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McDermott, Audrey Ann (2017) Genetics of milk protein composition and milk colour in irish dairy cattle. [Tesi di dottorato]

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Abstract (inglese)

The overall aim of this thesis was to determine the feasibility of breeding for improved milk quality and in particular protein fractions, free amino acids (FAA) and milk colour. To breed for a characteristic such as milk quality it must be; (i) economically or socially important (ii) exhibit genetic variation (i.e be heritable), and (iii) be measurable or genetically correlated with a measurable trait. Gold standard data was determined from 715 milk samples. Spectral data used consisted of ~ 95,000 milk samples from seven research herds and ~ 40,000 milk samples (morning and evening milk samples combined) from 69 commercial herds. The greatest correlation coefficients of external validation obtained for protein fractions, FAA and milk colour were 0.74 (total casein), 0.75 (glycine) and 0.72 (yellowness), respectively. Milk protein fractions and FAA change across calendar months of the year, stage of lactation and parity. A peak in the concentration of all casein fractions was evident in the months of August, September and October. The concentration of glutamic acid was greatest during the months of February, March, April and June when adjusted for milk yield. Changes in individual milk protein fractions and FAA across calendar months of the year and across stages of lactation could provide useful input parameters for decision support tools in the management of product portfolios by processors over time. Heritability of the predicted protein fractions and FAA ranged from 0.04 (beta casein) to 0.61 (total lactoglobulin) and from 0.05 (aspartic acid) to 0.58 (serine), respectively. The coefficient of genetic variation of gold standard protein fractions and FAA ranged from 3.01 (alpha lactalbumin) to 22.98 (total lactoglobulin) and from 1.01 (glutamic acid) to 25.65 (serine), respectively. Milk colour traits were low to moderately heritable ranging from 0.29 (lightness) to 0.35 (yellowness), respectively. The coefficient of genetic variation of milk colour ranged from 0.37 (lightness) to 1.72 (greeness), respectively. Results from this thesis clearly show that some protein fractions, some FAA and milk colour are predictable from MIRS and these predictions exhibit genetic variation and thus breeding for improved milk quality is feasible. The outcome of this thesis is primarily that the prediction of these traits by MIRS could benefit the dairy breeding industry worldwide through genetic selection of animals with higher quality milk and allowing for the more accurate selection of milk for human consumption, infant milk formula, and cheese production. The generated predictions could also be useful for herd and processor management strategies.

Abstract (italiano)

L’obiettivo generale della presente tesi è stato quello di determinare la possibilità di poter migliorare, tramite programmi di selezione genetica, la qualità del latte e in particolare le frazioni proteiche, gli amino acidi liberi (FAA) e il colore. Per essere migliorato geneticamente un carattere (incluso la qualità del latte) deve: i) essere di importanza, sia essa economica o anche sociale; ii) esibire variabilità genetica, ossia deve essere ereditabile; iii) essere misurabile o correlato geneticamente con un carattere che sia
misurabile. Le analisi di riferimento per i suddetti parametri di qualità del latte sono state determinate su 715 campioni di latte. Il dataset di spettri includeva misurazioni infrarosse su circa 95 000 campioni di latte raccolti in sette aziende sperimentali, mentre altri circa 40 000 spettri (determinati su campioni di latte di entrambe le mungiture giornaliere) erano provenienti da 69 aziende commerciali. I più alti coefficienti di correlazione, in validazione esterna, ottenuti per frazioni proteiche, FAA e colore del latte sono stati rispettivamente di 0.74 (caseine totali), 0.74 (glicina) e 0.72 (indice del giallo). Le frazioni proteiche del latte e gli FFA hanno dimostrato variazioni tra mesi dell’anno, tra stadi di lattazione e tra ordini di parto. Un picco nella concentrazione di tutte le frazioni caseiniche è stato evidente nei mesi di Agosto, Settembre ed Ottobre. La concentrazione di acido glutammico è stata maggiore nei mesi di Febbraio, Marzo, Aprile e Giugno a parità di produzione di latte giornaliera. Le variazioni di frazioni proteiche e FAA attraverso mesi dell’anno e stadi di lattazione possono fornire all’industria di trasformazione lattiero-casearia uno strumento per gestire il proprio portafoglio prodotti lungo uno specifico periodo produttivo. I valori di ereditabilità dei fenotipi predetti hanno avuto un minimo di 0.04 (beta caseina) ed un massimo di 0.61 (lattoglobulina totale) per le frazioni proteiche, mentre per quanto riguarda gli FAA hanno variato tra 0.05 (acido
aspartico) e 0.58 (serina). Il coefficiente di variazione genetico per frazioni proteiche misurate ha variato tra 3.01% (alfa lattoalbumina) e 22.98% (lattoglobulina totale), mentre per gli FFA misurati ha variato tra 1.01% (acido glutammico) e 25.65% (serina).
Il caratteri di colore del latte hanno dimostrato una ereditabilità medio-bassa, con un range compreso tra 0.29 (luminosità) e 0.35 (indice del giallo). Il coefficiente di variazione genetico del colore del latte ha avuto un minimo di 0.37% (luminosità) ad un massimo di 6.68% (indice del giallo). I risultati della presente tesi dimostrano chiaramente che alcune frazioni proteiche, alcuni FAA e il colore del latte sono di possibile predizione attraverso la tecnologia nel medio-infrarosso, e tali fenotipi predetti hanno variabilità genetica il che implica che programmi di selezione per migliorare la qualità del latte sono possibili. I risultati principali di questa tesi sono che le predizioni di questi caratteri usando la spettroscopia nel medio infrarosso possono rappresentare un beneficio per gli allevatori di vacche da latte attraverso la selezione genetica di animali con una migliore qualità del latte. Inoltre, questa tesi offre delle opportunità per una selezione più accurata del latte destinato al consumo umano, alla produzione di latte per neonati e alla produzione di formaggio. Inoltre, tali predizioni possono rappresentare dlle opportunità per il management aziendale e industriale.

Tipo di EPrint:Tesi di dottorato
Relatore:De Marchi , Massimo - McParland, Sinead
Dottorato (corsi e scuole):Ciclo 29 > Corsi 29 > SCIENZE ANIMALI E AGROALIMENTARI
Data di deposito della tesi:18 Luglio 2017
Anno di Pubblicazione:18 Luglio 2017
Parole chiave (italiano / inglese):MILK PROTEIN COMPOSITION, NIRS, IRISH DAIRY CATTLE, MILK COLOUR
Settori scientifico-disciplinari MIUR:Area 07 - Scienze agrarie e veterinarie > AGR/19 Zootecnica speciale
Struttura di riferimento:Dipartimenti > Dipartimento di Agronomia Animali Alimenti Risorse Naturali e Ambiente
Codice ID:10442
Depositato il:16 Nov 2018 09:02
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