Quantifying yield gaps for rain-fed maize (Zea Mays) in South Africa: A bottom-up approach
| dc.contributor.advisor | Le Roux, Marcellous | en_ZA |
| dc.contributor.advisor | De Vries, Sander | en_ZA |
| dc.contributor.author | Mandigora, Brian George | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of AgriSciences. Dept. of Agronomy. | en_ZA |
| dc.date.accessioned | 2018-02-28T13:03:24Z | |
| dc.date.accessioned | 2018-04-09T07:08:52Z | |
| dc.date.available | 2018-02-28T13:03:24Z | |
| dc.date.available | 2018-04-09T07:08:52Z | |
| dc.date.issued | 2018-03 | |
| dc.description | Thesis (MScAgric)--Stellenbosch University, 2018. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: Maize (Zea mays) is an important crop that supports livelihoods in South Africa (RSA) and most of the Sub-Saharan Africa (SSA) region. Currently, RSA is the biggest maize producer in the region, exporting to countries like Zimbabwe, Botswana and Malawi. However, the anticipated increase of the world population to 9 billion people by 2050 presents new challenges for resource supply and management, including food supply. The bulk of this population increase is expected to occur in the SSA region, and feeding this bigger population without compromising land and water for other needs is a priority. This thesis presents a yield gap study that seeks to ascertain the levels to which South African yellow and white maize yields can be increased on more or less the same spatial scale by applying the Global Yield Gap and Water Productivity Atlas (GYGA) protocol. The South African maize producing regions were subdivided into five key agro-climatic zones, referred to as designated climate zones (DCZs), which are explained by the GYGA Extrapolation Domain (GYGA-ED) zonation scheme. Within these DCZs, eight Reference Weather Stations (RWS) were selected to represent the South African maize production zones. Using Geographic Information Systems (GIS), buffer zones of 100km radius were delineated around the RWS, and were clipped according to CZs to avoid overlap. Climatic, edaphic and crop management data were collected for each of the RWS buffer zones. These data were used to simulate water-limited potential yields (Yw) for yellow and white maize for the three main soil types within the buffer zone under specific crop management practices from 2000 to 2014. Data for actual yields achieved by farmers during the same 15-year period (Ya) were sourced from the GrainSA database, and was corrected for moisture content. The Hybrid-Maize model was used to simulate Yw for yellow and white maize for the period from 2000 to 2014. The national yield gap (Yg) was calculated as the difference between the weighted values of Yw and Ya (Yg = Yw – Ya). The relative yield percentage (Y%) was also calculated as Y% = Ya/Yw x 100. This study found that for South Africa, the yield gaps between average farmers’ yields and simulated water limited potential yields were 2.70 tha-1 for yellow maize and 3.14 tha-1 for white maize, which represent 52.99% and 57.88% of the white and yellow maize yields, respectively that are achievable as simulated by Hybrid-Maize. The exploitable yield gap (Ye), which is calculated as Ye = 0.8Yw – Ya, is the yield that can realistically be achieved by farmers when economic and bio-physical limitations are considered. If the Ye is to be met by South African maize farmers, this would increase annual production by about 1.5 million tonnes (yellow maize) and 3 million tonnes (white maize), which indicate a total maize yield increase of 42%, translating to over R9 billion in additional gross income for farmers. Therefore, there is considerable potential for RSA to increase maize production on existing farmland using current crop management practices, which could provide national and regional food security. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Mielies (Zea mays) is ‘n belangrike gewas wat die lewensbestaan van verskeie mense in Suid-Afrika (RSA) en ‘n groot deel mense van die Sub-Sahara Afrika (SSA) streek onderhou. Huidiglik, is RSA die grootste mielie produsent in die streek en voer uit na lande soos Zimbabwe, Botswana en Malawi. Hoewel, die verwagte verhoging in die wêreld bevolking tot 9 miljard mense by 2050 hou nuwe uitdagings in vir voorsiening en bestuur van voedsel. Die grootste deel van die bevolkingsgroei word in SSA verwag en om die groter bevolking te voed sonder om grond- en waterbronne ten koste van ander moontlike gebruike te belemmer, is ‘n prioriteit. Die tesis het onderneem om ‘n opbrengste gaping studie te doen om die vlakke waartoe Suid-Afrikaanse geel- en wit mielie opbrengste verhoog kan word op min of meer dieselfde ‘ruimtelike’ skaal volgens die Globale Opbrengste Gaping en Water Produktiwiteits Atlas (‘GYGA’) protokol kon vasstel. Die mielie-produserende streke van RSA is onderverdeel in vyf sleutel agro-klimatologiese sones, wat na verwys word na as die gereserveerde klimaatsones (‘DCZs), en onderstreep word deur die GYGA-Ekstrapolasie Domein (GYGA-ED) sonasie skema. Agt verwysings weerstasies (‘RWS’) was gekies binne hierdie DCZs wat verteenwoordigend is van RSA se mielie-produserende streke. Deur gebruik te maak van Geografiese Informasie Stelsels (GIS), was buffer sones binne ‘n 100 km radius binne afgebakende ‘RWS’ opgestel, wat dan voorts gesnoei is volgens die klimaatsones om oorvleueling uit te skakel. Klimaats-, grond- en gewas bestuur data is geneem vir elke ‘RWS’ buffer sone. Die data was gebruik om water-beperkte potensiële opbrengste (Yw) vir geel- en wit mielies vir die drie hoof grondtipes binne die buffersones onder sekere spesifieke gewas bestuurspraktyke vanaf 2000 to 2014 te simuleer. Data vir die werklike opbrengste (Ya) soos deur boere vermag vir dieselfde 15-jaar tydperk is verkry vanaf die GraanSA databasis. Die ‘Hybrid-Maize’ model was gebruik om die Yw te simuleer vir geel- en wit mielies vir die periode tussen 2000 en 2014. Die nasionale opbrengste gaping (Yg) was bereken as die verskil tussen die vasgestelde waardes van Yw en Ya (Yg = Yw – Ya). Die relatiewe persentasie (Y%) is bereken volgens Y% = Ya/Yw x 100. Die studie het bevind dat die opbrengste gaping, dus die tussen die gemiddelde werklike opbrengste deur boere en gesimuleerde water-beperkte potensiële opbrengste, 2.70 t.ha-1 vir geel mielies en 3.14 t.ha-1 vir wit mielies was in Suid-Afrika, wat ‘n 57.88% en ‘n 52.99% van die wit- en geel mielies opbrengste, respektiewelik verteenwoordig soos gesimuleer deur ‘Hybrid-Maize’. Die uitbytbare opbrengste gaping (Ye), wat bereken was as Ye = 0.8Yw – Ya, verwys na die opbrengs wat realisties bereik kan word deur boere, wanneer ekonomiese en bio-fisiese beperkings in ag geneem word. Indien die Ye bereik kan word deur Suid-Afrikaanse boere, sal dit jaarlikse produksie verhoog tot 1.5 miljoen ton (geel mielies) en 3 miljoen ton (wit mielies), wat ‘n totale mielie opbrengs verhoging van 42% beteken, en indien omskryf word, tot oor R9 miljard in addisionele inkomste vir boere sal behaal. Dus, daar is aansienlike potensiaal vir RSA om mielie produksie te verhoog op bestaande boerdery landgoed indien bestaande gewas bestuurspraktyke gebruik word, wat sal lei tot nasionale en plaaslike voedsel sekuriteit. | af_ZA |
| dc.format.extent | 99 pages : illustrations, maps | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/10019.1/103762 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject | Zea maize -- South Africa | en_ZA |
| dc.subject | (Corn or) maize -- production economics agricultural | en_ZA |
| dc.subject | Maize -- production control | en_ZA |
| dc.subject | UCTD | en_ZA |
| dc.title | Quantifying yield gaps for rain-fed maize (Zea Mays) in South Africa: A bottom-up approach | en_ZA |
| dc.type | Thesis | en_ZA |