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Assessment of mobile advisory services for improving agricultural livelihood of farmers

in tribal dominated district of Western Madhya Pradesh.

A.K. Badaya, G.S. Gathiye, K.S. Kirad, S. S. Chauhan, J.S. Rajpoot and Swati barche*

Krishi Vigyan Kendra (RVSKVV, Gwalior), Dhar 454001 (M.P.)

*Associate Professor (Horticulture), RVSKVV, College of Agriculture, Indore

Corresponding Author’s Email: badaya_ashok@rediffmail.com

ABSTRACT

Mobile phone based ICT’s helps to reduce the risks and uncertainties, emerging

challenges in agriculture and provides instant solutions, timely market information and

improve livelihood and also helps to overcome information asymmetry existing among the

group of farmers. In this context, Krishi Vigyan Kendra, Dhar started timely and need based

systematic bulk text message as Kisan Mobile Advisory (KMA) during the year 2011-12 to

2015-16 and registered 26500 mobile holder farmers for sending information in hindi

language through short messages (SMS) twice a week on agriculture and allied aspects in

their Mobile phones. The impact of technology dissemination of four year’s study was

conducted during April to May, 2016. For this purpose enterprise wise 1000 beneficiaries and

non- beneficiaries were randomly selected and interviewed personally through questionnaire

developed based on objective of the study.The outcome of the study revealed that messages

delivered in hindi language were highly understandable to majority of users (83.60%), the

expectations of the respondents towards frequencies of messages delivered suggested daily to

twice a week (72%) and majority of farmers (97.10%) conveyed the text message to other

farmers in their social system. It was also observed that socio-economic profile of the farmers

also play an important role in adoption and usefulness of technology dissemination. The

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analysis showed that majority of medium category farmers (70.67%) having higher level of

education found the need based information delivered was most useful followed by large

farmers (60.32%). The farming community engaged in enterprise such as Agriculture +

Horticulture + Dairy found usefulness of information (88.43) followed by Agriculture +

Dairy and Horticulture + Dairy. Results of study also showed the majority of respondent

adopted the information regarding plant protection measures, seed and its availability, Govt.

schemes, weather forecasts and farm mechanization and got monitory benefits for their

livelihood security. In the same way the knowledge level of information of KMA registered

farmers was higher than the non-registered. The overall high impact of of messages through

KMA services was reported by 71.70 % farmers during the study. The use of mobile phones

has helped in increasing farm income of farming community who are involved in enterprises

of Agriculture +Horticulture +Dairy (45.71 %) followed by Horticulture +Dairy (40.0%) and

Agriculture +Dairy (33.33 %). This paper also reflects the attitude of KMA users in reducing

the cost of cultivation and enhancing productivity of crops by indirect way.

KEYWORDS: Information and communication technology (ICT), Kisan mobile advisory,

Enterprise, Farming community, Livelihood

INTRODUCTION

The agriculture information is vast, interdisciplinary and specific to different agro

climatic zones and needs a proper information dissemination system for its effective use. In

present day agriculture, soft resources like knowledge and skills are as important as hard

resources like inputs, and sometimes more important. But estimates indicate that 60 per cent

of farmers do not access any source of information for advanced agricultural technologies

resulting in huge adoption gap. The requirement of field level extension personnel is

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estimated to be about 1.3 -1.5 million against the present availability of about 0.1 million

personnel (Saravanan and Bhattacharjee, 2014).

In the 21st century in the era, cost effective and efficient communication technologies

are required to take lead in changing agricultural scenario (Sandhu et al, 2012). The concept

of utilizing mobile phones to bridge information and knowledge gaps among farmers and

rural service providers is based on two assumptions. The first is the near ubiquity of access

and use of mobile phones. The second is that farmers (especially in developing economies)

have specific information and knowledge needs that are currently only met partially, if at all.

According to Islam and Gronlund (2011) digital ICTs are playing a major role in

sustainable agricultural development by bridging the gap between farmers and experts in

agricultural innovation systems since early decades and now the modern ICTs as smart

phones and computers have created a revolution in the developing countries.

The dearth of traditional extension workers and the diverse challenges of agricultural

production force governments in many countries to look favourably at communication

channels, such as mobile phone technology, to provide advisory services to farm

communities and other factors involved in agriculture (Jayade and Khot, 2014).

Keeping the importance of KMA an attempt has been made to analyze the reaction of

the farmers towards Kisan Mobile Advisory (KMA) service as a source of reliable and timely

information about best production practices, input utilization and risk-covering informations.

MATERIALS AND METHODS

Krishi Vigyan Kendra, Dhar started systematic bulk text message service for sending

information through short message service (SMS) for advisory to input dealers, extension

workers by 1000 registered farmers since 2011-12 and 26 thousand farmers of the district

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were added till April, 2013 to solve the problems related to agriculture and horticulture crops,

livestock management, weather, marketing, awareness and other enterprise on their registered

cell phone. The list of farmers was collected from M.P. State Civil Supplies Corporation,

Dhar, which is the main agency for food grains procurement and the public distribution

system in Madhya Pradesh. The tribal district consists thirteen blocks covering 1579 villages

out of them, farmers of 850 villages which are well network connected were selected for

KMA.

In general, two short messages per week have been delivered in Hindi language as per

need, season and cropping system of the district. In this way during 2012-13 one hundred

three, 2013-14 one hundred eight, 2014-15 one hundred five and during 2015-16 one hundred

thirteen messages delivered to the farmers. The feedback of four year’s study from 2012-13

to 2015-16 were conducted during April to May, 2016. For this purpose enterprise wise 1000

users were selected from the beneficiaries. Responses were gathered through questionnaire

developed based on objective of the study and the data were collected by personnel interview

with all the respondents regarding the impact of advisory service and their satisfaction.

Keeping in view the objectives of the study, stratified statistical tools such as frequency,

mean and percentage were employed to analyse the data. To assess the overall impact of

technology a device developed and suggested by Parganiha, et al, (2012) for recording the

responses of the respondents on a four point continuum scale for each aspects and assigned a

scores like; a) Need and time based information (Needful & timely-3, Needful & not timely-

2, Not needful & timely-1, Not needful & not timely-0) b) Understanding of the message

(Highly-3, Medium-2, Low-1, Not-0), and c) Applicability of message (Fully-3, Medium-2,

Partially -1, Not-0). Finally an index was worked out to assess the overall impact of

technology with the help of following equations.

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TI = O/S × 100, Where, TI = Technology impact index of a respondents, O = Total scores

obtained by respondents, S = Total obtainable score

RESULTS AND DISCUSSION

Feedback and Impact of KMA on transfer of agricultural technology was documented and

being discussed as under.

1. Realization on content of text message: The results of Table 1 revealed that the text

messages delivered for advisory were highly understandable to majority (83.60%) of the

user farmers while it was medium understandable for 13.70 per cent farmers and less than

one per cent farmers reported that message was not understandable to them because of

some of the tribal farmers are only literate and some of the text content was not

understandable to them.

2. Expectations of users about frequency of the advisories: The expected frequency of the

messages delivered was also measured. The result (Table 2) indicated that majority of user

farmers (72 %) were expected to deliver the advisory daily and twice in a week, followed

by 14.80 per cent advised to sand message whenever needed, while only 8.20 per cent

farmers required once in a week and 7.60 per cent suggested once in a fortnight. Thus, it

can be said that favourable expectation was observed among the farmers to get technical

advisory. Chauhan (2010) also studied and reported that most of the respondents expected

to deliver advisory twice a week in Anand district of Gujrat.

Table 1. Distribution of the respondents according understanding to the content of

mobile text message

Category Farmers n=1000

No. percentage

Highly understandable 836 83.60

Medium understandable 137 13.70

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Understandable Low 21 2.10

Not understandable 06 0.60

Table 2. Frequency of respondents expected to use KMA (N=1000)

S. No Frequency to deliver KMA No. %

1 Daily 486 48.60

2 Twice in a week 234 23.40

3 Once in a week 82 8.20

4 Once on fortnight 36 3.60

5 Once in month 14 1.40

6 Whenever needed 148 14.80

Total 1000 100.00

3. Advisories conveyed to other farmers: It is evident from Table 3 that majority of user

farmers (66.70%) were conveyed the text message minimum to one another farmer in their

social system, while 23.60 per cent conveyed to more than 5 farmers and only about 3 per

cent would not convey the information to others. It could be concluded that advisory user

farmers disseminate the technological information to other farmers and try to solve their

problems through mouth publicity.

4. Usefulness of Information based on socio-economic profile of respondents: As we

know any technology which has its usefulness would be adopted by farmers quickly, also

its horizontal spread among the farmers is faster. Therefore, usefulness of the SMS was also

studies on three-point continuum i.e. Very useful, Not so useful and not useful. Thirty-

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seven per cent of the user farmers who were registered for mobile phone advisory service

were from medium category. Majority of medium category farmers (70.67%) reported the

information as useful followed by large farmers (60.32%). About forty-eight per cent small

and marginal farmers also found the information as useful. While 22.22 per cent small and

marginal farmers stated the information is not useful as it was oriented towards main crops

and information was missing on some other income generation activities such as goatry,

backyard poultry adopted by them and some of them also engaged as labourers for

livelihood security. As expected respondents with high level of education (81.53%) and

medium level of education (79.76%), reported the information via text message through

mobile phone as useful. The user farmers having with very low level of education

(21.61%), medium level of education (7.54%) and low level of education (4.06%) reported

the information as not useful (Table 4). Higher percentage of users (92.02%) in the middle

age category found mobile phone advisory useful as compared to old age category

(91.98%) and other young (82.0%) users. This may be due to the lack of interest of some

young farmers in agriculture and less education level. Sandhu et al, (2012) also reported

that more than 60% respondents of south western Punjab informed text messages are very

useful but its impact is depend on socio-economic profile of the community.

In the same way, more than 42 per cent users engaged in enterprise such as

Agriculture + Horticulture + Dairy reported usefulness of information and found higher

percentage (88.43) followed by Agriculture + Dairy (85.68%) and Horticulture + Dairy

(75.36%).Thus, it is clear from the data that the resource poor and socio-economic condition

of the household play an important role in adoption of useful technologies.

5. Adoption of various kind of information: Efforts were also made to assess the adoption

level, annual household income of users and equal representation of non-user farmers

regarding ten type of advisory/ information delivered and compared. For the purpose, non-

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user enterprise wise farmers randomly selected from the different villages at the time of

study .The gathered data were processed, tabulated, classified and analysed. The adoption

of the users was measured in terms of mean percent scores (MPS) and their ranking. Ten and

more than 10 per cent difference between users and non- user farmers were considered as

significant difference. Table 5 also depicted that the user farmers adopted maximum

information related to plant protection measures with MPS 97.67 followed by seed and its

availability, Govt. schemes, weather forecasts, farm mechanization with MPS 91.02, 86.92,

86.50 and 84.65, respectively. The study further indicates that other information delivered

on fertilizer management, tillage and soil conservation operations, market management,

vegetables, fruit and flower cultivation & livestock management also shows high level of

adoption by the user farmers and the MPS ranged from 73.60 to 83.73. The findings

corroborated with those of Kanavi and Jahagirdar (2016) who reported that KMA services

related to plant protection perceived as most useful by the 70.83% farmers of Dharwad

district of Karnataka.

The extent of adoption of the same ten type of information by non- user farmers were

also interviewed. Further, the data of Table 5 revealed that they had knowledge of

information on seed and its availability to the highest extent with MPS 87.34 followed by

tillage and soil conservation operations (MPS 82.03) and farm mechanization (MPS 81.63).

The study also indicated that the knowledge of information and their adoption on

fertilizer management, plant protection, vegetables, fruit and flower cultivation and livestock

management were found to be least by non- user farmers with 60.05, 65.93, 67.34 and 69.86

MPS, respectively. The data also revealed that the difference in the knowledge of information

and their adoption level between users and non- user farmers ranged from MPS 2.29 to 31.73.

The highest and significant difference between both the categories of farmers was observed

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in plant protection with MPS 31.73 followed by fertilizer management and vegetables, fruit

and flower cultivation with MPS 23.68 & 11.74, respectively.

The overall difference in extent of knowledge of information and their adoption level

between both the categories of farmers recorded MPS 9.58 which was considered as non-

significant. But the average knowledge level of information of user farmers was higher than

the non-users. This might be due the fact that there were number of other extension

education programmes which are conducting on the principle of "learning by doing" and

"seeing is believing" organised by different government organisations, NGOs in the district

and communication media used by farmers for providing knowledge about various

technology of crop production, awareness and livestock management to them, resulting in

increase of knowledge of various information not only to user but non user farmers also. Das

et al. (2012) reported that the information provided through voice messages on fertilizer,

pesticide and seed were prioritized as first, second and third in Paschim Medinipur district of

West Bengal. Similar findings was also reported by Patra et al, (2016) as time specific

advisory services is more important for kisan mobile service followed by weather forecasting

and market information.

Table 3. Distribution of KMA users according to their frequencies of message

conveyed to other farmers.

S. No. Farmers n=1000

1 Category of conveyed farmers Numbers %

2 0 29 2.90

3 1-5 667 66.70

4 6-10 236 23.60

5 10- above 68 6.80

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Table 4. Relationship between Socio-economic profile with usefulness of Information.

(N = 1000)

S. No. Parameter Socio-

economic

Profile

Usefulness

1 Land holding Useful Not so useful Not useful

a Marginal and

small(1-2 ha)

315 (31.50) 150 (47.62) 95 (30.16) 70 (22.22)

b Medium (2-10 ha) 375 (37.50) 265 (70.67) 62 (16.53) 48 (12.8)

c Large (> 10 ha) 310 (31.0) 187 (60.32) 88 (28.39) 35 (11.29)

2 Education  

a High (Graduation

or above)

352 (35.20) 287 (81.53) 53 (15.06) 12 (3.40)

b Medium ( Higher

secondary)

252 (25.20) 201 (79.76) 32 (12.70) 19 (7.54)

c Low (Middle) 197 (19.70) 177 (89.85) 12 (6.10) 08 (4.06)

d Very low (Primary) 199 (19.90) 87 (43.72) 69 (34.67) 43 (21.61)

3 Age  

a Young (<30 years) 250 (25.0) 205 (82) 37 (14.8) 08 (3.2)

b Middle (Between

30-45 years )

426 (42.60) 392 (92.02) 21 (4.93) 13 (3.05)

c Old (> 45 years) 324 (32.40) 298 (91.98) 17 (5.24) 9 (2.77)

4 Enterprise  

a Agriculture+Dairy 398 (39.80) 341 (85.68) 38 (9.54) 19 (4.77)

b Horticulture+Dairy 138 (13.80) 104 (75.36) 21 (15.22) 13 (9.42)

c Agriculture+Hortic 432 (42.20) 382 (88.43) 32 (7.40) 18 (4.16)

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ulture+Dairy

d Dairy 32 (3.20) 23 (71.88) 6 (18.75) 3 (9.37)

Figures in parenthesis are percentages

Table 5. Extent of adoption level of various kind of information delivered to the users.

S.

No.

Type of information

provided

Max.

score

Users

(n=1000)

Non-users

(n=1000)

Difference

MPS Rank MPS Rank

1 Seed and its availability 10 91.02 II 87.34 I 3.68

2 Fertilizer management 15 83.73 VI 60.05 X 23.68*

3 Plant protection 15 97.67 I 65.93 IX 31.73*

4 Farm mechanization 10 84.65 V 81.63 III 3.02

5Tillage and soil

conservation operations

10 83.10 VII 82.03 II 1.07

6 Market management 10 82.45 VIII 80.16 IV 2.29

7 Govt. Schemes 05 86.92 III 79.92 V 7.00

8Vegetables, fruit and

flower cultivation

05 79.08 IX 67.34 VIII 11.74*

9 Livestock management 10 73.60 X 69.86 VII 3.74

10 Weather forecasts 10 86.50 IV 78.63 VI 7.87

Overall 100 84.87 - 75.29 - 9.58

*Significant difference

Table 6. Distribution of the respondents according to overall impact of KMA.

Category Farmers (N=1000)

No. percentage

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Low (Score up to 1-3) 42 4.20

Medium (Score up to 3.1-6) 241 24.10

High (Score up to 6.1-9) 717 71.70

6. Overall Impact of KMA: Table 6 indicated the overall impact of messages and it was

found that mobile advisory imposes high impact on 71.70 per cent of user of farmers.

Medium impact was reported by 24.10 % and lower impact was recorded 4.20 % of users.

The probable reason might be farmer’s scientific orientation, scientific insight and attitude

in determining the adoption of improved technologies. The results of this study are in the

line of Parganiha, et al, (2012) and Kumar et al, (2014).

Table 7. Impact of KMA on annual income level of household of respondents.

Enterprise Respondents

(%)

Average annual income (in

lakhs) level of mobile phones

users (household)

% increased in

income (lakhs)

2010-11 2015-16

Agriculture+Dairy (39.80) 1.5 2.0 33.33

Horticulture+Dairy (13.80) 2.5 3.10 40.0

Agriculture+Hortic

ulture+Dairy(42.20) 3.5 5.10 45.71

Dairy (3.20) 1.25 1.5 20

The data presented in Table 7 indicated that the income level of various enterprises

was low to medium before the advisory service started to the respondents and it was ranged

from Rs. 1.25 to Rs. 3.50 per household. The data on income showed that the highest income

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(45.71 %) of farmers found in the adoption of the enterprise of Agriculture+Horticulture

+Dairy followed by Horticulture +Dairy (40.0%) and Agriculture +Dairy (33.33 %). While

the lowest, only 20% income increased of the respondents who adopted only dairy because of

less number of messages delivered to them on this aspect by the KVK. It indicates that use of

mobile advisories in agriculture is significantly profitable and increasing the knowledge of

even in the lower income groups.

7. Indirect benefits of KMA: Table 8 showed the attitude of mobile users towards indirect

benefits gained by the statements received during the study. It is clear from the Table that

majority (96.50 %) of KMA users stated that by the frequent and timely delivery of

advisories the cost of pest and disease management is reduced by foreclosing the

indiscriminate use of pesticides. It is noticed that the overall cost of cultivation is reduced by

the 95.0 % users and 92.0% user's belief about the input cost (seed, fertilizer, pesticide, fuel

etc.) reduced and this statement was placed at rank of third. Other important statement

committed by the respondents were productivity enhanced (89.50%), varieties of crops

replaced (81.50%), use of seed treatment and bio-fertilizers increased (80.50%), reducing

information search costs and market efficacies (79.0%), it also helped in crop diversification

through spices, fruits and vegetables (77.50%). Only 66.50 % users viewed about “reducing

transaction cost and makes logistics efficient” which was ranked last. Similarly, in a study

with small holder vegetable growers in Sri Lanka, De Silva and Ratnadiwakara (2010)

concluded that mobile phones can significantly reduce transaction costs and encourage small

holders to participate in commercial agriculture. In the same way Veerarghavan et al, (2009)

indicated that mobile phones have significantly reduced the cost of doing business by a

sugarcane cooperative in the state of Maharastra, India. Mittal and Mehar (2012) conducted

survey during 2011 & concluded that about 34.63% of farmers who experienced an increased

level in yields due to the availability of this information. Of these, the highest yield gains

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were observed by farmers in Punjab (49.2%) and Haryana (42.9%). While in Bihar it was

21.1% of farmers using mobile phones reporting yield gains, 29.4% in Uttar Pradesh and

34.01% of such farmers in West Bengal. Mukherjee (2015) reported that the use of mobile

phones in agriculture improving productivity in West Bengal and Jehan et al, (2014)

observed high correlation between cell phone used and crop productivity in Pakistan.

Table 8: Distribution of advisory users according to indirect benefits (N=1000)

S. No. Statement Frequency %

1 Pest & disease control cost reduced 965 96.50

2 Overall cost of cultivation reduced 950 95.0

3 Input cost reduced 920 92.0

4 Productivity enhanced. 895 89.50

5 Varieties of crops replaced 815 81.50

6 Use of seed treatment & bio-fertilizer increased 805 80.50

7 Reducing information search costs and increasing

market efficiencies.

790 79.0

8 It also helped in crop diversification through spices,

fruits and vegetables growing.

775 77.50

9 Reduces transaction cost and makes logistics efficient 665 66.50

CONCLUSION

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Based on various studies mobile-enabled information services helps for the speedy

dissemination of information to farmers and bridge the gap between the availability and

delivery of agricultural inputs and agriculture infrastructure. It also helps to reduce the risks

and uncertainties, emerging challenges in agriculture and provides timely market information

and improves livelihood of the farmers by increasing farm earnings through higher price

realization and reduction in cost of cultivation. Eventually, it is expected that mobile-based

information services will influence the behavior pattern of farmers and this will facilitate

adoption of improved techniques leading to better yields. It is also indicated by different

research that adoption of mobile phone applications in agricultural has increased the

productivity of various crops.

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