ACUTE VIEW

Model plant systems in salinity and drought stress proteomicsstudies: a perspective on Arabidopsis and SorghumR. Ngara1 & B. K. Ndimba2,3

1 Department of Plant Sciences, University of the Free State, Phuthaditjhaba, South Africa

2 Proteomics Research Group, Department of Biotechnology, University of the Western Cape, Bellville, South Africa

3 Proteomics Research and Services Unit, Agricultural Research Council, Stellenbosch, South Africa

Keywords

Arabidopsis; drought stress; model plant

systems; proteomics; salinity stress; Sorghum.

Correspondence

R. Ngara, Department of Plant Sciences,

University of the Free State, Qwaqwa

Campus, Private Bag X13, Phuthaditjhaba

9866, South Africa.

E-mail: ngarar@qwa.ufs.ac.za

Editor

H.-P. Mock

Received: 1 April 2014; Accepted: 4 August

2014

doi:10.1111/plb.12247

ABSTRACT

More than a decade after the sequencing of its genome, Arabidopsis still stands as theepitome of a model system in plant biology. Arabidopsis proteomics has also taught usgreat lessons on different aspects of plant growth, development and physiology. With-out doubt our understanding of basic principles of plant biology would not have beenthis advanced if it were not for knowledge gained using Arabidopsis as a model sys-tem. However, with the projections of global climate change and rapid populationgrowth, it is high time we evaluate the applicability of this model system in studiesaimed at understanding abiotic stress tolerance and adaptation, with a particularemphasis on maintaining yield under hot and dry environmental conditions. Becauseof the innate nature of sorghum’s tolerance to drought and moderate tolerance tosalinity stresses, we believe sorghum is the next logical model system in such studiesamongst cereals. In this acute view, we highlight the importance of Arabidopsis as amodel system, briefly discuss its potential limitations in drought and salt stress stud-ies, and present our views on the potential usefulness of sorghum as a model systemfor cereals in drought and salinity stress proteomic studies.

INTRODUCTION

Drought and high soil salinity negatively affect crop productiv-ity worldwide. The Intergovernmental Panel on ClimateChange projects that, by 2020, Africa will experience a 50%reduction in crop yield due to adverse effects of climate change(Boko et al. 2007). By 2050, high soil salinity is expected toaffect 50% of arable land worldwide (Wang et al. 2003), thusindirectly affecting the growth and productivity of crops. Areduction in crop yield in turn threatens food security for theever-growing world population. Currently estimated at about 7billion, by 2050 the world’s population is projected to hit the9.6 billion mark (United Nations, Department of Economic &Social Affairs, Population Division 2013). Under the envisagedconditions of high temperatures, low and erratic rainfall pat-terns and high soil salinity in arable lands, how possible is it tomaintain adequate food provision? A potential solution is todevelop food crops that produce maximum yields under theseunfavourable conditions. However, the success of crop breed-ing and/or genetic engineering initiatives aimed at increasingcrop yield requires prior in-depth knowledge on how cropsrespond, tolerate and adapt to these abiotic stresses. Thereafter,the knowledge gained would be translated to susceptible buteconomically important crops. The proposal of adopting sor-ghum as a potential model system amongst cereals was intro-duced in an earlier review (Ngara & Ndimba 2014). In thecurrent acute view, we build upon that proposal, highlightingthe importance of Arabidopsis as a model plant system, itspotential limitations in drought and salt stress studies, and thepotential application of sorghum as a model system for cereals.

THE ARABIDOPSIS MODEL SYSTEM IN PLANT SCIENCES

Genomics and proteomics initiatives continue to enlighten uson the molecular basis of drought and salinity stress responsemechanisms in plants. Most of this knowledge, however, hasbeen gained from work using the model plant Arabidopsis thali-ana (Zhu 2000; Denby & Gehring 2005; Vinocur & Altman2005). Detailed historical accounts on the development of Ara-bidopsis as a model plant are available elsewhere for in-depthreading (Somerville & Koornneef 2002; Koornneef & Meinke2010; Muller & Grossniklaus 2010). Indeed, the adoption ofArabidopsis as a model system was initially due to its short lifecycle, small plant size, the production of large amounts of seed(Koornneef & Meinke 2010) and its high transformation effi-ciency using Agrobacterium tumefaciens (Clough & Bent 1998;Bent 2000; Hays 2002). In addition to its small-sized genome,Arabidopsis was the first plant genome to be fully sequenced(The Arabidopsis Genome Initiative 2000), thus paving theway for genomics and proteomics studies on different aspectsof plant biology.Published work on Arabidopsis proteomics is innumerable,

ranging from proteome profiling of tissues/organs/organelles/subcellular compartments (Baginsky & Gruissem 2004; Koma-tsu 2008; Wienkoop et al. 2010; Albenne et al. 2013; Carroll2013; Ito et al. 2014) to their responses under a range of stressconditions (Taylor et al. 2009). Readers should note thatbecause of the tremendous amount of Arabidopsis proteomicsdata available, we have decided to only cite review articles cov-ering a broad spectrum of such studies. This alone tells the suc-cessful story of a model system that has, for over a decade,

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands 1

Plant Biology ISSN 1435-8603

been used in decoding different aspects of plant growth anddevelopment. Whether or not any other plant system(s) willmeasure up to or surpass this high standard of worldwideacceptance is only to be seen in the distant future. The extentto which knowledge gained in Arabidopsis could possibly begeneralised across other plants, including crop plants, has beendiscussed in earlier reviews (Bevan & Walsh 2004; Zhang et al.2004).Nevertheless, even if Arabidopsis is generally regarded as an

excellent model system in plant biology, its use in salinity and/or drought stress studies has limitations. First, Arabidopsis is atypical glycophyte that is not adapted to either salt or droughtstress (Zhu 2000; Vinocur & Altman 2005). Second, this plantis a dicot and agriculturally unimportant (van Wijk 2001). It isalso known that monocots and dicots are fundamentally differ-ent in their structure, development (Tester & Bacic 2005) andmechanisms of osmotic adjustment (Flowers & Yeo 1986). Forinstance, dicot halophytes tolerate high concentrations ofsodium and chloride while monocot halophytes prefer to takeup potassium rather than sodium from the environment(Flowers & Yeo 1986).A comparative leaf proteomics study of Arabidopsis and its

halophytic relative Thellungiella halophila under salinity stresshas been reported (Pang et al. 2010). The results showed a lar-ger number of salt-responsive proteins, higher abundancechanges, higher levels of chlorosis, low water content in tissuesand higher electrolyte leakage in Aradidopsis than in Thellungi-ella (Pang et al. 2010), further indicating differences in thephysiological impacts of salt stress between glycophytes andhalophytes. A review on comparative proteome responsesunder salt stress between glycophytes and halophytes has alsobeing summarised (Kosova et al. 2013). The authors concludedthat halophytes possibly display enhanced constitutive expres-sion of salt-responsive genes and fewer salinity disturbances inenergy metabolism; thus making them more equipped to thriveunder saline conditions. Therefore, looking at the differencesin stress response mechanisms between glycophytes versushalophytes (Pang et al. 2010), and monocots versus dicots(Flowers & Yeo 1986), the transfer of physiological knowledgegained using model plants such as Arabidopsis to agriculturallyimportant cereals, for instance, might not be possible orstraightforward (Denby & Gehring 2005; Tester & Bacic 2005).

MOVING FROM THE TRADITIONAL MODEL PLANT TOCROP PLANTS

Rice (Oryza sativa), the first cereal crop to have its genomesequenced (International Rice Genome Sequencing Project2005), is currently regarded as a model plant amongst cereals.Rice proteomics studies under drought and salinity stress havebeen reviewed (Singh & Jwa 2013; Kim et al. 2014) andcontinue to provide insights on response mechanisms ingrasses. As with Arabidopsis, however, rice is a glycophyte andthe most salt-sensitive cereal (Munns & Tester 2008). Further-more, this crop naturally grows in flooded fields. As such,drought and/or salt stress experiments on rice might not giveconclusive insights on tolerance and adaptation to these stres-ses. In our view, a potential model system in drought and/orsalt stress proteomics studies amongst the grasses would be sor-ghum [Sorghum bicolor (L.) Moench]. Sorghum is naturallydrought- (Rosenow et al. 1983; Doggett 1988) and moderately

salt- (Krishnamurthy et al. 2007) tolerant. It is mainly used as afood source for humans in Africa and Asia, as well as stock feedand a potential source of bio-ethanol in the United States (Sa-saki & Antonio 2009). The sorghum genome has beensequenced (Paterson et al. 2009) and is publicly available as areference tool in both genomics and proteomics studies. Inaddition, genome sequence information is useful for the identi-fication of variations in gene sequence that can be used in vari-ous plant breeding strategies (Sasaki & Antonio 2009).

Sorghum’s mechanisms of drought tolerance are partly dueto biochemical and structural features such as C4 photosynthe-sis, a deep root system and a thick waxy cuticle that improveefficiency in water use (Buchanan et al. 2005). The C4 photo-synthetic pathway helps plants to maintain high photosyntheticactivity under conditions of high temperature, light intensity,water stress and CO2 deficiency (Sage 1999; Buchanan et al.2005; Sasaki & Antonio 2009; Wang & Paterson 2013). Underthese limiting conditions, sorghum fixes CO2 more efficiently(Buchanan et al. 2005; Sasaki & Antonio 2009) when comparedto C3 plants such as rice. Physiological drought tolerance insorghum may either be ‘pre-flowering’ or ‘post-flowering’(Rosenow et al. 1983). Pre-flowering drought tolerance occursduring the early vegetative stages of seedling growth and pani-cle development, while post-flowering drought tolerance isexpressed during grain development. Post-flowering droughttolerance is also associated with the stay-green trait, whereleaves retain chlorophyll and thus maintain photosyntheticactivity under stress conditions (Sanchez et al. 2002; Harriset al. 2007). A review from Tari et al. (2012) also collatessome physiological data on responses of sorghum to nutrientdeficiency, drought, salinity, waterlogging, temperature andaluminium stresses, and can be accessed for further reading.

Mace et al. (2013) presented the genome sequences of 44sorghum accessions at mid- to high coverage levels. Theirresults indicated that sorghum possesses diversity in its genepool, which is an invaluable resource in breeding programmesto meet future food demands. The progress on improvingsalinity tolerance in cereals such as wheat, rice, barley, maize,millet and sorghum is also reviewed elsewhere (Shahbaz & Ash-raf 2013). As summarised in that review, progress in terms ofconventional breeding, marker-assisted selection and geneticengineering for salt tolerance had been made in other cereals,such as rice for instance. However, comparable studies in sor-ghum are limited, with just two possible molecular markers forscreening salinity response in sorghum being reported by Raoet al. (2007). The identification of quantitative trait loci (QTL)for drought tolerance in sorghum has been reported (Sakhiet al. 2013) and also reviewed by Sanchez et al. (2002), withnone reported for salinity tolerance in the same crop. Bucha-nan et al. (2005) also studied the transcriptome changes inresponse to dehydration and high salinity in sorghum.

It is now 5 years since publication of the sorghum genomesequence (Paterson et al. 2009), but sorghum proteomicsunder drought and salt stresses is still in its infancy. At present,only two research papers on sorghum leaf proteomics undersalt stress (Kumar Swami et al. 2011; Ngara et al. 2012) havebeen published. At this rate, sorghum proteomics might nevermeasure up to the successful tale of Arabidopsis. However, dig-ging deeper into the sorghum proteome at both organellar andsubcellular compartmental levels would possibly elucidateother yet to be elucidated mechanisms that allow this crop to

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands2

Model plant systems in salinity and drought stress proteomics studies Ngara & Ndimba

be a fail-safe in hot and dry environments. Furthermore, ifmany of the most productive crops in agriculture are C4 plants(Wang & Paterson 2013), the C4 photosynthetic pathway(Lopes et al. 2011) in sorghum might be a worthwhile aspect toexplore further, with an ultimate goal of breeding for improvedyield in other crops. A generalised overview of some of theresearch questions to be answered in sorghum proteomicsstudies are summarised in Fig. 1. Without doubt, this illustra-tion is not exhaustive, but it gives some of the most commonpoints of scientific enquiry and application. Furthermore, withthe wide range of available proteomic tools, the array of possi-ble experimental designs and the wide diversity in sorghumgermplasm collections currently available worldwide, an enor-mous amount of data could be generated. Using sorghum as amodel system in such studies could possibly help us to under-stand how this crop adapts well to hot and dry environments,where other crops would normally succumb. In addition, col-laborative research activities between plant breeders andmolecular biologists (involved in plant genomics, transcripto-mics and proteomics), aimed at assessing and selecting traitsthat are not only adapted to stresses but also contributetowards increased yield under these unfavourable conditions,should be encouraged and financially supported. In theirreview article, Araus et al. (2002) discuss factors that influence

the choice of a trait in the context of drought stress in cereals.These authors state that trait(s) of interest should be directlyrelated to increased yield. Readers are referred to the article foran in-depth review on breeding cereals for increased yieldunder drought conditions.

CONCLUDING REMARKS

Arabidopsis is, and will for decades to come, remain the epit-ome of a model system in general plant biology. However, sor-ghum, a C4 cereal that is naturally well adapted to hot and dryconditions, is a useful model proposition for drought and/orsalinity stress proteomics studies. A combination of sorghum’sgenome sequence and a germplasm collection exhibiting widegenetic and phenotypic diversity in agriculturally importanttraits are all useful resources to exploit when breeding forimproved crop yield under the changing climate conditions.Only time will tell whether or not sorghum proteomics willreceive its deserved scientific enquiry and research funding rel-ative to that of Arabidopsis. For now, given our views as statedabove, it is an opportune time to explore and exploitsorghum’s research potential, with the overall objective ofbreeding crops for increased productivity under hotter anddrier environmental conditions.

REFERENCES

Albenne C., Canut H., Jamet E. (2013) Plant cell wall

proteomics: the leadership of Arabidopsis thaliana.

Frontiers in Plant Science, 4, 111.

Araus J.L., Slafer G.A., Reynolds M.P., Royo C. (2002)

Plant breeding and drought in C3 cereals: what

should we breed for? Annals of Botany, 89,

925–940.

Baginsky S., Gruissem W. (2004) Chloroplast proteo-

mics: potentials and challenges. Journal of Experi-

mental Botany, 55, 1213–1220.

Bent A.F. (2000) Arabidopsis in planta transformation.

Uses, mechanisms, and prospects for transformation

of other species. Plant Physiology, 124, 1540–1547.

Bevan M., Walsh S. (2004) Positioning Arabidopsis in

plant biology. A key step toward unification of plant

research. Plant Physiology, 135, 602–606.

Boko M., Niang I., Nyong A., Vogel C., Githeko A.,

Medany M., Osman-Elsha B., Tabo R., Yanda P.

(2007) Africa. In: Parry M.L., Canziani O.F., Pal-

utikof O.F., van der Linden P.J., Hanson C.E. (Eds),

Climate Change 2007: Impacts, Adaptation and Vul-

nerability. Contributions of working Group II to the

Fourth Assessment Report of the Intergovernmental

Panel on Climate Change. Cambridge University

Press, Cambridge, UK, pp 433–467.

Fig. 1. A generalised overview of some of the research questions to be answered in sorghum proteomics studies.

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands 3

Ngara & Ndimba Model plant systems in salinity and drought stress proteomics studies

Buchanan C.D., Lim S., Salzman R.A., Kagiampakis I.,

Morishige D.T., Weers B.D., Klein R.R., Pratt L.H.,

Cordonnier-Pratt M.M., Klein P.E., Mullet J.E.

(2005) Sorghum bicolor’s transcriptome response to

dehydration, high salinity and ABA. Plant Molecular

Biology, 58, 699–720.

Carroll A.J. (2013) The Arabidopsis cytosolic ribosomal

proteome: from form to function. Frontiers in Plant

Science, 4, 32.

Clough S.J., Bent A.F. (1998) Floral dip: a simplified

method for Agrobacterium-mediated transforma-

tion of Arabidopsis thaliana. The Plant Journal, 16,

735–743.

Denby K., Gehring C. (2005) Engineering drought and

salinity tolerance in plants: lessons from genome-

wide expression profiling in Arabidopsis. Trends in

Biotechnology, 23, 547–552.

Doggett H. (1988) Sorghum. Longman Scientific &

Technical, New York, USA, 512 pp.

Flowers T.J., Yeo A.R. (1986) Ion relations of plants

under drought and salinity. Australian Journal Plant

Physiology, 13, 75–91.

Harris K., Subudhi P.K., Borrell A., Jordan D., Rose-

now D., Nguyen H., Klein P., Klein R., Mullet J.

(2007) Sorghum stay-green QTL individually reduce

post-flowering drought-induced leaf senescence.

Journal of Experimental Botany, 58, 327–338.

Hays J.B. (2002) Arabidopsis thaliana, a versatile model

system for study of eukaryotic genome-maintenance

functions. DNA Repair, 1, 579–600.

Initiative T.A.G. (2000) Analysis of the genome

sequence of the flowering plant Arabidopsis thaliana.

Nature, 408, 796–815.

International Rice Genome Sequencing Project (2005)

The map-based sequence of the rice genome. Nature,

436, 793–800.

Ito J., Parsons H.T., Heazlewood J.L. (2014) The Ara-

bidopsis cytosolic proteome: the metabolic heart of

the cell. Frontiers in Plant Science, 5, 21.

Kim S.T., Kim S.G., Agrawal G.K., Kikuchi S., Rakwal

R. (2014) Rice proteomics: a model system for crop

improvement and food security. Proteomics, 14,

593–610.

Komatsu S. (2008) Plasma membrane proteome in

Arabidopsis and rice. Proteomics, 8, 4137–4145.

Koornneef M., Meinke D. (2010) The development of

Arabidopsis as a model plant. The Plant Journal, 61,

909–921.

Kosova K., Vitamvas P., Urban M.O., Prasil I.T. (2013)

Plant proteome responses to salinity stress – com-

parison of glycophytes and halophytes. Functional

Plant Biology, 40, 775–786.

Krishnamurthy L., Serraj R., Hash C.T., Dakheel A.J.,

Reddy B.V.S. (2007) Screening sorghum genotypes

for salinity-tolerant biomass production. Euphytica,

156, 15–24.

Kumar Swami A., Alam S.I., Sengupta N., Sarin R.

(2011) Differential proteomic analysis of salt stress

response in Sorghum bicolor leaves. Environmental

and Experimental Botany, 71, 321–328.

Lopes M.S., Araus J.L., van Heerden P.D., Foyer C.H.

(2011) Enhancing drought tolerance in C4 crops.

Journal of Experimental Botany, 62, 3135–3153.

Mace E.S., Tai S., Gilding E.K., Li Y., Prentis P.J., Bian

L., Campbell B.C., Hu W., Innes D.J., Han X., Cru-

ickshank A., Dai C., Frere C., Zhang H., Hunt C.H.,

Wang X., Shatte T., Wang M., Su Z., Li J., Lin X.,

Godwin I.D., Jordan D.R., Wang J. (2013) Whole-

genome sequencing reveals untapped genetic poten-

tial in Africa’s indigenous cereal crop sorghum.

Nature Communications, 4, 2320.

Muller B., Grossniklaus U. (2010) Model organisms –

A historical perspective. Journal of Proteomics, 73,

2054–2063.

Munns R., Tester M. (2008) Mechanisms of salinity

tolerance. Annual Review of Plant Biology, 59, 651–

681.

Ngara R., Ndimba B.K. (2014) Understanding the

complex nature of salinity and drought-stress

response in cereals using proteomics technologies.

Proteomics, 14, 611–621.

Ngara R., Ndimba R., Borch-Jensen J., Jensen O.N.,

Ndimba B. (2012) Identification and profiling of

salinity stress-responsive proteins in Sorghum bicolor

seedlings. Journal of Proteomics, 75, 4139–4150.

Pang Q., Chen S., Dai S., Chen Y., Wang Y., Yan X.

(2010) Comparative proteomics of salt tolerance in

Arabidopsis thaliana and Thellungiella halophila.

Journal of Proteome Research, 9, 2584–2599.

Paterson A.H., Bowers J.E., Bruggmann R., Dubchak I.,

Grimwood J., Gundlach H., Haberer G., Hellsten U.,

Mitros T., Poliakov A., Schmutz J., Spannagl M.,

Tang H., Wang X., Wicker T., Bharti A.K., Chapman

J., Feltus F.A., Gowik U., Grigoriev I.V., Lyons E.,

Maher C.A., Martis M., Narechania A., Otillar R.P.,

Penning B.W., Salamov A.A., Wang Y., Zhang L.,

Carpita N.C., Freeling M., Gingle A.R., Hash C.T.,

Keller B., Klein P., Kresovich S., McCann M.C.,

Ming R., Peterson D.G., Mehboob ur R., Ware D.,

Westhoff P., Mayer K.F., Messing J., Rokhsar D.S.

(2009) The Sorghum bicolor genome and the diversi-

fication of grasses. Nature, 457, 551–556.

Rao M.V.S., Kumari P.K., Manga V., Mani N.S. (2007)

Molecular markers for screening salinity response in

Sorghum. Indian Journal of Biotechnology, 6, 271–

273.

Rosenow D.T., Quisenberry J.E., Wendt C.W., Clark

L.E. (1983) Drought-tolerant sorghum and cotton

germplasm. Agricultural Water Management, 7, 207–

222.

Sage R.F. (1999) Why C4 photosynthesis? In: Sage R.F.,

Monson R.K. (Eds), C4 Plant Biology. Academic

Press, London, UK, pp 3–16.

Sakhi S., Shedzad T., Rehman S., Okuno K. (2013)

Mapping the QTLs underlying drought stress at

developmental stage of sorghum (Sorghum bicolor L.

Moench) by association analysis. Euphytica, 193,

433–450.

Sanchez A.C., Subudhi P.K., Rosenow D.T., Nguyen

H.T. (2002) Mapping QTLs associated with drought

resistance in sorghum (Sorghum bicolor L. Moench).

Plant Molecular Biology, 48, 713–726.

Sasaki T., Antonio B.A. (2009) Plant genomics: sor-

ghum in sequence. Nature, 457, 547–548.

Shahbaz M., Ashraf M. (2013) Improving salinity toler-

ance in cereals. Critical Reviews in Plant Sciences, 32,

237–249.

Singh R., Jwa N.S. (2013) Understanding the responses

of rice to environmental stress using proteomics.

Journal of Proteome Research, 12, 4652–4669.

Somerville C., Koornneef M. (2002) A fortunate

choice: the history of Arabidopsis as a model plant.

Nature Reviews Genetics, 3, 883–889.

Tari I., Laskay Z., Takacs Z., Poor P. (2012) Response

of sorghum to abiotic stresses: a review. Journal of

Agronomy and Crop Science, 199, 264–274.

Taylor N.L., Tan Y.F., Jacoby R.P., Millar A.H. (2009)

Abiotic environmental stress-induced changes in the

Arabidopsis thaliana chloroplast, mitochondria and

peroxisome proteomes. Journal of Proteomics, 72,

367–378.

Tester M., Bacic A. (2005) Abiotic stress tolerance in

grasses. From model plants to crop plants. Plant

Physiology, 137, 791–793.

United Nations, Department of Economic and Social

Affairs, Population Division. (2013) World Popula-

tion Prospects: The 2012 Revision, Key Findings and

Advance Tables. Working Paper No. ESA/P/WP.227.

Vinocur B., Altman A. (2005) Recent advances in engi-

neering plant tolerance to abiotic stress: achieve-

ments and limitations. Current Opinion in

Biotechnology, 16, 123–132.

Wang X., Paterson A.H. (2013) Comparative genomic

analysis of C4 photosynthesis pathway evolution in

grasses. In: Paterson A.H. (Ed.), Genomics of the Sac-

charinae, Plant Genetics and Genomics: Crops and

Models. Springer, New York, USA, pp 447–477.

Wang W., Vinocur B., Altman A. (2003) Plant

responses to drought, salinity and extreme tempera-

tures: towards genetic engineering for stress toler-

ance. Planta, 218, 1–14.

Wienkoop S., Baginsky S., Weckwerth W. (2010)

Arabidopsis thaliana as a model organism for

plant proteome research. Journal of Proteomics, 73,

2239–2248.

van Wijk K.J. (2001) Challenges and prospects of plant

proteomics. Plant Physiology, 126, 501–508.

Zhang J.Z., Creelman R.A., Zhu J.K. (2004) From labo-

ratory to field. Using information from Arabidopsis

to engineer salt, cold, and drought tolerance in

crops. Plant Physiology, 135, 615–621.

Zhu J.K. (2000) Genetic analysis of plant salt tolerance

using Arabidopsis. Plant Physiology, 124, 941–948.

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands4

Model plant systems in salinity and drought stress proteomics studies Ngara & Ndimba