Livestock Research for Rural Development 19 (5) 2007 Guide for preparation of papers LRRD News

Citation of this paper

Studies on the reproductive performance of crossbred dairy cows raised on smallholder farms in eastern Usambara mountains, Tanzania

E S Swai, P Kyakaisho* and M S Ole-Kawanara**

Veterinary Investigation Centre, P O Box 1068, Arusha, Tanzania
emasw@yahoo.co.uk
*
District Veterinary Office, P.O. Box 20 Muheza, Tanga, Tanzania
** Divisional Dairy development Office, P.O. Box 4 Amani, Muheza, Tanzania
 

Abstract

A retrospective questionnaire based cross-sectional study was conducted to asses reproductive performance and factors influencing reproductive efficiency of crossbred cows in smallholder farms in Amani, Tanzania. The study was carried out during the period of October to November 2003. The study also estimated the frequency and determinants of long calving interval (LCI), retention of foetal membrane (RFM), dystocia (D), and abortion (A) in smallholder crossbred cattle and explored birth trends. Sixty-three dairy farms (average breedable cows = 2, range 1 to 9) were visited and data on reproductive, breeding and management histories were collected and statistically analyzed. Overall, 179 breedable cows were observed to be alive at some stage in 2002. These cows contributed a total risk period of 62,780 cow days, equivalent to 2,093 cow months or 171.9 cow years. The mean (±SE) calving interval and the interval between calving and the initiation of ovarian activity were 476 ± 14 and 108 ± 6.7 days, respectively. Birth rate was 52 per 100 cows years, with birth been reported to occur in all months of the year. Of the 123 cows that were reported to have calved more than once in their lifetime 4(3.3%), 3 (2.4%) were associated with abortion and dystocia, respectively. Fifteen (12.2%) of the animals suffered RFM.

Significant factors that were associated with LCI and RFM as was revealed from multiple logistic regression models were age of the cows, distance range between bull source and cows, farmer attending basic animal husbandry training and the owner of the cows. Cow that was located over 2 km away from the breeding bull source was associated with LCI (Odd ratio [OR] 2.7, P = 0.020) and older cow with lower odds for RFM (OR = 0.97, P = 0.001). Animals belonging to male and a farmer who has attended a basic training had lower odds for LCI and RFM (OR = 0.31, P = 0.001 for male cow owner and OR = 0.37, P = 0.033 for attending training, respectively). Though not statistically different (P>0.05), poor reproduction performance was also linked with farm managerial factors. Under nutrition, poor heat detection despite of farmer being aware of the cardinal signs of heat, poor monitoring of heat signs due to the inadequate usage of breeding supporting tools were also found to negatively influence reproduction efficiency.

We conclude that, the present estimate of LCI, birth rate, prevalence of peripartum disorders often inter linked by farm managemental attributes, indicate and suggest poor reproductive performances of cows in Amani smallholder dairy farms. Identification and quantification of the specific reproductive disorders and associated interacting factors (feeding/managemental) contributing to such poor reproductive performance call for detailed investigation.

Key words: Africa, Amani, reproductive performance, smallholder dairy production, Tanzania


Introduction

Although the smallholder dairying is an important source of income and has attracted a lot of poor families in Tanzania is not without constraints. Poor management, poor nutrition, lack of good breeds, infertility, reproduction disorders, animal diseases and the poor marketing system are among of the major constraints (Mdoe 1993; Leslie et al 1999; Swai et al 2005a,b).

Profitability and eventually sustainability of dairy smallholdings are to the larger extent determined by reproductive performance (Peters and Ball 1995). The main index to estimate reproductive performance is the calving interval (the period in days between two subsequent calvings). Calving interval is an important index of cow reproductive performance and calving interval of 365 days is desirable for efficient production (Esslemont 1993). For smallholder dairy cattle in urban and peri-urban parts of Tanga region, the calving interval is long, averaging 496 to 500 days (Lyimo et al 2004; Swai et al 2005b). Similar figures are reported from other areas in Tanzania (Anon 1995; 1996), whereas much longer days are also observed in Kenya (Odema et al 1994). These intervals are considerably longer than the standard recommendation of 430 days under tropical conditions and they reflect evidence of poor reproductive performance in such farms (Mujuni 1991; Kanuya 1992).

Joint results of participatory rural appraisal survey carried out in 2001 in Amani Division through Eastern zone client research and extension (EZCORE), revealed and rank the problem of long calving interval to be the main dairy production constraint (Anon 2001). It was against the above background that this survey was carried out so that information's on the real problem and magnitude can be identified, quantified and availed to extension agents, district policy makers and other key stake holders i.e. researchers etc so that interventions can be made available for controlling the problem.

The purpose of the present study was therefore to assess the reproductive performance of stall fed cows in the eastern Usambara mountain area, Amani division of Muheza, Tanzania. The primary objective was to identify and quantify factors that are potentially associated with long calving intervals in the herds towards developing strategies aimed at improving reproductive performance.
 

Materials and methods

The study site

This study was conducted in Amani Division, Muheza district of Tanga region. Amani division, one out of the six division of Muheza district, comprise of a cool, rainy eastern elevation of Usambara Mountains. The area is located between Longitude 38.5-39.50 E and Latitude 4.5-5.00S covering approximately 316 km2. Mountains covers approx. 1300 km2 . Amani division is located about 75 kilometres from Tanga municipality and 32 kilometers from Muheza town, representing a typical rural setting as defined by Swai et al (2005a) The division occupies 7% and 11% of Muheza land mass and human population, respectively (Anon 2002). The average number of household size is estimated at 4.7 and the population density is estimated at 100.6 people per km2 (Anon 2002). Most of the Amani division area is covered with tropical evergreen rain forest. The soils at Amani are of the type generally found under the rain-forests in Usambara i.e. deeply weathered red loam soils derived from gneiss, granulite's or pegmatite which is acidic in nature (pH of 4.6 to 5.2). Amani, lies at an altitude of 1700 metres above sea level and receives over 2000 mm of rainfall per year. During the hot season (Dec - March) the average daytime temperature is 25-29 0c and 22 -26 0c at night and during the cool season (May-Sept) 18-220c in daytime and 16 -200c at night.

History of dairy farming

Unlike other areas in Tanga region, there was no history of small-scale keeping of dairy cattle by smallholder farmers in Amani division until mid 1980s when the then joint Dutch/Tanzania, Tanga Dairy Development Programme (TDDP) introduced smallholder dairy farming in the area (Zylstra et al 1995). Prior to this period, the National Malaria Research Institute owned few crossbred dairy cattle. As of December 2002, the number of reporting farmers and dairy cattle were reported to be 462 and 1254, respectively. Smallholder dairy farming is perceived as one of the major sources of income to farmers in Amani division (Anon 2001; 2003).

Management of cattle herds

The smallholder dairy farm as defined by Tanga dairy development programme is a dairy unit having less than ten animals of all ages and sex (Anon 1999). Majority of the studied farm (>95%) were classified as smallholder dairy production units. Under this system, cattle were fed mainly native grass, farm established Guatemala spp, and supplemented with varying amount of home made concentrate mixture of cereal grain i.e. maize bran and oil seed cake i.e. cotton seed cake and leucena leaf meal. The amount and type of supplement utilized varied from farm to farm and from season to season. Animals were watered daily. The animals were confined in doors in a house that was roofed with corrugated metal sheets or grass thatched and had a concrete or stone floor. Cows were hand milked twice daily and calves were either allowed to suckle before milking (to stimulate milk let -down) and after milking (to feed the calf).

Breeding bulls used

The type of breeding bulls kept and used for breeding includes taurine breeds (Friesian, Ayrshire, Simmental) and crosses of these breeds with bos indicus (Tanzania short horn zebu, boran and Sahiwal). The level of taurine genes varied from 62.5 to 85%. Majority (>80%) of the breeding bulls used are crosses of Holstein Friesian and Tanzanian short horn zebu. Identification of the future breeding bulls is done through Tanga dairy development programme. Artificial insemination born bulls from pure taurine sire (progeny tested) and best performing first filial generation (F1 or taurine genes of 50%) dams are bought at the age of 3-6 months. Artificial insemination is limited to urban-based farms in Tanga. These bulls were bought by dairy programme and eventually sold to rural located farmers including Amani at a subsidized price. The responsibility of the bull keeper is to raise the bull until when they attain a mating age and to keep all mating records. All mating services rendered to the cows are paid. Fee varied from Tsh 3000-5000/=(or equiv. to 2.3 to 3.8US$) per service irrespective of conception.

Study animals and study procedures

Farms for the study were identified from the Division Dairy Development Programme (DDDP) office database. Based on the previous study (Swai et al 2005b), a sample size of farms and animals was estimated using Epi-Info version 6.04b (CDC, Atlanta, USA 1996) in order to provide 80% power, with a confidence of α = 0.05, to estimate disease prevalence and detect associations between dependent and independent variables (French et al 2001). Sixty-three smallholder dairy units from a sampling frame of 462 farms were randomly selected for the study. Farms were estimated to have an average of 2 to 3 female dairy stock (of breedable age) so a farm sample size of 63 was considered necessary to provide between 126 and 189 animals required. These farms contributed 179 breedable female stocks of various physiological status that were eligible for the study. The farms were visited once (cross-sectional study) during the period of October-November 2003. All the information collected (excepting calving dates) related to farm and animal events occurring in, or relevant to 2002. This involved detailed tracing of all animals on the farm, and examination of any written records, so that all ages of the cattle, calving dates, date of deaths and other movements of cattle on and off the farms agreed chronologically.

Other information collected by the questionnaire included details whether or not the animal had access to minerals, whether the animal had grazed or been zero grazed, whether the cattle owner had attended any dairy husbandry training, the herd size, feeding regime, source and distance to breeding bull (in kilometers), awareness and monitoring of heat signs, breeding record keeping, labor and breeding related task division, age of the cow, breed, filial generation (classified as F1, F2 and F3 basing on the level of exotic genes from breeding records), source of animals (home-bred or brought-in), calving dates, and any histories of abortion, dystocia and retention of fetal membrane. Using a tailoring tape measure (Goldfish, China), live weight estimates were calculated by using the following formula as modified by Msangi et al (1999). BWT = 4.0914 HG + 1.674BL - 459.75 [BWT: Body weight (in kgs), HG: Heart girth (in cm), BL = Body length (in cm)]. Body condition was scored to on a 5-point scale (1-5, where 1 represents very thin and 5 represent grossly over fat) according to the guidelines described by Nicholson and Butterworth (1986).

Definition of reproduction parameters

Birth rate (BR): was defined as the proportion of total number of births in 2002 to total number of cows alive or cow days in 2002 (French et al 2001)

Cow-days (or year) at risk (CDR): are the total numbers of days the study animals were present during the year under study. A cow's number of days present during the study was calculated as the difference between its date of exit (or end of December 2002) and its date of entry (or start of January 2002).

Calving interval (CI): was defined as the average interval between the two most- recent consecutive calvings for each cow in each herd.

Long calving interval (LCI) was considered to occur if the CI was beyond the standard recommended of 430 days under tropical condition. (Mujuni 1991; Kanuya 1992).

Abortion (A): was defined as the expulsion of one or more calves < 271 days after natural mating or artificial insemination (Roy 1983).

Foetal membranes (FM) were considered retained (RFM) if they remained unexpelled for at least 12 hours after calving or abortion.

Dystocia (D) was considered to occur if parturition was assisted either by the farmer or by a field officer.

Statistical analysis

Descriptive statistics for the animal and farm level explanatory variables examined in the study were developed using Epi-Info version 6.04d (CDC, Atlanta, USA 1996) .The unit of analysis was individual potential breedable females (cows and heifers > 30 months old) that were on the farm in 2002. The outcome (dependent) responses investigated were LCI and evidence of RFM as binary variables. Explanatory (independent) variables investigated were history of farmer training, feeding of minerals, gender of animal owner, cattle breed, filial generation, source of animals, condition score, weight of animal, frequency of extension officer contact and distance to breeding bull. Continuous variables such as age, parity, weight and score were transformed into i.e. age centre, weight centre, parity centre, score centre in order to normalise the data and ease analysis. Associations between dependent and independent variables were investigated in two steps by logistic regression (using Egret for Windows version 2.0, Seattle, USA) with 'farm' as a random effect because cows on one farm may not be statistically independent of one another (Kristula et al 1992). In the first step, relationships between each independent and outcome variable were individually investigated. In the second step, any variables that were significantly associated at the P< 0.25 level were included in multivariable models producing, by forwards and backwards substitution and elimination, the most parsimonious models in which all independent variables remained significant at the P < 0.05 level.
 

Results and discussion

Dairy herd type, composition and management

All selected farms were visited and farmer interviewed during the period of October-November 2003(a 100% response rate). The dairy cattle in the study area comprised crosses of indigenous Tanzania short horn zebu (TSHZ), Boran and taurine breeds (Holstein, Aryishire, Simmental), often confined indoors through out the year. Of the 179 cows examined, 44(24.6%), 29(16.2%), 28(15.6%) and 78(43.6%) were breeding heifers, dry, pregnant and lactating cows respectively, at the day of examination. The proportions of cow in each category of each variable investigated are detailed in Table 1.


Table 1.  The proportions of cows in each category of each variable investigated during the study (n=179)

Variables

Categories

Number of animals, %

Animal level variables

 

 

Source of animals

Homebred

Brought-in

112(62.6)

67(37.4)

Filial generation

F1

F2

F3

26(14.3)

144(80.4)

9(5.3)

Age

3 to 5 yrs

>5 to 8 yrs

> 8 yrs

78(43.5)

70(39.2)

31(17.3)

Breed codes

Aryshire cross

Friesian cross

TSHZ cross

Boran cross

14(7.8)

176(98.3)

169(94.4)

10(5.6)

Condition score

0 to 2

>2 to 3.5

>3.5 to 5

53(29.6)

106(59.2)

20(11.1)

Bull location

< 2 km

>2 km

115(64.2)

64(35.7)

Parity

1 to 3

>3 to 6

> 6

69(56)

39(31.7)

22(17.6)

Physiological state

Breeding heifer

Dry cows

Pregnant

Lactating

44(24.6)

29(16.2)

28 (15.6)

78(43.6)

Body weight (in kg)

210 to 300

>300 to 400

>400

68(37.9)

91(50.9)

20(11.2)

LCI (n =123)

>430 days

<430 days

52(42.3)

71(57.7)

RFM (n =123)

Yes

No

15(12.2)

108(87.8)

Farm level variables

Attended a training course

Yes

No

31(17.4)

148(82.6)

Gender: owner

Male

Female

128(71.5)

51(28.5)

Acquisition type

Bought cash

Credit

95(53)

84(47)

Frequency extension officer contact

No visit

>2 to 4 visit/year

>4 visit /year

42(23.6)

105(58.6)

32(17.8)

Feeding minerals

Yes

No

134(74.8)

45(25.2)


The average number of breedable females (cows) per farm was 2(range, 1 to 9). The average age and mean body weight (in kgs) of the investigated cows were 5 years and 338 ± 4.3, with range varying from 3-13 yrs and range of 210 to 480 kgs, respectively.

Body condition score (BCS)

The overall mean (±SE) body score was 2.6± 0.04. No single cow was recorded to have a score of 0 and >4.5. Majority of the cows (59.3%) had a body score ranging from 2.5 to 3.0.. Since the score was performed at a particular point time, the current estimate may not be adequate to compare with other works and draw conclusions from. However it does indicate the nutritional status of cows at least at a time of examination.

Perceived breeding constraints

Of the 54 respondents, 39% identified poor heat detection as the most important breeding constraint, 26% mentioned the bull source to be far from their cowshed, 19% identified high breeding cost as a prohibitive factor. Low conception rates were mentioned by 16% of the respondents.

Labour requirement and division of breeding related tasks

Overall, 58.7% of the 63 farms visited employed labour. Majority of the farms (94.6%) employed temporary labour of less than 6 months while 5.4% employed permanent labour of more than 6 months. Besides other farm activities, the day-to-day breeding activities include monitoring heat signs, taking a cow to a bull, making decision on taking a cow to a bull and paying for a breeding fee. In general, monitoring heat signs (36.5%), taking a cow to a bull (39.7%) making decision to take a cow to a bull (52%) paying for a breeding fee (60.4%) are most often done by husband or men closely followed by wife (Table 2).


Table 2.  Dairy cattle breeding:  activity and responsibilities profile (N= 63)

Activity executed by:

Husband

Wife

Attendant

Son

Others

Monitoring heat signs

36.5%

27%

30%

6.5%

0%

Take a cow to a bull

39.6%

7.9%

38.1%

11%

3.7%

Make breeding decision

52.3%

43%

1.6%

3.1%

0%

Payment for a breeding fee

60.4%

36.5%

0%

3.1%

0%


Hired labour is responsible for monitoring heat signs (30%), taking a cow to a bull (38%) and cutting grass or collecting water. Contributions of children (son) in most of the breeding activities are minimal. Traditionally men have a stronger role in decision-making. This finding is consistent with the findings of Mhina et al (1995).

The distance range between cow residences relative to the bull source

The distance to bull centre tended to affect the efficiency of mating, as 42 % of the households lived 2-4 km away from the source of breeding bull, while 5 % lived over 4 km away. Majority of the farms 52% were less than 2 km from the breeding bull source. The distance range between cow area of domicile and the bull centre can influence reproduction in several ways: delayed mating or late mating of cows, discourage or retard the morale of trekker. Long distance trekking may impose stress on cows/heifers, resulting in low conception rates. Trekking a cow is usually the time consuming task in dairy cattle breeding. The observed ratio of cow to bull in the study area was noted to be 25: 1. This ratio was considered to be lower considering the terrain, hilly and the poor infrastructure (road) network in Amani. Artificial insemination service is not offered due to the economy of scale reasons. The time required to carry out this task is very location specific and depends entirely on the distance between area of domicile and the location of the bull.

Heat sign awareness

Knowledge on heat signs is important element for improved reproduction efficiency. Of the interviewed farms, fifty-seven (90%) of the participants could recognize at least one of the cardinal signs of heat namely discharge of white mucus. Over 50 % could recognize other signs like restless, bellowing and mounting other cows (Figure.1).



Figure 1.
  The most observed heat signs


Monitoring heat signs

Dairy farming is labour intensive enterprise and monitoring of heat signs is a routine task. Twenty-five (39.6%) of he 63 interviewed farmers do not check heat signs. Of the 38(60.4%) farms that responded to check heat signs, 25(65.3%) and 13(34.7%) mentioned to check twice and once a day, respectively. Like any other farm tasks, managing reproductions (heat signs) is a skill and develop with practice. There are few farmer who are quite familiar with his cows can recognize less visible signs like a small drop of blood on the vulva. This may indicate that the cow has just been in heat, and can be used as a marker to estimate when the cow is due to go into heat again. As cows do not necessary 'follow books' farmer should learn that heat could manifest itself in many ways. Also there are many one-cow farmers whose animals have no herd mate to mount or be mounted by so consequently these farmers will have to look for other signs. Possibly some farmers do recognize the signs but have other reason why their cow are not being bred. These reason are:

1) Some farmers are scared of handling their animals but won't admit it.

2) Sometimes a bull keeper and cattle keeper may not get along well and the result is that the cow keeper refuses to bring his /her animal to the bull for breeding.

3) A mobile owner (wife or husband) may be coincidentally away when the cow comes into heat and his laborers may not recognize the signs, have the authority to act or have the courage to escort the cow to a bull.

4) Inexperienced or new farmer may be enthralled with having a dairy cow and a new calf that they forgot to breed the cow again or fail to see the importance of doing so.

The use of breeding support tools

Of the 63 interviewed farms, only 76.2% claimed to keep breeding related records.

Fifteen farmers (23.8%) had no records. Most of the records were kept on school exercise book or'daftari' 65%, cow cards 32 % and on house wall calendar 3 %. The information kept includes date of major breeding events like calving, mating, abortion dates, milk production and sell records. The use or revisiting records for timely farm or breeding management decision was not properly carried out. Eighteen (37.5%) farmers responded to consult their record every month, 6 (12.5%) once every year and 24(50%) do not consult record at all.

Farm dynamics, fertility and birth trends

Information gathered from study farms includes detailed tracing of all cows that stayed at some stage in the study farm during the year 2002. 5 animals left the study areas due to various reasons including, 2 (40 %) sold for breeding or paying back credit, and 3 (60%) left for other reasons including gifts. During the same period, 3 animals entered the study area as a result of purchases for breeding (3; 100%). No animal was reported to have died or stolen. At the end of the study, data were available for 179 breedable females above three years. These animals were alive at some stage during 2002. The overall contribution of the 179 breedable female to the study was 62,780 cow days. This is equivalent to 2,093 cow months or 171.9 cow years.

Pattern of births

Between January 2002 to December 31, 90 calves were born. Of the born alive calves, 47(53%) were males and 43 (47%) females. Births were reported to occur in all months of the year. However, a substantial proportion of calves were born in January, July and November. The few number of births in August is difficult to explain. No seasonality pattern could be elucidated from these findings. The temporal patterns of birth are shown in Figure 2.


Figure 2.   The number of calves born by months of the year in Amani division 2002. (N = 90)


The estimated overall birth rate was 52 per 100 cow's years. The estimated birth rates for each age category are shown in Table 3.


Table 3.  The birth rates by age category for cattle on smallholder dairy  farms in Amani Division, Tanzania

Age category

Number of births

Cow time in years

Birth rate per 100 cow-years

3 to 5 yrs

12

73

17.9

> 5 to 8 yrs

49

68

72

>8 yrs

29

31

93

Overall

90

171.9

52.3


Cows above 5 years old had significantly higher birth rates (P< 0.001). The overall estimated birth rate was lower than that reported in some studies (Roberts 1986) and Swai et al (2005b) in coastal humid districts of Tanga region but comparable to that reported in small-scale farms in Zimbabwe (French et al 2001; Masama et al 2006). Again this observation suggests problem of long calving interval in smallholder dairy farming are broadly similar.

Estimated calving interval

The mean (mean ± SE) estimated CI of the cows that had calved more than once was 476 ± 14 days. The estimated mean calving interval was longer than that previously reported for cows kept in government institutional farm in Tanzania, however, consistent with the figure recorded in smallholder zero grazed in Northern and Southern highlands of Tanzania (Shekimweri 1982; Kifaro 1985; Kanuya et al 2000) but longer than recommended interval of 430 days for Tanzanian dairy cattle (Mujuni 1991; Kanuya 1992). Such a long calving interval implies that farmer's income suffers because cows spend a greater portion of their lactation at low production levels. The calf crop is also reduced. The mean interval between calving and the initiation of ovarian activity was 108 ± 6.7 days. This interval is comparable to the value of 107 ± 9.2 and 116 ± 6.6 days reported by Obese et al (1999) for the Sanga cattle breed in W. Africa and Msanga and Bryant (2003) for crossbred dairy cattle in coastal humid parts of Tanga region. These figures reflect a postpartum anoestrous or silent oestrus or poor heat detection problem in the animals. This might have contributed to the long calving interval obtained in this study. Sixty to ninety days postpartum is recommended for mating exotic dairy cows (Esslemont 1993; Peters and Ball 1995). The observed long calving interval predicts reduced reproductive efficiency, which may also be due to diseases, poor nutrition and poor management. Management factors such as failure of heat detection, absence of record, minimal role (division of responsibilities) extended by cow owner as was revealed in this study may play a key role.

Prevalence of abortion and peripartum problems

Of the 123 cows that were reported to have calved more than once in their lifetime 4(3.3%), 3 (2.4%) were associated with abortion and dystocia, respectively. Evidence of retention of fetal membrane was reported from 15 (12.2%) cows only. This finding is slightly lower than the 18% estimated in peri-urban smallholders dairy cows in Morogoro and Dar-es-salaam (Nkya and Swai 2000). The present estimate of occurrence of peripartum disorders does not seem to be serious. Comparable figures were reported in Ethiopia by Lobago et al (2006). The recorded prevalence of 12% cases of retention of fetal membrane is within the limit of 5% to 12% in normal population of calving dairy cows reported by Roberts (1986) and Younquist (1988). Causes such as nutrition, diseases such as brucellosis and factors associated with cross breeding may be responsible for the observed cases.

The observed incidence of abortion was lower than the level of 5% considered normal (Gaines 1990). The detected abortion of 3.3% reflect significant economic loss in terms of calf crop, drop in milk production, costs of treatment and prolonged calving interval and also danger to public health. The actual cause(s) of abortion in the present study were not ascertained. However, occurrence of infectious diseases and some locally un-measurable factors might contribute to abortion. No history of s.19 vaccination against brucellosis was recorded during our survey.

Factors influencing LCI and RFM

The factors, which significantly remain explanatory of long LCI and retention of FM in the most parsimonious multivariable regression models, are shown in Table 4..


Table 4.  Factors associated with LCI and retention of FM in dairy cattle in Amani division in multivariable logistic regression models- adjusted for farm effects

Variable

β (SE)

Wald P

LRS

LRP

Odds Ratio, 95% CIs

Outcome variable: evidence long calving interval (LCI) - Multivariable model

Constant

2.5 (0.51)

 

 

 

 

Age (centered) in yrs

-0.09 (0.03)

0.001

 

 

0.90 (0.85 0.96)

Attend training: Yes vs No

-0.97 (0.460)

0.033

 

 

0.37 (0.15 0.92)

Distance: over 2 km: Yes vs No

0.99(0.430)

0.020

5.07

0.024

2.70(1.15 -6.35)

Random term

0.00 (0.850)

 

 

 

 

Outcome variable: evidence retention of fetal membrane (RFM) - Multivariable model

Constant

3.70(0.630)

 

 

 

 

Attend training:  Yes vs No

-1.30 (0.470)

0.006

 

 

0.27 (0.10 - 0.69)

Age (centered) in yrs

-0.087(0.03)

<0.001

 

 

0.91(0.86 -0.97)

Owner: Male vs Female

-1.04 (0.440)

0.019

7.17

<0.001

0.35 (0.14 0.84)

Random term

0.00(0.607)

 

 

 

 

β  = Coefficient of regression (or parameter estimate), SE = Standard error of Coefficient,
 OR = Odd ratio,

CI = Confidence Interval of OR, P = level of significance, LRS = Likelihood ratio statistic,
LRP = Likelihood ratio p value


Old animals owned by farmers who have attended any training were significantly less likely to be associated with long calving interval (β for age = -0.09, P = 0.001 and odd ratio [OR] for training = 0.37, P = 0.033). Animal located over and above 2 km from the bull centre were significantly two fold as likely to be associated long calving interval interval (OR = 2.7, P = 0.020).

Evidence of retention of fetal membrane varied significantly with the ownership status of the dairy cattle. Animals owned by male farmer were significantly less likely to have retained placenta than cattle owned by female's farmers. (OR = 0.35, P = 0.001). Retention of fetal membrane was significantly and negatively associated with whether farmer had attended any training and the old age of the cows (OR for training 0.27, P = 0.006 and -0.087, P = 0.001 for age, respectively).

Allowing for the fixed effect of parity, level of exotic blood and breed codes (zebu, Friesian), farmer attending training and the distance between cow places of domicile relative to the bull centre were found to be associated with either long or short calving intervals. Farmer related attributes like failing or delaying mating due to the poor availability of breeding bull, deficiency (qualitative and quantitative) in feed supplies, which was common during our survey could probably account for poor reproduction performance. Majority of the studied cows were zero grazed. This indicates that the failure or inaccuracy of owners or attendants to detect oestrous (as was revealed by this study) and / or reporting it too late for breeding and confinement were partly responsible for the observed long calving intervals. The attendance of a farmer on a training course appeared to be a factor protective against LCI and RF of his or her cattle. This suggests that the extension messages of existing (or past) training courses have been effective in reducing LCI and RF. Any effect of training on reduction of LCI and cases of RF may have been more due to recognition of heat signs and prompt breeding or reporting to the extension officer for assistance rather than actually be attended by farmers him/herself.


Conclusions


Acknowledgements

We thank Muheza District authority through EZCORE for financing this work. Generous cooperation of smallholder's farmers, and extension staff in Amani division is also acknowledged. Thanks are extended to the Director of Veterinary Service for permission to publish this work.


References

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Received 10 February 2007; Accepted 17 March 2007; Published 1 May 2007

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