Livestock Research for Rural Development 25 (11) 2013 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Do neighbours of agricultural research stations learn anything from them: the case of Rubona station, Rwanda

A Musoni*, **, D R Kugonza**, *** and D Gahakwa***

* Faculty of Agriculture and Rural Development, Higher Institute of Agriculture and Animal Husbandry (ISAE),
PO Box 210, Musanze, Rwanda
** Department of Agricultural Production, College of Agricultural and Environmental Sciences (CAES), Makerere University,
PO Box 7062, Kampala, Uganda
donkugonza@agric.mak.ac.ug
*** Rwanda Agriculture Board (RAB),
PO Box 5016, Kigale 138, Huye, Rwanda

Abstract

This study on adoption of cattle husbandry technologies at an African national research station used the Rwanda Agriculture Board’s Rubona station as a case study and was conducted through a survey of 92 randomly-selected cattle keeping households in Rusatira Sector of Huye District where the station is located. Respondents were interviewed using a pre-tested structured questionnaire and data were analysed using standard statistical procedures.

The study revealed that all the respondents knew at least one cattle-related service/technology provided by Rubona station. The majority (61.9%) ranked station services as very good, 29.4% as good, while to 8.7%, the services were bad. While only 63% of all households reared crossbred cattle, all respondents credited the station which intensively promotes grade dairy germplasm. Over half of the respondents used bovine artificial insemination (AI) service provided by station staff. Among the users of AI, 54.3% relied on it for genetic improvement, 20.6% targeted disease control, while others claimed uses that are not technically associated with it. A high (P<0.05) proportion of farmers (48%) reported frequent failure of AI as the problem which limits its use. Analysis of forage seed sources showed that Rubona station was the major provider (58.7%). Also, the station was singled out as the main contributor to disease prevention in the study area, through its novel “livestock improvement parks”. Generally, livelihoods were attributed to the station suggesting that many of its technologies are being sufficiently acquired. Correlation analysis showed that education level positively influenced adoption of improved cattle breeds (r=+0.62, P=0.001), AI (r=+0.55, P=0.001), and castration (r=+0.57, P=0.001) while age of household head negatively influenced adoption of exotic breeds (r= –0.56, P=001), AI (r= –0.48, P=0.001), however, gender was not a significant factor.

It is concluded that neighbours of research stations do learn a lot from the stations, but the adoption of what they learn depends on a number of factors. This study therefore recommends strengthening of the extension service on cattle management targeting the elders and the non-educated, since these were the least adopters. 

Key words: adoption, innovations, livestock technologies, research station


Introduction

Introduction of technological innovations in agriculture has attracted considerable attention among development workers because the majority population of developing countries derives its livelihood from agricultural production (Diederen et al 2003). Indeed, agriculture progresses technologically as farmers adopt innovations (Faith 2007). The extent to which farmers adopt available innovations and the speed by which they do so determines the impact of those innovations in terms of productivity (Karki and Siegfried 2004). New technologies seem to offer an opportunity to increase production and act as levers of substantial income rises. But, the introduction of many new technologies has only met with partial success, as measured by observed rates of adoption (Karki and Siegfried 2004). The conventional wisdom is that constraints to the rapid adoption of innovations involve factors such as the lack of credit, limited access to information, aversion to risk, inadequate farm size, inadequate incentives associated with farm tenure arrangements, insufficient human capital, labour shortages (thus preventing timeliness of operations), chaotic supply of equipment, and inappropriate transportation infrastructure (Richard et al 2000), but these may not be the only underlying causes.

It is a common phenomenon that farmers like any other kind of entrepreneurs do not adopt innovations simultaneously as they appear on the market. Diffusion typically takes a number of years, and seldom reaches a level of 100% of the potential adopters’ population (Rogers 1995). Apparently, some farmers choose to be innovators (first users) while others prefer to be early adopters, late adopters, or non-adopters (Diederen et al 2003). Innovators are described as individuals who are venturesome, eager to try new ideas and willing to take risks. Early adopters are described as the local opinion leaders in the system who function as the role models and are quick to see the value of innovations (Richard et al 2000). The early majority is always the largest category of adopters; these people only make a decision after they are convinced of the benefits. The late majority are cautious and skeptical persons who do not adopt until the large majority has done so. They are usually the relatively poor and are averse to risk. The last group of adopters is the laggards that are suspicious of innovations and change agents; are usually poor and seldom take risks (Faith 2007).

Across the world, adoption studies on crop agriculture abound. Regarding livestock, the situation is less glamorous though several recent efforts in developing countries have happened largely driven by foci of development partners. Home-born efforts are less common but the future in this regard is bright with much effort being put today in raising answers for the question, “is there value for money in terms of adoption and impact for newly generated technologies?” Some answers arise from such recent work as Mujuni et al (2012) who assessed adoption of recent innovations in beekeeping in Uganda. Rwanda on its part was regarded for a long time as a country of old pastoral traditions, and that in keeping cattle, one got honour, power, prestige and wealth. This has been changing though in general, the possession of cattle is still a means of domination in Rwandan society. Recently, the cattle population in Rwanda was estimated at about one million head of which 86% are of the local Ankole longhorn breed, 13% cross and 1% exotic breeds (Nabasirye et al 2012). Currently, livestock development is one of the major priorities of Rwanda in its 2020 vision for poverty alleviation and livestock does contribute to food security as well as income generation since it is a source of milk, meat and other animal products.

Despite the potential of the country, the current livestock production level does not meet the national demand. Productivity has been hampered by a number of constraints which include: insufficiency of animal feeds, not only in terms of quantity but also quality; animal diseases, especially the epidemic ones; limitation of public veterinary services all over the country; low level of investments in the livestock sector leading to the absence of infrastructure necessary to transform it; low levels of knowledge and capabilities of farmers; land shortage which influences the shortage of pasture due to high growth of the population. Despite all the challenges, the farmers must intensify their agricultural practices by closer integration of livestock and agriculture and the practice of agro-forestry in their small holdings to maximize their returns (Ombudsman 2010).

New technology is always a critical element in a changing industry structure. Johnson and Ruttan (1997) found that livestock breeding technologies to be the most significant factor contributing to farm productivity in the livestock sector since the 1940s. They observed that modern dairy cows with higher production potential have been developed through genetic selection, and that this needs to continue into the future. Short (2004) also indicated that a relatively large proportion of farms used genetic selection and breeding programs to improve herd quality, and this is tending to the norm. On the other hand, higher yielders require greater management; and failing to recognize this fact may result in financial loss (Britt 1985). There appears to be a direct relationship between herd management and reproductive performance, ultimately influencing farm profit (Britt 1985). Genetics has accounted for about 55% of gains in the yield traits and about one-third of the change in the time interval required to achieve conception in cattle (Shook 2006).

The Rwandan government has always set programs for improving this sector and recently, it created the Rwanda Agriculture Board (RAB) to support the transformation to modern agriculture through promotion of scientific and technical development of agriculture and animal husbandry in Rwanda. The Board was created from the merger of three precursor organizations, namely: Rwanda Institute of Agricultural Research/Institut Des Sciences Agronomiques Du Rwanda (ISAR), Rwanda Agricultural Development Authority (RADA) and Rwanda Animal Resources Development Authority (RARDA). The nascent organization is currently headquartered in the capital city, but possesses over twenty stations spread across the country, the largest being Rubona station in the southern province. Despite these restructuring processes/ efforts, agricultural production is still low across the country largely because many people continue to practice the traditional techniques of farming. In view of the afore-going issues, we took the opportunity to carry out a scientific study on adoption of technologies/innovations in cattle husbandry by farmers of Rusatira geographical sector, where Rubona station is located.


Materials and Methods

Study area

Rubona station is located in Rusatira sector of Huye district (formerly called Butare) in Southern Province of Rwanda (Figure 1), and the sector was purposively selected for this study. The study itself covered six cells of the sector, namely: Kiruhura, Gafumba, Kimirehe, Buhimba, Mugogwe and Kimuna. The research focused on cattle-keeping households of different cells.

Figure 1: Map of Rwanda showing the location of Rusatira sector, the study location
Farmer selection

This study was carried out from April to August 2011. A random sample of 92 smallholder households was randomly drawn from the six cells. Respondents were selected from a total population of 1980 stockbreeders in the six cells of Rusatira sector. According to Bouchard (1989), when the population of interest is less than 1,000,000 individuals, the sample size is calculated from the formula:

Nc = (N × n)/ (N + n)

Where Nc is the representative sample size; N is the total population; n is the constant 96. For the case of Rusatira sector: Nc = (1980 x 96) / (1980 + 96) = 92. The number of questionnaires administered to farmers in each cell were 18 (Kiruhura), 16 (Gafumba), 14 (Kimirehe), 14 (Buhimba), 18 (Mugogwe) and 12 (Kimuna). The numbers were based on the proportion of the number of stock-keepers in those cells.

Data collection and analysis

Data collection was done through household interviews using a structured questionnaire. The questionnaire was designed to collect data on characteristics of households, technologies known and those adopted and the spread of the adoptions. Information was also collected on farmers’ level of education, details on livestock, and adoption of innovations and other animal husbandry techniques. Two stages of collecting the data were used, namely, interview and personal observation. During the survey period, personal observation was used in order to complete and adjust the information given by the farmers. The MS Excel software was used for data entry, tabulation and calculation of percentages. The analysis of variance was performed by using Genstat discovery Edition 3, while correlation analysis of variables was done using correlation procedures of Statistical Analysis Systems (SAS 2004). The confidence level used was 95% for P<0.05.


Results

Features of studied households

Concerning the level of education of the heads of households, the majority (65.2%) had attained primary education (Table 1), though a significant 22% had never been to school. No child-headed households were found; almost half of all households were headed by young adults/youths (18-35 years of age); while the rest (51.1%) were true adults (35-65 years of age). More than 60% of the homesteads were headed by women. On land size, less than 20% owned land bigger than one hectare, while majority owned 0.25-0.5 ha.

Table 1: Characteristics of the cattle keeping households

Factor

Level

Proportion (%) of households

Level of education of household head

 

 

None

21.8

 

Primary

65.2

 

Secondary

  8.7

 

Higher education

  4.3

Age category (yrs) of household head

 

 

< 18

  0.0

 

18-35

48.9

 

35-65

31.5

 

> 65

19.6

Gender of household head

 

 

Female

60.9

 

Male

39.1

Farm  size (ha)

 

 

 

< 0.25

16.3

 

0.25-0.5

41.3

 

0.5-1

23.9

 

>1

18.5

Research station technologies and their adoption

We found that all the respondents (100%) knew at least one cattle-related service provided by the research station (Table 2). According to the majority of respondents (61.95%), Rubona station services were very good, to 29% the services were good and a mere 8.7% claimed the station services were bad. Most (63%) of farmers in the study area reared crossbred cattle and only 6.5% reared pure exotic breeds. However, Ankole breeds are still common encountered at a rate of 30.5%. A high number of respondents (48.9%) stated that the cows they reared were bought from market, 41.2% obtained cows from Rubona station and 10.9% were supported by the government through its nascent one-cow-per-poor-household “Girinka” Program.

Adoption of artificial insemination by the surveyed farmers is 58.7%, and of these, genetic improvement was the focal objective of 54.3% and control of diseases (20.6%). The frequent failure of AI which leads to increases in parturition intervals was mentioned by 48% of the farmers as the major reason which limits the use of AI technology (Figure 2).

Table 2. Knowledge of livestock related technologies provided by Rubona station and their levels of adoption

Factor

Level

Proportion (%) of households

Knowledge of services provided

Know at least one service provided by Rubona station

100.0

Appreciation level of services

Very Good

61.9

provided

Good

29.4

 

Bad

  8.7

Race of cattle reared

Ankole

30.5

 

Cross-breeds

63.0

 

Exotic

  6.5

Adoption of artificial

Yes

58.7

insemination (AI)

No

41.3

Reasons of adopting AI by

Disease control

20.6

adopters

Genetic improvement

54.3

 

It is available

13.0

 

No idea

12.0

Fodder combinations adopted

Grasses only

53.3

 

Grasses and legumes

12.0

 

Grasses and fodder trees

26.0

 

Grasses, fodder trees & legumes

  8.7

Source of forage seeds

Rubona station

58.7

 

Local extension workers

16.3

 

NGOs

  8.7

 

Neighbours

16.3

Forage conservation methods

Informed of silage

22.8

 

Informed of hay

37.0

 

Both ideas

26.0

 

No idea

14.2

Supplement feed  provided

Rock salts only

81.5

 

Concentrates & Mineral licks

  6.5

 

Minerals licks only

  4.4

 

Nothing

  7.6

Limitation to use of supplements

Expensive

62.0

 

Inaccessible

29.3

 

Lack of information

  8.7

Cattle health service provider

Rubona station staff

45.6

 

Local extension workers

34.8

 

Private

19.6

Cattle housing system adopted

Permanent stabling

59.8

 

Temporary stabling

40.2

Rubona station was the main contributor to disease prevention in the study area through their community action programme, but in addition, help from state and private veterinarians was also acknowledged (Table 2). Some of the adopted technologies on disease prevention included deworming and regular spraying of animals against ecto-parasites.

Figure 2. Reasons why some households did not adopt artificial insemination

The cattle housing systems used in the study area were of two types, notably; permanent stabling used by more than 59% of respondents while the semi-permanent stabling was being used in 40.2% of the farms. All the cowsheds in the locality were built with wood and none of the farmers had cowshed built with bricks. Also, there were no cowsheds built of concrete. Roofing was dominantly done using sheet metal or tiles (Table 3), though use of straw was also common.

Table 3: Materials used in cow shed construction

 

 

Number of farms per sub-location

Building part

Materials used

Kir
n=18

Gaf
n=16

Kim
n=14

Buh
n=14

Mug
n=18

Kimn
n=12

Total (%)

Roofing

Straw

7

6

5

7

10

7

42 (45.7)

Sheet metal/or tiles

11

10

9

7

8

5

50 (54.3)

Wall

Perches/wood

18

16

14

14

18

12

92 (100)

Ground

Beaten ground with slope

4

7

4

3

5

2

25 (27.2)

Beaten ground no slope

14

9

10

11

13

10

67 (72.8)

 Kir=Kiruhura, Gaf=Gafumba, Kim=Kimirehe, Buh=Buhimba, Mug=Mugogwe, Kimn=Kimuna
Correlation analysis of livestock technologies adoption drivers

Pearson’s correlation analysis showed that level of education of the household head significantly influenced the adoption of improved cattle breeds (r = 0.62), p=0.001), use of AI as opposed to use of bulls (r = 0.55, p=0.001); use of intensive rearing systems (r = 0.33; p=0.01) and practicing castration (r = 0.57; p=0.001), however, level of education did not correlate with appreciation level for Rubona station services (r = 0.12; p p=0.238). The analysis showed that age of the household head strongly correlated with a number of factors. For instance, age negatively correlated with exotic breed adoption (r=-0.56; p=0.001) and reproductive method used (r = –0.48; p=0.001). Older household heads tended to be associated with indigenous cattle; and also tended to prefer use of bulls for breeding. It was therefore confirmed by correlation that cattle breed strongly correlated with breeding method (r = 0.74; p=0.001), implying that ownership of exotic animals was associated with reliance on the use of artificial insemination. Also it was observed that cattle breed correlated with the degree of intensification in rearing (r = 0.52; p=0.01). Indigenous cattle were move likely to be put under extensive grazing; while exotic ones were put in permanent stabling. However, we find no relationship between age of household head and level of appreciation of station services (r= 0.18; p=0.079). The analysis showed also that gender was not a significant factor.

Constraints to adoption of technologies and innovations

The major constraints to cattle keeping were: inadequate housing (78%), low production (71.7%), lack of training (65.2%) and lack of veterinary services (41.3%) (Figure 3).

Figure 3. Contraints to rearing of cattle


Discussion

Appreciating the role of agricultural research stations to the livelihoods of neighbouring households should ideally not be difficult to find. Either these households would provide their human unskilled or skilled labour to the research station and this would in return boost their incomes and hence livelihoods; or, the households would adopt the on-station technologies and where necessary adapt those technologies to their own circumstances, at their own farms and in the process transform their levels of productivity and directly impacting on their households’ livelihoods.

Universal primary education is now constitutionally enshrined in most developing countries. Driven by the tenets of the knowledge economy, Rwanda’s literacy levels are growing in bounds but with almost one quarter of respondents in this study declaring illiteracy, adult literacy programmes for the agricultural community will have to be undertaken to bring the agro-sector players closer to the national average and thrust Rwanda towards achieving Millennium Development Goal number two that seeks to achieve universal primary education for all world citizens by 2015 (http://www.developmentgoals.org).  The importance of education cannot be overemphasized as we found that level of education of the head of household had a significant influence on adoption of improved cattle breeds, artificial insemination, intensive cattle rearing systems and castration of excess bulls. Higher educated farmers have greater allocative ability and respond more efficiently to change (Karki and Siegfried 2004). Generally education is thought to create a favourable mental attitude for the acceptance of new practices especially the information-intensive and management-intensive practices (Caswell et al 2001).

Age is said to be a primary latent characteristic in adoption decisions (Mujuni 2011), and this was confirmed in our study with age of household negatively correlating with adoption of exotic breeds and artificial insemination. The effect is thought to stem from accumulated knowledge and experience of farming systems obtained from years of observation and experimenting with various technologies (Bonabana 2002). Younger farmers have been found to be more likely to adopt the new technologies than older farmers (Seon-Ae et al 2006). Older farmers, perhaps because of investing several years in a particular practice, may not want to jeopardize it by trying out a completely new method (Diederen 2003). In addition, farmers’ perception that technology development and the subsequent benefits, require a lot of time to realize, can reduce their interest in the new technology because of the farmers’ advanced age, and the possibility of not living long enough to enjoy it (Caswell et al 2001; Khanna 2001).

Population pressure appears to be driving the scarcity of farmland for the cattle rearing households. The common occurrence of < 0.5 ha as land owned per household was matched by the low average age of heads of households. Despite population growth controls that have been set up, more needs to be done to regulate the massive growth of the young population in the entire greater East African region.

Knowledge of technologies available to farmers is a major precursor to their adoption, since what is not known cannot be adopted and in any case, would have to first be innovated first. In the current study, all the respondents (Table 2) knew at least one technology available at the research station, but as would be theoretically expected, not even one technology had been universally adopted. This was because, even after several years of diffusion, adoption rarely reaches 100% of the potential adopters (Rogers 1995). For every available agricultural technology, there are early adopters, late adopters and non-adopters (Diederen 2003), the latter category popularly known as laggards.

Most farmers in this study had preference for crossbreeds (Ankole x Friesian breed) due to the high milk yield that is produced by crossbreeds compared to local breeds (MINAGRI 2008), as the crossbreeds tolerate higher ambient temperatures and other inclement weather compared to pure exotic breeds such as Friesian cattle. There is a relationship between milk yield, climate tolerance and dairy cattle breed preference by farmers. However, the persistence of some farmers on rearing of the local Ankole breeds could be correlated to their advantages. Ankole cattle tolerate high temperature, poor feeding and tick borne disease while exotic cattle are not adapted to local condition. It could be also ascribed to the financial means of the farmers. The observation of few numbers of farmers who reared exotic breeds can be correlated to the high investment needed to keep them. Exotic breeds require more care in terms of feeding and health than crossbreeds. Over the past seven years, the Rwanda government has been proactively engaged in an innovative program that uses the dairy sector development as a vehicle for boosting household incomes from milk sales and crop productivity improvement from manure use. This one-cow-per-poor-household program locally called “Girinka” targets the distribution of at least 600,000 cows by 2015, though currently, the program has just passed the 150,000 mark. Efforts of this program to which Rubona station provides cows and heifers must have contributed to the 69.5% coverage of exotic and crossbred cattle in our study area.

The majority of the farmers neighbouring the research station preferred the use of artificial insemination instead of using bulls due to the benefits of crossbreeding compared to continued rearing of the indigenous Ankole breed or relying on low grade crossbred bulls which would not achieve fast genetic progress that is largely preferred. In most cases, cows are artificially inseminated with the objective of improving the performance of the following offspring (MINAGRI 2011). Famers of the study area chose artificial insemination because they targeted cattle genetic improvement and disease control. The targeting of improved herd performance has also been of focus elsewhere (Chin 2002). The continued use of bulls for breeding among some studied households was attributed to failure of conception after artificial insemination, and the inaccessibility of inseminators, issues that have also been reported elsewhere (Sinniah and Pollott 2006). Artificial insemination can fail due to incorrect heat detection; hence identification of cattle in heat is critical especially in large herds. The farmer must closely monitor those cattle exhibiting oestrus to decide when they are in standing heat and ready to breed.

Feeding of cattle was largely based on grasses and fodders as these are easier to grow and bulk up easily compared to other feedstuffs. Grasses are adapted to high rainfall (>1000 mm per year) and are tolerant to a wide variety of soil conditions that are prevalent in the central and southern plateaus of Rwanda. It can also be related to the palatability and rapid growth of the grasses (Kitalyi et al 2005). It is important that diets for intensively managed cattle are balanced to contain cereals, legumes and vitamin-mineral supplements (Kitalyi et al 2005), since the animals that are confined cannot on their own have access to any missing nutrients. In our study, 26% of the respondents provided cereals and fodder tree legumes particularly Leucaena spp and Calliandra spp. These were adopted from Rubona station, which provides seeds and demonstrations on fodder establishment. In most cases these fodder trees are grown with other crops on the same pieces of land within the same years (MINAGRI 2004). Land size has been documented as positively impacting on feed availability (SNV 2010). Low levels of supplementary feeding have also been reported for communal livestock farmers in Namibia (Musaba 2010), and efforts geared to promoting use of crop residues would be of substantial role.

The lack of knowledge about forage conservation by the farmer community may be attributed to weak extension services in this regard. It is also plausible that shortage of forage due to low yields can also be responsible. Forage conservation is generally not a common practice among smallholder livestock keepers in the tropics, probably because of the very poor quality of mature tropical grass (Chedly and Lee 2000), but also because there is some grass always, in whatever state, compared to the temperate where season long standing forage absence occurs. Due to high market prices of dairy cattle commercial concentrates and minerals licks, most farmers could only resort to providing only rock salts to their cows because it was cheaper and readily available.

Partly due to the inadequate feeding regime of the cows (low quality and quantity of forage or lack of supplements feeds), plus their inferior genetics, low productivity was always going to be a major concern of the farmers, and indeed, many acknowledged this. Poor nutrition is one of the major problems affecting livestock productivity in the tropics. This is normally reflected in reduced live weights, perpetual low animal productivity, greater age at first parturition, increased parturition intervals, prolonged non-productive life and high mortalities (Kitalyi et al 2005). Higher producing cows must receive a concentrate ration in addition to roughage (Cheeke 2005). 

Farmers ranked inadequate housing as a top problem for their cattle husbandry and this is related with the lack of start-up capital, and could result into failure to prevent disease outbreaks. The housing of the animals is a crucial factor which must be taken into consideration seeing that there is a great influence on cattle health, nutrition and on the quality of milk (Webster et al 2005). Good enough, farmers preferred permanent stabling as rearing system which stops animals from loitering about in neighbours gardens and homes, where they could pick up pathogens. Zero grazing is almost inevitable given that more than 50% of the families in Rwanda have less than 0.75 ha of land (MINAGRI 2011). Adoption of dairy Farming technologies by livestock owners was found to be significantly influenced by information input, information output, farmer intra-system communication, farmer-researcher communication, farmer-extensionist communication, availability of input facilities and overall knowledge level about dairy farming technologies (Rezvanfar 2007).


Conclusion


Recommendations

The following recommendations have been formulated for ensuring increased adoption of cattle management technologies:


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Received 7 September 2013; Accepted 30 September 2013; Published 1 November 2013

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