Livestock Research for Rural Development 21 (5) 2009 Guide for preparation of papers LRRD News

Citation of this paper

Analyzing the farmer-specific and socio-personal factors influencing adoption of pasture conservation technologies amongst livestock farmers in the Tehran Province of Iran

A Rezvanfar and F Arabi

Department of Agricultural Extension and Education, College of Agriculture and Natural Resources, Faculty of Economics and Development, University of Tehran, Karaj. Iran
arezvan@ut.ac.ir

Abstract

The main purpose of this study was to analyze the farmer- specific and socio-personal factors influencing adoption of pasture conservation technologies amongst livestock farmers in the Tehran Province of Iran. The statistical population includes all livestock farmers living in villages, which locate in the East Region of Tehran Province.  A sample of 110 livestock farmers were selected by the use of “classified proportional random sampling” method. A questionnaire was used to collect data. For determining the validity of the questionnaire, the content validity was used.  Cronbach's alpha was used to measure reliability of the index measuring “level of adoption of pasture conservation technologies” that its extent was 0.77 and showed that mentioned variable had high reliability. The data were analyzed by the use of descriptive and inferential statistics such as extent of mean, standard deviation, t Test, coefficient of variation, correlation analysis and regression analysis.

 

Based on the results, it can be concluded that majority of livestock farmers (71.8%) of the two groups were found belonging to medium level of adoption of pasture conservation technologies, followed by 21.4 and 1.8 percent livestock farmers with high and low level of adoption behavior with respect to pasture conservation technologies. Age, during use of pastures, family size, availability of communication channels, land size managed about pasture conservation technologies had positive and highly significant relationship (P<0.01) and educational level, rate of income from main occupation and herd size had positive and significant relationship (P<0.05) with level of adoption of pasture conservation technologies. The result of multiple regression showed that variables of age, rate of income from main occupation, during use of pasture, herd size, land size and species of livestock 35% of the variation in the level of livestock farmers' adoption level of pasture conservation technologies.

Key Words: adoption, adoption behavior, conservation technologies, livestock farmer, pasture management


Introduction

Pastures as a broad category of land comprising more than 40% of the earth, land area, are characterized by native plant communities and seeded lands that are managed like rangelands which are often associated with grazing (Walker and Hodgkinson 2000).          

 

The pasture management constraints include environmental, managerial, socioeconomic and financial factors due to which these important natural resources are degrading and deteriorating at faster pace (Johnson 1999 and Sardar 2000).

 

Having suitable pastures and conservation technologies remains important for any livestock farmer, as proportion of livestock and pastures, availability to water resources, coverage of pastures are major constraints on livestock production in Iran (Cassman and Pingali 1995). This leads to the major problem that livestock farmers produce below capacity.

 

The reason for poor adoption of conservation technologies amongst livestock farmers all over the world is not fully understood. Never the less, the question of why livestock farmers did not adopt new technologies is complex.

 

Up to a few years ago the diffusion of innovation research established the importance of adoption conservation technologies in the modernization process at the local level. In this way many scholars (Obinne and Anyanwe 1991; Williams and Williams 1991; World Bank 1993; Adedoyin and Macoyawa 1995; Islam and Kassem 1999; Boyazoglu and Nardone 2003 and Mafimisebi et al 2005) have used the diffusion model for analyzing the adoption behavior of farmers. However, innovation adoption is different from individual to individual according to their socio-personal characteristics. Hence, it was proposed to analyze variables such as socio-personal characteristics factors influencing the adoption behavior of livestock farmers with reference to the adoption of pasture conservation technologies (Nells 1998; Johnson 1999; Emtage and Suh 2006 and Mofimisebi et al 2005). The specific objectives of the study were:

 

1) To determine the levels of adoption of the various recommended pasture conservation technologies.

3)  To study differences in mean values of adoption of pasture conservation technologies.

2) To study the factors associated with adoption of pasture conservation technologies amongst livestock farmers.

 

Theoretical approach

 

The theoretical approach used to guide the study is draw from selected components of adoption of conservation technologies. The literature on adoption of conservation technologies suggest that the conservation technologies about pasture of farmers is explained by farmer and household characteristics (Huntsinger 2002 and Sardar 2000), institutions and infrastructure variables (Fried 2002; Umrani 1998; Nardone and Gibon 2000) and perceptions and attitudes about conservation technologies of livestock farmers (Simcox and Hodgson 1993; Starr and Huntsinger 1998).

           

A few recent studies have more focused especially on farmers’ adoption behavior in the field of conservation technologies in pastures which explained by perception about grazing system (Nells 1998; Bieling and Plieninger 2003; Diao 2006), property form of pastures (Knight 2002), private and cooperative owned land (Sulak and Huntsinger 2002 and Emtage and Suh 2006), mean head of livestock (Mafimisebi et al 2005), pests and weed control (Sellers et al 2006), choice of the livestock to farm (Nardone and Gibon 2000), and livestock movement (Sowell et al 1999; Roger and Sheley 2004).

 

Methods and materials 

The selection of variables as possible predictors for the conservation technologies in pastures was based on pasture management technologies and past empirical work.

 

A questionnaire was developed to obtain information at farm level from randomly selected livestock farmers in Tehran Province of Iran. As regards the selection of respondents, rural areas of the East region of the Tehran Province were divided into two different regions consisting High Lands (HLs) and Low Lands (LLs) based on agro-climatic and geographical conditions. From each region, two districts were selected purposively. Then with remark to the difference of population of the livestock farmers, 15 villages (ten from High Lands and other five from Low Lands) were selected randomly. For the purpose of selection of the respondents finally proportional random sampling was used. However, totally 110 respondents (75 livestock farmers from high lands and 35 livestock farmers from low lands) constitute the sample size. The socio-economic and personal traits and management variables of livestock farmers were selected for the study purpose. Adoption of conservation technologies in pastures was the dependent variable.

           

To determine the different levels of adoption of pasture conservation technologies amongst livestock farmers the described process in mean deviation was used. However, Adoption of conservation technologies in pastures was studied at three levels, low, medium and high, respectively. Variety of statistical techniques like frequency distribution, percentage, means, standard error, t-Test, product moment correlation and multiple regression analysis was used to analysis the data.

 

Findings and discussions 

Adoption of pasture conservation technologies

 

The farmers were asked whether they adopted some of the recommended common conservation technologies on their pasture or not. The results pertaining to this are presented in Table 1 which clearly indicates that 25.4 percent of livestock farmers from both areas did not adopt rotational grazing and livestock movement, while 33.6 percent of them did not adopt using fens for subdivided into paddocks to their pastures.

           

It could further be seen that 44.6 percent of livestock farmers had adopted technology of developing ponds and building check dams. The percentage of adopters was over the one-second in the case of species proportional selection of livestock (59.1%).

           

Further, as shown in Table 1 about 53.7 percent of farmers did not adopt establishment of fodder banks while majority of them (59.1%) had adopted identify the kinds of different plants in pasture in their pastures.

 

Nearly one-second of the farmers had adopted technology related to medical, biological and chemical weed control and 52.7 percent had adopted technology related to prevention of firing into pasture. Further perusal of Table 1 indicates that the percentage of adopters of LLs the technologies is relatively higher in rural areas in LLs than HLS. Thus it can be concluded that the extent of adoption of common conservation technologies in LLs was better amongst as compared to their counterparts in HLs. 


Table 1.  Frequency Distribution of Livestock Farmers as per their Adoption of Pasture Conservation Technologies

Sl. No.

Adoption of Technologies

HLs  (n=75)

LLs  (n=35)

Total  (N=110)

Adopted

Non-adopted

Adopted

Non-adopted

Adopted

Non-adopted

F

%

F

%

F

%

F

%

F

%

F

%

1.

Rotational grazing

10

13.6

65

86.4

17

48.6

18

51.4

28

25.4

82

74.6

2.

Using fens for subdivided into paddocks

30

40.8

45

59.2

7

20

28

80

37

33.6

73

66.3

3.

Livestock movement

19

25.8

56

74.2

9

25.7

26

74.3

28

25.4

82

74.6

4.

Developing ponds and building check dams

37

50.3

38

49.7

24

48.6

11

31.4

61

55.4

49

44.6

5.

Species proportional selection of livestock

29

39.4

46

63.3

17

48.6

18

51.4

46

41.8

64

58.2

6.

Establishment of fodder banks

27

36.7

48

63.6

14

40

21

60

51

46.3

59

53.7

7.

Identify the kinds of different plants in pasture

43

58.4

32

41.6

22

62.9

13

37.1

65

59.1

45

40.9

8.

Medical, biological and chemical weed control

36

48.9

39

51.1

12

34.3

23

45.7

48

43.6

62

59.4

9.

Prevention of firing into pasture

47

63.9

28

36.1

16

45.7

19

54.3

63

52.7

47

42.7


Ranking of adoption of pasture conservation technologies

 

Data shown in Table 2 indicate that rotational grazing, use fens for subdivided into paddocks, livestock movement, are the first to third ranks about adoption of conservation technologies in High Lands (HLs).

 

Further, as shown in Table 2 about Adoption of conservation technologies in Low lands (LLs) and rotational grazing, livestock movement, use fens for subdivided into paddocks are the first to third ranks about adoption of conservation technologies in Low Lands (LLs).

While medical, biological and chemical weed control and prevention of firing into pasture were the last ranks about adoption of conservation technologies in High and Low Lands.


Table 2.  Ranking of Adoption of Pasture Conservation Technologies

HLs  (N=75)

Ranking of adoption of conservation technologies in pastures

LLs  (N=35)

Ranke

CV

Standard

Deviation

Mean

 

Mean

Standard

Deviation

CV

Ranke

1

0.03

0.11

2.98

Rotational grazing

2.91

0.32

0.10

1

2

0.06

0.19

2.96

Use fens for subdivided into paddocks

2.89

0.35

0.12

3

3

0.10

0.30

2.93

Livestock movement

2.88

0.32

0.11

2

4

0.13

0.38

2.89

Developing ponds and building check dams

0.333

0.42

0.14

5

5

0.19

0.53

2.81

Species proportional selection of livestock

2.89

0.38

0.13

4

6

0.21

0.54

2.57

Establishment of fodder banks

2.77

0.54

0.19

7

7

0.23

0.64

2.72

Identify the kinds of different plants in pasture

1.02

0.16

0.16

6

8

0.25

0.67

2.64

Medical, biological and chemical weed control

2.74

0.56

0.20

8

9

0.39

0.90

2.28

Prevention of firing into pasture

2.31

0.86

0.37

9


On the whole, as evident in the Table 3, majority of the farmers (71.8%) were found belonging to medium level of adoption behavior, followed by 26.8 percent and 1.8 percent of the farmers with high and low level of adoption behavior in respect of conservation technologies viz. grazing system, fencing, pests control technologies. This finding supports the finding of Williams and Williams (1991); Adedoyin and Macoyawa (1995); Islam and Kassem (1999); Boyazoglu and Nardone (2003), Mafimisebi et al (2006), who had stated that majority of farmers, had medium level of adoption behavior.


Table 3.  Frequency distribution of farmers as per their level of adoption of pasture conservation technologies

S1. No.

Adoption (Score)

HLs  (n=75)

LLs  (n=35)

Total  (N=110)

F

%

F

%

F

%

1.

Low (<21)

16

21.3

13

37.1

29

26.4

2.

Medium (21-43)

57

76.0

22

62.9

79

71.8

3.

High (>43)

2

2.7

-

-

2

1.8


Differences in mean values of adoption of pasture conservation techniques

           

It is amply clear from the Table 4 that highly significant (P<0.01) difference was observed in the mean values of adoption of conservation techniques in memberships of community-based organization and privately owned land between farmers of HLs and LLs. However, no significant difference was observed in the mean scores of adoption of conservation techniques between farmers who not membership of organization as well as cooperatively owned land between farmers of HLs and LLs.


Table 4.  Mean values of adoption of pasture conservation technologies in different groups of farmers (N=110)

S1.

No

Variable (Adoption of conservation technologies)

 

Mean

Values

 

HLs (n=75)

LLs (n=35)

t  Values

1

Membership of community-based organization

Membership

7.99

2.9

3.44**

 

 

No Membership

11.8

10.32

0.77

2

Property form of pasture

Privately owned land

13.8

2.9

4.42**

 

 

Cooperatively owned land

6.12

6.4

1.04

**P <0.01


Adoption of conservation techniques was found to be significantly higher amongst the farmers in HLs than LLs. Mean values of the adoption of conservation techniques of the farmers of HLs and LLs differed highly and significantly (P<0.01).


Table 5.  Mean values of adoption of pasture conservation technologies in different groups of farmers  (N=110)

S1. No.

Variable

Mean

Values

 

HLs  (n=75)

LLs  (n=35)

t  Values

1

Adoption of conservation technologies

12.40

5.63

2.892**


Relationship between amounts of adoptions of pasture conservation technologies by farmers with other independent variables

 

It is clear from the Table 6 that age, during use of pasture, family size and availability of communication channels had positive and highly significant relationship (P<0.01) with level of adoption of pasture conservation technologies.

 

Further perusal of Table 5 indicated that level of education, rate of income from main occupation, herd size and land size managed had positive and significant (P<0.05) relationship with adoption of pasture conservation technologies This findings supports the finding of Adedoyin and Macoyawa (1995); Islam and Kassem (1999) and Mafimisebi et al (2006), who had reported relationship between some individual and economical variables and adoption of technologies.  


Table 6.  Correlation coefficient of adoption of pasture conservation technologies by farmers with farmer- specific and socio-personal variables (N=110)

Correlation coefficient

Variables

S1. No.

0.35**

Age

X1

0.22*

Level of education

X2

0.24*

Rate of income from main occupation

X3

0.28**

During use of pastures

X4

0.27*

Herd size

X5

0.19**

Family size

X6

0.25**

Availability of communication channels

X7

0.13*

Land size managed

X8

*P<0.05             **P<0.01


Regression coefficient of adoption of pasture conservation technologies on  independent variables             

As shown in Table 6 the positive and highly significant partial regression coefficient of age and rate of income from main occupation (P<0.01) and during use of pasture, herd size, land size and species of livestock (P<0.05) was found to have contributed in the increase of overall adoption of pasture conservation technologies among farmers. The R2 value of 0.355 with F value of 17.12 indicates its significance 0.01 level of probability and revealed that 35.5 percent variation in adoption of conservation technologies of the farmers could be explained with the help of these five variables.


Table 7.   Partial regression coefficient of adoption behavior of farmers on farmer- specific and socio-personal variables

S1. No.

Variables

Partial regression coefficient, Y1

X1

During use of pastures

2.29*

X2

Herd Size

0.118*

X3

Age

0.09**

X4

Rate of income from main occupation

0.08**

X5

Land size managed

2.05*

X6

Species of livestock

3.25*

 

F Value

17.12**

 

R 2  

0.355

** P<0.01    * P<0.05


These results which are supported by several authors (Nells 1998; Johnson  1999; Emtage and Suh 2006; Mafimisebi et al 2006) show the importance of farmer- specific and socio-personal variables over adoption of pasture conservation technologies among livestock farmers.

 

Conclusions and recommendations 

 

References 

Adedoyin S F and Macoyawa O O 1995 Operational modes of providing linkage between veterinary extension service and livestock farmers in Ogun State. Nigeria Department of Agricultural Extension and Rural Sociology, Ogun State University, Agoiwoye, Nigeria. Agro Search 1: 17-24

 

Bieling C and Plieninger A 2003 Stinking, disease-spreading brutes, or four-legged landscape managers? Livestock, Pasturalism and Society in Germany and the USA. Journal of Agriculture 32(1): 7-12

 

Boyazoglu J and Nardone A 2003 The relationship between environment and animal production, Aristotle University, Thessaloniki, Greece 11(1): 57-64

 

Cassman K G and Pingali P L 1995 Extrapolating trends from long-term experiments to farmer fields: The Case of Irrigated Rice System in Asia, UK, pp. 63-84.

 

Diao B 2006 Livestock production and conservation in and around protected areas: The project for integrated ecosystem management in Senegal. Senegalese Institute of Agricultural Research (ISRA). Dakar, Senegal.

 

Emtage N F and Suh J 2006 Socio-economic factors affecting smallholder tree planting and management intention in Leyte Province, The Philippines. Small-scale Forest Economics, Management and Policy 3(2): 257-270.

 

Fried T 2002 Making a living of Wal-Mart, in Knight R L, Gilbert W C and Marston E editors., Ranching West of the 100th Meridian: culture ecology and economic, Island Press, Washington, DC, pp.183-194.

 

Huntsinger L 2002 End of the trail: ranching transformation on the pacific slope, in Knight R L, Gilbert W C and Marston E editors, Ranching West of the 100th Meridian: culture ecology and economic, Island Press, Washington, DC, pp77-90.

 

Islam M M and Kassem M A 1999 Farmers' use of ethno-veterinary medicine (EWM) in the rearing and management of livestock: an empirical study in Bangladesh. Journal of sustainable agriculture 13(4): 39-56

 

Johnson T R 1999 Community-based forest management in the tropics: social and economic analysis policy, Edward Elgar, Cheltanham, pp. 227-240.

 

Knight R L 2002 The ecology of ranching in Knight R L, Gilbert W C and Marston E editors, Ranching West of the 100th Meridian: culture ecology and economic, Island Press, Washington, DC, pp123-145.

 

Mafimisebi T E, Onyeka U P, Ayinde I A and Ashaolu O F 2005 Analysis of farmer–specific socio–economic determinants of adoption of modern livestock management technologies by farmers in Southwest Nigeria. Journal of Food, Agriculture and Environment 4 (1): 183-186

 

Nardone A 2000 Weather conditions and genetics of breeding systems in the Mediterranean area. Proceeding of the 35th International Symposium of Società Italiana per il Progresso della Zootecnia, Ragusa, 67-91 pp.

 

Nardone A and Gibon A 2000 Livestock Farming Systems, research and development issues. Proceeding of the 35th International Symposium on Technical and Social Systems Approaches for Sustainable Rural Development. 71-92 pp.

 

Nells W T 1998 Transfer and adoption of technology: The case of sheep and goat farmers in Qwaqwa. (Unpublished Ph.D. Thesis), University of the Orange, Free State, Bloemfontein. Retrieved in August 12, 2003 from: http://www.uovs.ac.za/faculties/agric/centre
 

Obinne C O and Anyanwu A C 1991 Communication factors determining adoption of improved cassava technologies in small-holder agriculture. Nigerian Journal of Rural Extension and Development 1(1):15-23

 

Roger L and Sheley A 2004 Rangeland weed management.  The U.S. Department of Agriculture (USDA), Montana State University and the Montana State University Extension Service. 4 pp. (on line). Retrieved in April 20, 2007 from: http://attra.ncat.org/attra-pub/past_range_graze.html

 

Sardar M R 2000 Management constrains and possible solution to high altitude pastoral systems of Pakistan. Pakistan, PFI, Peshawar. 50 PP.

 

Sellers B A, Ferrell J A, Mullahey J J and Brecke B J 2006 Pasture weeds management. Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. 4pp. Retrieved in February 14, 2007 from:  http://edis.ifas.ufl.edu/pdffiles/AG/AG17400.pdf

 

Simcox D E and Hodgson R W 1993 Strategies in intercultural conservation for natural resources agencies. In Evert A E, Chavez D J and Majills A W, editors. Culture conflict and communication in the Wild land-Urban interface, West view press, Boulder, San Francisco and Oxford, pp 217-227.

 

Sowell B F, Mosley J C and Bowman J G P 1999 Social behavior of grazing beef cattle: Implications for management. Proceedings of the American Society of Animal Science 231:406-412 http://jas.fass.org/cgi/reprint/77/E-Suppl/1-t.pdf

 

Starr P and Huntsinger L 1998 The cowboy and buckaroo in American ranch hand styles, Rangelands 20(5): 36-40

 

Sulak A and Huntsinger L 2002 Sierra Nevada grazing in transition: The role of forest service in the foothill ranches of California. Sierra Nevada Alliance, California Rangeland Trust, California Cattlemen's Association, Berkeley, C.A.

 

Umrani A P 1998 Sustainable approaches for rangeland management and livestock production in Pakistan. PhD Thesis, Agriculture Department, Aberdeen University UK. ftp://ftp.fao.org/docrep/nonfao/lead/x6181e/x6181e00.pdf


Walker J W and Hodgkinson K C 2000 Grazing management: new technologies for old problems. 15 pp. (on line). Retrieved in February 12, 2007 from:: http://sansangelo.taumu.edu/walker/ircpaper.htm 


Williams C E and Williams S K T 1991 Extension services in livestock production sector in Nigeria. Nigerian journal of rural extension and development 1(1): 1-13

 

World Bank 1993 A strategy to develop agriculture in Sub-Saharan Africa and a focus for the World Bank. World Bank Technical Paper 203:61-77



Received 26 January 2008; Accepted 3 March 2009; Published 1 May 2009

Go to top