Monthly Test Day Research Articles

Association of lactation persistency with genetic variants of bovine growth hormone gene in Indian Sahiwal cows

The aim of this study was to determine the associations of persistency with genetic variants of bovine growth hormone (bGH) gene in Indian Sahiwal cows. The data pertaining to the monthly test day milk yield (MTDMY) and first lactation length (FLL) of 305 lactating Sahiwal cows over a period of 23 years (1993–2016) were subjected to analysis. Persistency of milk yield was estimated by using test day based ratio method and Wilmink b function. Mean LL was 220.06±8.15 days in all studied Sahiwal cows, however, 276.67±10.25 days in cows with ≥100 days of LL and having 500 kg MY. The peak of milk yields was achieved at third TD of the first lactation. Macrophage stimulating protein 1 (MspI) and Arthrobacter luteus1 (AluI) restriction endonucleases were used to digest the amplified regions in intron 3 and exon 5, respectively of bGHgene. The bGHMspI restriction fragment length polymorphism (RFLP) yielded TT, CT and CC genotypes, whereas bGH-AluIRFLP yielded CC, CG and GG genotypes. Significant association was found between first lactation persistency estimated using test day based ratio method and bGH-MspI polymorphism. No significant association was found between first lactation persistency and bGH-AluI polymorphism. In summary, results of present study revealed that the TT genotype of bGH–MspI gene in Sahiwal cows has better lactation persistency than other genotypes.

Testing the efficacy of different lactation curve models for monthly test day milk yield

The test day milk yield data on 511 crossbred cattle were obtained and utilized according to monthly interval upto 305 th day maintained at Instructional Dairy Farm, of G. B. Pant University of Agriculture and Technology, Pantnagar (Uttarakhand). The different statistical models considered in this study for predicting the shape of lactation curve were Exponential Function, Parabolic Exponential Function, Inverse Polynomial Function and Gamma Type Function. Maximum coefficient of determination (R 2 ) value was observed for Inverse Polynomial function (R 2 = 99.97%) followed by Gamma function (R 2 = 88.28%), Parabolic function (R 2 = 80.95 %), and Exponential function (R 2 = 39.10%). The root mean square error (RMSE) was least for Inverse Polynomial function (0.07 kg) followed by Gamma Type function (0.10kg ), Parabolic Exponential function (0.12 kg ) and Exponential function (0.21 kg ). The absolute mean deviation (AMD) was least for Inverse Polynomial (0.16 Kg) followed by Gamma Type function (0.24 Kg), Parabolic Exponential (0.31Kg) and Exponential function (0.48) confirming the same order of superiority.

Effect of Season, Parity and Stage of Lactation on Productive Performance of Sahiwal Cattle

The study was conducted to understand the effect of season, parity and stage of lactation on productive performance of Sahiwal cattle. The data of productive traits of 133 Sahiwal cattle from 2016 to 2018 maintained at the Livestock Research Center, Karnal, Haryana, were used for this study. The production data were analyzed using least-square procedures based on season, parity and stage of lactation. Results indicated that the parity had significant (p less than 0.05) influence on monthly milk yield (MMY) whereas, the stage of lactation had highly significant (P less than 0.01) influence on monthly milk yield (MMY) and test day milk yield (TDMY). However, there was no significant effect of season on different productive performance traits in Sahiwal cattle. The phenotypic parameter estimates indicated that the parity and stage of lactation of cattle can be used as a selection tool for improvement of productive traits considering its high positive phenotypic correlations with succeeding productive traits in Sahiwal cows.

Мастнокиселинен състав на мляко от биволици при интензивно и пасищно отглеждане

With the aim to assess the fatty-acid profile of buffalo milk from intensive and pasture farming system, the study included two farms. Farm 1 assigned 9 non-grazing buffaloes raised on green fodder or maize silage, and Farm 2 – 8 buffaloes on pasture until November and hay in winter. Individual samples of milk, taken in 7 monthly test days from August to February, were subjected to the Roese-Gottlieb lipid analysis. Analyses of variance were carried out per each fatty acid (FA), including the effects of farming, test day, milk yield and fat content. Farming system was established to be significant source of variation of all individual monounsaturated and polyunsaturated FAs (PUFA) and total PUFA. All PUFAs, except C20:3n3 and C20:2n6, showed better values in the milk from the buffaloes on pasture – more than 2-fold difference in total conjugated linoleic acids (0.913%) and rumenic acid (0.829%) in particular, in alpha-linolenic (0.145%) and gamma-linolenic (0.502%) acid, and in omega-3 FAs (n3), rendering n6/n3 ratio definitely lower (1.99). This applies also to greater extent to trans-C18:1 (4.027%) and vaccenic acid (2.323%) in particular, and to lesser to atherogenicity (2.44) and thrombogenicity (3.21) index. While C18:4n3 was found to increase, vaccenic and gamma-linolenic acid decline throughout grazing season, as well as conjugated linoleic acids with the exception of a peak in December. C20:5n3, C22:5n3 and C20:3n6 are characterized by such even more pronounced peak.

Comparative study of ANN and conventional methods in forecasting first lactation milk yield in Murrah buffalo

Present investigation was undertaken to predict first lactation 305-day milk yield (FL305DMY) using monthly test day milk records. Under this study, multiple linear regression (MLR) and artificial neural network (ANN) approach were used. Effectiveness of both methods was also compared for prediction of FL305DMY in Murrah buffalo. The data on 3336 monthly test day milk yields records of first lactation pertaining to 556 Murrah buffaloes maintained at National Dairy Research Institute, Karnal; Central Institute for research on buffalo; Guru Angad Dev Veterinary and Animal Sciences University (GADVASU), Ludhiana and Choudhary Charan Singh Haryana Agricultural University (CCSHAU), Hisar were used in this study. In MLR study, it was observed that model 14 having four independent variable, i.e. FSP, TD2, TD4 and TD6 fulfilled most criteria such as highest R2, lowest MSE, lowest RMSE, lowest CP, lowest MAE, lowest MAPE, and lowest U value. In the present investigation, the accuracy of prediction obtained from ANN was almost similar to MLR for prediction of FL305DMY using monthly test day milk records in Murrah buffalo. The best ANN algorithm achieved 76.8% accuracy of prediction for optimum model, whereas the MLR explained 76.9% of accuracy of prediction of FL305DMY in Murrah buffalo. MLR method is simple as compared to ANN, hence MLR method could be preferred.

Three-breed rotational crossbreds of Montbéliarde, Viking Red, and Holstein compared with Holstein cows for feed efficiency, income over feed cost, and residual feed intake

Rotational 3-breed crossbred cows of Montbéliarde, Viking Red, and Holstein (CB) were compared with Holstein (HO) cows for alternative measures of feed efficiency as well as income over feed cost (IOFC) and residual feed intake (RFI) during the first 150 d of first, second, and third lactations. Primiparous and multiparous CB (n = 63 and n = 43, respectively) and HO (n = 60 and n = 37, respectively) cows were fed the same total mixed ration twice daily with refusals weighed once daily. Feed was analyzed for dry matter content, net energy for lactation, and crude protein content. Body weight (BW) was recorded twice weekly. Daily production of milk, fat, and protein were estimated from monthly test days with best prediction. Measures of efficiency from 4 to 150 d in milk (DIM) were feed conversion efficiency (FCE), defined as fat plus protein production (kg) per kilogram of dry matter intake (DMI); ECM/DMI, defined as kilograms of energy-corrected milk (ECM) per kilogram of DMI; net energy for lactation efficiency (NELE), defined as ECM (kg) per megacalorie of net energy for lactation intake; crude protein efficiency (CPE), defined as true protein production (kg) per kilogram of crude protein intake; and DMI/BW, defined as DMI (kg) per kilogram of BW. The IOFC was defined as revenue from fat plus protein production minus feed cost. The RFI from 4 to 150 DIM for each lactation was the residual error remaining from regression of DMI on milk energy output (Mcal), metabolic BW, and energy required for change in BW (Mcal). Statistical analysis of measures of feed efficiency and RFI for primiparous cows included the fixed effects of year of calving and breed group. For multiparous cows, statistical analysis included breed as a fixed effect and cow as a repeated effect nested within breed group. Primiparous CB cows had higher means for FCE (+5.5%), ECM/DMI (+4.0%), NELE (+4.0%), and CPE (+5.2%) and a lower mean DMI/BW (-5.3%) than primiparous HO cows. Primiparous CB cows ($875) also had higher mean IOFC than primiparous HO cows ($825). In addition, mean RFI from 4 to 150 DIM was significantly lower (more desirable) for primiparous CB cows than HO cows. Likewise, multiparous CB cows had higher means for FCE (+8.2%), ECM/DMI (+5.9%), NELE (+5.8%), and CPE (+8.1%) and a lower mean for DMI/BW (-4.8%) than multiparous HO cows. Multiparous CB cows ($1,296) also had a higher mean for IOFC than multiparous HO cows ($1,208) and a lower mean for RFI from 4 to 150 DIM than HO cows.

Annual rhythms of milk and milk fat and protein production in dairy cattle in the United States

An annual pattern of milk composition has been well recognized in dairy cattle, with the highest milk fat and protein concentration observed during the winter and lowest occurring in the summer; however, rhythms of milk yield and composition have not been well quantified. Cosinor rhythmometry is commonly used to model repeating daily and annual rhythms and allows determination of the amplitude (peak to mean), acrophase (time at peak), and period (time between peaks) of the rhythm. The objective of this study was to use cosinor rhythmometry to characterize the annual rhythms of milk yield and milk fat and protein concentration and yield using both national milk market and cow-level data. First, 10 yr of monthly average milk butterfat and protein concentration for each Federal Milk Marketing Order were obtained from the US Department of Agriculture Agricultural Marketing Service database. Fat and protein concentration fit a cosine function with a 12-mo period in all milk markets. We noted an interaction between milk marketing order and milk fat and protein concentration. The acrophase (time at peak) of the fat concentration rhythm ranged from December 4 to January 19 in all regions, whereas the rhythm of protein concentration peaked between December 27 and January 6. The amplitude (peak to mean) of the annual rhythm ranged from 0.07 to 0.14 percentage points for milk fat and from 0.08 to 0.12 percentage points for milk protein. The amplitude of the milk fat rhythm generally was lower in southern markets and higher in northern markets. Second, the annual rhythm of milk yield and milk fat and protein yield and concentration were analyzed in monthly test day data from 1,684 cows from 11 tiestall herds in Pennsylvania. Fat and protein concentration fit an annual rhythm in all herds, whereas milk and milk fat and protein yield only fit rhythms in 8 of the 11 herds. On average, milk yield peaked in April, fat and protein yield peaked in February, fat concentration peaked in January, and protein concentration peaked in December. Amplitudes of milk, fat, and protein yield averaged 0.82 kg, 55.3 g, and 30.4 g, respectively. Milk fat and protein concentration had average amplitudes of 0.12 and 0.07, respectively, similar to the results of the milk market data. Generally, milk yield and milk components fit annual rhythm regardless of parity or diacylglycerol O-acyltransferase 1 (DGAT1) K232A polymorphism, with only cows of the low-frequency AA genotype (5.2% of total cows) failing to fit rhythm of milk yield. In conclusion, the yearly rhythms of milk yield and fat and protein concentration and yield consistently occur regardless of region, herd, parity, or DGAT1 genotype and supports generation by a conserved endogenous annual rhythm.

Three-breed rotational crossbreds of Montbéliarde, Viking Red, and Holstein compared with Holstein cows for dry matter intake, body traits, and production

Rotational crossbred cows of the Montbéliarde, Viking Red, and Holstein (HO) breeds (CB) were compared with HO cows for dry matter intake (DMI), body weight (BW), cow height, body condition score (BCS), and production during the first 150 d of first, second, and third lactations. Primiparous and multiparous CB (n = 63 and 43, respectively) and HO (n = 60 and 37, respectively) cows calved from September 2014 to June 2017. Cows were fed the same total mixed ration twice daily, with refusals weighed once daily. The BW was recorded twice weekly, and height at the withers and the hips was recorded monthly. The BCS was evaluated weekly. The fat plus protein production from 4 to 150 d in milk was calculated from monthly test days using best prediction. Primiparous and multiparous cows were analyzed separately. Statistical analysis for primiparous cows included the fixed effects of year of calving and breed group, and the analysis for multiparous cows included the fixed effect of breed group and the repeated effect of cow nested within breed group. Primiparous CB cows (2,807 kg) had lower mean DMI than HO cows (2,948 kg) from 4 to 150 d in milk of first lactation. Mean BW was not different for the CB (562 kg) and HO (556 kg) cows, but primiparous CB cows had mean wither height that was 4.0 cm shorter and mean hip height that was 2.0 cm shorter than that of HO cows. Primiparous CB cows (3.46) had higher mean BCS compared with HO cows (3.20). Mean fat plus protein production did not differ for the primiparous CB and HO cows (331 vs. 329 kg, respectively). Multiparous CB cows (3,360 kg) also had lower mean DMI than HO cows (3,592 kg) and did not differ (636 kg) from HO cows (644 kg) for mean BW. The CB cows had mean wither height that was 3.5 cm shorter than that of HO cows, but mean hip height did not differ for multiparous CB (145.2 cm) and HO (146.4 cm) cows. Mean BCS was higher for multiparous CB cows (3.25) than for HO cows (3.06), and mean fat plus protein production was not different for multiparous CB (445 kg) and HO (441 kg) cows. The lower DMI of the CB cows than HO cows resulted in less feed cost without loss of revenue from fat plus protein production.

Changes in milk yield in the proximity of AI as predictors of conception risk

Adequate increments in milk yield during early lactation are an indication of proper transition from the negative energy balance after calving to more stable stages as lactation progresses. Most research in this area has focused on the transition period, encompassing the 3 weeks before and after calving. However, changes in milk yield in proximity of AI may better predict the probabilities for a successful insemination. We hypothesize that the change in milk yield in 2 consecutive monthly test days around AI is associated with potential fertility of insemination. Therefore, our objective was to test the effect of magnitude of change in milk production in the proximity of AI on the risk of conception in a large population of Holstein cows. The potential associations with cow survival also were analyzed as a secondary objective.

Identification of critical heat stress zone for energy corrected milk yield in Murrah buffaloes using temperature humidity index under subtropical climatic conditions

The present study was conducted to identify the critical heat stress zone (CHSZ) in a year for energy corrected milk yield (ECMY) of Murrah buffaloes. Monthly test day fat percentage data on 734 Murrah buffaloes spread over 20 years (March 1994 to 2013) were collected from ICAR-National Dairy Research Institute, Karnal and climatic parameters, viz. dry bulb temperature, wet bulb temperature and relative humidity for corresponding periods were collected from ICAR-CSSRI, Karnal. The overall least-squares means for monthly test day fat % ranged from 7.58±0.04 in TD2 to 8.02±0.04 in TD9. The monthly test day fat % data was adjusted for the significant non-genetic factors and was used to estimate ECMY (Kcal/kg). The non-heat stress zone (October–March) and heat stress zone (April–September) were identified based on the trend of monthly average test day ECMY in relation to monthly average THI. Within the heat stress zone, July to September exhibited maximum decline in the trait and was empirically identified as the CHSZ. Regression of monthly average ECMY (Kcal/kg) on monthly average THI in the empirically identified CHSZ was carried out to identify the most CHSZ. During July and August, maximum decrease (–8.18) in monthly average ECMY (Kcal/kg) was observed per unit rise in THI. Therefore, July and August months were identified as CHSZ for ECMY in Murrah buffaloes under subtropical climatic condition. Hence, heat stress amelioration programmes should be undertaken during the period to improve ECMY in Murrah buffaloes.

Identification of quantitative trait loci for milk yield in Murrah buffaloes

A reference family consisting of 12 half sib sire families were created for the identification of QTLs for milk yield in buffaloes. Daughters were recorded for monthly test day milk yield. The number of daughters per sire varied from 50 to 335 daughters per sire. Seventy nine polymorphic microsatellite markers located on 8 chromosomes were genotyped for 2281 daughters of the 12 sires. Whole chromosome scanning was done using single marker analysis and interval mapping using three different algorithms. The analysis was carried out sire family wise. QTLs (63) were identified in single marker analysis and 32 QTLs were identified using interval mapping. The significance of LOD score was tested using permutation tests. The metaQTL analysis was carried out to find out the consensus chromosomal regions associated with milk yield in buffaloes. Five models were utilised and the best was selected on the basis of Akaike Information content. Total 23 chromosomal regions were identified for milk yield in buffaloes. 2 metaQTL chromosomal regions were identified on buffalo chromosome BBU2q; 3 metaQTLs each on buffalo chromosomes BBU8, BBU10 and BBU15 and 4 metaQTL regions each on BBU1q, BBU6, BBU9.

Estimation of 305 Day Milk Yield from Cumulative Monthly and Bimonthly Test Day Records in Indonesian Holstein Cattle

The aims of this study were to estimate 305 day first lactation milk yield of Indonesian Holstein cattle from cumulative monthly and bimonthly test day records and to analyze its accuracy.The first lactation records of 258 dairy cows from 2006 to 2014 consisted of 2571 monthly (MTDY) and 1281 bimonthly test day yield (BTDY) records were used. Milk yields were estimated by regression method. Correlation coefficients between actual and estimated milk yield by cumulative MTDY were 0.70, 0.78, 0.83, 0.86, 0.89, 0.92, 0.94 and 0.96 for 2-9 months, respectively, meanwhile by cumulative BTDY were 0.69, 0.81, 0.87 and 0.92 for 2, 4, 6 and 8 months, respectively. The accuracy of fitting regression models (R2) increased with the increasing in the number of cumulative test day used. The used of 5 cumulative MTDY was considered sufficient for estimating 305 day first lactation milk yield with 80.6% accuracy and 7% error percentage of estimation. The estimated milk yield from MTDY was more accurate than BTDY by 1.1 to 2% less error percentage in the same time.

Identification of best temperature humidity index model for assessing impact of heat stress on milk constituent traits in Murrah buffaloes under subtropical climatic conditions of Northern India

The present study was conducted to identify the most suitable temperature humidity index (THI) model among seven reported THI models for analyzing the impact of thermal stress on monthly test day fat % (MTDF%),monthly test day SNF% (MTSNF%), monthly test day fat yield (MTDFY) and monthly test day SNF yield (MTDSNFY) of Murrah buffaloes at subtropical climatic conditions of Karnal, India. A total of 8868 MTDF% and 8606 MTDSNF% records from 1107 lactational records of Murrah buffaloes under five parities were included in the present study and weather information on dry bulb temperature (Tdb), wet bulb temperature (Twb) and relative humidity (RH in %) for the corresponding period of 20 years (March 1994- December 2013) were collected from ICAR-NDRI and ICAR-CSSRI, Karnal, respectively. The overall least-squares means for MTDF% ranged from 7.71 ± 0.067 in TD1 to 8.10 ± 0.08 in TD 9 and MTDSNF% ranged from 9.61 ± 0.01 in TD5 and TD 6 to 9.65 ± 0.01 in TD 8. The overall least squares means of MTDFY (g) ranged from 411.23 ± 14.74 to 745.98 ± 13.57 while for MTDSNFY (g) the value ranged from 491.90 ± 17.21 to 922.16 ± 15.17. Monthly average THI was computed for each of the seven models. The lowest monthly average THI value was found in January, while either May, June or July showed the highest average THI value for all seven THI models. Regression analysis was performed for identifying the best THI to assess the impact of heat stress on milk constituent traits under study anda negative association was found between the milk constituent traits and monthly average THI values.The THI model[THI = (0.55 × Tdb + 0.2 × Tdp) × 1.8 + 32 + 17.5]developed by NRC(1971)was identified as the most suitable THI model to assess the impact of heat stress on milk composition traits of Murrah indicating maximum decline in MTDF% (-0.005), MTDFY (-0.68 g),MTDSNF% (b=-0.0008) and MTDSNFY (-2.25 g) per unit rise in THI.

Impact of environmental factors on milk constituents and yield traits in Murrah buffaloes

The present study was carried out to analyse milk constituents and yield traits using 1,582 first lactation monthly test day records of 224 Murrah buffaloes, calved between 2006 and 2014. The overall least-squares means of monthly test day milk constituent traits, viz. fat, protein, lactose, solids-not-fat (SNF) and total solids (TS) were 7.96 ±0.07, 3.86±0.02, 5.63±0.02, 9.97±0.01 and 17.75±0.07%, respectively. The overall least-squares means ofmonthly test day milk constituent yield traits, viz. milk yield, fat yield, protein yield, lactose yield, SNF yield and TS yield were 6.95±0.15 kg, 549.76±12.97 g, 269.17±6.12 g, 392.52±8.65 g, 681.02±14.97 g and 1231.00±27.46 g, respectively. The estimates of milk constituent traits were found higher in autumn and lower in summer season, except SNF (%) that was found higher in rainy season. All the yield traits were found higher in winter and autumnseason and lower in rainy season. Milk protein (%) was significantly higher during early stage (<90 days) and decreased along with stage of lactation. On the other hand, milk lactose (%) was minimum during early stage of lactation and increased thereafter. All the yield traits were significantly higher during early stage and decreased with the stage of lactation. All the milk constituent traits were higher in buffaloes calved up to the age of 51 months; whereas, buffaloes calved after 51 months of age had higher yield traits. Phenotypic correlations revealed that, milk fat, lactose and TS per cent had very low and negative correlation with monthly test day milk yield. The milk fat (%) had very high and positive correlation with TS (%), indicating that, buffaloes with higher fat content may be selected for higher TS content in milk. Data on variation of milk constituent and yield traits over the years, seasons, stages of lactation and age of buffaloes can be utilized to improve quality as well as quantity of milk in breed improvement programmes.

Artificial Intelligence for Prediction of Standard Lactation Milk yield in Deoni Cattle

A study was carried out on 1764 test day records of Deoni cattle breed located in cattle breeding farm, College of Veterinary and Animal Sciences, Udgir Dist- Latur Maharashtra, the western state of India. A multilayer feed forward neural network with back propagation of error learning mechanism was developed using artificial neural network. The network was trained and simulated using Bayesian regularization (BR) algorithms. The performance efficiency of the network model was evaluated using the value of coefficient of determination (R2-value) and root mean square error. It was observed that, the mean value of test days varies from 1.13 to 1.83 with standard deviation ranged from 0.50 to 1.01. Test day nine contributes highest (87.57%) to the total variability. The highest coefficient of determination i.e. 89.55 % was explained in fourth set with 2 layers and 10 neurons. It was inferred that, standard lactation milk yield of Deoni cows could be predicted on the basis of monthly test day milk records as early as 155th days of lactation with 89.55 % of coefficient of determination and 0.138 of root mean squares error.

Comparison of Three Different Lactation Curve Models for Prediction of Monthly Test Day Milk Yields in First Lactation Murrah Buffaloes

Comparison of Three Different Lactation Curve Models for Prediction of Monthly Test Day Milk Yields in First Lactation Murrah Buffaloes

Genetic and phenotypic analysis of daily Israeli Holstein milk, fat, and protein production as determined by a real-time milk analyzer

The objective was to test the hypothesis that more frequent but less accurately analyzed milk components may give a more representative measure of a cow's total lactation production. Daily records for milk production and fat and protein concentration collected by the AfiLab recording system (Afimilk, Kibbutz Afikim, Israel) from January 2014 to January 2016 from 47 large kibbutz (communal) herds distributed throughout Israel with a total of 37,486 Israeli Holstein cows were compared with the same statistics derived from monthly test day records derived by Bentley and Foss milk analyzers at the central laboratory of the Israel Cattle Breeders Association. The lactation means for all traits were quite similar for the 2 methods in both parities, except for fat production, which was lower for the daily records. This finding corresponded to fat lactation curves, which showed that daily results were lower with low days in milk (DIM) but almost equal to the monthly results after 125 DIM. Relative to monthly records, daily records overestimated protein percentage before 150 DIM and underestimated protein percentage in the second half of the lactation. The standard deviation for first- and second-parity daily records scored by the monthly and daily system were least similar for fat percentage, but even for this trait the difference was no more than 0.1 percentage points. The standard deviations for complete lactation production were slightly lower for the daily results for all traits but protein production. First-parity heritabilities were higher for lactations computed from daily records for all traits except for protein percentage, but differences were not significant. For daily records, coefficients of determination to predict future milk, fat, and protein lactation production from truncated lactations were greatest and root mean squared errors were least if the mean production from the last 2 weeks before the truncation date was used to estimate future production. Daily first-parity partial lactations for milk, fat, and protein production with <150 DIM predicted future lactation more accurately than corresponding monthly partial lactations. With only 30 DIM, genetic correlations between predicted and actual lactations ranged from 0.73 to 0.79 for milk, fat, and protein production. Real-time daily recording of fat and protein concentration by the daily recording system may be preferable to monthly analysis for herd-management decisions and genetic evaluation. Further study is required to compare the results of individual cows in multiple lactations.

Estimates of genetic parameters for fat yield in Murrah buffaloes.

Aim:The present study was performed to investigate the effect of genetic and non-genetic factors affecting milk fat yield and to estimate genetic parameters of monthly test day fat yields (MTDFY) and lactation 305-day fat yield (L305FY) in Murrah buffaloes.Materials and Methods:The data on total of 10381 MTDFY records comprising the first four lactations of 470 Murrah buffaloes calved from 1993 to 2014 were assessed. These buffaloes were sired by 75 bulls maintained in an organized farm at ICAR-National Dairy Research Institute, Karnal. Least squares maximum likelihood program was used to estimate genetic and non-genetic parameters. Heritability estimates were obtained using paternal half-sib correlation method. Genetic and phenotypic correlations among MTDFY, and 305-day fat yield were calculated from the analysis of variance and covariance matrix among sire groups.Results:The overall least squares mean of L305FY was found to be 175.74±4.12 kg. The least squares mean of overall MTDFY ranged from 3.33±0.14 kg (TD-11) to 7.06±0.17 kg (TD-3). The h2 estimate of L305FY was found to be 0.33±0.16 in this study. The estimates of phenotypic and genetic correlations between 305-day fat yield and different MTDFY ranged from 0.32 to 0.48 and 0.51 to 0.99, respectively.Conclusions:In this study, all the genetic and non-genetic factors except age at the first calving group, significantly affected the traits under study. The estimates of phenotypic and genetic correlations of MTDFY with 305-day fat yield was generally higher in the MTDFY-5 of lactation suggesting that this TD yields could be used as the selection criteria for early evaluation and selection of Murrah buffaloes.

Comparison of different lactation curve models in Sahiwal cattle up to fourth parity using monthly test day milk yields.

In present study data of 6391 monthly test day milk yield (MTDMY) records of first lactation pertaining to 691, 4048 MTDMY records of second lactation pertaining to 454, 3013 MTDMY records of third lactation pertaining to 340 and 2280 MTDMY records of fourth lactation pertaining to 249 Sahiwal cows, spread over a period of 51 years (1961- 2011), maintained at NDRI, Karnal were used to compare different lactation curve models. The five different models viz. inverse polynomial function, Wilmink’s exponential function, gamma type function, quadratic cum log function and mixed log function were fitted on MTDMY by statistical package SAS version 9. The relative efficiency of the models was determined on the basis of the higher value of coefficient of determination (R 2 -value) and lesser value of root mean square error (RMSE). The R 2 values ranged from 72.96% (0.154 kg) for Wilmink’s function in first lactation to 99.98% (0.0.043 kg) for inverse polynomial function in third lactation with RMSE values in parentheses. The R 2 value for different lactation curve models showed that the inverse polynomial function gave best fit; whereas Wilmink’s function was found to be least fit in Sahiwal cattle. Hence it can be concluded that inverse polynomial function is the model of choice for estimating the trend of milk production in Sahiwal cattle.

Two approaches to improve fertility of subclinical mastitic dairy cows

Mastitis, particularly in its subclinical form, is a widely spread disease that reduces the fertility of lactating cows. A major cause of poor conception risk has been associated with delayed ovulation of a large subgroup of subclinical mastitic cows. This study examined 2 approaches to improve fertility in this subgroup. Subclinical mastitic cows were defined by somatic cell count elevated above a threshold of 150,000 cells/mL of milk determined in all monthly test day samples collected before AI. Uninfected (control) cows were defined by somatic cell count below threshold. In experiment 1, we examined a hormonal approach aimed to correct the timing of ovulation in mastitic cows in which it would otherwise be delayed. The probability of conception of mastitic and uninfected groups following Ovsynch (OVS) and timed AI versus AI following detected estrus (E) was examined (n=1,553 AI) and analyzed by a multivariable, logistic model statement using the GLIMMIX procedure of SAS. The OVS protocol significantly elevated the probability of conception of mastitic cows to a level similar to that of their uninfected counterparts. Actual mean conception risks for uninfected-E, subclinical-E, uninfected-OVS, and subclinical-OVS groups were 41.8, 26.4, 39.3, and 40.5%, respectively. The OVS protocol did not improve probability of conception in cows diagnosed with uterine disease postpartum. In experiment 2, a management approach aimed to better synchronize timing of ovulation with timing of AI in subclinical mastitic cows was examined. A second AI was added 24h after the first (routine) AI, following detection of natural estrus. Probability of conception did not differ between subclinical mastitic cows inseminated once or twice. Lack of improvement in conception risk might be related to low preovulatory LH surge in mastitic cows, which is likely to induce not only delayed ovulation but also disruption of oocyte maturation. Thus the OVS protocol can improve fertility of subclinical mastitic cows, probably due to “corrected” timing of ovulation in cows in which it would otherwise be delayed.