Livestock Research for Rural Development 25 (2) 2013 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Participatory Rural Appraisal to characterize dairy production systems in Bangladesh

M M Uddin, M N Sultana* and K J Peters**

IFCN Dairy Research Center at the Department of Agricultural Economics, University of Kiel, Schauenburger Str. 116, 24118 Kiel, Germany.
muddin_bau@yahoo.com
* Department of Agricultural Economics, Humboldt University of Berlin, Hanoversche Str.27, H-12,10115, Berlin, Germany
** Department of Crop and Animal Science, Humboldt University of Berlin, Philip Str. 13, H-9, 10115 Berlin, Germany

Abstract

The objective of this study was to characterize traditional, extensive and intensive milk production systems with special emphasis on breeding, feeding and diseases prevalence. A participatory rural appraisal (PRA) method was applied pertaining data for this study. A total of 16 PRA sessions consisting of, on an average, 11 participants in each session were conducted in 16 villages under three regions (Dinajpur, Sirajgonj and Kishorgonj).

The Holstein Friesian (HF) was highly ranked in all three production systems. The feed ration varies from high concentrate use in intensive system to high straw in traditional system. The milk yield (liter/day/cow) is highly influenced by seasons and green fodder availability, a low milk production is observed in May-August while high production in January-April in all three production systems. The prevalence of anthrax was ranked highest in intensive while Foot and Mouth Diseases (FMD) in extensive and traditional production systems. In terms of labour women contributes substantial working hours to daily dairying activities in traditional and extensive systems while men take significant role in intensive production system.

The result of this study might be useful to understand the existing dairy production systems which ultimately disclose the possible ways for interventions to enhance dairy development in Bangladesh and possibly in other tropical countries having similar production characteristics.

Keywords: characterization, dairy development, interventions, milk production systems, participatory rural appraisal


Introduction

Dairying, as a part of integrated agriculture, plays a tremendous role in uplifting the rural economy and reducing poverty. The increased demand (on an average 4% per year from 1996-2012) for milk and milk products, mainly driven by rapid population growth, growing urbanisation and rise in absolute income, opens significant market opportunity for the dairy farmers to increase income and improve livelihoods (Delgado et al 1999; Uddin et al 2010a; Hemme  2012). The livestock sub-sector currently accounts for about 3% of the national Gross Domestic Products (GDP) and 15% of employment (Jabbar 2010). The high income (1.62) and expenditure elasticity (0.95) of milk indicates a real market driven demand for milk (Islam and Jabbar 2009). This indicates a signal of structural change from more traditional and family-oriented dairy production systems to more market-oriented dairy production systems resulting a substantial higher income and entrepreneur’s profit per unit of milk production (Uddin et al 2010b).

To respond to the rapid structural changes, there might need a clear and target-oriented development programme. The success in dairy development, however, depends on the rate of adoption of different  development intervention and the farmer’s positive perception on specific technology or development programme (Batz et al 2003). Given with such background, the country has been continuously striving to implement several interventions to improve dairy farmer’s income and livelihoods (Haque 2009). But with few exceptions, the research findings and dairy development programmes were adopted at a low rate by the majority of the farmers because either the innovations did not fit with the perceived needs or there is a lack of direct participation of the farmers (Shamsuddin et al 2007). 

The information on production system characterization might facilitate to identify the real demands of the farmers and thus enhance the farmer’s participation in the development process. Developing appropriate interventions to assist smallholder dairy households, and identifying those which should be targeted requires a clear understanding of the dairy systems (Mburu et al 2007). Characterization is the grouping of farmers with similar practices and circumstances for whom a given recommendation would be broadly appropriate (Byerlee et al 1980). In Bangladesh, information on characterization of dairy system are relatively scarce and sporadic and not updated. One exception is the study done by Uddin et al (2011) who identified three dominant dairy production systems based on input and output, e.g., traditional, extensive and intensive production systems. However, their study focused more on qualitative information and the in-depth quantification of production system characterization is still missing.  

In this regards, the participatory action-oriented research (PAR) could play a significant role in enhancing the participation of the farmers in the research and development agenda. Concurrently, Participatory Rural Appraisal (PRA)- a branch of PAR is a helpful tool to characterize the resources, production system, constraints, develop interventions, assessing knowledge of the local participants, develop market link and to analyse the institutional performance (Shamsuddin et al 2007; Steglich 2007; Rekhis et al 2007; Ghaffar et al 2007; Nkya et al 2007).  The PRA method, however, has two fold benefits: firstly, this ensures participation of the farmers in the research process and delivery of data in a more simple and informal way which facilitates to gain more in-sights on a specific topic than a structured questionnaire; and secondly, the high rate of adoption of the intervention that is based on the research findings where the farmers themselves were involved. Therefore, this study applies the PRA method with the aim to characterize breeding, feeding and disease prevalence in traditional, extensive and intensive production systems. Since the use of family labour especially women in dairying play a crucial role in developing country, this study also focused on the contribution of the women in day to day activities related to dairying. Understanding the key characteristics, thus, would guide to find the possible interventions for dairy development.


Materials and Methods

Study areas

This study was conducted in three regions from north and north-eastern part of the country (Dinajpur, Sirajgonj and Kishorgonj) due to their substantial variation in terms of agro-climatic conditions and well representation of three key dominant production systems such as traditional, extensive and intensive production systems. Each of the production systems within and across the regions vary with different magnitude from each other in relation to inputs (e.g. land ownership, labour employed in the farms, feedstuffs and feeding systems, breeds and breeding management, veterinary services, technology involved, institutional link and degree of market link) and outputs (e.g. milk yield) (Uddin et al 2011). Moreover, those regions are highly potential for improving productivity and dairy development.

Data collection      

The PRA is considered as “bottom-up” approach and informal technique to collect in-depth data as well as other relevant information of a system (Devendra 2007). Matsaert (2002) defined PRA as an approach which uses visual and diagrammatic methods of collecting and analysing data that is particularly suitable for working with groups of people. This provides a basis for incorporation of local needs and knowledge which is further used as a basis for decision-making, operating through local organisations, generating local experimentation, innovation and interventions (Warren et al 1995; Ghaffar et al 2007) that would fully fit to the local needs.

The different PRA tools (explained below) were applied in this study pertaining data and relevant information. The PRA team consisted of five members: one external researcher, one local expert, one master student, one representative from Ministry of Fisheries and Livestock (MOFL) and one local guide. One hundred and eighty dairy farmers from traditional, extensive and intensive production systems participated in the PRA during 16 successive sessions organised in 16 villages under three administrative districts for a period of 6 months in 2010. An overview of the PRA is depicted in Table 1.

Table 1: The organisation of the PRA sessions in three production systems

Production systems

 

No. of participant villages*

No. of participants per session

Number of PRA sessions

Key indicators

Average No. of cows/farm

Average milk yield/cow/day (litres)

Income from dairying (%) ***

Traditional

4

15

4

2.1

3.86

45

Extensive

6

10

6

3.4

5.03

54

Intensive

6

10

6

7.3

8.10

93

Total

16

180**

16

 

-

-

* The number of participant villages was based on the willingness of the participants

** Indicate total number of participants in all 16 PRA sessions;*** The percentage indicate the amount of income come from dairying in relation to total household income including other agriculture, horticulture and off-farm jobs

A detailed guideline for PRA survey (Devendra 2007; Perera 2007) was prepared before implementation of this research. The PRA team organised several meetings with key stakeholders (institutional head of the Department of Livestock Services (DLS), local leaders and local dairy farmers. A transect study (Transect study means to walk through the village and gather information randomly on basic facts of dairy production systems without any formal interview) and telephone contact was performed. The objectives and methodology of this study together with the background information and predicted benefit from the outcome of this study were explained to all stakeholders.

The following PRA tools were used in this study:

i)                    Group discussions and semi-structured interviews were used to collect data on socio-economic characteristics of dairy farmers and some basic facts about their farms and farming systems. A set of questions were asked to the participating farm families on age, experience, education, sources of income, land holding, access to extension and credit services, distance to feed and milk market from the farms, and access to off-farm jobs.

ii)                  Preference ranking and scoring tool were used to identify the available breeds, their choices for breeds and to identify the most important diseases occurs frequently and severely in their farms.

iii)                Seasonal calendar was mainly to evaluate the seasonal variations on fodder availability and milk yield. The participant farmers were asked to develop a fact sheet for fodder availability and the corresponding milk yield per cow per day.

iv)                Activity profile was used to show the proportion of work done by men and women on a daily basis.

For scoring and ranking, the milk yield per cow per day (litres) was used as the major criteria for all three production systems although a second criteria such as calves colour and general health condition (economic trait) was used. The economic trait here indicates that farmer prefer calves that are healthy and good body condition that gains additional market value both male and female calves.

All quantitative data were analysed by using STATA version 9.1 and Microsoft Excel 2010was used to depict graphical presentation.


Results and discussion

Socio-economic profile of dairy farm households and farming circumstances

The socio-economic profile of the participant dairy farmers is depicted in Table 2. The average age of the dairy farmers was higher in traditional production systems while the average years of education received by the farmers were higher in intensive production system. The education enhances specific management skill which might help to run the commercial dairy farms which are key activities within intensive production systems. At the same pace, the average experience of the farmers (16.42 years) was substantially higher in intensive system compared to extensive (6.12 years) and traditional (7.40 years), respectively. 

Table 2: Socio-economic characteristics of dairy farmers participating in PRA from three production systems

Parameters

Production systems

All farm

types

Traditional

Extensive

Intensive

Age (years)

48.1

45.5

47.7

47.1

Education (years)

4.13

5.73

7.38

5.74

Experience of the farmers (years)

7.40

6.12

16.42

9.98

Access to extension services (Yes=1; No=0)

0.35

0.42

0.72

0.51

Access to off-farm jobs (Yes=1; No=0)

0.43

0.30

0.27

0.71

About 72% of intensive farmers have access to extension services compared to 35% and 42% in traditional and extensive production system, respectively. The main reason could be that intensive farmers need more advise and hence invest time and resources to get contact with extension workers. The access to off-farm jobs is higher in traditional (43%) followed by extensive (30% and intensive (27%) production systems. This can be attributed that as the farms are moving from traditional management to intensive management, the farms require substantial labour inputs due to which intensive farmers find no additional time to search for alternative jobs. The other explanation might be that the return from dairying in traditional typical farming system is reasonably low corresponds to 45% to the total household income compared to 93% for intensive production systems. This eventually compelled to do additional work other than dairy in order to maintain the family living expenditure (Hemme and Uddin  2010). 

Characterization of different dairy production systems
Breeds and breeding systems

The farmers’ perception on breeds, distribution pattern, ranking, and their breeding practices across the production systems are compiled in Table 3. The limited access to obtain preferred breeds, poor management condition and low economy of scale of their business does not support them to keep pure high yielding breeds even their aim is to improve milk production.  This was reflected in this study as except for the intensive production systems all other dairy farmers have substantially higher percentage of non-descript zebu cattle.  Additionally, low input systems compelled them to rely on indigenous cattle. This is the reason why a non-descriptive zebu cattle are prevailing in the traditional and extensive system. Since their aim is to increase their milk production they prefer high yielding cows. The Holstein Friesian (HF) crossbred got the highest score and ranked as 1 (average score 9 out of 10) followed by Sahiwal (score 7.33/10). The  reason for higher preference of HF is that calves have attractive appearance which is a non-economic trait but add a very high market value. In relation to economic traits, milk yield from HF crossbred is higher than any other breed in Bangladesh. The study done by Jabbar, (2010) showed a breed preference score of 3.4 out of 10 for Shahiwal followed by Holstein Frisian (3.3/10).

Table 3: Farmers’ ranking on breeds and their distribution among farmers participated in PRA in three production systems

Cattle breeds

Production systems

% farmers

Score

% farmers

Score

% farmers

Score

HF

1

1 (8)

3

1 (9)

37

1 (10)

Shahiwal

3

2 (6)

8

2 (8)

15

2 (6)

Jersey

4

3 (5)

5

4 (6)

15

4 (2)

Local

 

 

 

 

 

 

-PMC*

-

-

-

3 (3)

22

3 (3)

-Non-descript zebu

92

4 (4)

82

5 (1)

11

5 (1)

Breeding system***

 

 

 

 

 

 

AI***

60

95

68

 

 

 

Natural

24

3

18

 

 

 

Both

16

2

14

 

 

 

*PMC stands for Pabna Milking Cows-local improved breeds only found in the intensive production systems

Figures in the parentheses indicates the total score (out of 10) given by the farmers.

- indicates do not have

** Figure expressed as % farmers having such breeds; *** Artificial insemination

The Pabna Milking Cows (PMC) is one of the important breed for the intensive farmers and hence, showed higher preference than Jersey (3rd for PMC and 4th for Jersey). The PMC has a higher average productivity than any other local breeds.  The higher preference for PMC can also be justified due to the fact that PMC is highly adapted to the local climatic conditions and less prone to diseases compared to cross bred cows. But extensive and traditional production systems are lacking from this breed as it is only available in intensive area.

The main reason why neither traditional nor extensive system keeps this breed is limited access to this breed. Even with superior merit policy was not well forwarded to disseminate this breed to other production systems. Therefore, in order to improve milk productivity, two options might be foreseen, i) to improve local superior breeds such as PMC and disseminate to other production systems, and ii) to improve other non-descript zebu cattle via upgrading or crossbreeding. Dairy cattle are mostly (60-95%) bred by Artificial Insemination (AI), notably high in intensive production system. The study done by Uddin (2006) supports this result who reported the use of AI by 87% of farmers and the rest is using natural mating. The higher use of AI in intensive system is due to the fact that intensive system has reasonably higher access to AI (Islam et al 2010). The use of AI depends on the availability of effective services, distances to farms, communication means and the cost.  

Feeds, fodder availability and Dry Matter intake  

The major feed ingredients fed to the dairy cattle are depicted in figure 1. Rice straw and green grass (mostly non-cultivated) are the major feeds for dairy cattle across the production systems although the share of rice straw in total ration is substantially higher (46 to 67%) compared to green grass (23 to 33%) and concentrates (8 to 17%). Except in the intensive production system, dairy cattle are underfed (based on total DM intake/day) against the recommended amount of 10 kg DM/day based on 3.5% to their live weight (Khan et al 2009). This is due to the high price of concentrates, lack of green fodder and above all, the strong influence of seasonal variation on fodder availability.  

The influence of seasonality on green grass availability and milk yield across the production systems is illustrated in figure 2. The higher green grass availability and corresponding the higher milk yield was observed highest during the period of January to April (Winter and Spring) for all three production systems followed by the lowest in May-August (Summer and Monsoon) and moderate for September to December (Autumn and Late Autumn).

Figure 1. Typical feed ration and the corresponding DM intake for dairy cattle in three different production systems

*DM intake based on farmers'  data and estimated based on the proximate composition from the study done by Khandaker and Uddin (2002)

The highest production in winter and spring is due to the fact that just after monsoon disappears, the farmers cultivate fodder on own fellow land as well as embankments of the river sides. As a result, plenty of fodder is available in these periods. The lowest fodder availability and milk yield across the production system occurs during the Monsoon because all the cultivable land is inundated. This implies that augmenting green fodder production is the effective way of increasing milk production.

Figure 2. Seasonal influences on fodder availability and milk yield in three production systems

Prevalence of diseases and farmers’ perception on their severity and frequency  

The farmers’ perceptions and ranking diseases prevalence in three production systems are shown in Table 4. This study identified the three most important diseases in terms of frequency of occurrence and severity of the prevalence which ise Foot-and-Mouth Diseases (FMD), followed by Anthrax and Mastitis. Anthrax tends to occur all the year round with high prevalence in February and March. The FMD has two peak times to occur, February and March and again October and November. The first peak is due to very dry, windy weather and lack of rain with hot weather and the second peak is due to prolong exposure to monsoon during June to August.

Table 4: Farmers ranking based on the severity of the prevalence of diseases in different production systems

Disease prevalence and ranking*

Production systems

Traditional

Extensive

Intensive

Anthrax**

2

2

1

FMD***

1

1

2

Mastitis

3

4

3

Black quarter

6

3

5

Bloat≠

4

5

4

Milk fever

5

6

6

* Rank is in order of importance from 1 to 10 ( where 1 indicate most frequent occurrence with highest severity )

** Anthrax  occurs all the year round with high prevalence in February and March

*** FMD occurs February and March and again in October and November

The study done by Shamsuddin et al (2007) in Bangladesh and Gaffar et al (2007) in Pakistan are similar in terms of their trend and order of importance of the diseases found in the present study. Bloat occurs mostly during stall feeding with high amounts of concentrate supplementation during monsoon, and mainly in the intensive production system

Women’s participation in dairying  

The relative time involvement of women in dairying and their contribution to the total work is depicted in Table 5. The PRA study revealed that women do a substantial part of the dairying activities varying in different production system. The most important work where women do 100% is the cleaning of cow sheds and processing of cowdung to be used for fuel. On the other hand, the men captured the highest share of work when the dairy activities are commercialized (e.g. intensive production systems)

Table 5: Contribution of female labour in dairying in different dairy production systems

Activities*

Production systems

Extensive

Intensive

Traditional

M

F

M

F

M

F

Cleaning, washing cowsheds

12

88

28

72

45

55

Milking

31

69

53

47

84

16

Milk transport/sale

35

65

85

15

95

5

Feed collection

28

72

65

35

85

15

Feeding to cows

66

34

58

42

90

10

Cow dung process for fuel

0

100

0

100

0

100

* Activities are expressed in terms of per cent out of total working hours (hours/person/day) for each activity

M = Male; F = Female

The use of cow dung as fuel has a very common tradition in rural areas throughout the country. Therefore, this work has significant benefit towards generation of additional farm income. The involvement of women in dairying is ranked as order of highest, medium and lowest for traditional, extensive and intensive production systems, respectively. This might be explained by the facts that in the traditional production system, a lower economy of scale does not permit to employ hired labour and men can work in other sectors to raise off-farm income to compensate the low return from dairying. The opposite is true in the intensive production system. The contribution and involvement of women as revealed from the present study is a good basis to start interventions on reducing rural unemployment by increasing the involvement of women and recognising the economic value of their inputs. Thus, dairying could be an excellent tool to empower women and to raise their social capital via increased farm income. Therefore, additional training targeted to women is required to improve their farm management skills.


Conclusions


Acknowledgement

The authors highly acknowledge the International Foundation for Science (IFS), Sweden for providing grant for conducting field study (Grant Reference: S/4874-1, 2009)


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Received 8 December 2012; Accepted 13 January 2013; Published 5 February 2013

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