Demography of smallholder agricultural enterprise led by women and youth, and their association with the cultivation of the Okra (Abelmoschus esculentus L. Moench) vegetable crop

Introduction

Okra (Abelmoschus esculentus (L.) Moench) is a yearly fruit vegetable crop propagated. Through seed and normally grown commercially in tropical and sub-tropical regions of the world (Abe, 2018) [1] . It is also grown in warmer temperate regions of the Mediterranean region (Dhankhar, 2009) [8] . According to the writings of Kochhar (1986) [14] and Thakur (1986) [28] Okra is currently found in most countries of the African continent and Asia. Sathish (2013) [26] did a review on the work done on the crop and reported that it originated in Ethiopia and was cultivated by the ancient Egyptians. Several authors (Kochhar, 1986; Thakur, 1986; Gemede et. al., 2015 and Gemede et. al., 2016) [11,12,14,28] reported that okra is a multi-use crop due to its numerous usages of the pods, fresh leaves, buds, flowers, stems, and seeds. The young fruits can be consumed as vegetables, in the form of salads, soups and stews, fresh or dried, fried or boiled. Woolfe et al, (1977) [31] in his studies done on mucilage's extracted from Okra found that the plant contains gum like substances in various plant parts, which is associated with other important substances including tannins. The main purposes of mucilage within the plant includes helping in water storage, decreasing diffusion in plants, assistance in seed dispersal and germination, and acting as a membrane thickener and food reserve. Okra mucilage is used for manufacturing in glace paper production and medicinal applications as a plasma replacement or blood volume expander (Akinyele et al., 2007) [3] in different parts of the world. Nutritionally, Okra contains proteins, carbohydrates, and vitamins that plays a vital role in food security, human health, and nutritional security (Lamont, 1999) [16] . The young and green fruits are consumed as fresh fruits, in boiled, fried, or cooked variety of forms. Tindall (1983) [27] indicated that the seeds of Okra contain about 20% protein and 20% oil. Moekchantuk (2004) [19] in his work to export Okra reported that the seeds of the crop can be dried, and the dried seeds are a nutritious material that can be used to prepare vegetable curds or roasted and ground to be used as coffee additive or substitute. Doijode, (2001) [9] also reported that okra leaves can also be used as animal feed, whilst the green leaf buds and flowers are also edible (Akinyele et al., 2007) [3] . A study by Kumar et al. (2009) [15] in China suggested that an alcohol extract of okra leaves can eliminate oxygen free radicals, alleviate renal tubularwww.extensionjournal.com interstitial diseases, reduce proteinuria, and improve renal function. Okra as a vegetable crop has become traditional with comparatively low agricultural input needed. Historically, the intercropping of crops by smallholder farmers has been a common exercise throughout the years. The advantage of the practice may allow balancing interactions in crops that have greater system resilience, in some instances reduce insect pest incidence and deliver environmental benefits such as greater soil and water conservation potential. Over 75% of maize and 60% of okra grown in Nigeria are produced under intercropping system. On average SHAW-YE produce okra on an average plots of 2.13 ha per entrepreneur under irrigation which is the second out of all the vegetable crops. In the context that 89% of the population of Limpopo Province is classified as rural, the smallholder sector producing Okra has a potential to play a major role in the economic development of rural areas of the Province (Nesamvuni et al., 2003) [21] . However, socio-economic factors continue to play a critical role in determining the levels of production undertaken and the sort of crops planted. This was corroborated by von Braun and Mirzabaev (2015) [30] who stated that the production levels are not the only areas affected but also the way business enterprises are managed which put the socioeconomic characteristics of the smallholder farmers and entrepreneurs into focus. Previous studies (Mwaniki, 2006 [2,5,20,24] have resolved that if assistance is to be extended to crop producers their demography is worth investigating to fully comprehend their needs. The relationship between demography and socio-economic factors will be described in this study to produce appropriate policy information to agricultural stakeholders and government. In developing women and youth agricultural entrepreneurs producing Okra there is lack of knowledge on its contribution to women and youth livelihood and incomes in SHAW-YEs in rural South Africa. The main objective of this study was therefore to assess the demography of SHAW-YEr and the associated cultivation of Okra under irrigation.

Methodology Study Area

The study was carried out in Vhembe District Municipality of Limpopo Province, South Africa. The specific areas were Madimbo Corridor in Musina and Mutale Valley in Thulamela Local Municipality. The two areas were categorized as independent SHAW-YE each with a private water supply in the case of Madimbo and as irrigated enterprises which are served by communal water supply infrastructure in the case of Mutale. The two areas of Madimbo Corridor and upper Mutale Valley irrigation schemes constitute a total of more than 2270 ha of production area.

Sampling Procedure

Stratified random sampling was used to obtain a representative sample of villages and households for interview (Leedy et al, 2010) [17] with target population being SHAW-YEs. A two-stage random sampling process was conducted using SURVEYSELECT procedure of SAS.

The PROC SUREVEYSELECT allowed for probabilitybased random sampling where sampling in a category or class depended on the number of units within that class. The sampling was regarded appropriate for handling selection bias.

Data Collection

A semi structured household questionnaire was used to carry out a survey with an emphasis on SHAW-YE. Total number of SHAW-YE interviewed were two hundred and ninety-four (N=294) with a response rate of 75 percent. The sample was comprised of 71 youths aged 18 to 35 years old (56 females and 15 males) and 223 women of whom 153 were adults (36-59 years) and 70 pensioners (≥ 60 years old).

Data analysis

Statistical Package for the Social Sciences (SPSS) version 22 was used to analyse quantitative data. Descriptive statistics included frequency tables and measures of central tendency. Inferential statistics were in the form of chi square analyses, which assessed the association between major demographic variables (gender, age, education, and income) and vegetable/ field crop production, water resources and governance. Fischer Exact tests were interpreted in cases where the assumptions for chi square analysis had been violated. A Bonferroni adjustment was made to prevent a type I error; therefore, significance was considered when p <0.013. Qualitative data was analysed using MS Excel, themes for each question were created according to participant's responses and each response was coded accordingly. (In some cases, these themes were further broken down into one or more relevant sub-themes.)

Results and Discussion

The production potential The average production area under irrigated for Okra was 1.64 ha per farmer. The production area was 0.49 ha more in winter than in summer. It was reported that winter had production potential of up to 5000 bags in summer as compared to 200 bags at the most in winter. The price for Okra was on average the same at R50 / bag.

The association between cultivating Okra and gender

A chi-square test for association was conducted between cultivating Okra and gender (Table 1). It is necessary to establish the differences in the roles played by males and females in farm households since this gender differences are likely to influence their capacity to adapt to climate change as well as their choices of climate change adaptation strategies (Gerald, 2009) [13] . The test of association in the winter season showed that all the expected cell frequencies were greater than five, which means that the assumption for the test was not violated. However, there was not a statistically significant association between cultivating okra and gender, χ2 = 0,028, p = 0.866. It was determined that 46.7% of males cultivated okra compared to 44.4% females. In line with the result not being statistically significant, the effect size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.010, p = 0.866. The test for association in the summer season indicated that all the expected cell frequencies were greater than five, the test's assumption was not violated. The results also showed that there was not a statistically significant association between cultivating okra and gender, χ2 = 0,524, p = 0.56. It was determined that 26.7% males cultivated okra compared to 35.8% females. In line with the result not being statistically significant, the effect size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.042, p = 0.469. Though there were seasonal differences found in this study, males were still participating more in producing Okra.

Similar observations were made in a study of youth agricultural projects in Limpopo Province, Maele et al.

(2015) [18] revealed that majority of farmers (74%) were male. The finding that men were majority owners of agricultural projects was also affirmed by Bembridge and Tshikolomo (1998) [6] who revealed that 90% of fruit growers in the Phaswana area of the Limpopo Province were males.

The association between cultivating Okra and age

The Chi-square test of association between age of the respondent and the cultivation of Okra crop in winter and summer is reflected in Table 2. For winter season the results showed that all the expected cell frequencies were greater than five, for the Chi-square test assumption not to be violated. There was not a statistically significant association between cultivating okra and age, χ2 = 1,431, p = 0.489. It was determined that 46,5% of 18-35-year participants cultivate okra compared to 46,5% and 38,2% of 36-59-year and those >60 years respectively. In line with the result not being statistically significant, the effect size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.070, p = 0.489. A chi-square test for association was conducted between cultivating okra and age in summer (Table 2). All the expected cell frequencies of the table were greater than five, therefore the test assumption was not violated.

There was not a statistically significant association between cultivating okra and age, χ2 = 3,114, p = 0.211. It was determined that 42.3% of 18-35-year participants cultivated okra compared to 35.5% of 36-59-year participants and 27.9% of those >60-years. In line with the result not being statistically significant, the effect of size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.103, p = 0.211. Okra seems to be a youth-oriented crop judged by the trends showing higher participation of youth between the ages of 18-35-yer both in winter and summer. More participation seems to be in winter (44.6%) than in summer (35%). The results showed how youth tend to take new challenges in the name of a new crop for the area and adopt it for the market. This was corroborated by Fussel and Klein ( 2006) who reported that older farmers could be resistant to change and thus may not see the need of employing new technologies and would prefer the traditional models of farming that they are familiar with other than adopting new methods. Farm productivity has been shown to deteriorate with the farmers' age, especially among the smallholders who largely rely on their own physical labour to execute many farming responsibilities (Uddin et al., 2014) [29] . The advantage with youth farmers was they may have a longer planning horizon and to take up long term measures that will influence their decision to increase production levels.

The association between cultivating Okra and education

A chi-square test for association was conducted between cultivating okra and household head education (Table 3). The importance of education in successful developmental activities such as farming cannot be overemphasized. The level of education has a strong influence on the extent to which a farmer can access new information and technology, not only through improved literacy that enables the farmers to access written information, but also through the increased ability to search for information using modern information technologies. Citing Appleton and Balihuta (1996) [4] , Oduro-Ofori et al. (2014) [23] described the effect of education on agricultural productivity as cognitive and noncognitive.

Cognitive effects reportedly emphasize basic literacy and numeracy that farmers achieve from education while noncognitive effects emphasize the change in the attitude of farmers who attended school due to improved discipline introduced by formal schooling. Better education may therefore be associated with the improved adaptive capacity to adverse effects of climate change and variability. The results showed no statistically significant association between cultivating okra and household head education in winter, χ2 = 3.545, p = 0.315. It was determined that 52.5% of participants whose household head's had no/ primary school cultivated okra, while 47.4% and 39.4% of participants with household head education levels of secondary and tertiary level cultivated okra respectively. Also, 38.3% of participants with household head education of ABET planted the crop. In line with the result not being statistically significant, the effect size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.110, p = 0.315. The level of education for SHAW-YE producing Okra seems to be poor as 90.8% of respondents either had no primary schooling or had Adult Basic Education & Training (ABET). A chi-square test for association was conducted between cultivating okra and household head education for the summer season. There was not a statistically significant association between cultivating okra and household head education, χ2 = 6,250, p = 0.100. It was determined that 24,6% of participants with no/ primary household head education cultivated okra while 43,1% of participants with household head with secondary education cultivated okra and 36,4% and 33,3% of participants with household heads with tertiary education and ABET respectively cultivated okra. In line with the result not being statistically significant, the effect size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.147, p = 0.100.

The association between cultivating Okra and income

A chi-square test for association was conducted between cultivating okra and monthly income (Table 8.8). According to Nouman et al. (2013) [22] , household income is also one of the determinants of the amount of credit that can be borrowed by the farmers. High income farming households can therefore not only better afford needs such as production inputs and other production factors but would also easily qualify for credit to procure the assets that would otherwise not be affordable. The results revealed that there was not a statistically significant association between cultivating okra and monthly income, χ2 = 0.121, p = 0.728. It was determined that 44.0% of participants earning < R5000 a month cultivated okra, compared to 46.4% of those earning > R5000 a month. In line with the result not being statistically significant, the effect size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.020, p = 0.728. Similarly, for the summer season there was not a statistically significant association between cultivating okra and monthly income, χ2= 0.210, p = 0.647. It was determined that 34.7% of participants earning < R5000 a month cultivated okra, compared to 37.7% of those earning > R5000 a month. In line with the result not being statistically significant, the effect size showed a weak association (Cohen, 1988) [7] , as measured by the Phi measure of effect size, φ = 0.027, p = 0.647.

Conclusion

The results of the study indicate some imperative conclusions about the demographic profile of the Smallholder Agricultural Enterprises and their association with the production of Okra. The study revealed that gender, age, education, and income seem to have an influence, but we had statistically not significant results on the production of Okra in the Madimbo Corridor in Musina and Mutale Valley in Thulamela Local Municipality. However, there was no statistical significance and weak association between the demography and production of Okra. The study revealed that the SHAW-YE producing Okra are characterized by small land areas under cultivation. The increased participation of SHAW-YE around the ages of 18-35-year gave a trend suggesting that youth were the dominant participants in the production of this crop.

However, the poor level of education for 90.8% of participants re-emphasizes the need for Government to enhance skills training on-farm to SHAW-YE to complement the farmers experience with cultivation of Okra. About 44.0% of the SHAW-YE earned less than R5000.00 compared with 46.4% earning more than R5000.00. Markets channels and access should be promoted for SHAW-YE to enable throughput of Okra to not only informal but also fresh produce and retail markets.

References

1. Abe S. Agronomic performance, nutritional phenotyping and trait associations of okra (Abelmoschus esculentus) genotypes in South Africa. 2018. http://dx.doi.org/10.5772/intechopen.70813
2. Abdulai S, Nkegbe PK, Donkoh SA. Technical efficiency of maize production in northern Ghana. Afr J Agric Res. 2013;8(43):5251-5259.
3. Akinyele BO, Temikotan T. Effect of variation in soil texture on the vegetative and pod characteristics of okra (Abelmoschus esculentus (L.) Moench). Int J Agric Res. 2007;2:165-169.
4. Appleton S, Balihuta A. Education and agricultural productivity: evidence from Uganda. J Int Dev. www.extensionjournal.com 1996;8:415-444.
5. Asante BO, Osei MK, Dankyi AA, Berchie JN, Mochiah MB, Lamptey JNL, et al. Producer characteristics and determinants of technical efficiency of tomato-based production systems in Ghana. J Dev Agric Econ. 2013;5(3):92-103.
6. Bembridge TJ, Tshikolomo KA. Communication and decision making among fruit growers in the Phaswana area of Northern Province. S Afr J Agric Ext. 1998;27:19-29.
7. Cohen J. Statistical power analysis for the behavioural sciences. 2nd ed. Hillsdale (NJ): Lawrence Erlbaum Associates; 1988.
8. Dhankhar BS, Mishra JP. Origin, history, and distribution. In: Dhankhar BS, Singh R, editors. Okra: Handbook of global production, processing, and crop improvement. New York (NY): HNB Publishing; 2009. p. 100-124.
9. Doijode SD. Seed storage of horticultural crops. New York (NY): Food Product Press; 2001.
10. Füssel HM, Klein RJT. Climate change vulnerability assessments: an evolution of conceptual thinking. Clim Change. 2006;75:301-329.
11. Gemede HF, Ratta N, Haki GD, Woldegiorgis AZ, Beyene F. Nutritional quality and health benefits of okra (Abelmoschus esculentus): a review. J Food Process Technol. 2015;6:458.
12. Gemede W, Haki GD, Beyene F, Woldegiorgis AZ, Rakshit SK. Proximate, mineral, and anti-nutrient compositions of indigenous okra (Abelmoschus esculentus) pod accessions: implications for mineral bioavailability. Food Sci Nutr. 2016;4(2):223-233.
13. Gerald C, Nelson GC, Rosegrant MW, Koo J, Robertson R, Sulser T, et al. Climate change impact on agriculture and costs of adaptation. Washington (DC): International Food Policy Research Institute (IFPRI); 2009.
14. Kochhar SL. Okra (lady's finger). In: Kochhar SL, editor. Tropical crops: a textbook of economic botany. New Delhi: Macmillan; 1986. p. 263-264.
15. Kumar P, Nenes A, Sokolik IN. Importance of adsorption for CCN activity and hygroscopic properties of mineral dust aerosol. Geophys Res Lett. 2009;36(24).
16. Lamont WJ. Okra-A versatile vegetable crop. HortTechnology. 1999;9:179-184.
17. Leedy PD, Ormrod JE. Practical research: planning and design. 9th ed. New Jersey (USA): Pearson Merrill Prentice Hall; 2010.
18. Maele LM, Nesamvuni AE, Tshikolomo KA, Afful DB, Norris D. Characterization of youth agricultural projects in Limpopo Province of South Africa. J Agric Sci. 2015;7(7):42-52.
19. Moekchantuk T, Kumar P. Export okra production in Thailand. Bangkok: FAO; 2004.
20. Mwaniki A. Achieving food security in Africa: challenges and issues. New York: United Nations; 2006.
21. Nesamvuni AE, Oni SA, Odhiambo JJO, Nthakheni ND. Agriculture as the cornerstone of the economy of the Limpopo Province. Limpopo: Department of Agriculture; 2003.
22. Nouman M, Siddiqi MF, Asim SM, Hussain Z. Impact of socio-economic characteristics of farmers on access to agricultural credit. Sarhad J Agric. 2013;29(3):469476.
23. Oduro-Ofori E, Aboagye AP, Acquaye NAE. Effects of education on the agricultural productivity of farmers in the Offinso Municipality. Int J Dev Res. 2014;4(9):1951-1960.
24. Onumah JA, Al-Hassan RM, Onumah EE. Productivity and technical efficiency of cocoa production. [Journal details not provided]. 2013.
25. Saifullah M, Rabbani MG. Evaluation and characterization of okra (Abelmoschus esculentus L. Moench) genotypes. SAARC J Agric. 2009;7:92-99.
26. Sathish D, Eswar A. A review on Abelmoschus esculentus (okra). Int Res J Pharm Appl Sci. 2013;3:129-132.
27. Tindall HD. Vegetables in the tropics. London (UK): Macmillan Education Ltd; 1983.
28. Thakur MR, Arora SK. Okra. In: Bose TK, Som MG, editors. Vegetable crops in India. Calcutta: Naya Prokash; 1986. p. 610-618.
29. Uddin M, Bokelmann W, Entsminger J. Factors affecting farmers' adaptation strategies to environmental degradation and climate change effects: a farm-level study in Bangladesh. Climate. 2014;2(4). http://www.mdpi.com/2225-1154/2/4/223
30. von Braun J, Mirzabaev A. Small farms: changing structures and roles in economic development. ZEF Discussion Papers on Development Policy No. 204. Bonn: Centre for Development Research; 2015.
31. Woolfe ML, Chaplin MF, Otchere G. Studies on the mucilages extracted from okra fruits (Hibiscus esculentus L.) and baobab leaves (Adansonia digitata L.). J Sci Food Agric. 1977;28:519-529.