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dc.contributor.advisorSteyn, A. S.
dc.contributor.advisorCeronio, G. M.
dc.contributor.authorNape, Kholofelo Moses
dc.date.accessioned2015-09-08T08:51:34Z
dc.date.available2015-09-08T08:51:34Z
dc.date.copyright2011-11
dc.date.issued2011-11
dc.date.submitted2011-11
dc.identifier.urihttp://hdl.handle.net/11660/1188
dc.description.abstractEnglish: In order to meet the food requirements of an ever-growing population, agricultural production needs to increase. This is especially true for maize production in South Africa as it is the staple food for a large portion of the rural indigenous population. Climate variability is one of the major causes of volatility in agricultural production and causes uncertainty for maize production at the subsistence level. Small-scale farmers within the Modder River Catchment have a poor quantative understanding of seasonal rainfall and their relationship to their management strategies. In countries prone to high seasonal climatic variability, crop growth models such as APSIM can be used to assist farmers in making decisions regarding the suitability of different management strategies. This means that climate forecasts could be translated into crop production, while alternative management practices would be associated with different economic outcomes. The opportunity arose to aid these farmers by optimising rainfed maize production. Subsequently, the objective of this study was to produce an advisory for small-scale rainfed maize farmers in the Modder River Catchment. Historical rainfall data (1950-1999) from selected rainfed maize production areas within the Modder River Catchment were used to calculate the seasonal rainfall totals for October to December (OND) and January to March (JFM). During dry seasons, the expected rainfall totals was less than 101.0 and 147.5 mm for OND and JFM, respectively. During wet seasons, the expected rainfall totals was more than 204.0 and 267.5 mm for OND and JFM, respectively. Recommended management practices were employed to validate APSIM using observed environmental and maize yield data for the 1980/81 to 2004/2005 seasons in the vicinity of Bloemfontein. Maize yields were simulated using two medium growth period cultivars (PAN 6479 and Pioneer 3237) under different planting dates, plant population densities, fertiliser applications and weeding frequencies. The model simulated PAN 6479 better than Pioneer 3237. For Pan 6479, the best set of management practices corresponded to a R2 of 0.66, D-index of 0.89, modelling efficiency of 0.59 and RMSEu/RMSE of 0.88. For Pioneer 3237, the modelling efficiency values under different management practices were negative. Stepwise linear regression was used to select those yield predictors that adhered to a partial R2 value greater than 0.0001 at a significance level of 0.15. In general it‟s usually better to plant early (November) regardless of the seasonal rainfall scenarios. Advisories were set up to convey information regarding the best, second best and worst set of management practices under each seasonal rainfall scenario. These advisories also include the related field costs along with potential yields and economic benefits at the 25, 50 and 75% probability levels for each set of management practices. For example, during AN-AN rainfall conditions, the best set of management practices involved planting during 16-30 November and 1-15 November, weeding twice, 50 and 75 kg ha-1 N and using 21 000 and 18 000 plants ha-1 for PAN 6479 and Pioneer 3237, respectively. Farmers would spend R1 798 ha-1 on field costs when planting PAN 6479, while obtaining a yield of 2 854 kg ha-1 and making a profit of R1 972 ha-1 at the 50% probability level. For Pioneer 3237 the field costs would amount to R2 338 ha-1, while realising a yield of 4 232 kg ha-1 resulting in a profit of R3 253 ha-1 at the same probability level. The recommended management practices under various seasonal rainfall scenarios could assist small-scale rainfed maize farmers to increase their yields and maximise the associated profit. Unfortunately, site-specific calibration of APSIM is required against observed sets of climate, soil and yield data for which the associated management practices are known before these advisories can be used by extension officers to advise small-scale farmers within the Modder River catchment.en_ZA
dc.description.abstractAfrikaans: Landbouproduksie sal moet toeneem om in die voedselbehoeftes van „n steeds groeiende bevolking te voldoen. Dit is veral waar in die geval van mielieproduksie in Suid-Afrika aangesien dit die stapelvoedsel vir „n groot gedeelte van die landelike inheemse bevolking uitmaak. Klimaatveranderlikheid is een van die hoofoorsake van onstabiliteit in landbouproduksie en bedreig mielieproduksie op bestaansvlak. Kleinskaalse boere in die Modderrivier-opvanggebied weet nie altyd hoe om inligting rakende die seisoenale reënval in hul bestuurspraktyke te inkorporeer nie. In lande wat onder hoë seisoenale klimaatveranderlikheid gebuk gaan, kan gewasgroeimodelle soos APSIM gebruik word om boere te help om besluite te neem rakende die geskiktheid van verskillende bestuurstrategieë. Dit beteken dat klimaatvoorspellings gebruik kan word om gewasproduksie te skat, terwyl alternatiewe bestuurspraktyke met verskillende ekonomiese uitkomste geassosieer sal word. Die geleentheid het homself voorgedoen om hierdie boere by te staan deur droëland mielieproduksie te optimeer. Gevolglik was die doel van hierdie studie om „n advieshulpmiddel vir kleinskaalse droëland mielieboere in die Modderrivier-opvanggebied daar te stel. Historiese reënvaldata (1950-1999) van gekose droëland mielieproduksie-areas binne die Modderrivier-opvanggebied is gebruik om die seisoenale reënvaltotale vir Oktober tot Desember (OND) en Januarie tot Maart (JFM) te bereken. Gedurende droë seisoene was die verwagte reënvaltotale respektiewelik minder as 101.0 en 147.5 mm vir OND en JFM. Gedurende nat seisoene was die verwagte reënvaltotale respektiewelik meer as 204.0 en 267.5 mm vir OND en JFM. Aanbevole bestuurspraktyke is aangewend om APSIM te verifieër aan die hand van waargenome omgewingsdata en mielie-opbrengsdata vir die 1980/81 tot 2004/2005 seisoene in die omgewing van Bloemfontein. Mielie-opbrengste is gesimuleer vir twee medium-groeier kultivars (PAN 6479 en Pioneer 3237), onder verskillende plantdatums, plantbevolkingsdigthede, kunsmistoedienings en onkruidbeheer-frekwensies. Die model het PAN 6479 beter as Pioneer 3237 gesimuleer. Vir Pan 6479 het die beste stel bestuurspraktyke ooreengestem met „n R2 van 0.66, D-indeks van 0.89, modelleringseffektiwiteit van 0.59 en RMSEu/RMSE van 0.88. Die modelleringseffektiwiteitswaardes vir Pioneer 3237 was negatief onder verskillende bestuurspraktyke. Stapsgewyse lineêre regressie is gebruik om daardie opbrengsvoorspellers te kies wat voldoen het aan „n gedeeltelike R2-waarde groter as 0.0001 by „n betekenisvlak van 0.15. In die algemeen is dit normaalweg beter om vroeër te plant (November) ongeag die seisoenale reënvalscenario. Advieshulmiddels is opgestel om inligting rakende die beste, tweede beste en slegste stel bestuurspraktyke onder elke seisoenale reënvalscenario weer te gee. Hierdie advieshulpmiddels sluit ook in die verwante veldkoste tesame met die potensiële opbrengste en ekonomiese voordele by die 25, 50 en 75% waarskynlikheidsvlakke vir elke stel bestuurspraktyke. Byvoorbeeld, gedurende bo-normale gevolg deur bo-normale reënvaltoestande het die beste stel bestuurspraktyke behels dat daar respektiewelik aangeplant word gedurende 16-30 November en 1-15 November, onkruidbeheer twee maal toegepas word, 50 en 75 kg ha-1 N toegedien word en 21 000 en 18 000 plante ha-1 gebruik word vir PAN 6479 en Pioneer 3237. Boere sal R1 798 ha-1 aan veldkostes spandeer wanneer hul PAN 6479 aanplant, terwyl hul „n opbrengs van 2 854 kg ha-1 kon inbring en „n wins van R1 972 ha-1 maak teen die 50% waarskynlikheidsvlak. Vir Pioneer 3237 sou die veldkoste sowat R2 338 ha-1 beloop teenoor „n opbrengs van 4 232 kg ha-1 wat sou lei tot „n wins van R3 253 ha-1 teen dieselfde waarskynlikheidsvlak. Die aanbevole bestuurspraktyke onder verskeie seisoenale reënvalscenario‟s kan droëland mielieboere in staat stel om hul opbrengste te vergroot en die meegaande wins te maksimeer. Voordat hierdie advieshulpmiddels deur voorligtingsbeamptes gebruik kan word om kleinskaalse boere in die Modderrivier-opvanggebied te adviseer, word ʼn punt-spesifieke kalibrasie van APSIM teenoor waargenome stelle klimaat-, grond- en opbrengsdata benodig waarvoor die meegaande bestuurspraktyke bekend is.af
dc.description.sponsorshipWater Research Commission (WRC)en_ZA
dc.description.sponsorshipInkaba yeAfricaen_ZA
dc.language.isoenen_ZA
dc.publisherUniversity of the Free Stateen_ZA
dc.subjectSmall-scale farmersen_ZA
dc.subjectRecommended management practicesen_ZA
dc.subjectClimate variabilityen_ZA
dc.subjectEconomic analysisen_ZA
dc.subjectCrop growth modelen_ZA
dc.subjectCorn -- Breeding -- South Africa -- Free Stateen_ZA
dc.subjectCorn -- Climate factors -- South Africa -- Free Stateen_US
dc.subjectCrops and climateen_ZA
dc.subjectDissertation (M.Sc.Agric. (Soil, Crop and Climate Sciences))--University of the Free State, 2011en_ZA
dc.titleUsing seasonal rainfall with APSIM to improve maize production in the Modder River catchmenten_ZA
dc.typeDissertationen_ZA
dc.rights.holderUniversity of the Free Stateen_ZA


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