els || water use efficiency of cultivated crops

Water Use Efficiency ofCultivated CropsNader Katerji, INRA, Unite de Recherche Environnement et Grandes Cultures, Thiverval-

Grignon, France

Marcello Mastrorilli, Consiglio per la Ricerca e la sperimentazione in Agricoltura,

Agricultural Research Council – Research Unit for Agriculture in Dry Environments (CRA-SCA), Bari,

Italy

The concept of crop water use efficiency (WUE), deter-

mined by the ratio between the marketable yield and the

seasonal values of actual evapotranspiration, has become

a suitable tool for analysing the strategies that allow

attaining the best use of water in agriculture. Crop WUE is

easy to quantify from field measurements, but it is a

complex indicator because wide differences can be

observed for the WUE values of the same species culti-

vated under the same site.

In this article, the major causes of the large range of

WUE values are identified and analysed. The authors

demonstrate that the WUE variability can be ascribed

mainly to three factors: agro-techniques (water regime,

mineral supply and water quality), crop (species, varieties

and sensitivity of the growth stage to the stress) and

environment(climate,atmosphericpollution, soil texture

and climate change).

Understanding and taking into consideration the WUE

variability are primary conditions for advanced studies on

WUE. The paths for further research and management

programmes, allowing to valorise the water in agri-

culture, can be drawn from the analysis reported here.

Introduction

The irrigated cropping systems (differently from the rain-fed agriculture) are themainwater consumers of the planet.They utilised 64% of the total water withdrawals and 83%of the total consumptions in 2010. Water withdrawals andconsumptions increased six times on an average between1900 and 2010, nevertheless they could still increase by

18% between 2010 and 2025 (Roche and Zimmer, 2006).However, these global data mask a wide diversity at dif-ferent scales: regional, seasonal and interannual. Suchvariability is due mainly to the climate and to the raindistribution in particular, accompanied by the atmosphericevaporative demand, which is strictly linked to the airtemperature. The drier the climate, the more agriculturedepends on crop irrigation in order to obtain significantand regular productions and, as a consequence, waterwithdrawal does increase. Approximately 75% of thevegetal productions in water scarce regions come from theirrigated surfaces. In these regions the water allocation foragriculture use can attain 90% of the total withdrawals. Itis actually, the major constraint for other water uses(mainly municipal and industrial) that is at the base ofpeople’s well-being.Agricultural sector, especially in regions where water is

scarce, is currently faced with the challenge of newapproaches to water resource management that ensuresprotection of water resources and their integrity. Thisobjective can be attained by three types of strategies(Katerji et al., 2008):

. Save water by controlling water supply through betterdetermination of crop evapotranspiration, that is, waterrequirement (see the review by Rana and Katerji, 2000).

. Ameliorate the performance of irrigation systems sup-plying water to field through new techniques and meth-ods (see review of Pereira et al., 2002).

. Improve water use of cultivated crops.

The third strategy requires the identification and ana-lysis of the major causes acting on the water use of culti-vated crops. This topic is the objective of this article.

Methodology for Determination ofWater Use Efficiency (WUE)

Two approaches can be considered to determineWUE (seeKaterji et al., 2006b for extensive description).

1. The eco-physiological approach is based on the analysisat a given instant of the relationship between carbon

Advanced article

Article Contents

. Introduction

. Methodology for Determination of Water Use Efficiency

(WUE)

. The Concept of the Crop WUE

. A Review of the Value of WUE for Cultivated Crops

. Analysis of WUE

. Conclusion

Online posting date: 15th April 2014

eLS subject area: Plant Science

How to cite:Katerji, Nader; and Mastrorilli, Marcello (April 2014) Water UseEfficiency of Cultivated Crops. In: eLS. John Wiley & Sons, Ltd:

Chichester.

DOI: 10.1002/9780470015902.a0025268

eLS & 2014, John Wiley & Sons, Ltd. www.els.net 1

assimilation rate and transpiration rate per leaf unitarea. This approach helps reach the following results:

. To describe the processes (stomatal and nonstomatalconductance) determining water use efficiency at theleaf scale through theoretical approaches (Cowan,1982).

. To compare the leaf carbon assimilation and tran-spiration capacity of a species cultivated in relationwith soil water deficit conditions and the hormonalsigns from the root system (Damour et al., 2010).See also: Plant Response to Water-deficit Stress;Plant–Water Relations

. To underline the role of the breeding on leaf gasexchanges (Condon et al., 2004), and in particular, itsadvances onmolecular genetics approaches. See also:Abiotic Stress

The eco-physiological approachhelps in the understandingof global results obtained from the agronomical approach.It is evoked in the following paragraphs, which discuss thecauses of the following:

. the differences on crop water use values observedbetween C3 and C4 species,

. the effect of soil texture on crop water use values,

. the lack of a relationship between water use efficiencyand air pollution under water stress condition,

. the effects of the climate change on the water useefficiency.

However, it is not possible to calculate final crop yielddirectly fromcarbon assimilation rate per leaf unit area dueto the interference with many factors like respiration, leafgrowth, partition of assimilates flowering and pod setting.

2. The agronomical approach is based on crop waterconsumption and yield concepts. The time scale con-sidered is the whole vegetative cycle. They are key datato manage crop productions and for studying how tovalorise water in agriculture.

Ecophysiological and agronomic approaches are reallylinked, as showed byHsiao et al. (2007). The use ofwater toproduce food, according to these authors, is retained as aninterlinked chain of sequential efficiency steps. Their ana-lysis represents a relatively simple way to quantify theoverall water use in terms of the efficiency of each of thesteps, which can be divided according to engineering,agronomical and physiological processes.This article is aimed to analyse the WUE through the

agronomic approach. This approach refers to the sametime (the whole crop cycle) and space (the field plot) scalesretained by the three strategies, which have been identifiedin the introduction for setting up correct politics of waterresources management.

The Concept of the Crop WUE

Different concepts have been proposed and discussed tooptimise the crop water use (Pereira et al., 2002; Zwart and

Bsatiaanssen, 2004; Turner, 2004). The most known con-cept is the crop WUE (in kgm23), which results from theratio between yield (kgm22) and water consumption (i.e.actual evapotranspiration during cropping season(m3m22)). Yield is defined at the plot scale and it can beindicated by two parameters: biomass dry matter andmarketable yield.The marketable crop yield is a more interesting criterion

than dry matter, because in some species, like durumwheat, characterised by similar biomass, marketable yieldcan vary significantly as a result of genetic improvement(Katerji et al., 2005a,b).Moreover, it should be underlinedthat it is the marketable yield, and not the biomass, whichsettles on the economic value of any production.

A Review of the Value of WUE forCultivated Crops

Table 1 reports the crop WUE values for 16 species. Thisreview considers uniquely data from the Mediterraneanregion in order to minimise the role of the geographic andclimatic variability on WUE values (see section Climate).In addition, these values derive only from measured dataobtained from experimental setups on marketable yieldand on actual evapotranspiration.In general the crop productions seem highly costly in

water. Crops have to consume 1m3 (1000 l or kgs) of waterlost in air as evapotranspiration for producing 0.5 kgof grains from the broad bean or from the chickpea, 1 kgof grains from wheat, 6.5 kg of roots from sugar beet or oftubers from potato and 17 kg of table grape from thevineyards.The value of WUE of the species whose marketable

values are related to fresh weight (having a high watercontent in the vegetal tissues, as tomatoes and grape) arereasonably higher than the values observed for species withdry yield, like grain crops. For the latter ones, however,large differences exist between crops having C4 or C3metabolism. Corn (a species having the C4 metabolism) ischaracterised by aWUEvalue higher than that observed forcrops having the C3 metabolism, such as sunflower. Thesedifferences are explained by the analysis of the relationshipbetween carbonassimilation rate and stomatal conductanceobserved, at the leaf scale, on this two species (see Katerjiet al., 2006b). They can also be explained by seed compo-sition: corn contains essentially starch, whereas sunflowercontains 50% oil and 20% protein. The biosynthesis oflipids and protein is more expensive than starch.The large differences can be also observed between the

WUEvalues of the same species. These differences can existnot only in studies conducted in different countries, butalso in studies made at the same site. This can not only beseen for winter crops, like wheat, but also for summercrops, like corn (Table 1). This is the rationale of a series ofstudies aiming to analyse and understand the reason of thisvariability.

eLS & 2014, John Wiley & Sons, Ltd. www.els.net2

Water Use Efficiency of Cultivated Crops

Analysis of WUE

The analysis of WUE at the crop scale consists of findingcorrelations between the observed values and a number of

parameters that are retained susceptible to explain theorigin of the WUE variability.The schema for analysing this variability was proposed

by Katerji et al. (2008). It consists in a synthesis of the

Table 1 Observed WUE values (kgm23) for species cultivated in the Mediterranean region

Grain crops

Wheat Syria 0.5–2.5 Oweis, 1997

Morocco 0.11–1.15 Corbeels et al., 1998

Morocco 0.32–1.06 Mrabet, 2002

Israel 0.6–1.60 Amir et al., 1991

Italy 1.02–1.20 van Hoorn et al., 1993

Italy 1.08–1.59 Katerji et al., 2005b

Turkey 1.33–1.45 Sezen and Yazar, 1996

Corn Turkey 1.65–2.15 Dagdelen et al., 2006

Turkey 0.22–1.25 Gencoglan and Yazar, 1999

Italy 1.35–1.80 Ben Nouna et al., 2000

Italy 0.82–1.17 Katerji et al., 1996

Lebanon 1.36–1.89 Karam et al., 2003

France 1.6 Marty et al., 1975

Spain 1.5–2.16 Fernandez et al., 1996

Barley Italy 1.46–2.78 Katerji et al., 2006b

Sunflower Italy 0.39–0.72 Katerji et al., 1996


Soybean Italy 0.47–0.77 Katerji et al., 2003



Sorghum Italy 0.67–1.59 Mastrorilli et al., 1995b

Broad bean Italy 0.86–1.37 Katerji et al., 2003

Italy 0.45–0.92 Katerji et al., 2005a

Syria 0.45–0.66 Oweis et al., 2005

Chickpea Italy 0.46–0.98 Katerji et al., 2005a

Syria 0.4–0.6 Oweis et al., 2004

Lentil Italy 0.36–2.09 Katerji et al., 2003

Syria 0.44–0.58 Oweis, 2004

Industrial crops

Cotton Turkey 0.61–0.72 Dagdelen et al., 2006

Turkey 0.50–0.74 Yazar et al., 1999

Israel 0.22–0.35 Saranga et al., 1998


Sweet sorghum Italy 3.69–4.20 (stalk) Mastrorilli et al., 1995a

Fresh yield crops

Potato Italy 16.2–18.5 Katerji et al., 2003

Sugar beet Italy 6.6–7.0 Katerji et al., 2003

Tomato Italy 4.4–8.3 Katerji et al., 2003

Italy 20 (globe fruit) Rana et al., 2001

Italy 22.2 (long fruit) Katerji and Rana, 2006

Fruit trees

Grapes Italy 16–18.1 Rana and Katerji, 2007

Clementine Italy 18.8 Rana et al., 2005

Source: Reproduced from Katerji et al. (2008).# Elsevier.



recent studies. According the schema shown in the Figure 1,the variability in WUE values derives from three mainfactors:

. Agro-techniques: water and fertiliser applied to cropsand analysed in terms of quantity and quality.

. Crop: differences between species, variety effects andphenological stage sensitivity to water constraints.

. Environment: soil and climate.

The last factor includes evaporative demand, atmosphericpollution and climatic changes.In reality, the different causes act together and indepen-

dently. For example, sunny days favour, at the same time,soil and atmospheric water deficits as well as the increasein air pollution. However, each identified cause will bediscussed separately in order to provide evidence for itsrole and its contribution to the variability of WUE values.

Agro-techniques factors

Water regime

The role of the water regime as a factor influencing WUEwas underlined byOweis (1997).Hemeasured the values ofwheat WUE in the semiarid environment of Syria forseveral years. Wheat was cultivated under irrigated andnonirrigated experimental conditions. This author noticedthat the average WUE of rain-fed wheat in Syria is0.5 kgm23, although with good management and favour-able rainfall amounts and distribution, this average couldbe increased to 1 kgm23. In fully irrigated areas with goodmanagement, the WUE was approximately 0.75 kgm23.

However, water used in supplemental irrigation conditionscan be much more efficient (WUE=2.5 kgm23). Thisextremely high WUE is mainly attributed to the effective-ness of a small amount of water in alleviating severemoisture stress during the most sensitive stages of cropgrowth.The averageWUE of rain-fed wheat observed in Syria is

close to the average (0.43 kgm23) observed in the MiddleEast–North Africa zone (de Fraiture andWichelns, 2007).The value is lower than those observed under the Medi-terranean climate of Australia. In fact, in south-westernAustralia, the average WUE of rain-fed wheat is approxi-mately 1 kgm23 (Sadras and Angus, 2006).

The previous observations, concerning the relationshipbetween WUE and water regime underlines two issues:

. the limit between WUE determined on irrigated andnonirrigated winter crops is not clear;

. the WUE of irrigated crops can present a large range ofvalues.

The generic term ‘irrigated crops’ or ‘rain-fed crops’ caninclude, in reality, extremely different situations of plantwater supply.Ben Nouna et al. (2000) pursued the lesson of Oweis

(1997) by quantifyingmore precisely the cropwater regimeduring the crop season. Three treatments, correspondingto three conditions of corn water status, monitored bypredawn leaf water potential measurements (the value ofthe leaf water potential determined before the sunrise),were identified: (1) IRRI, irrigated when predawn leafwater potential reached –0.3MPa. Such threshold value,

Parameters

Sources of variability

Environment Crop Agro-techniques

Variety

Water regime

Mineral nutrition

WUE

Soil texture

Phenological stage sensitivity

Climate

Air pollution

Climate changesWater quality

C3 and C4 species

Figure 1 Main factors affecting the WUE variability: Schema of analysis. Reproduced from Katerji et al. (2008). & Elsevier.



corresponds to the level at which maize leaf gas exchangesare affected bywater constraints. (2) STR1, irrigated, whenpredawn leaf water potential reached –0.6MPa. Thistreatment corresponded to moderate stress. (3) STR2,irrigated when predawn leaf water potential reached–1.2MPa. This treatment corresponded to severe stress.By using this field protocol for irrigation scheduling,

values of WUE calculated for maize decreased graduallywith the reduction of water supply, and it remained stablefrom one year to the next for the same water supply level(1.82 and 1.74 kgm23 under IRRI treatment, 1.61 and1.63 kgm23 for STR1 treatment and 1.35 and 1.53 forSTR2 treatment).The previous example provides evidence for the neces-

sity of reviewing studies on the relationship ‘water supply–WUE’ using a criterion appropriate to plant water status.The exact definition of the crop water status helps to dis-tinguish the limits between the different water regimes and,consequently, reduces the actual variability in WUEvalues.

Fertilisation supply

The action of mineral supply on WUE seems often to bestrictly related to water supply regime (Oweis, 1997; Oweiset al., 2000; Sadras, 2002, 2004; Zwart and Bastiaanssen,2004). As an example, Oweis (1997) noted that under rain-fed conditions, the rate of nitrogen fertiliser needed forwheat crop is not high, and that 50 kg ha21 is sufficient.However, with higher water supply, the crop responds tonitrogen up to 100 kg ha21 after which no benefit isobtained (Figure 2). This rate of N greatly improves WUE.It is also important tomaintain available phosphorus in thesoil so that the response to N and applied irrigation is notconstrained.The relationship ‘fertilisation–WUE’ for wheat growing

under the Mediterranean climate of Australia has been

discussed by Turner (2004) who simulated yield and eva-potranspiration on soils having different textures. Thesesimulations highlight the role of fertilisation technique inimproving WUE.

Water quality

Soil salinity corresponds to salt accumulation in the rootzone, leading to damage of cultivated plants. The soilsalinity can be characterised through the soil electricalconductivity (in dSm21) of the saturated soil paste extractsampled from the root zone. Themain causes of salinity arethe inappropriate management of irrigation and the use ofmarginal-quality water resources in agriculture, especiallyin water scarce environments.Soil salinity and soil water deficit have similar effects on

crops (Katerji et al., 2009, 2011). In fact, as salinity and soilwater deficit increase, the soil water availability decreases,and thismodifies plantwater status and gas exchange in theshort term, whereas growth and yield in the long term(Katerji et al., 2003).

In the frame of a long duration experiment carried on insouthern Italy, Katerji et al. (2008) analysed the con-sequences of using water of different salinity levels on theWUEof 10 species cultivated in lysimeter. The study showsa good correlation between species tolerance to soil salinityand their aptitude to maintain or to improve WUE whenirrigated with saline water. Based on the average values ofWUE obtained in clay and loam soils, a classification ismade and it led to the identification of two groups of spe-cies (Figure 3). The first includes wheat, sunflower, potato,maize and sugar beet. These species are tolerant to soilsalinity (see the review from Katerji et al., 2003) becausethey maintain, or slightly ameliorate, their WUE with anincrease in soil salinity. The second group includes tomato,lentil, broad bean and chickpea. These species are sensitiveto soil salinity, because their WUE is reduced with the

2.5

Rain-fed

1.0

1.5

2.0

WU

E (k

g m

−3)

Supplemental irrigation

0.0

0.5

0 50 100 150

Nitrogen application (kg ha−1)

Figure 2 Interaction between mineral supply and water supply regime on water use efficiency observed on wheat crop. Adapted from Oweis (1997) and

Katerji et al. (2008). & Elsevier.



increase in soil salinity. The previous observations areimportant for choosing the most appropriate species forsaline soils or for irrigation with saline water. Moreover,the soil salinity for certain species constitutes a cause ofvariability in the determination of WUE values.

Crop factors

This section discusses only the processes associated withcrop water supply responses.

Water stress deficit sensitivity at different cropgrowth stages

From the studies aiming to identify stress-sensitive phe-nological stages on species cultivated in theMediterraneanregion two interesting issues resulted:

. the critical stages correspond to major ones (e.g. flow-ering stage or fruit setting or assimilate transfer) in theelaboration of crop yield.

. during these critical stages amoderate water deficit leadsto a severe yield reduction and to a considerable varia-tion of WUE. In practice, this knowledge leads to theidentification of the conditions necessary for high

efficiency of water supply in relation to crop phenolo-gical stage sensitivity.

To define the sensitive stages, three methods are cur-rently used:

. by introducing soil water stress at a single phenologicalphase;

. by introducing at a single phenological phase a waterdeficit based on the ratio ‘actual evapotranspiration/maximal evapotranspiration’;

. by reducing the leaf water potential (through waterrationing) of plants at different phenological stages(Mastrorilli et al., 1995b, 1999).

Figure 4 and Table 2 provide an example of the methodbased on the field survey of the leaf-water applied to thegrain sorghum crop.When water stress was applied duringthe flowering stage (Figure 4a), the WUE value was one-third of that observed in the control and other treatments(Table 2). This reduction in WUE value is the result of thereduction in grain yield of 65% in respect to the controltreatment (Figure 4b).

The previous examples indicate that the irrigationcalendar, corresponding or not to sensitive phenological

0

30

60

90

0 2 4 6

WU

E (%

)

ECe (dS m−1)

(1) Wheat (1.04)

(2) Sunflower (0.21)

(3) Potato (18.5)

(4) Corn (0.98)

(5) Sugar-beet (7.0)

5)2)

1)

3)

4)

0

30

60

90

0 2 4 6

WU

E (%

)

ECe (dS m−1)

(6) Soybean (0.77) (7) Tomato (8.3)

(8) Broadbean (1.37) (9) Lentil (2.09)

(10) Chickpea (0.81)

10)7)

6)

8)

9)

0

30

60

90

0 2 4 6

WU

E (%

)

ECe (dS m−1)

(1) Wheat (1.04)

(2) Sunflower (0.21)

(3) Potato (18.5)

(4) Corn (0.98)

(5) Sugar-beet (7.0)

2)5)

1)

3)

4)

0

30

60

90

0 2 4 6ECe (dS m−1)

(6) Soybean (0.77) (7) Tomato (8.3)(9) Lentil (2.09) (10) Chickpea (0.81)(8) Broadbean (1.37)

10)7)

6)

8)

9)

Figure 3 Effects of soil salinity ECe on the water use efficiency of 10 species. ECe is soil electrical conductivity of the saturated soil paste extract.

Reproduced from Katerji et al. (2008). & Elsevier.



stages, has an important effect on yield, and consequently,it can be a cause of variability observed in WUE values.

Variety response to water stress

Many studies have been dedicated to the analysis of cropresponse to water stress caused by soil water deficit or soilsalinity in order to identify factors associated with planttolerance (see i.a. Munns, 2002) that may be taken intoconsideration for the creation of new resistant varieties(Ceccarelli et al., 2004).

Genetic improvements affecting the response of culti-vated species to water stress deficit have made importantprogresses in the past 20 years (Cattivelli et al., 2008). Thisprogress, however, has not involved salinity (Sharma andGoyal, 2003; Ashraf and Foolad, 2013).A significant number of recent studies has provided ele-

mentson the relationshipbetweenWUEandplant variety inthe presence and absence of saline stress for many Medi-terranean species. These studies concerned chickpea, broad-bean, durum wheat and barley (Katerji et al., 2005a, b,2006a, 2008).The study on durum wheat included the analysis of the

behaviour of varieties with different genetic origins.Experimental tests in greenhouses analysed yield andwater efficiency of seven varieties irrigated with three dif-ferent water qualities: fresh water, 4 dSm21, and 8 dSm21.

Irrigation was performed whenever soil water contentreached 30% of maximum water content value. Thisexperimental protocol avoided the exposure of plants tosoil water deficit.The seven studied varieties exhibited (Table 3) a large

range ofWUE, depending on irrigation water quality. Thefunctional classification of differentwater qualities allowedfor the identification of two varieties (Haurani andCham1)exhibiting the extreme behaviours at different salineconditions.The difference in WUE of these two varieties confirmed

the results obtained, under soil water deficit conditions, infield experiments (Annicchiarico and Pecetti, 2003) andthrough irrigation with different water qualities (Katerjiet al., 2005b). The WUE values obtained in this study arepresented in Table 4. The Cham1 variety had a higherWUEin comparison with Haurani when irrigated with freshwater, and it ameliorated its WUE when irrigated withsaline water. Under these conditions, both varieties pre-sentedWUE differences that reached approximately 40%.The previous example of wheat underlines two aspects:

. the importance of the choice of varieties resistant to saltor soil water deficit, in order to ameliorate WUE;

. the large variability in WUE, observed within the samespecies, can be attributed to a varietal response to thewater stress, caused either by soil water deficit or salinity.

30

50

70

90

Seed setting Grainformation

Control

Gra

in y

ield

(% o

f the

con

trol

)

(b)

**

n.s.

n.s.

Flowering−3.0

−2.5

−2.0

−1.5

−1.020 40 60 80

MPa

Days after emergence

(a)

Control

Flowering

Seed-setting

Grain formation

Figure 4 Grain sorghum crop: (a) predawn leaf-water potential (in MPa) measured during the crop cycle in 4 water treatments: Control (without any

water stress) + 3 temporary stress at a single phenological stage (flowering, seed-setting, grain formation); (b) grain yield (in % respect to the control)

measured from the 4 water treatments. Reproduced from Mastrorilli et al. (1995b). & Elsevier.

Table 2 Seasonal ET, water use efficiencies for grain (WUEg) and biomass (WUEb) for grain sorghum observed on the control

and temporary stressed treatments

Stress at ET (mm) WUEg (kgm23) WUEb (kgm

23)

Flowering (T1) 369 0.67 2.64

Seed-setting (T2) 360 1.59 4.01

Seed ripening (T3) 390 1.41 4.51

Never (Control) 420 1.51 4.85

Source: Reproduced fromMastrorilli et al. (1995b).# Elsevier.



Environmental factors

Climate

Climate plays a central role inWUE value. On the basis ofobservations made in dry environments (including LoessPlateau of China, Mediterranean region, North AmericaGreat Plains and south-eastern Australia), Sadras andAngus (2006) demonstrated that the variation in WUE ofwheat (ranging from 1 to 0.53 kgm23) was largelyaccounted for by reference evapotranspiration around theflowering stage. The daily evapotranspiration increases inrelation with the increase of air temperature and vapourpressure deficit (VPD).Higher WUE is achievable at lower VPD. The last

parameter represents the difference between the actual andmaximum pressure of water vapour in the air. The effectof VPDonWUEhas been the subject of previous analyses.A review conducted by Zwart and Bastiaanssen (2004) onWUE values observed for a winter crop (wheat) and threesummer crops (corn, rice and cotton), cultivated undersimilar experimental conditions between 10 and 40 degreeslatitude, is of considerable interest. These authors notedthat the VPD generally decreases when moving qawayfrom the equator and WUE is expected to increase withincreasing latitude. For example, the highest WUE valuesoccur between 30 and 40 degrees latitude where a two- tothreefold difference in WUE of wheat, rice and maize wasdetected when compared to areas between 10 and 20degrees latitude. Also, Rodriguez and Sadras (2007)reported a relationship existing between variations inWUE of wheat and latitude in eastern Australia.

The interannual climatic variability observed at the sameexperimental site affects the measured values of WUE aswell. Results of a study released by Katerji et al. (2010) insouthern Italy during a 25-year period, under experimentalneutrality (the same variety, sowing time, fertilisationsupply, soil texture, irrigation scheduling and water qual-ity), showed that the average value of WUE, observed onirrigated corn, is affectedby a standard error of 17%,whichis due exclusively to the climatic variability.

Atmospheric pollution

Some climatic conditions, high temperatures and solarlevels combinedwith stable airmasses and high emission ofair pollutants, favour the formation of secondary pollu-tants such as ozone (O3). Ozone concentration in theatmosphere is evaluated through indices, asAOT40.This isthe accumulated ozone over a threshold of 40 ppb duringan hour. When cumulated AOT40 during the growingseason exceeds a certain threshold, which depends on theozone sensitivity of each species, plant functions, mainlygas exchange, leaf growth, flower andpod setting, yield, areaffected (i.a. Morgan et al., 2003). However, the reportedresults did not provide any information about the rela-tionship between WUE and ozone exposure.One of the first studies on this subject was conducted by

Bou Jaoude et al. (2008a, b) in southern Italy on soybeancrops. Soybean was classified as a species sensitive to ozoneconcentration in atmosphere. WUE value, observed onwell-watered soybean subjected to high level of ozone dur-ing the vegetative cycle (cumulated AOT40=8500pbb.h),

Table 3 Classification of seven durum wheat varieties according to the water use efficiency (WUE) at three salinity levels of

irrigation water

WUE (kgm23)

ECiw=

0.9dSm

–1 V6 1.61 a

ECiw=

4.0dSm

–1 V5 1.68 a

ECiw=

8.0dSm

–1 V7 1.75 a

V7 1.59 a V7 1.61 a V5 1.69 a

V5 1.45 ab V6 1.49 a V6 1.41 b

V4 1.35 ab V4 1.26 b V4 1.40 b

V1 1.24 ab V2 1.21 b V2 1.04 c

V2 1.21 ab V3 1.09 bc V1 0.83 c

V3 1.16 b V1 0.93 c V3 0.78 c

Note: V1 Om Rabi-5; V2 Hagla; V3 Haurani; V4 Gidara-2; V5 Cham-1 (Waha); V6 Jennah Khetifa and V7 Belikh-2.Numbers followed by different letters are significantly different at the 5% level according to the Student–Neuman–Keuls test.Source: Reproduced from Katerji et al. (2008).# Elsevier.

Table 4 Interactive effects of three levels of soil salinity during the growing season and two durumwheat varieties (salt sensitive,

Haurani; salt tolerant, Cham-1) on seasonal actual evapotranspiration (ET), grain yield and water use efficiency (WUE)

Haurani Cham-1

Soil salinity (dSm21) 0.9 4.8 7 0.9 4.2 6.9

ET (m3m22) 0.72 0.64 0.60 0.68 0.60 0.55

Yield (kgm22) 0.83 0.69 0.66 0.97 0.96 0.87

WUE (kgm23) 1.15 1.08 1.10 1.43 1.58 1.59

Source: Reproduced from Katerji et al. (2005b).# Elsevier.



decreased by 30% in comparison with a control treatment(cumulated AOT40=0, obtained after air filtering). Con-versely, ozone had a not-significant effect on the WUEvalues observed on water-stressed soybean. Authorsdemonstrated that the absence of effect on water-stressedplants is due to stomatal closure, which reduces ozone fluxtowards leaves and thus its action on plant functions. Theseresults are the same as those observed in wheat (Khan andSoja, 2003), cotton (Heagle et al., 1988) and white clover(Fagnano and Merola, 2007).

Soil texture

The effect of soil texture, as a factor susceptible to mod-ifying WUE, was examined by Turner (2004). The authorreports that for wheat grown in Australia, WUE deter-mined on clay soil is lower thanWUEdetermined on sandysoil.Moreover, he highlights that the observed reduction isaffected by the level of nitrogen in the soil (see sectionFertilisation supply). However, these observations are notderived from measurements because they have beenobtained through simulations of yield, soil evaporationand plant transpiration.The study by Katerji and Mastrorilli (2009) on six spe-

cies (Table 5) is based onmeasurements of marketable yieldand seasonal actual evapotranspiration (ET) obtainedunder experimental neutrality (the same variety, sowingtime, fertilisation supply, irrigation scheduling and freshwater quality) in clay and loam soils.

TheWUE values observed in the loam soil (Table 5) weresystematically higher than those observed in clay. How-ever, the species can be classified into two groups. The firstgroup includes potato, corn, sunflower and sugar beet. Forthese species, the reduction in WUE in clay soil was sig-nificant and ranged from 22% to 25% with respect to theWUE values observed in the loam soil. This was due tosignificant reductions both in yield andETobserved in claysoil, with corn being the only exception. The reduction inWUE in this crop depended solely on a decrease in yield,whereas the differences in ET between the two soils werenot significant. The second group included soybean andtomato. For both species, the level of reduction in WUEobserved in clay soil was only 10%, which is not statisti-cally significant. In the case of soybean, there were nosignificant differences between the two soils for yield andET. Although in the case of tomato, only the variable yieldwas significantly lower in the clay soil.Convergent observations of stomatal conductance, leaf

water potential and actual evapotranspiration emphasisethat the water status of sugar beet plants growing in clay isless favourable than the water status of plants growing inloam (Katerji andMastrorilli, 2009). The more favourablecondition in loam soil has two origins:

. higher available water and easier soil water movements;

. higher root system capacity for water uptake.

The latter depends on root density and distribution,which in turn depends on the soil texture.

Table 5 Evapotranspiration (ET in mm), marketable yield (t ha21), WUE (kg m23) observed in different soil textures for the six

studied crops

Crop Clay Loam

Potato ET 363 415 a

Yield (tuber) 5.8 8.6 b

WUE 16.1 21.0 a

Corn ET 644 607 n.s.

Yield (grain) 0.55 0.68 b

WUE 0.87 1.13 a

Sunflower ET 1215 1450 a

Yield (grain) 0.22 0.35 b

WUE 0.18 0.24 a

Sugar beet ET 731 836 a

Yield (root) 4.47 6.56 b

WUE 6.11 7.85 b

Soybean ET 430 410 n.s.

Yield (grain) 0.31 0.33 n.s.

WUE 0.73 0.81 n.s.

Tomato ET 667 708 n.s.

Yield (fruit) 5.31 6.12 a

WUE 8.01 8.65 n.s.

ap40.05.

bp40.01.n.s.=not significant.Source: Reproduced from Katerji and Mastrorilli (2009).# Elsevier.



Climatic changes

Climatic change is due to the continuous rise of greenhousegases, primarily in the form of CO2. According to recentscientific reports, the effect of these variations on meanearth temperature levels are not yet known, especiallywhenthey are evaluated through general circulation models.These models were developed to take into considerationmany processes essential in determining future climate(radiation, convection, air mass circulation and turbulenceexchange with the surface), and they are susceptible, con-sequently, to important variability.In the analysis of the effect of environmental modifica-

tion on WUE, it is necessary to distinguish the effectsrelated toCO2 and temperature increases from thosewhichdepend on thewater regimes and their possible interactions(Katerji et al., 2008).

The rise in CO2 levels increase WUE values for the fol-lowing two reasons:

. The increase in photosynthesis results in a yield increase.C3 crops (wheat, rice and potato) increase yield up to30% when CO2 doubles. For C4 crops (corn and sor-ghum), however, the effect of CO2 levels on photo-synthesis is lower and final yield is not significantlyaffected.

. The reduction in stomatal conductance entails thereduction in transpiration of C3 and C4 plants. Formaize, with the doubling of CO2 level, transpiration isreduced by 15–17%. As a consequence, the WUE forbiomass increased by 24% (Bethenod et al., 2001).

Temperature increases modify WUE for two reasons:

. The reduction of crop cycle, which reduces water con-sumption (Campi et al., 2012).

. The increase of daily evapotranspiration due to theincrease in air in temperature and VPD (see sectionClimate).

The analysis of the interaction between temperature andCO2, associated with more or less important modificationson water regimes, is possible nowadays through the use ofcrop simulatingmodels that incorporate climatic scenariosexpected to occur in the future. Thus, these models givepredictions in relation to crop type,water amount, fertiliseruptake, and they test the strategies of water need andadaptation to climatic change.A recent example of such studies was performed using

two extreme climatic scenarios on corn grown under con-trasting water condition in southern Italy. This studyreported by Katerji et al. (2008) simulated the yield andwater use of corn through the Stics model (Brisson et al.,2003).In comparison with the 1984–2004 period, the corn

simulation in the 2070–2099 period, under both climaticscenarios, will reduce slightly the above-ground biomass.Conversely, grain yield is severely affected due to lowergrain weight. This yield component is reduced as a con-sequence of the shorter duration of the flowering-maturity

phase. Simulation also shows a reduction in seasonal eva-potranspiration. Finally, WUE values provided for thesimulations in the 2070–2099 period seem lower.However,due to a high variability, they do not differ significantlyfrom the values observed during the 1984–2004 period.For the C3 species results are different, as reported by

Asseng et al. (2004) for wheat, simulated in the Medi-terranean environment of western Australia. The increasein temperature andCO2 has a positive effect on grain yield,whereas evapotranspiration is reduced. According to theseobservations the WUE for wheat is expected to increase.However, after a more detailed simulation for differentAustralian sites and climatic scenarios, Ludwig andAsseng(2006) report that the predicted WUE increment varieswith seasonal rainfall distribution and differs significantlybetween soil types and locations.

Conclusion

The concept of crop WUE is easy to quantify from fieldmeasurements, but it should be retained as a complex indi-cator, because its intrinsic variability in relation with somefactors are identified and analysed in this article. Only if thecauses of such variability are known and taken into rightconsideration, the concept of WUE can represent an inter-esting tool for studying how to valorise the water in agri-culture. Studies on this topic should cover two pathways:

. The first type of studies are based essentially on fieldmeasurements and it consists of identifying and analys-ing the relation between the observed WUE values,obtained from different crops, and a number of para-meters that are retained as important to explain theorigin of the WUE variation and variability. The studyreported here is an example of this kind of approach.

. The second type of studies aim to highlight differentpotential strategies, based on agronomic and economicmanagements, in order to ameliorate crop WUE parti-cularly in areas where water resources are limited(Katerji et al., 2010; Andarzian et al., 2011; Garcia-Vilaand Fereres, 2012). For recommending solid watermanagement choices, each factor affecting crop WUEshould be previously identified and successively theirpotential interactions can be assessed. This objective isachievable through the correct use of crop models(Ritchie and Basso, 2008; Katerji et al., 2013). Never-theless, the choice of an operative model dependson its performance in correctly simulating, under con-trasting water stress conditions, the actual crop evapo-transpiration, biomass production and the finalharvestable yield. Many models can be generated tosatisfy the above exigencies, and these models havebecome available in the scientific literature over the pastthirty years. This is the case in some models: CERES(Jones and Kiniry, 1986), WOFOST (Van Diepen et al.,1989), EPIC (Jones et al., 1991), CropSyst (Stockle andNelson, 2000), STICS (Brisson et al., 2003), CRITERIA



(Marletto et al., 2007) and AquaCrop (Steduto et al.,2012).

References

Amir J, Krikun J, Orion D, Putter J and Klitman S (1991) Wheat

production in arid environment. 1. Water-use efficiency, as

affectedbymanagement practices.FieldCropResearch 27: 351–

364.

Andarzian B, BannayanM, Steduto P et al. (2011) Validation and

testing of the AquaCrop model under full and deficit irrigated

wheat production in Iran.AgriculturalWaterManagement 100:

1–8.

Annicchiarico P and Pecetti L (2003) Developing tall durum

wheat plant type for semi-arid Mediterranean cereal-livestock

farming systems. Field Crop Research 80: 157–164.

AshrafMandFooladMR (2013) Crop breeding for salt tolerance

in the era of molecular markers and marker-assisted selection.

Plant Breeding 132: 10–20.

Ben Nouna B, Katerji N and Mastrorilli M (2000) Using the

CERES-Maize model in a semi-arid Mediterranean environ-

ment. Evaluation of model performance. European Journal of

Agronomy 13: 309–322.

Bethenod O, Ruget F, Katerji N, Combe L and Renard D (2001)

Impact of atmospheric CO2 concentration on water use effi-

ciency of maize. Maydica 46: 75–80.

Bou Jaoude M, Katerji N, Mastrorilli M and Rana G (2008a)

Analysis of the effect of ozone on soybean in theMediterranean

region. I. The consequences on crop-water status. European

Journal of Agronomy 28: 508–518.

Bou Jaoude M, Katerji N, Mastrorilli M and Rana G (2008b)

Analysis of the ozone effect on soybean in the Mediterranean

region. II. The consequences on growth, yield and water use

efficiency. European Journal of Agronomy 28: 519–525.

Brisson N, Gary C, Justes E et al. (2003) An overview of the crop

model STICS. European Journal of Agronomy 18: 309–332.

Campi P, Navarro A, Giglio L, Palumbo AD and Mastrorilli M

(2012)Modelling forwater supply of irrigated cropping systems

on climate change. Italian Journal of Agronomy 7. doi:10.4081/

ija.2012.e14.

Cattivelli L, Rizza F, Badeck FW et al. (2008) Drought tolerance

improvement in crop plants: an integrated view from breeding

to genomics. Field Crop Research 105: 1–14.

Ceccarelli S, Grando S, BaumMandUdupa SM (2004) Breeding

for drought resistance in a changing climate. In: Baker FWG

(ed.) Drought Resistance in Cereals, pp. 167–190. Wallingford,

UK: CAB International.

Condon AG, Richards RA, Rebetzke GJ and Farquhar GD

(2004) Breeding for high water-use efficiency. Journal of

Experimental Botany 55: 2447–2460.

Corbeels M, Hofman G and van Cleemput O (1998) Analysis of

water use by wheat grown on a cracking clay soil in a semiarid

Mediterranean environment: weather and nitrogen effects.

Agricultural Water Management 38: 147–167.

Cowan IR (1982)Regulationofwater use in relation to carbongain

in higher plants. In: Lange OL, Nobel PS and Osmond CB (eds)

Physiological Plant Ecology II (Water Relations and Carbon

Assimilation), pp. 589–613. Berlin Heidelberg: Springer.

Da&gdelen N, Yılmaz E, Sezgin F and Gurbuz T (2006) Water-

yield relation and water use efficiency of cotton (Gossypium

hirsutum L.) and second crop corn (Zea mays L.) in western

Turkey. Agricultural Water Management 82: 63–85.

Damour G, Simonneau T, Cochard H and Urban L (2010) An

overview of models of stomatal conductance at the leaf level.

Plant Cell and Environment 33(9): 1419–1438.

Fagnano M and Merola G (2007) Ozone and water stress: effects

on the behaviour of twowhite clover biotypes. Italian Journal of

Agronomy 2: 3–12.

Fernandez JE,Moreno F,Murillo JM et al. (1996)Water use and

yield of maize with two levels of nitrogen fertilization in SW

Spain. Agricultural Water Management 29: 215–233.

de Fraiture C and Wichelns D (2007) Looking ahead to 2050:

scenarios of alternative investment approaches. In: Molden D

(ed.) Water for Food, Water for Life: A Comprehensive Assess-

ment of Water Management in Agriculture, pp. 91–145.

London: International Water Management Institute. Earth-

scan and Colombo.

Garcia-Vila M and Fereres E (2012) Combining the simulation

crop model AquaCrop with an economic model for the opti-

mization of irrigation management at farm level. European


Gencoglan C and Yazar A (1999) The effects of deficit irrigation

on corn yield and water use efficiency. Turkish Journal of

Agriculture and Forestry 23: 233–241.

Heagle A, BodyD andHeckW (1988) An open-top field chamber

to assess the impact of air pollution on plants. Journal of

Environmental Quality 2: 365–368.

van Hoorn JW, Katerji N, Hamdy A and Mastrorilli M (1993)

Effect of saline water on soil salinity and on water stress,

growth, and yield of wheat and potatoes. Agricultural Water

Management 23: 247–265.

Jones CA, Dyke PT, Williams JR et al. (1991) EPIC: an opera-

tional model for evaluation of agricultural sustainability.

Agricultural Systems 37(4): 341–350.

Jones CA and Kiniry JR (1986) CERES-Maize. A Simulation

Model of Maize Growth and Development, 194 pp. College

Station, TX: Texas A &M University Press.

Karam F, Breidy J, Stephan C and Rouphael J (2003) Evapo-

transpiration, yield and water use efficiency of drip irrigated

corn in the Bekaa Valley of Lebanon. Agricultural Water


Karam F, Masaad R, Daccache A, Mounzer O and Rouphael Y

(2006)Water use and lint yield response of drip irrigated cotton

to the length of irrigation season. Agricultural Water Manage-

ment 85: 287–295.

KaramF,MasaadR, Sfeir T,Mounzer O andRouphael Y (2005)

Evapotranspiration and seed yield of field grown soybeanunder

deficit irrigation conditions. Agricultural Water Management

75: 226–244.

Katerji N, Campi P and Mastrorilli M (2013) Productivity, eva-

potranspiration, and water use efficiency of corn and tomato

crops simulated by AquaCrop under contrasting water stress

conditions in the Mediterranean region. Agricultural Water


Katerji N, vanHoorn JW,HamdyA,KaramF andMastrorilliM

(1996) Effect of salinity on water stress, growth, and yield of

maize and sunflower.AgriculturalWaterManagement 30: 237–

249.



Katerji N, van Hoorn JW, Hamdy A and Mastrorilli M (2003)

Salinity effect on crop development and yield, analysis of salt

tolerance according to several classification methods. Agri-

cultural Water Management 62: 37–66.

Katerji N, van Hoorn JW, Hamdy A, Mastrorilli M and Oweis T

(2005a) Salt tolerance analysis of chickpea, faba bean and

durumwheat varieties. I. Chickpea and faba bean.Agricultural

Water Management 72: 177–194.

Katerji N, van Hoorn JW, Hamdy A et al. (2005b) Salt tole-

rance analysis of chickpea, faba bean and durum wheat vari-

eties. II. Durum wheat. Agricultural Water Management 72:

195–207.

Katerji N, van Hoorn JW, Hamdy A et al. (2006a) Classification

and salt tolerance analysis of barley varieties. Agricultural

Water Management 85: 184–192.

KaterjiN andMastrorilliM (2009) The effect of soil texture on the

water use efficiency of irrigated crops: results of a multi-year

experiment carried out in the Mediterranean region. European


Katerji N, Mastrorilli M and Cherni HE (2010) Effects of

corn deficit irrigation and soil properties on water use effi-

ciency. A 25-year analysis of a Mediterranean environment

using the STICS model. European Journal of Agronomy 32:

177–185.

Katerji N, Mastrorilli M, van Hoorn JW et al. (2009) Durum

wheat and barley productivity in saline–drought environments.

European Journal of Agronomy 31: 1–9.

Katerji N, Mastrorilli M, Lahmer FZ, Maaloufd F and Oweis T

(2011) Faba bean productivity in saline–drought conditions

European Journal of Agronomy 35(1): 2–12.

Katerji N, Mastrorilli M and Rana G (2006b) Analysis and

improvement of water use efficiency for crops cultivated in the

Mediterranean regions: the state of the art, 32 pp. Bari: CRA

SCA.ISBN 2-85352-348-9.

Katerji N, Mastrorilli M and Rana G (2008) Water use efficiency

of crops cultivated in the Mediterranean region: review and

analysis. European Journal of Agronomy 28: 493–507.

Katerji N andRanaG (2006)Modelling evapotranspiration of six

irrigated crops under Mediterranean climate conditions. Agri-

cultural and Forest Meteorology 138: 142–155.

Khan S and Soja G (2003) Yield responses of wheat to ozone

exposure as modified by drought-induced differences in ozone

uptake. Water Air Soil Pollution 147: 299–315.

Ludwig F and Asseng S (2006) Climate change impacts on wheat

production in a Mediterranean environment in Western Aus-

tralia. Agricultural Systems 90: 159–179.

Marletto V, Ventura V, Fontana G et al. (2007) Wheat growth

simulation and yield prediction with seasonal forecasts and a

numerical model. Agricultural and Forest Meteorology 147(1–

2): 71–79.

Marty JR, Puech J, Maertens C and Blanchet R (1975) Etude

experimentale de la reponse de quelques grandes cultures a

l’irrigation. Comptes Rendus de l’Academie d’Agriculture de

France 61: 560–567.

Mastrorilli M, Katerji N, Rana G and Steduto P (1995a) Sweet

sorghum in Mediterranean climate: radiation use and biomass

water use efficiencies. Industrial Crops Products 3: 253–260.

Mastrorilli M, Katerji N and Rana G (1995b) Water efficiency

and stress on grain sorghum at different reproductive stages.


Mastrorilli M, Katerji N and Rana G (1999) Productivity and

water use efficiency of sweet sorghum as affected by soil water

use deficit occurring at different vegetative growth stages.

European Journal of Agronomy 11(3–4): 206–216.

MorganPB,AinsworthEAandLongSP (2003)Howdoes elevated

ozone impact soybean? A meta-analysis of photosynthesis,

growth and yield. Plant, Cell and Environment 26: 1317–1328.

Mrabet R (2002) Wheat yield and water use efficiency under

contrasting residue and tillage management systems in a semi-

arid area of Morocco. Experimental Agriculture 38: 237–248.

Munns R (2002) Comparative physiology of salt and water stress.

Plant, Cell and Environment 25: 239–250.

Oweis T (1997) Supplemental irrigation. A highly efficient water

use practice ICARDA Editions, 16 pp.

Oweis T (2004) Lentil production under supplemental irrigation

in a Mediterranean environment. Agricultural Water Manage-

ment 68: 251–265.

Oweis T, Hachum A and Pala M (2004) Water use efficiency of

winter-sown chickpea under supplemental irrigation in a

Mediterranean environment. Agricultural Water Management

66: 163–179.

Oweis T, Hachum A and Pala M (2005) Faba bean productivity

under rainfed and supplemental irrigation in northern Syria.


Oweis T, ZhangH and PalaM (2000)Water use efficiency of rain-

fed and irrigated bread wheat in aMediterranean environment.

Agronomy Journal 92: 231–238.

Pereira LS, Oweis T and Zairi A (2002) Irrigation management

under water scarcity.Agricultural WaterManagement 57: 175–

206.

Rana G and Katerji N (2000) Measurements and estimation

of actual evapotranspiration in the field under Mediterra-

nean climate: a review. European Journal of Agronomy 13: 125–

153.

Rana G and Katerji N (2007) Direct and indirect methods to

simulate the actual evapotranspiration of irrigated overhead

table grape vineyard under Mediterranean conditions. Hydro-

logical Processes 22: 181–188.

Rana G, Katerji N and De Lorenzi F (2005) Measurement and

modelling of evapotranspiration of irrigated citrus orchard

under Mediterranean conditions. Agricultural and Forest

Meteorology 128: 199–209.

Rana G, Rinaldi M, Introna M and Cicirietti L (2001) Determi-

nazione sperimentale dei consumi idrici del pomodoro da industria

in Capitanata. Atti del Convegno ‘‘Modelli di agricoltura

sostenibile per la pianura meridionale: gestione delle risorse

idriche nelle pianure irrigue’’, pp. 99–106. 6 November 2000,

Salerno.

Ritchie JT and Basso B (2008)Water use efficiency is not constant

when crop water supply is adequate or fixed: the role of agro-

nomic management. European Journal of Agronomy 28: 273–

281.

Roche PA and Zimmer D (2006) Eau, Amenagement et Usages.

In: Les Eaux Continetales. Rapport sur la Science et la Tech-

nologie No 25 (Ghislain De Marsily Animateur), pp. 9–93. Les

Ulis (France): Academie des Sciences.

Sadras VO (2002) Interaction between rainfall and nitrogen fer-

tilization of wheat in environments prone to terminal drought:

economic and environmental risk analysis. Field Crops

Research 77: 201–215.



Sadras VO (2004) Yield and water-use efficiency of water- and

nitrogen-stressed wheat crops increase with degree of co-lim-

itation. European Journal of Agronomy 21: 455–464.

Sadras VO and Angus JF (2006) Benchmarking water use effi-

ciency of rain-fed wheat in dry environments. Australian Jour-

nal of Agriculture Research 57: 847–856.

Saranga Y, Flash I and Yakir D (1998) Variation in water-use

efficiency and its relation to carbon isotope ratio in cotton.Crop

Science 38: 782–787.

Sezen SM and Yazar A (1996) Determination of water-yield

relationship of wheat under Cukurova conditions. Turkish

Journal of Agriculture and Forestry 20: 41–48.

Sharma SK and Goyal SS (2003) Progress in plant salinity resis-

tance research: need for an integrative paradigm. In: Goyal SG,

Sharma SK and Rains DW (eds) Crop Production in Saline

Environments: Global and Integrative Perspectives, pp. 387–407.

Binghampton, NY: Haworth Press.

Steduto P, Hsiao TC, Fereres E and Raes D (2012) Crop yield

response to water FAO Irrigation and Drainage Paper 66, 500

pp. Rome, Italy.

Stockle CO and Nelson RL (2000) CropSyst User’s Manual

(Version 3.0), Biological Systems Engineering Department.

Pullman, WA: Washington State University.

Turner NC (2004) Agronomic options for improving rainfall-use

efficiency of crops in dryland farming systems. Journal of

Experimental Botany 55: 2413–2425.

Van Diepen CA, Wolf J, Van Keulen H and Rappoldt C (1989)

WOFOST: a simulationmodel of crop production.SoilUse and


Yazar A, Howell TA, Dusek DA and Copeland KS (1999) Eva-

luation of water stress index for LEPA irrigated corn. Irrigation

Science 18: 171–180.

Zwart SJ and BastiaanssenWGM (2004) Review of measured

crop water productivity values for irrigated wheat, rice, cotton,

and maize. Agricultural Water Management 69: 115–133.

Further Reading

Fereres E and Soriano MA (2007) Deficit irrigation for reducing

agricultural water use. Journal of Experimental Botany 58: 147–

159.

Hsiao T, Steduto P and Fereres E (2007) A systematic and

quantitative approach to improve water use efficiency in agri-

culture. Irrigation Science 25: 209–231.

KaterjiNandRanaG(2014)FAO-56methodology fordetermining

water requirement of irrigated crops: critical examination of the

concepts, alternative proposals and validation in Mediterranean

region.Theoretical and Applied Climatology. doi:10.1007/s00704-

013-0972-3. http://dx.doi.org/10.1007/s00704-013-0972-3.

Kirda C,Moutonnet P, Hera C andNielsenDR (eds) (1999)Crop

Yield Response to Deficit Irrigation, 262 pp. Dordrecht, The

Netherland: Kluwer Academic Publishers.



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