Projections of protein needs for animal consumption for 2010 and 2020
Compiled by JSG Joubert (February 2006)

  1. Introduction

    Four (4) different scenarios in Tables 1 to 4 reflect the projected protein needs for animal consumption for the periods 2010 and 2020.

    1. The period 2004 used as the base year for projections refer to the period 1 April 2004 to 31 March 2005.
    2. The protein needs for 2004 used as point of departure is 1 472 315 tons and includes 100 000 tons fishmeal and 104 400 tons poultry waste.
    3. The fishmeal and poultry by-products used were multiplied by 1.4 and 1.2 respectively to convert it into a soybean oilcake equivalent.
    4. To this end the focus is on the expected consumption of oilcake and the fishmeal and poultry by-products are subtracted from the projected protein consumption after it has been converted to an oilcake equivalent. For projection purposes the fishmeal and poultry by-products are pinned down against the base year quantities used.
    5. The four (4) scenarios involve the following:
      • High income-growth and keep protective tariffs in place;
      • High income-growth and phase out protective tariffs;
      • Low income-growth and keep protective tariffs in place;
      • Low income-growth and phase out protective tariffs.
    6. BER's population growth projections were used.
    7. The APR model (Briedenhann's model) was used to calculate the oilcake consumption ratio amongst the various species; and
    8. International market factors (for example supply and demand with regards to animal products and the derivative demand for protein for animal consumption and the effect thereof on prices in real terms) were taken into consideration.

    Table 1

    Protein needs projections for 2010 and 2020 for four (4) different scenarios ¹
    Scenario Base year 2004 Annual growth
    from base year    		 2010 Annual growth
    from base year    		 2020
    Tonnes % Tonnes % Tonnes
    Scenario 1 1 472 315 2.46 1 703 735 2.15 2 068 449
    Scenario 2 1 472 315 0.13 1 483 793 1.13 1 762 883
    Scenario 3 1 472 315 0.84 1 547 672 0.56 1 609 962
    Scenario 4 1 472 315 -1.13 1 375 649 -0.17 1 433 381

    ¹   Scenario 1: High income-growth and keep protective tariffs in place.
    Scenario 2: High income-growth and phase out protective tariffs.
    Scenario 3: Low income-growth and keep protective tariffs in place.
    Scenario 4: Low income-growth and phase out protective tariffs.

    For reference purposes a few variables used in the Protein Needs projections are indicated below in Table 2.

    Table 2

    Income growth and population growth
    Asians Urban Blacks Rural Blacks Coloureds Whites
    % per annum
    Low income growth 1.0 0.0 -2.0 0.0 0.0
    High income growth 2.8 2.8 0.8 2.8 1.5
    Asians Urban Blacks Rural Blacks Coloureds Whites
    % per annum
    Population growth until 2011 1.42 1.31 0.57 0.18 1.14
    Population growth until 2016 1.14 1.08 0.53 0.02 0.93
    Population growth until 2021 0.95 0.90 0.43 -0.08 0.77
    Population growth until 2026 0.81 0.76 0.33 -0.16 0.63
    Population growth until 2031 0.69 0.64 0.24 -0.22 0.52

  2. Projected protein requirements

    To determine if local production of oilcake is keeping tread with the projected consumption of oilcake it has to be decided which scenario of the four projections best resembles reality. Given the current economic parameters and what is anticipated in the medium term, the high income-growth figures portrayed in Table 2 closer reflects reality. According to experts it is also highly unlikely that protective tariffs currently applicable to livestock products will be phased out over the period in question. As a result the projected protein needs according to scenario 1 will therefore be used to compare the progress of the locally produced oilcake.

    1. Projected oilcake needs for 2010 and 2020 is the projected protein needs minus the fishmeal component (100 000 x 1.4 = 140 000 tons oilcake) and minus the poultry by-products (104 400 x 1.2 = 125 280 ton oilcake).
    2. In the base year 2004/2005 the actual consumption of oilcake was 1 212 593 tons and local production 416 736 tons that resulted in a local production of 34.4% in terms of total consumption. During 2003/2004 this percentage was 43.6% and for the 2005/2006 season it is estimated at 39.4%. The extent of locally produced oilcake is determined by various factors for instance climate and therefore the average of the three (3) seasons is used in this exercise.

    Table 3

    Locally produced oilcake as percentage of total consumption
    Period Locally produced oilcake Percentage of total consumption
    Tonnes %
    2003/2004 489 413 43.6
    2004/2005 416 736 34.4
    2005/2006 472 221 39.4
    Average 459 457 37.9

  3. Based on information gathered from A and B answers can be given to the following questions

    1. At what rate must local production of oilcake grow annually to still be able to supply in 38% of the total needs?
    2. At what rate must local production of oilcake grow annually in order to reduce the current gap between local production and consumption?
    3. If local oilcake production continues to grow at the historical growth rate, what percentage will it constitute of the 2010 and 2020 projected oilcake needs?

    Table 4

    Locally produced oilcake as percentage of projected oilcake needs 2010 (projected consumption is 1 438 455 tons)
    Local production growth rate per annum Oilcake quantities Percentage of projected consumption
    % Tonnes %
    2.94 546 613 38
    11.08 863 073 60
    16.54 1 150 764 80
    20.95 1 438 455 100
    Local growth at historical rate
    3.69 571 072 39.7

    Table 5

    Locally produced oilcake as percentage of projected oilcake needs 2020 (projected consumption is 1 803 169 tons)
    Local production growth rate per annum Oilcake quantities Percentage of projected consumption
    % Tonnes %
    2.53 685 204 38
    5.50 1 081 901 60
    7.41 1 442 535 80
    8.92 1 803 169 100
    Local growth at historical rate
    3.69 820 544 45.5

    Table 6

    Production and consumption trends of protein commodities
    Commodity 96/97 97/98 98/99 99/00 00/01 01/02 02/03 03/04 04/05 05/06 Average
    annual
    growth %
    Tonnes
    Fishmeal consumption 196 039 187 374 96 267 127 386 142 848 118 414 82 988 127 000 127 000 127 000 -0.29
    Fishmeal production 78 430 100 000 88 340 95 000 110 000 128 000 123 000 122 000 132 000 121 000 5.63
    Fishmeal imports 117 809 87 374 7 927 32 386 32 848 0 0 0 0 6 000 22.30
    Oilcake consumption 832 600 785 401 1 080 354 1 063 338 1 021 862 1 149 224 1 210 396 1 121 460 1 212 593 1 200 000 4.88
    Oilcake production 400 675 319 006 493 581 554 903 514 020 482 448 472 311 489 413 416 736 472 221 3.69
    Oilcake imports 431 925 466 395 586 773 508 435 507 842 666 776 738 085 632 047 795 857 727 779 7.26
    Area planted Ha
    Soybeans 87 000 125 000 130 500 93 787 134 150 124 150 100 150 135 000 150 000 208 090 13.43
    Sweet Lupins NA NA 16 300 19 000 14 705 14 785 11 000 10 100 7 100 14 100 4.23
    Canola NA NA 17 000 25 000 19 145 27 000 33 000 44 200 44 250 41 200 16.29
    Production Tonnes
    Soybeans 76 806 120 000 200 900 188 367 148 720 209 705 216 000 136 500 220 000 272 500 20.96
    Sweet Lupins NA NA 9 000 13 000 17 360 16 338 11 700 4 040 3 950 14 100 33.28
    Canola 8 734 11 000 21 000 23 000 26 549 25 750 37 975 40 770 32 000 45 310 23.75

    Figure 1

    Oilcake consumption, production and imports

    Graph showing oilcake consumption, production and imports

    Figure 2

    Area planted and production of protein commodities

    Graph showing areas and production of protein commodities

  4. A few conclusions

    1. The historical rate at which the annual production of local oilcake has increased will succeed in maintaining the gap between production and consumption of oilcake until 2010.
    2. If the historical annual growth rate of locally produced oilcake can be sustained until 2020, the gap between production and consumption will be marginally improved.
    3. The area planted with proteinaceous crops is influenced in the medium to long term by several factors, of which an important role is played by the relative price ratios among commodities and local as well as international market factors. Climate also plays an important role in the short term. Another limitation is land and it is questionable if the historical growth rate of 3.69% can be sustained in the longer term.
    4. Biodiesel plants will increase the level of oilcake production significantly, which will result in an increase in oilcake production in the short to medium term. It is still questionable, however, if a higher than historical growth rate can be sustained in the long term.
    5. The PRF's task to promote the production of proteinaceous commodities was hampered by factors on the international market (increasing stock, record planting and supply, unfavourable exchange rates, etc.) that had a negative effect on local prices for proteinaceous seed. Relative unfavourable maize and wheat prices, however, were used to put an intensified promotional campaign into action.
    6. Table 6 provides information on historical production and consumption trends of protein commodities. A positive aspect is the area increase of soybeans and canola on an annual basis at 13.43% and 16.29% respectively. More important is the respective increase of quantities produced on an annual basis with 20.96% and 23.75%. This indicates that the quantities have increased in proportion higher to that of the area. Even though climate had a definite influence, I would also like to attribute it to the positive impact of research and transfer of technology.
    7. The noteworthy increase in area planted with lupins during the past season has turned the previously negative historical rate into a positive growth rate. The PRF trusts that this trend will be sustainable.
    8. Seeing that land is a limitation and negative factors on the international market, the PRF will have to emphasise research that will promote productivity as well as improved quality (for instance higher protein per mass and per area). As a result the crop involved will become more competitive relative to competing crops and also yield higher profit margins per unit. In addition the promotion of these crops must enjoy a higher priority as a rotational crop.

(Based on certain information generated from the Nieuwoudt/McGuigan Model)