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Home All issues Volume 27 (2020) OCL, 27 (2020) 41 References
Open Access
Issue
OCL
Volume 27, 2020
Article Number 41
Number of page(s) 9
Section Agronomy
DOI https://doi.org/10.1051/ocl/2020032
Published online 07 August 2020
  • Arunrat N, Wang C, Pumijumnong N, Sereenonchai S, Cai W. 2017. Farmers’ intention and decision to adapt to climate change: a case study in the Yom and Nan basins, Phichit province of Thailand. J Clean Prod 143: 672–685. [Google Scholar]
  • Asrat S, Yesuf M, Carlsson F, Wale E. 2010. Farmers’ preferences for crop variety traits: lessons for on-farm conservation and technology adoption. Ecol Econ 69(12): 2394–2401. [Google Scholar]
  • Baiphethi MN, Jacobs PT. 2009. The contribution of subsistence farming to food security in South Africa. Agrekon 48(4): 459–482. [CrossRef] [Google Scholar]
  • Biofuels Industrial Strategy (BIS) of the Republic of South Africa. 2007. Department of Minerals and Energy. Available from http://www.info.gov.za/view/DownloadFileAction?id=77830 (accessed November 2019). [Google Scholar]
  • Botha M. 2006. Design and implementation of Capacity Development strategies. In: FAO, ed. Workshop Proceedings on Design and Implementation of Capacity Development Strategies: Final Report. 56th IEC Meeting and 19th Congress of the A South African case study International Commission on Irrigation and Drainage (ICID). Ch. 6, 67–88. Rome, Italy: Food and Agriculture Organization of the United Nations. [Google Scholar]
  • Briggs J. 1985. An exploratory study of farmers’ choice of crops in Central Sudan. Transactions of the Institute of British Geographers: 170–180. [CrossRef] [Google Scholar]
  • Caldas MM, Bergtold JS, Peterson JM, et al. 2014. Factors affecting farmers’ willingness to grow alternative biofuel feedstocks across Kansas. Biomass Bioener 66: 223–231. [CrossRef] [Google Scholar]
  • Chen J, Yu Z, Ouyang J, Van Mensvoort M. 2006. Factors affecting soil quality changes in the North China Plain: a case study of Quzhou County. Agric Syst 91(3): 171–188. [Google Scholar]
  • Department of Agriculture, Forestry and Fisheries (DAFF). 2012. A framework for the development of smallholder farmers through cooperatives development. Pretoria: Department of Agriculture, Forestry and Fisheries. [Google Scholar]
  • Department of Agriculture, Forestry and Fisheries (DAFF). 2018. Abstract of agricultural statistics. South African Department of Agriculture, Forestry and Fisheries. Available from http://www.daff.gov.za/Daffweb3/Portals/0/Statistics%20and%20Economic%20Analysis/Statistical%20Information/Abstract%202018.pdf. [Google Scholar]
  • Dube K. 2016. Implications of rural irrigation schemes on household economy. A case of Lower Gweru Irrigation Scheme, Zimbabwe. South African Journal of Agricultural Extension 44(1): 75–90. [Google Scholar]
  • Dury J, Garcia F, Reynaud A, Bergez J-E. 2013. Cropping-plan decision-making on irrigated crop farms: a spatio-temporal analysis. Eur J Agron 50: 1–10. [Google Scholar]
  • Free State Freight Transport Data Bank (FTDB). 2008. Grain and seed production. Available from http://www.freetrans.gov.za/FTD/fs/industries/grain_seeds/index.html (accessed November 2019). [Google Scholar]
  • Greig L. 2009. An analysis of the key factors influencing farmer’s choice of crop, Kibamba Ward, Tanzania. J Agric Econ 60(3): 699–715. [Google Scholar]
  • Haile MG, Kalkuhl M, von Braun J. 2014. Inter- and intra-seasonal crop acreage response to international food prices and implications of volatility. Agric Econ 45(6): 693–710. [Google Scholar]
  • Harvest Choice. 2010. Available from http://harvestchoice.org/data/aez-16-class. [Google Scholar]
  • Henderson AD, Asselin-Balençon AC, Heller M, Lessard L, Vionnet S, Jolliet O. 2017. Spatial variability and uncertainty of water use impacts from US feed and milk production. Environmental Science & Technology 51(4): 2382–2391. [CrossRef] [PubMed] [Google Scholar]
  • Huang PC. 1986. Small peasant economy and social change in North China. Beijing, China: Zhonghua Book Company. [Google Scholar]
  • Jaffe J. 1989. Land use, soil degradation, and farmer decision-making: a Sondeo report of Cavalier, Despa, Kols, and Saut Mathurine, Haiti. Port-au-Prince, Haiti. [Google Scholar]
  • Katundu MA, Mhina ML, Mbeiyererwa AG. 2014. Socio-economic factors limiting smallholder groundnut production in Tabora region. Available from http://www.repoa.or.tz/documents/REPOA_RR_14.1.pdf (accessed on 15 May 2018). [Google Scholar]
  • Khapayi M, Celliers P. 2016. Factors limiting and preventing emerging farmers to progress to commercial agricultural farming in the King William’s Town area of the Eastern Cape Province, South Africa. S Afr J Agric Ext 44(1): 25–41. [Google Scholar]
  • Kinuthia KJ, Inot SK, Nakhone L. 2018. Factors influencing farmer’s choice of crop production response strategies to climate change and variability in Narok East sub-county, Kenya. Journal of Natural Resources and Development 08: 69–77. [Google Scholar]
  • Krupnik TJ, Schulthess U, Ahmed ZU, McDonald AJ. 2017. Sustainable crop intensification through surface water irrigation in Bangladesh? A geospatial assessment of landscape-scale production potential. Land Use Policy 60: 206–222. [CrossRef] [PubMed] [Google Scholar]
  • Lawas MCM, Luning HA. 1998. GIS and multivariate analysis of farmer’s spatial crop decision behaviour. NJAS Wageningen Journal of Life Sciences 46(2): 193–207. [Google Scholar]
  • Liancui W, Honghui C. 2010. Positive study on the effect of grain subsidy policy on farmers’ planting behavior. Technology Economics 6: 68–73. [Google Scholar]
  • Limpopo Department of Agriculture (LDA). 2012. The Mapping of Agricultural Commodity Production in the Limpopo province, South Africa. [Google Scholar]
  • Liu S, Zhang P, Marley B, Liu W. 2019a. The factors affecting farmers’ soybean planting behavior in Heilongjiang Province, China. Agriculture 9(9): 188. [CrossRef] [Google Scholar]
  • Liu S, Zhang P, Marley B, Liu W. 2019b. The factors affecting farmers’ soybean planting behavior in Heilongjiang Province, China. Agriculture 9(9): 188. [CrossRef] [Google Scholar]
  • Liu L. 2000. Labor location and agricultural land use in Jilin, China. Prof Geogr 52(1): 74–83. [Google Scholar]
  • Low A. 1986. Agricultural development in Southern Africa: farm household-economics and the food crisis. James Currey. [Google Scholar]
  • Mahon N, McGuire S, Islam MM. 2016. Why bother with Bere? An investigation into the drivers behind the cultivation of a landrace barley. J Rural Stud 45: 54–65. [Google Scholar]
  • Mandryk M, Reidsma P, Kanellopoulos A, Groot JC, van Ittersum MK. 2014. The role of farmers’ objectives in current farm practices and adaptation preferences: a case study in Flevoland, the Netherlands. Reg Environ Change 14(4): 1463–1478. [Google Scholar]
  • Mukwevho R, Anim F. 2014. Factors affecting small scale farmers in accessing markets: a case study of cabbage producers in the Vhembe District, Limpopo Province of South Africa. J Hum Ecol 48(2): 219–225. [Google Scholar]
  • Navarrete M, Le Bail M. 2007. SALADPLAN: a model of the decision-making process in lettuce and endive cropping. Agron Sustain Dev 27(3): 209–221. doi:10.1051/agro:2007009. [Google Scholar]
  • Negatu B, Vermeulen R, Mekonnen Y, Kromhout H. 2016. A method for semi-quantitative assessment of exposure to pesticides of applicators and re-entry workers: an application in three farming systems in Ethiopia. Ann Work Expo Health 60(6): 669–683. doi:10.1093/annhyg/mew022. [Google Scholar]
  • Oni SA, Nesamvuni AE, Odhiambo JJ, Dagada DC. 2012. Executive summary of a study of agricultural industry of Limpopo Province. South Africa: Centre for rural development: department of soil science. [Google Scholar]
  • Paul J, Sierra J, Causeret F, Guindé L, Blazy J-M. 2017. Factors affecting the adoption of compost use by farmers in small tropical Caribbean islands. J Clean Prod 142: 1387–1396. [Google Scholar]
  • Pereira L. 2017. Climate change impacts on agriculture across Africa. Oxford Research Encyclopedia of Environmental Science. [Google Scholar]
  • Popescu A, Alecu IN, Dinu TA, Stoian E, Condei R, Ciocan H. 2016. Farm structure and land concentration in Romania and the European Union’s agriculture. Agriculture and Agricultural Science Procedia 10: 566–577. [CrossRef] [Google Scholar]
  • Ravnborg HM, Rubiano JE. 2001. Farmers’ decision making on land use—the importance of soil conditions in the case of Río Cabuyal watershed, Colombia. Geografisk Tidsskrift-Danish Journal of Geography 101(1): 115–130. [CrossRef] [Google Scholar]
  • Ryder R. 2003. Local soil knowledge and site suitability evaluation in the Dominican Republic. Geoderma 111(3–4): 289–305. [Google Scholar]
  • Saito K, Linquist B, Keobualapha B, Shiraiwa T, Horie T. 2006. Farmers’ knowledge of soils in relation to cropping practices: a case study of farmers in upland rice based slash-and-burn systems of northern Laos. Geoderma 136(1–2): 64–74. [Google Scholar]
  • Schulze RE, Durand W. 2016. Maize yields over South Africa under historical and projected future climatic conditions. In: Schulze RE, ed. Handbook for farmers, officials and other stakeholders on adaptation to climate change in the agriculture sector within South Africa. Section C: Crops and Climate Change, Chapter C2. pp. 22. [Google Scholar]
  • Seo SN, Mendelsohn R. 2008. An analysis of crop choice: adapting to climate change in South American farms. Ecol Econ 67(1): 109–116. [Google Scholar]
  • Statistics South Africa. 2010. Mid-year population estimates. Available from http://www.scielo.org.za/scielo.php?script=sci_nlinks&ref=3619992&pid=S0301-603X201600010000300033&lng=en. [Google Scholar]
  • Statistics South Africa. 2012. Census 2011. Available from http://www.scielo.org.za/scielo.php?script=sci_nlinks&ref=3619994&pid=S0301-603X201600010000300034&lng=en. [Google Scholar]
  • Thamaga-Chitja JM, Morojele P. 2014. The context of smallholder farming in South Africa: towards a livelihood asset building framework. J Hum Ecol 45(2): 147–155. [Google Scholar]
  • Trochim W.M. 2006. Nonprobability sampling. Research methods Knowledge Base 1(1): 1–10. [Google Scholar]
  • Tuckman BW. 2000. Conducting educational research, 5th ed. Fort Worth, TX: Harcourt Brace. [Google Scholar]
  • Van Niekerk P. 2002. Product development as part of a positioning strategy for the hunting industry in the Eastern Cape. DTech thesis. Port Elizabeth: Port Elizabeth Technikon. [Google Scholar]
  • Wang T, Luri M, Janssen L, et al. 2017. Determinants of motives for land use decisions at the margins of the Corn Belt. Ecol Econ 134: 227–237. [Google Scholar]
  • Wauters E, Mathijs E. 2014. The adoption of farm level soil conservation practices in developed countries: a meta-analytic review. Int J Agric Resour Gov Ecol 10(1): 78–102. [Google Scholar]
  • Wu L, Cai H. 2010. Positive study on the effect of grain subsidy policy on farmers’ planting behavior. Technology Economics 29(6): 68–73. [Google Scholar]
  • Wu J, Murphy F, Garvey J, Ma W. 2015. The role of market participants in agricultural futures markets. Outl Agric 44(2): 97–108. [CrossRef] [Google Scholar]
  • Wu W, Yang P, Meng C, et al. 2008. An integrated model to simulate sown area changes for major crops at a global scale. Sci China D Earth Sci 51(3): 370–379. [CrossRef] [Google Scholar]
  • Yang L, Liu M, Lun F, Yuan Z, Zhang Y, Min Q. 2017. An analysis on crops choice and its driving factors in agricultural heritage systems—a case of Honghe Hani Rice Terraces System. Sustainability 9(7): 1162. [Google Scholar]
  • Yu J, Smith A, Sumner DA. 2016. The effects of the premium subsidies in the US federal crop insurance program on crop acreage (No. 333-2016-14232). [Google Scholar]
  • Zhang Y, Li X, Song W, Zhai L. 2016. Land abandonment under rural restructuring in China explained from a cost-benefit perspective. J Rural Stud 47: 524–532. [Google Scholar]

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