translational research impacting on crop productivity in drought-prone environments

Available online at www.sciencedirect.com

Translational research impacting
on crop productivity indrought-prone environmentsMatthew Reynolds1,2 and Roberto Tuberosa3
Conventional breeding for drought-prone environments (DPE)

has been complemented by using exotic germplasm to extend

crop gene pools and physiological approaches that consider

water uptake (WU), water-use efficiency (WUE), and harvest

index (HI) as drivers of yield. Drivers are associated with proxy

genetic markers, such as carbon-isotope discrimination for

WUE, canopy temperature for WU, and anthesis-silking interval

for HI in maize. Molecular markers associated with relevant

quantitative trait loci are being developed. WUE has also been

increased through combining understanding of root-to-shoot

signaling with deficit irrigation. Impacts in DPE will be

accelerated by combining proven technologies with promising

new strategies such as marker-assisted selection, and genetic

transformation, as well as conservation agriculture that can

increase WU while averting soil degradation.

Addresses1 International Maize and Wheat Improvement Center (CIMMYT),

Int. AP 6-641, 06600 Mexico, D.F., Mexico2 Australian Centre for Plant Functional Genomics (ACPFG),

Adelaide, Australia3 Department of Agroenvironmental Sciences and Technology,

Viale Fanin 44, 40127 Bologna, Italy

Corresponding author: Reynolds, Matthew ([email protected])

Current Opinion in Plant Biology 2008, 11:171–179

This review comes from a themed issue on

Plant Biotechnology

Edited by Jan Leach and Andy Greenland

Available online 7th March 2008

1369-5266/$ – see front matter

# 2008 Elsevier Ltd. All rights reserved.

DOI 10.1016/j.pbi.2008.02.005

IntroductionImproving crop productivity in drought-prone environ-

ments (DPEs) is a daunting challenge because of the many

traits involved and their interactions with the environment

(Table 1). Conventional breeding [1,2] and more recently,

trait-based approaches [3�] and wide-crossing [4,5] have

achieved significant impacts. With respect to molecular

technologies, marker-assisted selection (MAS) is routinely

applied for genetically simple traits indirectly related to

drought tolerance like disease resistance [6�,7]. Quantitat-

ive trait loci (QTLs) become an unavoidable crossroad for

the molecular tailoring of crops because most drought-

adaptive traits are polygenic. However, despite theoretical

advantages of utilizing MAS to improve quantitative traits

www.sciencedirect.com

[8] and the impressive progress of the ‘-omics’ platforms

during the past decade [9], the overall impact of MAS on

the direct release of drought-tolerant cultivars remains

negligible. Transgenic and genomic technologies have

generated considerable information on the molecular basis

of abiotic-stress adaptation [9–11] and may soon deliver

impacts [12,13��]. Although breeding accounts for half or

less of productivity gains in DPE, crop management

explains the rest [14]. Since the latter has focused largely

on the availability and efficient use of soil resources it is,

therefore, highly complementary to genetic approaches

which have focused prevalently on the expression of

above-ground traits, in addition to the fact that soil

resources represent an essential baseline for genetic im-

provement. This review addresses translational research in

the above areas, where investigations have led to inno-

vations impacting on crop productivity, along with emer-

ging areas strategic for future impacts.

Exploring genetic diversityWhile conventional plant breeding has achieved signifi-

cant progress in DPE [1,2], three main approaches can be

employed to widen gene pools [9,11], namely: first, intro-

gression from germplasm with compatible genomes; sec-

ond, wide crosses involving inter-specific or inter-generic

hybridization; and third, genetic transformation. Land-

races have been used extensively to introduce genes for

biotic-stress and abiotic-stress resistance [2,5]; for

example, drought tolerance of biological nitrogen fixation

in soybeans [20].

Despite extensive use of inter-specific and inter-generic

hybridization to introgress genes for biotic stress [21],

only few wild relatives of crops have been used to

improve drought adaptation [22]. However, wheat has

been an outstanding model for alien introgressions [5].

The evolution of hexaploid wheat resulting from hybrid-

ization between tetraploid wheat and diploid Aegilopstauschii created a genetic bottleneck that can be overcome

by resynthesizing the hybridization using a spectrum of

diploid and tetraploid accessions [5]. Drought-adaptive

traits associated with A. tauschii have been used for

semi-arid environments in Australia [23] and by

the International Maize and Wheat Improvement Centre

(CIMMYT) [5,24,25]. Comparison of synthetic derivative

lines with recurrent parents showed increased water

uptake associated with a root system that was more

responsive to moisture stress than conventional varieties,

changing its relative depth profile according to moisture

availability [24].


mailto:[email protected]

http://dx.doi.org/10.1016/j.pbi.2008.02.005

172 Plant Biotechnology

Table 1

Factors directly affecting productivity in drought-prone environments

References

Genetic

Traits presented in Figure 1

Crop phenology and stress escape [14]

Ability of plants to sense and respond to environmental cues (e.g. through root signaling) [15]

Balance between conservative mechanisms which favor evolutionary survival versus those which favor economic productivity [10]

Epistasis [16]

Environment

(a) Seasonal water distribution profile

(b) Meteorological factors affecting plant–water relations (radiation, temperature, humidity, and wind)

(c) Soil physical properties that influence root growth, access to water, and water storage capacity

(d) Soil chemical properties that influence the utility of water sources (e.g. toxic levels of Bo and Na or

deficiencies in microelements such as Zn)

[7,17]

(e) Presence of diseases that exacerbate drought stress (especially root diseases) [6�,7]

(f) Crop management practices that impact on water availability [18�]

(g) Latitude and sowing date that affect photoperiod response

Genotype � environment (and management) interaction

Trait interaction with site-specific or region-specific environmental factors (a) to (g)

Trait interaction with seasonal variation in environmental factors, especially (a) and (b)

Trait interaction with field-scale spatial variation in environmental factors, especially (c), (d), (e), and (f)

Three-way interaction of crop phenology, trait expression, and environmental factors, especially (g)

Economic imperative to combine drought-adaptation with yield-responsiveness in favorable years [19��]

[QTL � environment interactions are implicit in the above]

References are given where, for the sake of conciseness, themes are not explicitly addressed in the text or otherwise selfevident.

The transgenic approach is theoretically unlimited in its

potential to exploit genetic diversity across taxonomic

groups, and much data have been collected for candidate

genes that improve survival of both model and crop

species under drought in controlled environments

[10,11,13��]. More candidate genes must be tested in a

range of relevant field environments [12,13��] if impacts

of this powerful technology are to be achieved. Candidate

genes, such as those associated with functional proteins

and especially upstream regulation, could affect any of

the drivers of yield (Eq. (1)) depending on at what stage of

development and in which tissue they are expressed.

Therefore, it is important to design experiments to test

these effects, for example, distinguishing between water

uptake (WU) and water-use efficiency (WUE) when

drought tolerance is reported, as well as considering

potential effects on reproductive growth affecting harvest

index (HI) so that genes can be more effectively targeted

in breeding for different environmental constraints. Such

information will facilitate multiple transformation strat-

egies by indicating gene combinations likely to achieve

cumulative gene action.

A framework for genetic improvement andtrait dissectionEq. (1) [26] provided a theoretical framework that stimu-

lated trait-based breeding and genetic dissection of

drought-adaptive mechanisms. While a comprehensive

genetic basis of cultivar level differences in drought

adaptation is being unraveled, physiological traits can

be used as ‘proxy’ genetic markers for relatively heritable


attributes (Figure 1) permitting first, allele enrichment for

specific physiological features in progeny selection [3�] and

second, strategic hybridization between genotypes with

complementary traits [24]. Relative value of candidate

traits (Figure 1) will be a function of target environment:

yield ¼WU�WUE� HI (1)

Traits associated with water uptakeAlthough considerable genetic diversity exists in root

exploration capacity [24], direct selection for variation

in root characteristics is impractical. Nonetheless,

measurements associated with stomatal conductance,

such as canopy temperature (CT), provide indirect

indicators of water uptake by roots [27]. Validation studies

have shown that CT during peak stress periods was

associated with approximately 50% of the variation in

water extraction in deep soil profiles [24] and was also

associated with root length density. CT measured on

wheat recombinant inbred lines (RILs) was associated

with 60% of variation in yield under different DPE [28�].Economic analysis has confirmed the value of CT as an

indirect selection tool to increase breeding efficiency [29]

and CT is used by CIMMYT to shift allele frequencies in

early breeding generations in favor of dehydration avoid-

ance before yield testing is feasible [25].

Given the difficulty of phenotyping roots, molecular

screens are likely to have a considerable cost-benefit

[30�]. Marker-assisted backcrossing (MABC) facilitated

introgression of four QTLs for root length from Azucena


Translational research in drought Reynolds and Tuberosa 173

Figure 1

Conceptual model for traits (expressed in cereals) associated with adaptation to drought-prone environments grouped according to main drivers of

yield under drought as defined by Passioura [26]; relative value of traits will be a function of target environments.

into the upland rice variety Kalinga III [31]; when near

isogenic lines (NILs) obtained through MABC were field-

tested they out-performed the recurrent parent for yield

and biomass.

There is evidence that osmotic adjustment (OA) can

sustain root growth under drought and genetic control

of OA appears to be relatively simple, though benefits of

OA are debated [32]. Nonetheless, the accumulation of

compatible solutes plays a clear role in desiccation toler-

ance, a phenomenon which, though only expressed at

seedling stage in cereals [33] could be further exploited in

DPE [34]. It is expected that more sophisticated

approaches for studying roots [35,36] and better under-

standing of rhizosphere interactions [37�,38] combined

with the power of MAS for hard-to-phenotype traits [30�]will improve WU in crops.

In environments with intermittent rainfall, up to 50% of

precipitation may evaporate from the soil surface. Early

vigor (EV), through reducing evaporation, increases

potential WU; considerable diversity for EV exists among

cereals [39]. Studies using barley chromosome substi-

tution lines in a wheat background led to the develop-

ment of ‘Vig 18’ wheat which achieved ground cover well

before the best parent [40]. Low genetic variation for EV

in wheat is because of the predominance of Rht1 and Rht2alleles that reduce cell length. Alternative dwarfing genes

have been targeted which reduce plant height without

reducing EV; implementation of MAS is being facilitated

by the identification of QTLs of large effect [41].


Traits associated with WUERubisco discriminates in favor of the lighter (and more

common) CO2 isotope (i.e. 12CO2 versus 13CO2). Tissue

analysis confirmed theoretical considerations suggesting

that plants with higher transpiration efficiency (resulting

from a lower stomatal conductance) would express lower13C-isotope discrimination (CID) [39,42��,43]. In

Australia, the trait has been incorporated into wheat

breeding for environments where water must be used

conservatively to permit seed maturation, and cultivars

have been released [42��]. The CID trait has shown

promise/application in several crops [42��] and mapping

studies indicate a polygenic basis [43].

Delayed leaf senescence (stay-green) has been used as a

selection criterion for sorghum breeding under drought in

USA and Australia [44]. Under rain-fed conditions, closely

related hybrids showed stay-green associated with up to

50% more postanthesis biomass than senescent lines.

Trait dissection identified four major stay-green QTLs

(Stg1–Stg4) and their NILs are permitting physiological

dissection [44].

Spike photosynthesis in cereals — associated with high

WUE partially due to re-fixation of respiratory CO2 —

plays a major role in grain-filling under drought, though

genetic diversity for the mechanisms involved [45�] has

yet to be identified. Other subcellular processes such as

photo-protective mechanisms including antioxidant sys-

tems [46], regulation of water flow via aquaporins [47],

and signaling molecules such as abscisic acid (ABA)



Box 1 Model species for dissecting the genetic basis of adaptation

to water-deficit

Attractive features of Arabidopsis as a model for elucidating the

genetic basis of the response to water deficit are the availability of a

well-annotated sequence and extensive collections of genetic

materials coupled with the possibility to carry out high-throughput

phenotyping at a fraction of the cost required with crops [79]. An

example is the identification of genes and QTLs controlling root

architecture and its plasticity [80]. Equally worthy of exploration are

the mechanisms regulating signal transduction in response to

dehydration [48] and the ensuing modifications in gene expression

[81].

Positional cloning has pinpointed the role of the ERECTA gene in

Arabidopsis in the regulation of plant transpiration efficiency.

ERECTA is the first gene described to act on the coordination

between transpiration and photosynthesis, and, as such, to be

identified as a transpiration efficiency gene. ERECTA homologs have

been identified in several species and would represent an interesting

target for an association study in crops. Phylogenetic analysis has

pinpointed that ERECTA has evolved during or before early

Angiosperm evolution, hence underlining its likely role on plant

fitness under the selective pressure of water-limited conditions.

Genetic engineering of ERECTA improved transpiration efficiency in

Arabidopsis without detectable penalty in growth, suggesting the

potential value of its manipulation as a path for improving crop

performance under dry conditions [82].

The growing interest in Arabidopsis and other model plants such as

resurrection plants, [34] will provide additional insights in the genetic

and biochemical basis of adaptation to water scarcity [9]. To what

extent this knowledge will impact on the release of better performing

crops will largely depend on our capacity to identify crops’ orthologs

to Arabidopsis at the target QTLs and properly evaluate their effects

on crops’ response to drought [13��].

which help coordinate these processes [48], may increase

WUE by improving metabolic efficiency. However, their

application in crop improvement will require research

that identifies economically important genetic diversity

and develops tools for their integration in breeding

programs.

Traits associated with harvest indexAlthough increasing HI of cereals crops by the introgres-

sion of dwarfing alleles [41] has had the largest impact of

any genetic intervention on crop productivity [2], the

benefit is less obvious under DPE [49]. Nonetheless,

extreme sensitivity of reproductive processes to drought

is broadly recognized [14,50�], and as a result of repro-

ductive failure yield losses associated with low HI may

eliminate benefits associated with favorable WU or

WUE. Maize shows genetic variation in the relative

timing of male and female ‘readiness’, referred to as

anthesis-silking interval (ASI), a trait exacerbated by

stress. Longer ASI is associated with larger investment

in male versus female reproductive structures, and

because variation in yield showed negative association

with ASI while showing no association with dehydration

avoidance mechanisms, it suggests an evolutionary sur-

vival strategy prioritizing transmission of genes via pollen

[51]. ASI is an example of a survival trait which is

agronomically detrimental and CIMMYT achieved large

genetic gains by selecting against it. Introgression of five

QTL alleles for short ASI has also been achieved through

MABC [52]. Building on ASI-improved germplasm and

the concept of selection under well-managed stress

environments, a CIMMYT-coordinated breeding pro-

gram resulted in significant impacts across southern

Africa [53].

Storage of water-soluble carbohydrates (WSC) in the stem

of small grain cereals and their subsequent remobilization

to grain can directly influence HI especially under post-

anthesis stress. A recent QTL study for WSC [54], sup-

ports earlier observations of drought-independent and

drought-dependent components of HI associated with

large effects of Rht and pleiotropic effects of WU + WUE,

respectively [39].

A modified framework for yield incorporatinggenetic and temporal effectsObservation shows that drivers of yield (Eq. (1)) can be

dissected in terms of their interactions with each other

(pleiotropic and epistatic effects) and over time (pheno-

logical stage and environmental fluxes), permitting a

modification (Eq. (2)) to the conceptual model:

yield ¼Z

WUðLþ sÞ �WUEðLþ sÞ � HIðLþ sÞ (2)

where L is the genes of large effect, s the genes of small

effect andR

is the integration over duration of crop life

cycle.


The model has the following properties: first, relative

genetic independence among drivers of yield is main-

tained; second, coefficients L and s distinguish between

genes of large effect (e.g. photoperiod genes) and genes of

small effect, respectively; third, by considering their

integration over time the drivers of yield are indicated

to interact with phenological stage and temporal changes

in environment. However, the L or s classification for any

given gene (with respect to its effect on yield) will

ultimately be a function of environment, and this is

exemplified by the fact that the dwarfing gene (Sd1) in

rice has large effects on yield under irrigated conditions

and small (or even negative) effects on yield under

drought [49]. The degree of genetic dependence among

traits depends on epistatic interactions among their

respective alleles as well as with environment, processes

which can be modeled [16] and readily validated for traits

amenable to large-scale phenotyping.

Genomics approaches for improving droughttoleranceBoth forward-genetics and reverse-genetics offer unpre-

cedented opportunities to further our understanding of

the genetic basis of drought tolerance in crops [55] and

model species (Box 1). This molecular information can be

exploited for genomics-assisted crop improvement [56]



and MAS. Importantly, during the selection phase MAS

reduces or eliminates the constraints associated with

difficult-to-phenotype traits such as root architecture

[31], osmotic adjustment [32], growth rate [57��], and

WSC translocation [54].

However, only a few QTLs of large effect have been

documented [58]. Because parental lines used for QTL

discovery have been prevalently chosen based on differ-

ences for the traits of interest, and not on the basis of their

agronomic value, QTL alleles associated with high per-

formance are likely to be those already optimized through

conventional breeding in elite materials; additionally, no

systematic effort was made to fix genes of major agro-

nomic effect in RIL populations, making the task of

identifying genes of minor effect statistically more chal-

lenging. This is exacerbated by the extreme sensitivity of

reproductive growth to environment [50�]; consequently,

in experimental populations with variable phenology,

RILs reaching critical growth stages on different days

may trigger different signal transduction pathways.

Accordingly, QTL studies frequently identify major loci

related to flowering time, as those most strongly are

associated with drought adaptation [59,60]. Gene discov-

ery will be accelerated using populations with more

uniform phenology, thereby taking better advantage of

large-scale phenotyping approaches such as IR thermo-

metry [27,28�] and spectral reflectance [61]. Epistasis

further contributes to the inconsistency of QTL effects

in different genetic backgrounds [8]. Therefore, gauging

the importance of epistasis and G � E interactions for

target traits is an important component of the design and

optimization of any MAS strategy [8,62�]. Finally, a major

limitation of MAS pertains to the high cost still associated

with QTL discovery and validation [63].

Table 2

Factors associated with reversing soil degradation and improving wa

Major benefits of CA practices

Reduced water evaporation from soil surface

Increased infiltration of rain water into the soil profile

Improved soil structure and organic matter content increasing

Water-holding capacity

Cation exchange capacity

More stable soil structure that is less prone to wind and water erosion

Strategic research issues facilitating adoption of CA

Genomic studies to develop MAS for CA adaptive traits

Biological control of pests and diseases in CA systems

Bio-fumigation of soils for root disease control

Managing arbuscular mycorrhizae in cropping systems

Biological drilling to increase root penetration to deep water

Exploiting growth promoting rhizobacteria

Quantification of impacts of CA on natural resources

System-level water productivity

Carbon cycle and C sequestration

N cycle, soil microbiology, and greenhouse gas emissions

Interaction of physical fluxes at soil surface (i.e. water, gases, heat, a


Root:shoot interaction and deficit irrigationStudy of root:shoot interaction is fundamental to increas-

ing productivity in DPE. Theoretically, while hydraulic

feedback could explain the reaction of leaf conductance

to soil water deficit, evidence of chemical signals indi-

cated a more sophisticated response consistent with

annual plants’ need to budget available water [15]. This

principle has long been exploited in DPE where inte-

grated long-term response to controlled deficit irrigation

reduces net assimilation rate without decreasing yield

because partitioning to seeds/fruit is maintained at the

expense of structural tissue [64��]. However, new insights

into root-to-shoot signaling have led to novel water-con-

serving irrigation approaches [65]. ABA synthesized in

roots has a central role while apoplastic pH, which is

sensitive to soil and atmospheric conditions, regulates

stomatal response to ABA [15,65]. The mechanism has

been utilized in grape vines through partial root-zone

drying (PRD) where each side of the crop row is irrigated

independently [65] and has potential to improve water

productivity in a wide range of crops [65,66�].

Irrigation efficiency can be further improved through the

application of remote-sensing technologies; thermal ima-

ging that detects spatial variability in fields can be used in

combination with variable rate applicators to apply water

as needed with a resolution of a few meters [67]. Similarly,

simulation models that assist farmers with crop manage-

ment decisions in DPE are becoming more sophisticated,

incorporating information on supplemental irrigation, N

fertility and seed rate [68].

Conservation and precision agricultureCostly investment in genetic improvement will not

achieve impacts if soil degradation because of unsustain-

ter harvest through conservation agriculture

References

[18�,69��]

[74]

[75]

[71]

[37�]

[72]

[38]

[76,77]

nd dust particles) with tillage and crop residues



able cultivation techniques continues [18,69��]. Conserva-

tion agriculture (CA) practices increase both the amount of

water available to crops as well their WUE by reducing

stresses associated with degraded soils (Table 2). Strategic

research (Table 2) is facilitating adoption of CA by small-

scale farmers worldwide. Experimental platforms can be

used to quantify first, water fluxes at the soil surface;

second, nutrient cycling in the rhizosphere; third, bio-

logical control of diseases, pests, and weeds; and fourth,

changes in soil physical and chemical properties. While

research into these areas is relatively new [70�], long-term

trials in rain-fed regions have shown that zero-tillage can

result in substantial productivity gains if residues are

retained [70�]. A key question that simulation modeling

could help to answer, is how much residue must remain so

that the remainder (having economic value as fodder/bio-

fuel) can be safely removed.

Other areas of strategic research that focus on manipulating

the crop environment include: bio-fumigation that permits

control of root diseases (especially prevalent in DPE)

through the rotation with crops leaving biocidal residues

[71]; exploitation of subsoil water through ‘biological dril-

ling’ by the rotation with deep rooting perennial pastures

[72]; exploitation of mycorrhizal fungi to increase water

uptake, improve crop nutrition, and control pathogens

[37�]; use of rhizobacteria which promote growth under

stress [38]; and technologies directed at providing specific

crop needs, that is precision agriculture [73]. An example of

the latter is represented by work showing that zinc

deficiency exacerbates drought stress because of its essen-

tial role in the detoxification of reactive oxygen species;

this led to recommendations for foliar applications affect-

ing 4 million ha of wheat in Turkey alone [17].

ConclusionsTranslational research in DPE consists of a continuum of

activities which may start with the phenotype (obser-

vation of ASI in maize), complex mechanistic theory

(carbon-isotope discrimination by Rubisco), or socioeco-

nomic imperatives (attrition of natural resources). None-

theless, hypothesis testing, extensive phenotyping, and

integration of cost-effective technologies are prerequisite

to achieving impacts; altogether, there is no evidence for a

‘magic bullet’. Within these caveats, new areas of transla-

tional research as discussed can be expected to deliver

urgently needed impacts in DPE and are most likely to be

realized from multidisciplinary approaches that integrate

the wealth of information now readily available (see

http://www.plantstress.com). A starting point would be

to determine which disciplinary approach is most cost-

effective [78]. For example, in a given environment,

genetic efforts could be focused on improving WUE

and HI where analysis suggests agronomic approaches

to be more cost-effective at increasing WU. In summary,

many strands of research offer promise for DPE and their

impact can be accelerated by judicious deployment of


resources at the interface of manipulating both genome

and cropping environment.

AcknowledgementsAuthors thank Richard Richards, Scott Chapman, and Pat Wall for theiruseful discussions on aspects of this review, and many of the authors citedfor suggesting up-to-date literature. The Australian Grains Research andDevelopment Corporation (GRDC) and The Australian Centre for PlantFunctional Genomics (ACPFG) are gratefully acknowledged for theirsupport. Thanks to Julian Pietragalla for the help with technical assistance.

References and recommended readingPapers of particular interest, published within the annual period ofreview, have been highlighted as:

� of special interest

�� of outstanding interest

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This study describes a number of concrete examples from wheat, maize,soybean and sorghum of how physiological approaches have impactedon genetic improvement for DPE.

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