Simulation of the biomass production of winter wheat and comparison with measured data for locations in different climatic regions

Agricultural and Forest Meteorology, 32 (1984) 225--247

225

Elsevier Science Publishers B.V., A m s t e r d a m -- Printed in The Netherlands

SIMULATION OF THE BIOMASS PRODUCTION OF WINTER WHEAT AND COMPARISON WITH MEASURED DATA FOR LOCATIONS IN DIFFERENT CLIMATIC REGIONS HANS-WERNER DANNECKER

Deutscher Wetterdienst, Frankfurter Str. 135, D-6050 Offenbach~Main (West Germany) (Received N o v e m b e r 15, 1983; revision a c c e p t e d March 30, 1984)

ABSTRACT Dannecker, H.W., 1984. Simulation of the biomass p r o d u c t i o n o f winter wheat and c o m p a r i s o n with measured data for locations in different climatic regions. Agric. For. Meteorol., 32: 2 2 5 - - 2 4 7 . F r o m 1972 to 1976 an e x p e r i m e n t with wheat was carried o u t by m e m b e r s of the Commission for Agricultural M e t e o r o l o g y of the World Meteorological Organization. A p h o t o p e r i o d i c indifferent variety of w h e a t was grown at eleven e x p e r i m e n t a l sites in different climatic regions. The m e t e o r o l o g i c a l and yield data were used to test the applicability of t w o simulation models, a relatively simple one for winter wheat and a c o m p l e x m o d e l for maize that had been changed to correspond to the physiological properties of a C3-plant. Comparing simulated and measured yield of dry matter, it is f o u n d that neither m o d e l is generally valid for climates under which wheat is normally grown. The question of h o w the processes of tillering, f o r m a t i o n of ears and of weight of 1000 kernels can be treated in a m o d e l remains open. INTRODUCTION

In 1971 the Commission for Agricultural Meteorology (CAgM) of the World Meteorological Organization decided to perform an international experiment to obtain data which describe the connection between weather and yield of crops. This decision coincided with the activities of other organizations, for example the FAO, which had mainly been p r o m p t e d by the famine in the Sahel region. Apart from fertilisation, cultivation technique, variety, and pest management, the yield of a crop essentially depends on the weather during all stages of the crop growth. "Weather" includes not only damaging events such as hail, frost, or tropical cyclones, but also temperature, precipitation, or radiation in quite " n o r m a l " ranges where they exert influences on both vegetative and generative development. Since in some countries attempts had already been made to study crop yields in relation to weather and climate with statistical or simulation models, it was considered that it would be very useful if experiments could be done in various climatic regions to collect data on crops and weather which could be used with those models. Wheat was chosen as the test crop; it is grown in many different climatic 0168-1923/84/$03.00

© 1984 Elsevier Science Publishers B.V.

226

regions and is a staple food crop and it was t h o u g h t that wheat was relatively uncomplicated, its yield mainly depending on radiation, temperature conditions and soil moisture. The models to be tested should be able to forecast the yield for a specific year and c o u n t r y on the basis of the actual weather, as well as predict potential yields in a given area where the climatic patterns are known. A working group was formed by the CAgM which had, among others, the following tasks: (1) To choose a variety of wheat which had to be cultivated at various places in different climatic regions. Thanks to the International Maize and Wheat Improvement Center (CIMMYT) in Mexico the photoperiodic indifferent variety Siete Cerros could be made available to all participating members. (2) To define uniform m e t h o d s of cultivation as well as of performance of meteorological and biological observations. (3) To select appropriate test sites in various parts of the world. Eleven places were f o u n d -- details concerning their location are shown in Fig. 1. (4) To collect the meteorological and biological data of all participating stations and make them available to potential users in a form suitable for automatic data processing.

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Fig. 1. Position of the stations of the World Wheat Experiment.

227

However, in the event no agreement could be achieved a b o u t the a m o u n t o f fertilizer (N, P, K) needed. It was decided t h a t " o p t i m u m fertilizer" was to be defined by local standards. U n f o r t u n a t e l y , the am ount s of fertilizer used were in m o s t cases n o t recorded. T h e r e f o r e the differences in cropyields and yield c o m p o n e n t s , i.e. n u m b e r of grains per ear or weight of 1000 kernels, must be assumed to be d e p e n d e n t on climate and fertilization. The E x p e r i m e n t started in aut um n 1972 and spring 1973 and concl uded with the harvest of 1976. As some stations started their co-operation one year later or had to i n t e r r u p t it, a sample of 37 elements (years when wheat was grown in any of the places) was available in that period. In conceiving the meteorological measuring programme only those parameters were to be recorded which are exchanged in international meteorological net w or ks since onl y such data would operationally be available for yield forecasts and agroclimatological assessments. A list of the meteorological and biological parameters measured is presented in Table I -- m o r e detailed i nf or m at i on can be found in a paper by Heger (1981). It is i m p o r t a n t to not e t ha t no measurements of leaf area index were made and t h a t the dry m a t t e r of plants was det erm i ned only once per year, at harvest time. The models which were published in scientific

TABLE I Measured and observed elements during the International Wheat Weather Experiment Air temperature (2 m) Relative humidity (2 m)

Hourly intervals

Duration of sunshine Global radiation Precipitation Maximum and m i n i m u m of soil temperature in 5, 10, and 20cm depth Mean wind speed for intervals 8 a.m. to 8 p.m. and 8 p.m. to 8 a.m. local

Daily intervals

Soil moisture in layers of 10 cm down to a depth of 1 0 0 c m

Irregularly ( ~ weekly)

Volume weight, wilting point, and field capacity of the soil in layers of 10 cm Phenological data for seeding, emergence, 50%, 75%, and 100% cover, jointing, heading, anthesis, milk,stage, soft dough, and total ripeness Number of plants, ears and unproductive tillers per area Weight of 1000 kernels, grain water percentage, a m o u n t of protein, weight of dry matter, weight of grains, total height of plants (all at time of harvest)

Once per year

228

papers mostly lack information about LAI and also about dry matter accumulated at certain stages of development. One of the test sites in the Soviet Union, Naro-Fominsk, continued to grow the Mexican variety in 1977 after the end of the official experiment. In that year samples of LAI and of dry matter (above the soil) were taken at 9 different stages. The models described below used these data as representative values for LAI and accumulated dry matter at the phenological stages concerned. Figure 2 shows the course of the LAI. The increase in the index at the milk ripeness stage is questionable. Due to the short time from the start of the milk stage to its general occurrence a correction of the observed LAI resulted in changes of the dry matter simulation of less than 1%. Apart from the variety Siete Cerros, which was grown in a standard mode as well as under changed conditions with regard to fertilizing and date of planting, a high-yielding home variety was planted at each of the test sites. In this case the cultivation was restricted to the standard values for fertilization and date of planting. Comparisons of the results of the models gained at different sites should always be made regarding the Mexican variety in order to avoid the additional effect of differing biological responses of home varieties. Exceptions to this rule must be made for the sites in Italy and West Germany. In Giessen the home variety was winter wheat whereas Siete Cerros is not winter-hardy and thus had to be planted as a spring wheat. Therefore, it was necessary to compare the results of the models to the measured yields for winter and spring wheat. In the case of both Italian stations, Siete Cerros was planted at dates which were likely to be typical for LA I

Phenological stage Fig. 2. L e a f Area I n d e x as m e a s u r e d in N a r o - F o m i n s k ( w i t h o u t c o n t r i b u t i o n o f s t e m s a n d ears) o f t h e M e x i c a n variety Siete Cerros.

229

winter wheat; however, as no severe frosts occurred, Siete Cerros survived, even though it was spring wheat. Thus the calculations for Rome and Castelvolturno were performed in two different sets of computer runs under the assumptions of winter and of spring wheat. CLIMATIC C O N D I T I O N S

Figure 3 shows the climatological values of air temperature and precipitation for a sample of test sites that participated in the experiment; Table II lists the monthly data for most of the growing periods. Naro-Fominsk and Swiftcurrent are typical for stations of a continental climate characterized by very low mean temperatures in winter and high temperatures in summer.

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230 The maximum precipitation is observed in the summer with droughts, however, occurring rather frequently. Climatic data for Kherson were not made available. Comparing climatic information from other places in the region and considering personal communications, it can be said t h a t the mean m o n t h l y temperatures range between 0 and 22°C and that lack of moisture is a problem often faced in that part of the Soviet Union. At Rome and Castelvolturno are found the typical features for a Mediterranean climate: in winter mean m o n t h l y temperatures fall slightly below 10°C, in summer they increase to about 26°C. Most of the rain is observed in a u t u m n and in the beginning of winter. Average m o n t h l y rainfall declines in spring, falling to a minimum of less than 20 mm in July. As and Giessen are in the temperate latitudes. Mean m o n t h l y temperatures range between - - 5 and ca. 17°C in As, and between 0 and 18°C in Giessen. The distribution of precipitation is comparatively uniform with a maximum in summer (Giessen) or the second half of the year (As). The annual fluctuation in m o n t h l y mean temperatures is small, at both stations in South America; in Pelotas the range is from 13 to 23°C, in Buenos-Aires between 13 and nearly 24°C. The Brazilian site has the highest annual precipitation of all places taking part in the experiment. Mean m o n t h l y rainfall generally amounts to 100 ram. The horizontal lines in Fig. 3 mark the length of the growing period of wheat (Mexican variety) averaged for the years that the respective site joined the experiment. The date of sowing was chosen according to local standards; no a t t e m p t was made to define a c o m m o n date for all test sites. MEASURED YIELDS DURING THE PERIOD 1973 TO 1976 During the growing period and at the time of harvest yield components and total yield were observed. The single quantities are listed in Table II. Figure 4 shows the harvested dry matter of the Mexican variety under normal cultivation. The yields of the Italian sites were the highest in comparison with other countries. Data for the 1973 harvest are not available as Rome and Castelvolturno started their co-operation one year later. In As and Giessen the harvested dry matters are comparable in the first three years of the experiment; then, in 1976, we find a clear reduction of dry matter in As, but nearly constant production for Giessen. In that year there was an exceptional drought in Central Europe and Scandinavia, affecting As and Giessen to a similar degree. However, it should be mentioned that the field in Giessen is on a slope (ca. 2 °) and that the soil contains a layer of loam which provides relatively high moisture at a depth of between 60 cm and lm. Dry matter yields in Buenos-Aires and Pelotas are again similar and are, on the average, a bit lower than at As and Giessen. Very low results were reported from Swiftcurrent and Naro-Fominsk (both stations are in con-

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Fig. 4. Harvested dry matter, Mexican variety, in g m -2 Fig. 5. Harvest Index, Mexican variety, calculated as percentage (dry weight of kernels/ plant dry matter above ground) both at harvest.

tinental climatic areas), and from Kherson where temperatures are favourable for wheat but where soil moisture is deficient. The high yields at Swiftcurrent and Naro-Fominsk coincided with sufficient water in the whole vegetation period o f that year. Large differences are n o t observed when comparing these findings to the measured weights of grain. R o m e and Castelvolturno are again top with Giessen n o w closely following. On the other hand, the weights of grains reported by the South American stations approach those of Swiftcurrent and Naro-Fominsk. The harvest index, Hi, is defined as the fraction of the biomass of a crop that is economically useful. Here it is c o m p u t e d as the weight of grains divided b y the weight of plant dry matter above the soil. According to the FAO (1978) its range lies between 0.35 and 0.45 for wheat under non-irrigated conditions. (In the Wheat Experiment of the CAgM no irrigation was used.) Figure 5 shows the harvest indices for the nine stations and all years under investigation, calculated under the assumption of absolute dry grains. Table III gives the average Hi for the stations. It should be pointed o u t that Hi depends on fertilization (amount and time of application) and on processes like tillering, formation of spikelets, flowering, and translocation processes. The average of harvest indices for Swiftcurrent and Giessen lies above, the indices for Buenos Aires and Pelotas below, the range indicated. Especially in 1974 and 1976 the differences between maximum and minimum of Hi are remarkable. This clearly indicates the necessity of including the processes of grain formation and reduction in a simulation model for the yield of wheat.

235 TABLE III Average Harvest Index, Hi, for the test sites under consideration Giessen As Rome Kherson Pelotas

0.58 0.45 0.42 0.35 0.31

Swiftcurrent Naro-Fominsk Castelvolturno Buenos Aires

0.47 0.44 0.41 0.33

Dry matter and grain weights are influenced in a complex manner by internal processes that determine the number of plants per area, the number of ears per plant, and the number of spikelets or grains per ear. These processes depend on wheat variety and, among others, on the meteorological conditions to which the plants are subjected during certain periods of their life-cycle. No connections could be found between the number of plants after emergence or after wintering, as counted in the Wheat Experiment, and the measured yield of either dry matter or weight of grains. Instead, when a particular test site is inspected, curves of the number of ears (per area) at the time of yellow ripeness often run parallel to those of dry matter harvested. If, however, all places are taken together, correlation coefficients between number of ears and dry matter or weight of grains are just 0.607 and 0.561. These results are restricted to the Mexican variety and normal planting date. Several authors (Day and Intalap, 1970; Singh and Malik, 1983) studied the influence of soil moisture stress on the yield components of wheat, others (Halse and Weir, 1974; Warrington et al., 1977) investigated the influence of temperature in different stages of plant development. The details of these yield-forming processes are not y e t known with sufficient accuracy; this is w h y the testing of models with the data gained in the Wheat Experiment was restricted to all the dry matter of the wheat plants which was above the soil. Braun and Fischbeck (1978) found that the grain yield of a spring wheat is mainly influenced by the n u m b e r of grains per ear; most of the differences in harvests of different years and varieties can thus be explained. Therefore, simulation models for the grain yield of wheat have to be able to predict that number. As the number of grains per ear was n o t recorded in the experiment, it had to be calculated from the grain weight, the number of ears per area, and the weight of 1000 kernels. Here again, the details of the processes that control the number of grains cannot be described satisfactorily. Also, the amounts of flattening of stalks was not recorded. Both these factors influence the weight of 1000 kernels, which according to Reiner et al. (1981) also depends heavily on genetic characteristics. Boguslawski writes (1981) that the number of tillers in general, as well as that of productive tillers, mainly depends on planting density, b u t increasing temperatures together with high light intensities and a decreasing day-length can foster the tillering. The number of spikelets is mainly a response to the

236 length of the period in which t h e y were formed, that length being temperature~lependent. COMPARISON BETWEEN MEASURED AND SIMULATED YIELDS The data gained in the International Wheat Experiment were used as input for two simulation models for the biomass of a crop. The first model was published by Hodges and Kanemasu (1977) and was originally designed for winter wheat. It is a relatively simple simulation model that connects ecological and plant physiological quantities by linear or exponential equations in which some constants were derived from experiments made in Kansas, U.S.A. With a time step of one day one calculates gross photosynthesis as a function of leaf area index and photosynthetically active radiation (PAR). The respiration in that model depends on m a x i m u m and minimum of air temperature, length of day and night, gross photosynthesis, and dry matter accumulated. The other model was developed by De Wit et al. (1978). It is much more expensive in that it works with a time step of one hour and tries to cover m a n y ecological and physiological details. Originally, it was designed for maize in the climatic conditions of The Netherlands. A submodel calculates the radiation balance in the canopy by taking into account direction and inclination of leaves as well as interactions between leaves and radiation in several spectral regions. Another submodel links the water uptake of the root, the plant water percentage and the transpiration rate of the canopy. The newly formed dry matter is distributed between shoot and root, depending on plant water percentage. Other processes considered are the suberization of y o u n g and the rotting of old roots, the regulation of stomatal opening by the water content and the CO 2 concentration in the leaves, and the energetics of biochemical processes. To adjust the latter model to the conditions of wheat some modifications had to be undertaken: (1) In order to cover the physiological features of C3plants, the proposals of De Wit et al. (1978) to alter some of the constants in the model were adopted. (2) The m a x i m u m rate of CO 2 assimilation of a leaf was decreased from 70kg(CO2)/ha(leaf)/h to 30 kg(CO2)/ha(leaf)/h and this rate versus air temperature at 300 vppm CO2 (AMTB) was according to Lundegardh (1949) and Larcher (1980) defined as in Table IV. (3) If the crop was regarded as winter wheat, as was done on trial in the case of the German and both Italian stations, the m a x i m u m rate of CO2 assimilation was set to 6 kg(CO2)/ha(leaf)/h for the time from emergence till jointing. (4) I cm was chosen as leaf width. (5) The values for the fractions of organic anions, fats, lignin, minerals, carbohydrates, and protein versus time used by De Wit and co-authors for maize were adopted unchanged and spread over the whole vegetation period of the wheat. (6) The soil moisture in the layer 0--60 cm, sometimes 0--100 cm, was simulated using a submodel described by Heger (1977), which has been in practical use by the German Weather

237 TABLE IV Table of the CO2 assimilation rate of a leaf of wheat at light saturation and at 300 vppm CO2 versus air temperature Temperature (°C)

CO2 assimilation rate in kg(CO2 )/ha(leaf)/h

--10.0 --0.1 0.1 10.0 20.0 30.0 45.0

0 0 3.0 21.2 30.0 25.0 0

Service for m o r e than t en years. The possibility of m oni t ori ng the influence o f changing soil moisture on the f o r m a t i o n of biomass is thus provided, whereas in th e m o d e l of De Wit et al. the water tension of the soil is set t o a c o n s t a n t - - 0 . 1 bar. (7) As measured soil t e m p e r a t u r e data were available, it was n o t necessary to c o m p u t e t hem on the basis of the air t e m p e r a t u r e . (8) LAITB and WSMTP (LAI and weight of shoot, bot h measured versus time) had to be taken as results of the trial in Naro-Fominsk in 1977. (9) For consideration o f the p h o t o r e s p i r a t i o n it was decided to fix the dissimilation rate o f leaves t h a t p h o t o s y n t h e s i z e in daytime t o 30% of the average CO2 assimilation rate during the day (Schnarrenberger and Fock, 1976). At night it remained unchanged, i.e. 11% of t he average CO2 assimilation rate. G r o w t h and maintenance respiration were treated as suggested by De Wit et al. (10) If th e difference between the water upt ake of the r o o t (WUR) and the transpiration rate of the c a n o p y (TRC) did n o t fall below the given limits, which it sometimes failed t o do in the first few weeks of growth, slight modifications in t he dry m a t t e r of t he leaves and of the roots were made to make th e water balance numerically stable. N ot m o r e than five of these modifications were allowed per vegetation period. In most cases none was necessary. F o r b o t h models t he results of the simulation runs are c o m p a r e d with t he measured dry mat t er . In South America, Canada, Norway, G e r m a n y , and the Soviet Union Siete Cerros was grown as a spring wheat, in Italy as a winter wheat. To co mp a r e t he p e r f o r m a n c e of this variety with (high yielding) local varieties one o f the latter was always seeded on the same date as Siete Cerros. In Giessen the local variety was a winter wheat.

Results concerning the single test places Figure 6 shows measured and simulated dry m a t t e r for b o t h stations in the Soviet Union. In t he case o f Naro-Fominsk the shape of the three curves agrees quite well, whereas their levels reveal remarkable differences. These

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Fig. 6. Measured and calculated biomass, Mexican variety. Fig. 7. Measured and calculated biomass, Mexican variety.

differences are also found in the case of Kherson, but with a much poorer agreement of the trends. Both models predict dry matter productions that are clearly higher than those actually observed. Since in both places the wheat was planted in spring and no damaging frosts occurred, the differences cannot be explained by frost. Much of the variation from year to year could result from variation on precipitation. In Naro-Fominsk the highest yield of dry matter (in 1976) coincided with the highest sum of precipitation for the months of May and June (compared to the other three years); in 1973 soil moisture was usually near 40% plant-useable water capacity between the jointing and milk-stage, when strong rains occurred. The correlation between soil moisture and dry matter produced is less pronounced for Kherson. For the step from 1974 to 1975 there is a decrease in average soil moisture and a reduction in dry matter. Although the soil moisture conditions did not improve in 1976, we find the best result in dry matter for the three years of the experiment. In that same year the weight of grain was not so good, thus leading to a poor harvest-index. In Fig. 7 the results for both South American places are presented. In the

239 case of Pelotas, situated in the south-east of Brazil, there is again a big difference between the levels of measured yield and the yields of the models. The course of the three curves is also quite different. In contrast to the m a x i m u m in the measured yields in 1974 neither model shows a distinct m a x i m u m year. It is important to remember t h a t Pelotas is the test site with the highest average a m o u n t of rain. Due to frequent and intense precipitation, soil moisture rarely fell below 60% plant-useable water capacity. The model of Hodges and Kanemasu works with constants derived in the dry central region of the U.S.A. and therefore m a y not be applicable for such h u m i d conditions. It remains unclear what might be the reason for the m a x i m u m in measured dry m a t t e r in 1974, the grain yield showing only very small fluctuations from one year to the next. In Buenos-Aires the agreement is good in the first three years, the simple model by Hodges and Kanemasu being especially suitable to describe the a m o u n t of biomass that will be formed. From 1975 to 1976 an obvious increase in dry m a t t e r is calculated by both models which was not measured in reality. A comparatively small increase in the weight of grains (from 280 to 3 4 0 g m -2) was, however, reported. The poor performance of b o t h models could be explained by the fact that in 1976, because of sufficient rain, the formation of new biomass was not hindered by the lack of soil moisture which had been a general problem in the preceding years. Both models probably tend to overestimate the importance of water availability. Of course, the possibility also exists that pests, weeds, or other influences, which m a y have been less strong during the other years, caused a reduction in biomass. It may even be possible that high soil moisture was the reason for the good development of competitive weeds to the detriment of the wheat. The high number of ears per unit area and the good yield in grain weight in 1976, in spite of the normal level of dry matter could, nevertheless, be explained: from 1973 until 1975 the soil moisture had been below 40% plant-useable water capacity in the first two weeks after anthesis, thus reducing the number of kernels to be filled. In 1976 sufficient water supply in the filling period contributed to a good yield of grains. In southern Norway, Fig. 8 every summer from 1973 until 1976 had less rain than normal. Most remarkable was the drought in 1976, when the sum of the m o n t h l y precipitations from March until August reached 52% of the long-term average. Normally the simulation of biomass had been undertaken by restricting the zone where the plants take their moisture from, down to a depth of 60 cm. In the case of As a second set of computer runs of the De Wit model was executed assuming that the wheat could reach all the water down to 100 cm. The correspondence between measured biomass and the predictions of the model by Hodges and Kanemasu is satisfying. Again, the remarkable decline in the model from 1974 to 1975 coincides with a strong reduction in precipitation. As reported the highest value for the number of ears at the time of

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yellow ripeness in 1974, being clearly higher than in the other three years. It remains open h o w this may have been caused by meteorological factors and h o w these effects could be treated in a model. It still must be investigated as to h o w the models could be changed in order to make their predictions of biomass development less dependent on soil moisture; o f course, they must be able to predict the decline in biomass observed in 1974. The De Wit model could not be computed for the year 1976 in Swiftcurrent as the hourly meteorological values were incomplete. Apart from this, the correspondence of measurements and models is remarkably good. As far as the model of Hodges and Kanemasu is concerned, this can be seen as an indication of the good applicability of the model in regions with similar climatic patterns and similar agronomic standards. This model, developed for winter wheat, gives very good results even if it is applied to a spring wheat. In the case o f the test site at Giessen the computations were made for the Mexican variety, which was treated as a spring wheat, as well as for the home variety, a winter wheat. Due to a suspected mistake detected recently in the phenological observations the results for the Mexican variety in Giessen are different to those published by Heger (1982).

241

Figure 9 shows the results for the Mexican variety. The test site was on a slope of about 2 ° inclination; its soil is loess o f a vertical extension o f several meters with a good capillary conductivity. Thus, at Giessen the simulation o f the soil moisture was also extended to 1 m depth. From the measurements o f the very dry year 1976 one can see that the soil moisture in the layer from 60 to 100 cm was near 50% plant-useable water capacity even at the end of the vegetation period o f wheat. Thus, it can be explained w h y for the test field a reduction o f o n l y 7.5% in harvested dry matter was observed (compared to the average for 1 9 7 3 - - 1 9 7 5 ) whereas statistics mention about 20% for the region. The c o m p u t e d dry matter in 1 9 7 6 is therefore more representative o f the real conditions of the area than is the measured biomass. An attempt was made to measure the effect of capillary rise by updating the simulated soil moisture by the measured value each time a sample had been taken. However, the increase in dry matter was less than 100 g/m -2 for the De Wit-model, which is t o o small. The relatively high yield that is calculated by the model of Hodges and Kanemasu for 1 9 7 4 seems again to be a consequence of the soil moisture. In that year precipitation was near normal in that part of Germany, whereas it was t o o low in the other three years. The results for winter wheat, Fig. 10, which amounts to 90% of the wheat grown in West Germany, are also far from satisfactory. For the growing period 1 9 7 3 / 7 4 one finds again a strong maximum c o m p u t e d by the DRY M A T T E R G-M~

18oo[ DRY MATTER G'M 1600

+ GIESSEN

/A

1400 T

1400 .

i 1200 t

..---. 1200 i

"', /../"

\.

" " i"...

800 i

,

\.

" :i[.,

\

"\

400 •

--..

.....~......

600 ~ \.

.....

' :::?...

I

\. __MEAS .... H K.

"

'"

",

~

6oo t rL

,

, '"

| t lOOO ~

"', "\\

400 t

~

,, " "-.

. . . . .

i lOOO~

800,

GIESSEN

/

........'-... '.... "."""....

MEAS ..... R K . .......... De Wit

.......... '.~'ii'~iiii~...:..~ ~ :'

____De Wit ( 1 0 0 cm)

200 ~

200 -

73

~ 74

+ 75

~ 76

YEAR

-

72/73

Fig. 9. Measured and calculated biomass, Mexican variety. Fig. 10. Measured and calculated biomass, home variety.

t 73/74

~ 74/75

÷ 75/76

YEAR

242

Hodges--Kanemasu model. This can be explained by the fact that in this year soil moisture seldom fell below 50% plant-useable water capacity. In this model a differentiation is made between assimilation before and after jointing. Something similar had to be provided for the model by De Wit to simulate the dormancy in winter. Results in Fig. 10 show what happens under the assumption that the maximum rate of CO2 assimilation of a leaf before jointing is 10% or 20% of the rate after that date. Unfortunately, for both versions the model became numerically unstable with the data for 1 9 7 2 / 7 3 being used as input. The results for both Italian test sites are plotted in Fig. 11. They started their participation in the experiment one year later, therefore results are presented for three years only. The coincidence between measured and calculated plant dry matter is extremely low, especially for Castelvolturno. The Mexican and the home variety were seeded on the same date, and the DRY MATTER G.M -2

'~,

1600 I 1400|

!

~ . - -

MEAS. MEX. VAR. MEAS.

"',

~,

,"

.OMEWR.

1 2OO ~ ..... H.-K. ......... oo w.

1ooo~

"~" \ \

"-,

............ WmTER-WHE^T -

8004

\\.

". -.

600

..~ /" "..

/.. /.." '.. "....:. .:"

CASTELVOLTURNO

i 1400

t

..... --~

72173

/

,/

+ ~

•..

""

"..:"."/"

~ ~ 74•75

73174

12001000I

-- - -

75/76

fi

,"

--

YEAR

ROME W,.,gh, o~ AI00O "~,~1,

A No o, .la.l~ o, ea,~

5O L

800

40 T SPRtNG WHEAT . . "'....

6OO WINTEn

400

WHEAT ..

]

I

> .....

i

".

t.o

30~ ""..

~

I

i 30

"'..%

74

75

76 HARVEST

Fig. 11. Measured and calculated biomass, M e x i c a n and h o m e varieties. Fig. 12. N u m b e r o f plants after wintering ( ), n u m b e r o f ears after soft dough (-- - per 0.5 m row. Weight o f 1 0 0 0 kernels in g ( - - - - - ) for the test site R o m e .

-)

243 d a t e s on w h i c h p h e n o l o g i c a l p h a s e s o c c u r r e d w e r e n e v e r s e p a r a t e d b y m o r e t h a n five days. T h e q u e s t i o n has t o be raised o f w h e t h e r M e x i c a n a n d h o m e v a r i e t y s h o u l d be t r e a t e d as w i n t e r or spring w h e a t . T h e M e x i c a n v a r i e t y is n o t w i n t e r h a r d y , b u t n o severe f r o s t was o b s e r v e d in t h e t h r e e w i n t e r s u n d e r c o n s i d e r a t i o n . T a b l e V lists t h e d a t e s o f e m e r g e n c e a n d t h e lengths o f t h e intervals f r o m e m e r g e n c e t o j o i n t i n g f o r h o m e a n d M e x i c a n varieties f o r t h e s t a t i o n s Giessen, R o m e , a n d C a s t e l v o l t u r n o . A l t h o u g h t h e t e m p e r a t u r e s w e r e s u f f i c i e n t f o r g r o w t h a n d soil m o i s t u r e was available, t h e M e x i c a n v a r i e t y ( p h o t o p e r i o d i c i n d i f f e r e n t ) b e h a v e d like a w i n t e r w h e a t . T h e m o d e l b y H o d g e s a n d K a n e m a s u is i n t e n d e d t o c o m p u t e t h e b i o m a s s p r o d u c t i o n o f w i n t e r w h e a t a n d was t r e a t e d as such. T h e m o d e l b y De Wit was c a l c u l a t e d in t h e v e r s i o n f o r spring w h e a t , w h i c h m e a n s n o r e d u c t i o n o f m a x i m u m CO2-assimilation r a t e b e f o r e j o i n t i n g and also w i t h the 80% r e d u c t i o n t y p i c a l f o r w i n t e r w h e a t d u r i n g winter. H o m e a n d M e x i c a n varieties h a d t h e i r t o p b i o m a s s p r o d u c t i o n ( a c c o r d i n g to m e a s u r e m e n t s ) in t h e g r o w i n g p e r i o d 1 9 7 4 / 7 5 , w h e n t h e curves o f b o t h m o d e l s s h o w t h e i r m i n i m a . This g r o w i n g p e r i o d h a d t h e l o w e s t p r e c i p i t a t i o n a n d , h e n c e , lack o f soil m o i s t u r e a f t e r t h e d a t a o f heading. This leads t o a l o w b i o m a s s p r o d u c t i o n in t h e m o d e l . It is i n t e r e s t i n g t o n o t e again t h e o v e r e s t i m a t i o n o f t h e i n f l u e n c e o f m o i s t u r e on t h e d r y m a t t e r p r o d u c t i o n m o d e l l e d . A t t h e t i m e o f t h e 1 9 7 5 h a r v e s t in C a s t e l v o l t u r n o o n e finds t h e highest figures ( o u t o f t h r e e ) f o r w e i g h t o f a t h o u s a n d kernels, n u m b e r o f ears p e r m 2 a n d w e i g h t o f grains. In the o t h e r g r o w i n g periods, 1 9 7 3 / 7 4 a n d 1 9 7 5 / 7 6 , m o i s t u r e c o n d i t i o n s in C a s t e l v o l t u r n o w e r e f a v o u r a b l e . I t r e m a i n s u n k n o w n w h y t h e m e a s u r e d yields {plant d r y m a t t e r a n d grains) d r o p p e d o f f

TABLE V Dates of emergence and length of time (in days) from emergence until jointing Home variety

Mexican variety

Emergence

Emergence until jointing

Emergence

Emergence until jointing

Castelvo|turno

1973174 1974/75 1975/76

7 Dec. 26 Dec. 7 Nov.

91 92 127

10 Dec. 28 Dec. 7 Nov.

84 87 125

Rome

1973/74 1974/75 1975/76

21 Dec 1 Jan. 26 Nov.

83 97 120

23 Dec. 7 Jan. 27 Nov.

81 93 117

Giessen

1972/73 1973/74 1974/75 1975176

1 Dec. 26 Nov. 2 Dec. 16 Nov.

153 143 161 163

31 March 20 March 21 March 3 April

27 50 34 36

244 f r o m the period 1974/75. Explanations may be the washing out of fertilizer, weeds, pests, birds, or u n k n o w n effects of ecological quantities. An additional f acto r in the low yield of grains in 1976 may be the fact t hat the anthesis in this year occurred during a period of f r e q u e n t precipitation and daily m a x i m u m temperatures below 16°C, thus possibly causing disturbances o f the pollination. The results for R o m e are n o t much better. Again, the relatively small biomass p r o d u c t i o n calculated according to Hodges and Kanemasu for 1 9 7 4 /7 5 can be explained by the low soil moisture during t hat summer. The re du ctio n o f the measured biomass f r om 1975 to 1976 is predicted by neither of the models. As in the case of Castelvolturno, no reliable explanation can be provided. T ha t reduction coincides with a strong decrease in the n u m b e r of ears per area at the time of harvest and with a small diminution in the n u m b e r of plants after wintering. F o r details see Fig. 12. To predict the yield of grain by a model it is, of course, necessary to cover the effects that direct the f o r m a t i o n of all these parameters such as numbers o f plants per area at different phenological stages, n u m b e r of ears per area, n u m b e r o f kernels per ear, and weight of 1000 kernels. CONCLUSIONS Correlation coefficients between measured and calculated dry m at t er were c o m p u t e d and are given in Table VI. These are slightly changed com pared to the values published by Heger {1982) as some m i nor changes have recently been i n t r o d u c e d into the input data. As a simulation of the different processes that act together in forming the yield of grains ( n u m b e r of tillers per unit area, n u m b e r of kernels per ear, weight of 1000 kernels) seemed t o o difficult, an a t t e m p t was made to restrict working with the data of the Wheat E x p e r i m e n t to the biomass or dry m a t t e r above the soil. It is d o u b t f u l w h e t h e r in the near future it will be possible to handle a crop simulation model t ha t is applicable u n d e r most or all climates. The results p r o d u c e d indicate t ha t the data collected in the Wheat Weather E x p e r i m e n t were n o t sufficient t o forecast the growth of the dry m a t t e r of the whole cereal plant. One has n o t only to plant the same variety, as was done, but in TABLE VI Correlation coefficients between harvested and simulated dry matter All sites Measured, Hodges--Kanemasu Measured, De Wit et al. De Wit et al., Hodges--Kanemasu

0.413 0.187 0.838

Winter wheat 0.132 -- 0.006 0.868

Spring wheat 0.366 0.220 0.876

245 DRY MATTER G*M 2

A 1500"I

A B C G K

J I /

As Buenos Aires Castelvolturno Giessen Kherson

N P R S

Naro Forninsk Pelotas Rome Swiftcurrenl

i 1000 B s

N

!

GP

G

B °G

I 500 *

s NA s

s*

50

60

70

80

90

100

110

120

130

140

150

in days

Fig. 13. Dry matter accumulated until harvest as compared to the length of time from emergence to heading (vegetative growth) for the Mexican variety.

order to test a model in different parts of the world homogeneous conditions have to be created concerning plant nutrition and pest management. If that is impossible, sophisticated sub-models have to be provided to describe the influences of the mineral c o n t e n t in the soil, soil structure, root growth and depth, pests, and competition with other plants, normally weeds. Nieder (1981) found out that the a m o u n t of biomass of a wheat crop depends on the duration of the vegetative development. This could not be determined by the data measured in the International Experiment by the CAgM. Figure 13 shows that the results of comparable test-sites concentrate in parts of the diagram; the correlation coefficient of all data points amounts to 0.659. The results presented indicate an overestimation of the biomass formation in the model by Hodges and Kanemasu. It assumes no reduction o f gross photosynthesis unless the soil moisture falls below 35% of the available soil water at field capacity. Experience in Central-Europe has indicated that this threshold should be replaced by 50% of plant-useable water capacity. For a given intercepted photosynthetically active radiation the gross photosynthesis is constant for a soil moisture down to 50% plant-useable water capacity and then decreases linearly to zero at 0% plant useable water (= wilting point). The results presented by Hodges and Kanemasu show a good fit to this approximation and this is also demonstrated by the results from Swiftcurrent. For the other test sites, especially when water is plentiful, the calculated yields are too high. To adapt the model to other climatic conditions at least the t r e a t m e n t of the water balance has to be modified. In the model of De Wit a modification was undertaken, i.e. taking the water

246 p o t e n t i a l o f t h e soil as o n e o f the i n p u t p a r a m e t e r s f o r the w a t e r u p t a k e o f t h e r o o t . While t h e H o d g e s - - K a n e m a s u m o d e l generally o v e r e s t i m a t e s t h e b i o m a s s d e v e l o p e d , t h e version b y De Wit clearly o v e r e s t i m a t e s it f o r t h e s t a t i o n s in t h e Soviet U n i o n a n d f o r P e l o t a s b u t gives t o o low results f o r As, Giessen, and t h e sites in I t a l y . Since t h e s t a r t o f the s t u d y in 1972, findings h a v e b e e n p u b l i s h e d stating t h a t t h e ear, t h e flag-leaf, a n d t h e s e c o n d leaf c o n t r i b u t e m o s t l y t o p h o t o s y n t h e s i s . T o d e v e l o p m o r e a p p r o p r i a t e simul a t i o n m o d e l s o n e has t o k n o w t h e leaf area indices f o r t h e s e p l a n t p a r t s and the p h o t o s y n t h e t i c a c t i v i t y o f the ear. Special c o n s i d e r a t i o n has to be given to t h e p r o c e s s o f wilting a n d its s i m u l a t i o n to c o v e r firstly the r e d u c t i o n o f CO 2 a s s i m i l a t i o n a n d s e c o n d l y t h e t r a n s l o c a t i o n processes during ripening. T h e m e a s u r e m e n t s o f t h e n u m b e r s o f p l a n t s s h o r t l y a f t e r e m e r g e n c e or a f t e r tillering p r o v e d n o t t o be s u f f i c i e n t to e x p l a i n the yield variation, n e i t h e r o f d r y m a t t e r n o r o f grains. T h e a g r e e m e n t s m a d e w h e n t h e s t u d y was s t a r t e d w e r e n o t d e t a i l e d e n o u g h to r e c o r d s u f f i c i e n t l y t h e tillering. A s t r o n g correl a t i o n was f o u n d m a i n l y b e t w e e n t h e yield a n d t h e n u m b e r o f ears p e r area at t h e t i m e o f y e l l o w ripeness, t h e c o r r e l a t i o n w i t h t h e w e i g h t o f 1000kernels m o s t l y being q u i t e w e a k . As m e n t i o n e d a b o v e , t h e h a r v e s t i n d e x o f t h e M e x i c a n v a r i e t y differs m a r k e d l y b e t w e e n t h e test sites o f t h e W h e a t E x p e r i m e n t . T o solve t h e p r o b l e m o f its a s s e s s m e n t b y m e a n s o f a c o m p u t e r m o d e l all t h e d i f f e r e n t p r o c e s s e s o f f o r m a t i o n o f yield c o m p o n e n t s m u s t be q u a n t i t a t i v e l y k n o w n . B r a u n and F i s c h b e c k ( 1 9 7 8 ) , N i e d e r ( 1 9 8 1 ) , and H e r z o g ( 1 9 8 0 ) as well as m a n y o t h e r a u t h o r s p r o v e d t h e d e p e n d e n c e o f t h e yield c o m p o n e n t s and t h e i r d e v e l o p m e n t on t h e v a r i e t y used. L a c k o f water, o c c u r r i n g in d i f f e r e n t p h e n o l o g i c a l stages, p r o d u c e s d i f f e r e n t i n f l u e n c e s on t h e grain yield. A p a r t f r o m a r e d u c t i o n o f t h e mass o f p h o t o s y n t h e s i z i n g tissue K u l i k a n d S i n e l s h c h i k o v ( 1 9 7 6 ) m e n t i o n the n u m b e r o f ears p e r plant, the n u m b e r o f spikelets p e r ear, t h e n u m b e r o f kernels p e r ear, and t h e w e i g h t o f 1 0 0 0 kernels, all o f w h i c h can be c h a n g e d . T h e m e a s u r e m e n t s and o b s e r v a t i o n s u n d e r t a k e n d u r i n g t h e W h e a t E x p e r i m e n t w e r e n o t designed to t a k e all these effects into account.

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247 Halse, N.J. and Weir, R.N., 1974. Effects of Temperature on Spikelet Number of Wheat. Austr. J. Agric. Res., 25: 687--695. Heger, K., 1977. Organisation der meteorologischen Beratung fur die Feldberegnung in Deutschland. Z. Bew~serungswirtschaft, 12 (Heft 2): 105--126. Heger, K., 1981. Basic Data R e q u i r e m e n t s - - Experience with the World Wheat Experiment of the World Meteorological Organization. In: W. Bach, J. Pankrath and S.H. Schneider (Editors), Food--Climate Interactions, Reidel, Dordrecht, pp. 362--382. Heger, K., 1982. Report of the Working Group on Analysis of Wheat Weather Data, World Meteorological Organization, Geneva, CAgM Rep. No. 11, 36 pp. Herzog, H., 1980. Source- und Sink-Verhaltnis w~ihrend der Kornffillungsperiode bei sechs Winterweizensorten. Z. Acker- und Pflanzenbau, 149: 472--487. Hodges, T. and Kanemasu, E.T., 1977. Modelling Daily Dry Matter Production of Winter Wheat. Agron. J., 69: 974--978. Kulik, M.S. and Sinelshcnikov, V.V., 1976. Lectures on Agricultural Meteorology, Publ. for the U.S. Department of Agriculture, Soil Conservation Service and the National Science Foundation, Washington, D.C. by the Indian National Scientific Documentation Centre, Hillside Road, New Delhi, 402 pp. Larcher, W., 1980. Okologie der Pflanzen, 3rd edn., Ulmer, Stuttgart, 399 pp. Lundegardh, H., 1949. Klima und Boden in ihrer Wirkung auf das Pflanzenleben. Verlag Gustav Fischer, Jena, 484 pp. Nieder, G., 1981. Sortenspezifisches Ertragsverhalten von Weizen unter besonderer Ber/icksichtigung des Wasserhaushaltes. Arbeiten zur Pflanzenokologie, Nr. 1, Inst. f. Pflanzenbau und Pflanzenz/ichtung der Bundesforschungsanstalt f/Jr Landwirtschaft, Braunschweig, 133 pp. Reiner, L., Becker, F.A., Brandenburger, H., Deecke, U., Ktihne, P., Schwerdtle, J.G., Franck, P., Grass, K., Grosskopf, W., Kurten, P.W., Meier, B., Oppitz, K. and Mangstl, A., 1981. Weizen aktuell, DLG-Verlag, Frankfurt/Main, 174 pp. Singh, T. and Malik, D.S., 1983. Effect of Water Stress at Three Growth Stages on the Yield and Water-Use Efficiency of Dwarf Wheat. Irrig. Sci., 4: 239--245. Warrington, I.J., Dunstone, R.L. and Green, L.M., 1977. Temperature Effects at Three Development Stages on the Yield of the Wheat Ear. Aust. J. Agric. Res., 28: 11--27, Schnarrenberger, C. and Fock, H., 1976. Interaction among Organelles Involved in Photorespiration. In: C.R. Stocking and U. Heber (Editors), Encyclopedia of Plant Physiology, New Series, Springer, Berlin, Heidelberg, New York, pp. 185--234.