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The partitioning of assimilates to the various crop organs (leaves, stems, storage organs) has a strong effect on crop growth. First, since there is a linear relationship between weight and area of leaves (SLA), the amount of assimilates partitioned to leaves affects the surface area of leaves. This then affects the amount of intercepted radiation, which directly affects crop photosynthesis and the amount of assimilates produced for the crop as a whole. Second, the partitioning determines the amount of assimilates partitioned to the storage organs (panicles) and hence the harvest index and the yield produced. Partitioning, however, is difficult to parameterize. It is derived from calculating the difference in weight of each crop organ between two consecutive dates of measurement, and expressing this as a fraction of the difference in weight of all crop organs combined. For a complete calibration, we need measurements of dry weights of green leaves, dead leaves, stems and panicles (storage organs) with a high frequency.
Ex-VI.10. Study the computed partitioning factors in the file PARAM.OUT:
* Calculated partitioning factors
DVSM FLV FST FSO
0.062 0.500 0.500 0.000
0.161 0.493 0.507 0.000
0.263 0.500 0.500 0.000
0.397 0.492 0.508 0.000
0.559 0.424 0.576 0.000
0.731 0.289 0.689 0.022
0.906 0.154 0.576 0.270
1.172 -0.375 -2.358 3.732
1.575 0.097 -0.047 0.950
1.907 -3.002 -6.007 10.009
2.005 0.215 0.284 0.501
The variable DVSM is the calculated development stage midway between two consecutive measurements. After flowering, other processes in addition to partitioning of assimilates affect the weight increase of crop organs, e.g. leaf death and remobilization of stem reserves to the storage organs. Therefore, the computed partitioning factors after DVS=1 (indicating flowering) should be carefully interpreted. In our case, the last four rows show negative values that are caused by internal remobilization of biomass and leaf loss, and are to be ignored (see also pg 173 in the book). The rectified table shows as:
* Calculated partitioning factors
DVSM FLV FST FSO
0.062 0.500 0.500 0.000
0.161 0.493 0.507 0.000
0.263 0.500 0.500 0.000
0.397 0.492 0.508 0.000
0.559 0.424 0.576 0.000
0.731 0.289 0.689 0.022
0.906 0.154 0.576 0.270
1.172 0.000 0.000 1.000
1.575 0.000 0.000 1.000
1.907 0.000 0.000 1.000
2.005 0.000 0.000 1.000
Partitioning tables are constructed by plotting the computed partitioning factors against development stage (the DVSM values above), and fitting straight lines through them. The end points of the lines are the data sets that characterize the partitioning tables and are to be entered in the crop data file. This fitting of the lines is more an art than a science, since no statistical tools are available for this procedure.
Note that, at each value of DVS, the sum of the (interpolated) values of the partitioning factors for leaves (FLV), stems (FST) and storage organs (FSO) should be 1.
In Figure VI.4, we have plotted the computed partitioning factors against development stage. Note the paucity in data around flowering. This is typical for many data sets, since most measurements after flowering cannot be used to calculate partitioning. A more accurate derivation of partitioning tables requires a higher frequency of measurements around flowering. Moreover, it is preferable to combine data from a number of field experiments (see, for example, Figure 7.1 in Chapter 7.3 of the book ‘ORYZA2000: modeling lowland rice’). With the few data we have available, we fitted the following partitioning tables:
* Table of fraction shoot dry matter partitioned to the leaves (-; Y-value)
* as a function of development stage (-; X value):
FLVTB = 0.00,0.50,
0.40,0.50,
0.75,0.30,
1.00,0.00,
1.30,0.00,
2.50,0.0
* Table of fraction shoot dry matter partitioned to the stems (-; Y-value)
* as a function of development stage (-; X value):
FSTTB = 0.00,0.50,
0.40,0.50,
0.75,0.70,
1.00,0.50,
1.30,0.00,
2.50, 0.
* Table of fraction shoot dry matter partitioned to the panicles (-; Y-value)
* as a function of development stage (-; X value):
FSOTB = 0.00,0.00,
0.40,0.00,
0.75,0.00,
1.00,0.50,
1.30,1.00,
2.50, 1.0
Ex-VI.11 (OPTIONAL). Copy the data on partitioning given in PARAM.OUT to a spreadsheet (e.g., Excel) and make a graph of the partitioning factors for leaves, stems, storage organs, and leaves plus stems combined, versus development stage. Include the partitioning tables above as straight lines and try to reproduce Figure VI.4. Examine effect of changes in some of the values in the partitioning tables while assuring that the sum of (interpolated) values of all three partitioning factors remains 1.
Ex-VI.12. Open the file JD305.DAT and change the partitioning tables for leaves, stems and storage organs to the ones supplied above. Run ORYZA2000, and make graphs of simulated and measured LAI, WAGT, WSO, WLVG and any other variable of your choice versus time. Comment on the difference between simulated and measured values, and on the differences between Run 0 and Run 1.
Compared with the previous calibration step (Ex-VI.6-9, Figure VI.3), there is a considerable improvement in the simulation of LAI (Figure VI.5a) and WLVG (Figure VI.5b). The simulation of WAGT again slightly improved (Figure VI.5c) between days 180 and 220, whereas there is hardly any change in the simulation of WSO (Figure VI.5d). WSO is still underestimated at the end of the season.
Figure VI.4a. Measured (data points) and fitted (drawn line) partitioning factor for leaves (FLV) versus development stage (DVS); cv. JD305, Beijing, 1987.
Figure VI.4b. Measured (data points) and fitted (drawn line) partitioning factor for stems (FST) versus development stage (DVS); cv. JD305, Beijing, 1987.
Figure VI.4c. Measured (data points) and fitted (drawn line) partitioning factor for leaves and stems combined (FLV+FST) and for storage organs versus development stage (DVS); cv. JD305, Beijing, 1987.
Figure VI.5a. Simulated and measured leaf area index (LAI; -); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area and partitioning tables.
Figure VI.5b. Simulated and measured dry weights (kg ha-1) of green leaves (WLVG); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area and partitioning tables.
Figure VI.5c. Simulated and measured dry weights (kg ha-1) of total above-ground biomass (WAGT); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area and partitioning tables.
Figure VI.5d. Simulated and measured dry weights (kg ha-1) of storage organs (WSO); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area and partitioning tables.
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