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Library Philosophy and Practice 2012

ISSN 1522-0222

Information on Maize Production among Rural Youth: A Solution for Sustainable Food Security In Nigeria

O.A. Olaniyi
J.G. Adewale

Department of Agricultural Extension and Rural Development
Ladoke Akintola University of Technology
P.M. B 4000, Ogbomoso, Oyo State, Nigeria

Introduction

Maize (Zea mays) is a member of the grass family (gramineae). It originated from South and Central America. It was introduced to West Africa by the Portuguese in the 10th century. Maize is one of the important grains in Nigeria, not only on the basis of the number of farmers that engaged in its cultivation, but also in its economic value. Maize is a major important cereal crop being cultivated in the rainforest and the derived savannah zones of Nigeria. Maize has been in the diet of Nigerians for centuries. It started as a subsistence crop and has gradually become more important crop. Maize has now risen to a commercial crop on which many agro-based industries depend on as raw materials (Iken and Amusa, 2004). Maize is highly yielding, easy to process, readily digested and cost less than other cereals. It is also a versatile crop, allowing it to grow across a range of agro ecological zones (IITA, 2001). It is an important source of carbohydrate and if eaten in the immature state, provides useful quantities of Vitamin A and C. Maize thrives best in a warm climate and is now grown in most of the countries that have suitable climatic conditions.

Rural youth are actively involved in agricultural production in Nigeria but the socioeconomic conditions have constrained them and they lack access to scientific and technological information that could enhance their production capacity. Generally, the adult farmers have more access to agricultural extension services than young able bodied farmers in the rural areas in Nigeria (CTA, 1995). Rural youth are the future farmers who are to carry on farming as a profession for sustainable food production in the nation. Arokoyo and Auta (1992) posited that it is only the energetic, creative, innovative, productive and committed workforce that can bring expected development in agriculture. This group of people is the youth. The word Youth is mostly used to refer to a person who is neither an adult nor a child, but, somewhere in between. Therefore, for meaningful sustainable agricultural and rural development in Nigeria depends not only on the mobilization of large number of youth as active participants in the developmental process, but also on how accessible and well utilised the agricultural information are made available to this important target group. Aina et al, (1995) asserted that information has a vital role to play in improving and sustaining agricultural production of any nation. According to Fawole (2008) information dissemination to farmers in the rural areas is an integral part of the clamor for adoption of innovations and agricultural development. The effectiveness of sources and frequency of agricultural information availability then become of paramount importance; if any meaningful development is to be achieved.

One of the pre- requisites for information use is its accessibility. Information may be physically accessible but may not be intellectually accessible (Opara, 2010). Neelemaghan (1981) posited that illiteracy and poverty are important factors militating against information use. Mere provision of agricultural information to farmers does not guarantee its use. This is because a host of social, economic and psychological factors influence the rate of agricultural information use (Akande, 1999).

Recent literature search on utilization of agricultural information, most of the empirical studies on the subject matter has not focused its attention on the important segment of the rural population (youth) in relation to utilisation of agricultural information. Hence, the need to examine the utilisation of agricultural information among rural youth becomes very imperative for effective policy formulation on agricultural development programmes in Nigeria especially for youth.

Specifically, the study identified the personal characteristics of the respondents; ascertained the sources of information available for rural youth; and categorised the respondents based on the level of use of agricultural information on maize production in the study area.

Hypotheses

  1. There is no significant relationship between selected personal characteristics of the respondents and level of utilization of information on maize production.
  2. There is no significant difference in the level of utilisation of agricultural information on maize production across the selected local government areas of southwest Nigeria.

Materials and Methods

The study was carried out in selected states of Southwest Nigeria. This lies between latitude 50N and 90N of the Equator and longitudes 2.50 and 60 East of the Greenwich Meridian. It is bounded by the Atlantic Ocean in the South, Kwara and Kogi states in the North, Anambra state in the Eastern Nigeria and Republic of Benin in the West. The study area has a land area of about 114,271km2 representing about 12 percent of the country's total land area. The zone comprised of six states viz: Lagos, Ogun, Osun, Oyo, Ondo and Ekiti States. The climate in southwestern Nigeria is predominantly humid with rainfall from 1500mm to 3000mm per annum .The mean monthly temperature ranges from 180C to 240C during the raining season and 200C to 350C during the dry season (Sahib et al, 1997).

Multistage sampling technique was adopted in the selection of the respondents for the study. Firstly, a purposive selection of two states from the constituents states of Southwest Nigeria. In this case, Oyo and Osun states were selected based on the fact that they are major producers of maize in the zone. Secondly, fifteen percent of the total ( 33 and 30) local government areas in each state was randomly selected, making five local government areas from each state respectively, making ten local government areas altogether. The third stage, from the village lists provided by the two states Agricultural Development programmes (ADPs), five percent of the total villages in the selected local government areas from the selected states were randomly selected. The last stage, at the village levels the researcher and six other trained enumerators developed sample frame for rural youth according to age criteria 18- 35 years (NYP, 2001) in the two selected states. This involved the determining the total number of rural youth in each village. A total population of nine hundred and nine rural youth formed the sample frame and fifty percent of the total was randomly selected. A total sample of two hundred and forty and two hundred and fifteen rural youth were selected from both Oyo and Osun respectively making a total of four hundred and fifty- five respondents. Structured interview schedule was used to elicit information from the respondents. Data analysis was carried out using frequency counts, percentages, mean and standard deviation as descriptive statistics while Pearson Product Moment Correlation (PPMC), Chi square and ANOVA were employed as inferential statistical tools.

Measurement of Variables

The dependent variable is the rural youth's utilisation of agricultural information on maize production. The respondents were asked to indicate the number of times the respondents' use the information on maize production in the past five planting seasons. The total score of the respondents for the number of items indicated were expressed with the maximum score obtained being 124 points while the minimum score is 0 points. Z score was used to make comparison of the utilization scores obtained and convert the score into standard score with the formula below:

where Z = Z scores, X = raw utilization scores, = Mean Scores and S = Standard deviation. Categorization of young maize crop farmers was made on the basis of level of utilization of agricultural information using the scores which gave rise to a continuum from high to low users of agricultural information. Farmers' raw scores were transformed into standard Z – scores. It is the Z – scores that qualifies a respondent into any category from their utilization of agricultural information scores.

Results and Discussion

(a) Personal characteristics of the respondents

Age: From Table 1 it was revealed that 58.5% of the sampled rural youth are within the age of 30 to 35 years while more than one-quarter (28.1%) are within the age category of 24 to 29 years and 13.4% of them fell within the age range of 18 to 24 years. The mean age of the respondents was 29.2 years. The result of this finding shows that older youth were more involved in the agricultural activities in the study area. This result follows the assertion of Durston (1996) who had earlier reported that this category of youth is considered to be matured and more productive in economic enterprises.

Years of education: The mean year of formal education of the respondents was 8.3 years. The results shows that majority (87.5%) of the respondents are literate who had between 1 and 18 years of formal education and the remaining (12.5%) of them had no formal education as shown in Table 1. The implication of this finding is that there is high level of literacy among rural youth in the study area. High level of literacy among rural youth in the study area would immensely contribute to their innovativeness and adoption of various farm technologies as well as influence the use of agricultural information.

Farming experience: About 57.0% of the sampled rural youth had between more than 11 years of farming experience, 32.1% had between 6 and 10 years, and 11.2% of the respondents had between 1 and 5 years of farming experience. The mean farming experience was 12.2 years. This implies that the respondents have acquired much experience in farming enterprise.

Farm Size: Majority (71.0%) of the respondents cultivated land areas of a size between less than1 and 2.99 hectares, 17.4% had farm size between 3 and 4.99 hectares while 11.6% of them had farm size of 5 and 6.99 hectares and 7 hectares and above respectively. The average cultivated land was 2.1 hectares. The implication of this finding is that majority of the respondents are small scale farmers which is a characteristic of an African farmer.

Household Size: Close to half (49.9%) of the rural youth surveyed had between 4 and 6 members. About 40% had between 1 and 3 members while 8.4% had between 7 and 9 members and (1.3%) had between 10 and above members. The mean household size was 4. The result of this finding indicates that there is relatively small household size among the respondents in the study area. This had implication on level of dependants and hence the level of poverty in the household since the larger the household size the higher the number of mouths to be feed and vice versa. On the other hand it has positive implication on family labour availability for farming enterprises.

Membership of social organization: The result of the analysis reported in Table 1 further revealed that majority (52.5%) of the rural youth surveyed claimed that they belong to social organization their within community while (47.5%) were not members of any social organization. This implies that majority of the respondents did have social affiliations within their communities. Membership of social organization however, tend to favour rural youth level of participation in community life in the rural area. This therefore has implication for both governmental and Non- governmental agencies in reaching out to rural youth in terms of aids and financial assistance for increased agricultural production.

Contact with Extension Agents: The finding of this study revealed that majority (63.1%) of the respondents indicated that they have contact with extension agents while others (36.9%) did not have contact. This implied that majority of the young farmers were reached with adequate information from the extension agents. Contact with extension agent may probably increase the knowledge of young farmers on farm technologies. This is in line with Ogunwale (2005) assertion that contact with extension agents under T and V system brings about remarkable increase in knowledge of farmers about farm technologies and practices.

Table 1: Distribution of Respondents according to personal Characteristics

Age (Years)

Frequency

Percentage

18- 23

61

13.4

24- 29

128

28.1

30- 35

266

58.5

Educational level

Frequency

Percentage

0

56

12.5

1 – 6

140

30.8

7 – 9

71

15.6

10 – 12

102

22.4

13 and above

86

18.9

X = 8.25yrs

   

Farming Experience

Frequency

Percentage

1- 5

51

11.2

6 – 10

146

32.1

11 and above

258

56.7

X = 12. 2 yrs

   

Farm size (ha)

Frequency

Percentage

< 1

51

11.2

1 – 2.99

272

59.8

3.0 – 4.99

79

17.4

5.0 – 6.99

42

9.2

7 and above

11

2.4

X = 2.12(ha)

   

Household size

Frequency

Percentage

1- 3

184

40.4

4 -6

227

49.9

7 – 9

38

8.4

10 and above

06

1.3

X = 4.00

   

Membership of social organisation

Frequency

Percentage

Yes

239

52.5

No

216

47.5

Contact with Extension agent

Frequency

Percentage

Yes

287

63.1

No

168

36.9

Source: Field survey, 2010

Cosmopolitanness: Data presented in Table 2 shows the frequency of contact of respondents with other places apart from their immediate environment. It was revealed that close to half (45.3%) of the respondents made contact with other states annually, while more than one – third (36.5%) made contact with other local government area in the state annually and 27.0% made contact with other local government area within the state fortnightly. About 42.0% of the respondents made contact with other communities outside their local government areas fortnightly, while about one – quarter (25.9%) had contact with other communities outside their local government area on weekly basis and few (8.1%) had contact with other communities outside their local government area daily and annually respectively.

The finding shows that the respondents do frequently have external orientations apart from their immediate environment. As a matter of fact it could have various implications on rural youth staying back in the rural areas and encourage rural – urban migration.

Table 2: Distribution of respondents by Frequency of contact with outside communities (Cosmopoliteness)

Cosmopoliteness

Daily

F (%)

Weekly

F (%)

Fortnightly

F (%)

Monthly

F (%)

Annually

F (%)

Total

Other states

36 (7.9)

42(9.2)

122(26.8)

49(10.8)

206(45.3)

455(100.0)

Other local Government Area in the State

20(4.4)

75(16.5)

123(27.0)

71(15.6)

166(36.5)

455(100.0)

Other local Community outside the Local Government Area

36(7.9)

118(25.9)

189(41.5)

111(24.4)

1(0.2)

455(100.0)

Other community within the Local Government Are

38(8.4)

158(34.7)

191(42.0)

68(14.9)

0(0.0)

455(100.0)

Major Towns within the Local Government Area

45(9.9)

221(48.6)

152(33.4)

37(8.1)

0(0.0)

455(100.0)

Neigbouring Communities

204(44.8)

144(31.6)

97(21.3)

10(2.2)

0.(0.0)

455(100.0)

Source: Field Survey, 2010.

(b) Availability of sources of agricultural information

Table 3 shows that majority (99.1%) the respondents accessed agricultural information from radio, followed by fellow young farmers (89.0%); extension agent (80.4%); commercial input dealers (71.6%); cooperative societies (77.8%); parent (70.5%); mobile phone (GSM) (60.7%); newspapers (61.5%); town crying (50.5%); friends/ neighbour (61.3%) and agricultural shows (51.0%). Others sources of information include: Television (46.2%); role play (30.1%) and internet (29.0%) and folk music (24.0%). The result of this finding shows that the respondents accessed agricultural information through electronic media, interpersonal and modern information technology as well as indigenous media in the study area in order to satisfy their agricultural information needs.

Table 3: Distribution of respondents according to availability of sources of information

Sources of information

Available

Frequency (%)

Radio

451 (99.1)

Television

210 (46.2)

Newspaper

280 (61.5)

Extension agent

366 (80.4)

Parent

321 (70.5)

Fellow young farmer

405 (89.0)

Commercial input dealer

326 (71.6)

Internet

132 (29.0)

Mobile phone

276 (60.7)

Folk music

109 (24.0)

Role play

137 (30.1)

Town crying

230 (50.5)

Friends / Neighbour

279 (61.3)

Agric. Show

232 (51.0)

Cooperative society

354 (77.8)

Source: Field survey, 2010 * parenthesis indicates percentage

(c) Utilisation of agricultural information on maize production

This result of data analysis reported in Table 4 reveals that the sampled rural youth most often use agricultural information on improved maize varieties (WMS= 3.42); selection and rate of chemical application for weed control (WMS = 3.30); and method of fertilizer application (WMS = 2.50). These were ranked first, second and third respectively. Other agricultural information used by the respondents include: Treated maize seed for planting (WMS = 3.24); improved method of controlling pests and diseases of maize (WMS = 3.05); Availability of input on maize at subsidize rate (WMS = 3. 04); Use of tractor for harrowing (WMS = 3.00); Use of tractor for ploughing (WMS = 2.99); use of tractor for ridging (WMS = 2.98); use of tractor for land clearing (WMS = 2.91); Improved spacing for planting maize (WMS = 2.84); mechanized method of harvesting maize (WMS = 2.80); marketing of maize through cooperatives (WMS = 2.57); Prevailing maize crop price in the market (WMS = 2.56); Market outlet for harvested maize (WMS = 2.56); Soil management practices (WMS = 2.53); Storage of maize in modern cribs/ silos (WMS = 2.52); Information on loan interest rate (WMS = 2.45). Loan acquisition / credit facilities (WMS = 2.44); Soil fertility testing (WMS = 2. 24); Weather information on maize planting (WMS = 2.02); Environmental protection (WMS = 1.97); Mechanized method of shelling maize grains /cob (WMS = 1.78); Better record keeping on sales of maize (WMS = 1.65); Government policies on land acquisition (WMS = 1.51); and payment of compensation for crop grown on government acquired land (WMS = 1.51). The agricultural information least used by the respondents are majorly legal and economic information on maize production. The pattern of utilisation of agricultural information could be linked to the availability of agricultural information on maize production in the study area.

Table 4: Distribution of Respondents according to Utilisation of agricultural information on maize production

Agricultural information on maize

WMS

SD

Rank

Improved maize varieties

3.42

1.82

1st

Selection and rate of chemical application for weed control

3.30

1.97

2nd

Method of fertilizer application e.g. foliar, ring, broadcasting and type of fertilizer

3.25

1.96

3rd

Treated maize seeds for planting

3.24

1.98

4th

Improved method of preventing pests and diseases of maize

3.05

2.06

5th

Improved method Controlling of pests and diseases of maize

3.04

2.10

6th

Use of tractor for harrowing

3.00

1.99

7th

Use of tractor for ploughing

2.99

2.06

8th

Use of tractor for ridging

2.98

2.02

9th

Use of tractor for land clearing

2.91

2.19

10th

Availability of input on maize at subsidized rate

2.84

2.15

11th

Improved plant spacing for maize

2.80

2.09

12th

Loan acquisition / credit facilities

2.57

2.72

13th

Mechanized method of shelling of maize grains/cobs

2.56

2.23

14th

Storage of maize in modern cribs / silo

2.56

2.24

14th

Soil management practices

2.53

2.25

15th

Mechanized method of harvesting maize

2.52

2.10

16th

Market outlet for harvested Maize

2.45

2.23

17th

Prevailing maize crop prices in the market

2.44

2.16

18th

Soil fertility testing

2.24

1.90

19th

Weather forecast information on maize planting

2.02

1.17

20th

Information on loan interest rate

1.97

1.78

21st

Better record keeping on sales of maize produced

1.78

1.66

22nd

Payment of compensation for crop grown on government acquired land

1.65

1.52

23rd

Marketing of maize produce through cooperatives

1.51

1.51

24th

Environmental protection on land

1.51

1.44

24th

Government policies on land acquisition

1.36

1.35

25th

Source: Field survey, 2010 WMS- Weighted Mean score, SD- Standard Deviation

(d) Categorisation of respondents based on level of utilization of agricultural information

From Table 5, it was revealed that 42.4% of the respondents were classified as high users of agricultural information on maize production while 36.0 percent were of low category and about 22.0 percent were moderate users of agricultural information on maize production with the Z – score ranged from -1.52 to 1.25. Generally, a high proportion of the sampled rural youth fell into moderate and high users' categories of agricultural information on maize production in the study area. The finding of the study is similar to that of Fakoya et al., (2002) that a high percentage of farmers were categorised as medium to high level of sustainable land management practices in southwest Nigeria.

Table 5: Categorization of respondents according to level of utilization of agricultural information in maize production

Z – score

Category of information users

Frequency

Percentage

-1.52 to -0.60

-0.61 to 0.25

0.26 to 1.25

Low

Moderate

High

162

97

191

36.0

21.6

42.4

Source: Field survey, 2010

Test of Hypotheses

Hypothesis 1: There is no significant relationship between personal characteristics of rural youth and level of utilization of agricultural information.

Table 6 shows that positive and significant relationship exists between age (r = 0.322, P < 0.05), household size (r = 0.156, P <0.05) and level of utilization of agricultural information. This implies that the more the respondent advances in age, the higher the level of utilization of agricultural information. Also the larger the household size of the respondents, the higher the level of utilization of agricultural information. Conversely, there exists negative and significant relationship between farm size (r = -0.177, P<0.05); cosmopoliteness (r = -0.476, P < 0.05) and level of utilization of agricultural information. This indicates an inverse relationship among the variables hence, the smaller the farm size, the higher the level of utilization of agricultural information. This implies that utilisation of agricultural information acquired by the respondents does not necessarily lead to increase in farm size. This may probably be due to some inherent constraints to utilization of agricultural information. Also, the more the respondents have external orientation about their immediate environment, the lower the level of utilization of agricultural information. This implies that external orientation of rural youth is not in favour of utilization of agricultural information. This could have implication on the rural youth staying back in the rural areas and sustainable food security in the study area.

Finally, it was revealed from the same Table 6 that there is no significant relationship between farming experience, years of formal education and level of utilization of agricultural information.

Table 6: Summary of correlation analysis establishing relationship between personal characteristics of rural youth and level of utilisation of agricultural information on maize production

Variable

r

P – value

Remark

Age

Years of Education

Farming experience

Household size

Farm size

Cosmos politeness

0.322**

-0.012

0.080

0.156**

-0.177**

-0.476**

0.000

0.796

0.089

0.001

0.000

0.000

Significant

Not Significant

Not significant

Significant

Significant

Significant

Source: Field survey, 2010 ** Correlation is significant at the 0.01 level (2 tailed)

The result of Chi square analysis reported in Table 7 revealed that membership of social organization (X2 = 5.235, P< 0.05), extension contact (X2 = 13.739, P <0.05) significantly influenced the level of utilisation of agricultural information on maize production. Membership of social organization and extension contact has weak contingency coefficient values of 10.8% and 17.1% respectively.

Table 7: Summary of Chi – square test establishing relationship between personal of rural youth and utilisation of agricultural information on maize production

Variable

X2 value

Cc

df

P – value

Remark

Membership of social organization

5.235

0.108

1

0.021

Significant

Extension contact

13.739

0.171

1

0.000

Significant

Source: Field survey, 2010 cc- contingency coefficient, df- degree of freedom

Hypothesis 2: There is no significant difference in the level of utilisation of agricultural information on maize production across the selected local government areas of southwest Nigeria.

The result Analysis of variance (ANOVA) in Table 8 shows that significant differences exists in the level of utilisation of agricultural information across the selected local government Areas in the study area (F = 46.14, P<0.05). Hence the null hypothesis is rejected.

Table 8: Summary of Analysis of Variance (ANOVA) showing differences in level of utilisation of agricultural information on maize production across selected local government areas.

Variable

Source of Variation

Sum of Squares

Degree of freedom

Mean Square

F value

P value

Remark

Utilisation of agricultural Information

Between Local government areas

Within Local government areas

Total

19726.511

211389.278

23115.789

9

445

455

2191.835

47.504

46.10

0.000

Significant

Source: Field Survey, 2010

Conclusion and Recommendations

The result presented here shows that rural youth utilised agricultural information moderately especially those of technical information category. However, the respondents utilised less of information on economic and legal issues. This may probably be attributed to the availability of agricultural information on maize production through the identified sources of information. For sustainable food security in Nigeria, rural youth should be targeted with relevant and timely agricultural information in order to boost their maize production capacity. However, there is need for the Nigerian government to intensify her efforts on rural development programmes in order to reduce the menace of rural urban migration among rural youth in Nigeria. Dissemination of agricultural information on economic and legal issues should be highly promoted by the extension institutions in order to enhance high level of utilisation of these categories of agricultural information by the respondents. Also, provision of information resource centres in the rural areas is of paramount importance in order to facilitate easy access to agricultural information among rural youth in the study area.

Acknowledgement

This research was funded through Academic Staff union of Universities (ASUU) Doctoral Research Grant (2010) Nigeria.

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