Livestock Research for Rural Development 23 (3) 2011 Notes to Authors LRRD Newsletter

Citation of this paper

Use of quality information for decision-making among livestock farmers: Role of Information and Communication Technology

Jabir Ali

Centre for Food and Agribusiness Management, Indian Institute of Management,
Prabandh Nagar, Off Sitapur Road, Lucknow – 226 013, Uttar Pradesh, India
jabirali@iiml.ac.in

Abstract

The rapid growth in the demand for high value agriculture of which livestock products constitute the major share, and fast changing livestock production system necessitate the provision of efficient flow of information and knowledge to the livestock farmers for better decision-making. This paper analyses the use of information and communication technology (ICT) enabled services for livestock information delivery based on primary survey of 342 livestock farmers in eight districts of Uttar Pradesh. The differences in quality of decisions on various livestock practices, between users and non-users of ICT driven information system have been assessed using analysis of variance (ANOVA) technique.

Results indicate that ICT users are making significantly better quality decisions as compared to non-users. Correlation analysis between frequency of ICT use and socio-demographic profile of livestock farmers indicate a significantly positive relationship with a number of factors, which provides practical insights for designing target based ICT driven information system for livestock sector development.

Keywords: animal husbandry, decision-making, ICT, information system, India


Introduction

Livestock sector plays a multi-faceted role in socio-economic development of rural households and contributes about 4.2 percent to the Gross Domestic Product and 25.6 percent to the Agricultural Gross Domestic Product in the country. Over the last three decades, livestock sector has grown at an annual rate of 7 percent, which is more than double the growth of the agricultural sector. Empirical evidences indicate that livestock is an important component of the agriculture system, providing an additional source of income and nutritional cover to a large section of the rural population, particularly the disadvantaged and poor households (Rao et al 2003; Birthal and Ali 2005; Ravikumar and Chander 2006, Singh et al 2007). The distribution of livestock, as a liquid asset to poor families, is more egalitarian as compared to land (Taneja and Birthal 2004; Ali 2007). However, the recent trend in livestock sector growth suggests that in order to meet the emerging demand for livestock based products, both in domestic and global markets, there is a need to reorient the production system by enhancing the efficiency and creating quality consciousness. Verbeke (2001) argued that the consumer concerns about food safety of animal based products have led to an increased demand for information and transparency in food chains, and have acted as the major driver for the development of traceability systems. Adhiguru et al (2009) argued that farmers are not only looking for various information sources for carrying out their production and marketing tasks efficiently but also for ensuring delivery of safe and quality products to the consumers.  

With the changing environment of food and agriculture sector including livestock based high value agriculture segment, information and knowledge has increasingly become an important factor of production for effective decision-making (Birkhaeuser et al 1991; Cash 2001; Galloway and Mochrie 2005; Adhiguru et al 2009). In most of the developing countries, information on improved agricultural technologies and practices are public goods and agricultural extension services are one of the most common means of public-sector knowledge dissemination (Birkhaeuser et al 1991; Dancey 1993; Umali and Schwartz 1994; Nirmala et al 1995; Dinar 1996; Umali-Deininger 1997, Anderson and Feder 2004). However, dissemination of information on livestock production has rarely been a priority for centralised extension services in developing countries (Morton and Matthewman 1996).  Though veterinary services are being provided by the public sector in India, the financial constraints with most of the state governments have made it difficult to expand the reach of livestock services as well as to improve the quality of service delivery (Ahuja et al 2003; Bardhan 2010).

Information adoption among farming community is widely acknowledged as one of the critical factors for efficient and effective agricultural decision-making (Cash 2001, Galloway and Mochrie 2005, Rao 2006). Sasidhar and Sharma (2006) have emphasised that the use of Information and Communication Technology (ICT) has potential to change the economy of livestock, agriculture, and rural artisans in India. Tiwari et al (2010) argued that the livestock sector should come up with the need based, location specific and local language contents in the form of computer software’s and other electronic material in regards to livestock disease control, dairy herd management, livestock production and for marketing of livestock and livestock produce. ICT based information delivery to livestock sector can significantly improve the quality of decision-making in livestock farming system. With intensification of crop/ livestock production systems and increased market demand of animal based products, the importance of information is growing in many developing countries (Morton and Matthewman 1996). In this process of structural change and potential growth in high value products (Gulati et al 2007), ICT based livestock advisory services for knowledge dissemination to the farming communities for better and informed decision-making at the farm level, have become essential.

This study analyses the use of ICT based information delivery systems on various livestock practices based on primary and secondary sources of data. The primary data has been collected through a structured survey of 342 farmers in eight districts of Uttar Pradesh with the help of personal interviews on information usage for livestock rearing. The differences in quality of decisions on various aspects of animal husbandry between ICT users and non-users have been analyzed using analysis of variance technique. Further, the Spearman’s Rank Correlation analysis has been done to understand the relationship between frequency of ICT usage in livestock decision-making and socio-demographic profiles of livestock farmers.

Material and Methods

Data collection, survey instrument and data analysis

This study is primarily based on the primary survey of 342 livestock farmers belonging to eight districts of Uttar Pradesh in India - Aligarh, Allahabad, Etawah, Bareilly, Hardoi, Pratapgarh, Raibareilly and Shahjahanpur. Initially, questionnaire survey was administered among 461 farmers and their responses to various questions related to information usage on agricultural practices were obtained and recorded in the last quarter of 2007. However, this study only includes the responses from 342 livestock farmers. To ensure proper representation of users and non-users of ICT based information systems for livestock decision-making, a total of 30 villages were surveyed, where 15 villages were having e-Choupals[1], established by the private and public agencies. Out of the total 15 e-Choupal villages, 10 villages were covered by the private agency i.e. Indian Tobacco Company (ITC) and 5 villages were covered by the public agency i.e. Uttar Pradesh Bhumi Sudhar Nigam (UPBSN). For each village, a minimum 15 randomly selected user farmers were surveyed personally with the help of a structured questionnaire. ICT users were categorized based on the usage of information from one or more than one ICT based sources i.e. e-Choupals, televisions and radios.

Secondary data has been collected from the 59th round report on the Situation Assessment Survey of Farmers, conducted by the National Sample Survey Organization (NSSO), Ministry of Statistics & Programme Implementation, Government of India in 2003. Farmers’ responses on various livestock information services have been analyzed with Simple Statistical Techniques such as descriptive analysis, cross-tabulation, chi-square test, analysis of variance (ANOVA) and Spearman’s Rank Correlation with the help of the statistical software for social sciences (SPSS 15.0).  

Profile of ICT users and non-users

Out of 342 livestock farmers surveyed, a total of 107 farmers reported the use of ICT based information for livestock related decision-making i.e. 31.3 percent. Table 1 provides summary profile of sample livestock farmers with respect to age, education, social category, income level and landholding size. Majority of the respondents were of the age between 25 to 60 years with an average age of 43 years, indicating a mature livestock rearing group. However, there was no significant difference in average age of ICT users and non-users ( =2.03, p>0.1). With regard to education, ICT users were comparatively more educated than non-users, as revealed by the results of chi-square tests ( =17.9, p<0.01). Most of the ICT users belong to general category, representing the higher social groups as compared to non-users. The results of chi-square tests revealed a significant difference in social background of users and non-users of ICTs ( =6.42, p<0.05).  


Table 1. Sample demographic characteristics (N=342)

Socio-demographics

ICT Users (n=107)

ICT Non-Users (n=235)

Chi-square test

N

%

N

%

Age, years

 

 

 

 

 

<25

9

8.4

13

5.5

2.03

25-40

45

42.1

115

48.9

df=3

40-60

38

35.5

79

33.6

 

>60

15

14.0

28

11.9

 

Average age, years

44

 

43

 

 

Education

 

 

 

 

 

Illiterate

3

2.8

34

14.5

17.92***

Junior High School & Below

30

28.0

89

37.9

df=3

High School/Intermediate

57

53.3

82

34.9

 

Graduate/Post Graduate

17

15.9

30

12.8

 

Social category

 

 

 

 

 

General

56

52.3

94

40.0

6.42**

Other Backward Class, OBC

46

43.0

115

48.9

df=2

Schedule Caste, SC

5

4.7

26

11.1

 

Monthly Income, Rs.

 

 

 

 

 

<1000

4

3.7

35

11.4

10.24*

1001-2000

28

26.2

65

27.2

df=5

2000-3000

36

33.6

62

28.7

 

3001-4000

13

12.1

27

11.7

 

4001-5000

9

8.4

16

7.3

 

>5000

17

15.9

30

13.7

 

Landholding Size

 

 

 

 

 

Marginal, <1 ha

11

10.3

70

29.8

16.35***

Small, 1-2 ha

43

40.2

75

31.9

df=3

Medium, 2-4 ha

38

35.5

58

24.7

 

Large, >4 ha

15

14.0

32

13.6

 

Average landholdings, ha

2.77

 

2.40

 

 

***Significant at the 0.01 level, **Significant at the 0.05 level, *Significant at the 0.10 level


In terms of monthly income levels, ICT users belong to comparatively higher income groups as compared to non-users ( =10.2, p<0.10). On the basis of land holding size, the sample can be divided into four categories: large (land holding equal to or more than 4 ha), medium (land holding 2-4 ha), small (land holding 1-2 ha) and marginal (land holding less than 1 ha). Average landholdings of ICT adopters was estimated to be 2.77 hectares, which is relatively higher than non-users (2.40 ha). The results of chi-square tests for landholding size indicated a significant difference ( =16.3, p<0.01).

Results and Discussion

Sources of information on animal husbandry

Agricultural extension services in most of the developing countries including India, are usually designed around crop husbandry, while public sector initiatives towards animal husbandry are often dominated by animal breeding and health services (Morton and Matthewman 1996). Several argue that the concentration of government focus on livestock health is justified as farmers gain confidence that diseases are under control and  are thereby prepared to invest more on livestock production (de Haan and Bekure 1991; Morton and Matthewman 1996). However, the changes in Indian livestock production have necessitated the provisions of delivering seamless information on various aspects of animal husbandry including processing and market linkage for animal based products.

A recent Situation Assessment Survey of Farmers by the National Sample Survey Organization (NSSO) on Access to Modern Technology for Farming indicates that only 5.1 percent of the households access information on animal husbandry (NSSO 2005).  Figure 1 provides details of types of information used by the famers for livestock decision-making. In India, most of the farmers seek information on production related activities such as health care, breeding and feeding, while information on livestock management is being used by only 9 percent households. In case of Uttar Pradesh, the use of information becomes even more skewed towards livestock production system where about 70 percent households use information on livestock health care followed by breeding and feeding (Figure 2). The dominance of production related information does not mean that farmers do not require information on livestock management, prices and market linkages; rather this may be due to the supply constraints of livestock extension services. 

A closer look on the type of livestock extension services delivered clearly indicates that health and breeding information has been given more attention by the policy planners and agricultural extension organizations, whereas value addition aspects have been largely neglected. The importance of information for livestock based processing, product prices and marketing has significantly increased in the present market-driven high value food economy, demanding reorientation in livestock information delivery by the public as well as private agencies.


Figure 1.  Distribution of households by types of information on animal husbandry – India.
Source: Report No. 499(59/33/2), Access to Modern Technology for Farming, NSSO, GoI, 2005
Figure 2.  Distribution of households by types of information on animal husbandry – Uttar Pradesh.
Source: Report No. 499(59/33/2), Access to Modern Technology for Farming, NSSO, GoI, 2005

The National Sample Survey results indicate that the main sources of information on animal husbandry in India are the progressive farmers (29%) followed by electronic and print media (Table 2). The penetration level of government extension system in information dissemination seems to be low. In case of Uttar Pradesh a significant 61 percent of livestock information is primarily supplied by the progressive farmers followed by electronic and print media (Table 2). The results also indicate that most of the information related to breeding, feeding and healthcare is provided by the progressive farmers. Television and radio together are used by about 37 percent livestock farmers for breeding information, 29 percent for animal feed related information and about 25 percent for health care advise. 


Table 2. Sources of information on animal husbandry in India (%)

Sources of Information

Breeding

Feeding

Healthcare

Management

Others

Overall

India

 

 

 

 

 

 

Training, demonstration & study tour

3.7

2.8

3.5

4.9

1.8

3.3

Krishi vigyan kendra

0.1

0.6

0.4

0.0

0.4

0.3

Extension worker

2.8

4.4

5.2

2.5

4.0

4.2

Television

21.5

12.1

10.3

9.6

12.6

13.1

Radio

15.0

17.2

15.3

6.0

13.6

14.5

Newspaper

9.8

11.8

8.2

7.5

14.4

9.8

Input dealer

0.2

10.3

2.3

5.6

5.4

3.8

Other progressive farmers

28.6

27.4

36.2

30.7

4.5

28.8

Para technician/ private agency/ NGO

0.5

0.6

4.7

2.7

0.9

2.6

Primary cooperative society

3.8

3.4

0.8

1.1

8.2

2.8

Output buyer/food processor

1.3

3.1

0.1

5.5

6.0

2.0

Credit agency

3.5

1.8

0.4

13.7

12.6

4.0

Others

4.2

2.4

11.2

6.6

10.5

7.9

Uttar Pradesh

 

 

 

 

 

 

Training, demonstration & study tour

0.0

0.0

0.1

0.0

0.0

0.1

Extension worker

0.0

0.0

0.8

0.0

0.0

0.5

Television

4.1

0.8

6.3

34.4

18.6

6.7

Radio

29.9

27.3

22.4

0.0

37.6

24.3

Newspaper

2.2

0.0

1.0

62.6

26.1

3.7

Input dealer

0.0

4.6

0.0

0.0

0.0

0.5

Other progressive farmers

49.5

66.8

68.5

0.0

0.0

60.7

Para technician/ private agency/ NGO

2.7

0.0

0.0

0.0

0.0

0.3

Primary cooperative society

6.2

0.0

0.0

0.0

0.0

0.7

Output buyer/food processor

2.4

0.0

0.0

0.0

0.0

0.3

Credit agency

0.0

0.0

0.8

0.0

0.0

0.5

Others

0.0

0.5

0.2

3.0

9.2

0.8

Source: Report No. 499(59/33/2), Access to Modern Technology for Farming, NSSO, GoI, 2005


ICT in livestock decision-making

The major characteristics of quality information are relevance, accuracy, sufficiency and timeliness of service delivery for better decision-making. Quality information plays a pivotal role in enlightening and raising the level of knowledge of livestock farmers on best practices across the value chain. The quality perceptions of the farmers on various aspects of animal husbandry were recorded on a five point likert scale. The results of mean scores of information quality and analysis of variance between users and non-users of ICT based information sources on 8 dimensions of livestock decision-making are given in Table 3. The results on mean value of responses on various livestock practices are less than 3 in most of the cases, which clearly indicate that farmers are receiving quality information for livestock decision-making. The results also indicate that the mean scores on all the parameters of livestock rearing are lower in case of ICT users as compared to non-users. In order to analyze the difference in quality of information received by them, analysis of variance (ANOVA) has been carried out. Results of the analysis indicate that the value of F-statistics are significant at 1% level of significance for most of the production related decisions such as breeding, feeding, healthcare and livestock production management. The usage level of this information is also comparatively higher as compared to information usage on processing and marketing of livestock based products. 


Table 3. ANOVA on quality of information on animal husbandry

Livestock activities

ICT based

Non-ICT based

F-value

N

Mean

Std. Deviation

N

Mean

Std. Deviation

Breeding

101

1.82

0.79

172

2.68

0.72

83.50***

Feeding

102

1.87

0.80

184

2.55

0.66

59.83***

Livestock healthcare

104

1.96

0.87

224

2.73

0.63

82.94***

Livestock management

59

2.19

0.75

135

2.60

0.66

14.76***

Milking techniques

57

2.54

0.85

118

2.83

0.71

5.53**

Quality management

52

2.42

0.85

105

2.75

0.79

5.83**

Market price analysis

54

2.17

0.75

117

2.38

0.64

3.84*

Marketing & selling

53

2.09

0.77

115

2.36

0.65

5.25**

***Significant at the 0.01 level, **Significant at the 0.05 level, *Significant at the 0.10 level
Note: Responses in five points likert scale indicated as very good=1, good=2, average=3, poor=4 and very poor=5


The adoption of milking technique, quality management of livestock products due to highly perishable nature, market price analysis and marketing and selling are critical areas of decision-making for the livestock farmers. However, the usage of information on these post-harvest practices is comparatively lower among both ICT users and non-users. Nonetheless, it is evident from the findings that the users of ICT based information are getting better quality information and are hence making significantly better decisions on all aspects of livestock farming. This implies that there is a huge potential to increase the quality of information delivery by adopting modern technologies.

Factors affecting ICT adoption

Several studies have analyzed the factors affecting the adoption of modern technologies and practices in agriculture sector including animal husbandry (Agwu and Anyanwu 1996, Ramirez and Shultz 2000, Doss and Morris 2001, Rahelizatova and Gillespie 2004; Park and Lohr 2005, Alvarez and Nuthall 2006), where the producers’ characteristics such as age, education, social category and income, and farm characteristics such as size of landholdings, number of crops grown and purpose of agriculture & livestock were investigated as important factors that affect the information adoption in agricultural decisions. In the present study, the relationship between frequency of ICT based information used in livestock decision-making and socio-demographic profiles of livestock farmers is analyzed using Spearman Rank Correlations.       


Table 4. Spearman's rho Correlations Matrix between use of ICT and socio-demographic factors

Variables

Number of times ICT used

Age,Years)

Education level

Social Category

Income level

Operational land-holdings

Number of Crops

Farming & livestock as business

Membership in Farmers' Organization

Number of times ICT used

1.00

 

 

 

 

 

 

 

 

Age,Years

0.04

1.00

 

 

 

 

 

 

 

Education level,High School & above = 1, otherwise=0

0.21**

-0.13**

1.00

 

 

 

 

 

 

Social Category,General =1, otherwise=0

0.12*

-0.012

0.19**

1.00

 

 

 

 

 

Income level, > Rs. 3000 = 1, otherwise=0

0.12*

-0.03

0.20**

0.14**

1.00

 

 

 

 

Operational landholdings, ha

0.16**

-0.04

0.29**

0.16**

0.24**

1.00

 

 

 

Number of Crops

0.23**

-0.05

0.33**

0.17**

0.17**

0.34**

1.00

 

 

Farming and livestock as business, Yes=1, No=0

0.14**

0.015

0.020

0.046

-0.031

0.24**

0.077

1.00

 

Membership in Farmers' Organization, Yes=1, No=0

0.07

-0.015

0.18***

-0.019

0.17**

0.091*

0.25**

-0.059

1.00

SHG Membership, Yes=1, No=0

0.018

0.03

0.004

-0.049

-0.008

0.020

0.15**

0.014

0.31**

** Correlation is significant at the 0.01 level, * Correlation is significant at the 0.05 level



The results of rank correlation analysis are presented in Table 4, which clearly indicate that use of ICT based information is positively and significantly related with the operational landholdings (p<0.01), education (p>0.01), social category (p>0.05), income level (p>0.05), number of crop grown (p>0.01) and considering farming and livestock as business (p>0.01). This implies that education, social category and income of the farmers are important socio-demographic factors affecting the adoption of ICT based information system. Similarly, farmers with larger landholdings, cultivating more number of crops in a year and considering farming and livestock as business venture are more likely to use ICT based information for livestock decision-making.

Conclusion and Implications

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Received 14 January 2011; Accepted 19 February 2011; Published 6 March 2011

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[1] e-Choupals are information technology based knowledge dissemination centres named after Hindi word Choupal means traditional village gathering place, where farmers gather in group, mostly in the evening, to discuss the village level issues. e-Choupal model was first introduced by the International Business Division (IBD) of Indian Tobacco Company (ITC) in the year 1999–2000, covers about 4 millions farmers in 40,000 villages across 10 states of the country through 6,500 installed e-Choupals. Sodic e-Choupal is recent initiative of Uttar Pradesh Bhoomi Sudhar Nigam - a public sector undertaking of the Government of Uttar Pradesh started in the year 2005 in 15 districts of the state.