Effect of season and parity on lactation of crossbred Ayrshire cows reared under coastal tropical climate in Tanzania

A Epaphras, E D Karimuribo* and S N Msellem

Nguva Dairy Farm, PO Box 22566, Dar-es-Salaam-Tanzania
^*Sokoine University of Agriculture, P.O. Box 3021, Morogoro-Tanzania.
 ekarimu@yahoo.co.uk   karimuribo@suanet.ac.tz

Abstract

A study was carried out at Nguva dairy farm located in Dar-es-Salaam, Tanzania in order to investigate factors affecting milk production. The farm had an average of 37 (Range=31 to 42) lactating crossbred cows of Ayrshire breed every calendar month. Daily records of milk production for all cows on farm between June 2002 and September 2003 were used to derive lactation curves and assess effect of season and parity on milk production.

The average daily production at cow and farm level was 7.1±0.6 and 244±23.2 (mean±SD) litres, respectively. Critical period with lowest cow and farm daily production was December 2002 to February 2003 with production having dropped to as low as 6.1 and 205 litres/day per cow and farm, respectively. This period corresponds to the hottest months along the eastern coast of Tanzania. Production was highest during April 2003 to May 2003 period when the average daily milk at cow and farm level was 7.8 and 290 litres, respectively. There was no significant difference between average daily milk production between dry and wet seasons. The average daily production for cows calved once, twice, thrice and four times and more was 6.3±2.5, 7.9±4.0, 9.2±4.3 and 5.0±1.5 litres, respectively. Average production in all four categories of parity was significantly different from each other.

Results from this study show that December to February is an important period when supplementation may be required in order to maintain optimal production.

Key words:  Cows, milk, parity, season, Tanzania

Introduction

Milk is nutritious food from lactating animals, which is rich in carbohydrates, protein, fats, vitamins and minerals (Blowey and Edmondson 2000; Sinha 2000). Milk is synthesized by secretory cells in the mammary glands. Most milk producers understand that milk production fluctuates up and down from one lactation to the next. A lactation curve depicts a cow's milk yield after colostrum to drying off (Mason 2000). Analysis of lactation curve shape is important as it helps to identify feeding and management problems within a dairy herd. Generally high production requires high peak and persistency of milk production. A number of factors have been reported to affect milk production in the tropics. These include genetic, climatic, disease, feeding, year of calving and managerial factors (Payne and Wilson 1999; Msanga et al 2000). Animal factors such as breed, age, stage of lactation, parity and even milking frequency, have also been reported in other studies to affect milk production (Karaca and Freeman 1996; Tekerli et al 2000; Johnson et al 2002).

Whereas information on lactation curves in the developed countries is available (Quinn et al 2003; Schnier et al 2003), little is known about this trait in the developing countries and Tanzania in particular. The objectives of this study were to characterize the milk production pattern of the crossbred Ayrshire cows, including derivation of lactation curves at Nguva farm; to assess the effects of season and parity on lactation and to identify the critical period along the calendar year when lactation is lowest.

Materials and methods

This study was carried out at the Nguva farm, a medium-scale dairy farm located South-East of Dar-es-Salaam, approximately 23 kilometres from the Kigamboni creek. The farm is found in Kajificheni area, Tumaini village, within Temeke municipality. Nguva farm is situated at 06^o56.7' South of Equator and 039^o23.9' East of Greenwich. The farm was established during 1989 with an area estimated at 144 hectares and is privately owned by the Msellem Family. It lies in the narrow coastal plains of the Indian ocean with typical coastal climate characterized by hot and humid weather. The hottest months are November to February due to hot north-east monsoon winds. The area receives total annual rainfall ranging from 721 to 2,273 mm (Nahonyo and Kabigumila 2002). Long rains usually fall between March and May every year. Soils at Nguva farm are predominantly sandy and coralline with poor moisture holding capacity, extremely alkaline and with hard subsoil resulting in poor drainage.

Currently the farm has a number of animal species including crossbred dairy cattle of Ayrshire breed (110), dairy goats (275), sheep (395), camels (50), donkeys (7) and horses (2). The dairy cows are grazed extensively on native pastures within the farm during daytime and supplemented with maize bran, minerals and cotton seed cake during milking. In the evening, all lactating cows were also provided with green fodder. On average each lactating cow is provided with about 2 kg of a compounded feed containing ingredients mentioned above. All lactating cows are hand-milked two times a day using cow attendants employed by the farm. Milking is done in a special shed on the farm, which serves as a milking parlour. Sources of water for animals are boreholes and the river Nguva, where animals can either drink from water troughs or directly from the river during grazing time. Routine activities carried out at the farm include tick control by application of 'pour on' preparation every two weeks, worming using albendazole 10% for calves every month and fenbendazole (VermofasÒ) for pregnant cows every three months.

The daily recording of milk production at cow and farm levels is supervised by a veterinarian (first author, EA) employed by the farm. During this study, records of milk production for all lactating dairy cows (average 37 and range between 31 and 42 cows per month) on the farm between June 2002 and September 2003 were used to derive lactation curves. In order to assess the effect of season, data for only one-year period (June 2002 to May 2003) were used. All animals included in this study were crossbred cows of Ayrshire breed.

Data collected were entered in an electronic database and analysed using the Epi Info program (Dean et al 2001). Milk production defined as either litres of milk produced per cow/day or litres of milk per farm/day, was used as dependent variable during data analysis. Lactation season was classified as 'short rain' for October to January, 'long rain' for February to May, and 'dry season' for June to September period (Shem et al 2002). Because records of age for some cows were missing, we could not use this variable in data analysis. Instead, parity (number of times a cow had calved) was used as an indirect indicator of effect of age on milk production. Month of calendar year between June 2002 and May 2003 was also used as an independent variable for milk production. This allowed identification of critical months when milk production at cow and farm levels was lowest and also used to identify months when milk production was at the peak. For statistical comparison of differences in amount of milk yield in different categories of independent variables, analysis of variance (ANOVA) was used with a probability of 0.05 used for significant difference.

Results

The lactation curve hardly peaked during the first three months post partum after which there was a sharp decline with a steep down-slope between the fourth and eleventh month post partum (Figure 1).  On average, 26 cows were in milk every month (Figure 2). By the seventh month post partum, 21 (50%) of the 42 cows were still in milk but only 12% and 7% of these cows were in milk during the 10^th and 11^th month post partum, respectively.

Figure 1. Lactation curve of crossbred dairy cows at Nguva farm

Figure 2. The proportion of cows by month post partum included in derivation of the lactation curve

The average daily farm and cow milk production between June 2002 and May 2003 (Figures 3 and 4), show a similar pattern of fluctuating production with a sharp drop in daily milk production between December 2002 and February 2003. During mid-January 2003, 11 cows were dried off after their pregnancy status had been confirmed.

Figure 3. Fluctuation of average daily farm milk production between June 2002 and May 2003

Figure 4. Fluctuation of average daily cow milk production between June 2002 and May 2003

Most of the cows dried off were low producers thus leaving relatively high yielders in the study population. However the average daily cow milk production had already started to decline earlier even before removal of dried-off cows and instead of milk production increasing (as cows that remained in the study were high producers), it was still going down during February 2003. The critical period with lowest cow and farm daily production was identified to be between December 2002 and February 2003 when milk production had dropped to as low as 6.1 and 205 litres/day per cow and farm, respectively. On the other hand, milk production was highest during April 2003 to May 2003 period when the average daily milk at cow and farm levels was 7.8 and 290 litres, respectively.

The average cow milk production during the dry season, long rains and short rains was 7.2±3.7, 7.9±3.7 and 6.7±3.3, respectively (Figure 5). Overall, the differences in average milk production during the three seasonal categories were significant. However, pair-wise comparison of seasonal categories showed that only milk production between the long and short rain seasons differed.

Figure 5. Average cow milk production during dry season and long and short rains between June 2002 and May 2003

Further analysis when average milk production was stratified by parity revealed that only cows of third parity has different milk yield during the three seasonal categories (Table 1).

A total of 391 cow months were included in the data analysis and they were distributed as 155, 133, 70 and 33 cow months for parities 1, 2, 3 and 4 and more, respectively.  There was an increasing milk production from parity 1 to 3 after which production dropped (Figure 6).

Figure 6. Effect of parity on milk production

Discussion

The findings from the current study showed that the average daily milk production did not peak after calving and instead of production being persistent, there was a sharp decline soon after calving as compared to the typical lactation curves for cows in temperate countries (Mason 2000; Theron et al 2002; Mostert et al 2003). Possible explanations for this observation may include the effect of climate, particularly the hot and humid weather under which cows in this study were kept. Studies elsewhere have shown that hot climate contributes significantly to reduced milk production indirectly through its effect on feed intake (Mayer et al 1999; Payne and Wilson 1999; West 2003). This may be supported by findings in this study that December to February were critical months when milk production was lowest compared to other calendar months. This is usually the hottest period of the year along the eastern coastal plains of Tanzania due to the hot north-east monsoon winds (Nahonyo and Kabigumila 2002). Few clinical cases of mastitis occurred throughout the year and therefore mastitis had little influence on the shape of the lactation curve. Other possible explanations for the low milk production include reduced quantity and quality of natural pasture during dry and short rain periods. The pregnant cows or in-calf heifers need to be in good body condition with enough body reserves before calving in order to get enough milk post partum. Therefore poor nutrition may also explain the type of the curve obtained from the current study. This situation may be exacerbated by the long distance lactating animals at Nguva farm had to walk during dry and short rain seasons in search of grasses. Studies carried out elsewhere reported lower milk production in pasture-fed than zero-grazed cows (White et al 2002). When compared to the lactation curves in temperate countries (Mason 2000), the curve at Nguva farm was lower.

December to February was identified as the critical period when daily milk production was lowest. From our experience, the critical period corresponds to months with highest ambient temperature and low rainfall along the eastern coastal plains in Tanzania. The effect of weather on feed intake is well known. Although it was anticipated that reducing number of lactating cows by drying most of heavily pregnant cows in mid-January 2003 could have significantly reduced the average daily farm milk production, this decision would either have no effect or resulted in increased average milk production. To the contrary, the average daily cow milk production was also decreasing, suggesting that factors other than drying off cows was contributing to the observed results. It is interesting to observe that highest production at both farm and cow levels was attained during the long rains (March to May 2003 months).

Parity was positively associated with milk production. This finding tallies with other studies and may be partly explained by highest milk production capacity coupled with greater feed intake in older cows than young ones (Johnson et al 2002). However, cows in 4^th and more lactations were no longer better producers compared to those in their 3^rd lactation (Figure 6). The older age may contribute to reduced milk production through turnover rate of secretory cells, with higher numbers dieing compared to the newly produced active secretory cells. Fat tissue cells usually replace dead secretory cells. More data are needed to support this suggestion, since  only 70 and 33 cow months were registered for 3^rd and 4 and more lactations, respectively.
 

Conclusions

• Under the conditions of this study, with Ayshire cows exposed to a hot and humid tropical climate in the coastal region of  Tanzania, and with inadequate grazing in the dry season and short rains, average daily milk production did not peak after calving and showed poor persistency through the lactation.
• The critical period, in terms of daily milk was production, was from December through February, a period of high ambient temperature and low rainfall.

Acknowledgements

The authors thank all workers at Nguva farm who participated in this study.

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