1,721,210 research outputs found
Survival analysis as a statistical methodology for analyzing factors that affect milk coagulation time in Holstein-Friesian and Brown Swiss cows
No full textThe aim of this study was to propose the survival analysis technique as a statistical approach for the analysis of rennet coagulation time (RCT) able to make use of coagulating and noncoagulating (NC) milk information in order to estimate potential sources of variations that affects RCT. A total of 1,025 Italian Holstein-Friesian cows (HF; progeny of 54 sires) and 1,234 Brown Swiss cows (BS; progeny of 58 sires) reared in 34 and 38 herds, respectively, were milk-sampled once. Rennet coagulation time was analyzed with a semiparametric proportional hazard model (i.e., a Cox model), with the NC samples considered as censored records. Furthermore, a different censoring scenario, with a new end point at 18 min, was considered after the rearrangement of the time space originally used for the observation of RCT. The percentage of NC samples was almost 10% for HF and 3.5% for BS cows in in the 31 mm set, whereas it increased to 44 and 24.9%, respectively, in the 18 min set. Estimated hazard ratios indicated that the most important factors affecting the coagulation process were herd, days in milk, casein number, and milk acidity (expressed in terms of titratable acidity) for both HF and BS, whereas the SCS was relevant only for BS. The survival model seems to be particularly suitable for this analysis, as it can properly account for censored and uncensored records and appropriately use all available information. Moreover, this methodology allows us to rearrange the time space used for the observation of RCT and to define alternative traits (i.e., RCT with an end point at 18 min). Our restriction of the time space and the increased percentage of censored records did not highlight any substantial differences in terms of the risk of coagulating with respect to the traditional 31 mm testing time. Although further research is needed to investigate the effect of these sources of variation on cheese yield, our results indicate that casein number, acidity, and SCS may be used as indicator traits for enhancing the technological properties of bovine milk
Analysis of piglet survival in a dry-cured ham-producing crossbred line
Full text linkPiglet death during the perinatal and lactation periods is one of the most detectable causes of reduced production efficiency in swine herds. and it has also been identified as an important welfare issue. Piglet mortality within the first three days of life is still a problem in intensive farms. Mortality rates vary between 10 and 20% depending on the housing system. Data used in this study were collected in the nucleus and sib testing program of the C21 Large White boar line (Gorzagri, Fonzaso, Italy) from 2000 to 2006. In the selection nucleus farm (Riese Pio X, Italy) the pure C21 boars are produced and mated to pure C21 sows, while in a sib testing program farm (Todi, Italy), the same C21 boars are mated to crossbred sows to produce crossbred piglets. The general aim of this thesis was to explore the genetic aspects of piglet survival in the aforementioned dry-cured ham-producing crossbred line. In chapter 2 the piglet pre-weaning survival and its relationship with a total merit index (TMI) used for selection of Large White terminal boars for dry-cured ham production was investigated. Piglet pre-weaning survival was analyzed under a frailty proportional hazards model, assuming different baseline hazard functions and including sire and nursed litter as random effects. Estimated hazard ratios (HR) indicated that sex, cross-fostering, year month of birth, parity of the nurse sow, size of the nursed litter and class of TMI were significant effects for piglet pre weaning survival. Female piglets had less risk of dying than males (HR = 0.81) as well as cross-fostered piglets (HR = 0.60). Survival increased when piglets were nursed by sows of third (HR = 0.85), fourth (HR = 0.76) and fifth (HR = 0.79) parity. Piglets of small (HR = 3.90) or very large litters (HR > 1.60) had less chances of surviving in comparison with litters of intermediate size. Class of TMI exhibited an unfavorable relationship with survival (HR = 1.20 for the TMI top class). The modal estimates of sire variance under different baseline hazard functions were 0.06 whereas the variance for the nursed litter was close to 0.7. The estimate of the nursed litter effect variance was higher than the sire, underlying the importance of the common environmental generated by the nurse sow. The relationships between sire ranking obtained from different survival models highly agreed each others. The heritability estimate in equivalent scale was low (0.03).
Nevertheless, the exploitable genetic variation for this trait justifies the inclusion of piglet pre-weaning survival in the current breeding program for selection of Large White terminal boars for dry-cured ham-production.
In order to evaluate the opportunity of including the survival trait in such breeding programme, the relevance of purebred information for predicting genetic merit of survival at birth of crossbred piglets was assessed (chapter 3). A question is whether purebred performance (in the nucleus) predicts accurately outcomes in crossbreds (commercial tier). This was investigated by considering the two performances as different traits in a model and by estimating the genetic correlation. The objective of chapter 3 was to infer (co)variance components for farrowing survival in purebred (P) and crossbred (C) pigs; the latter were from crosses between P boars and Large White-derived crossbred sows. If the genetic correlation between C and P traits is large enough, selection in P would produce a correlated response in C. Data were from 13,643 (1,213 litters) C and 30,919 (3,162 litters) P pigs, produced by mating the same 168 P boars to 319 Large White derived crossbred females and 1,413 P sows, respectively. The outcome variable was pig survival at birth as a binary trait. A Bayesian bivariate threshold model was implemented via Gibbs sampling. Effects of sex, parity of the dam, litter size and year-month of birth were assigned flat priors; those of litters, dams and sires were given Gaussian prior distributions. Marginal posterior means (SD) of the sire, dam and litter variances in P were 0.018 (0.008), 0.077 (0.020), 0.347 (0.025), respectively in the liability scale. For C, corresponding estimates were 0.030 (0.018), 0.120 (0.034), and 0.189 (0.032), respectively. The posterior means (SD) of heritability of survival in P and C, and of the genetic correlation between these traits were 0.049 (0.023), 0.091 (0.054) and 0.248 (0.336), respectively. Heritability estimates were low and in agreement with previous reports. The genetic correlation was also low, and a 95% Bayesian confidence region (-0.406, 0.821) included zero. Even though variation of estimates is large, results suggest that genetic progress expected in C when selection is based on P may be nil.
In chapter 4 different methodologies (proportional hazard, threshold and sequential threshold model) for predicting genetic merit of piglet survival were compared in terms of predictive ability and goodness of fit. Data structure was the same used in chapter 3. A frailty proportional hazard model, assuming two different baseline hazard function (Cox and Weibull) and including sire and nursed litter as a random effects were fitted. The threshold and sequential threshold model considered the same effects. Model fitting was evaluated in terms of goodness-of-fit and predictive ability, using the mean square error as reference parameters. Estimated sire variances for piglet pre-weaning mortality were low, and heritability ranged from 0.04 to 0.06. All four models led to similar ranking for sires, with strong correlation between methods. The sequential threshold model had a better performance for predicting piglet survival but it had a lower performance in terms of goodness-of-fit than Cox model. Results from this study suggest that sequential threshold model may, globally, be better than other methods tested, both for its better predictive ability of piglet survival in genetic evaluations and for its easier interpretation. Further, sequential threshold model is computationally less demanding and can be extended to allow for different variance components by different period from birth to weaning.Gli obiettivi del moderno allevamento suinicolo mirano principalmente a garantire buone performance in termini produttivi e costi di produzione contenuti. Il controllo della mortalità neonatale rappresenta una delle tematiche più attuali, proprio per gli importanti riflessi sul bilancio aziendale. Attualmente, il tasso di mortalità totale sino allo svezzamento può variare dal 18 al 20% sia per la realtà europea che statunitense. Il numero di suinetti annualmente partoriti da una scrofa è probabilmente considerato il carattere riproduttivo più importante, in grado di condizionare il management aziendale e spesso, per tali motivazioni, l’unico ad essere considerato nei programmi di miglioramento genetico di linee suine. In realtà, gli indubbi miglioramenti ottenuti relativamente a questo aspetto sono spesso vanificati da peggioramenti nella capacità di sopravvivenza del suinetto, sia al parto che durante la fase di allattamento.
I dati utilizzati in questa tesi sono stati raccolti presso il nucleo di selezione Gorzagri, sito a Riese Pio X (TV, Italia) e il centro genetico, sito a Todi (PG, Italia) e dedicato al programma di sib-testing della linea verri C21. L’attività del centro è finalizzata alla produzione di famiglie di suinetti ibridi, originati dall’accoppiamento di verri C21 e scrofe ibride Goland. Questi suinetti, di costituzione genetica identica all’ibrido Gorzagri allevato negli allevamenti commerciali, producono le informazioni necessarie per la stima del valore genetico e successiva selezione dei verri e scrofe della linea C21. La linea verri C21 è oggetto di attività di selezione secondo obiettivi finalizzati al miglioramento delle performances di allevamento e dell’attitudine alla produzione del prosciutto crudo stagionato DOP. Obiettivi selettivi sono il miglioramento dell’attitudine alla trasformazione industriale della carcassa e della coscia, particolarmente in relazione alla copertura di grasso della coscia e alla sua qualità (numero di iodio e acido linoleico) e alla presenza di difetti della stessa quali la globosità ed il grado di marezzatura della carne. Inoltre, lo schema selettivo mira all’ottenimento di animali omogenei in termini di accrescimento al fine di permettere un’ottimale organizzazione produttiva all’interno degli allevamenti.
Recentemente, anche la capacità di sopravvivenza e la robustness del suinetto sono divenuti oggetto di interesse selettivo. I dati di mortalità dei suinetti sino allo svezzamento sono stati raccolti sia presso il nucleo di selezione che presso il centro genetico di Todi a partire dal 2000. Nel primo contributo i dati di sopravvivenza dei suinetti fino allo svezzamento rilevati presso il centro genetico di Todi, sono stati analizzati utilizzando un modello dei rischi proporzionali e testando diverse baseline hazard function. Il tempo di sopravvivenza del suinetto, considerato come l’intervallo tra la nascita e lo svezzamento, è stato analizzato prendendo in esame gli effetti sistematici dovuti al sesso, messa a balia, mese-anno di nascita, ordine di parto della scrofa allattante, dimensione della nidiata e classi di indice genetico standardizzato dei verri. Quest’ultimo si è reso indispensabile per poter apprezzare le relazioni intercorrenti tra obiettivi di selezione della linea verri C21 attualmente perseguiti e sopravvivenza della progenie; nel modello sono stati inclusi anche gli effetti casuali della nidiata e la componente genetico additiva del verro. La mortalità in allattamento dei suinetti ibridi Goland si è attestata intorno al 14% con un tempo di morte medio pari a 6 giorni. L’effetto del sesso è risultato essere un fattore rilevante sulla mortalità in allattamento: le femmine hanno una probabilità di morire del 20% in meno rispetto alla classe di riferimento (maschi). Lo spostamento a balia ha anch’esso un effetto significativo sulla mortalità in allattamento. I soggetti trasferiti dalla madre “biologica” ad una balia presentano una probabilità di morire del 40% inferiore rispetto ai suinetti non spostati (classe di riferimento). Tali risultati confermano l’importanza di questa pratica manageriale, che porta ad una significativa riduzione della mortalità neonatale. Considerando il fattore “ordine di parto della balia”, si è osservato come i suinetti allattati principalmente da balie primipare abbiano manifestato una probabilità di morire superiore rispetto ai suinetti allattati da pluripare. In particolare, si è potuta osservare una diminuzione del rischio di morte fino al quarto ordine di parto, per il quale il rischio di morte si attestava attorno al 75% di quello che caratterizza suinetti nati da scrofe di secondo ordine di parto (considerate in questo caso come riferimento).
Considerando la dimensione della nidiata, è stato possibile constatare che la probabilità di morire aumenta in modo significativo per i suinetti allattati in nidiate di dimensioni ridotte (inferiore a 5 suinetti) oppure molto numerose (superiore ai 15 suinetti) rispetto alla classe di riferimento che in questo caso è rappresentata da nidiate costituite da 9-11 suinetti. Nidiate molto numerose comportano una maggiore competizione tra i suinetti per la mammella (difficoltà ad assumere il colostro) e sovraffollamento con maggiore possibilità di schiacciamento. Per quanto riguarda le nidiate di dimensioni ridotte queste sono state osservate, generalmente, in scrofe che hanno avuto una gestazione non regolare.
L’effetto dell’anno e della stagione di nascita è risultato essere un effetto altamente significativo, imputabile a fattori di natura climatica, epidemiologica e manageriale esistenti tra il 2000 ed il 2006. Per quanto riguarda l’indice genetico standardizzato dei verri, da questo studio è emerso che i verri con un indice di merito genetico globale superiore rispetto alla media di popolazione, hanno generato progenie, nel corso degli anni oggetto di studio, con un rischio di morte pre-svezzamento superiore a quelli con indice inferiore rispetto alla media di popolazione.
Per quanto riguarda la stima della variabilità genetico additiva indotta dal verro e quella ambientale permanente indotta dalla nidiata sulla capacità di sopravvivenza del suinetto, è emerso che l’effetto della nidiata ha una rilevanza maggiore rispetto a quella del verro e mette in evidenza l’importanza dell’effetto ambientale esercitato dalla scrofa allattante. L’ereditabilità stimata per la sopravvivenza è risultata bassa (0.03), in accordo con stime di ereditabilità reperite in bibliografia. Tuttavia la variabilità genetica associata a questa caratteristica è risultata molto elevata e di grado tale da permettere interventi specifici di miglioramento dei verri appartenenti alla linea C21.
I risultati ottenuti nell’ambito del presente lavoro sottolineano che la selezione per la diminuzione della mortalità dei suinetti in allattamento può essere perseguita attraverso l’inclusione della capacità di sopravvivenza del suinetto negli obiettivi di selezione della linea C21.
Al fine di testare la possibilità di includere il carattere “sopravvivenza” tra gli obiettivi di selezione della linea verri C21, nel secondo contributo si è proceduto alla valutazione dell’importanza delle informazioni fenotipiche provenienti dal nucleo di selezione Gorzagri per la stima del valore riproduttivo della sopravvivenza alla nascita dei suini ibridi allevati presso il centro genetico. Obiettivo specifico di questo lavoro è stato quello di stimare le correlazioni genetiche tra sopravvivenza alla nascita dei suini puri e sopravvivenza alla nascita dei suini ibridi, originati dai medesimi verri della linea pura, in modo da testare la possibilità di introdurre metodologie selettive CCPS (combined crossbred and purebred selection). La stima della correlazione genetico additiva permette di quantificare, in parte, l’entità dell’interazione genotipo – ambiente degli animali allevati presso strutture differenti. Lo studio è stato condotto su 30,919 (3,162 nidiate) suini di linea pura e 13,643 (1,213 nidiate) suini ibridi. Gli animali di linea pura sono stati generati da 168 verri C21 e 1,413 scrofe C21 di linea pura. I suini ibridi, allevati presso il centro genetico di Todi, sono stati generati impiegando gli stessi 168 verri e 319 scrofe ibride di derivazione Large-White. Il carattere analizzato è stato la sopravvivenza alla nascita come carattere categorico (vivo o morto). Per la stima dei parametri genetici è stato fittato un modello statistico bivariato a soglie (threshold model) utilizzando un approccio Bayesiano. Il modello statistico ha considerato l’effetto del sesso, dell’ordine di parto della scrofa, della dimensione della nidiata e l’anno mese di nascita dei suinetti. Per la stima dei parametri del modello sono state adottate, per gli effetti “fissi”, delle flat priors, mentre per l’effetto della nidiata, della scrofa e la componente genetico additiva del verro, sono state adottate delle Gaussian prior distributions. La media della distribuzione marginale a posteriori della componente di varianza del verro, della scrofa e della nidiata nei suini puri è risultata pari a 0.018 (0.008), 0.077 (0.020), 0.347 (0.025), rispettivamente. Per quanto riguarda le stime delle componenti di varianza nei suini meticci, le stime sono risultate pari a 0.030 (0.018), 0.120 (0.034), and 0.189 (0.032), rispettivamente per la componete del verro, della scrofa e della nidiata. L’ereditabilità per sopravvivenza alla nascita nei suini puri e risultata pari a 0.049 (0.023) mentre quella dei meticci 0.091 (0.054). Per quanto riguarda la correlazione genetica tra questi due caratteri (sopravvivenza in soggetti puri e meticci) è risultata pari a 0.248 (0.336). Tuttavia, l’ampia variabilità di stima (95% Bayesian confidence region: -0.406 - 0.821) suggerisce che il progresso genetico atteso, quando la selezione è basata solamente soggetti puri, potrebbe essere nullo.
Nel terzo contributo sono state messe a confronto diverse metodologie per la stima del valore riproduttivo della sopravvivenza del suinetto durante la fase di allattamento. Il modello dei rischi proporzionali, assumendo due differenti baseline hazard function (Cox e Weibull), è stato comparato con un thershold e un sequential threshold model, in termini di capacità predittiva del modello (predictive ability) e di goodness of fit. Le stime di ereditabilità sono risultate basse per tutti e quattro i modelli e variabili tra 0.04 e 0.06. Inoltre le stime dei valori riproduttivi dei verri non hanno provocato sostanziali re-ranking dei riproduttori. Tuttavia in termini di capacità predittiva dei modelli, il sequential threshold model ha manifestato le migliori performance e proprio per questo motivo e per la sua facile interpretazione, potrebbe essere proposto come sistema di valutazione genetica da implementare all’interno del programma di selezione della linea verri C21
Genetic analysis of elbow and hip dysplasia in Italian population of Bernese Mountain dogs
No full textThe objective this study was to estimate genetic parameters for hip (HD) and elbow dysplasia (ED) in Italian Bernese Mountain dogs. Data included screening results provided by two different screen- ing centres of 2051 dogs (1223 females and 828 males) for HD and 1564 dogs (935 females and 629 males) for ED. Screening date ranged from 1995 to 2011 and from 1999 to 2011 for HD and ED, respectively. The outcome variables were: HD score, performed according to the official protocol of the Federation Cynologique Internationale (FCI) and based on a 5-class linear scoring system (from A to E); and ED score, performed according to the International Elbow Working Group (IEWG) protocol and based on a 4-class grading system (from grade 0 to grade III). The pedigree file was provided by the Italian Kennel club (ENCI) and included 5983 dogs. A Bayesian analysis was implemented via Gibbs sam- pling. Effects of sex, year-month of birth, age of the dog at screen- ing, the experience of the x-raying veterinarian and the screening centre were assigned flat priors; those of kennel and animals were given Gaussian prior distributions. Prevalence for HD (i.e. percent- age of hips scored C, D or E) was 15.9%, and prevalence for ED (i.e. percentage of elbows graded I, II or III) was 20.3%. Marginal poste- rior medians and the lower and upper bound of the 95% highest posterior density (HPD95) of heritabilities of HD and ED were 0.22 (0.13-0.33) and 0.16 (0.07-0.30), respectively. The genetic correla- tion between these two traits were 0.53 and the HPD95 did not include zero. These could ensures feasibility of selection pro- grammes aimed to reduce prevalence of skeletal diseases, provided that a regular screening program of Bernese Mountain dogs is per- formed
Genetic and environmental relationships of different measures of individual cheese yield and curd nutrients recovery with coagulation properties of bovine milk
No full textThe aim of this study was to elucidate the relationships between various cheesemaking-related traits, namely the well-known traditional milk coagulation properties (MCP), the new curd firming and syneresis traits, the cheese yield, and the curd nutrient recoveries or whey losses (all measured at the individual level). Data were obtained from 1,167 Brown Swiss cows reared in 85 herds. A 2-milk sample was collected once from each animal and assessed for 10 phenotypes related to changes in curd firmness (CF) over time, plus 7 cheesemaking traits. The CF-related traits included 4 traditional single-point lactodynamographic properties [rennet coagulation time (RCT, min); time to a CF of 20 mm, min; and the CF 30 and 45 min after rennet addition (a30 and a45, respectively)], 4 parameters used to model the 360 CF data recorded over time for each milk sample [the potential asymptotic CF at infinite time (CFP, mm); the CF instant rate constant, % × min-1; the syneresis instant rate constant, % × min-1; and the RCT obtained from modeling individual samples], and 2 traits calculated from individual equations [the maximum CF(CFmax, mm); and the time at CFmax, min]. The cheesemaking traits included 3 cheese yield traits (weights of the fresh curd, curd solids and curd moisture as percent of the weights of the processed milk) and 4 milk nutrient recoveries in the curd (calculated as the percent ratios between a given nutrient in the curd versus that in the processed milk). Bayesian methodology-based multivariate analyses were used to estimate the phenotypic, additive genetic, herd/date, and residual relationships between the aforementioned traits, whereas statistical inferences were based on the marginal posterior distributions of the parameters of concern. The a45, CFP, and CFmax traits were genetically associated with all of the percent cheese yield traits (the additive genetic correlations varied from 0.752 to 0.855 for a45; 0.496 to 0.583 for CFP; and 0.750 to 0.801 for CFmax) and the nutrient recovery traits (additive genetic correlations varied from 0.296 to 0.901 for a45; 0.428 to 0.697 for CFP; and 0.412 to 0.941 for CFmax). Moreover, the nutrient recoveries for fat, solids, and energy exhibited large additive genetic correlations with the other coagulation and curd firming traits. In particular, recovery of protein and fat were found to be powerful instruments for understanding the relationships between milk technological properties and cheese quantity or quality. We observed only weak genetic relationships with the milk quality and MCP traits, suggesting that the highly heritable trait of protein recovery should perhaps be included as a genetic index when seeking to improve cheesemaking efficiency at the population level. In contrast, we found that fat recovery exhibited moderate genetic variation and could be improved through the CF over time traits, especially using those recorded during the late phase of the curd firming process. Moreover, our results demonstrated that the traditional MCP have limited relevance for predicting individual cheese yield. Therefore, their use for this purpose in the dairy industry and breeding programs seems questionable
Genetic analysis of the Fourier-transform infrared spectra of bovine milk with emphasis on individual wavelengths related to specific chemical bonds
No full textFourier-transform infrared (FTIR) spectra are used to predict the fat, protein, casein, and lactose contents of milk. These estimates are currently used to predict the individual estimated breeding values of animals. The objective of the present study was to estimate the genetic variation and heritabilities of the milk transmittance spectrum at each individual FTIR wave. Milk was sampled once per cow from a total of 1,064 Italian Brown Swiss cows from 30 herds, sired by 50 artificial insemination sires. The FTIR spectra of all samples were collected within 3 h of sampling from 25 mL of milk. The obtained spectral range comprised wavenumbers 5,000 to 930 x cm(-1), corresponding to wavelengths 2.00 to 10.76 mu m and frequencies from 149.9 to 27.9 THz, for a total of 1,056 waves. These were acquired using a MilkoScan FT120 FTIR interferometer (Foss Electric A/S, Hillerod, Denmark). Each spectral data point was treated as a single trait and analyzed using an animal model REML method. The results indicated that the transmittance of the bovine milk FTIR spectrum was heritable for most individual waves in the wavenumber interval from 5,000 to 930 x cm-1. Moreover, the transmittance of contiguous FTIR waves was much more highly correlated in terms of the average value and phenotypic variation, compared with genetic variation. In the present study, we characterized 5 regions of the FTIR spectrum that were relevant to the analysis of milk; 2 regions, one in the transition area between the short-wavelength infrared (SWIR) and mid-wavelength infrared (MWIR) divisions of the electromagnetic spectrum (SWIR-MWIR region) and another very short region in the MWIR division (MWIR-2 region), were characterized by very high phenotypic variability in the transmittance of individual milk samples within each wave. This was caused by the absorption peaks of water, which can mask the effects of other important milk components. These regions also showed high genetic variability in transmittance, and the heritability estimates of individual waves were generally very low (with some exceptions). The 3 other identified regions contained many transmittance peaks that represented important chemical bonds; these showed much lower phenotypic and genetic variability in terms of individual waves, but relatively higher and less variable heritability estimates. Among them, the SWIR region (near-infrared) showed a peculiar cyclic pattern of the heritability coefficients of transmittance, the MWIR-1 region was particularly important for the estimation of fat, and the MWIR-LWIR region (also known also as the "fingerprint region") had 3 areas of relatively high heritability. In summary, we found that the transmittance data from the FTIR spectra of milk have genetic variability that may prove useful for the direct genetic improvement of dairy species, rather than only through indirect phenotypic predictions of individual milk quality and technological traits
Effect of feeding system on fatty acid profile of lambs of three Veneto Region Alpine breeds
No full textThe aim of this trial was to investigate the effect of diet, breed, gender and the tissue on the fatty acid (FA)
profiles of lambs of three native Italian sheep breeds. Thirty-six lambs, belonging to flocks subjected to an
in situ conservation program (Legnaro-Villiago), were used. Six males and 6 female lambs for each breed:
Alpagota, Brogna and Foza, were divided in three groups characterized by different feeding systems:
pasture, penned in an open barn and fed with hay and concentrate and penned in the open barn and fed with
hay and concentrate added with rpCLA supplement. At the age of 225 days the lambs were slaughtered,
samples of muscles, fatty depots and liver were collected and analyzed for FA profile. FA were extracted
and analyzed through GC. Data were analyzed by PROC MIXED of SAS considering the effect of the
feeding system, breed, gender, age and tissue. The random effect of animal was used to test feeding system,
breed, gender and age, whereas the effects of tissue and corresponding interactions were tested on the
residual. Among the factors of variation of FA profiles feeding system was the most important one because,
respect to the dry diets, pasture did not caused a variation of proportion among SFA, MUFA and PUFA,
but changed the proportion within SFA (C18:0;C18:1vaccenic), and PUFA (C18:2c9 t11 CLA; >C18:3 α
Linolenic; <C20:4n6 arachidonic), and decreased the omega6/omega3 ratio (3.28 vs. 6.17; P<0.0002). The
supplementation of rpCLA on barn diet increased both CLA isomers (C18:2c9, t11, P=0.010, and C18:2
t10, c12, P=0.018). The tissue was the most important within-animal cause of variation and affected all
the individual FA and their categories. Liver presented a FA profile very different from that of muscles and
fatty depots and, among these last tissues, kidney fat was very peculiar
379 ASAS-EAAP Talk: Precision Phenotyping using Infrared Spectroscopy to Improve the Quality of Animal Products
Full text linkThere is an ever-growing interest in research oriented towards the improvement of quality of animal products. In this context, one major operational bottleneck is the possibility to collect quality indicators over the meat and dairy chains and for selective breeding purposes. The use of near-infrared (NIR) and the Fourier-transformed infrared (FTIR) spectroscopy techniques have been proven to be powerful precision phenotyping tools for high-throughput meat and milk quality assessment. Such technologies allow scoring large number of animals and/or derived-products for novel (predicted) phenotypes and indicator traits to set-up potential new payment systems and boost the genetic improvement. One important step in the use of NIR and FTIR tools is the definition of the “gold standard” as the infrared-based predictions could act only as indicators traits. Indeed, the definition of a robust calibration set, the assessment of repeatability and reproducibility of the reference (i.e., gold standard) as well as the detection of random and systematic errors are crucial steps. Once the reference phenotype has been defined, different statistical methodologies could be applied to infrared spectra data. For instance, the partial least squares regression (PLS) is a multivariate regression method commonly used to build up prediction models using NIR and FTIR spectra data. However, the implementation of advanced statistical approaches, such as Bayesian approaches and machine learning methods, might allow us to achieve more robust and accurate predictions. In this talk, we will describe and discuss some of the challenges and potentials of NIR and FTIR tools for large-scale precision phenotyping. Some examples include the use of NIR and Visible-NIR (Vis-NIR) for assessing meat quality parameters (also using portable instruments able to collect spectra directly from the muscle surface at the slaughterhouse) and the use of FTIR for predicting several traits related to fine milk composition and technological traits in dairy cattle
Effect of genetic type and dietary crude protein level on carcass and ham traits of finishing heavy pigs
No full textThis trial was supported by AGER, grant n. 2011-0280, and aimed to study the effect of genetic type and dietary crude protein (CP) level on carcass and ham traits of heavy pigs. Genetic types were selected according to their diffusion in commercial herds and involved Duroc x Large White ANAS (A), C21 Goland (G), Tempo x Topigs 40 (T) and DanBred (D) lines. A total of 184 pigs (gilts and barrows) progeny of at least 4 sires per line were raised in 2 subsequent trials from 90 to 165 kg BW and were fed convention- al or low-protein diets providing on average 140 g CP and 6.45 g lysine/kg or 106 g CP and 4.85 g lysine/kg of diet, respectively. Pigs were slaughtered at 9 months of age (average BW: 165±12.4) in the same abattoir and on a single day per trial. Hot carcass weight, backfat thickness and typical cuts weight were recorded for all carcasses. After a 24-h chilling period, hams were trimmed and then weighed and evaluated for shape, fat coverage and marbling. Fat covering depth was recorded through ruler and ultrasound, and a sample of trimmed fat was taken from all hams to assess iodine number and linoleic acid content. All hams were cured according to the San Daniele procedure, and weight losses during ageing and number of hams discarded were recorded. All traits were analyzed through ANOVA. Genetic type highly affect- ed most carcass traits, and D pigs provided carcasses with the highest incidence of lean and the lowest incidence of fat cuts. Also ham quality traits were mostly affected by genetic types, and hams from A and G had higher fat covering thickness, lower iodine number and a better overall evaluation than other genetic types. Incidence of hams not suitable for DPO production was nearly double in D and T with respect to A and G. Effects of diets were less important, but lowering dietary CP tended to improve ham subcutaneous fat covering and quality. No interaction effect between genetic type and diet was detected
Effect of low-protein diets on carcass traits and ham quality of heavy pigs
No full textA trial was conducted to evaluate the effect of low-protein diets on carcass traits and ham quality of heavy pigs. A total of 160 ani- mals, divided in two cycles (80 individuals per cycle), were blocked by weight in a randomized block design (10 pigs per pen and 2 pens per dietary treatment). Four iso-energetic diets (ME= 12.9 MJ/kg) were formulated to contain 14.2, 13.2, 11.9, and 11.4% of crude protein (CP) and 45.8 g of lysine per kg of CP, achieved by a progressive replacement of soya-bean meal with wheat grain. Animals were slaughtered at 9 months of age (aver- age BW of 168.9±9.0 kg) in the same abattoir and on a single day. During the first hour after slaughter, hot carcass weight was recorded and all carcasses were dissected into typical commer- cial cuts. Carcass yield (%), backfat (mm), lean (%) and fat cuts (%) were measured. After the 24-h chilling period, fresh hams were trimmed to produce the typical round-shape of San Daniele ham. At the end of the trimming line, hams were weighed and evaluated for overall fatness and marbling. All left hams were then cured according to the San Daniele ham procedure. Measures of ham quality traits were: fat covering measured by ultrasound (mm), iodine number, initial weight (kg), intermedi- ate weight (kg) and final weight (kg) after the ripening process. All traits were analyzed by ANOVA. No significant effects due to the treatment were observed on carcass traits except for the inci- dence of lean cuts: carcasses from pigs fed with lowest CP had lower incidence of lean cuts than carcasses from pigs fed highest CP ration (61.3% vs 62.3%, respectively; P<0.05). Backfat was higher for pigs fed with low than with high CP rations (32.1 mm vs 27.7 mm, respectively; P<0.05). Results suggest that pigs can be fed with 11.4% of CP without detrimental effects on carcass traits and ham quality
Prolonged observation and modelling of milk coagulation, curd firming, and syneresis
No full textThe aim of the present work was to evaluate the prolonging of the lactodynamographs observation
period from 30 to 90 min, and to model curd firmness as a function of time (CFt, mm) using a fourparameter
asymptotic function. The model tested was: CFt 1⁄4 CFP ð1 ekCFðtRCTÞÞ ekSRðtRCTÞ,
where RCT (min1) is the rennet coagulation time, CFP (mm) is the potential asymptotical CF at an infinite
time, kCF (min1) the curd-firming rate constant, and kSR (min1) the curd syneresis rate constant. The CFt
model was applied to data from milk of 105 Brown Swiss cows. The model appears promising as the four
novel parameters are less interdependent than are the traditional measures and it gives also an insight
on the syneresis. The repeatability of parameters of the CFt equation, estimated using information obtained
from 50 samples (two bulk milks 5 consecutive days 5 replicates each) gave better results
than traditional parameters
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