Breeding and Genetics : Estimation of Daily Milk Yields from AM/PM Milking Records

( Deuk Hwan Lee ),( Hong Rip Min ) 한국동물자원과학회(구 한국축산학회) 2013 한국축산학회지 Vol.55 No.6

Daily milk yields on test days were estimated using morning or afternoon partial milk yields collected by official agencies and the accuracy of the estimates was determined. Test-day data for milk yields consisted of 3,156,734 records of AM/PM partial milking measurements of 255,437 milking Holstein cows from 3,708 farms collected from December 2008 to April 2013. A linear regression model(LRM) was applied to estimate daily milk yields using alternate AM/PM milk yield records within lactation stages, milking intervals, and parities on every daily milk yield. The alternate statistical approach was a non-linear hierarchical model(NHM) in which Brody`s growth function was implemented by reflecting an animal`s physiological milk production cycle. When compared with LRM, daily milk yields predicted by the NHM were assumed to be functionally related to day in milk(or lactation) stage, milking intervals, and partial milk yields. Since the results were in terms of accuracies based on comparisons of different statistical models, accuracies of estimates of daily milk yields by NHM were close to those determined by the LRM. The average of these accuracies was 0.94 for AM partial milk yields and 0.93 for PM partial milk yields for first calving cows. However, the accuracies of AM/PM milk yield estimations from cows under a calving stage higher than the first parity were 0.96 and 0.95, respectively. Correlations between the estimated daily milk yields and the actual daily milk yields ranged from 0.96~ 0.98. These accuracies were lower for unbalanced AM/PM milking intervals and the first calving cows. Overall, prediction of daily milk yields by NHM would be more appropriate than by LRM due to its flexibility under different milk yield-related circumstances, which provides an idea of the functional relationship between milking intervals and days in milk with daily milk yields from statistical viewpoints.

검정일 1회 검정에 의한 착유우의 1일 유량 추정시 오차와 정확도

조용민,안병석,최유림 한국동물자원과학회 2003 한국축산학회지 Vol.45 No.5

This study was conducted to evaluate the adequacy of an alternative ㏂-㏘ testing scheme for milk yield in comparison with the official test method based on weighing two milkings within 24 h. A total of 8,309 ㏘ milking weights and 6,767 ㏂ milking weights from 72 Holstein cows raised at N.L.R.I. were collected between October 2000 and November 2001. Ratios were computes for daily milk yield to ㏂ and ㏘ milking weights(direct yield ratios) and ratios of ㏂ and ㏘ milking weights to daily milk yield (inverse yield ratios). Analysis of variance indicated that the milking interval is the most important source of variation for yield ratios. Adjustment factors for estimating daily milk yield from single milking weights were derived through regression analysis of direct and inverse yield ratios on the length of the milking interval. Daily milk yield was estimated more precisely and accurately when adjustment factors were used than when single milking weights were doubled. In conclusion, alternative recording of ㏂ and ㏘ milking weights led to reliable estimates of milk yields.

The effect of lactation number, stage, length, and milking frequency on milk yield in Korean Holstein dairy cows using automatic milking system

Mayakrishnan Vijayakumar,박지후,기광석,임동현,김상범,박성민,정하연,박범영,김태일 아세아·태평양축산학회 2017 Animal Bioscience Vol.30 No.8

Objective: The aim of the current study was to describe the relationship between milk yield and lactation number, stage, length and milking frequency in Korean Holstein dairy cows using an automatic milking system (AMS). Methods: The original data set consisted of observations from April to October 2016 of 780 Holstein cows, with a total of 10,751 milkings. Each time a cow was milked by an AMS during the 24 h, the AMS management system recorded identification numbers of the AMS unit, the cow being milking, date and time of the milking, and milk yield (kg) as measured by the milk meters installed on each AMS unit, date and time of the lactation, lactation stage, milking frequency (NoM). Lactation stage is defined as the number of days milking per cows per lactation. Milk yield was calculated per udder quarter in the AMS and was added to 1 record per cow and trait for each milking. Milking frequency was measured the number of milkings per cow per 24 hour. Results: From the study results, a significant relationship was found between the milk yield and lactation number (p<0.001), with the maximum milk yield occurring in the third lactation cows. We recorded the highest milk yield, in a greater lactation length period of early stage (55 to 90 days) at a 4× milking frequency/d, and the lowest milk yield was observed in the later stage (>201 days) of cows. Also, milking frequency had a significant influence on milk yield (p<0.001) in Korean Holstein cows using AMS. Conclusion: Detailed knowledge of these factors such as lactation number, stage, length, and milking frequency associated with increasing milk yield using AMS will help guide future recommendations to producers for maximizing milk yield in Korean Dairy industries.

Genetic parameters for milk yield in imported Jersey and JerseyFriesian cows using daily milk records in Sri Lanka

Samaraweera Amali Malshani,Boerner Vinzent,Cyril Hewa Waduge,van der Werf Julius,Hermesch Susanne 아세아·태평양축산학회 2020 Animal Bioscience Vol.33 No.11

Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and –0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.

Rumen bacteria influence milk protein yield of yak grazing on the Qinghai-Tibet plateau

Fan, Qingshan,Wanapat, Metha,Hou, Fujiang Asian Australasian Association of Animal Productio 2021 Animal Bioscience Vol.34 No.9

Objective: Ruminants are completely dependent on their microbiota for rumen fermentation, feed digestion, and consequently, their metabolism for productivity. This study aimed to evaluate the rumen bacteria of lactating yaks with different milk protein yields, using high-throughput sequencing technology, in order to understand the influence of these bacteria on milk production. Methods: Yaks with similar high milk protein yield (high milk yield and high milk protein content, HH; n = 12) and low milk protein yield (low milk yield and low milk protein content, LL; n = 12) were randomly selected from 57 mid-lactation yaks. Ruminal contents were collected using an oral stomach tube from the 24 yaks selected. High-throughput sequencing of bacterial 16S rRNA gene was used. Results: Ruminal ammonia N, total volatile fatty acids, acetate, propionate, and isobutyrate concentrations were found to be higher in HH than LL yaks. Community richness (Chao 1 index) and diversity indices (Shannon index) of rumen microbiota were higher in LL than HH yaks. Relative abundances of the Bacteroidetes and Tenericutes phyla in the rumen fluid were significantly increased in HH than LL yaks, but significantly decreased for Firmicutes. Relative abundances of the Succiniclasticum, Butyrivibrio 2, Prevotella 1, and Prevotellaceae UCG-001 genera in the rumen fluid of HH yaks was significantly increased, but significantly decreased for Christensenellaceae R-7 group and Coprococcus 1. Principal coordinates analysis on unweighted UniFrac distances revealed that the bacterial community structure of rumen differed between yaks with high and low milk protein yields. Furthermore, rumen microbiota were functionally enriched in relation to transporters, ABC transporters, ribosome, and urine metabolism, and also significantly altered in HH and LL yaks. Conclusion: We observed significant differences in the composition, diversity, fermentation product concentrations, and function of ruminal microorganisms between yaks with high and low milk protein yields, suggesting the potential influence of rumen microbiota on milk protein yield in yaks. A deeper understanding of this process may allow future modulation of the rumen microbiome for improved agricultural yield through bacterial community design.

Prediction of Future Milk Yield with Random Regression Model Using Test-day Records in Holstein Cows

Park, Byoungho,Lee, Deukhwan Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.7

Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to predict future milk yield of Holstein cows in Korea. A total of 257,908 test-day (TD) milk yield records from a total of 28,135 cows belonging to 1,090 herds were considered for estimating (co)variance of the random covariate coefficients using an expectation-maximization REML algorithm in an animal mixed model. The variances did not change much between the models, having different order of Legendre polynomial, but a decreasing trend was observed with increase in the order of Legendre polynomial in the model. The R-squared value of the model increased and the residual variance reduced with the increase in order of Legendre polynomial in the model. Therefore, a model with $5^{th}$ order of Legendre polynomial was considered for predicting future milk yield. For predicting the future milk yield of cows, 132,771 TD records from 28,135 cows were randomly selected from the above data by way of preceding partial TD record, and then future milk yields were estimated using incomplete records from each cow randomly retained. Results suggested that we could predict the next four months milk yield with an error deviation of 4 kg. The correlation of more than 70% between predicted and observed values was estimated for the next four months milk yield. Even using only 3 TD records of some cows, the average milk yield of Korean Holstein cows would be predicted with high accuracy if compared with observed milk yield. Persistency of each cow was estimated which might be useful for selecting the cows with higher persistency. The results of the present study suggested the use of a $5^{th}$ order Legendre polynomial to predict the future milk yield of each cow.

Monitoring Feeding Adequacy in Dairy Cows Using Milk Urea and Milk Protein Contents under Farm Condition

Dhali, A.,Mehla, R.K.,Sirohi, S.K.,Mech, A.,Karunakaran, M. Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.12

The experiment was conducted on 264 crossbred Karan-Fries (Holstein Friesian${\times}$Tharparkar) cows, over one year to explore the possibility of using milk urea (MU) concentration and milk protein content to monitor feeding adequacy under farm condition and to investigate the effects of different animal factors and season on MU concentration. Individual noon (1200 to 1300 h) milk samples were collected once in every month and analysed for urea and protein contents. Representative feed samples were also collected on the same day of milk collection and were analysed for CP content. A significant positive association (p<0.01) between MU concentration and milk yield was observed. MU concentrations (mg/dl) were found to be significantly (p<0.01) higher and lower in first lactation (44.8${\pm}$0.7) and in early lactation stage (40.7${\pm}$0.5), respectively. Average MU values were found to be significantly (p<0.01) higher in winter (50.7${\pm}$0.3) and lower in summer (32.9${\pm}$0.6). During the investigation, of the total MU observations, 50.3% were within the range of 30 to 50 mg/dl, 21.4% were <30 mg/dl and only 7.5% were >60 mg/dl. MU concentration was found to be associated significantly (p<0.05) with CP content of forages rather than concentrate. A close positive association (p<0.01) between MU level and daily milk protein (DMP) yield was observed during the investigation. The regression equation, DMP yield (g) = -24.6+33.5 daily milk yield (kg) +0.9 MU (mg/dl) was developed to establish the reference level of DMP yield. The result indicates that the effect of parity and stage of lactation may be ignored while interpreting MU values. However, reference MU values may be standardised separately for high milk yielders as level of milk yield contributes significantly to the variation of MU. The study revealed that the MU values together with DMP yield and milk protein content could be used as a potential non-invasive pointer to monitor feeding adequacy in dairy cows under farm conditions.

Quality and Amount of Morning and Evening Milk of the Bangladesh Baghabarighat Milk Shed Area Throughout the Year

Islam, K.M.S. Asian Australasian Association of Animal Productio 2001 Animal Bioscience Vol.14 No.1

The Baghabarighat Milk Shed Area (BMSA), in Bangladesh belonging to the Bangladesh Milk Producers Cooperative Union Limited (BMPCUL) was selected to study the qualitative and quantitative aspects of dairy milk and to establish a trend throughout the year (July 1995 to June 1990) of milk collected at morning and evening, and daily. The average fat, solids-not-fat (SNF) and total solid (TS) contents of the morning milk were 4.58, 7.75 and 12.33%, respectively, and evening milk contained 5.41, 7.81 and 13.23%. The values for the quality varied (p<0.01) throughout the year without a specific trend. Higher milk collection occured at morning (52.77%) than evening (47.24%), but total yield of fat from morning milk was lower (48.74%) than evening milk (51.26%) due to a lower fat value (4.58%). Yield of SNF (52.57% morning, 47.37% evening) followed the values of the amount of milk collected due to their similar value at morning (7.75) and evening (7.81). Overall, TS yield was 51 and 49% from morning and evening. There was not a significant (p>0.01) relationship between fat and TS values of morning milk with those of evening milk, but there was a correlation (p<0.01) between milk yield at morning and all other parameters for evening. Solids-not-fat value of morning milk was related with yield and SNF value of milk from evening, but not with fat and TS evening milk. It may be concluded that evening milk contains higher amounts of fat, SNF and TS, but yields were higher at morning, except fat. Milk collected at morning showed a relationship with all the parameters found at evening.

Lactation Persistency as a Component Trait of the Selection Index and Increase in Reliability by Using Single Nucleotide Polymorphism in Net Merit Defined as the First Five Lactation Milk Yields and Herd Life

Togashi, K.,Hagiya, K.,Osawa, T.,Nakanishi, T.,Yamazaki, T.,Nagamine, Y.,Lin, C.Y.,Matsumoto, S.,Aihara, M.,Hayasaka, K. Asian Australasian Association of Animal Productio 2012 Animal Bioscience Vol.25 No.8

We first sought to clarify the effects of discounted rate, survival rate, and lactation persistency as a component trait of the selection index on net merit, defined as the first five lactation milks and herd life (HL) weighted by 1 and 0.389 (currently used in Japan), respectively, in units of genetic standard deviation. Survival rate increased the relative economic importance of later lactation traits and the first five lactation milk yields during the first 120 months from the start of the breeding scheme. In contrast, reliabilities of the estimated breeding value (EBV) in later lactation traits are lower than those of earlier lactation traits. We then sought to clarify the effects of applying single nucleotide polymorphism (SNP) on net merit to improve the reliability of EBV of later lactation traits to maximize their increased economic importance due to increase in survival rate. Net merit, selection accuracy, and HL increased by adding lactation persistency to the selection index whose component traits were only milk yields. Lactation persistency of the second and (especially) third parities contributed to increasing HL while maintaining the first five lactation milk yields compared with the selection index whose only component traits were milk yields. A selection index comprising the first three lactation milk yields and persistency accounted for 99.4% of net merit derived from a selection index whose components were identical to those for net merit. We consider that the selection index comprising the first three lactation milk yields and persistency is a practical method for increasing lifetime milk yield in the absence of data regarding HL. Applying SNP to the second- and third-lactation traits and HL increased net merit and HL by maximizing the increased economic importance of later lactation traits, reducing the effect of first-lactation milk yield on HL (genetic correlation ($r_G$) = -0.006), and by augmenting the effects of the second- and third-lactation milk yields on HL ($r_G$ = 0.118 and 0.257, respectively).

The Yield and Composition of Milk from Transgenic Rabbits

Chrenek, P.,Chrastinova, L.,Kirchnerova, K.,Makarevich, A.V.,Foltys, V. Asian Australasian Association of Animal Productio 2007 Animal Bioscience Vol.20 No.4

Basic objective of this research was to compare the milk yield and composition of New Zealand White transgenic rabbit females expressing recombinant human factor VIII (hFVIII) in mammary gland during lactation with that of non-transgenic rabbit females of the same age during 30 days of lactation. Transgenic founders were generated by the microinjection of foreign DNA (mWAP-hFVIII gene construct) into the egg. F1, F2 and F3 generations of transgenic rabbits were obtained after mating of transgenic founder rabbits with non-transgenic rabbits. The amount of milk rejected was measured by weight-suckle-weight method at $10^{th}$, $20^{th}$and $30^{th}$ day of lactation. Quality of milk (content of fat, protein, lactose, dry ash, and some minerals) from transgenic and non-transgenic rabbit was also determined. Comparison of milk yield, determined by weight-suckle-weight method, showed significantly higher (p<0.05) milk production at day 20 of first lactation in non-transgenic females, but on the same day of second lactation higher milk yield was measured in transgenic ones. Significantly higher (p<0.05) content of milk fat and protein was determined in transgenic milk whilst higher content of lactose was found in non-transgenic milk. The content of minerals (calcium, phosphorus, magnesium and sodium) did not differ in both experimental and control groups. Our results showed that milk yield and composition of transgenic rabbit females (mammary specific transgenic over-expression of hFVIII) over several generations is only slightly and transiently different from milk yield of non-transgenic females, which had no significant consequence on the litter size and viability.