FACTORS AFFECTING THE MILK PRODUCTION OF DAIRY CATTLE IN NORTHERN RURAL AREAS OF BANGLADESH

A cross sectional study was conducted to observe the factors affecting the productive performance of dairy cattle from northern rural areas of Bangladesh during July and September 2013. Data of 105 cows, 85 (80.95%) from local and 20 (19.05%) cows from cross breed, were randomly selected for the study. A binary logistic regression, expressed by odds ratio with 95% confidence interval, was done to determine the association of daily milk production categorized into ≤ 2 and > 2 liters (L), based on median, with the significant explanatory variables of body weight, age at first calving, lactation period, vitamin use, type of floor and milking person. The result demonstrated that the probability of milk production of >2 L was 6.16, 4.5, 20.65 and 5.7 times higher from the with animal body weight of >140 kg, age at first calving of >36 m, lactation period of >8 m and vitamin use than that of body weight of 140 kg, age at first calving of ≤36 m, lactation period of ≤ 8 m, and not vitamin used respectively. The chance of milk production of > 2 L was 0.25 and 0.22 times lower for mud floor, and owner milking than that of brick floor and gowala (professional milking person) respectively.


Introduction
An important component of national economy, Bangladesh has 47.51 million livestock of which 22.87 million are cattle, plays a vital role for economic development of Bangladesh (BBS, 2008).Better genotype and sound management are the major determinants of profitability of dairying at either farm or individual level (Djemali and Freeman, 1987;Rahman et al., 1987) although, performances of high yielding exotic crossbred cows may differ among different geographical areas (Jahan et al., 1990;Alam and Ghosh, 1994).Biological potential for milk production also depends on the age at puberty, first calving age, number of parity and calving interval (Djemali and Freeman, 1987;Rahman et al., 1987).Around 2 years age of first calving and less than 13 to 14 months calving interval are the indicators of better management index of a farm (Wiltbank, 1970;Sarder, 2001).Besides, some diseases also have influence on the milk production where mastitis is one of the most devastating and farmers in Bangladesh are not well aware of the best practices to control (Rehman et al., 1997).For good health and high milk yields, cows need to be fed the proper amounts of available minerals and vitamins (Weiss, 1998).The present study was therefore undertaken to detect the factors of milk production.To be specific, the goal was to quantify the significant association of milk production with other covariates and factors by implying binary logistic regression model.

Materials and Methods
A cross sectional study was conducted at Rangpur and Gaibandha districts of northern rural areas of Bangladesh.A total of 105 cows were randomly selected where 85 were local and 20 were cross breed between July and September 2013.

Statistical analysis
Logistic regression, a type of probabilistic statistical classification model can be used to predict a binary response from a binary predictor and for predicting the outcome of a categorical dependent variable based on one or more predictor variables.Where 'ln' denotes the natural logarithm, is the probability that the dependent variable of milk production (>2 liters), is the intercept from the linear regression, is the regression coefficient multiplied by predictor, x can be categorical or continuous but Y always categorical.According to equation 1, the relationship between logit (Y) and X is linear.Yet, according to equation 2, the relationship between the probability of Y and X is nonlinear.For this reason, the natural log transformation of the odds in equation 1 is necessary to make the relationship between a categorical outcome variable and its predictor(s) linear.A binary logistic regression model was fitted with least significant value <0.05 (Hosmer and Lemeshow, 2000) and result was interpreted by odds ratio.Data analysis was done by statistical software packages SAS 9.2 and RStudio.

Results
The average Body weight (Kg), Daily milk production (L), Lactation period (m), Age of first calving (m) and Calving interval (m) of local and cross breed were 131.49  The bar diagram shows in Fig. 1  The pie chart presents in Fig. 2 portrays the frequency and percentage distribution of different variables.Among the cows, local and cross breed were 85 (81%) and 20 (19%) where only 8 (8%) and 7 (7%) cows showed the clinical sign of mastitis and FMD respectively.The season of calving in summer, rainy and winter were respectively 50 (48%), 16 (15%) and 39 (37%).
The number of vaccinated cows were only 42 makes up 41%.In case of cowsheds, the brick floor and mud floor were found 69 (56%) and 46 (44%) respectively.

Fig. 2. Pie-chart of different categorical variables
A contingency analysis was conducted to observe the frequency and percentages among the different cells distribution.From the binary logistic regression analysis, it was observed some variables were significantly associated with milk production.The odds of milk production > 2 liters for body weight >140 kg was 6.16 times than that of body weight ≤140 kg, 4.58 times higher for age of first calving of >36 m than ≤ 36 m, 20.65 times higher for lactation period >8 m than ≤ 8 m and, 5.7 times higher for vitamin use than no vitamin used cows.The probability of milk production > 2 liters for mud floor type was 0.25 times lower than that of brick floor type and 0.22 times lower in owner milking than gowala.

Discussion
From the study, it was revealed that, significant relation was pragmatic between milk production and age at first calving which was consistent with previous literature (Pirlo et al., 2000;Bayram et al., 2009;Bajwa et al., 2004).On the other hand, no significance relation of age of first calving with milk production in Brown Swiss Cattle investigated by Bayram et al. (2009).Lactation period was significantly associated with milk production, which was similarly demonstrated in the research result of Baul et al. (2012).In case of parity, no significant relation between milk yield and 4 th gives the highest production.Dhumal et al. (1989) found no relation between milk yield and parity.Similarly, 4 th parity was detected with highest production by Bajwa et al. (2004) whereas Tahir et al. (1989) registered 5 th lactation.Similar significant effect of vitamin use on milk production of this study was observed by Bregsten et al. (2003) for high yielding cows whereas 20 mg of supplemental biotin per day in higher producing cows (>75 lbs day -1 ) increase milk production 2 to 7 lbs day -1 but no response in lower producing cows (<45 lbs day -1 ).In this study, floor type has significant effect on milk production, in opponent, no significant relation was observed by Kremer et al. (2007).In this study, there was no significant relation between anthelmentic use and milk production.However, a study by Gross et al. (1999) delineated that a median increase in milk production of 0.63 kg/cow per day might be expected after anthelmintic treatment.Another study of meta analysis done by Sanchez et al. (2004) showed that on average, an increase of milk production of 0.35 kg cow -1 day -1 might be expected after anthelmintic treatment of naturally infected lactating dairy cows.Finally it was observed that the milk production was 0.22 times lower for owner milkers than gowala, this may be due to owner's inefficiency or their tendency to give the adequate milk left for calf.

Table 1 .
and 253.3 kg, 1.66 and  6.63 liters, 7.41 and 10.8 months, 35.36 and 41.55  months, and, 14.96and 15.2 months respectively presenting in Table 1.Descriptive statistics of different quantitative variables

Table 2 .
Percent distribution of different categorical variables on the basis of milk production