Income and Cost Budgets for Summer Crops
2018/2019 season
Area coverage
Table 1.1 and Table 1.2 indicates the area of coverage and include the dryland and irrigated crops. The source of data and collaborators are also included.
Table 1.1Area | Dryland crops | Source and Collaborators |
---|---|---|
KwaZulu-Natal | ||
Bloedrivier | Maize and soybeans | GSA / BFAP / Individual farmers |
Mpumalanga | ||
Middelburg / Trichardt | Maize, soybeans and grain sorghum | GSA / BFAP / Individual farmers |
Ermelo | Maize and soybeans | GSA / BFAP / Individual farmers |
Eastern Free State | ||
Reitz region | Maize, soybeans, sunflower and dry beans | GSA / VKB / BFAP / Individual farmers |
Western / Northern Free State | ||
Wesselsbron (high potential) | Maize | GSA / Senwes / BFAP |
Bothaville | Maize | GSA / Senwes / BFAP |
Western / Northern Free State | Maize, soybeans, sunflower, groundnuts and grain sorghum | GSA / Senwes / BFAP |
North West | ||
Koster | Maize, soybeans and sunflower | GSA / NWK / BFAP / Individual farmers |
Lichtenburg | Maize, soybeans, sunflower and groundnuts | GSA / NWK / BFAP / Individual farmers |
Area | Irrigated crops | Source and Collaborators |
---|---|---|
Northern Cape | ||
GWK area | Maize, soybeans, groundnuts and sunflower (oil) | GWK / GSA / BFAP |
KwaZulu-Natal | ||
Bergville | Maize and soybeans | GSA / Individual farmers |
North West | ||
Britz / Northam / Koedoeskop | Maize, soybeans, sunflower and sorghum | GSA / NWK / Individual farmers |
Limpopo | ||
Loskop Irrigation Scheme | Maize and soybeans | GSA / Individual farmers |
Yield assumptions
Figure 1.1 and Figure 1.2 present the yield assumptions for dryland and irrigated crops. The assumptions represent target yields and crop input allocation is based on achieving the stipulated target yields. The respective target yields were determined in a round table discussion with industry experts.
Crop price assumptions
Annually, the Bureau for Food and Agricultural Policy (BFAP) publishes an outlook on agricultural production, consumption, prices and trade in South Africa over a 10-year period. The information presented is based on assumptions about a range of economic, technological, environmental, political, institutional, and social factors. The outlook is generated by the BFAP system of models. A number of critical assumptions have to be made for baseline projections. One of the most important assumption is that normal weather conditions will prevail in Southern Africa and around the world; therefore, yields grow constantly over the baseline as technology improves. Assumptions regarding the outlook on macroeconomic conditions are based on a combination of projections developed by the International Monetary Fund (IMF), the World Bank and the Bureau for Economic Research (BER) at Stellenbosch University. Baseline projections for world commodity markets were generated by FAPRI at the University of Missouri. Once the critical assumptions are captured in the BFAP system of models, the Outlook for all commodities is simulated within a closed system of equations. This implies that, for example, any shocks in the grain sector are transmitted to the livestock sector and vice versa. Therefore, for each commodity, important components of supply and demand are identified, after which an equilibrium is established through balance sheet principles by equalling total demand to total supply.
Figure 1.3 illustrates the commodity price assumptions for white maize, yellow maize, sorghum, sunflower and soybeans that were used in the summer crop budgets for the 2018/19 production season. The sensitivity analysis in the respective crop budgets makes provision for variation in price and yield and indicates the gross margin under each price and yield combination.
Input cost trends and assumptions
The firm depreciation in the Rand over the period from June to beginning September 2018 raises concerns on the cost for agricultural inputs for the 2018/19 production season. It is acknowledged that the depreciation provides support to domestic price levels, however it could be harmful in a scenario where the Rand appreciate towards the harvesting season. Figure 1.4 illustrates the recent increasing cost trends for key fertilisers and agricultural fuel in South Africa. Figure 1.5 presents a summary for input cost inflation assumptions for the period from 2017/18 to 2018/19 production seasons. It is important to note that intra-regional variation will occur, however, the estimates serve only as a guideline, based on trends observed in agricultural input markets.