Towards Intensive Co-operated Agribusiness: A Gender-Based Comparative Borich Needs Assessment Model Analysis of Beef Cattle Farmers in Eswatini
Abstract
:1. Introduction
- Describe the differences in self-evaluated levels of importance of competencies between male and female beef cattle farmers;
- Identify proficiency differences in competencies between the gender groups; and
- Evaluate the inter-gender group discrepancies in beef cattle production and related agribusiness management competencies among farmers.
2. Literature Review
2.1. Farmer Training in Eswatini
2.2. Training Needs Assessment
2.3. Gender-Based Training Needs Assessment
3. Materials and Methods
3.1. Study Area
3.2. Sampling and Data Collection
3.3. Analytical Framework
4. Results and Discussion
4.1. Descriptive Statistics
4.2. Importance of Main Production and Agribusiness Management Practices
4.3. Proficiency in Production and Agribusiness Management Practices
4.4. Competency Discrepancies among Beef Cattle Farmers
4.5. Overall Training Needs for Female Beef Cattle Farmers
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Upton, M. The Role of Livestock in Economic Development and Poverty Reduction; FAO: Rome, Italy, 2004. [Google Scholar]
- Department of Veterinary and Livestock Services. Animal Production Annual Report; Ministry of Agriculture, Government of Eswatini: Mbabane, Eswatini, 2017.
- Department of Veterinary and Livestock Services. Animal Production Annual Report; Ministry of Agriculture, Government of Eswatini: Mbabane, Eswatini, 2018.
- Hashemi, S.M.; Mokhtarnia, M.; Erbaugh, J.M.; Asadi, A. Potential of extension workshops to change farmers’ knowledge and awareness of IPM. Sci. Total Environ. 2008, 407, 84–88. [Google Scholar] [CrossRef] [PubMed]
- Hashemi, S.M.; Hosseini, S.M.; Damalas, C.A. Farmers’ competence and training needs on pest management practices: Participation in extension workshops. Crop Prot. 2009, 28, 934–939. [Google Scholar] [CrossRef]
- Morton, J.; Mattewman, R. Improving livestock production through extension: Information needs, institutions and opportunities. Nat. Resour. Perspect. 1996, 12, 1–8. [Google Scholar]
- Heffernan, C.; Nielsen, L. The livestock guru: The design and testing of a tool for knowledge transfer among the poor. Inf. Technol. Int. Dev. 2007, 4, 113–121. [Google Scholar] [CrossRef]
- Niewolny, K.L.; Lillard, P.T. Expanding the boundaries of beginning farmer training and program development: A review of contemporary initiatives to cultivate a new generation of American farmers. J. Agric. Food Syst. Community Dev. 2010, 1, 65–88. [Google Scholar] [CrossRef] [Green Version]
- Government of Eswatini. Veterinary & Livestock. Available online: http://www.gov.sz/index.php/ministries-departments/ministry-of-agriculture/veterinary-a-livestock (accessed on 27 February 2020).
- Kumar, N.; Vimal, R.; Jiji, R.; Rajkamal, P. Training needs of dairy farm instructors in fodder production and management. J. Vet. Anim. Sci. 2013, 44, 46–50. [Google Scholar]
- Ampaire, A.; Rothschild, M.F. Effects of training and facilitation of farmers in Uganda on livestock development. Livest. Res. Rural Dev. 2010, 22, 1–7. [Google Scholar]
- Jacob, S.K.; George, A. Assessing the training need of dairy farmers on scientific cattle management practices. Int. J. Sci. Res. 2013, 2, 496–497. [Google Scholar] [CrossRef]
- Jadav, S.; Rani, V.D.; Mudgal, S.; Dhamsaniya, H. Women empowerment through training in dairy farming. Asian J. Dairy Food Res. 2014, 33, 147–153. [Google Scholar] [CrossRef]
- Sah, U.; Kumar, S.; Fulzele, R. Perceived needs of dairy farmers and farm women related to improved dairy farming in India: An overview. Agric. Rev. 2002, 23, 65–70. [Google Scholar]
- Pourouchottamane, R.; Venkatasubramanian, V.; Singha, A.K.; Mishra, A.; Pankaj, P.K. Training needs analysis of livestock farmers and rural youths of north eastern India. Vet. Pract. 2012, 13, 374–379. [Google Scholar]
- Borich, G.D. A needs assessment model for conducting follow-up studies. J. Teach. Educ. 1980, 31, 39–42. [Google Scholar] [CrossRef]
- Umar, S.; Man, N.; Nawi, N.M.; Latif, I.A.; Smah, B.A. Core competency requirements among extension workers in peninsular Malaysia: Use of Borich’s needs assessment model. Eval. Program Plan. 2017, 62, 9–14. [Google Scholar] [CrossRef] [PubMed]
- Farinde, A.J.; Ajayi, A.O. Training needs of women farmers in livestock production: Implications for rural development in Oyo State of Nigeria. J. Soc. Sci. 2005, 10, 159–164. [Google Scholar] [CrossRef]
- Vaarst, M.; Byarugaba, D.; Nakavuma, J.; Laker, C. Participatory livestock farmer training for improvement of animal health in rural and peri-urban smallholder dairy herds in Jinja, Uganda. Trop. Anim. Health Prod. 2007, 39, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Simpson, B.M.; Owens, M. Farmer field schools and the future of agricultural extension in Africa. J. Int. Agric. Ext. Educ. 2002, 9, 29–36. [Google Scholar] [CrossRef]
- Kilpatrick, S. Education and training: Impacts on farm management practice. J. Agric. Educ. Ext. 2000, 7, 105–116. [Google Scholar] [CrossRef]
- Abiddin, N.Z. The practice of training program design at selected training institutes in Malaysia. J. Hum. Resour. Adult Learn. 2005, 1, 8–15. [Google Scholar]
- Mizoguchi, N.; Luluquisen, M.; Witt, S.; Maker, L. A Handbook for Participatory Community Assessments: Experiences from Alameda County; Public Health Department: Oakland, CA, USA, 2004. [Google Scholar]
- Braun, A.; Jiggins, J.; Röling, N.; van den Berg, H.; Snijders, P. A global survey and review of farmer field school experiences. In A Report for the International Livestock Research Institute; International Livestock Research Institute: Wageningen, The Netherlands, 2006. [Google Scholar]
- Rivera, W.; Alex, G. Demand-Driven Approaches to Agriculture Extension; The World Bank: Washington, DC, USA, 2004; Volume 3. [Google Scholar]
- Agholor, I.A.; Monde, N.; Obi, A.; Sunday, O.A. Quality of extension services: A case study of farmers in Amathole. J. Agric. Sci. 2013, 5, 204–212. [Google Scholar]
- Meitei, L.S.; Devi, T. Farmers information needs in rural Manipur: An assessment. Ann. Libr. Inf. Stud. 2009, 56, 35–40. [Google Scholar]
- Abugu, R.; Chah, J.; Nwobodo, C.; Asadu, A.; Igbokwe, E. Agricultural extension needs of farmers in telfairia production and marketing in Enugu State, Nigeria. J. Agric. Ext. 2013, 17, 49–60. [Google Scholar] [CrossRef] [Green Version]
- Keller, B.; Mbewe, D.C. Policy and planning for the empowerment of Zambia’s women farmers. Can. J. Dev. Stud. 1991, 12, 75–88. [Google Scholar] [CrossRef]
- Barbercheck, M.; Brasier, K.; Kiernan, N.E.; Sachs, C.; Trauger, A.; Findeis, J.; Stone, A.; Moist, L. Meeting the extension needs of women farmers: A perspective from Pennsylvania. J. Ext. 2009, 47, 1–11. [Google Scholar]
- Arshad, S.; Muhammad, S.; Ashraf, I. Women’s participation in livestock farming activities. J. Anim. Plant Sci. 2013, 23, 304–308. [Google Scholar]
- Durgga, R.V.; Subhadra, M. Training needs of farm women in dairy farming. Vet. World 2009, 2, 221–223. [Google Scholar]
- Nosheen, F.; Ali, T.; Anwar, H.N.; Ahmad, M. An assessment of participation of rural women in livestock management and their training needs in Potohar Region. Pak. Vet. J. 2011, 31, 40–44. [Google Scholar]
- World Bank. Employment in Agriculture, Female (% of Female Employment) (Modelled ILO Estimate). Available online: http://data.worldbank.org/indicator/SL.AGR.EMPL.FE.ZS (accessed on 16 May 2019).
- Rais, M.U.N.; Solangi, A.W.; Sahito, H.A. Economic assessment of rural women involved in agriculture and livestock farming activities. J. Agric. Res. 2013, 2, 115–121. [Google Scholar]
- FAO. The State of Food and Agriculture; FAO: Rome, Italy, 2002. [Google Scholar]
- FAO. The Role of Women in Agriculture; FAO: Rome, Italy, 2011. [Google Scholar]
- Luqman, M.; Shahbaz, B.; Khan, I.A.; Safdar, U. Training need assessment of rural women in livestock management-case of Southern Punjab, Pakistan. J. Agric. Res. 2013, 51, 99–108. [Google Scholar]
- Magagula, S.D.M.; Dlamini, E.V.; Mkhwanazi, E.M. Modern Agriculture for Swaziland 1, 17th ed.; Oxford University Press Southern Africa: Cape Town, South Africa, 2009. [Google Scholar]
- Central Statistics Office. Swaziland Household Income and Expenditure Survey; Ministry of Economic Planning and Development, Kingdom of Eswatini: Mbabane, Eswatini, 2010.
- Ministry of Labour and Social Security. The Swaziland Integrated Labour Force Survey; Government of Eswatini: Mbabane, Eswatini, 2013.
- Worldometer. Eswatini Population. Available online: https://www.worldometers.info/world-population/swaziland-population/ (accessed on 27 February 2020).
- FAO. AQUASTAT Country Profile—Swaziland; FAO: Rome, Italy, 2005. [Google Scholar]
- Singh, A.S.; Masuku, M.B. Sampling techniques & determination of sample size in applied statistics research: An overview. Int. J. Econ. Commer. Manag. 2014, 2, 1–22. [Google Scholar]
- Shain, D.; Klopfenstein, T.; Stock, R.; Vieselmeyer, B.; Erickson, G. Evaluation of grazing alternate summer and fall forages in extensive beef cattle production systems. Prof. Anim. Sci. 2005, 21, 390–402. [Google Scholar] [CrossRef] [Green Version]
- Casasús, I.; Sanz, A.; Villalba, D.; Ferrer, R.; Revilla, R. Factors affecting animal performance during the grazing season in a mountain cattle production system. J. Anim. Sci. 2002, 80, 1638–1651. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fox, D.G.; Sniffen, C.; O’connor, J. Adjusting nutrient requirements of beef cattle for animal and environmental variations. J. Anim. Sci. 1988, 66, 1475–1495. [Google Scholar] [CrossRef]
- National Veterinary Services. Annual Report; Ministry of Agriculture, Government of Eswatini: Mbabane, Eswatini, 2018.
- Weatherspoon, D.; Cacho, J.; Christy, R. Linking globalization, economic growth and poverty: Impacts of agribusiness strategies on sub-Saharan Africa. Am. J. Agric. Econ. 2001, 83, 722–729. [Google Scholar] [CrossRef]
- Dlamini, S.I.; Huang, W.-C. A double hurdle estimation of sales decisions by smallholder beef cattle farmers in Eswatini. Sustainability 2019, 11, 5185. [Google Scholar] [CrossRef] [Green Version]
- Masuku, T.; Masuku, M.; Mutangira, J. Performance of multi-purpose cooperatives in the Shiselweni Region of Swaziland. Int. J. Sustain. Agric. Res. 2016, 3, 58–71. [Google Scholar] [CrossRef]
- Hao, J.; Bijman, J.; Gardebroek, C.; Heerink, N.; Heijman, W.; Huo, X. Cooperative membership and farmers’ choice of marketing channels: Evidence from apple farmers in Shaanxi and Shandong Provinces, China. Food Policy 2018, 74, 53–64. [Google Scholar] [CrossRef]
- Dlamini, S.; Huang, W.-C. Agricultural Cooperatives in the Kingdom of Eswation: Financial efficiency, challenges and opportunities. Int. J. Community Coop. Stud. 2019, 7, 1–16. [Google Scholar]
- Alibaygi, A.; Zarafshani, K. Training needs of Iranian extension agents about sustainability: The use of Borich’s needs assessment. Afr. J. Agric. Res. 2008, 3, 681–687. [Google Scholar]
- Ruxton, G.D. The unequal variance t-test is an underused alternative to Student’s t-test and the Mann–Whitney U test. Behav. Ecol. 2006, 17, 688–690. [Google Scholar] [CrossRef]
- Sokal, R.R.; Rohlf, F.J. Introduction to Biostatistics; Dover Publication Inc.: Mineola, NY, USA, 1987. [Google Scholar]
- Zimmerman, D.W. Comparative power of Student t-test and Mann-Whitney U-test for unequal sample sizes and variances. J. Exp. Educ. 1987, 55, 171–174. [Google Scholar] [CrossRef]
- Dankel, S.J.; Mouser, J.G.; Mattocks, K.T.; Counts, B.R.; Jessee, M.B.; Buckner, S.L.; Loprinzi, P.D.; Loenneke, J.P. The widespread misuse of effect sizes. J. Sci. Med. Sport 2017, 20, 446–450. [Google Scholar] [CrossRef] [PubMed]
- Nakagawa, S.; Cuthill, I.C. Effect size, confidence interval and statistical significance: A practical guide for biologists. Biol. Rev. 2007, 82, 591–605. [Google Scholar] [CrossRef] [PubMed]
- Turturean, C. Who’s afraid of the effect size? In Proceedings of the 7th International Conference on Globalization of Higher Education in Economics and Business Administration, Iași, Romania, 24–26 October 2013; pp. 665–669. [Google Scholar]
- Lakens, D. Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Front. Psychol. 2013, 4, 1–12. [Google Scholar] [CrossRef] [Green Version]
- Slavin, R.E. A reader’s guide to scientifically based research. Educ. Leadersh. 2003, 60, 12–16. [Google Scholar]
- LeBlanc, V.; Cox, M. Interpretation of the point-biserial correlation coefficient in the context of a school examination. Tutor. Quant. Methods Psychol. 2017, 13, 46–56. [Google Scholar] [CrossRef] [Green Version]
- Tirivayi, N.; Nennen, L.; Tesfaye, W.; Ma, Q. The benefits of collective action: Exploring the role of forest producer organizations in social protection. For. Policy Econ. 2018, 90, 106–114. [Google Scholar] [CrossRef]
Continuous Variable | Male (smale = 199) | Female (sfemale = 198) | t-Value | ||
---|---|---|---|---|---|
Mean | SD | Mean | SD | ||
Age (years) | 56.52 | 13.401 | 60.25 | 12.000 | 2.921 *** |
Education (years) | 9.88 | 4.385 | 8.00 | 4.507 | −4.222 *** |
Herd size (number) | 20.97 | 15.254 | 11.31 | 9.892 | −7.491 *** |
Experience (years) | 20.236 | 12.025 | 18.417 | 11.974 | −1.511 |
Categorical Variable | Male (smale = 199) | Female (sfemale = 198) | χ2 | ||
Farm location | Hhohho = 49, Lubombo = 50, Manzini = 50, Shiselweni = 50 | Hhohho = 49, Lubombo = 50 Manzini = 49, Shiselweni = 50 | 2.849 | ||
Off-farm income (Emalangeni) | < E1000 = 57, E1000–E10 00 = 91, > E10 000 = 51 | < E1000 = 84, E1000–E10 00 = 77, > E10 000 = 37 | 8.562 ** | ||
Marital Status | Single = 10, Married = 173, Widowed = 16 | Single = 2, Married = 60, Widowed = 136 | 154.871 *** | ||
Ecological zone | Lowveld = 42, Middleveld = 115, Highveld = 42 | Lowveld = 32, Middleveld = 109, Highveld = 57 | 3.782 |
Mean | SD | Gender | Importance | Proficiency | MWDS | |
---|---|---|---|---|---|---|
Gender | 0.5 | 0.501 | 1 | |||
Importance | 4.493 | 0.295 | 0.047 ns | 1 | ||
Proficiency | 1.891 | 0.529 | 0.289 *** | 0.234 *** | 1 | |
MWDS | 11.692 | 2.433 | −0.257 *** | 0.316 *** | −0.849 *** | 1 |
Overall (S = 397) | Males (smale = 199) | Females (sfemale = 198) | t-Value | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Competency | Mean | SD | Rank | Mean | SD | Rank | Mean | SD | Rank | (p-Value) |
Disease control | 4.971 | 0.160 | 1 | 4.978 | 0.142 | 1 | 4.965 | 0.176 | 1 | −0.846 (0.398) |
Marketing and pricing | 4.829 | 0.375 | 2 | 4.862 | 0.328 | 2 | 4.797 | 0.415 | 2 | −1.733 (0.084) |
Farm business management | 4.713 | 0.382 | 3 | 4.715 | 0.372 | 4 | 4.711 | 0.393 | 3 | −0.103 (0.918) |
Fodder production and storage | 4.698 | 0.359 | 4 | 4.725 | 0.315 | 3 | 4.670 | 0.397 | 4 | −1.536 (0.125) |
Pasture management | 4.591 | 0.392 | 5 | 4.616 | 0.360 | 5 | 4.566 | 0.421 | 5 | −1.291 (0.198) |
Breeding and rearing | 4.275 | 0.444 | 6 | 4.327 | 0.429 | 6 | 4.224 | 0.454 | 6 | −2.326 ** (0.021) |
Nutritional needs and deficiencies | 4.184 | 0.429 | 7 | 4.208 | 0.381 | 7 | 4.160 | 0.472 | 8 | −1.109 (0.268) |
Farmers’ cooperative management | 4.131 | 0.960 | 8 | 4.099 | 0.984 | 8 | 4.163 | 0.939 | 7 | 0.668 (0.505) |
Shed and pen construction | 3.979 | 0.694 | 9 | 4.010 | 0.702 | 9 | 3.947 | 0.686 | 9 | −0.906 (0.366) |
Overall (S = 397) | Males (smale = 199) | Females (sfemale = 198) | t-Value | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Competency | Mean | SD | Rank | Mean | SD | Rank | Mean | SD | Rank | (p-Value) | d-Value |
Disease control | 2.775 | 0.969 | 1 | 3.214 | 0.843 | 1 | 2.333 | 0.884 | 1 | −10.162 *** (0.000) | 1.020 |
Breeding and rearing | 2.541 | 0.625 | 2 | 2.810 | 0.541 | 2 | 2.270 | 0.586 | 2 | −9.543 *** (0.000) | 0.958 |
Sheds and pen construction | 1.883 | 0.496 | 3 | 2.113 | 0.473 | 3 | 1.652 | 0.403 | 4 | −10.472 *** (0.000) | 1.050 |
Pasture management | 1.838 | 0.508 | 4 | 2.042 | 0.451 | 4 | 1.633 | 0.481 | 6 | −8.742 *** (0.000) | 0.877 |
Farm business management | 1.804 | 0.934 | 5 | 1.869 | 0.985 | 6 | 1.739 | 0.877 | 3 | −1.382 (0.168) | 0.139 |
Fodder production and storage | 1.782 | 0.371 | 6 | 1.916 | 0.333 | 5 | 1.646 | 0.358 | 5 | −7.776 *** (0.000) | 0.780 |
Marketing and pricing | 1.710 | 0.892 | 7 | 1.829 | 0.951 | 7 | 1.590 | 0.813 | 8 | −2.698 *** (0.007) | 0.271 |
Cooperative management | 1.658 | 0.845 | 8 | 1.714 | 0.907 | 8 | 1.603 | 0.775 | 7 | −1.309 (0.191) | 0.131 |
Nutritional needs and deficiencies | 1.193 | 0.417 | 9 | 1.229 | 0.478 | 9 | 1.157 | 0.344 | 9 | −1.745 (0.082) | 0.175 |
Overall (S = 397) | Males (smale = 199) | Females (sfemale = 198) | t-Value | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Competency | MWDS | SD | Rank | MWDS | SD | Rank | MWDS | SD | Rank | (p-Value) | d-Value |
Marketing and pricing | 15.066 | 4.304 | 1 | 14.646 | 4.547 | 1 | 15.488 | 4.013 | 1 | 1.956 (0.051) | 0.196 |
Farm business management | 13.712 | 4.382 | 2 | 13.417 | 4.480 | 2 | 14.009 | 4.271 | 3 | −1.383 (0.168) | 0.135 |
Fodder production and storage | 13.699 | 2.327 | 3 | 13.196 | 2.160 | 3 | 14.204 | 2.385 | 2 | 4.413 *** (0.000) | 0.443 |
Pasture management | 12.640 | 2.904 | 4 | 11.820 | 2.664 | 5 | 13.464 | 2.909 | 4 | 5.873 *** (0.000) | 0.589 |
Nutritional needs and deficiencies | 12.513 | 2.535 | 5 | 12.461 | 2.600 | 4 | 12.566 | 2.474 | 6 | 0.413 (0.680) | 0.041 |
Disease control | 10.920 | 4.928 | 6 | 8.769 | 4.300 | 7 | 13.081 | 4.568 | 5 | 9.685 *** (0.000) | 0.972 |
Cooperative management | 10.215 | 4.627 | 7 | 9.853 | 4.819 | 6 | 10.578 | 4.409 | 7 | 1.562 (0.119) | 0.157 |
Sheds and pen construction | 8.338 | 3.160 | 8 | 7.547 | 3.086 | 8 | 9.133 | 3.039 | 8 | 5.156 *** (0.000) | 0.518 |
Breeding and rearing | 7.414 | 2.643 | 9 | 6.483 | 2.299 | 9 | 8.351 | 2.640 | 9 | 7.519 *** (0.000) | 0.755 |
Variable | Sample (S = 397) | Males (smale = 199) | Females (sfemale = 198) | t-Value (p-Value) | d-Value | |||
---|---|---|---|---|---|---|---|---|
Mean | SD | Mean | SD | Mean | SD | |||
Importance | 4.493 | 0.295 | 4.507 | 0.279 | 4.480 | 0.310 | −0.933 (0.352) | 0.094 |
Proficiency | 1.891 | 0.529 | 2.044 | 0.528 | 1.738 | 0.484 | −6.004 *** (0.000) | 0.603 |
Discrepancy | 11.692 | 2.433 | 11.069 | 2.340 | 12.317 | 2.369 | 5.280 *** (0.000) | 0.530 |
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Dlamini, S.I.; Huang, W.-C. Towards Intensive Co-operated Agribusiness: A Gender-Based Comparative Borich Needs Assessment Model Analysis of Beef Cattle Farmers in Eswatini. Agriculture 2020, 10, 96. https://doi.org/10.3390/agriculture10040096
Dlamini SI, Huang W-C. Towards Intensive Co-operated Agribusiness: A Gender-Based Comparative Borich Needs Assessment Model Analysis of Beef Cattle Farmers in Eswatini. Agriculture. 2020; 10(4):96. https://doi.org/10.3390/agriculture10040096
Chicago/Turabian StyleDlamini, Sicelo Ignatius, and Wen-Chi Huang. 2020. "Towards Intensive Co-operated Agribusiness: A Gender-Based Comparative Borich Needs Assessment Model Analysis of Beef Cattle Farmers in Eswatini" Agriculture 10, no. 4: 96. https://doi.org/10.3390/agriculture10040096
APA StyleDlamini, S. I., & Huang, W. -C. (2020). Towards Intensive Co-operated Agribusiness: A Gender-Based Comparative Borich Needs Assessment Model Analysis of Beef Cattle Farmers in Eswatini. Agriculture, 10(4), 96. https://doi.org/10.3390/agriculture10040096