Analysis of lactation shapes in extended lactations

In order to describe the temporal evolution of milk yield (MY) and composition in extended lactations, 21 658 lactations of Italian Holstein cows were analyzed. Six empirical mathematical models currently used to fit 305 standard lactations (Wood, Wilmink, Legendre, Ali and Schaeffer, quadratic and cubic splines) and one function developed specifically for extended lactations (a modification of the Dijkstra model) were tested to identify a suitable function for describing patterns until 1000 days in milk (DIM). Comparison was performed on individual patterns and on average curves grouped according to parity (primiparous and multiparous) and lactation length (standard ⩽305 days, and extended from 600 to 1000 days). For average patterns, polynomial models showed better fitting performances when compared with the three or four parameters models. However, LEG and spline regression, showed poor prediction ability at the extremes of the lactation trajectory. The Ali and Schaeffer polynomial and Dijkstra function were effective in modelling average curves for MY and protein percentage, whereas a reduced fitting ability was observed for fat percentage and somatic cell score. When individual patterns were fitted, polynomial models outperformed nonlinear functions. No detectable differences were observed between standard and extended patterns in the initial phase of lactation, with similar values of peak production and time at peak. A considerable difference in persistency was observed between 200 and 305 DIM. Such a difference resulted in an estimated difference between standard and extended cycle of about 7 and 9 kg/day for daily yield at 305 DIM and of 463 and 677 kg of cumulated milk production at 305 DIM for the first- and second-parity groups, respectively. For first and later lactation animals, peak yield estimates were nearly 31 and 38 kg, respectively, and occurred at around 65 and 40 days. The asymptotic level of production was around 9 kg for multiparous cows, whereas the estimate was negative for first parity.     

Modelling of lactation curves of dairy cows based on monthly test day milk yield records under inconsistent milk recording scenarios

The objective of this study was to describe the lactation curve of dairy cattle in Kenya using a suitable lactation function in order to facilitate inclusion of partial lactations in national dairy cattle evaluation and to assess the effect of data characteristics on lactation curve parameters. Six functions were fitted to test day (TD) milk yield records from six parities of Ayrshire, Guernsey, Holstein Friesian, Jersey and Sahiwal cattle. Five datasets: DS-1 (12-TD dataset with randomly missing records), DS-2 (10-TD dataset without missing records), DS-3 (10-TD dataset with randomly missing records), DS-4 (7-TD dataset, with only TD 4 to 10 records) and DS-5 (7-TD dataset, with TD 1 to 4, 6, 8 and 10 records) depicting various recording circumstances were derived to assess the effects of data characteristics on lactation curves and to assess the feasibility of reducing the number of TD samples per lactation. The fit of the functions was evaluated using adjusted R(2) and their predictive abilities were compared using mean square prediction error, percentage of squared bias and the correlation between the predicted and actual milk yield. These criteria plus the changes in the parameters of curve functions and their associated standard errors were used in determining the effects of data characteristics on lactation curves. The mechanistic functions of Dijkstra (DIJ) and Pollott (APOL), and the incomplete gamma function of Wood (WD) had the highest adjusted R(2) > 0.75. The APOL function was eliminated due to convergence failures when analysis of individual lactations within breeds was carried out. Both DIJ and WD had good predictive ability, although DIJ performed slightly better. Convergence difficulties were noted in some DIJ analysis where data were limiting. Missing records, especially at the beginning of a lactation, greatly influenced parameters a and b of the functions. It also resulted in estimates with large standard errors. Missing records in later lactation hardly affected the parameter estimates. The WD and DIJ functions showed superior fit to the data. The WD function demonstrated higher adaptability to various data characteristics than DIJ and could be used in situations where animal recording is not consistently practised and where recording of animal performance is routinely practised. DIJ function had high data requirements, which restricts it to dairy systems with consistent recording, despite easy physiological interpretation of its parameters. The number of TD per lactation could be reduced by minimising sampling frequency in the later lactation while maintaining the monthly sampling frequency in early lactation.     

Accurate mathematical models to describe the lactation curve of Lacaune dairy sheep under intensive management

Although the intensive production system of Lacaune dairy sheep is the only profitable method for producers outside of the French Roquefort area, little is known about this type of systems. This study evaluated yield records of 3677 Lacaune sheep under intensive management between 2005 and 2010 in order to describe the lactation curve of this breed and to investigate the suitability of different mathematical functions for modeling this curve. A total of 7873 complete lactations during a 40-week lactation period corresponding to 201 281 pieces of weekly yield data were used. First, five mathematical functions were evaluated on the basis of the residual mean square, determination coefficient, Durbin Watson and Runs Test values. The two better models were found to be Pollott Additive and fractional polynomial (FP). In the second part of the study, the milk yield, peak of milk yield, day of peak and persistency of the lactations were calculated with Pollot Additive and FP models and compared with the real data. The results indicate that both models gave an extremely accurate fit to Lacaune lactation curves in order to predict milk yields (P = 0.871), with the FP model being the best choice to provide a good fit to an extensive amount of real data and applicable on farm without specific statistical software. On the other hand, the interpretation of the parameters of the Pollott Additive function helps to understand the biology of the udder of the Lacaune sheep. The characteristics of the Lacaune lactation curve and milk yield are affected by lactation number and length. The lactation curves obtained in the present study allow the early identification of ewes with low milk yield potential, which will help to optimize farm profitability.     

Evaluation of type traits in relation to production,and their importance in early selection for milk performance in dairy buffaloes

Type traits (TTs) can contribute to breeding animals with good economic traits such as production, longevity, fertility, and profitability. Dairy buffaloes are the second largest source of milk supply in the world, and their TTs should be taken into consideration in future dairy buffalo breeding programmes. However, the relationship between TTs and milk production traits in buffalo remains largely unknown. The study aimed to establish an early selection method for buffaloes with desirable milk performance by TTs. Using 1 908 records from 678 buffaloes, the relationship between TTs and milk production traits was analysed and the optimal growth curves of TTs related to milk production traits were constructed. We examined the correlations between 45 TTs (33 body structural, 12 udder and teat morphological traits) and three milk production traits (milk yield (MY), milk fat percentage (MF), and milk protein percentage (MP)). The results showed that the highest correlation was found between MY and udder circumference (r = 0.438), teat length (r = ?0.380) or heart girth (r = ?0.341). The teat distance and teat circumference exhibited a significant negative correlation with MF and MP. Rump length was the only trait that had a significant positive correlation with milk production traits, suggesting that milk performance could be comprehensively improved by including rump length in the selection procedure. Notably, we found that high milk production traits was obtained from the buffaloes with short teats (<6 cm), small heart girth (<200 cm), large udder circumference (>104 cm), long rump (>39 cm), and small distance between teats. Moreover, an early selection method for buffaloes with excellent milk performance was developed based on the non-linear models. Brody model exhibited the best fitting effect for heart girth and rump length, while the Logistic model displayed the best fitting effect for teat length. Our findings provide theoretical basis for the early selection of buffaloes with desirable milk performance.     

Genetic parameters of a biological lactation model: early lactation and secretion rate traits of dairy heifers

Early lactation parameters are difficult to estimate from commercial dairy records due to the small number of records available before the peak of production. A biological model of lactation was used with weekly milk records from a single Holstein herd to estimate these early lactation parameters and the secretion rate of milk from the average cell throughout lactation. A genetic analysis of the lactation curve parameters, calculated curve characteristics and secretion rate traits was undertaken. Early lactation traits were found to have little genetic variation and effectively zero heritability. Secretion rate traits for milk, protein, lactose and water were all moderately heritable and highly genetically correlated (>0.87) but fat secretion rate had lower genetic correlations with the other secretion rates. A similar pattern of correlations was seen between total lactation yield traits for fat, protein, lactose and water. The genetic correlations between the lactation curve traits and the secretion rate traits were calculated. Total milk yield, peak yield and maximum secretion potential were all highly correlated with milk, lactose and water secretion rates but less so with fat and protein secretion rates. In particular, fat secretion rate had a moderate to low genetic correlation with these lactation curve traits. Persistency of lactation was highly correlated with fat and protein secretion rates, more persistent lactations being associated with lower rates of secretion of these milk components. Similar levels of heritability were found, where trait genetic parameters were directly equivalent to those derived from the same dataset by random regression methods. However, by using a biological model of lactation to analyse lactation traits new insights into the biology of lactation are possible and ways to select cows on a range of lactation traits may be achieved.     

Relationship between milk energy intake and growth rate in suckling mammalian young at peak lactation: an updated meta-analysis

The milk energy intakes and growth rates of suckling young at peak lactation of 62 mammalian species and subspecies, all measured using either the weigh–suckle–weigh, the isotope dilution or the isotope transfer method, were evaluated. The mean daily gross energy intakes (GEI) were as low as 12 kJ in a small rodent (mouse) to as high as 249 MJ in a phocid seal (hooded seal Cystophora cristata ), while the daily growth rates at peak lactation ranged from 0.4 to 5.9 kg. Several allometric equations were calculated to explore the relationships between gross energy intake via milk and body weight (BW), growth rate and BW, as well as between gross energy intake via milk and growth rate. The results suggest that both GEI via milk and growth rates are proportional to BW to the power of 0.82. Accordingly, the metabolic weight of suckling mammalian young should be expressed as BW^0.82. The predictive values of the calculated equations indicate that suckling young at peak lactation consume c . 883 kJ day⁻¹ kg⁻¹ BW^0.82 and have growth rates of 32 g day⁻¹ kg⁻¹ BW^0.82. However, large deviations for some species and few outliers were found. These equations could be used to predict values for species that have not been studied, provided that the BW falls within the range of weights used to derive the equations.     

Genetic and phenotypic parameters of lactations longer than 305 days (extended lactations)

Test-day milk yield and somatic cell count data over extended lactation (lactation to 540-600 days) were analysed considering part lactations as different traits and fitting random regression (RR) models. Data on Australian Jersey and Holstein Friesian (HF) were used to demonstrate the shape of the lactation curve and data on HF were used for genetic study. Test-day data from about 100 000 cows that calved between 1998 and 2005 were used for this study. In all analyses, a sire model was used.When part lactations were considered as different traits, protein yield early in the lactation (e.g. first 2 months) had a genetic correlation of about 0.8 with protein yield produced after 300 days of lactation. Genetic correlations between lactation stages that are adjacent to each other were high (0.9 or more) within parity. Across parities, genetic correlations were high for both protein and milk yield if they are within the same stage of lactation. Phenotypic correlations were lower than genetic correlations. Heritability of milk-yield traits estimated from the RR model varied from 0.15 at the beginning of the lactation to as high as 0.37 by the 4th month of lactation. All genetic correlations between different days in milk were positive, with the highest correlations between adjacent days in milk and decreasing correlations with increasing time-span. The pattern of genetic correlations between milk yield in the second 300 days (301 to 600 days of lactation) do not markedly differ from the pattern in the first 300 days of lactation. The lowest estimated genetic correlation was 0.15 between milk yield on days 45 and 525 of lactation. The result from this study shows that progeny of bulls with high estimated breeding values for yield traits and those that produce at a relatively high level in the first few months are the most likely candidates for use in herds favouring extended lactations.     

Genome-wide associations for investigating time-dependent genetic effects for milk production traits in dairy cattle

Phenotypic variation in milk production traits has been described over the course of a lactation as well as between different parities. The objective of this study was to investigate whether variation in production is affected by different loci across lactations. A genome-wide association study (GWAS) using a 50-k SNP chip was conducted in 152 divergent German Holstein Friesian cows to test for association with milk production traits over different lactations. The first four lactations were analysed regarding milk yield, fat, protein, lactose, milk urea nitrogen yield and content as well as somatic cell score. Two approaches were used: (i) Wilmink curve parameters were used to assess the genetic effects over the course of a lactation and (ii) test-day yield deviations (YD) were used as a normative approach for a GWAS. The significant effects were largest for markers affecting curve parameters for which there was a statistical power <0.8 of detection even in this small design. While significant markers for YDs were detected in this study, the power to detect effects of a similar magnitude was only 0.11, suggesting that many loci may have been missed with this approach in the present design. Furthermore, all significant effects were specific for a single lactation, leading to the conclusion that the variance explained by a certain locus changes from lactation to lactation. We confirm the common evidence that most production traits vary in the degree of persistency after the peak as a result of genetic influence.     

Enhancing captive breeding in giant pandas (Ailuropoda melanoleuca): maintaining lactation when cubs are rejected,and understanding variation in milk collection and associated factors

From 1997 to 2002, a female giant panda (Ailuropoda melanoleuca) was artificially stimulated and lactation was maintained, after her neonates were removed due to the female's inability to provide maternal care. Milk samples were collected and the amount of milk collected was quantified. The lactation curve of this animal was estimated based on the Gamma function: Y_t=at^be^−ct. The amount of milk collected showed significant, positive relationships with the number of days after parturition both in 1999 and in the whole study period from 1998 to 2002. This female's lactation curves fit the type I pattern of a typical mammalian lactation curve. Daily milk collection (g) during the first 30 days after parturition, and from 31 to 60 days after parturition, showed a consistent pattern with one peak at around 8:00 hr. More milk was collected during the latter period than during the former period. The amount of milk (g) collected on mucus excretion days was significantly less than that on days after mucus excretion had ended, yet no significant difference was found between milk collected one day before mucus days and on mucus days, or between milk collected one day before and one day after mucus days. Mucus excretion from the gastrointestinal tract significantly impacted the amount of milk collected. The results from this study may aid the captive propagation and conservation of giant pandas and other endangered and rare captive mammal species. Zoo Biol 28:331–342, 2009. © 2009 Wiley-Liss, Inc.     

Comparison of non-linear growth models to describe the growth curve in West African Dwarf sheep

The objectives of this study were to compare the goodness of fit of four non-linear growth models, i.e. Brody, Gompertz, Logistic and Von Bertalanffy, in West African Dwarf (WAD) sheep. A total of 5274 monthly weight records from birth up to 180 days of age from 889 lambs, collected during 2001 to 2004 in Betecoucou breeding farm in Benin were used. In the preliminary analysis, the General Linear Model Procedure of the Statistical Analysis Systems Institute was applied to the dataset to identify the significant effects of the sex of lamb (male and female), type of birth (single and twin), season of birth (rainy season and dry season), parity of dam (1, 2 and 3) and year of birth (2001, 2002, 2003 and 2004) on the observed birth weight and monthly weight up to 6 months of age. The models parameters (A, B and k), coefficient of determination (R²), mean square error (MSE) were calculated using language of technical computing package Matlab®, 2006. The mean values of A, B and k were substituted into each model to calculate the corresponding Akaike’s Information Criterion (AIC). Among the four growth functions, the Brody model has been selected for its accuracy of fit according to the higher R², lower MSE and AIC. Finally, the parameters A, B and k were adjusted in Matlab®, 2006 for the sex of lamb, year of birth, season of birth, birth type and the parity of ewe, providing a specific slope of the Brody growth curve. The results of this study suggest that Brody model can be useful for WAD sheep breeding in Betecoucou farm conditions through growth monitoring.     

Profile and genetic parameters of dairy cattle locomotion score and lameness across lactation

This study investigated the profile of locomotion score and lameness before the first calving and throughout the first (n=237) and second (n=66) lactation of 303 Holstein cows raised on a commercial farm. Weekly heritability estimates of locomotion score and lameness, and their genetic and phenotypic correlations with milk yield, body condition score, BW and reproduction traits were derived. Daughter future locomotion score and lameness predictions from their sires’ breeding values for conformation traits were also calculated. First-lactation cows were monitored weekly from 6 weeks before calving to the end of lactation. Second-lactation cows were monitored weekly throughout lactation. Cows were locomotion scored on a scale from one (sound) to five (severely lame); a score greater than or equal to two defined presence of lameness. Cows’ weekly body condition score and BW was also recorded. These records were matched to corresponding milk yield records, where the latter were 7-day averages on the week of inspection. The total number of repeated records amounted to 12 221. Data were also matched to the farm’s reproduction database, from which five traits were derived. Statistical analyses were based on uni- and bivariate random regression models. The profile analysis showed that locomotion and lameness problems in first lactation were fewer before and immediately after calving, and increased as lactation progressed. The profile of the two traits remained relatively constant across the second lactation. Highest heritability estimates were observed in the weeks before first calving (0.66 for locomotion score and 0.54 for lameness). Statistically significant genetic correlations were found for first lactation weekly locomotion score and lameness with body condition score, ranging from −0.31 to −0.65 and from −0.44 to −0.76, respectively, suggesting that cows genetically pre-disposed for high body condition score have fewer locomotion and lameness issues. Negative (favourable) phenotypic correlations between first lactation weekly locomotion score/lameness and milk yield averaged −0.27 and −0.17, respectively, and were attributed to management factors. Also a phenotypic correlation between lameness and conception rate of −0.19 indicated that lame cows were associated with lower success at conceiving. First-lactation daughter locomotion score and/or lameness predictions from sires’ estimated breeding values for conformation traits revealed a significant linear effect of rear leg side view, rear leg rear view, overall conformation, body condition score and locomotion, and a quadratic effect of foot angle.     

Evaluation of reference lactation length in Chios dairy sheep

Definition and establishment of a fixed reference lactation length could provide useful tools for on-farm comparison of ewes and flock management as well as genetic evaluations for the breeding programme. The objectives of this study were to (i) evaluate different reference lactation lengths for the Chios dairy sheep and (ii) define the most suitable reference length for the breed. A total of 260 042 test-day milk records from 24 474 ewes in 130 flocks collected between 2003 and 2014 were used; 15 different lactation lengths were evaluated ranging from 120 to 260 days, defined at 10-day intervals as reference for the Chios sheep. The evaluation criteria included: (a) heritability and repeatability of milk yield in each reference lactation, (b) genetic correlation of reference lactation milk yield with actual lactation milk yield and yield at first test-day record and (c) correlated response in reference lactation milk yield from selection based on first test-day milk yield. The latter emulates genetic gains achieved for milk yield based on early lactation selection. Heritability and repeatability estimates of reference lactation milk yield and genetic correlation with actual lactation yield favoured long reference lactations (180 to 230 days). On the contrary, correlation with first test-day record milk yield was higher for short lactations (120 to 170 days). Moreover, selection on first test-day record milk yield would lead to a correlated response in reference yield in 220 days equal to 85% of the highest estimate achieved in the maximum reference length of 260 days (190 days when only considering first lactation milk yield). Based on the results of the present study, an overall reference lactation length for the Chios breed of 220 days post-lambing and a first lactation reference length of 190 days post-lambing are recommended.     

The Effect of Calf Gender on Milk Production in Seasonal Calving Cows and Its Impact on Genetic Evaluations

Gender of the calf whose birth initiates lactation could influence whole lactation milk yield of the dam due to hormonal influences on mammary gland development, or through calf gender effects on gestation length. Fetal gender could influence late lactation yields because cows become pregnant at peak lactation. The effects of calf gender sequences in parities 1–3 were assessed by separately fitting animal models to datasets from New Zealand comprising 274 000 Holstein Friesian and 85 000 Jersey cows, decreasing to 12 000 and 4 000 cows by parity 3. The lactation initiated by the birth of a female rather than a male calf was associated with a 0.33–1.1% (p≤0.05) higher milk yield. Female calf gender had carryover effects associated with higher milk yield in second lactations for Holstein Friesians (0.24%; p = 0.01) and third lactations for Jerseys (1.1%; p = 0.01). Cows giving birth to bull calves have 2 day longer gestations, which reduces lactation length in seasonal calving herds. Adding a covariate for lactation length to the animal model eroded some of these calf gender effects, such that calving a female led to higher milk yield only for second lactation Holstein Friesians (1.6%; p = 0.002). The interval centering method generates lower estimates of whole lactation yield when Wood’s lactation curves are shifted to the right by 2 days for male calves and this explained the higher yield in female calves when differences in lactation length were considered. Correlations of estimated breeding values between models including or excluding calf gender sequence were 1.00 for bulls or cows. Calf gender primarily influences milk yield through increased gestation length of male calves, and bias associated with the interval centering method used to estimate whole lactation milk yields. Including information on calf gender is unlikely to have an effect on selection response in New Zealand dairy cattle.     

Relationships between conception rate in Holstein heifers and cows and milk yield at various stages of lactation

We investigated the relationships between conception rates (CRs) at first service in Japanese Holstein heifers (i.e. animals that had not yet had their first calf) and cows and their test-day (TD) milk yields. Data included records of artificial insemination (AI) for heifers and cows that had calved for the first time between 2000 and 2008 and their TD milk yields at 6 through 305 days in milk (DIM) from first through third lactations. CR was defined as a binary trait for which first AI was a failure or success. A threshold-linear animal model was applied to estimate genetic correlations between CRs of heifers or cows and TD milk yield at various lactation stages. Two-trait genetic analyses were performed for every combination of CR and TD milk yield by using the Bayesian method with Gibbs sampling. The posterior means of the heritabilities of CR were 0.031 for heifers, 0.034 for first-lactation cows and 0.028 for second-lactation cows. Heritabilities for TD milk yield increased from 0.324 to 0.433 with increasing DIM but decreased slightly after 210 DIM during first lactation. These heritabilities from the second and third lactations were higher during late stages of lactation than during early stages. Posterior means of the genetic correlations between heifer CR and all TD yields were positive (range, 0.082 to 0.287), but those between CR of cows and milk yields during first or second lactation were negative (range, −0.121 to −0.250). Therefore, during every stage of lactation, selection in the direction of increasing milk yield may reduce CR in cows. The genetic relationships between CR and lactation curve shape were quite weak, because the genetic correlations between CR and TD milk yield were constant during the lactation period.     

Effect of lactation length adjustment procedures on genetic parameter estimates for buffalo milk yield

The objectives of this study were to estimate the genetic parameters for milk yield unadjusted and adjusted for days in milk and, subsequently, to assess the influence of adjusting for days in milk on sire rank. Complete lactations from 90 or 150 days of lactation to 270 or 350 days in milk were considered in these analyses. Milk yield was adjusted for days in milk by multiplicative correction factors, or by including lactation length as a covariable in the model. Milk yields adjusted by different procedures were considered as different traits. Heritability estimates varied from 0.17 to 0.28. Genetic correlation estimates between milk yields unadjusted and adjusted for days in milk were greater than 0.82. Adjusting for days in milk affected the parameter estimates. Multiplicative correction factors produced the highest heritability estimates. More reliable breeding value estimates can be expected by including short length lactation records in the analyses and adjusting the milk yields for days in milk, regardless of the method used for the adjustment. High selection intensity coupled to the inclusion of short length lactations and adjustment with multiplicative factors can change the sire rank..     

Development of a new grading system to assess the foster performance of lactating sows

Increasing litter size has created the need for more sophisticated, accurate, and welfare-oriented systems for assessing the foster performance of lactating sows. The estimation of milk yield alone is not sufficient for meeting these requirements. Therefore, the aim of the current study was to develop a grading system for assessing the foster performance of lactating sows that can be easily applied in commercial farm practice. Data were collected in two German conventional farrow-to-feeder farms with a total sample size of 639 sows (4.05 ± 2.86 parities) and 1 728 litters. Besides general performance data, the piglets were weighed individually within the first 24 hours after birth and at the peak of lactation (day 18.22 ± 2.48). Based on these data, we proposed a new score referring to the milk score (MS). This score was compared with the commonly used formula for estimating milk yield (est. MY), which solely involves litter weight gain and litter size. The improvement of the developed MS allowed us to distinguish between the birth and foster performances of the lactating sows through considering cross-fostering, litter size, individual piglet weights, and piglet mortality during lactation. Both scores showed a similar progression across parities. It was found that litter size had a significant impact on the performance of lactating sows. A high est. MY was found to be associated with a significantly higher number of piglets per litter (15.79 ± 2.20), lower weight gain per piglet, and increased piglet mortality during lactation compared with sows with high MS, which showed a smaller litter size (13.51 ± 2.18) (P < 0.05). The focus on smaller litter size indicates a performance limitation, which seems to be related to the average teat number of 13–15 teats per sow. We recommend the consideration of the number of functional teats, because a litter size above it will not result in a sow having higher foster performance. In conclusion, as an extension of the common est. MY calculation, the MS considers cross-fostering as current farm-management practice when dealing with larger litters. Our recommendations emphasise the importance of an MS which indicates smaller litter size, higher piglet weight gain, and lower piglet mortality during lactation; these factors are related to an improvement in animal welfare for sows and piglets. Moreover, the presented MS could be used to develop a management tool for farmers to assess the foster performance of lactating sows, considering individual farm-management practices.     

Jennet milk production during the lactation in a Sicilian farming system

In Italy, the interest for jennet milk production has recently developed. An 18-month-long experiment was carried out on a jennet farm near Milo (CT), where 24 jennets, which derived from the Ragusana breed, were tested for milk yield and composition over an entire lactation period. The jennets were fed with hay and concentrate in a large paddock. From the 28th post-foaling day to the end of the lactation, the jennets were machine-milked twice a day with an in-between milking interval of 5 h. The milk amount from each jennet was recorded every 3 weeks and individual samples were collected and analyzed for fat, protein, casein, non-proteic nitrogen, lactose and somatic cell count. This study showed that jennets at Sicilian latitudes are not seasonal polyestrous. The daily milk yield, the length of lactation and the milk characteristics varied depending on the foaling season. The total average milk production was 490 ± 36 kg in 295 ± 12 post-foaling days, considering two milking records per day. During the lactation, milk yield decreased constantly from 1.98 to 1.28 kg/jennet per day. When looking at the jennet milk quality during lactation, the percentage of fat and protein decreased, while the lactose percentage increased, according to a tendency apparently unique for equines when compared to the ruminants. When looking at the productive season, spring generally gave the best qualitative and quantitative results. Based on these results, jennet milk yield and quality could be improved; furthermore, jennet milk production may turn out to be a profitable business.     

Exploration of lagged relationships between mastitis and milk yield in dairycows using a Bayesian structural equation Gaussian-threshold model

A Gaussian-threshold model is described under the general framework of structural equation models for inferring simultaneous and recursive relationships between binary and Gaussian characters, and estimating genetic parameters. Relationships between clinical mastitis (CM) and test-day milk yield (MY) in first-lactation Norwegian Red cows were examined using a recursive Gaussian-threshold model. For comparison, the data were also analyzed using a standard Gaussian-threshold, a multivariate linear model, and a recursive multivariate linear model. The first 180 days of lactation were arbitrarily divided into three periods of equal length, in order to investigate how these relationships evolve in the course of lactation. The recursive model showed negative within-period effects from (liability to) CM to test-day MY in all three lactation periods, and positive between-period effects from test-day MY to (liability to) CM in the following period. Estimates of recursive effects and of genetic parameters were time-dependent. The results suggested unfavorable effects of production on liability to mastitis, and dynamic relationships between mastitis and test-dayMYin the course of lactation. Fitting recursive effects had little influence on the estimation of genetic parameters. However, some differences were found in the estimates of heritability, genetic, and residual correlations, using different types of models (Gaussian-threshold vs. multivariate linear).     

The composition of Australian fur seal (Arctocephalus pusillus doriferus) milk throughout lactation.

The proximate chemical composition of milk was determined throughout lactation in the Australian fur seal (Arctocephalus pusillus doriferus Wood Jones), a temperate species with an 11-mo lactation period typical of most temperate otariids. Average lipid and protein contents were 42% and 10%, respectively, which is similar to that recorded for the polar otariid species but higher than reported in other temperate, long-lactation species. Milk composition, however, varied substantially throughout lactation, with lipid content rising from 30% soon after parturition to 50% at 230 d postpartum before decreasing to 45% toward weaning. The trend in water content was opposite to that of lipid, while protein content increased only slightly during lactation from 10% to 12%. The peak in lipid content occurred at approximately 70% of the way through lactation, similar to that found in the Australian sea lion and several phocid seal species. Significant positive relationships were found between milk lipid content and both the duration of the preceding foraging trip and body mass. A highly significant and close correlation was found between milk water and lipid contents such that gross energy content may be accurately predicted from water content alone. Similar predictive equations have been found for several other otariid and phocid species, but these appear to differ between phylogenetic groups.