinata alla conoscenza della lingua inglese, in forma scritta e orale, almeno ad un livello che consenta l'utilizzo della letteratura scientifica internazionale (almeno livello B2).
Prova finale
La prova finale consiste nella preparazione e discussione di una tesi elaborata in modo originale dallo studente sotto la guida di un relatore, relativa a tematiche affrontate nel percorso formativo e con un impegno complessivo di 15 CFU.
Per essere ammessi alla prova finale occorre aver conseguito tutti i crediti relativi alle attività formative previste dal piano di studio, ad eccezione di quelli riservati alla prova finale.
La votazione della prova finale è espressa in centodecimi con eventuale lode.
Alla formazione della votazione finale concorrono la carriera studiorum dello studente, la valutazione della qualità e originalità della tesi e della qualità della presentazione dinanzi alla commissione di laurea magistrale.
Orientamento in ingresso
Lo staff dell'orientamento attualmente è costituito da:
• Sergio Madonna (delegato del Direttore con funzione di coordinamento)
• Emilia Gitto (mansioni amministrative ed organizzative)
• Doriano Vittori (mansioni organizzative e logistiche)
• Claudia Menghini e Nino De Pace (questi ultimi pur ricoprendo principalmente altre mansioni rappresentano una stabile ed efficace interfaccia, soprattutto nel periodo estivo per ricevere e smistare gli studenti).
Tutors – Durante l’anno accademico sono reclutati, con un numero di ore variabile a disposizione, alcuni tutors che sono utilizzati sia per le attività di orientamento in sede (accoglienza e ricevimento presso l'Ufficio orientamento nei giorni previsti, gestione delle visite presso le nostre strutture, presenza negli Open Day Unitus e DAFNE ecc.); sia per la organizzazione e gestione delle attività fuori sede (presenza presso gli stand organizzati nelle varie manifestazioni, distribuzione di materiale informativo, ecc.).
Il Delegato del Direttore, la Dott.ssa Gitto ed il Dott.
Vittori svolgono mansioni di gestione e di organizzazione delle attività di orientamento ed in particolare:
• Contatti con gli Istituti
• Controllo e gestione attività tutor (controllo presenze, fogli firme, ecc.)
• Organizzazione e logistica delle attività esterne in occasione di Open Day, Salone dello studente, etc.
(trasporto materiale, istallazione e presenza nello stand, ecc.)
• Front office orientamento (informazioni riguardanti la struttura e le attività didattiche, organizzative, amministrative e di servizio dell'Ateneo, del Dipartimento e del CCS; supporto nella comunicazione diretta dello studente con il corpo docente)
• Pianificazione visite o esercitazioni presso i laboratori di ricerca del Dipartimento (Contatti con i docenti responsabili dei Laboratori del DAFNE, contatti con i docenti degli Istituti superiori, ecc.).
• Contatti con centro Stampa di Ateneo per realizzazione flyer, locandine e manifesti
• Cura (in collaborazione con il Direttore), della pagina Facebook DAFNE (Dott.ssa Gitto)
• Contatti con gestore interno sito Dipartimento per news relative ad attività di orientamento, Open Day, iniziative varie, Bandi (Dott.ssa Gitto)
• Integrazione informazioni di orientamento su attività Erasmus nel DAFNE (Dott.ssa Gitto - referente outgoing e incoming nella segreteria didattica)
Le attività di orientamento del Dipartimento DAFNE sono coordinate ed armonizzate con le attività di orientamento dell'Ateneo.
Il Corso di Studio in breve
Il corso di Laurea Magistrale 'Gestione digitale dell’agricoltura e del territorio montano' (GEDAM) è finalizzato alla formazione di professionisti agronomi o forestali, con particolari competenze specifiche nel campo: della gestione dei dati digitali, della sensoristica applicata all’agricoltura e alle foreste, delle tecniche di agricoltura di precisione, della gestione di sistemi informatici applicati alla gestione del territorio montano e all’agricoltura.
Il laureato sarà esperto nell’introduzione e nella gestione delle innovazioni tecnologiche in agricoltura e nel territorio montano.
Il corso si inquadra nell’interclasse LM69 (Scienze e Tecnologie Agrarie) e LM73 (Scienze e Tecnologie Forestali ed Ambientali).
La LM interclasse consente di differenziarsi da molte offerte formative nazionali in quanto non ci si focalizza al solo ambito strettamente agricolo, o forestale, ma la visione presente nelle due classi di LM viene integrata fornendo alla laurea in GEDAM uno spiccato carattere di unicità.
La presente LM si prefigge di formare tecnici con competenze in due grandi aree d’intervento presenti nel Piano Nazionale di Ripresa e Resilienza (PNRR), cioè la Transizione verde e la Trasformazione digitale.
Il laureato in GEDAM sarà in grado di utilizzare gli strumenti digitali per un’efficiente produzione agricola e una corretta gestione del territorio con particolare riferimento a quello montano.
La figura professionale proposta potrà occuparsi della gestione del territorio in modo più efficace adottando le tecnologie più innovative.
La figura professionale, inoltre, grazie al forte carattere innovativo e alle spiccate competenze in due dei sei pilastri del PNRR, rende il laureato in GEDAM particolarmente richiesto nel mondo del lavoro, grazie anche alle sue competenze al momento difficili da reperire.
Le funzioni che potranno svolgere i laureati GEDAM andranno dalla ricerca e sviluppo in aziende del settore agricolo, agro-alimentare, zootecnico, e forestale, alla collaborazione con aziende di produzione di tecnologie applicate all’agricoltura e alle foreste, agli enti di pianificazione e controllo territoriale.
L’impostazione della LM e le tematiche trattate si prestano allo sviluppo di un percorso internazionale: a questo proposito è in corso di perfezionamento una collaborazione con la Agricultural University of Tirana (Albania), con la quale sarà formalizzato uno specifico agreement, per l’avvio di una laurea magistrale (dual degree), in collaborazione con la facoltà di scienze forestali della stessa Università.
Pertanto, nel caso si riesca a formalizzare l’accordo con l’Agricultural University of Tirana entro i termini consentiti, si costituirà un percorso formativo parallelo a quello illustrato nel presente documento, nella logica della dual degree.
Altri corsi di laurea e master sulla agricoltura di precisione sono molto orientati verso grandi aziende, mentre GEDAM affronta tecniche e metodologie applicabili anche alle PMI e realtà locali, come quelle caratteristiche dell’ambito montano.
Il percorso formativo propone degli insegnamenti caratterizzanti quali: sistemi informativi, fondamenti di ingegneria digitale applicata all'agricoltura, tecniche digitali in agricoltura, droni e sistemi di rilevamento, innovazione nella gestione delle problematiche fitosanitarie, e tecnologie digitali applicate alla genetica.
Il percorso attualmente è suddiviso in due curriculum, il primo riguardante l’'Agricoltura digitale', mentre il secondo riguardante la 'Gestione digitale del territorio montano'.
Nel curriculum 'Agricoltura digitale' saranno presenti insegnamenti riguardanti la cartografia digitale, la cartografia digitale dei suoli, le applicazioni digitali in orto-floricoltura e nella zootecnia, le macchine e gli impianti per l’agricoltura di precisione.
Il curriculum 'Gestione del territorio montano' avrà invece insegnamenti orientati alla gestione digitale delle risorse idriche e del patrimonio forestale, al turismo, al monitoraggio ambientale e agli approvvigionamenti energetici.
Le conoscenze acquisite in entrambi i curriculum saranno sviluppate anche tramite esercitazioni pratiche di laboratorio e di campo, esercitazioni interdisciplinari effettuate fuori sede, attività seminariali e tirocini presso aziende di settore.
Gli studenti avranno la possibilità di esperienze all’estero, grazie alle convenzioni con Università internazionali già in essere per i corsi di laurea magistrale del DAFNE.
Il percorso di studi permetterà di partecipare all’esame di Stato per l’abilitazione alla professione di agronomo e dottore forestale, oppure per la successiva partecipazione alle scuole di dottorato di ricerca.
Lo studente espliciterà le proprie scelte al momento della presentazione,
tramite il sistema informativo di ateneo, del piano di completamento o del piano di studio individuale,
secondo quanto stabilito dal regolamento didattico del corso di studio.
GESTIONE DIGITALE DEL TERRITORIO MONTANO
FIRST YEAR
First semester
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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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Language
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119413 -
Fundamentals of digital engineering applied to agriculture
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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.
Learning skills 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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6
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ING-IND/12
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48
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-
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-
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-
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Related or supplementary learning activities
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ITA |
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-
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.
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6
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ING-IND/31
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48
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-
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-
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-
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Related or supplementary learning activities
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ITA |
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119466 -
Innovation in the management of phytosanitary issues
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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.
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3
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AGR/11
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24
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-
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-
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-
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Core compulsory activities
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ITA |
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-
Patologia
(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.
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3
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AGR/12
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24
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-
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-
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-
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Core compulsory activities
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ITA |
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119414 -
Digital techniques in agriculture
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Tecniche agronomiche di precisione
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Also available in another semester or year
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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.
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6
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AGR/03
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48
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-
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-
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-
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Core compulsory activities
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ITA |
Second semester
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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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Language
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119414 -
Digital techniques in agriculture
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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
|
|
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 |
|
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
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8
|
|
64
|
-
|
-
|
-
|
Elective 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
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Laboratory Hours
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Personal Study Hours
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Type of Activity
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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 |
|
119419 -
Digital tourism management
(objectives)
The aim of the Digital Tourism Management course is to accompany the class on a journey of knowledge of the state of the art of digital strategies in the tourism sector. A particular focus will be on digital strategies for incoming tourism in mountain environments.
Knowledge and understanding The course aims to develop in students knowledge and understanding regarding: • the historical evolution of the main tourism practices; • the new trends and practices of digital tourism; • the opportunities offered by the PNRR for the development of tourism 4.0; • tourism promotion strategies in the digital age; • tourism as a driving force for the relaunch of internal and mountain areas.
Ability to apply knowledge and understanding The course will allow students to use the knowledge acquired to: • describe the dynamics that characterize the tourism universe at local, national and international level; • hypothesize digital solutions suitable for the mountain environment; • design and implement an effective tourism communication campaign through digital tools.
Autonomy of judgment Students must be able to independently evaluate: • the strengths and weaknesses of a constantly evolving world; • any critical issues in governance in terms of digitalization; • the relationships and interactions between the issues of competitiveness and sustainability.
Communication skills The course will facilitate the development and application of communication skills, such as: • the ability to present a final report to an external audience; • the ability to use appropriate and up-to-date technical vocabulary; • the ability to work in a team.
Learning skills At the end of the course, students will have consolidated their learning skills, learning to: • independently identify ways to acquire information; • identify and use the most useful sources of information for personal development.
|
6
|
SPS/10
|
48
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
119484 -
Digital management of forest and water resources
|
|
|
-
Digital management of water resources
|
Also available in another semester or year
|
|
-
Digital forest management
(objectives)
The course aims to address the fundamental principles of sustainable forest management and the role of digital management in monitoring and analyzing forest as a support to the actions needed to achieve environmental sustainability objectives. After these premises, the course aims to develop skills in the management of forest geospatial data, including the collection, organization, manipulation and integration of data from different sources. Acquire knowledge of geomatics technologies used for the digital management of forest landscapes, including geographic information systems (GIS), remote sensing, GNSS and 3D modeling. Apply geomatics methods for the analysis and monitoring of forest consistency, including the assessment of forest composition and structure, tree species distribution and identification of habitats of community importance. Learn to use geospatial data and remote sensing techniques to assess the health status of forests, including the identification of insect infestations, forest diseases and fires.
Knowledge and understanding The course aims to develop in students’ knowledge and understanding skills, such as: • know and understand which technologies are useful for the analysis of forest systems for applications such as forest inventory; • know and understand the techniques and technologies that can be used to analyze the spatial and temporal variability of forest ecosystems, by exploiting change detection and time series analysis based on the use of multispectral indices; • know and understand the methods of development and application of forest geomatics techniques (precision forestry) for sustainable forest management.
Applied knowledge and understanding The course will allow to apply knowledge and understanding, allowing the student to: • know and use the main digital systems of proximal sensing for the inventory of forest resources and the acquisition of ground truth; • know and use the main sensors on board satellite, aerial, drone and terrestrial platforms suitable for precision forestry; • know and use cloud-based platforms for the analysis of the temporal and spatial variability of forest ecosystems; • know and use the techniques for the implementation of forecasting models and spatially explicit estimation of the main attributes of forest ecosystems; • know and use the techniques for mapping and estimating the severity of forest fires.
Making judgements The course will allow to develop critical sense and the ability to independently formulate judgments at various levels, such as: • hypothesize monitoring protocols and types of sensors to be used for the inventory of forest resources; • identify the factors limiting forest growth and the main factors of forest degradation; • propose effective digital data management for the purposes of forest restoration efforts and sustainable forest management.
Communication skills The course aims at the development and application of communication skills, such as: • having the ability to explain the knowledge acquired in a simple and exhaustive way even to non-expert audiences; • being able to present original works and manuscripts using the Italian or foreign language in an appropriate and correct way; • using an appropriate and updated technical forestry vocabulary.
Learning skills The course aims to consolidate self-learning skills, allowing for example: • to activate a program of continuous updating of one's knowledge; • to independently identify the ways to acquire information; • to identify and use the most useful and reliable sources of information and data for personal professional purpose; • to participate profitably in upgrade courses, masters, seminars, etc.
|
6
|
AGR/05
|
48
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
119428 -
Training
|
2
|
|
50
|
-
|
-
|
-
|
Other activities
|
ITA |
Second semester
|
Course
|
Credits
|
Scientific Disciplinary Sector Code
|
Contact Hours
|
Exercise Hours
|
Laboratory Hours
|
Personal Study Hours
|
Type of Activity
|
Language
|
|
119467 -
Environmental quality monitoring
(objectives)
The course aims to provide students with knowledge about the main natural and anthropogenic factors capable of influencing environmental balances in a context of climate change and sustainable development. The course will delve into the environmental dynamics that define the natural balances between soil, water, and air, as well as the indicators used to assess their quality.
Knowledge and understanding The course aims to develop students' knowledge and understanding, particularly regarding environmental quality monitoring. This includes understanding the techniques for monitoring environmental quality by first deepening their knowledge of the quality characteristics of soil, air, and water systems. A fundamental aspect is understanding the limits of application or interpretation of various quality indicators in relation to the reference system or environmental situation in which they are applied. The course also intends to provide adequate knowledge of the nutrient dynamics in the soil (nitrogen, phosphorus, and sulfur cycles) and the organic matter cycle. Additionally, the course will explore the effects of significant pollutants, such as heavy metals, the environmental issues related to their presence in the environment, and remediation strategies.
Applied knowledge and understanding The course enables the application of knowledge by developing practical laboratory skills and the ability to derive information from laboratory activities to support and integrate theoretical lessons.
Making judgements The course fosters the development of students’ autonomy in assessing soil, water, and air quality, and integrating various systems to define environmental quality. This is achieved through understanding the fundamental chemical and physical characteristics of soil, air, and water, as well as the natural and anthropogenic factors that have caused imbalances in these characteristics, leading to environmental degradation and quality loss.
Communication skills The course provides the ability to present acquired knowledge using appropriate language and technical terms.
Learning skills To improve their learning abilities, it is essential for students to attend lessons and independently utilize the provided materials. This approach supports continuous knowledge updating, allowing students to identify the most effective strategies for gathering information. Furthermore, it is crucial to develop the ability to independently update one's knowledge by conducting keyword searches and consulting texts, bibliographic databases, and significant scientific publications at both national and international levels.
|
6
|
AGR/13
|
48
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
119420 -
Energy supplies
(objectives)
The course aims to describe energy sources, their conversion and transformation, their use and rationalization. Once the primary and secondary forms of energy have been introduced, attention is focused on conservation principles applied to energy systems. Then conventional steam power plants are studied, followed by gas turbines, and internal and external combustion engines used as energy systems. Renewable power plants and direct conversion power plants are discussed. The final and rational use of energy, recovery and energy saving are also studied. Furthermore, the course will allow the acquisition of basic multidisciplinary skills to design, build and use economic analysis models of energy plants and systems so as to be able to evaluate the performance and applications of different energy systems, being also able to compare the specificity of each system and choose the best coupling solution between a given energy end use and the available energy conversion systems. The objectives of the course according to the Dublin descriptors are as follows:
Knowledge and understanding Understand the fundamental principles of energetics from a technical and economic point of view.
Applied knowledge and understanding Through the development of case studies, the student will be encouraged to develop an application capacity on the methodologies and techniques acquired.
Making judgements Being able to apply the acquired knowledge to solve simple and non-simple problems thanks to the multidisciplinary knowledge obtained.
Communication skills Being able to explain, both in written and oral form, the problem and possible solutions to simple situations concerning energy supply.
Learning skills Knowing how to collect information from textbooks and other materials for the autonomous solution of problems related to energy supply.
|
6
|
ING-IND/08
|
48
|
-
|
-
|
-
|
Related or supplementary learning activities
|
ITA |
|
119484 -
Digital management of forest and water resources
|
|
|
-
Digital management of water resources
|
6
|
AGR/08
|
48
|
-
|
-
|
-
|
Core compulsory activities
|
ITA |
|
-
Digital forest management
|
Also available in another semester or year
|
|
119429 -
Final test
|
20
|
|
375
|
-
|
-
|
-
|
Final examination and foreign language test
|
ITA |
Teachings extracurricular:
(hide)
|
|
|
|
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 |
|
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 |
|
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 |