DECLARATION 2- PUBLICATIONS
7.2 Model Calibration and Validation
7.2.3 Calibration of sugarcane yields
Knisel (1993) determined the per cent nitrogen content of the dry matter (cN) and crop yield (CY) from Equations 7.6 and 7.7 given below:
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cN c GRT c (7.6)
CY TDM GRT PY
DMR (7.7) where: cN = Demand nitrogen content of the crop;
GRT = Growth ratio expressed as a ratio of actual to potential LAI (base LAI);
c1 = is the Scale factor;
c2 = is the Shape factor;
CY = Crop yields;
TDM = Total Dry Matter;
DMR = Dry Matter Ratio and PY= Potential Yield.
Figure 7.12 shows the N concentration in plants as a function of plant maturity. Equations 7.6 and 7.7 show that the crop yields (CY) can be increased by either increasing the potential yield (PY) or lowering the demand N concentration (cN) through lowering of the scale factor c1.
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Figure 7.12: Demand nitrogen concentration as a function of growth ratio for sugarcane.
Solid line from original data base; dashed lines for the increased nitrogen demands.
From the initial runs the ACRU-NPS model was unable to predict sugarcane yields that were similar to the observed (actual) yields from the Mkabela Catchment (SASA, 2012). The simulated sugarcane yields from the model were lower than the observed sugarcane yields. It was also noted that the quarter fertilizer application rate produced similar yields to the base fertilizer application rate (Figure 7.13).
Figure 7.13: Comparison of sugar cane yield for various N fertilizer applications and potential yields, using values of c1 = 0.17 (initial), 0.325 (final) and 0.525. The dotted lines indicate the incremental crop yield for the different fertilizer applications compared to the use of no fertilizer.
0 1 2 3 4 5 6
0 0.2 0.4 0.6 0.8
Nitrogen Content, cN %
Growth Ratio (GRT)
Scaling - Up Demand Nitrogen Content in ACRU-NPSModel
c1 = 0.525 (1st trial, PY= 75t/ha) , c2 = - 0.686 c1 = 0.17 (original, PY = 67t/ha) , c2 = - 0.686 c1= 0.325 (final, PY = 126t/ha), c2 = - 0.686
0 5 10 15 20 25 30
0 10 20 30 40 50 60 70 80
High Base Low- 1/2 Low-1/4 Zero
Incremental crop yield, t/ha
Sugarcane yields, t/ha/yr
Fertilizer application rate Fertilizer application rate vs crop yields
c1= 0.525, Potential Yield = 75t/ha/yr c1= 0.17(original), Potential yield = 67t/ha/yr c1= 0.525, Potential Yield = 126t/ha/yr c1 = 0.325 (final), Potential Yield = 126t/ha/yr Incremental crop yields (final), kg/ha Incremental crop yields (original), kg/ha
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The following observations were made during the calibration of the ACRU-NPS model for the crop yield component (Figure 7.13):
Increasing the PY from 75t/ha to 126t/ha while maintaining c1 = 0.525 increased the simulated crop yields.
Lowering c1= 0.525 to c1 = 0.325 while maintaining the PY= 126t/ha increased the crop yields slightly.
The simulated base scenario average sugarcane yields of 67.5t/ha/yr for 50 years (1950- 1999) using c1 = 0.325 and PY = 126t/ha was comparable to the observed crop yields of 67.7t/ha for the Mkabela Catchment for the period 1997- 2011.
By comparing the original runs (c1 = 0.17, PY = 67t/ha) with the final runs (c1 = 0.325, PY =126t/ha), wider ranges in incremental crop yield is realised in the later as compared to the former when fertilizer rates are increased from low-1/2 towards high.
A sugarcane crop N55/805 on trials at the Agronomy Department in Mt Edgecombe SASA Station on a coastal red sand soil achieved a maximum crop yield of 142 t/ha/yr and the succeeding 12 month ratoon crops gave similar or slightly higher yields (Glover, 1972).
Figure 7.14 shows the ACRU-NPS model simulations using PY = 126t/ha and varying c1 values (0.17, 0.325, 0.525) for various fertilizer application rates. The simulated sugarcane yields responded in distinct ways:
c1 = 0.525, PY = 126t/ha: represents the highest N-concentration demand in the crop that results in highest N-stresses. This produces the lowest sugarcane yields among the three scenarios.
c1 = 0.325, PY = 126t/ha: represents intermediate N-concentration demand in the crop that results in intermediate N-stress and intermediate sugarcane yields.
c1 = 0.17, PY = 126t/ha: represents the lowest N-concentration demand in the crop which results in the lowest N-Stresses and hence highest sugarcane yields among the three scenarios.
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Figure 7.14: Comparison of sugar cane yield for various N fertilizer applications using values of c1 =0.17 (initial), 0.325 (final) and 0.525. The dotted lines indicate the incremental crop yield for the different fertilizer applications against zero fertilizer.
Using c1 = 0.17 in the simulation displays a much higher sensitivity or response to crop yield increase (15t/ha) for the 1/4 fertilizer application rate, but it may not reflect the reality on the ground (Figure 7.14). Besides this, the incremental sugarcane yields for the base application rate is high (22 tons/ha). The final value of c1 = 0.325 proposed rectifies the above anomalies. It allows the difference between incremental sugarcane yields in any two consecutive fertilizer application rates to be within realistic levels, while at the same time maintaining the sensitivity for the 1/4 fertilizer application rate from zero application to be low (7t/ha).
Field experiments and laboratory studies have shown that “the amount of nitrogen available to the crop differs markedly between soils and is probably influenced by factors such as climate, aeration, moisture availability, organic matter and the depth of the soil’’ (Moberly and Meyer, 1984). The differences in the response of ratoon cane grown to applied N in the Longlands, Mayo and Inanda form soils are shown in Figure 7.15. Similarly, Cartref soils, which belong to the same Soil Group as Longlands (Table 7.7), would be expected to produce much higher yields in response to applied N as compared to Hutton soils for similar fertilizer application rates.
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Figure 7.15: Ratoon cane responses to applied N in relation to soil form (Moberly and Meyer, 1984).
Moberly and Meyer (1984) suggested that the recommended amounts of nitrogen should be modified according to soil groups. The ratio of nitrogen (kg) to be used per ton of cane (tc) expected in each of the soil forms is given in Table 7.7. This however should be modified slightly according to factors such as soil depth and moisture availability.
Table 7.7: Nitrogen recommendations for sugarcane based on soil forms (Moberly and Meyer, 1984).
Soil group 1 2 3 4
Soil form
Fernwood Cartref Longlands Westleigh Kroonstad Katspruit Glenrosa (light)
Estcourt Sterkspruit
Dundee
Glenrosa (heavy) Clovelly (light)
Hutton (light) Oakleaf Swartland
Bonheim Valsrivier Tambankulu Willowbrook Rensburg
Milkwood Mayo Inhoek Arcadia
Hutton (moderate) Shortlands
Champagne Inanda Nomanci Kranbkop
Magwa Hutton (humic phase)
Clovelly (humic phase)
Griffin (humic phase)
Plant, kg N/ha 120 100 80 60
Ratoon, kg/tc 1.6 1.3 1.0 0.8
Testing the resulting model by applying deficit irrigation to sugarcane for the various land segments that have different soil types gave increased crop yields as would be expected
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because of reduced water stress. Similarly for the different soil forms present in Mkabela Catchment that were simulated, different sugarcane crop yields were realised. As noted above, this probably results from different moisture availability, organic matter and the depth of the soils that were used as input parameters to the ACRU-NPS model.