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ABSTRACT

The study was conducted to examine the involvement of rural women in farming activities in Akwa Ibom State, Nigeria.  The specific objectives were to examine the socio-economic characteristics of the respondents; identify the farming activities involved in and the constraints to women involvement in farming activities. Primary data was used for the study. The primary data were obtained with the aid of structured questionnaires administered to 175 rural women who were randomly selected. Frequency and percentage were used to analyze the objectives (1, 2 and 3) while multiple regression was used to test the relationship between the socio-economics characteristics and the involvement of women in farming activities. The result indicated that rural women were more into planting (39.9%), weeding (36.0%) and harvesting (14.9%) than other farming activities in the study area. On the constraints, the rural women identified lack of finance and poor returns (profit) as hinderance to women active involvement in full time farming activities. Also, the result from the regression analysis at 1% and 5% confidence interval revealed that age, marital status, household size and farm size were positively related to influencing rural women active involvement in farming activities. The study therefore recommended that government and non-governmental organization focus more in empowering rural women to access institutional credit and also build their capacity on the use of modern technology in planting, weeding and harvesting.

Keywords: Constraints, Determinants, Farming activities, Involvement, Rural women.

DOI: 10.55284/cjac.v7i2.696

Citation | Obot Akaninyene; Obed Rachael; Obiewke Ngozi (2022). Determinants of Rural Women Involvement in Farming Activities in Akwa Ibom State, Nigeria. Canadian Journal of Agriculture and Crops, 7(2): 98-104.

Copyright: © 2022 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Funding : This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

History : Received: 5 July 2022 / Revised: 17 August 2022 / Accepted: 30 August 2022 / Published: 19 September 2022.

Publisher: Online Science Publishing

Highlights of this paper

  • The research outcomes hight the important role of women in the attainment of the UN zero hunger 2030 in Nigeria and the need for government/stakeholders to support women in the aspect of farming activities of which they are mostly engaged in.

1. INTRODUCTION

Women play an important role in many parts of the world in ensuring that there is the availability of food to meet the global growing population and demand. Without the contribution of women to agriculture, there would been much food crises globally. In Africa including Nigeria, ILO [1] estimated that 78% women were actively involvement in agriculture as compared to 64% of their men counterparts. Ayioko and Igben [2] stated that African women especially in Nigeria played a key role in the production of about 60-80% of agricultural produce. Despite women active participation in the planting of agricultural crops, they also perform heavy work such as land clearing, tilling and ridge making. The Nigeria agricultural sector is still dominated by agrarian and women play a key part in the agricultural activities mostly in the rural communities.

According to Action Aid [3] women constitute about 60-80% of the agricultural labor force and also produce two-third of the total food crops in Nigeria. Institute of Development Studies (IDS) [4] stated that UNHRC in 2010 estimated that female farmers cultivate over 50% of every food grown in several regions of the earth mostly especially in underdeveloped countries. In Akwa Ibom State, women constitute 50.74% of the population.

World Bank Group [5]; Muhammad, et al. [6] stated that participation is the process through which stakeholders influence and share control of the major decision in any setting and this is important in the realization of the expected goals of its members. Therefore, for Nigeria agriculture to achieve the UN 2030 mandate of zero hunger, the recognition and support of women participation in agriculture becomes very important. In most families in the rural part of Nigeria, agriculture is the source of their livelihood and most women are involved in it but still little attention or recognition or support is given to them.

It is against this background that the study analyzed the determinants of rural women involvement in farming activities in Akwa Ibom State, Nigeria.

The specific objectives were to:

1. Describe the socio-economic characteristics of women farmers in the study area.
2. Examine the farming activities of women farmers.
3. Identify the constraints to women participation in farmer activities.
4. Determine the socio-economic characteristics affecting rural women involvement in farming activities.

2. METHODOLOGY

2.1. Study Area

Akwa Ibom State is located in South-South of Nigeria. The State lies between latitude 4°31 and 5°31 North and longitude 7°35 and 8°35 East; occupies a total land area of 7, 254, 935km2 and has an estimated population of 3, 920, 208 [7]. Located at an elevation of 42.58 meters (139.7 feet) above sea level, Akwa Ibom has a Tropical monsoon climate (Classification: Am). The city’s yearly temperature is 28.47ºC (83.25ºF) and it is -0.99% lower than Nigeria’s averages. Akwa Ibom State typically receives about 342.56 millimeters (13.49 inches) of precipitation and has 294.37 rainy days (80.65% of the time) annually.

2.2. Sampling Procedures

A multi-stage sampling technique was used. In stage one, five Local Government Areas (LGAs) in the State was randomly selected. The second stage, one community was selected from each of the LGAs randomly. The third stage, 35 female farming households were selected at random from each of the community which made up to 175 respondents.

2.3. Data Collection and Analysis

Data collection was done with the aid of administered structured questionnaires. Descriptive statistics involving the use of frequency counts and percentages were used to describe the socio‑economic characteristics of the respondents, type of farming activities and the constraints.

Regression (Ordinary Least Square) analysis model was used to determine the socio-economic characteristic affecting rural women involvement in farming activities at 1% and 5% confidence interval. The model was specified as follows:

Y = β0+ β1X1+ β2X2+ β3X3+ β4X4+ β5X5+ β6X6+….+e

β0 = intercept.
β1 – β7 = regression coefficients.

Y (dependent variable) = level of rural women in farming activities.

The independent variables of the model were measured as follows: X1 = age (in years), X2 = Marital Status, X3 = household size (number of people living under the same roof and feeding from the same pot), X4 = farming experience (years), X5 = primary occupation, X6 = level of education (number of years of schooling), X7 = farm size (acres) e = error term.

3. RESULTS AND DISCUSSION

3.1. Distributions According to Socio-Economic Characteristics

3.1.1. Age

The result in Table 1 below showed that majority of the respondents (59.4%) were within the age bracket of 41-50 years, 28.6% were within the age bracket of 31-40 years and 12.0% were within the age bracket of <18-30 years. This result therefore showed that the rural women in the study area were still in their active age and as such were productive. The findings agreed with Enete and Amusa [8]; Adams [9] that the sampled women fell within the age bracket of 21-50 years and therefore were in their economic active age.

3.1.2. Marital Status

The result showed that 83.4% of the respondents were married, 9.7% were single and 6.9% were widowed. This indicated that family labor was expected to be part of the farming activities. This result agreed with Enete and Amusa [8]; Fabiyi, et al. [10]; Adams [9] that the sampled women in their study areas were married.

3.1.3. Household Size

The result indicated that 87.4% had household size of 5-10 persons and 12.6% had household size of <5 persons. The high percentage of household size among the rural women farmers would contribute to the farming activities. This concurred with Adams [9] findings that more than 56% of the respondents had family size of six members and above.

3.1.4. Farming Experiences

The result indicated that 66.9% of the respondents had farming experiences of 21-30 years, 26.3% had 11-20years experiences and 6.8% had 1-10years experiences. The number of years of farming experiences would make the farmers to be more productive. This concurred with Enete and Amusa [8] that the women sampled had a farming experience of above 21 years.

3.1.5. Primary Occupation of Farmers

An assessment of the primary occupation of the respondents indicated that majority 93.7% were engaged in farming as their primary occupation and 6.3% were engaged in other activities outside farming. The result concurred with Adams [9] that majority of the respondents in the study area were highly engaged in agricultural production.

3.1.6. Educational Qualification

Majority of the respondents (61.1%) had formal education and 38.9% had no formal education. The findings showed that the farmers could read and write which made it easy for adoption of innovation and improve farming technique. The result agreed with Enete and Amusa [8]; Adams [9] that most of the sampled women had formal education.

Table 1. Distribution according to socio-economic characteristics.
S/N Variables
Frequency (n=175)
Percentage (100%)
1 Age (Year)
  <18-30
21
12.0
  31-40
50
28.6
  41-50
104
59.4
2 Marital Status
  Single
17
9.7
  Married
146
83.4
  Widowed
12
6.9
3 Household size
  <5 persons
22
12.6
  5-10 persons
153
87.4
4 Years of farming experiences
  1-10 years
117
66.9
  11-20 years
46
26.3
  21-30 years
12
6.8
5 Primary occupation
  Farming
164
93.7
  Others
11
6.3
6 Educational qualification
  No formal education
68
38.9
  Primary
79
45.1
  Secondary
15
8.6
  Tertiary
13
7.4
7 Farmland size (ha)
  <1
166
94.9
  1-2
7
4
  3-4
2
1.1
Source: Field study, 2022.

3.1.7. Farm Size

Majority of the respondents (94.9%) had farm size of <2 ha, 4% had 2-3ha and 1.1% had 4ha and above. This means that the respondents were mostly operating on fragmented farmland as most women were not entitled to land inheritance. The result confirmed Adams [9]; Obot, et al. [11] that majority 85% of the respondents had below two hectares of land and as such were small scale farmers.

3.2. Distribution of Women According to Farming Activities

From the Table 2, majority of the rural women farmers were into planting (38.9%), followed by weeding (36.0%), harvesting (14.9%), bush clearing/burning (7.4%) and tilling (2.9%). This was certain as the men left the planting and weeding aspect of the farming to the women and children.

Table 2. Distribution of women according to farming activities.
S/N Variables
Frequency (n= 175)
Percentage (100)
Ranking
1 Bush clearing/burning
13
7.4
4th
2 Tilling
5
2.9
5th
3 Planting
68
38.9
1st
4 Weeding
63
36.0
2nd
5 Harvesting
26
14.9
3rd
Note: Field study, 2022.

3.3. Constraints to Women Participation in Farming Activities

From the Table 3, majority of the respondents complained of lack of finance (24.6%) as a constraint to their active participation in farming activities, followed by Poor returns (20.0%), 15.4% lack of farming inputs, 11.4% lack of farmland, lack of contact with extension agent (10.9%), Lack of technical knowledge (9.7%) and gender discrimination was 8.0%. The result attested to the fact that access to finance and high returns (profit) played a vital role to the active involvement of rural women in farming activities. The result concurred Adams [9]; Enete and Amusa [8]; Obot, et al. [11] findings that inadequate capital was one of the major constraints to women participation in agricultural activities.

Table 3. Constraints to women involvement in farming activities.
S/N Variables
Frequency (n=175)
Percentage (100)
Ranking
1 Lack of finance
43
24.6
1st
2 Lack of contact with extension agents
19
10.9
5th
3 Lack of technical knowledge
17
9.7
6th
4 Lack of farming inputs
27
15.4
3rd
5 Gender discrimination
14
8.0
7th
6 Poor returns (Profit)
35
20.0
2nd
7 Lack of farmland
20
11.4
4th
Note: Field study, 2022.

3.4. Socio-Economic Characteristics Affecting Women Involvement in Farming Activities

As shown in Table 4, the multiple regression model with seven predictors produced R2 = 0.896, F = 140.819, p<0.000. The R2 was relatively high and the F values at p<0.000 affirms the goodness of the model to predict the effect on the regressors. Six variables were found to be significant and explained 89% of observed variation in the level of rural women involvement in farming activities. The significant variables were: age, marital status, farming experience, household size, level of education and farm size.

3.4.1. Age

Age was positively and significantly related with the level of women participation in farming activities. In other words, active age of the women was an incentive to their active participation in farming activities. The finding concurred with Omotesho, et al. [12]; Adams [9] that age had a positive coefficient which suggested that as the age increased, the participation of women in agricultural production increased.

3.4.2. Marital Status

Marital status was also positive and significant which indicated that marriage among the rural women encouraged the women to venture into active farming activities inorder to support the family. With the high cost of living, married women in the rural areas with their children through active involvement in farming activities secured food for the family and also sell the produce to support the men’s major occupation.

3.4.3. Farming Experience

Farming experience was negative but significantly related with rural women participation in farming activities. The result negated Enete and Amusa [8]; Abegunde [13]; Omotesho, et al. [12] that years of farming was positive and significantly related with women’s level of contribution to farming decision.

3.4.4. Household Size

The size of household was positively significant in explaining the level of women participation in farming activities. This agreed with Nuhu, et al. [14] that most Nigerian men believe women should spend more time taking care of their children and domestic activities than working.

3.4.5. Level of Education

Level of education was significant though negative. The result negated the findings by Adams [9]; Nuhu, et al. [14] that as the respondents improved on their education level, they became influenced to participate in agricultural production.

3.4.6. Farmland Size

Farm size was positively and significantly related. This corresponded Enete and Amusa [8]; Omotesho, et al. [12] that the access to farmland made women to contribute to decision making in household.

Table 4. Socio-economic characteristics affecting women involvement in farming activities.
Variables
Coef.
Std. Error
Beta
T
Sig.
Constant
0.533
0.156
3.419
0.001
Age
0.564
0.046
0.776
12.306
0.000*
Marital Status
0.207
0.057
0.145
3.649
0.000*
Household size
0.142
0.071
0.085
1.995
0.048**
Farming experience
-0.100
0.058
-0.154
-1.710
0.089
Primary occupation
0.142
0.071
0.085
1.995
0.048**
Educational level
-0.194
0.093
-0.092
-2.092
0.038**
Farmland size
0.072
0.019
0.217
3.819
0.000*

Note: Field study, 2022.
R = 0.946. R2 = 0.896. Adjusted R2 =0.889.
**p< 0.05.
*p<0.01%.

4. CONCLUSION

The study revealed that rural women were active in farming activities mostly in planting, weeding and harvesting. It also identified the age, marital status, household size, primary occupation, educational level and farm size as the socio-economic factors that encouraged the rural women to be involved in active farming activities.

Based on the findings from the study, the study recommended that government and non-governmental organization should make access to finances by the rural women and market for their agricultural produce is available. This will encourage more women both in the rural and urban setting to venture into active and profitable farming activities.

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