A risk-based planting schedule design for a Sandveld potato farm: case study Taaiboskraal farm

Hayward, Julie Christy (2017-03)

Thesis (MScAgric)--Stellenbosch University, 2017.

Thesis

ENGLISH SUMMARY : Risk in agriculture can primarily be classified systematically according to, the type, frequency and severity of an event. The outcome of the relevant unknown event determines the consequences of the chosen option. To manage risk, the prospective risk first needs to be identified. The interlink ages between the different sources of risk affects the farmers’ overall exposure to risk. An integrated risk assessment therefore helps to identify numerous sources of risk and leads to more efficient decision making. Managing risk does not mean removing risk: rather, it means ensuring that the risk that could occur is at an acceptable level for the decision maker. The best method of managing risk depends upon the nature of the risk involved and the appetite for risk. Potato producers in the Sandveld, farm in conditions of uncertainty. Farmers therefore constantly have to find ways in which to reduce their exposure. The purpose of this research was to determine an optimal four-year planting schedule for a farmer in the Elands Bay region in the Sandveld using Taaiboskraal farm as a case study. There are two predominant electricity tariffs that can be used, namely Ruraflex and Landrate. The farmer can choose between the Cape Town, Durban, Pretoria and Johannesburg fresh produce markets. The main objective of this research was therefore to evaluate the best planting schedule. This would be over four years for Taaiboskraal Farm in the Sandveld regarding the decision maker’s appetite for risk, preferred market and optimal electricity tariff. To obtain the gross margins for each pivot in each state of nature, the potential yields had to be determined using the LINTUL model. The irrigation costs, area and yield dependent costs needed to be determined using a cash flow model. The real prices were obtained for each of the four markets. Once the gross margins were determined, the correlation between prices and yield were determined using multivariate estimates (MVE). Stochastic Efficiency with Respect to a Function (SERF) is the most recent approach in ranking risky alternatives in terms of certainty equivalents (CE) for a specified range of attitudes to risk based on expected utility theory. The SERF model was then used to ascertain the optimal planting schedule after having determined the risk preference of the decision maker. The results indicate that Ruraflex is the best electricity tariff for Taaiboskraal farm. It would therefore not be a good investment to pay the fees to switch to Landrate. When the farmer could choose between the Cape Town, Durban, Pretoria and Johannesburg markets, the Cape Town market was the predominant market of choice. An optimal four-year planting schedule was determined taking into account all the possible opportunity costs.

AFRIKAANSE OPSOMMING : Risiko in die landbou kan hoofsaaklik sistematies geklassifiseer word ten opsigte van die tipe, frekwensie en omvang van 'n gebeurtenis. Die uitslag van die betrokke onbekende gebeurtenis bepaal dus die gevolge van die gekose opsie. Ten einde risiko te bestuur moet die voornemende risiko eers geidentifiseer word. Die interafhanklikhede tussen die verskillende bronne van risiko beinvloed die produsent se algehele blootstelling aan risiko. 'n Geintegreerde risiko-assessering help dus om verskeie bronne van risiko te herken en lei tot meer doeltreffende besluitneming. Die bestuur van risiko beteken nie die verwydering van risiko nie. Eerder beteken dit om te verseker dat die risiko wat kan voorkom op 'n aanvaarbare vlak vir die besluitnemer is. Die beste metode van bestuur van risiko hang af van die aard van die betrokke risiko en die besigheid/eienaar se risiko-aptyt. Aartappelprodusente in die Sandveld boer in toestande van onsekerheid en hulle moet voortdurend maniere vind om hul blootstelling te beperk. Die doel van hierdie navorsing is om 'n optimale vier jaar plant skedule te bepaal vir 'n boer in die Elandsbaai streek in die Sandveld met behulp van Taaiboskraal plaas as 'n gevallestudie. Daar is twee elektrisiteitstariewe wat van toepassing is: naamlik Ruraflex en Landrate. In die Sandveldkanboere slegs een keer elke vier jaar ʼn land gebruik om aartappels te plant. Die boer is in staat om te kies tussen die Kaapstad, Durban, Pretoria en Johannesburg se varsproduktemarkte. Die hoofdoel van hierdie navorsing is dus om die beste plantskedule oor vier jaar vir Taaiboskraal plaas in die Sandveld te evalueer ten opsigte van aptyt van die besluitnemer vir risiko, verkose mark en optimale elektrisiteitstarief. Om die bruto marges vir elke spilpunt vas te stel in elke staat van die natuur en om potensiele opbrengste te bepaal is die LINTUL model gebruik. Die besproeiingskoste, omgewing en opbrengs faktore is bepaal met behulp van 'n kontantvloei model. Die werklike pryse behaal vir elk van die vier markte is aangeteken. Die Stochastic Efficiency with Respect to a Function (SERF) model is die mees onlangse benadering tot die rangskikking van riskante alternatiewe in terme van sekerheidsekwivalente (CE) vir 'n bepaalde reeks van verhoudings. Die SERF model is daarna gebruik om die optimale plant skedule vir die plant siklus te bepaal nadat die risiko voorkeur van die besluitnemer bepaal is. Die uitslag van hierdie studie dui daarop dat Ruraflex die beste elektrisiteitstarief vir Taaiboskraal plaas is, en daarom sou dit nie 'n goeie belegging wees om die fooie te betaal om oor te skakel na Landratenie. Wanneer die boer tussen die Kaapstad, Durban, Pretoria en Johannesburg se markte kies is die Kaapse mark die oorheersende mark van keuse. 'n Optimale vier jaar plant skedule is vasgestel en geoptimaliseer met inagneming van al die moontlike geleentheidskoste.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/100845
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