in
Dupuy B. (ed.).
Aspects économiques de la gestion de l' eau dans le bassin méditerranéen Bari : CIHEAM
Options Méditerranéennes : Série A. Séminaires Méditerranéens; n. 31 1997
pages 289-312
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--- Steduto P. Modellin g for crop respon se to water: ph isiological aspects. In : D upuy B. (ed.).
Aspects économiques de la gestion de l'eau dans le bassin méditerranéen . Bari : CIHEAM, 1997. p.
289-312 (Options Méditerranéennes : Série A. Séminaires Méditerranéens; n. 31)
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Steduto
Agronomic Bari,
SUMMARY
-
The issue of crop response to water is presented in a theoretical framework which highlights some of the main approaches developed over time. After a brief introduction dealing with the advantages of using modelling as a quantitative tool in serving agricultural science, various physiological processes (i.e., leaf expansion, CO2 assimilation, partitioning of assimilates, osmotic adjustment and respiration) are synthetically reviewed in terms of their response to water stress. This introduces the basis for conceptual modelling of crop growth with notable focus on response to water. The standing crops are thus considered as dependent on their capture and use of environmental resources such as solar radiation, carbon dioxide, water and nutrients, and their growth and productivity are formulated both in terms of empirical and mechanistic relations. The approaches of solar-radiation and transpiration as related to productivity are discussed. However, all crop models generally allow the construction of a 'production function' of crop yield versus water use, which is necessary for the economic evaluation of water management at farm and regional scale. The specific case of the crop- growth submodel of EPIC (Erosion Productivity Impact Calculator) is repotted as a relatively simple example of implementation of process integration to mechanistically simulate growth and productivity. While discussing distinctive features of crop models relative to crop-water relations, limits in their use in the Mediterranean Basin are highlighted. Specifically, modelling aspects on tree crops and salinity are recalled. Relatively extensive literature is reported to allow furtherinsight on the various subjects treated. Finally, words of caution, perspectives, and research needs concerning crop models are remarked in the conclusions.
Key words: Crop-modelling, crop-water relations, yield-response functions.
1
290 Steduto
RESUME
-
Ce travail porte sur le problème de la réponse de la culture à l’eau suivant un cadre théorique illustrant les principales approches développées jusqu’à présent. Après une brève introduction sur les avantages de la modélisation en tant qu’outil quantitatif au service de la science agricole, on passe brièvement en revue les différents processus physiologiques (i.e.l’expansion foliaire, l’assimilation de CO, , la répartition des assimilats, l’ajustement osmotique et la respiration) et leur réponse à la contrainte hydrique. Cette introduction crée les bases pour la modélisation conceptuelle de la croissance culturale se référant notamment à la réponse à l’eau.
Le couvert végétal est considéré en termes de sa capacité d‘intercepter et utiliser les ressources environnementales telles que le rayonnement solaire, le gaz carbonique, l’eau et les éléments nutritifs, et sa croissance et sa productivité sont formulées par des relations empiriques et mécanistes. On discute aussi des approches du rayonnement solaire et de la transpiration vis-à-vis de la productivité. Tous les modèles culturaux permettent de construire une “fonction de production’’
mettant en relation le rendement cultural et l’utilisation de l‘eau, ce qui est nécessaire pour évaluer les aspects économiques de la gestion de l‘eau au niveau de l‘exploitation agricole et au niveau régional. On rapporte le cas spécifique du sous-modèle de la croissance culturale d‘€PIC (Erosion Productivity Impact Calculator) en tant qu’exemple relativement simple pour réaliser l’intégration des processus permettant de simuler la croissance et la productivité d‘une manière mécaniste. On discute des aspects distinctifs des modèles culturaux par rapport aux relations eau-culture, en soulignant leurs limites d‘emploi dans le pourtour méditerranéen. Notamment,
des rappels sont faits sur la modélisation des cultures arboricoles et de la salinité. Des références bibliographiques assez étendues permettront d‘approfondir les différents aspects. Enfin, dans les conclusions on donne quelques avertissements, les perspectives et les besoins de la recherche sur les modèles culturaux.
Mots-clés: Modélisation culturale, relations eau-plante, fonctions de réponse au rendement.
and the of
complex plants to physical
COZ, and ents play a fundamental
be viewed on time and space scales (Fig.
l), each one indicating a
level’ which allows to a complex system to sub-systems and components (Fig. 2).
Classical to
to based on same-
level) yield to
inputs) applied as an in- h c -
tions 1983)
simple second
optimal timing and depth of
tion is ‘dated’
tion functions obtained. this
identified, simplicity is maintained, but
explanation such a un-
a of same-level
is
location, soil,
the should to a
new to a hi-
level (Fig. 2), some physiological finding explanations to
some only
since the is (e.g., we may
say how leaf conductance, leaf
v e a index, etc., affected by the
gime, but still we cannot say to what extent that
in leaf and leaf con-
ductance affected yield).
for crop response to water: physiological aspects 29 1
l
lo’-10’
-
10’
-
I
i loll--
10 O- loz - lo4
-lo6-
los-
1o1O-
u
-
t !l 8
l
-
Schematic representation of the space-time scale of biological systems. Transitions between states (a space description) elicit biological processes (description ofand modzjîedfiom Osmond et al. (1980).
a of
is in the difficulty of the into a quantitative
modelling is the
aimed at the quantitative of the physio- logical
to in
the (in of both
quantity and quality) is the most limiting to
an is in
to make the best use of it to a final
objective. a
l), is wanted to ceed the solution of the optimization study.
on in
in fact, et al., 1994) is
modelling as an essential tool of assessment, scaling up and down between the (e.g., scheduling, management, pest management, and economic evalua- tion) and the (e.g., landscape ecology, soil
decision assessment).
292 Steduto
Explanation of phenomenon
i+
1
ii-
1 i-2
Significance of phenomenon
i-
3i-4
....
....
2 - Schematic subdivision a biological system into hierarchical levels organization.
observed at higher levels organization can be explained by observations made at lower levels organization. The signijkance the phenomena observed at lower levels organization can be evaluated by examining their quantitative efsects on the phenomena at higher levels organization.
and mod$edfiom Amthor
this sense, a feasible and model can be thought of as a complex function, and
an activities 1991),
to inputs
is tested, and sufficiently validated.
Always in mind that all of
and in plants with each
in a in the
mainly focused on the tionships between
physiological aspects highlighted to
weaknesses of To
allow the to gain insight into the dif-
subject a of
is
OF
When dealing in to
one has always to in mind the time- dependence of the events.
the dynamic of plant status, the de-
pendence of effects on its
and timing of the
cycle, and the developmental
among the difficulties in model-
ling This time-dependence
is at times especially by some
the to
as an oligo-genic the
at a
stage to any of the life cycle.
for crop response to water: physiological aspects 293
in to the
in dif- et al.,
is to such
is
area development
to be to
et al., 1993). The implication of this in
light thus in the
at no effect at all on
Following the of
of
(i) when the canopy is
ing phase), the is with time, and the
limiting; (ii) the ‘middle phase’, when the canopy is
filly the
phase), the the
incident photosynthetically active radiation
the nential’ that
effect on biomass and canopy size (the compound
Once the
of incident this stage, the
tive to
would not of inci-
to the
the well.
the last phase, the biomass accumulation is much to
the in leaf in
size), associated to a loss of assimilation capacity
in the biomass accu-
mulation slows down continuously up to the end of
Carbon dioxide msì~nzilatìon and stomatal resistance than 90-95% of plant
in the
fiom photosynthesis. While leaf the the leaf photosynthetic the
The effect of to sto-
mata1 non-stomata1 limitations to photosyn-
C02 assimilation of a leaf (Al ) in difision
A , = , CG - , ,
6 + q
+r, (1)c, is the C02
is the CO2 at the sites of the lation
rb
yrl ,
andr:
theleaf
to C02
,
the field,in of in
the soil, the in A1 is confined to the mand of the
the intensity of A1
in the
in the
to develop, photosyn- thesis is confiied to the
et al., 1986), and the
294 Steduto
such to shoot ‘signals’
(Y),
and va- thewith the
tance addition to the
of the is also affected by
in a with
evidence shows that the COz concen- (ci ) tends to
and constant ca and , so that is a et aZ.,
to the
ing such the this
to 1987).
though, ci tends to as a consequence of duced metabolic capacity of the photosynthetic ma-
and partìtìonìng of assimilates the
of h i t s the
h i t in
the to fmal yield if not all, of the following
h i t
in to the
plant in cotton the
is to plant height and in many
the is as-
sociated with the
in turn, allows a of functional to be supplied with the available assimilates. Thus, the
is on the of
its effect on plant size.
Subsequent abscission of
that
f i t s to
tion, and f i t setting development, it in
to of the young f i t s
in
likely to
thus, is set by the amount
of into the
the
the is
the just ex- filling stages, can
is still the to the
yield of et al. (1984) showed
that the
in time was only the
sults of an
in
ity not only because of its impact on but also be- cause of the
in
in in-
A that the
(€US) of with
198l), although the extent to which the
to that
can be shoot
for crop response to water: physiological aspects 295
also significantly depends on the ability of the
justment et al., as an optimization in
is ‘invested’ in to the ‘expense’ of the shoot to ‘gain’ to
sustain the This be-
in plant communities
spite of the played by assimilate
plant on
effect on the
still undefined
(Farrar,
the dence shows that
is the
photosynthesis of the the sink,
than on the conducting
of assimilates un-
Osmotic adjustment
osmotic adjustment, is
vant physiological mechanism adopted by plants to Feng et al., 1994; et al.
,
1994). Since total in plant cells
(Y),
at the is the sum of osmotic
solute potential
(vs)
and(vp)
with < O andvp
O, in os- motic potential, compatible with the cell biochemis-try, in This
photosynthesis activity at levels of not possible in its absence.
loss
an in as a con-
sequence of is con-
in addi-
tion to the effect of solute
have the ability to actively osmotic adjust-
ment to The solutes that ac-
cumulate adjustment may be na-
depending on species and timing of the cycle, but all can be to typical cell com- pounds such
ions (e.g., etc. Since also the solutes of the medium affect the potential in plants, salinity conditions in soils and
an of os-
et al.
,
1994).Osmotic adaptation of is also an mechanism to allow
plants to
deplete the soil soil potential
a soil
the additional
the soil is likely to be small, the the
of a soil volume could be significant.
the
with species, genotype, as well as with and de-
et al., 1995). and a small
induce justment than a slow
the effects on cell the maintenance of by osmotic adjustment of leaves may also
have a on final
is evidence, in fact, suggesting that
in the abscis-
sic acid (ABA) which in turn the viability of the
osmotic adjustment which can be identified as
inhibition.
Although the is well
known,
obtained in of optimizing its use in adaptation
well in the lack of
the fundamental of the photosynthetic
in the
a plant, it must be that two plants with in both total biomass and yield, because of the
in
such as the ones just examined. addition to these is
296 Steduto
Specifically,
a of
balance, budget, as it is
sible the all the
catabolic of the metabolism
involved the life cycle of a plant.
cost of can be satisfac- subdivided into two components: mainte-
nance ( R g )
Though this subdivision was
in time still holds
Essentially, mainte- nance
of and lipids
instead, supplies the synthesis of compounds and
lation of compounds in subse-
quent use, in
and of compounds.
This is of
in as
indicates that is
deficit is suffi- to
1976), although the extent of in
in photosynthesis. This is also in with the
that any that
should of
tion is valid
due to the between
although, on a basis, plants may accumulate
solutes a
fact, is some in- in
quent development.
With diminishing soil content, a in
Costa et al., looking at the
of used in and no effect on the (Loomis and
in
will be
in in the
salt
in a the
tion
salinity conditions, in addition to the as
tioned, maintenance costs expected to
also because of the cost associated with possible mechanisms of exclusion of salts.
of
needed
soil levels a
of the effects of on the
of will be possi-
This is even so sa- linity conditions.
Concluding remarks addition to
attention. One of these is the communication be- to the complexity of
in ex-
et al., 1994).
ABA, cytokinin, etc.) which can an addi-
tional on the to
stimuli.
is the photoinhibition of photosynthe- sis which significantly affects the balance of conditions of high light intensity in conjunction with
Although photoinhibition has been known many
decades as a light-induced pho-
tosynthesis, only it began to be elucidated, especially in of its significance to plant ductivity (e.g., et al., i987;
1994).
the that
involved a deficit event in
for crop response to water: physiological aspects 297
is
Although incomplete in the list
in status, this section can be
of a to (Fig. 3),
by
to notice that the of can- opy development leaf expansion) is line of defence of a deficit develops
(see also et al., 1993).
the is affected, and
an osmotic adjustment may take place. Only is advanced and intense enough
to a in leaf potential
(Y),
stomata start to close followed by consequent leaf wilting All the conditions then an of senescence, and ul- plant dessication. Again, in-tensity, timing
of one
I I I
3
-
Generalized time course gross and adaptive changes in crop plants in response to the gradual development water stress in the$eld í%e width of a band represents the relative magnitude of the response. The shape a band reflects the variation responses with increasing stress intensiv and duration. The starting position a band on the time scale indicates the water stress threshold foreliciting modiJiedfrom Bradford and Hsiao (1982).
OF tion,
the
a way, life the
and (Azam-Ali ant in the wave band of 400-700
nm.
Thiset al., 1994), as of
l is the pri-
298 Steduto
tion the sun) is in fact called photosyntheti- cally active radiation this
the of is a growth en-
gine which of calculating the
amount of assimilates that plants will
...”
(Azam-Ali et al., 1994).
The flux the to the
in
on the the
flux of the
leaves to the open on the same
of stomata1 opening link
between COZ assimilation and is in
thus, the
to the
the on the dominant
limiting of the study,
might be in using a
(Azam-Ali et al., 1994).
the two on the
tionships and and
discussed.
The biomass-solar radiation relationship
on the
1977), which scale and
definition
Typically, these models follow the indicated in Fig. 4.
this type of models is the
way the is
of using light to
the whole canopy height, a net con- effkiency (E),
is adopted.
E in-
if incident so-
to the foliage (ES); an efficiency due to the tion by foliage (Q); an efficiency due to the
an effi- ciency due to the
teins and lipids, (Q;
tion thus, is obtained by the
of the
(Hl) (€h) is an additional efficiency to be added to Eq. (2), and to the
for crop response to water: physiological aspects 299
(Y) as
h
Y
= dte
EN is the value of E the satu- of the Si is the incident
flux; e and
E shows to be
the of the
species (Fig. 5).
E, since the
of fact,
most of
in
tion, and validation. A is
in of
the of actual to potential ex- of
instance, might be ex- on the basis of the of 'supply' and 'demand' in hom O (total absence of supply) to 1 (full satisfaction of demand).
Timing of of
accounted of
the
of to the
of
in on
the (b) the spacehime
the system to
this still little is known in rithms
m--')
5 - cumulative biomass to cumulative intercepted for crops dlfSerent photosyn-
thetic metabolism. Synthesis dataji-om dlferent (1986).
300 Steduto
to a lack of suitable validation with the model being d e a s i b l e in
to
quantified.
with in
the and the
in the
etc.) in
leaf
etc.) which add
to to simplifying as-
in the the day, etc. (Azam-Ali et al., 1994).
on the simulations may
the models. A stochastic model to the
tainty of the input so that it
an (e.g., yield) with an
the the in the be-
the is the sto-
to
to in
to implement and to handle. At the moment, the the
The biomass-transpiration relationship One blame to the
to the difficulties in making the ef-
E a function of
such as the limiting
it to the
to
in
the
the beginning of this
in
At the weight
the total
amount of total plant
weight was calculated, defining the so called stone study on the investigated field studies, concluding that
to the
m is a coefficient (the slope)
E, the
to the
of the not
field studies, the
that the tween and T (Fig. 6) is
(e.g., et al., et al., 1977; Tan-
the slope m, as in Eq. (4)
with E, the
@), can be defined as the as
as et al.,
with Eq. (3), then, the
(Y) as
mN is the value of m
the T is the
flux;
and e, h,-and t defined as in Eq. (3).to
in m can the
in the the
crop response to water: physiological aspects 301
soil mass in field
Since it is to account bio- to
500
(u
i
a
k O
0 Avena sativa
v sativum
A A sativum
Stipa capensis
,
10 50
(kg
mm-')
6 - cumulative biomass to cumulative transpiration various field crops in containers, normalized for climatic evaporative demand. and modijìed j?om de Wit (1958).
be
diEculty of
in in is difficulty in con-
Q
(T), so is
used in place of T. This in m
on the of
ing biomass and soil the
stability of can be con-
in in
in the constancy of
m in said be-
cause of that
fact, a func-
be fi-om loca- tion to location with the not
The to the
engine is to the difficulties in sepa-
soil in
estimating the to total
ity.
the limitations due to those such as
tioning of assimilates
data to es-
tablish the stability of m in its con- can be definitely explained on
As two
can be invoked to explain such
(a) the of in both
photosynthetic assimilation and
(b) the of the pathway by
dioxide and the
and the of
the of shows to be domi-
3 O2 Steduto
nant the of the pathway most of the conditions
Since the extent of by the
essentially depends on the leaf displayed
unit of and the
bution of leaves within
between assimilation and of the is in the active wave band
photosynthetically active as-
similation, and all the waveband
is a quite constant
of the incident et
al., 1984) so that also the of to constant. The played by
by then, is in of a
between assimilation and a
tosynthetic assimilation (A) and (T) steady state, as
T = wi -W, 'b
w i and W, the within-leaf
con- and
leaf (mainly sto-
matal) to Q is the CO2
in the space of the leaf; and c,,
,
and have been Eq.
tween
thus, the gaseous phase of
dioxide the same pathways. Only COZ has an additional path to in the liquid
phase, to the sites This path
an additional (
indicated in of the
complex metabolic changes in as a function of conditions, can be avoided
as they in the Q value to ca
1993b). Since the between and and between and only due to diffusivity of and CO2 in ( E 1.6
,
and 1.37 the in valueswill have a impact on assimilation and so that the of assimilation to
will be to the of the C02 to between inside
A c, - ci T
w ~ - w ,
ci constant, to c,
,
and c, does time, then is in- to (wi - W,). As biomass is the of net assimilation, theship T the deficit
(D) would to m its
Although not conditions, in many
species ci has shown to be about constant the same c, (e.g., Wong et al., 1987, 1991). Evidence is accumulat- ing of this
(e.g., 1990; Steduto, 1995) and theo-
using as basis
estimating available (e.g.,
1983; 1993a,b;
teith, 1990, 1993).
All the validity the vegeta-
tive of field fits to
biomass but
tional to account the
yield. index is
taken as the
into yield. Although the
weight shows to be to total
biomass, is not a depending
of
on the stage at which the on the
of assimilates, and on the
tion between and sinks of assimilates
Then, based on way
of modelling can be set by
following
in guideline by
for crop response to water: physiological aspects 3
Y, is the actual Y, is
the maximum yield; ET, is the ET, is the
and ky is an
Eq. (9) showed to be useful and of application (e.g., Cavazza, 1988), adapting ky
the it assumes that input
not the lack
of with
involved in
The case of the crop-growth submodel of
Once the of Eq. (9) is
to developed,
can (b)
(c) to classify all the
job as they multiplicate continuously. Though, among the
the ones of those
cotton
potato
and all the
to of detailed
to accommodate possible changes
in is to Joyce and
an of
models.
can be used
in ag-
and 1982), and
(Stockle et al., the main multi- on which the of this
ticle has is
an example of application.
is a nally developed to evaluate the
sion on the of as
Committee of the United States (Williams et al., 1984). In to evaluate the
simulates on daily time-steps,
the in the
sub-models, each one focusing on a specific mecha- nism to simulate.
Those submodels
nomics, pesticides, and climate changes, added on
the is dis-
to the
tions details and tests on
et al. (1988,1990), and Steduto et al. (1995).
in is simulated, on daily time- step, by: (a) the potential
as function of leaf index of the
day and of the then calculat-
ing the and to
the (c) evaluating the actual
supply and the soil, assign-
ing index O to 1) to each po-
tentially limiting the mini-
as the most limiting day; (e) and lastly, using this
that day to the
The the of
closely the model of
Fig. 3, is shown in Fig. 7.
While the to
of impact on the
lacks of the on leaf ex-
pansion. the
any day ( S , i ) is S . = - 'Ji
W,1 (1 0)
3 04 Steduto
is the soil supply estimated on the basis of
the the
the
fiom than the
of to ex-
the
Shapley and Wil- liams, 1990); and E , i is the
demand, of of S , i is that
the supply (ui) does not match the demand This, is not suf-
of many the
such conditions, the demand is
the supply independently fiom the effect status on
in
et al., 1987; Cabelguenne et al., 1990; Steduto et al., 1995).
the of pos-
on leaf
Notwithstanding the of the
to the
of the conditions.
_ _
. . r - - - I
W I
Radiation'IC
Energy/Biornass conversion
t
7 - Schematic diagram of the relationships among the variables influencing growth and productivity
within the crop-g-owth submodel of Calculator). and
modifiedfrom Steduto et al. (1995).
for crop response to water: physiological aspects 305
The adaptability and flexibility of as a multi- in the Com- mission of the
and
technological development, so that on the
impact of on the economic vi-
systems
tool
to be used as inputs
tions to deal with
economic aspects, some with social issues, and oth-
with it of the
of modelling: the tool of an
OF
the
two main limiting aspects need to be pointed out when dealing with the
elling conditions.
modellìng
of deal with annual spe-
with a be-
which (exponential
two dimensions of the can
be enough to the system (e.g., the big leaf fit most of the field the time scale of the is limited to the life span of
the the and
tively
and the initial conditions of the sys- the least complicate. The system complicates when modelling
and to
show even
tion of this hom a 3-dimensional
and
in the son actual season assimilate allocation, etc.).
Attempts have been made to model et al., 1986) et al.,
on in a
to the incomplete- the
involved in
functions needed, then statistically show to be much
Salìnìty modelling
the
cannot be to
including the effects of salinity on
in the ftom quite a while, consid- the salinity in soil (e.g., Childs and
1975) in
et al., in these
models is that
its of
to the in osmotic potential in the soil which in turn the total potential the plant and the soil. This means that specific ion toxicity is
duction functions, including salinity in the
implemented (e.g., Solomon, 1985; Letey et al., 1985) and used to
could easily take into account the effect of uni- as well as the effect on use efficiency (Letey, 1993). They could also
be used management with
the only implication of
salinity on been on
as it is ftom osmotic
is that they do not take into account the
quality on the the soil.
This is in model-
ling if
long-time dependence of the
well.
306
To deal with the economic aspects of wa- management limited
as it is the case of the is
no question that
‘function’ is
physiological aspects involved in tionships, the
physiologists so that the system has been subdivided much
to handle. moving down in the to the mechanisms explaining the
to which
still does not the
the complex system to in inputs. That is, and
needed to
the attempt to
lationship between inputs and outputs, though, it is
a modelling of on the
of between
the the
identified’(L,oomis et al., 1979): (a) same-level mod-
standing of causality is quite low. Classical yield- h c t i o n to in this
in (b)
of ing of causality is substantially high. They ally tend to be and quantitative
explanation fì-om the knowledge of the
The fiom same-level
models including in implementation at least level below the one at which
to be made. is that is always ultimate
how many the model
stops and the
it to build a
model at no than one at most two levels of
the one of et al.,
1986). on the objec-
tive which the model is
built is being used (and on the data available, choose within
tunities going fkom to a
mechanistic model (Fig. 8).
What is not sufficiently indicated in the is that, as a tool, any model has
sociated to its which
need to using it
application. and
sensitivity analysis jobs which have not yet scientific
institutes.
economists should indicate the maximum values of
in u s e l l
ent significance depending on the objective.
attention in the yield
to as they to the
a than field
salinity issues need to be included in
of to
H
8
-
Schematic representation model types according to their relative empiricism and mechanism content. Some types models be indicated as: SA4 summarizing data; interpolative prediction; research management; extrapolative prediction; interpretation andsimulation experimental results. misler et al. (1986).
for crop response to water: physiological aspects 307
A to many
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to in plant populations, is not
in in
to
of the
some homeostatic mechanisms such as feedbacks and functional balances (Loomis et al., 1979). This
of the with the possibility of
A in using this in
to complexity.
Among the
the the most
used one, though its
is not limiting. the
the is the
in
it the
sponse in to the
fiom both types of models, though,
among the in
of
in the
of still to be
the
tools to be easily plugged into any of
As pointed out by Loomis et al. (1979), in fact, the
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