ABSTRACT: The efficiency of automatic milking systems depends on the continuous flow of cows, which may be affected by specific cow conducts, including milking unit preference. Moreover, providing resources that favor the expression of natural cow behaviors during the milking process may result in improved animal welfare. The objective of this study was to analyze the selection behavior for automatic milking units, comparing preference consistency across the lactation of 3 genetic groups (Holstein [HO], Jersey [JE], and Holstein × Jersey [HJ]) in a multibreed organic dairy farm using a batch milking system. To expand the main objective, a secondary aim was to examine the relationship between milking unit selection behavior and premilking waiting time (WT). The study included data from 1,762,461 milking events in 1,355, 1,876, and 475 HO, JE, and HJ cows, respectively, from May 2023 to September 2024 in a commercial organic grass-fed dairy in Texas in the United States. Cows were moved to the waiting area of the milk center twice per day, where they could select their milking visits among 22 automatic milking units. Cow preferences were analyzed at 3 levels: automatic milking unit (n = 22), barn location (east, n = 11; west), and robotic arm configuration (left, n = 11; right). Milking visit information was collected from the management software to establish the frequency of specific milking unit usage per cow during the study period. Subsequently, the frequencies for selection of the top choice for 1, 3, and 5 automatic milking units, the top choice for barn location, and the top choice for robotic arm configuration were calculated for each cow. Preference consistency scores (PCS) were calculated as a ratio between the excess frequencies of the first choice over the base frequency of any option other than the first choice. The PCS calculations considered the frequency of access to each automatic milking unit, barn location, and robotic arm configuration in 30-d periods until 305 DIM. Premilking waiting times were calculated for each cow as the difference between the entry time into the waiting area of the milk center, indicated by a pedometer affixed in the rear leg of each cow, and the start of the corresponding milking, as indicated by the milking unit in use. Least squares means for PCS were calculated within parity category by genetic group for each 30-d period and compared using repeated-measures ANOVA. Subsequently, PCS and WT values were categorized into quartiles, and LSM for PCS and WT were calculated for each of the PCS by WT combinations within each parity category. As indicated by the chi-squared test of independence and the ANOVA, the frequency of selection for the top choice and the PCS were different from those expected by random selection of automatic milking unit, barn location, and robotic arm configuration, signifying different levels of selection behavior in the study cows. Overall, HO cows evidenced the greatest PCS values, indicating more consistent behaviors in milking unit preference. Additionally, the analysis of the association between PCS and WT indicated that greater PCS were associated with shorter WT. The resulting PCS suggest variable degrees of consistency in the selection behavior for automatic milking units in dairy cows. The selection behaviors identified in this study may have implications for cow welfare, as well as for improving cow traffic and system efficiency.
Abstract Microstructure is a fundamental determinant of the quality, functionality, and stability of dairy products, governing critical attributes such as texture, rheology, meltability, and shelf-life. Conventional compositional analyses are not sufficient to fully explain processing-induced changes and product defects, necessitating microscopic approaches. This review examines the role of microstructural analysis as a quality assessment and process optimization tool for several dairy products, including fluid milk, fermented products, cheese, ice cream, butter, traditional dairy products, and milk powders. Emphasis is placed on the application of complementary microscopy techniques, light microscopy, confocal laser scanning microscopy, scanning and transmission electron microscopy, and cryogenic imaging methods, to elucidate the spatial organization and interactions of casein networks, fat globules, aqueous phases, air cells, and crystalline components. The review discusses evidence linking microstructural features with macroscopic product properties, demonstrating influence of processing variables such as homogenization, heat treatment, fermentation, freezing, and ripening on the changes in structural organization and, consequently, product characteristics. Furthermore, it illustrate the utility of microscopy in defect and critical control point identification, and industrial troubleshooting, including syneresis in yoghurt, textural defects in cheese, recrystallization in ice cream, and poor rehydration of milk powders and establishes microscopy as an indispensable tool for dairy product design, and quality control, providing considerable potential for enhancing consistency, functionality, and processing efficiency for dairy industry.
Fermentation was traditionally used all over the world, having the preservation of plant and animal foods as a primary role. Owing to the rise of dairy and meat alternatives, fermentation is booming as an effective technology to improve the sensory, nutritional, and functional profiles of the new generation of plant-based products. This article intends to review the market landscape of fermented plant-based products with a focus on dairy and meat alternatives. Fermentation contributes to improving the organoleptic properties and nutritional profile of dairy and meat alternatives. Precision fermentation provides more opportunities for plant-based meat and dairy manufacturers to deliver a meat/dairy-like experience. Seizing the opportunities that the progress of digitalization is offering would boost the production of high-value ingredients such as enzymes, fats, proteins, and vitamins. Innovative technologies such as 3D printing could be an effective post-processing solution following fermentation in order to mimic the structure and texture of conventional products.
Diana Plamada, Bernadette-Emőke Teleky, Silvia-Amalia Nemeș
et al.
One significant food group that is part of our daily diet is the dairy group, and both research and industry are actively involved to meet the increasing requirement for plant-based dairy alternatives (PBDAs). The production tendency of PBDAs is growing with a predictable rate of over 18.5% in 2023 from 7.4% at the moment. A multitude of sources can be used for development such as cereals, pseudocereals, legumes, nuts, and seeds to obtain food products such as vegetal milk, cheese, cream, yogurt, butter, and different sweets, such as ice cream, which have nearly similar nutritional profiles to those of animal-origin products. Increased interest in PBDAs is manifested in groups with special dietary needs (e.g., lactose intolerant individuals, pregnant women, newborns, and the elderly) or with pathologies such as metabolic syndromes, dermatological diseases, and arthritis. In spite of the vast range of production perspectives, certain industrial challenges arise during development, such as processing and preservation technologies. This paper aims at providing an overview of the currently available PBDAs based on recent studies selected from the electronic databases PubMed, Web of Science Core Collection, and Scopus. We found 148 publications regarding PBDAs in correlation with their nutritional and technological aspects, together with the implications in terms of health. Therefore, this review focuses on the relationship between plant-based alternatives for dairy products and the human diet, from the raw material to the final products, including the industrial processes and health-related concerns.
ABSTRACT: Substitution of soybean meal with dried distillers grains in calf starter feeds (SF) suppresses ADG and feed efficiency. Through the use of fractionation technologies, the ethanol industry is able to produce high-protein corn coproducts (HPCC), which are greater in protein and contain less fiber than traditional distillers grains, and more closely resemble the chemical composition of soybean meal. To evaluate the suitability of an HPCC as a substitute for soybean meal in calf grain, 21 male and 21 female Holstein calves were blocked by sex and birthdate, and randomly assigned to 1 of 3 calf grain treatments, which were offered beginning at 14 d of age. Calf grain treatments were formulated for 0% (CTRL), 50% (50HPCC), or 100% (100HPCC) replacement of the soybean meal (16.6% of diet DM) by HPCC. Rumen-protected Met and Lys were supplemented to meet estimated requirements. Calves were individually housed, and during the data collection period, which occurred after weaning (56–84 d of age), assigned grain was the only feed offered. Dry matter intake was recorded daily, and growth and blood samples were obtained every 14 ± 1 d. Fecal samples were collected on the last 4 d of trial to determine apparent total-tract digestibility. Data were analyzed using PROC MIXED in SAS (v. 9.4) for fixed effects of treatment, sex, and week, when applicable. Preplanned contrasts were used. Treatment, sex, and week interacted on grain intake, whereby 100HPCC males increased DMI more rapidly than males on other treatments but within females only CTRL and 50HPCC increased DMI. Increasing HPCC inclusion linearly increased BW and ADG. Treatment and sex interacted on feed efficiency, whereby 100HPCC males were more efficient than 100HPCC females. Wither height was affected quadratically, as 50HPCC calves were shorter than 100HPCC calves. Inclusion of HPCC increased calf plasma insulin concentration both linearly and compared with CTRL, but contrasts were not detected for blood BHB, BUN, glucose, free fatty acid, or triglyceride concentrations. Apparent total-tract digestibility of DM and CP in diets containing HPCC tended to be greater than CTRL. Overall results indicate the HPCC can replace soybean meal in SF when balanced for the limiting AA Met and Lys.
Jiaxin Xu, Taha Majid Mahmood Sheikh, Muhammad Shafiq
et al.
ABSTRACT: Cow milk protein allergy (CMPA) is a significant health concern characterized by adverse immune reactions to cow milk proteins. Biomarkers for the accurate diagnosis and prognosis of CMPA are lacking. This study analyzed the clinical features of CMPA, and 16S RNA sequencing was used to investigate potential biomarkers through fecal microbiota profiling. Children with CMPA exhibit a range of clinical symptoms, including gastrointestinal (83% of patients), skin (53% of patients), and respiratory manifestations (26% of patients), highlighting the complexity of this condition. Laboratory analysis revealed significant differences in red cell distribution width and inflammatory markers between the CMPA and control groups, suggesting immune activation and inflammatory responses in CMPA. Microbial diversity analysis revealed higher specific diversity indices in the CMPA group compared with those in control group, with significant differences at the genus and species levels. Bacteroides were more abundant in the CMPA group, whereas Bifidobacterium, Ruminococcus, Faecalibacterium, and Parabacteroides were less abundant. The control group exhibited a balanced microbial profile, with a predominant presence of Bifidobacterium bifidum and Akkermansia muciniphila. The significant abundance of Bifidobacterium in the control group (23.19% vs. 9.89% in CMPA) was associated with improved growth metrics such as height and weight, suggesting its potential as a probiotic to prevent CMPA and enhance gut health. Correlation analysis linked specific microbial taxa such as Coprococcus and Bifidobacterium to clinical parameters such as family allergy history, weight, and height, providing insights into CMPA pathogenesis. Significant differences in bacterial abundance suggested diagnostic potential, with a panel of 6 bacteria achieving high predictive accuracy (area under curve = 0.8708). This study emphasizes the complex relationship between the gut microbiota and CMPA, offering valuable insights into disease mechanisms and diagnostic strategies.
ABSTRACT: Dominant species common to the kefir grains from 7 different origins were analyzed using culture-dependent methods using agar media that were able to grow and discriminate Lactobacillus kefiranofaciens ssp. kefiranofaciens. Identification of all isolates was performed on the basis of MALDI-TOF MS analysis and colony morphology. Lactic acid bacteria were present at 9 log cfu·g−1 in all kefir grains. Lactobacillus kefiranofaciens was the predominant species (∼87%), followed by Lentilactobacillus kefiri (∼12%) in all grains. Within Lb. kefiranofaciens, Lb. kefiranofaciens ssp. kefirgranum (flocculent and nonflocculent strains) was most abundant (∼82%) and Lb. kefiranofaciens ssp. kefiranofaciens (kefiran producer) was present at ∼18%. Lentilactobacillus parakefiri, Leuconostoc mesenteroides, and Lactococcus lactis were also present in some grains as minor species. Yeasts were present at 6 to 7 log cfu·g−1 and were highly diverse; only Kazachstania exigua was found in all grains. We attempted to reconstruct kefir grains using strains of the following major and minor common species: Lb. kefiranofaciens ssp. kefiranofaciens, Lb. kefiranofaciens ssp. kefirgranum, Len. kefiri, Len. parakefiri, Leu. mesenteroides, Lc. lactis, and K. exigua. We obtained reconstructed kefir grains that could grow logarithmically to some extent in milk. They were elastic, but each grain was smaller than a natural kefir grain. At least a combination of Lb. kefiranofaciens ssp. kefiranofaciens, Lb. kefiranofaciens ssp. kefirgranum, and Len. kefiri or Len. parakefiri could initiate grain formation.
ABSTRACT: Palmitic and stearic acid are commonly fed to dairy cows but limited data are available on their effects on thermal properties of milk fat, especially when fed at different levels. Recently, some consumers voiced concerns about butter being harder at room temperature and questioned if it was caused by palmitic acid supplementation of dairy cows. Our hypothesis was that increasing palmitic acid intake would linearly increase palmitic acid in milk fat and, therefore, increase the solid fat content (SFC) of milk fat at 20°C, whereas increasing stearic acid intake would increase both stearic and oleic acid in milk fat and not change the SFC of milk fat at 20°C. A total of 12 second-lactation Holstein cows (106 ± 31 DIM) were arranged in a replicated 3 × 3 Latin square design with a dose escalation design within period and ≥10 d washouts between periods. Treatments included a no-supplement fat control (CON), a fatty acid (FA) supplement high in palmitic acid (PA; 88% palmitic and 8% oleic), and a FA supplement high in stearic acid (SA; 81% stearic and 10% oleic). The FA supplements were fed at increasing doses every 4 d, targeting 150, 300, 500, and 750 g/d. Milk samples were collected on d 3 and 4 of each dose, composited, and milk fat extracted from the fat cake by centrifugation. The FA profile of whole milk was analyzed using GC, and the melting properties of milk fat were characterized by differential scanning calorimetry. Data were analyzed by ANOVA with preplanned contrasts testing CON versus PA and CON versus SA at each dose level. Increasing PA progressively increased palmitic acid in milk fat, whereas increasing SA progressively increased both stearic and oleic acid. At 750 g/d, PA increased palmitic and palmitoleic acid in milk fat 5.7 and 0.25 percentage units compared with CON, whereas SA increased stearic and oleic acid in milk fat by 2.4 units and 3.0 units compared with CON. The SFC of milk fat at 20°C was linearly increased by PA but was decreased by SA. At the 750 g/d dose, PA increased SFC by 5.3 percentage units, whereas SA decreased it 3.2 percentage units compared with CON. In conclusion, increasing palmitic acid intake increases the SFC of milk fat at room temperature, whereas increasing stearic acid modestly decreases it, likely due to differences in the rates of desaturation of these FA by the stearoyl-CoA desaturase enzyme.
Alessandra Casagrande Ribeiro, F. A. Almeida, Mariana Medina Medeiros
et al.
Listeria monocytogenes is an opportunistic pathogen that affects specific groups of individuals, with a high mortality rate. The control of L. monocytogenes in dairy industries presents particular challenges, as this bacterium is capable of adhering and forming biofilms, as well as thriving at refrigerated temperatures, which enables it to persist in harsh environments. The consumption of dairy products has been linked to sporadic cases and outbreaks of listeriosis, and L. monocytogenes is frequently detected in these products in retail stores. Moreover, the bacterium has been shown to persist in dairy-processing environments. In this work, we review the main characteristics of L. monocytogenes and listeriosis, and highlight the factors that support its persistence in processing environments and dairy products. We also discuss the main dairy products involved in outbreaks of listeriosis since the early 1980s, and present control measures that can help to prevent the occurrence of this pathogen in foods and food-processing environments.
Highlights • CiteSpace 6.1. R2 can co-interpret the research on yak milk.• The feeding management, nutrition composition and microbial diversity of yak milk were systematically reviewed.• Yak milk and its products have various biological activities.• The processing and preparation of traditional fermented yak dairy products were reviewed.
S. de Las Heras-Delgado, S. Shyam, Èrica Cunillera
et al.
BACKGROUND Plant-Based Alternative Products (PBAPs) to meat and dairy are increasingly available. Their relative nutritional quality in comparison to animal-based homologs is poorly documented. OBJECTIVE To characterize and evaluate the plant-based alternatives available on the market in Spain in comparison to animal products in terms of their nutritional composition and profile, and degree of processing. METHODS Nutritional information for PBAPs and homologs were obtained from the Spanish 'Veggie base', branded food composition database. Five PBAPs categories (cheese, dairy products, eggs, meat, and fish, n = 922) were compared to animal-based processed (n = 922) and unprocessed (n = 381) homologs, using the modified version of the Food Standard Agency Nutrient Profiling System (FSAm-NPS score) and NOVA classification criteria. RESULTS Compared to processed or unprocessed animal food, PBAPs contain significantly higher sugar, salt, and fiber. PBAPs for fish, seafood, and meat were lower in protein and saturated fatty acids. Overall, 68% of PBAPs, 43% of processed and 75% of unprocessed animal-homologs had Nutri-Score ratings of A or B (most healthy). About 17% of PBAPs, 35% of processed and 13% of unprocessed animal-based food were in Nutri-Score categories D or E (least healthy). Dairy, fish, and meat alternatives had lower FSAm-NPS scores (most healthy), while cheese alternatives scored higher (least healthy) than animal-based homologs. Unprocessed fish and meat were healthier than similar PBAPs based on FSAm-NPS criteria. Approximately 37% of PBAPs and 72% of processed animal-based products were ultra-processed food (NOVA group 4). Within the ultra-processed food group, Nutri-Score varied widely. CONCLUSIONS Most PBAPs had better nutrient profile than animal-based homologs. However, cheese, fish and meats PBAPs had poorer nutrient profile and were more processed. Given the high degree of processing and variable nutritional profile, PBAPs require a multi-dimensional evaluation of their health impact.
Kristen Y. Edwards, Stephen J. LeBlanc, Trevor J. DeVries
et al.
Establishing accurate illness and treatment rates in dairy calves is crucial, yet calf health records are often incomplete. Thus, the objective of this study was to investigate barriers for dairy farmers for recording calf illnesses and treatments on dairy farms in Ontario, Canada. An online survey was completed by a convenience sample of 88 Ontario dairy farms in 2022, with 34 questions regarding farm demographics, current practices surrounding record keeping and analysis, and factors that would improve recording compliance. Multivariable models were built to assess associations between explanatory variables and the following outcomes: likelihood of making management or treatment protocol changes based on records analysis, factors that would increase the use of electronic recording methods, and whether all calf illnesses and treatments are recorded. Pearson's chi-squared tests were also used to investigate associations between explanatory variables and whether the respondent agreed or disagreed with a proposed reason for why a calf illness or treatment would not be recorded on their farm. Producers had 3.45 times greater odds of recording all antimicrobial treatments if they used a computer software system compared with those that did not. With respect to anti-inflammatory treatments, producers had 3.11 times greater odds of recording these treatments if records were located in the calf barn than elsewhere. Nonfamily employees had 6.08 times greater odds of recording all supportive therapy treatments than farm owners. When calf health records were kept in the calf barn, respondents were less likely to report that illnesses were not recorded due to time constraints (5% vs. 36% if records were elsewhere) or because calf health records were not analyzed (10% vs. 34% if records were elsewhere). On farms that recorded calf treatments in a paper booklet, respondents were more likely to report that treatments were not recorded because calf health records were not analyzed (44% for paper records vs. 21% for other systems). The most commonly indicated factors that would increase recording of illness were recording with a mobile app (27% of respondents) and for the recording system to be easy to use (31% of respondents). Overall, these data indicate that recording may be improved by keeping calf health records in close proximity to the calves and using a recording method that allows for data analysis. An easy-to-use mobile app may also improve recording if it could be used in the calf barn, provide data analytics, and allow for time-efficient data entry.
In developed countries, the dairy sector is going through a highly challenging phase as a consequence of changes in consumers’ expectations and the spread of new cultural approaches to food [...]
Waseem Shaukat, Ellen de Jong, Kayley D. McCubbin
et al.
ABSTRACT: Endemic infectious diseases remain a major challenge for dairy producers worldwide. For effective disease control programs, up-to-date prevalence estimates are of utmost importance. The objective of this study was to estimate the herd-level prevalence of bovine leukemia virus (BLV), Salmonella enterica ssp. enterica serovar Dublin (Salmonella Dublin), and Neospora caninum in dairy herds in Alberta, Canada, using a serial cross-sectional study design. Bulk tank milk samples from all Alberta dairy farms were collected 4 times, in December 2021 (n = 489), April 2022 (n = 487), July 2022 (n = 487), and October 2022 (n = 480), and tested for antibodies against BLV, Salmonella Dublin, and N. caninum using ELISA. Herd-level apparent prevalence was calculated as positive herds divided by total tested herds at each time point. A mixed-effect modified Poisson regression model was employed to assess the association of prevalence with region, herd size, herd type, and type of milking system. Apparent prevalence of BLV was 89.4%, 88.7%, 86.9%, and 86.9% in December, April, July, and October, respectively, whereas for Salmonella Dublin apparent prevalence was 11.2%, 6.6%, 8.6%, and 8.5%, and for N. caninum apparent prevalence was 18.2%, 7.4%, 7.8%, and 15.0%. For BLV, Salmonella Dublin, and N. caninum, a total of 91.7%, 15.6%, and 28.1% of herds, respectively, were positive at least once, whereas 82.5%, 3.6%, and 3.0% of herds were ELISA positive at all 4 times. Compared with the north region, central Alberta had a high prevalence (prevalence ratio [PR] = 1.13) of BLV antibody-positive herds, whereas south Alberta had a high prevalence (PR = 2.56) of herds positive for Salmonella Dublin antibodies. Furthermore, central (PR = 0.52) and south regions (PR = 0.46) had low prevalence of N. caninum-positive herds compared with the north. Hutterite colony herds were more frequently BLV positive (PR = 1.13) but less frequently N. caninum-positive (PR = 0.47). Large herds (>7,200 L/d milk delivered ∼>250 cows) were 1.1 times more often BLV positive, whereas small herds (≤3,600 L/d milk delivered ∼≤125 cows) were 3.2 times more often N. caninum positive. For Salmonella Dublin, Hutterite colony herds were less frequently (PR = 0.07) positive than non-colony herds only in medium and large strata but not in small stratum. Moreover, larger herds were more frequently (PR = 2.20) Salmonella Dublin-positive than smaller herds only in non-colony stratum but not in colony stratum. Moreover, N. caninum prevalence was 1.6 times higher on farms with conventional milking systems compared with farms with an automated milking system. These results provide up-to-date information of the prevalence of these infections that will inform investigations of within-herd prevalence of these infections and help in devising evidence-based disease control strategies.
ABSTRACT: The main objectives of this study were to estimate genetic parameters for milk urea nitrogen (MUN) in Holstein cattle and to conduct a single-step (ss)GWAS to identify candidate genes associated with MUN. Phenotypic measurements from 24,435 Holstein cows were collected from March 2013 to July 2019 in 9 dairy farms located in the Beijing area, China. A total of 2,029 cows were genotyped using the Illumina 150K Bovine Bead Chip, containing 121,188 SNP. A single-trait repeatability model was used to evaluate the genetic background of MUN. We found that MUN is a trait with low heritability (0.06 ± 0.004) and repeatability (0.12). Considering similar milk production levels, a lower MUN concentration indicates higher nitrogen digestibility. The genetic correlations between MUN and milk yield, net energy concentration, fat percentage, protein percentage, and lactose percentage were positive and ranged from 0.02 to 0.26. The genetic correlation between MUN and somatic cell score (SCS) was negative (−0.18), indicating that animals with higher MUN levels tend to have lower SCS. Both ssGWAS and pathway enrichment analyses were used to explore the genetic mechanisms underlying MUN. A total of 18 SNP (located on BTA11, BTA12, BTA14, BTA17, and BTA18) were found to be significantly associated with MUN. The genes CFAP77, CAMSAP1, CACNA1B, ADGRB1, FARP1, and INTU are considered to be candidate genes for MUN. These candidate genes are associated with important biological processes such as protein and lipid metabolism and binding to specific proteins. This set of candidate genes, metabolic pathways, and their functions provide a better understanding of the genomic architecture and physiological mechanisms underlying MUN in Holstein cattle.
ABSTRACT: The longevity of dairy cattle has economic, animal welfare, and health implications and is influenced by the frequency of mortality on the farm and sale for slaughter. In this study cows removed from the herd due to death or slaughter during the lactation were coded 1 and cows that were not terminated were coded 0. Genetic parameters for mortality rates (MR) and slaughter rates (SR) were estimated for Holstein (H) and Jersey (J) breeds by applying both linear (LM) and threshold (TM) sire models using about 1.2 million H and 286,000 J cows. Estimated breeding values (EBV) for MR and SR were predicted using animal models to assess the opportunity for selection and genetic trends. Cow termination data, recorded between 1990 and 2020 on a voluntary basis by Australian dairy farmers, were analyzed. Cow MR has increased from below 1% in the 1990s to 4.1% and 3.6% in recent years in H and J cows, respectively. Most dead cows (∼36%) left the herd before 120 d of lactation, while cows that were slaughtered left the herd toward the end of the lactation. Using the LM, heritability (h2) estimates for MR were lower (1%) than those for SR (2%–3.5%). When h2 were estimated using a TM, the estimates for both traits varied between 4% and 20%, suggesting that the difference in incidence level is one of the reasons for the difference in the h2 values between MR and SR. Early test-day milk yield (MY) and 305-d MY (305-d MY) have unfavorable genetic correlations (0.32–0.41) with MR in both breeds. The genetic correlations of calving interval with MR were stronger (0.54–0.68) than with SR (0.28–0.45) suggesting that poor fertility can serve as an early indicator of poor cow health that may lead to increased risk of death. High early test-day somatic cell count is genetically associated with increased likelihood of slaughter (0.24–0.46), but not with increased likelihood of death. In H, 305-d protein yield (PY) had the strongest genetic correlation (−0.34 to −0.40) with SR whereas in J, both 305-d PY and fat yield showed high genetic (−0.64 to −0.70) and moderate environmental (−0.35 to −0.37) correlations with SR. The genetic correlation of removal from the herd due to death and slaughter was negative (−0.3) in J and zero in H. Strong selection for improved fertility and survival and less selection emphasis for MY, has led to an improvement in the genetic trend for cow MR in H and the trend in J has stabilized. Although genetic evaluations for cow MR are feasible, the reliabilities of the EBV are low and the level of cow MR in Australia are relatively low compared with similar countries. Therefore, genetic evaluation for survival based on mortality and slaughter data could be sufficient in the current selection circumstances where breeding objectives are broadly defined. Nevertheless, all Australian farmers should be encouraged to continue recording mortality and slaughter data for monitoring of the trends and for future development of genetic evaluations.
Michele Pazzola, Giorgia Stocco, Alessandro Ferragina
et al.
ABSTRACT: The objectives of this study were to explore the use of Fourier-transform infrared (FTIR) spectroscopy on individual sheep milk samples for predicting cheese-making traits, and to test the effect of the farm variability on their prediction accuracy. For each of 121 ewes from 4 farms, a laboratory model cheese was produced, and 3 actual cheese yield traits (fresh cheese, cheese solids, and cheese water) and 4 milk nutrient recovery traits (fat, protein, total solids, and energy) in the curd were measured. Calibration equations were developed using a Bayesian approach with 2 different scenarios: (1) a random cross-validation (80% calibration; 20% validation set), and (2) a leave-one-out validation (3 farms used as calibration, and the remaining one as validation set) to assess the accuracy of prediction of samples from external farms, not included in calibration set. The best performance was obtained for predicting the yield and recovery of total solids, justifying for the practical application of the method at sheep population and dairy industry levels. Performances for the remaining traits were lower, but still useful for the monitoring of the milk processing in the case of fresh curd and recovery of energy. Insufficient accuracies were found for the recovery of protein and fat, highlighting the complex nature of the relationships among the milk nutrients and their recovery in the curd. The leave-one-out validation procedure, as expected, showed lower prediction accuracies, as a result of the characteristics of the farming systems, which were different between calibration and validation sets. In this regard, the inclusion of information related to the farm could help to improve the prediction accuracy of these traits. Overall, a large contribution to the prediction of the cheese-making traits came from the areas known as “water” and “fingerprint” regions. These findings suggest that, according to the traits studied, the inclusion of water regions for the development of the prediction equation models is fundamental to maintain a high prediction accuracy. However, further studies are necessary to better understand the role of specific absorbance peaks and their contribution to the prediction of cheese-making traits, to offer reliable tools applicable along the dairy ovine chain.