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

Similar documents
DETERMINATION OF THE BEST NONLINEAR MODEL FOR DESCRIBING COMPLETE LACTATION OF AKKARAMAN AND GERMAN BLACKHEADED MUTTON X AKKARAMAN CROSSBREED (F 1

Comparison of Mathematical Models Applied to F1 Dairy Sheep Lactations in Organic Farm and Environmental Factors Affecting Lactation Curve Parameter

Influence of some Genetic and Non-Genetic Factors on Total Milk Yield and Lactation Period in Iraqi Awassi Sheep

OPPORTUNITIES FOR GENETIC IMPROVEMENT OF DAIRY SHEEP IN NORTH AMERICA. David L. Thomas

Development of a Breeding Value for Mastitis Based on SCS-Results

1 of 9 7/1/10 2:08 PM

Adjustment Factors in NSIP 1

Growth and Mortality of Suckling Rabbits

TEST DAY MILK, COMPOSITION AND UDDER MORPHOLOGY AT WEST BALKAN MOUNTAIN SHEEP AND THEIR F 1 CROSSES WITH CHIOS BREED

Analysis of genetic improvement objectives for sheep in Cyprus

MILK AND LAMB PRODUCTION OF EAST FRIESIAN-CROSS EWES IN NORTHWESTERN WISCONSIN

7. Flock book and computer registration and selection

GENETIC AND NON GENETIC FACTORS AFFECTING THE LITTER TRAITS OF BROILER RABBITS*

INFLUENCE OF FEED QUALITY ON THE EXPRESSION OF POST WEANING GROWTH ASBV s IN WHITE SUFFOLK LAMBS

Variation in Piglet Weights: Development of Within-Litter Variation Over a 5-Week Lactation and Effect of Farrowing Crate Design

A Few Economic and Management Considerations for Dairy Heifers

CLUSTERING AND GENETIC ANALYSIS OF BODY RESERVES CHANGES THROUGHOUT PRODUCTIVE CYCLES IN MEAT SHEEP

OPTIMAL CULLING POLICY FOR

THE EFFECT OF IBR/PI3 AND PASTEURELLA VACCINATION ON THE MORTALITY RATE OF HIGH PERCENTAGE EAST FRIESIAN LAMBS

RUMEN-PROTECTED BYPASS FAT FOR DAIRY EWE COMMERCIAL MILK PRODUCTION

Factors affecting the milk yield and composition of Rahmani and Chios sheep

RELATIONSHIP BETWEEN GROWTH OF SUFFOLK RAMS ON CENTRAL PERFORMANCE TEST AND GROWTH OF THEIR PROGENY

TOTAL MIXED RATIONS FOR FEEDING DAIRY HEIFERS FROM 3 TO 6 MONTHS OF AGE. H. Terui, J. L. Morrill, and J. J. Higgins 1

Moved the file to the new template (v2017_08_29).

EFFECT OF SOME FACTORS ON THE WOOL YIELD AND STAPLE LENGTH AT DIFFERENT AGES IN SHEEP FROM THE NORTHEAST BULGARIAN FINE FLEECE BREED - SHUMEN TYPE

RELATIONSHIPS AMONG WEIGHTS AND CALVING PERFORMANCE OF HEIFERS IN A HERD OF UNSELECTED CATTLE

Economically important trait. Increased demand: Decreased supply. Sheep milk cheese. 2007: $2.9 million for milk production (Shiflett, 2008)

Consumer attitude towards poultry meat and eggs in Muktagacha powroshava of Mymensingh district

Relationships between external and internal udder measurements and the linear scores for udder morphology traits in dairy sheep

PRODUCTION, MODELING, AND EDUCATION. Investigation of nonlinear models to describe long-term egg production in Japanese quail

GROWTH OF LAMBS IN A SEMI-ARID REGION AS INFLUENCED BY DISTANCE WALKED TO WATER

Body weight, feed coefficient and carcass characteristics of two strain quails and their reciprocal crosses

The effect of weaning weight on subsequent lamb growth rates

Crossbred ewe performance in the Welsh hills

PROJECT SUMMARY. Optimising genetics, reproduction and nutrition of dairy sheep and goats

Managing to maximise lamb performance regardless of season. Doug Alcock

MILK FLOW KINETICS IN TSIGAI AND IMPROVED VALACHIAN EWES AS AN IMPORTANT MILKABILITY TRAIT

Environmental and genetic effects on claw disorders in Finnish dairy cattle

Mona I. Mohammady, A.H. Hammam and N. H. Ibrahim

Udder cistern size and milkability of ewes of various genotypes

Unravelling the genetic background of Interdigital Hyperplasia of the bovine hoof

Genetic (co)variance components for ewe productivity traits in Katahdin sheep 1

Estimates of Genetic Parameters and Environmental Effects of Hunting Performance in Finnish Hounds 1

OVULATION RATE AND LITTER SIZE OF BARBADOS, TARGHEE AND CROSSBRED EWES'

Genomic selection in French dairy sheep: main results and design to implement genomic breeding schemes

Growth Performance and Mortality in Hybrid Converter Turkeys Reared at High Altitude Region

Post-weaning Growth and Carcass Traits of St. Croix White and Dorper X St. Croix White Lambs Fed a Concentrate Diet in the U.S.

challenges for health data recording Artikel im Spiegel 16/2012

A Comparison of Pyronin Y-Methyl Green Stain and Methylene Blue Stain for Somatic Cell Count in Sheep Milk

FACTORS AFFECTING MILK TRAITS AND UDDER HEALTH IN EAST FRIESIAN MILK SHEEP. Christian Scharch, Reinhard Süß and Rolf-Dieter Fahr

Effect of supplementary feeding to ewes and suckling lambs on ewe and lamb live weights while grazing wheat stubble

Milk yield measured by oxytocin plus hand milking and weigh-suckle-weigh methods in ewes originating from local crossbred in Turkey

Total Sheep and Lamb Inventory Down 5 Percent

Mastitis in ewes: towards development of a prevention and treatment plan

Nordic Cattle Genetic Evaluation a tool for practical breeding with red breeds

Nutritional Evaluation of Yam Peel Meal for Pullet Chickens: 2. Effect of Feeding Varying Levels on Sexual Maturity and Laying Performance

Tab 1a. Pigs Data Entry and Assumptions

[ 144 ] THE GROWTH AND DEVELOPMENT OF MICE IN THREE CLIMATIC ENVIRONMENTS

Genetic parameters and breeding value stability estimated from a joint evaluation of purebred and crossbred sows for litter weight at weaning

Determination of morphological and linear udder traits in Morkaraman, Tuj and Awassi sheep

Lactational and reproductive effects of melatonin in lactating dairy ewes mated during spring

LIFETIME PRODUCTION OF 1/4 AND 1/2 FINNSHEEP EWES FROM RAMBOUILLET, TARGHEE AND COLUMBIA DAMS AS AFFECTED BY NATURAL ATTRITION ABSTRACT

COMPARISON OF THE PERFORMANCE OF PROGENY FROM A MERINO SIRE EXTENSIVELY USED IN THE LATE 1980s AND TWO WIDELY USED MERINO SIRES IN 2012

Josefina de Combellas, N Martinez and E Gonzalez. Instituto de Producción Animal, Facultad de Agronomia, Universidad Central de Venezuela, Maracay

EVALUATION OF EFFECTS OF A STRAIN, STOCKING DENSITY AND AGE ON BILATERAL SYMMETRY OF BROILER CHICKENS

FEEDING EWES BETTER FOR INCREASED PRODUCTION AND PROFIT. Dr. Dan Morrical Department of Animal Science Iowa State University, Ames, Iowa

HEALTH AND BODY CONDITION OF RABBIT DOES ON COMMERCIAL FARMS

Comparative growth performance of Kajli lambs suckling their dams or offered buffalo-milk, cow-milk or milk replacer during pre-weaning period

EUROPEAN MASTITIS PANEL CALLS FOR APPLICATION OF KNOWLEDGE AND TOOLS FOR PRACTICE

Gross Pathology. Johne s disease. Johne s Disease: The ostrich approach just isn t working! The result: Damaged intestine

Dominance/Suppression Competitive Relationships in Loblolly Pine (Pinus taeda L.) Plantations

University of Wyoming, Laramie

Breeding aims to develop sheep milk production

Electronic and visual identification for sheep and goats in Brazil

Sheep and Goats. January 1 Sheep and Lambs Inventory Down Slightly

AN INITIATIVE OF. Wean More Lambs. Colin Trengove. Member SA Livestock Consultants EVENT PARTNERS: EVENT SUPPORTERS:

Lower body weight Lower fertility Lower fleece weight (superfine) (fine)

Economic aspects of poultry meat production in Germany

Data presented in this publication are those available on the on-line database at 10 May 2009

Institut for Produktionsdyr og Heste

DESIGN AND IMPLEMENTATION OF A GENETIC IMPROVEMENT PROGRAM FOR COMISANA DAIRY SHEEP IN SICILY

STAT170 Exam Preparation Workshop Semester

Selection for Egg Mass in the Domestic Fowl. 1. Response to Selection

Feeding dairy ewes. Sam Peterson Institute of veterinary, animal and biomedical sciences Massey University

Sheep Breeding. Genetic improvement in a flock depends. Heritability, EBVs, EPDs and the NSIP Debra K. Aaron, Animal and Food Sciences

Optimising lamb growth rate from birth to slaughter

#3 - Flushing By tatiana Stanton, Nancy & Samuel Weber

Application of different models to the lactation curves of unimproved Awassi ewes in Turkey

Phenotypic study of egg production curve in commercial broiler breeders using Compartmental function

The effects of docking on fattening performance and carcass characteristics in fat-tailed Norduz male lambs

InternationalJournalofAgricultural

Comparison of Weigh-Suckle-Weigh and Machine Measuring Ewe Milk Production 1,2

Statistical Indicators E-27 Breeding Value Udder Health

MLA and AWI Wool and Sheepmeat Survey Report - Sheepmeat August, 2017 Prepared by Kynetec

Assessment of the Impact of Somatic Cell Count on Functional Longevity in Holstein and Jersey Cattle Using Survival Analysis Methodology

Genotypic and phenotypic relationships between gain, feed efficiency and backfat probe in swine

THIS ARTICLE IS SPONSORED BY THE MINNESOTA DAIRY HEALTH CONFERENCE.

Public perception of farm animal welfare in Spain B

Rearing heifers to calve at 24 months

Dr. Jerry Shurson Department of Animal Science University of Minnesota

Transcription:

Archiv Tierzucht 53 (2010) 4, 447-456, ISSN 0003-9438 Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany Comparison of models for describing the lactation curve of Awassi, Morkaraman and Tushin sheep OMER CEVDET BILGIN 1, NURINISA ESENBUGA 1 and MICHAEL E. DAVIS 2 1 Department of Animal Sciences, Faculty of Agriculture, Atatürk University, Erzurum, Turkey, 2 Department of Animal Sciences, The Ohio State University, Columbus, USA 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 (R 2 ), 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. Keywords: ewes, comparsion of races, lactation curve, mathematical models Zusammenfassung Modellvergleich zur Beschreibung von Laktationskurven der Schafrassen Awassi, Morkaraman und Tushin Ziel war die Findung eines geeigneten Modells für die Beschreibung der Laktationskurven der Schafrassen Awassi, Morkaraman und Tushin zur Bestimmung unterschiedlicher Zuchtmaßnahmen. Genutzt wurden die Milchleistungen von 182 Awassi-, 47 Morkaramanund 74 Tushinschafen. Bezüglich der Anpassung an die Standard Laktationskurve wurden 8 empirische Modelle verglichen. Bei allen drei Rassen erwies sich das Wood-Modell (WD) bewertet durch die mittlere quadratische Abweichung (MSPE), das Bestimmtheitsmaß (R 2 ) sowie die Autokorrelation (DURBIN, WATSON [DW]) als das am besten angepasste. Signifikante Unterschiede zwischen den drei Rassen ergaben sich für die Parameter a, b und c sowie die Laktationsleistungen. Die Awassischafe lagen am höchsten die anderen Rassen verhielten sich ähnlich mit geringerem Ertrag. Keine signifikanten Unterschiede ergaben sich bei den Paramertern des WD-Modells außer den Kurvengipfeln sowie den Zeitpunkten dieser Gipfel. Signifikante Interaktion konnten beim Ertragsgipfel zwischen den Rassen und Paritäten gefunden werden. Schlüsselwörter: Schafe, Rassenvergleich Laktationskurve, mathematische Modelle

448 BILGIN et al.: Comparison of models for describing the lactation curve of Awassi, Morkaraman and Tushin sheep Introduction The milk produced by dairy animals is crucial for feeding people. Although mainly cow milk is globally consumed for this purpose, a small amount of sheep and goat milk is also used. Especially in the Mediterranean, Middle East and Eastern Europe, milk is an important product from sheep (POLLOTT and GOOTWINE 2000). Sheep milk is an important product for Turkey. Total milk production of Turkey is about 8.4 million tons per year. Approximately 7.8 % of total milk production is produced by sheep (ANONYMOUS 2003). Lactation curves have been heavily studied in cows for a long time. However, few studies are available in sheep. Lactation curves have a wide variety of applications, such as extension of incomplete records for use in genetic evaluations, formulation of rations and economic evaluation of different management schemes (GRONEWALD et al. 1995, SWALVE 1995, HORSTICK and DISTL 2002, GIPSON and GROSSMAN 1990, SAKUL and BOYLAN 1992, DAG et al. 2005, KESKIN and DAG 2006). A lactation curve is particularly useful to make a decision that is time-dependent. If we know when to expect an animal to reach peak yield, we can arrange the feeding strategy to allow economic management of feed to the extent that would satisfy the animal s requirement during various stages of lactation, reduce cost, and possibly maintain peak yield for as long as possible (BAFFOUR-AWUAH et al. 1996, AMIN 2003, GRZESIAK et al. 2003). Appropriate mathematical models may also be used to predict future milk yield for lactations currently in progress. Several models of lactation curves have been developed. The incomplete gamma function, or Wood s model, developed by WOOD (1967) is the most well known and commonly employed mathematical model, specifically applied to cattle (SWALVE and GUO 1999). The vast majority of the other models are also based on Wood s model (COBBY and LE DU 1978, WILMINK 1987). They usually include additional parameters to improve fitness and have been developed from experimental data. For example, other alternatives comprise a four-parameter model by Morant (MORANT and GNANASAKTHY 1989) and a six parameter diphasic function by Grossman (GROSSMAN and KOOPS 1988). More proposed functional forms of lactation curves can be found in ROOK et al. (1993). These alternative models have traditionally been applied to lactation data for dairy cattle, but less often in sheep and goats (KOCAK and EKIZ 2008). To model the lactation curve of sheep most studies have been based on Wood s model. However, some other models are used to fit sheep lactation data. NELDER (1966) suggested an inverse polynomial model (NE) be fitted to lactation data for dairy cattle and his model has occasionally been used for sheep and goats. This function has a value of zero as its initial yield and is also intrinsically linear. This was followed by Wood s three parameter model (WD), which has been widely used, especially in dairy cows and in sheep and goats. Wood proposed an incomplete gamma function in which constants can be interpreted biologically (WOOD 1967). Of these constants, a is initial milk yield just after lambing, and b and c are slopes of the curve before and after, respectively, the peak yield of lactation. Peak yield is a(b/c)b exp(-b) and time of peak yield is b/c. SCOTT et al. (1996) reported that WD has a tendency to overestimate milk yield prior to peak yield and in late lactation. COBBY and LE DU (1978) proposed another model (CD) in which an exponential decline and a linear decline are combined. The peak yield is estimated as c-in(ac/b) and there is a linear decline after that point. DHANOA (1981) reparameterised Wood s model (DH) to eliminate the

Arch Tierz 53 (2010) 4, 447-456 449 problems based on its parameters. Parameter b in this model represents the time required to reach peak yield. WILMINK (1987) introduced a lactation model (WI) in which a quadratic term was added and an adjustment made to the exponential term. In this model, a may be interpreted as the level at which yield begins, b as the decrease after peak yield is reached and c as the initial increase to peak. The factor w was set equal to 0.05 based on the literature. MORANT and GNANASAKTHY (1989) adopted a different approach (MG) by considering the proportional rate of change in milk yield during lactation. They addressed the problem of a high level of correlation between the parameters of the incomplete gamma function and proposed a modified polynomial model with four parameters, which can also be used in log linear form, to overcome these correlations. GIPSON and GROSSMAN (1989) introduced a diphasic model (GR) to overcome problems of autocorrelation detected in models based on the gamma function. A diphasic logistic function has some advantages over the gamma function, which are due to smaller and more random residuals, prediction of total milk yield and meaningful functions of easily interpretable parameters that have biological importance as observed by GROSSMAN and KOOPS (1988). A non-linear modification of Wood s equation was developed by CAPPIO-BORLINO et al. (1995) (CB), which is especially appropriate when milk production dramatically decreases instantly after the lactation peak. The aim of this study was to identify a suitable mathematical model for describing the lactation curve of Awassi, Morkaraman and Tushin sheep and to determine breed differences. Material and methods Experimental materials and procedures The experiment was conducted at the Research and Application Farm of the College of Agriculture, Ataturk University, Erzurum, Turkey. The experiment was carried out with the lactations of 182 Awassi, 47 Morkaraman and 74 Tushin ewes. Age at first lambing was approximately 24 months. All ewes lambed in March. All lambs suckled their dams freely until first milk recordings. Ewes were hand-milked twice daily (morning plus evening) and the first milk test was performed in the first month after lambing. Lambs were kept with their dams until 2.5 months of age, the time when they were weaned completely from milk. All breed groups were treated similarly with respect to diet and management. Approximately 87 % of Turkey s sheep population (25.4 million heads) is fat-tailed breeds (Anonymous 2003). The sheep population of the eastern and northeastern parts of Turkey consists predominantly of the fat-tailed Morkaraman breed. These sheep are thought to have evolved through natural selection under harsh environmental conditions. For centuries, eastern Anatolian farmers have used the Morkaraman breed to produce milk, meat and wool. It is estimated that there are about 5.09 million heads (Anonymous 2003). The lactation period is 140-150 days. The average total milk yield is about 50-65 kg. Awassi is a fat-tailed breed reared extensively in southern part of Turkey and it is estimated that there are about one million Awassi sheep in Turkey. Awassi sheep breed has been imported from southern part to eastern part of Turkey to increase milk and meat production of Morkaraman. It has been raised at Research and Application Farm of Agricultural Faculty

450 BILGIN et al.: Comparison of models for describing the lactation curve of Awassi, Morkaraman and Tushin sheep since 1974. The Awassi is kept for milk, meat and wool production. The lactation period is 170-200 days. The average total milk yield is about 100-150 kg. Tushin sheep are also fat-tailed breed and it is estimated that they are about 120 000 heads (Anonymous 2003). The meat of Tushin sheep is known for its palatability and a nice aroma free of the specific acrid smell of mutton. Milk yield is not high, 50-60 kg per lactation. The lactation period is 100-140 days. Eight empirical models from the literature (Table 1) were used to fit the standard lactation curves in this study, where Y t is average daily milk yield in the t-th week of lactation and a, b, c and d are parameters. Models were fit to individual lactation data for each sheep. Table 1 The models for describing lactation curves Modelle zur Beschreibung von Laktationskurven Name Source Function of t Parameters NE Nelder (1966) Y t =t/a + bt + ct 2 3 WD Wood (1967) Y t =at b exp(-ct) 3 CD Cobby and Le Du (1978) Y t =a bt a exp(-ct) 3 DH Dhanoa (1981) Y t =at bc exp(-ct) 3 WI Wilmink (1987) Y t =a + bt + c exp(-wt) 3 MG Morant and Gnanasakthy (1989) Y t =exp(a + bt + ct 2 + d/t) 4 GR Gipson and Grossman (1989) Y t =a 1 b 1 (1-tanh 2 (b 1 (t-c 1 ))) + a 2 b 2 (1-tanh 2 (b 2 (t-c 2 ))) 6 CB Cappio-Borlino et al. (1995) Y t =at b exp(-ct) 3 To describe the lactation curves the parameters were estimated by fitting eight functions to the data. All analyses were conducted using the Statistical Analysis System (SAS) nonlinear least-squares regression (NLIN) procedure (SAS 2000). The Gauss-Newton algorithm was chosen for iterations of nonlinear fit. The maximum number of iterations used was 100 and the convergence criterion was (SSEj-1 SSEj)/(SSEj+10-6)<10-8, where SSE is the residual sum of squares after fitting the function to the data, and j denotes the round of iteration, as defaults for SAS. When needed, extra iterations were performed to provide convergence. To compare the suitability of the models, the following process was used: (1) Parameter values for each model and their standard errors were derived from the iterative process. (2) Goodness-of-fit for each model was evaluated using mean square prediction error (MSPE) and the adjusted coefficient of determination: 1 (n 1) R adj 2 = (n p)(1 R 2 ) (1) where R 2 is the multiple coefficient of determination, n is the number of observations, and p is the number of parameters in the model. Note that R 2 is adjusted for the number of parameters in the model to make a fair comparison of models, R 2 adj will be reported as R 2 for simplicity. (3) The Durbin-Watson statistic (DW) was used as a measure of first order positive autocorrelation to test whether the residuals were randomly distributed (DURBIN and WATSON 1951):

Arch Tierz 53 (2010) 4, 447-456 451 DW = n (e t e t 1 ) 2 t=2 n 2 t=1 e t (2) where e t is the residual at time t, and e t-1 the residual at time t-1. The observed value of DW was evaluated against the tabulated critical value to test for positive autocorrelation. Negative autocorrelation was not tested, because a negative autocorrelation coefficient of 1 implies that residuals fluctuate in a strict up and down rate around the actual curve, which in the case of lactation curves is not a problem (FERNÁNDEZ et al. 2002). Results and discussion The goodness of fit statistics for the models tested is presented in Table 2. As stated before, all models had high R 2 values, ranging from 0.703 to 0.937, except for NE, suggesting overall good fits to the data. In general terms, apart from NE, the models provided accurate fits to the data as judged by MSPE, adjusted R 2, and DW. The best fit was obtained with MG and was followed very closely by GR and WD. Again, the worst fit was found for NE. The MG, GR, and WD models had the lowest MSPE and a higher DW coefficient when compared with the others models. The nonlinear MG model gave better fit to the lactation data, having the lowest values of MSPE, and the highest values for the R 2 and the DW coefficients, meaning the fewest positive autocorrelated cases (Table 2). On the other hand, POLLOTT and GOOTWINE (2000) reported that the Morant function always gave the lowest MSPE in Awassi sheep in Israel. The NE model gave the poorest fit according to MSPE and the R 2. Although the MG model gave the smallest MSPE and the highest R 2, it turns out to be inappropriate for representing the lactation curves of all individual animals in all three breeds (Table 2). This makes the curve unreliable. The GR model proved unsatisfactory for individual animals due to over fitting and resultant unrealistically shaped curves in Morkaraman and Awassi after MG. There was very little difference between MG and WD models, with MG having marginally smaller MSPEs. In addition, it is said that early in lactation the diphasic model results in a poor fit, because the hyperbolic tangent requires symmetry in both phases, and, when only two phases are considered, a symmetric curve does not fit the possible steep rise that occurs early in lactation (FERNÁNDEZ et al. 2002, KOCAK and EKIZ 2008). Given the overall results of these analyses, the WD model was determined to provide the best fit to our data for all three breeds. Averaged predictions of the Wood Model against observed milk yields for the three breeds are given in Figure 1-3. A number of other researchers also have tried to test the reliability and adaptability of the Wood model to the lactation curve of sheep. The general conclusion was that the Wood model may be useful to estimate milk production in ewes with a good level of approximation (CAPPIO-BORLINO et al. 1989, CAPPIO-BORLINO et al. 1995, SAKUL and BOYLAN 1992, PORTOLONA et al. 1996).

452 BILGIN et al.: Comparison of models for describing the lactation curve of Awassi, Morkaraman and Tushin sheep Table 2 Comparison of the goodness-of-fit statistics of several models to describe the lactation curves of Awassi, Morkaraman and Tushin Vergleich der Einigkeitsübereinstimmung Statistiken mehrerer Modelle für die Definierung der Laktation kurve der Awassi, Morkaraman und Tushin Models N MSPE R 2 DW Awassi ** ** ns CB 182 0.115 ± 0.015 b 0.900 ± 0.006 c 3.361 ± 0.285 CD 182 0.114 ± 0.015 b 0.892 ± 0.006 c 3.393 ± 0.285 DH 182 0.099 ± 0.015 bc 0.901 ± 0.006 ab 3.319 ± 0.285 GR 181 0.059 ± 0.015 c 0.907 ± 0.006 bc 3.477 ± 0.285 MG 168 0.059 ± 0.015 c 0.932 ± 0.007 a 3.312 ± 0.285 NE 87 0.876 ± 0.022 a 0.226 ± 0.009 d 3.429 ± 0.313 WI 182 0.085 ± 0.015 bc 0.906 ± 0.006 bc 3.435 ± 0.285 WD 182 0.081 ± 0.015 bc 0.924 ± 0.006 ab 3.319 ± 0.285 Morkaraman ** ** ns CB 47 0.044 ± 0.009 b 0.913 ± 0.016 ab 3.358 ± 0.244 CD 47 0.050 ± 0.009 b 0.876 ± 0.016 bc 3.398 ± 0.244 DH 47 0.049 ± 0.009 b 0.891 ± 0.016 ab 3.317 ± 0.244 GR 47 0.029 ± 0.009 b 0.880 ± 0.016 bc 3.381 ± 0.246 MG 42 0.026 ± 0.009 b 0.937 ± 0.016 a 3.304 ± 0.246 NE 30 0.327 ± 0.011 a 0.318 ± 0.019 d 3.396 ± 0.283 WI 47 0.049 ± 0.009 b 0.851 ± 0.016 c 3.422 ± 0.246 WD 47 0.036 ± 0.009 b 0.919 ± 0.016 ab 3.317 ± 0.244 Tushin ** ** ns CB 73 0.057 ± 0.008 cd 0.829 ± 0.024 ab 3.374 ± 0.298 CD 70 0.106 ± 0.009 b 0.703 ± 0.024 c 3.408 ± 0.299 DH 73 0.053 ± 0.008 cd 0.814 ± 0.024 ab 3.347 ± 0.298 GR 61 0.028 ± 0.009 d 0.859 ± 0.026 a 3.391 ± 0.299 MG 63 0.030 ± 0.009 d 0.880 ± 0.026 a 3.242 ± 0.299 NE 21 0.309 ± 0.016 a 0.387 ± 0.045 d 3.459 ± 0.326 WI 67 0.067 ± 0.009 c 0.759 ± 0.025 bc 3.447 ± 0.299 WD 74 0.030 ± 0.008 cd 0.862 ± 0.024 ab 3.347 ± 0.298 ns non significant (P>0.05), **P<0.01, *P<0.05, a,b,c Means in rows with different superscripts are significantly different (P<0.05). In the Figures 1, 2, and 3 it can be seen that the Awassi breed produced milk more than the others in a longer lactation period.

Arch Tierz 53 (2010) 4, 447-456 453 Milk yield (kg/day) 1,3 1,2 1,1 0,9 1 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0 Observed Predicted 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 Length of lactation (week) Figure 1 Observed and predicted yields using WD model for Awassi Beobachteter und vorhergesagter Ertrag beim WD-Modell für Awassi Figure 2 Observed and predicted yield using WD model for Morkaraman Beobachteter und vorhergesagter Ertrag beim WD-Modell für Morkaraman Figure 3 Observed and predicted yields using WD model for Tushin Beobachteter und vorhergesagter Ertrag beim WD-Modell für Tushin

454 BILGIN et al.: Comparison of models for describing the lactation curve of Awassi, Morkaraman and Tushin sheep Table 3 Least square means and standard errors for lactation curve parameters, peak yield and peak time for WD model Geringste quadratische Abweichung und Standardfehler der Laktationskurvenparameter, Höchstleistung und Dauer beim WD-Modell Classification N a b c Peak yield, Peak time, Mean ± SE Mean ± SE Mean ± SE kg week Breed ** ** ** ** ns Awassi 182 1.045 ± 0.06 a 0.398 ± 0.08 b 0.111 ± 0.01 a 1.160 ± 0.03 a 4.94 ± 0.16 Morkaraman 47 0.462 ± 0.19 b 0.768 ± 0.27 a 0.142 ± 0.04 a 0.773 ± 0.08 b 5.68 ± 0.52 Tushin 74 0.984 ± 0.10 a 0.065 ± 0.04 c 0.064 ± 0.02 b 0.823 ± 0.05 b 5.23 ± 0.31 Lactation ns ns ns ** ** Parity 1 71 0.602 ± 0.09 0.477 ± 0.129 0.104 ± 0.018 0.789 ± 0.04 b 4.28 ± 0.27 a Parity 2 55 0.625 ± 0.12 0.553 ± 0.168 0.117 ± 0.023 0.861 ± 0.05 b 4.08 ± 0.35 a Parity 3 72 1.171 ± 0.24 0.322 ± 0.040 0.086 ± 0.046 1.051 ± 0.11 a 3.26 ± 0.66 b Parity 4 105 0.989 ± 0.09 0.439 ± 0.131 0.112 ± 0.018 1.126 ± 0.04 a 3.78 ± 0.25 ab B L ns ns ns ** ns ns non significant (P>0.05), ** P<0.01, * P<0.05, a,b,c Means in rows with different superscripts are significantly different (P<0.05). The results of the Analysis of Variances of Wood model parameters according to breed and lactation parity are presented in Table 3. As seen, 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 a parameter revealed the highly significant effect of breed groups. Awassi and Tushin were higher than Morkaraman. The b constant which measured the average slope of the lactation curve indicated by period of optimum daily production was significantly affected by breed. It was the lowest in Tushin. The c constant which describes the declining extreme of the curve was significantly affected by breed. It was the lowest in Tushin. The Awassi breed had the highest peak yield and the Morkaraman and Tushin breeds had statistically similar lower peak yields. Although it is not statistically significant, Morkaraman breed had the highest peak time. 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 (Figure 4). A positive relationship between scale and parity was observed, that is, first parity peak yields were lower than for later parities, similar to the findings of GIPSON and GROSSMAN (1990). Similar conclusions were also reported by RUIZ et al. (2000), and FERNÁNDEZ et al. (2002). In this study an attempt was made to find the mathematical model that most satisfactorily represents the lactation curves of Awassi, Morkaraman and Tushin sheep. Eight non-linear models were compared. The Wood model was considered as most accurate to describe lactation curves, according to R 2, MSPE and DW criteria, and its applicability to the data for all three breeds. Among the three breeds studied significant differences were observed for the parameters of the Wood model and peak yield. The peak yield and peak time were significantly different among parities.

Arch Tierz 53 (2010) 4, 447-456 455 Peak yield (kg/day) 1,60 1,40 1,20 1,00 0,80 0,60 0,40 0,20 0,00 Parity 1 Parity 2 Parity 3 Parity 4 Awassi Morkaraman Tushin Figure 4 Interaction between breed and parity for WD model Interaktion zwischen Rasse und Parität beim WD Model References Anonymous (2003) Statistical Yearbook of Turkey. State Institute of Statistics, Prime Ministry Republic of Turkey, Ankara, Turkey Amin AA (2003) Test-day model of daily milk yield prediction across stages of lactation in Egyptian buffaloes. Arch Tierz 46, 35-45 Baffour-Awuah O, Brotherstone S, Hill W (1996) Genetic analysis of test day production in second lactation of British Holstein Friesian cows. Arch Tierz 39, 213-26 Cappio-Borlino A, Pulina G, Rossi G (1989) The lactation curve of Sardinian ewes estimated by a gamma-type function. Zoot Nutr Anim 15, 59-63 [in Italian] Cappio-Borlino A, Pulina G, Rossi G (1995) A non-linear modification of Wood s equation fitted to lactation curves of Sardinian dairy ewes. Small Rumin Res 18, 75-9 Cobby JM, Le Du YLP (1978) On fitting curves to lactation data. Anim Prod 26, 127-33 Dag B, Keskin I, Mikailsoy F (2005) Application of different models to the lactation curves of unimproved Awassi ewes in Turkey. South African J Anim Sci 35, 238-43 Dhanoa MS (1981) A note on an alternative form of the lactation model of Wood. Anim Prod 32, 349-51 Durbin J, Watson GS (1951) Testing for serial correlation in least square regression. Biometrika 38, 159-78 Fernández C, Sánchez A, Garcés C (2002) Modeling the lactation curve for test-day milk yield in Murciano- Granadina goats. Small Rum Res 46, 29-41 Gipson TA, Grossman M (1989) Diphasic analysis of lactation curves in dairy goats. J Dairy Sci 72, 1035-44 Gipson TA, Grossman M (1990) Lactation curves in dairy goats: a review. Small Rumin Res 3, 383-96 Groenewald Ferreira AV, van der Merwe HJ, Slippers SC (1995) A mathematical model for describing and predicting the lactation curve of merino ewes. Anim Sci 61, 95-101 Grossman M, Koops WJ (1988) Multiphasic analysis of lactation curves in dairy cattle. J Dairy Sci 71, 1598-608 Grzesiak W, Wojcik J, Binerowska B (2003) Prediction of 305-day first lactation milk yield in cows with selected regression models. Arch Tierz 46, 215-26 Horstick A, Distl O (2002) Estimation of genetic parameters for test day results of milk performance in East Friesian milk sheep using Bayesian methods for longitudinal data. Arch Tierz 45, 61-8 [in German] Keskin I, Dag B (2006) Comparison of different mathematical models for describing the complete lactation of Akkaraman ewes in Turkey. Asian-Aust J Anim Sci 19, 1551-5

456 BILGIN et al.: Comparison of models for describing the lactation curve of Awassi, Morkaraman and Tushin sheep Kocak O, Ekiz B (2008) Comparison of different lactation curve models in Holstein cows raised on a farm in south-eastern Anatolia region. Arch Tierz 51, 329-37 Morant S, Gnanasakthy A (1989) A new approach to the mathematical formulation of lactation curves. Anim Prod 49, 151-62 Nelder JA (1966) Inverse polynomials, a useful group of multi-factor response functions. Biometrics 22, 128-41 Pollott GE, Gootwine E (2000) Appropriate mathematical models for describing the complete lactation of dairy sheep. Animal Sci 71, 197-207 Portolona F, Spatafora F, Bono G, Margiota S, Todaro M, Ortoleva V, Leto G (1996) Application of the Wood model to lactation curves of Comisana sheep. Small Rumin Res 24, 7-13 Rook AJ, France J, Dhanoa MS (1993) On the mathematical description of lactation curves. J Agric Sci 121, 97-102 Ruiz R, Oregui LM, Herrero M (2000) Comparison of models for describing the lactation curve of Latxa sheep and an analysis of factors affecting milk yield. J Dairy Sci 83, 2709-19 Sakul H, Boylan WJ (1992) Lactation curves for several US sheep breeds. Anim Prod 54, 229-33 SAS (2000) User s Guide Statistics v 8, SAS Inst. Inc., Cary, NC, USA Scott TA, Yandell B, Zepeda L, Shaver RD, Smith TR (1996) Use of lactation curves for analysis of milk production data. J Dairy Sci 79, 1885-94 Swalve HH (1995) Test day models in analysis of dairy production data- a review. Arch Tierz 38, 591-612 Swalve HH, Guo Z (1999) An illustration of lactation curves stratified by lactation yields within herd. Arch Tierz 42, 515-25 Wilmink JBM (1987) Adjustment of test-day milk, fat and protein yield for age, season and stage of lactation. Livest Prod Sci 16, 335-48 Wood PDP (1967) Algebraic model of the lactation curve in cattle. Nature 216, 164-65 Received 5 May 2009, accepted 22 January 2010. Corresponding author: OMER CEVDET BILGIN email: ocbilgin@atauni.edu.tr Department of Animal Sciences, Faculty of Agriculture, Atatürk University, 25240, Erzurum, Turkey