scholarly journals Comparison of the fit of automatic milking system and test-day records with the use of lactation curves

2020 ◽  
Vol 33 (3) ◽  
pp. 408-415
Author(s):  
B. Sitkowska ◽  
M. Kolenda ◽  
D. Piwczyński
Keyword(s):  
Bayesian Information Criterion ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Dairy Herds ◽  
Lactation Curve ◽  
Milk Performance ◽  
Automatic Milking System ◽  
Automatic Milking ◽  
Automatic Milking Systems ◽  
Wood Model

Objective: The aim of the paper was to compare the fit of data derived from daily automatic milking systems (AMS) and monthly test-day records with the use of lactation curves; data was analysed separately for primiparas and multiparas.Methods: The study was carried out on three Polish Holstein-Friesians (PHF) dairy herds. The farms were equipped with an automatic milking system which provided information on milking performance throughout lactation. Once a month cows were also subjected to test-day milkings (method A4). Most studies described in the literature are based on test-day data; therefore, we aimed to compare models based on both test-day and AMS data to determine which mathematical model (Wood or Wilmink) would be the better fit.Results: Results show that lactation curves constructed from data derived from the AMS were better adjusted to the actual milk yield (MY) data regardless of the lactation number and model. Also, we found that the Wilmink model may be a better fit for modelling the lactation curve of PHF cows milked by an AMS as it had the lowest values of Akaike information criterion, Bayesian information criterion, mean square error, the highest coefficient of determination values, and was more accurate in estimating MY than the Wood model. Although both models underestimated peak MY, mean, and total MY, the Wilmink model was closer to the real values.Conclusion: Models of lactation curves may have an economic impact and may be helpful in terms of herd management and decision-making as they assist in forecasting MY at any moment of lactation. Also, data obtained from modelling can help with monitoring milk performance of each cow, diet planning, as well as monitoring the health of the cow.

Evaluation of automatic milking system variables in dairy cows with different levels of lactation stage and reproduction status

2019 ◽  
Vol 86 (4) ◽  
pp. 410-415
Author(s):  
Vida Juozaitiene ◽  
Arunas Juozaitis ◽  
Judita Zymantiene ◽  
Ugne Spancerniene ◽  
Ramunas Antanaitis ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Dairy Herds ◽  
Additional Tool ◽  
Milk Flow ◽  
Lactation Stage ◽  
Automatic Milking System ◽  
Automatic Milking ◽  
Group 2 ◽  
Automatic Milking Systems ◽  
Group 1

AbstractIn this study, we hypothesized that differences of automatic milking systems (AMS) variables in dairy cows during estrus and through diverse stages of lactation can be suggested as alternative indicators to support the pregnancy in dairy farms using automatic milking systems. The key objectives were: (1) to determine the variation of automatic milking system indicators during lactation and to estimate the relationship with reproduction status in dairy cows; (2) to test the hypothesis that milking traits of cows can be influenced by estrus and conceiving, and can be used as a predictor of the likelihood of reproductive success in dairy herds. Estrus synchronization was performed in 368 healthy Lithuanian Black and White cows. All cows (n = 368) were synchronized and inseminated for the first time on the 91st day in milk (DIM). Cows not pregnant (17.39%) were synchronized and inseminated again at 132 DIM. After the first insemination pregnant (n = 304) cows were identified as group 1, after the second insemination pregnant (n = 58) cows – as group 2. Overall, 12 01 713 records of udder quarters in cows from 5 to 305 DIM were evaluated. The results revealed the reduction in milk yield during estrus 11.05% on 91 DIM and 13.89% on 132 DIM (P < 0.001) and an increment in milk flow traits in cows after 91 DIM (P < 0.05), also a slight decline in milk flow traits on 132 DIM. Furthermore, milking frequency (MF) of cows decreased significantly (P < 0.001) after conceiving. The interval between milkings (MI) increased (40.30%) during estrus of cows in group 1 (P < 0.001), and thereafter gradually increased, however in group 2 there was a temporary increment (6.06%) on the 91 DIM and steady rise (42.13%) on 132 DIM was noticed. The results highlight that changes in AMS indicators of cows may be considered as an additional tool for improvement of reproductive management in dairy herds, but further research-based studies are necessary before practical application.

Introducing a sinusoidal equation to describe lactation curves for cumulative milk yield and composition in Holstein cows

2020 ◽  
Vol 87 (2) ◽  
pp. 220-225
Author(s):  
Navid Ghavi Hossein-Zadeh ◽  
Hassan Darmani Kuhi ◽  
James France ◽  
Secundino López
Keyword(s):  
Linear Model ◽  
Milk Yield ◽  
Milk Fat ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Production Traits ◽  
Lactation Curve

AbstractThe aim of the work reported here was to investigate the appropriateness of a sinusoidal function by applying it to model the cumulative lactation curves for milk yield and composition in primiparous Holstein cows, and to compare it with three conventional growth models (linear, Richards and Morgan). Data used in this study were 911 144 test-day records for milk, fat and protein yields, which were recorded on 834 dairy herds from 2000 to 2011 by the Animal Breeding Centre and Promotion of Animal Products of Iran. Each function was fitted to the test-day production records using appropriate procedures in SAS (PROC REG for the linear model and PROC NLIN for the Richards, Morgan and sinusoidal equations) and the parameters were estimated. The models were tested for goodness of fit using adjusted coefficient of determination $\lpar {R_{{\rm adj}}^2 } \rpar $, root mean square error (RMSE), Akaike's information criterion (AIC) and the Bayesian information criterion (BIC). $R_{{\rm adj}}^2 $ values were generally high (>0.999), implying suitable fits to the data, and showed little differences among the models for cumulative yields. The sinusoidal equation provided the lowest values of RMSE, AIC and BIC, and therefore the best fit to the lactation curve for cumulative milk, fat and protein yields. The linear model gave the poorest fit to the cumulative lactation curve for all production traits. The current results show that classical growth functions can be fitted accurately to cumulative lactation curves for production traits, but the new sinusoidal equation introduced herein, by providing best goodness of fit, can be considered a useful alternative to conventional models in dairy research.

Application of the Wood model to analyse lactation curves of organic dairy sheep farming

2014 ◽  
Vol 54 (10) ◽  
pp. 1609 ◽  
Author(s):  
Juan Carlos Ángeles Hernández ◽  
Octavio Castelán Ortega ◽  
Benito Albarrán Portillo ◽  
Hugo H. Montaldo ◽  
Manuel González Ronquillo
Keyword(s):  
Milk Yield ◽  
Goodness Of Fit ◽  
Evaluation Criteria ◽  
Coefficient Of Determination ◽  
Dairy Sheep ◽  
Organic System ◽  
Dairy Ewes ◽  
Lactation Curve ◽  
Total Milk ◽  
Wood Model

The aim of the present study was to evaluate the performance of the Wood model to describe the characteristics of lactation curves of dairy ewes under organic management in Mexico. In total, 4861 weekly test-day milk yield records from 194 lactations of crossbred dairy ewes were analysed to assess the performance of an empirical model to fit their lactation curve. We used the mathematical model proposed by Wood. The evaluation criteria were the correlation coefficient (r) between the values of total milk yield observed and estimated, the coefficient of determination (R2), and the mean square prediction error (MSPE). In addition, the peak yield (PYest) and time at peak yield (PTest) were calculated. The Wood model showed adequate goodness of fit (r = 0.95, R2 = 0.92 and MSPE = 0.024). The Wood model detected that 52.06% of lactation curves had a continuously decreasing shape (atypical curve), probably as a consequence of the characteristic management of the organic system, mainly due to the genotype used and the nutritional management. Residuals were greater for atypical curves than for typical ones, indicating differences in the ability of the Wood model to fit the two types of shapes. In typical curves, the Wood model showed adequate estimates of total milk yield and time at peak yield. The peak yield was underestimated both in typical and atypical curves. The Wood model in atypical curves underestimated the time at peak yield and milk yields in late lactation. The Wood model showed a reasonable fit of lactation curve in dairy sheep in organic systems but presented deficiencies of fit in atypical curves; therefore, estimates should be interpreted carefully.

scholarly journals Sinusoidal function to describe the growth curve of dairy heifers

2019 ◽  
Vol 59 (6) ◽  
pp. 1039
Author(s):  
H. Darmani Kuhi ◽  
N. Ghavi Hossein-Zadeh ◽  
S. López ◽  
S. Falahi ◽  
J. France
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Bayesian Information Criterion ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Dairy Heifers ◽  
Growth Functions ◽  
Best Fit ◽  
Sinusoidal Function

The objective of the present study is to introduce a sinusoidal function into dairy research and production by applying it to bodyweight records (from 1 to 24 months) from six dairy cow breeds reported by the Dairy Heifer Evaluation Project of Penn State Extension (USA) from 1991 to 1992. The function was evaluated with regard to its ability to describe the relationship between bodyweight and age in dairy heifers, and then compared with seven standard growth functions, namely monomolecular, logistic, Gompertz, von Bertalanffy, Richards, Schumacher and Morgan. The models were fitted to monthly bodyweight records of dairy heifers using non-linear regression to derive estimates of the parameters of each function. The models were tested for goodness of fit by using adjusted coefficient of determination, root mean square error, Akaike’s information criterion and Bayesian information criterion. Values of adjusted coefficient of determination were generally high for all models, suggesting the generally appropriate fit of the models to the data. The sinusoidal function provided the best fit of the growth curves for Brown Swiss, Guernsey and Milking Shorthorn breeds due to the lowest values of root mean square error, Akaike’s information criterion and Bayesian information criterion. According to the chosen statistical criteria, the Richards function provided the best fit for Ayrshire heifers, and the monomolecular the best for Holstein and Jersey. The least accurate estimates were obtained with the logistic. In conclusion, the sinusoidal function introduced here can be considered as an appropriate alternative to standard growth functions when modelling growth patterns in dairy heifers.

scholarly journals Comparison of models for describing the lactation curve of Awassi, Morkaraman and Tushin sheep

2010 ◽  
Vol 53 (4) ◽  
pp. 447-456
Author(s):  
O. C. Bilgin ◽  
N. Esenbuga ◽  
M. E. Davis
Keyword(s):  
Prediction Error ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Peak Time ◽  
Mean Square ◽  
Lactation Curve ◽  
Breed Differences ◽  
Watson Statistic ◽  
Wood Model ◽  
Awassi Breed

Abstract. The aim of this study was to identify a suitable mathematical model for describing the lactation curve of Awassi, Morkaraman and Tushin sheep breeds and to determine breed differences. Data on milk yield of 182 Awassi, 47 Morkaraman and 74 Tushin ewes were used. Eight empirical models from the literature were used to fit the standard lactation curves. Among them the Wood model (WD) appeared the most appropriate according to mean square prediction error (MSPE), coefficient of determination (R2), Durbin-Watson statistic (DW), and its applicability to the data for all three breeds. There were statistically significant (P<0.05) differences among Awassi, Morkaraman and Tushin breeds in accordance with a, b and c parameters and peak yield. The Awassi breed had the highest peak yield and the Morkaraman and Tushin breeds had statistically similar lower peak yields. There were no significant differences among the parameters of the WD model except for peak yield and peak time in accordance with parities. Breed and parity interaction was significant (P<0.05) only for peak yield.

scholarly journals Comparison of the parameters of the lactation curve between normal and difficult calvings in Iranian Holstein cows

2019 ◽  
Vol 17 (1) ◽  
pp. e0401
Author(s):  
Navid Ghavi Hossein-Zadeh
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Lactation Curve ◽  
Non Linear ◽  
Best Fit

To evaluate effect of dystocia on the lactation curve characteristics for milk yield and composition in Holstein cows, six non-linear models (Brody, Wood, Sikka, Nelder, Dijkstra and Rook) were fitted on 5,917,677 test day records for milk yield (MY), fat (FP) and protein (PP) percentages, fat to protein ratio (FPR) and somatic cell score (SCS) of 643,625 first lactation Holstein cows with normal calving or dystocia from 3146 herds which were collected by the Animal Breeding Center of Iran. The models were tested for goodness of fit using adjusted coefficient of determination, root means square error, Akaike’s information criterion and Bayesian information criterion. Rook model provided the best fit of the lactation curve for MY and SCS in normal and difficult calvers and dairy cows with dystocia for FP. Dijkstra model provided the best fit of the lactation curve for PP and FPR in normal and difficult calvers and dairy cows with normal calving for FP. Dairy cows with dystocia had generally lower 100-d, 200-d and 305-d cumulative milk yield compared with normal calvers. Time to the peak milk yield was observed later for difficult calvers (89 days in milk vs. 79 days in milk) with lower peak milk yield (31.45 kg vs. 31.88 kg) compared with normal calvers. Evaluation of the different non-linear models indicated that dystocia had important negative effects on milk yield and lactation curve characteristics in dairy cows and it should be reduced as much as possible in dairy herds.

PROBLEMS OF PROVIDING COWS CONCENTRATES IN AUTOMATIC MILKING SYSTEMS

2020 ◽  
pp. 26-28
Author(s):  
Д.Р. ШАРИПОВ ◽  
О.А. ЯКИМОВ ◽  
И.Ш. ГАЛИМУЛЛИН
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Holstein Cows ◽  
Opposite Trend ◽  
Automatic Milking System ◽  
Automatic Milking ◽  
Automatic Milking Systems ◽  
The Given ◽  
Visiting Time

Изучена технология дополнительного скармливания концентрированных кормов во время доения в условиях системы автоматизированного доения на коровах голштинской породы, разделенных на 6 групп по молочной продуктивности. Исследования показали, что с повышением молочной продуктивности в группах коров увеличивается количество выданных и потребленных концентратов. Аналогичная закономерность установлена по времени посещения доильной станции на количество потребления комбикорма, чем дольше коровы задерживаются в боксах доения, тем больше концентрированных кормов они потребляют. Животные всех групп неполностью съедают комбикорм, получаемый на станции доения, остатки концентратов от выданной нормы в группе коров с удоем менее 20,0 кг составили 8,3%, 20,1—25,0 кг — 3,6%, 25,1—30,0 кг — 5,9%, 30,1—35,0 кг — 8,9%, 35,1—40,0 кг — 7,9% и в группе с удоем более 40,1 кг — 7,5%. Анализ затрат концентрированных кормов,получаемых на станции доения, на 1 кг молока показал, что группы коров с удоем 35,1—40,0 и более 40,1 кг на 11,5—18,9% недополучают концентратов, обратная тенденция в группе коров с удоем 20,1—25,0 и менее 20,0 кг, которым для сохранения интереса к роботизированной установке требуется на 9,4—10,4% больше концентрированных кормов. The technology of additional feeding of concentrated feeds during milking under the conditions of an automatic milking system on Holstein cows, divided into 6 groups according to milk production, has been studied. Studies have shown that with an increase in milk production in the groups of cows, the amount of concentrates allocated and consumed increases. The influence of box-visiting time per milking on the amount of concentrate consumption has been established, the longer the cows stay in the milking boxes, the more concentrated feed they consume. Animals of all groups do not fully consume the compound feed obtained in the milking box, the remains of concentrates from the given norm in the group of cows with a milk yield of less than 20.0 kg was 8.3%, in the group of  20.1—25.0 kg — 3.6%, in the group of  25, 1—30.0 kg — 5.9%, in the group of 30.1—35.0 kg — 8.9%, in the group of 35.1—40.0 kg — 7.9% and in the group with a milk yield of more  40.1 kg — 7.5%. Analysis of the costs of concentrated feed per kg of milk received at the milking box showed that groups of cows with a yield of 35.1—40.0 and more than 40.1 kg at 11.5—18.9% do not receive concentrates, the opposite trend is a group of cows with a milk yield of 20.1—25.0 and less than 20.0 kg, which require 9.4—10.4% more concentrated feed to maintain interest in a robotic unit.

The milking frequency of primiparous cows in their early stage of lactation and its impact on milking performance

2020 ◽  
Vol 60 (3) ◽  
pp. 436
Author(s):  
Beata Sitkowska ◽  
Dariusz Piwczyński ◽  
Magdalena Kolenda ◽  
Jolanta Różańska-Zawieja
Keyword(s):  
Early Stage ◽  
Stage Of Lactation ◽  
Holstein Friesian ◽  
Full Production ◽  
Milk Performance ◽  
Milking Frequency ◽  
Automatic Milking System ◽  
Automatic Milking ◽  
The Relationship ◽  
Potential Use

An automatic milking system allows cows to present their full production capability by not limiting them to a specific time when the milking occurs or a fix number of milkings per day. The beginning of the first lactation is a key point in terms of subsequent milk production. The aim of the present study was to indicate the relationship between the milking frequency of primiparous cows during the first month of lactation and their subsequent milk performance. Material of the study consisted of 25 Polish herds of Holstein–Friesian dairy cattle. All cows were milked with the use of an automatic milking system. Animals were divided into five groups, depending on the milking frequency in the first month after calving (MFF). The collected data were statistically processed using the multifactorial ANOVA. The best milk and milking parameters characterised primiparous cows, for which the average number of milkings per day was at the level of 3–3.5 or above, this group did not have a preferred time for their milking. This group of cows milked more frequently during the first month of lactation (MFF5) and had the highest milk yield (MY) and milking duration. The highest culling percentage (57.77%) was noted within the group of primiparous cows with the lowest milking frequency during the first month of lactation (MFF1). MFF5 animals maintained better milk and milking parameters in all months of lactation than did those in the other groups. Older animals, that calved after the 28th month of life, and those that calved during warmer seasons, showed the tendency to have a lower milking frequency and poorer milk and milking parameters. The findings obtained in the present study are interesting in terms of their potential use, because they show that frequent milking during the first month after calving corresponds to a better overall MY during that lactation. Hopefully, by promoting frequent milkings at the beginning of lactation, farmer may increase the overall lactation MY.

scholarly journals Mastitis diagnosis in ten Galician dairy herds (NW Spain) with automatic milking systems

2015 ◽  
Vol 13 (4) ◽  
pp. e0504 ◽  
Author(s):  
Angel Castro ◽  
Jose M. Pereira ◽  
Carlos Amiama ◽  
Javier Bueno
Keyword(s):  
Detection System ◽  
Operational Reliability ◽  
Clinical Mastitis ◽  
Standard Test ◽  
Primary Objective ◽  
Dairy Herds ◽  
Nw Spain ◽  
Streptococcus Uberis ◽  
Automatic Milking ◽  
Automatic Milking Systems

<p>Over the last few years, the adoption of automatic milking systems (AMS) has experienced significant increase. However, hardly any studies have been conducted to investigate the distribution of mastitis pathogens in dairy herds with AMS. Because quick mastitis detection in AMS is very important, the primary objective of this study was to determine operational reliability and sensibility of mastitis detection systems from AMS. Additionally, the frequency of pathogen-specific was determined. For this purpose, 228 cows from ten farms in Galicia (NW Spain) using this system were investigated. The California Mastitis Test (CMT) was considered the gold-standard test for mastitis diagnosis and milk samples were analysed from CMT-positive cows for the bacterial examination. Mean farm prevalence of clinical mastitis was 9% and of 912 milk quarters examined, 23% were positive to the AMS mastitis detection system and 35% were positive to the CMT. The majority of CMT-positive samples had a score of 1 or 2 on a 1 (lowest mastitis severity) to 4 (highest mastitis severity) scale. The average sensitivity and specificity of the AMS mastitis detection system were 58.2% and 94.0% respectively being similar to other previous studies, what could suggest limitations for getting higher values of reliability and sensibility in the current AMSs. The most frequently isolated pathogens were <em>Streptococcus dysgalactiae</em> (8.8%), followed by<em> Streptococcus uberis </em>(8.3%) and<em> Staphylococcus aureus </em>(3.3%).<em> </em>The relatively high prevalence of these pathogens indicates suboptimal cleaning and disinfection of teat dipping cups, brushes and milk liners in dairy farms with AMS in the present study.</p>

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