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2020-08-12Zeitschriftenartikel DOI: 10.3390/su12166528
An Economic Comparison between Alternative Rice Farming Systems in Tanzania Using a Monte Carlo Simulation Approach
dc.contributor.authorKadigi, Ibrahim
dc.contributor.authorMutabazi, Khamaldin D.
dc.contributor.authorPhilip, Damas
dc.contributor.authorRichardson, James W.
dc.contributor.authorBizimana, Jean-Claude
dc.contributor.authorMbungu, Winfred
dc.contributor.authorMahoo, Henry F.
dc.contributor.authorSieber, Stefan
dc.date.accessioned2020-09-14T12:05:50Z
dc.date.available2020-09-14T12:05:50Z
dc.date.issued2020-08-12none
dc.date.updated2020-09-02T19:08:16Z
dc.identifier.urihttp://edoc.hu-berlin.de/18452/22622
dc.description.abstractTanzania is the second-largest producer of rice (Oryza sativa) in Eastern, Central, and Southern Africa after Madagascar. Unfortunately, the sector has been performing poorly due to many constraints, including poor agricultural practices and climate variability. In addressing the challenge, the government is making substantial investments to speed the agriculture transformation into a more modernized, commercial, and highly productive and profitable sector. Our objective was to apply a Monte Carlo simulation approach to assess the economic feasibility of alternative rice farming systems operating in Tanzania while considering risk analysis for decision-makers with different risk preferences to make better management decisions. The rice farming systems in this study comprise rice farms using traditional practices and those using some or all of the recommended system of rice intensification (SRI) practices. The overall results show 2% and zero probability of net cash income (NCI) being negative for partial and full SRI adopters, respectively. Meanwhile, farmers using local and improved seeds have 66% and 60% probability of NCI being negative, correspondingly. Rice farms which applied fertilizers in addition to improved seeds have a 21% probability of negative returns. Additionally, net income for rice farms using local seeds was slightly worthwhile when the transaction made during the harvesting period compared to farms applied improved varieties due to a relatively high price for local seeds. These results help to inform policymakers and agencies promoting food security and eradication of poverty on the benefits of encouraging improved rice farming practices in the country. Despite climate variability, in Tanzania, it is still possible for rice farmers to increase food production and income through the application of improved technologies, particularly SRI management practices, which have shown a promising future.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectriceeng
dc.subjectmanagement practiceseng
dc.subjectriskeng
dc.subjectMonte Carlo simulationeng
dc.subjectstochastic variableseng
dc.subjectTanzaniaeng
dc.subject.ddc333.7 Natürliche Resourcen, Energie und Umweltnone
dc.subject.ddc690 Bau von Gebäudennone
dc.titleAn Economic Comparison between Alternative Rice Farming Systems in Tanzania Using a Monte Carlo Simulation Approachnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/22622-8
dc.identifier.doi10.3390/su12166528none
dc.identifier.doihttp://dx.doi.org/10.18452/21905
dc.type.versionpublishedVersionnone
local.edoc.container-titleSustainabilitynone
local.edoc.pages22none
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionLebenswissenschaftliche Fakultätnone
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameMDPInone
local.edoc.container-publisher-placeBaselnone
local.edoc.container-volume12none
local.edoc.container-issue16none
dc.description.versionPeer Reviewednone
local.edoc.container-articlenumber6528none
dc.identifier.eissn2071-1050
local.edoc.affiliationKadigi, Ibrahim L.; School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, Morogoro P.O. Box 3007, Tanzania, ibrahim.kadigi@sua.ac.tz Soil-Water Management Research Programme, Sokoine University of Agriculture, Morogoro P.O. Box 3003, Tanzania, ibrahim.kadigi@sua.ac.tznone
local.edoc.affiliationMutabazi, Khamaldin D.; School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, Morogoro P.O. Box 3007, Tanzania, khamaldin2011@gmail.comnone
local.edoc.affiliationPhilip, Damas; School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, Morogoro P.O. Box 3007, Tanzania, philip@sua.ac.tznone
local.edoc.affiliationRichardson, James W.; Department of Agricultural Economics, Texas A&M University, 600 John Kimbrough Blvd/AGLS Blg, College Station, TX 77843-2124, USA, jwrichardson@tamu.edunone
local.edoc.affiliationBizimana, Jean-Claude; Department of Agricultural Economics, Texas A&M University, 600 John Kimbrough Blvd/AGLS Blg, College Station, TX 77843-2124, USA, bizimanatex@tamu.edunone
local.edoc.affiliationMbungu, Winfred; Department of Engineering Sciences and Technology, Sokoine University of Agriculture, Morogoro P.O. Box 3003, Tanzania, winfredm@gmail.comnone
local.edoc.affiliationMahoo, Henry F.; Department of Engineering Sciences and Technology, Sokoine University of Agriculture, Morogoro P.O. Box 3003, Tanzania, mahoohenry@yahoo.comnone
local.edoc.affiliationSieber, Stefan; Leibniz-Centre for Agriculturald Landscape Research, Eberswalder Straße 84, 15374 Müncheberg, Germany, stefan.sieber@zalf.de Department of Agricultural Economics, Faculty of Life Sciences Thaer-Institute, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany, stefan.sieber@zalf.denone

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