Livestock Research for Rural Development 19 (10) 2007 Guide for preparation of papers LRRD News

Citation of this paper

Effect of breed, season, year and parity on reproductive performance of dairy cattle under smallholder production system in Bukoba district, Tanzania

L Asimwe and G C Kifaro

Department of Animal Science and Production, Sokoine University of Agriculture, P.O.Box 3004, Morogoro, Tanzania
kifaro@suanet.ac.tz

Abstract

A study was conducted to evaluate the effects of breed level and non-genetic factors on reproductive performance of dairy cattle under smallholder production system. The study focused on assessing the reproductive efficiency of dairy cattle under smallholder farms in Bukoba district, Tanzania. Data on age at first calving (AFC), calving to first service interval (CFSI), number of services per conception (NSC), days open (DO) and calving interval (CI) were collected from Kagera Dairy Development Trust (KADADET) in Bukoba district. General Linear models procedure of Statistical Analysis System (SAS) computer software was used to analyse the data. The fixed effects considered in the analyses were genetic group, parity, season and period of birth or of calving.

 

The overall mean for AFC was 35.1+9.7 months with a coefficient of variation of 18.6%, for CFSI it was 196.95+1.8 days with a coefficient of variation of 20% while the mean for NSC was 1.66+0.0 with a coefficient of variation of 21%. Further, the mean DO was 205.2+2.6 days with coefficient of variation of 19%, and CI averaged 480.4+2.4 days with a coefficient of variation of 22%. AFC was significantly affected by period of birth (P<0.001), level of exotic blood (P<0.05) and season of birth (P<0.05). Genetic group significantly influenced CFSI, NSC, CI (P<0.05) and DO (P<0.001). F1 crosses performed better than high-grades in all the traits with 34.6 months of AFC, 171 days of CFSI, 182 days of DO, and 455 days of CI. Season of calving significantly influenced CFSI (P<0.01), CI (P<0.001), NSC and DO (P<0.05). Cows calving in the long rain season were superior with 17 days of CFSI, 21 days open and had shorter (by 27 days) CI than those calving in the long dry season. Parity and period of calving significantly affected CFSI (P<0.05 and P<0.001), NSC (P<0.05), DO (P<0.01 and P<0.001), CI (P<0.05 and P<0.001) respectively. For these traits, performance was improving by advancement in age of cows. Milk yield in the first 100 days of lactation had no significant influence on post-calving reproductive traits.

 

It was concluded that reproductive performance was best in the long rain season and that with respect to reproductive traits F1 crosses were better than high grades in Bukoba district.

Key words: age at first calving, calving interval, calving to first service interval, days open, genetic and non-genetic factors, number of services per conception


Introduction

In developing countries the demand for dairy products is increasing as a result of fast growing populations and a rise in the per capita income (ILCA 1993). Improvement of production in dairy cattle is frequently considered possible by either improving the genetic merit and/or animal husbandry practices but often reproduction is neglected. Failure to maintain a high degree of reproductive efficiency has been associated with major economic losses in the dairy industry mainly through increase in the length of unproductive life of cows (Plaizier et al 1998).

 

Improvement in smallholder dairy production contributes to the availability of milk for public consumption and also improves the economic status of smallholder farmers. In order to maintain a long economically productive life of a cow, high reproductive efficiency and milk production are important (Das et al 1986). Reproduction is crucial for production of the necessary replacement stock, for reducing unproductive periods like dry periods and for increasing lifetime milk production and income (Das et al 1986; Nebel and McGilliard 1993). When the reproductive efficiency of a farm is poor the following losses can occur; less milk is sold as a result of longer days open, fewer calves are sold due to longer calving intervals, increased veterinary costs caused by greater number of problem cows, increased number of matings per conception as a result of poor heat detection and increased number of replacement heifers needed for non-voluntary reproductive culls.

 

While appreciating the importance of reproduction in the dairy enterprise, traits related to reproduction are mainly influenced by environmental factors such as feeding (Msanga et al 1999), tracking of reproductive cycles through record keeping (Balikowa 1997), access to bulls or efficiency with which AI is performed (Mulangila 1997), ability to detect heat (Ulmek and Patel 1992), reproductive health problems and other non-genetic factors (El-Keraby and Aboul-ela 1982). The aim of this study was therefore to assess the influence genetic and non-genetic factors on key reproductive traits in dairy cattle kept under smallholder production system in a high altitude humid area of the tropics. 
 

 

Materials and methods

 

The study area

 

This study was carried out in Bukoba district, which is one of the six districts of Kagera region in the northwest zone of Tanzania. The district lies between longitude 300 45 and 320 00east and between latitude 10 00 and 30 00south of the equator. It borders the Republic of Uganda on the northern side and lake Victoria in the east. The area receives bimodal rainfall that varies between 1000 and 2000 mm. The average temperature is 200 with variations between 150 and 280C.

 

Data collection and derivation of study variables

 

Data were collected from Kagera Dairy Development Trust (KADADET) office, which had been monitoring on-farm performance of cows between 1990 and 2000. Collected information was on birth dates, calving dates, dates of first and subsequent heats and insemination dates. Pregnancy diagnoses dates and their results were noted. Records of milk yield produced during the first 100 days of lactation were also transcribed from individual cow records.

 

From the collected information, the following dependent variables of interest were derived; age at first calving (AFC) as the number of months from birth date to first calving date, calving to first service interval (CFSI) was calculated as the interval in days from the calving date to the first service date, days open (DO) as the interval in days between calving and conception and calving interval (CI) was the interval in days between two consecutive calvings. The number of services per conception (NSC) was obtained by counting the number of services the cow was mated or inseminated until she conceived.

 

Data handling and analyses

 

Data were classified into several categories for statistical analyses. Two genetic groups F1  (with 50% Friesian blood) and high grades (with >50% but <100% Friesian blood) were identified. Four seasons were established based on weather and climatic conditions of the area (January to February as short dry period, March to May as long rain season, June to mid October as long dry season and mid October to end of December as short rain season). Further, all parturition numbers were classified into four groups; 1, 2, 3 and 4. All parities above 4 were pooled together in parity 4 because only a few cows that had completed more than five lactations. For age at first calving, the years of birth were grouped into the following periods of birth, those born in the years before 1985, between 1985 and 1990 and from 1991 to 1995. For CI, DO, CFSI and NSC, there was an additional period for animals that calved after 1995.

 

Data on NSC were tested for normality using UNIVARIATE procedure of Statistical Analysis System (SAS 2002) and found to conform to the normal distribution. The General Linear Models procedure of SAS (2002) was used to assess the effects mentioned above on the dependent variables. Data on AFC were analysed using model 1, while that of CFSI, NSC, DO and CI were analysed using model 2. Number of records available for analysis were; 436 for AFC, 2131 for CFSI, 2090 for NSC, 1985 for DO and 2009 for CI. Milk yield produced during the first 100 days of lactation was used as a covariate. The intention was to see if there was any significant association between level of milk production in early lactation and reproduction parameters considered. Least squares means from significant factors were compared by PDIFF procedure of SAS (2002).

 

Model 1

Yijkn = u + Bi + Sj + Yk + eijkn

Where:

Yijkn = Age at first calving of nth  cow born in kth period of birth, jth season of birth and of ith genotype

u = population mean

Bi = effect of ith genotype

Sj = effect of jth season of birth

Yk = effect of kth period of birth

eijkn = random residual error distributed as N(O,Iδ2 e)

 

Model 2

Yijklnm = u + Bi + Sj + Yk + Pl + b(xijklnm – x) + eijklnm

Where:

Yijklnm = the mth record of nth cow in lth parity, kth period of calving, jth season of calving and ith genotype

 u = population mean

Bi = effect of ith genotype

Sj = effect of jth season of calving

Yk = effect of kth period of calving
Pl = effect of lth parity

Xijklnm = milk yield during the first 100 days of lactation of the respective individual animal

X = overall mean milk yield during the first 100 days of lactation

b = linear regression coefficient of Yijklnm on X ijklnm

eijklnm = random residual error distributed as N (O,Iδ2 e)
 

  

Results and discussion

 

Age at first calving

 

Analysis of variance for AFC and other variables is given in Table 1.


Table 1.  A summary of analyses of variances for age at first calving (AFC), calving to first service interval (CFSI), number of services per conception (NSC), days open (DO) and calving interval (CI)

Factor

Mean squares x 103 for the traits

AFC

CSFI

NSC

DO

CI

Genetic group

176*

36.8*

3.12*

348.6***

69.2*

Season of birth/calving

130*

32.5*

1.62*

50.9*

77.6*

Period of birth/calving

524***

136***

1.49*

155***

163***

Milk yield in first 100 days (Regression)

 

0.8ns

1.77ns

12.2ns

25.4ns

Parity

 

23.9*

1.79*

65.9**

130***

Residual

38.4

6.8

0.50

12.5

11.2

R2

0.58

0.64

0.52

0.61

0.59

ns= not significant at P> 0.05, * = Significant at P<0.05, ** = Significant at P<0.01

*** = Significant at P<0.001


The mean age at first calving was 35.1± 9.7 months with a coefficient of variation of 18.6% (Table 2).


Table 2.  Least squares means (LSM) ± standard errors (SE) for age at first calving (AFC) in months

Factor

Levels

N

LSM ± SE

Overall mean

 

436

35.1±9.7

Genetic group

F1

263

34.6±12.7b

 

High grade

173

36.3±15.1a

Period born

 < 1985

165

37.3± 16.4a

 

1985 to 1990

213

33.3±12.9b

 

1991 to 1995

58

35.8±25.9a

Season of birth

Short dry season

82

34.8±24.2b

 

Long rain season

97

34.1±18.9b

 

Long dry season

147

36.6±16.5a

 

Short rain season

110

36.1±19.1a

ab Least squares means (LSM) within a column and factor with different superscripts are significantly different (P<0.05)


This mean is similar to values reported by Kiwuwa et al (1983) of 34.5 months and Balikowa (1997) of 36.7 months. It is however, higher than mean (32.4 months) reported by Syrstad (1996) under similar tropical environments. The period in which cows were born was a highly significant (P<0.001) source of variation. Heifers born in the period before 1985 had the highest mean (37.3+16.4 months) while heifers born from 1985 to 1990 had the lowest mean (33.3+12.9 months). Poor feeding and management could have been the reason for highest age at first calving during this period since a majority of farmers at that time had no experience in dairy cattle management.

 

Level of exotic blood among heifers significantly (P<0.05) affected AFC. The F1 crosses were found to calve earlier than the higher-grade counterpart heifers (Table 2). Such findings conform to results found by Sabota and Gill (1992), Kiwuwa et al (1983) and Syrstad (1996). F1 crosses were distributed to farmers when they were in-calf heifers but high-grade animals were born on-farm. The prolonged age at first calving of high-grade heifers could be attributed to factors such as poor nutrition and management practices including poor heat detection at the time of mating the heifers. With good nutrition it is expected that high-grade heifers would exhibit fast growth and attain higher weights at relatively younger ages.

 

AFC was also significantly (P<0.05) influenced by the seasons in which the heifers were born (Table 1). This conforms to the results of El-Keraby and Aboul-ela (1982) and Kifaro (1984). Differences in age at first calving between seasons might have been attributed to seasonal fluctuations in forage availability. Kifaro (1984) associated seasonal differences to variation in pasture availability and other supplementary feeds. Calves born during the dry season tended to have highest age at first calving of 36.6+16.5 months while those born during the long rain season had the lowest age at first calving (34.1+18.9 months). The variation could be attributed to differences in quality and quantity of forage, a common observation in the tropics.

 

Calving to first service interval

 

The overall mean for the interval between calving and first service was 169.9±1.8 days (Table 3), which is almost similar to results found by Estévez et al (1995) of 164.1 days.


Table 3.  Least squares means (LSM) ± Standard error (SE) for calving to first service interval and number of services per conception

Factor

Levels

Calving to first service interval

Number of services per conception

N

LSM± SE

N

LSM± SE

Overall mean

 

2131

170±1.8

2090

1.66±0.02

Genetic group

F1

1010

171±2.6b

1017

1.51±0.08b

 

High grade

1121

180±2.5a

1073

1.59±0.08a

Parity

1

763

185±3.1a

735

1.63±0.08a

 

2

529

173±3.7b

503

1.57±0.08ab

 

3

336

172±4.7b

327

1.54±0.09ab

 

³ 4

503

171±3.6b

525

1.48±0.09b

Season of calving

Short dry season

341

180±4.6ab

342

1.56±0.09ab

 

Long rain season

526

166±3.5b

536

1.49±0.08b

 

Long dry season

781

183±3.0a

746

1.62±0.08a

 

Short rain season

483

173±3.9b

466

1.56±0.09ab

Period of calving

 < 1985

92

145±4.9c

106

1.45±0.09b

 

1985 to 1990

116

226±9.9a

141

1.48±0.09b

 

1991 to 1995

1502

164±2.0b

1502

1.66±0.08a

 

 > 1995

421

167±4.0b

341

1.64±0.09a

ab Least squares means within a column and factor with different superscripts are significantly different (P<0.05)


However it is higher than the results reported by Dawuda et al (1988) and Mujuni et al (1990), which ranged from 93.2 to 151.7 days in various crosses. Such differences could have been caused by failure of farmers to detect heat signs after calving thus prolonging the interval, but could also be associated with low nutritional status of the cows, which did not allow them to recuperate fast enough after calving. Analysis of variance on calving to first service interval (Table 1) showed that period of calving was a highly significant (P<0.001) source of variation. Cows that calved in the period between 1985 and 1990 had the longest interval of 225.9+9.9 days from calving to first service followed by those that calved from 1995 onwards. The shortest interval of 145.3±4.9 days was observed in cows calving earlier than 1985 (Table 3). Season of calving was a significant (P<0.05) source of variation on calving to first service interval. Cows calving in the long dry season had the longest intervals 183.0+3.0 days, while those in the long rain season had the shortest interval 166.3+3.5 days. This could be caused by good pasture and its adequate availability during the rain season. The significant effects of period and season of calving on interval between calving and first service concurs with results reported by Dawuda et al (1988), Lozano et al (1992) and Estévez et al (1995). For example, Dawuda et al (1988) reported the interval to be 152.8 days in the rain season and 122.9 days in the dry season; here dry season calvers  had shorter CFSI by approximately one month. The effect of period of calving could be attributed to the improvement in management skills gained by farmers as years went by and possibly to random environmental effects.

 

Level of exotic blood and parity were other important sources of variation on interval from calving to first service (P<0.05). High-grade heifers had a mean interval of approximately 9 days longer compared to F1 crosses. It was observed that first calvers had the longest intervals (of 184.7+3.1 days) from calving to first service, while those that calved in fourth plus parities had the shortest intervals (170.8+3.6 days; Table 3). Physiological stress which first calvers do experience in early lactation could partly explain the observed longer CFSI. The second explanation is the fact that after the first parity, animals continue to grow whereby the dietary energy intake is partitioned to meet the requirements for maintenance, continuation of growth, lactation and reproduction.

 

Number of services per conception

 

The overall mean number of services per conception was 1.66±0.02 (Table 3) with a coefficient of variation of 21%, is close to the findings by Maniack et al (1978) of 1.8 in Jersey x Red Sindhi, Carmona Solano and Sato Vargas (1987) of 1.81 in dual purpose cows of Costa Rica and by Bekele et al (1992) of 1.66 in Holstein x zebu cows. The present finding is lower than the results found by Chaudry et al (1989) of 3.0 among Jersey x Sahiwal cows and by Kumar et al (1991) which averaged 2.05. Such differences could be ascribed to differences in management practices and mating systems used.

 

The analysis of variance (Table 1) shows that level of exotic blood, parity, season and period of calving had significant (P<0.05) effect on the number of services per conception. Heifers/cows that calved during the long dry season required more services per conception, while those that calved during the long rain season had fewer services per conception. Poor nutrition has often been a limiting factor to dairy cattle performance particularly in the long dry season when nutritive value of pasture is very low (Msechu and Mkonyi 1984). Hafez (1974) reported that insufficiency or an imbalance of protein, energy, roughage, vitamins and minerals do result in repeat breeders as well as low ovarian activity. High-grade cows under this study were also observed to require more services per conception compared to F1 crosses. Cows with higher milk yields are known not to breed quickly, have longer service periods and take a long time to conceive. Invariably, they require more services per conception than do cows with low milk yields (Berger et al 1981; Chauhan et al 1994).

 

Days open

 

The overall mean length of days open in this study was 205.2+2.6 days (Table 4) with coefficient of variation of 19%. This length of days open is similar to the results by Chaudry et al (1989) of 195.3 and Estévez et al (1995) of 197.7 days.


Table 4.   Least squares means (LSM) ± Standard error (SE) for days open and calving interval

Factor

Levels

Days open

Calving interval

N

LSM± SE

N

LSM± SE

Overall mean

 

1985

205± 2.6

2009

480± 2.4

Genetic group

F1

1061

183±3.5b

1082

456±3.4b

 

High grade

924

211±3.7a

927

469±3.4a

Parity

1

696

209±3.7a

701

478±4.5a

 

2

464

199±5.2a

490

474±4.9a

 

3

323

198±6.0ab

330

452±5.3b

 

³ 4

472

182±5.1b

488

444±4.4b

Season of calving

Short dry season

323

197±6.4ab

334

457±5.6b

 

Long rain season

515

188±4.8b

522

451±4.6b

 

Long dry season

699

209±4.2a

692

478±4.3a

 

Short rain season

448

193±5.7b

461

462±5.1b

Period of calving

 < 1985

46

198±5.5a

47

444± 6.9b

 

1985 to 1990

264

224±7.8a

276

491±7.2a

 

1991 to 1995

1480

206±2.9a

1493

481±2.8a

 

 > 1995

195

159±6.1b

193

432±5.6b

ab Least squarse means within a column and factor with different superscripts are significantly different (P<0.05)


However, the observation is lower than the result reported by Bekele et al (1992) of 232 days, but higher than the days open reported by Mangurkar et al (1985) and Sabota and Gill (1992) of 124 to 178 days. Such differences could have been caused by failure of farmers to detect heat signs after calving; as a result the interval from calving to first service was prolonged, and eventually influencing the number of days open. The significant effects of period (P<0.001) and season (P<0.05) of calving on days open shown in Table 1 was also reported by Carmona Solano and Sato Vergas (1987) and Mangurkar et al (1985). Cows that calved from 1985 to 1990 had the longest days open (224 days), while those that calved from 1995 onwards had the shortest days open (159 days). Such findings reflect the improvement in the reproductive management by farmers. Also poor quality feeds obtained during the dry periods resulted into longer days open for cows that calved during those periods because animals take a longer time to recover after calving.

 

For all parities studied, animals that calved in parity one had the highest mean DO of 208.8 days followed by those in second, third and the fourth parities (Table 4). Lozano et al (1992) have reported similar findings of DO tending to decrease with advancement in age. This could be due to physiological stress experienced by the first calvers in early lactation. Level of exotic blood was a highly significant (P<0.001) source of variation for days open. The high-grade heifers had longer days open than F1 crosses. High milk yields during early lactation is suspected to increase days open, perhaps due to biological antagonism between energy balance and reproductive cycling (Lee et al 1997).

 

Calving interval

 

The average calving interval observed in this study was 480.4+2.4 days, which is comparable to the results obtained by Kiwuwa et al (1983), which averaged 459 days and Balikowa (1997) of 484.6 days. The observed mean is longer than results found by different scientists in different tropical areas (Syrstad 1996), which ranged from 429 to 460 days. Mismanagement practices like poor heat detection and feeding could be the cause for long calving intervals. Phipps (1974) associated long calving intervals to nutritional factors notably level of nutrition and mineral imbalances. Msanga et al (1999) attributed long calving intervals to poor nutrition and /or failure to detect heat by farmers. Period and season of calving significantly (P<0.001) influenced calving intervals (Table 1). Kifaro (1984) and Lozano et al (1992) have been demonstrated similar findings. Year effect on calving intervals in the tropics has been reported to be indirect due to dynamic climatic changes which are frequently associated with forage fluctuations, disease pattern and changes in management by farmers (Mulangila 1997). The progressive reduction in calving intervals from 491.3 days for cows calving 1985-1990 to 432.3 days for cows calving from 1995 onwards could be a sign of improvement in the ability of farmers to manage their dairy cattle. The long calving interval (477.7 days) in the dry season and short (450.9 days) in the rain season was expected because cows/heifers that calved during the wet season received adequate feeds in terms of quality and quantity thus could recover within a short time compared to those that calved during the long dry season where there was in-adequate nutrients.

 

The decrease in calving interval between the first and subsequent parities (Table 4) conforms to earlier studies by Kifaro (1984), Agyemang and Nkhonjera (1986) and Balikowa (1997). This could be associated with improvement in reproductive management and it also indicates that physiological maturity is attained with advanced age of cows. The prolonged calving intervals for first calvers has been reported to be physiologically necessary to allow animals to replenish their fat reserves depleted during lactation and this allows them to put on weight prior to the next calving (Mahadevan 1951). Level of exotic blood among heifers was a significant (P<0.05) source of variation in calving interval (Table 1). High-grade heifers were found to have longer calving intervals than the F1 crosses a finding that is similar to Syrstad (1996). The reason for this could be poor fertility of high-grade animals as discussed earlier on.
 


Conclusions and recommendations

 

 


Acknowledgements

 

The authors are extremely grateful for the financial support provided by the SUA-MU ENRECA project. The assistance and cooperation provided by all staff of Kagera Dairy Development Trust (KADADET) in Bukoba district is highly acknowledged.

 


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Received 4 April 2007; Accepted 23 July 2007; Published 5 October 2007

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