MATHEMATICAL AND STATISTICAL MODELS FOR PRECISION AGRICULTURE AND PRECISION LIVESTOCK FAMING

Single discipline educational activity

Course Sheet

Academic Year of enrolment:

2020/2021

Type of Course:

Related/Supplementary

Optional/Mandatory:

Optional

Degree:

Master's Degree Programme in AGRICULTURAL SYSTEMS

Disciplinary Sector:

General Techniques for Zoology and Genetic Improvement

Language:

Italian

Credits:

Programme Year:

Professor and Collaborators:

MACCIOTTA Nicolo' Pietro Paolo

Obligatory attendance:

Yes

Minimum hours of attendance:

Hours of classroom activity:

Prerequisites:

Students should know algebra and the Euclidean geometry. The knowledge of elements of trigonometry is also required.

AF code:

A001649

Assessment Methods

Verification of learning:

WRITTEN TEST
Evaluation of the ability of intepretation and analysis of generated in the in agro-zootechnical industry
(25% of final evaluation)

LAPTOP TEST
Evaluation of the ability to use the integrated scientific approach in agriculture using computer technology technology
(50% of final evaluation)

ORAL EXAM
Evaluation of konewledge on the use of “big data” in agro-zootechnical precision farming systems and of generating scientific and technical reports
(50% of final evaluation)

Teaching period

First semester

Objectives

The course is aimed at providing mathematical and statistical tools for studying and interpreting data generated from precision farming instruments. Moreover, mappraches for handling big data will be presented.

Contents

Basic programming in R.
Data description using plots and tables; measures of center and dispersion. Main probability distributions. (1 CFU)

Statistical inference: parameter estimation and hypothesis testing. (1 CFU)

Concepts of modelling. The linear model. Mean and proportion comparisons. Analisis of variance. Linear regression. (2 CFU)

Elements of multivariate statistics. (2 CFU)

Handling of data generated from precision farming: food spectral analysis, production and managemetn data of farms, climate data (1 CFU)

Recommended Bibliography

book: aa.vv. "Elementi di statistica d base per le scienze zootecniche"

Slides
Course notes

Methods of Provision

Conventional

Teaching Methods

Theoretical lessons.
Practice on real and simulated data using laptop and R software
Visits on farm

Contacts/More Information

The course will be developed using the R software

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MATHEMATICAL AND STATISTICAL MODELS FOR PRECISION AGRICULTURE AND PRECISION LIVESTOCK FAMING