Embedded Files
Leaves die and fall off with ageing of the crop. Though most leaf loss occurs after flowering, some of it takes place earlier in the season as well. The loss of leaves just before flowering is compensated by leaf growth. It is not possible to separately quantify the loss rate and the growth rate from measurements of dry weight of leaves only. However, dry weights of green and dead leaves are usually the only measurements we have. We can calculate a ‘net’ loss rate from the difference in value of the logarithm of green leaf weights between two successive measurements. This should only be done for that part of the growing season when the weight of leaves decreases (indicating there is a net leaf loss). This net loss rate varies with the development stage of the crop. After flowering, no leaf growth take place, and the calculated ‘net’ values are the true loss rates.
Ex-VI.13. Study the computed leaf death rate DRLV in the file PARAM.OUT:
* Calculated relative death rate leaves
* Only when leaf biomass declines
DVSM DRLV
0.161 0.034
0.906 0.001
1.172 0.028
1.575 0.041
1.907 0.068
2.005 0.222
In Figure VI.6, we have plotted the computed leaf death factor DRLV against development stage. Then, we fitted the following leaf death function (table):
* Table of leaf death coefficient (d-1; Y-value) as a function of development
* stage (-; X value):
DRLVT = 0.00, 0.000, ! Leaf death coefficient as function of DVS
1.00, 0.015,
1.25, 0.025,
1.50, 0.045,
2.10, 0.070,
2.50, 0.070
The computed value of 0.222 at harvest (DVS=2) is unrealistically high and was discarded in the fitting of the function. In the fitted function, we see that leaves start to die directly following emergence, though this only becomes noticeable around panicle initiation (PI; at DVS=0.65).
Ex-VI.14 (OPTIONAL). Copy the computed data on leaf death rate in PARAM.OUT to a spreadsheet and make a graph of the leaf death rates versus development stage. Include the leaf death table above and try to reproduce Figure VI.6.
Ex-VI.15. Open the file JD305.DAT and change the leaf death table into the one 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.10-12, Figure VI.5), the simulation of LAI (Figure VI.7a) and WLVG (Figure VI.7b) is now satisfactory. The simulation of WAGT again slightly improved overall (Figure VI.7c), whereas there is hardly any change in the simulation of WSO (Figure VI.7d) that still underestimates measured values at the end of the season.
Figure VI.6. Measured (data points) and fitted (drawn line) leaf death rate (DRLV) versus development stage (DVS); cv. JD305, Beijing, 1987.
Figure VI.7a. Simulated and measured leaf area index (LAI; -); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area, partitioning tables and leaf death rate.
Figure VI.7b. Simulated and measured dry weights (kg ha-1) of green leaves (WLVG); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area, partitioning tables and leaf death rate.
Figure VI.7c. 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, partitioning tables and leaf death rate.
Figure VI.7d. Simulated and measured dry weights (kg ha-1) of storage organs (WSO); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area, partitioning tables and leaf death rate.
In the pre-flowering phase of crop growth, some assimilates are stored in the stems, the so-called ‘stem reserves’. After flowering, about 95% of these stem reserves are remobilized and transported to the storage organs. The fraction carbohydrates of the stems that is stored as stem reserves and eventually remobilized, FSTR, can be calculated from the difference in stem weight at the end of the season and at the moment of maximum weight, which is around flowering.
Ex-VI.16. Study the computed fraction stem reserves (FSTR) in the file PARAM.OUT:
* Calculated fraction stem reserves
FSTR WSTMAX DVSMAX WSTEND DVSEND
0.404 10408. 1.004 6203. 2.007
Open the file JD305.DAT and change the value of the fraction stem reserves into the calculated one, i.e. 0.40. Run ORYZA2000, and make graphs of simulated and measured LAI, WAGT, WSO, WLVG and, now also of WST, versus time. Comment on the difference between simulated and measured values, and on the differences between Run 0 and Run 1.
In our example, FSTR is 0.40. For reference, the program PARAM also gives the stem weights used in the calculation, and the (calculated) corresponding development rates at which these were measured: WSTMAX is the maximum stem weight and DVSMAX the development stage at which this was measured, and WSTEND is the stem weight at the end of the growing season and DVSEND the development stage at which this was measured. Sometimes, errors or inaccuracies in measurements result in a stem weight that is higher at a stage before or after flowering. Therefore, these data can be used to check the validity of the computations. In our example, maximum stem weight was found just at flowering and the end-of-season weight was indeed at physiological maturity. Check the calculation of FSTR from WSTMAX and WSTEND!
A: FSTR = (10408-6203) / 10408 = 0.404.
In Figure VI.8, we see the typical pattern of stem growth: an increase in weight until flowering, and a decrease afterwards not because of stem death (similar to leaf death; see above), but because of remobilization of stem reserves to the storage organs. Note the close fit between simulated and measured stem weights in Run 1 after full calibration.
In Figure VI.9, we now see a very good agreement between simulated and measured values for all variables, LAI, WAGT, WLVG and WSO. The underestimation of measured WSO at the end of the season has disappeared, because of the added assimilates that have been remobilized from the stems. The example of calibration of fraction stem reserves illustrates how a parameter that (such as the fraction stem reserves), at first sight does not seem to have any effect on a particular variable (such as weight of storage organs), eventually plays a significant role in the simulation of that particular variable.
The parameterization of ORYZA2000 for the variety JD305 in Beijing, 1987, is finished. For reference, the full crop data file JD305.DAT after calibration is included in Appendix 7 ‘The parameterized crop data file JD305.DAT’.
Figure VI.8. Simulated and measured dry weights (kg ha-1) of stems (WST); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area, partitioning tables, leaf death rate and fraction stem reserves.
Figure VI.9a. Simulated and measured leaf area index (LAI; -); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area, partitioning tables, leaf death rate and fraction stem reserves.
Figure VI.9b. Simulated and measured dry weights (kg ha-1) of green leaves (WLVG); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area, partitioning tables, leaf death rate and fraction stem reserves.
Figure VI.9c. 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, partitioning tables, leaf death rate and fraction stem reserves.
Figure VI.9d. Simulated and measured dry weights (kg ha-1) of storage organs (WSO); cv. JD305, Beijing, 1987; after calibration of development rates, specific leaf area, partitioning tables, leaf death rate and fraction stem reserves.
Report abuse