Composition of living matter: carbohydrates, fats, proteins, minerals and vitamins. Feed behaviour of wildlife species. Ruminal fermentation. Nutrient metabolism. Characteristics and use of forages and concentrates. Nutritional requirements. Population genetics. Genetic diversity. Probability and statistics. Relationship and inbreeding. Analysis of genetic variability. Threats to diversity.
Bittante G., Andrighetto I., Ramanzin M. - Fondamenti di zootecnica. Liviana, Padova 1990.
Ferragutti M. Castellacci C. Evoluzione. Modelli e processi. Pearson ed. 2011.
Campbell A.N., Reece J.B. Principi di Biologia. Pearson Ed. 2010.
Additional material provided by the teacher
Principles of feeding and nutrition for wildlife species. Chemical composition, quality and use of the main feedstuffs. Principle of evolution and genetics applied to animal science.
Estimation of requirements of animals and nutritive values of feedstuffs.
Planning of feeding schemes.
Knowledge of modern practices of genetics and evolutionary biology.
Skills acquired (at the end of the course): Students should be able to realize feeding plans for the animal species and to estimate the main genetic parameters of a population.
Courses recommended: Organic chemistry, Wildlife morphology and physiology
Number of credits: 9
Total hours of the course (including the time spent in attending lectures, seminars, private study, examinations, etc...):: 9*25=225
Hours reserved to private study and other individual formative activities:153
Contact hours for: Lectures (hours): 48
Contact hours for: Laboratory-field/practice (hours): 18
Seminars (hours): 6
Frequency of lectures, practice and lab: although not compulsory, it is strongly recommended
Video projector, PC, overhead projector, experimental farms, labs, informatics room
Type of Assessment
Exam modality: Oral examination on the subjects of lectures and practices.
Importance and role of animal nutrition. Composition of vegetal and animal living matter: carbohydrates, fats, proteins, minerals and vitamins. Chemical analyses of feedstuffs and fibrous fractions. Feed behavior of wildlife species. Ruminal fermentation of carbohydrates and proteins, protein/energy ratio. Metabolism of nutrients. Energy distribution: GE, DE, ME, Net E. Energy evaluation of feedstuffs: Meat FU and Milk FU. Protein metabolism and evaluation of protein: P.D.I. Forages: harvest forms; pasture, hay, silage. Concentrates and by-products. Nutrient requirements of the main livestock species.
Origins of genetics; the birth of population genetics; the purpose of population genetics; mathematical models in population genetics; the arrival of molecular biology; the evolutionary forces. Heterozygosity and genetic variability; genetic diversity and Coalescent; effective population; probability of fixation and replacement rate; non-neutral forces; Association among loci; demografic factors; genetic and environmental phenomena; polygenic hypothesis; models; heritability; the molecular revolution; candidate genes and mapping by association. The probability in evolution; classical probability; populations and samples; frequency distributions; normal distribution; statistical test; analysis of variance; regression analysis; Bayesian probability. Kinship; consanguinity; basic measures of kinship; calculation of additive kinship and consanguinity; variability of the populations; family link on a molecular basis. Restriction enzymes; RFLP; the advent of PCR; PCR and cDNA; microsatellites; single nucleotide polymorphisms (SNPs); DNA sequencing; phylogenetic reconstruction methods. Speed of extinction; causes of extinction; vulnerability to extinction. Minimum viable population; loss of genetic variation in small populations; actual size of population; demographic fluctuations, extinction vortexes; monitoring of populations; population viability analysis.
Feedstuffs chemical analysis following Weende, van Soest. Ruminant and monogastric rations. Farm visits. Data management in wildlife sciences. Descriptive statistics. Common software (text editor – spreadsheet – dbase). Data base creation. Allele Frequency measure. Chi-Square analysis. Graphical representation of data. Analysis of variance and group comparison. Molecular analyses.