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BioSystems 103 (2011) 205–211

Contents lists available at ScienceDirect

BioSystems

journa l homepage: www.e lsev ier .com/ locate /b iosystems

verview: Early history of crop growth and photosynthesis modeling

abrouk A. El-Sharkawy ∗

entro Internacional de Agricultura Tropical (CIAT), Cali, Colombia

r t i c l e i n f o

rticle history:eceived 8 July 2010eceived in revised form 17 August 2010ccepted 18 August 2010

eywords:gricultural researchomputer simulation

a b s t r a c t

As in industrial and engineering systems, there is a need to quantitatively study and analyze the manyconstituents of complex natural biological systems as well as agro-ecosystems via research-based mech-anistic modeling. This objective is normally addressed by developing mathematically built descriptionsof multilevel biological processes to provide biologists a means to integrate quantitatively experimentalresearch findings that might lead to a better understanding of the whole systems and their interactionswith surrounding environments. Aided with the power of computational capacities associated with com-puter technology then available, pioneering cropping systems simulations took place in the second half

3, C4 speciesield cropsnvironmental factorseaf canopyight interceptionhotosynthesis modeling

of the 20th century by several research groups across continents. This overview summarizes that initialpioneering effort made to simulate plant growth and photosynthesis of crop canopies, focusing on thediscovery of gaps that exist in the current scientific knowledge. Examples are given for those gaps whereexperimental research was needed to improve the validity and application of the constructed models,so that their benefit to mankind was enhanced. Such research necessitates close collaboration amongexperimentalists and model builders while adopting a multidisciplinary/inter-institutional approach.

roductivity predictionoil water stress

. Introduction

It has been pointed out frequently that the potential of cropystem modeling is to integrate information from different cropubsystems from many disciplines to better understand how theystem responds to environmental and crop management prac-ices, to identify critical-limiting factors and information gaps ando get the necessary research done needed to improve a model inrogress (Penning de Vries et al., 1989). As photosynthesis is theasic process that determines the primary productivity in terres-rial ecosystems, it received early attention by experimentalists asell as modelers via research ranging from the biochemical levels

o the canopy level (e.g., Yuncker, 1916; Dastur, 1925; Heinicke,933; Singh and Lal, 1935; Heinicke and Childers, 1936; Schneidernd Childers, 1941; Decker, 1947; Saad, 1954a,b; Sesták et al.,971; Grodzinskii, 1972; Monsi et al., 1973; Boote and Loomis,991; Pessarakli, 2005). These photosynthetic research and mod-ling efforts were essential inputs needed to build more compleximulators that described the dynamics of plant growth and envi-

onmental interactions at the larger scales of plant communitynd cropping systems. Furthermore, simulation approaches mayelp in detecting apparent shifts in land use patterns from natu-al bio-systems to agro-ecosystems and vice versa (Ewers et al.,

∗ Corresponding author at: A. A. (P.O. Box) 26360, Cali, Colombia.E-mail addresses: mabrouk99@hotmail.com, elsharkawy@emcali.net.co.

303-2647/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved.oi:10.1016/j.biosystems.2010.08.004

© 2010 Elsevier Ireland Ltd. All rights reserved.

2009), and in improving water productivity in agricultural sys-tems (Kijne et al., 2003). In this overview, a few papers that hadlaid the groundwork in all this will be cited. Since the theoreti-cal and mathematical structure of computer simulation modelingare well covered in numerous books and publications, often overlyproduced, the present paper focuses on the importance of generat-ing the essential experimental research needed to close many gapsin knowledge so that problems can be solved benefiting mankind.Devoting enough time and resources to conduct essential researchthat feeds back to successful modeling must be top priorities in thiscase.

2. Background and early work

The importance of a single environmental factor affecting bio-logical systems was first popularized by the chemist Justus vonLiebig in 1840, after the principle developed in agricultural sci-ence by Carl Sprengel (1839), both 19th century German scientists.Liebig formulated the ‘law of the minimum’, which states thatin ecological processes the growth of a plant will be limited bywhichever requisite factor is the most deficient in the local envi-ronment, although later research downgraded its significance. In

early 20th century, Blackman (1905) proposed a similar law, thatis the ‘law of single factor limitation’ as applied to the process ofphotosynthesis, i.e., plant photosynthetic process is controlled bythe most limiting factor, mainly irradiance level and CO2 supply.However, later photosynthetic research and theoretical model-

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ng indicated the oversimplification of Blackman law (Singh andal, 1935; Gaastra, 1959; El-Sharkawy and Hesketh, 1965; El-harkawy et al., 1967; Farquhar et al., 1980; Sharkey, 1985; Bootend Loomis, 1991; Stitt and Schulze, 1994; Farazdaghi, 2009). Nev-rtheless, that principle along with ‘the compound interest law’Blackman, 1919), stimulated research that described the dynam-cs of multi-factor controlled biological processes such as plantrowth and plant photosynthesis and has led to the developmentf the classic growth analysis method initiated by the British schoolWatson, 1952). This method has become a standard tool andsed worldwide for determining plant growth patterns, net assim-

lation rates, and total canopy photosynthetic carbon productions determinants of whole crop productivity (Nichiporovich et al.,961; El-Sharkawy, 1975). The classical model of plant canopy

ight interception and transmission based on the application ofBeer–Lambert’ optic law and as affected by leaf area index wasrst worked out by Monsi and Saeki in Japan (1953) [see also theeview by Monsi et al. (1973)], followed by the development ofhe aerodynamic principles for estimating canopy photosynthe-is by Inoue et al. (1958), also in Japan. Gaastra (1959), in theetherlands, adopted the concepts of ‘Ohms’ electricity law ineveloping an analogy model for gas diffusion resistances (H2Ond CO2) around and inside plant leaves, which was an innovativeethod for quantifying differences in leaf gas exchange character-

stics among species (El-Sharkawy and Hesketh, 1965). Computerodeling of leaf canopy architecture, patterns of light distribution

rofiles within canopy, flux of CO2, and leaf/canopy photosynthe-is was worked out by de Wit in the Netherlands (1965), Monteitht al. (1964) and Monteith (1965) in UK, Duncan et al. at Davis,A (1967), and Ross (1981). These models laid the foundations

or further mechanistic and more sophisticated crop growth andhotosynthesis simulation efforts under field conditions (Baker etl., 1971; Loomis et al., 1979; Hesketh and Jones, 1980; Bunce,986) and under glasshouse environments (Acock, 1991). More-ver, these pioneering plant community modeling efforts wereurther complemented by relevant respiration–photosynthesis-elated physiological processes and plant nutrient status (Baker etl., 1971; McCree, 1974; Penning de Vries, 1975; McDermitt andoomis, 1981; Amthor, 2000) and by detailed enzymatic kinet-cs/biochemical modeling for C3 plants that were worked out byeveral researchers across continents (Farquhar et al., 1980; vonaemmerer and Farquhar, 1981; Woodrow and Berry, 1988; Bootend Loomis, 1991; Farazdaghi, 2009). Since the mechanistic modelsre not perfect for predicting the reality of these highly interactivend complex biological processes, whether at the biochemical ort the different tissues and the whole plant levels, complementaryenetic manipulation/transgenic approaches and molecular biol-gy tools may enhance the identification of the many rate-limitingactors as well as the fine sites involved in controlling photosyn-hesis/respiration and plant growth (Somerville and Ogren, 1979;titt and Schulze, 1994; Peterhansel et al., 2010).

Huge resources are going into relevant subsystems of basichotosynthetic research, but large critical information gaps haveeen found recently. Some need immediate research such as thoseelated to leaf ontogenesis, leaf anatomy and development, cellivision and expansion, and regulatory control mechanisms under-

ying growth of cell wall in expanding leaves and their implicationsor photosynthetic rate (Sesták, 1985; Dale, 1988; Ishida et al.,005; Begonia and Begonia, 2007; El-Sharkawy, 2009; Sage andage, 2009). Rooting systems profiling, and quantification of root-ng patterns and rooting length density in the field among cultivars

nd species is another area that need detailed research in relation tolant–soil–atmosphere modeling (Taylor and Klepper, 1978; Böhm,979; Passioura, 1988; Klepper and Rickman, 1991; Gregory, 2006;rachsel et al., in press). Moreover, some adaptive plant root traitshat may develop in response to abiotic stresses appear to have

s 103 (2011) 205–211

important implications for plant-water relations, growth and nutri-ent acquisition. For example, Postma and Lynch (2010) reportedthat root cortical aerenchyma developed under soil phosphorusdeficiency may reduce root respiration, allowing carbon to be usedfor greater soil exploration, as well as inducing internal remobi-lization of phosphorus. Effects of such anatomical traits need tobe taken into consideration while modeling plant-soil-atmosphereinteractions. Papers in Photosynthetica by El-Sharkawy (2005) andby Begonia and Begonia (2007) describe some of this with namesof researchers now and in the past making progress being dis-cussed and cited. In a recent review, Prasad et al. (2008) indicatedthe many information gaps needed to be addressed in the area ofwater and heat stresses in order to improve crop modeling. How-ever, modelers involved, as well as concerned research managers,need to be aware of what is needed to produce progress takingadvantage of current interests in research addressing global climatechange and the effects of elevated atmospheric carbon dioxide onagro-ecosystems, natural bio-systems and secured-food produc-tion (Long et al., 2006; Stige et al., 2006; IPCC, 2007; Adler et al.,2009; UN SCN-News, 2010).

3. Pioneering modeling efforts and its implications forimproving agricultural productivity

An effort was initiated at Mississippi State University (MSU) andUSDA/ARS to build a crop growth model for cotton in the 1960swhich had far reaching implications (Hesketh and Baker, 1967;Baker et al., 1971, 1983; Whisler et al., 1986). The effort had led tothe construction of GOSSYM, a dynamic cotton (Gossypium hirsutumL.) simulation model as a tool to enhance efficiency of crop manage-ment. It simulates most of the physiological and edapho-climaticphysical processes affecting cotton growth, development and yield.It was an effort to integrate information from many crop and soildisciplines to create a tool for farmers to predict how their cropwill yield if they make certain management decisions prior to andthroughout the growing season. The model is used mainly for irriga-tion and nitrogen fertilization management and for plant growthregulators application, based on daily weather data, soil physicaland chemical characteristics of each site and some cultural charac-teristics. After 20 years of it at MSU, it became clear that how datawere taken to be used in the model, as well as critical gaps in knowl-edge associated with different disciplines, determined the rate ofprogress of the effort. The crop computer model was an essentialpart of this process but not an end unto itself. Disciplines integratedinto the model included Plant Pathology and Entomology.

Crop models often had to be ‘calibrated’ to predict crop behaviorunder ‘local’ conditions. It should be pointed out that such a calibra-tion was needed to test, among other things, water stress effects onthe crop. Pests contribute to such effects, either on the effectivenessof roots or the shoot xylem to transport water through the plant.Pests also reduce the crop’s leaf area, which is needed for photo-synthate supply to the crop and late in the season N-redistributionto the organ in the plant associated with yield.

Most scientific discoveries are made by committed research sci-entists, particularly those in computer science. Scientific managersneed to hire more experimentalists who via applying scientificmethods can generate the logics needed for simulators. Unfortu-nately, the computer modeling part of the effort attracted someextreme theoretically oriented staff, greatly slowing the progressmade and generally wasting money.

The first discovery made was done with Robert Musgrave at Cor-nell University, in Ithaca, NY, who took his students to the fieldto do photosynthetic research (Moss et al., 1961; Musgrave andMoss, 1961; Hesketh and Musgrave, 1962; Baker and Musgrave,1964; Moss and Musgrave, 1971). Early results, including mine

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El-Sharkawy, 2009), disqualified efforts underway to model leafhotosynthesis based upon potted plants grown under low lightr shady conditions in the greenhouse or growth cabinet. Photo-ynthesis of leaves of such potted plants was light saturated at 1/4ull sunlight, while the leaf photosynthesis of field-grown plantsesponded up to full sunlight. It was found possible to grow well-atered potted plants in the field, particularly in Arizona, the leaves

f which behaved similarly to those of field-grown plants in soil.lants grown in a special facility in a Tempe AZ lab, using nutrientulture and intense artificial lights, actually had higher leaf pho-osynthetic rates than field-grown plants, at ambient and doublehe atmospheric CO2 levels. No effort was made to enhance theumidity around the plants. Both kinds of leaves (in ambient and 2×mbient atmospheric CO2) accumulated especially large amountsf starch and sugar. Tests made in the field by Begonia et al. (1996,999), using open-top chambers with ambient and double atmo-pheric CO2 levels, did not do as well as the Tempe plants. Theseuthors were able to duplicate results from their field work usingotted plants grown outside, once again using open-top chambers,t Jackson State University in MS. For quite a while their work wast the cutting edge, compared to what was being done in the hugeederally funded climate change effort.

In The Netherlands, a leaf gas exchange model was devel-ped along with associated research which quantified howtomata behaved in plants that had adequate and less-than-dequate water, as well as responses to CO2, irradiance andeaf temperature (Gaastra, 1959). That pioneering research-based

odeling of leaf gas exchange enhanced further research inlant–water–atmosphere relations that led to major discoveriesmong higher plant species that differed in their carbon fixa-ion pathways. For example, El-Sharkawy and Hesketh (1965) andl-Sharkawy et al. (1967) used and extended Gaastra’s leaf gasxchange model in their pioneering photosynthetic research andn identifying the various physiological, stomatal, and mesophyllraits separating C3 and C4 plants. One paper (El-Sharkawy andesketh, 1965), was later cited as a Citation Classic by the Insti-

ute for Scientific Information (ISI), PA, USA, in 1986 (El-Sharkawynd Hesketh, 1986) and was among the 20 most cited publicationsn Crop Science until 1990. It was the first report to link leaf Kranznatomy characteristics, found in monocot tropical grasses and inhe dicot, Amaranthus spp., with their high photosynthetic rates,hich was also associated with zero CO2 release outside of leaves

n intense light and CO2-free air. These species with inherent lowertomatal conductance and higher leaf water use efficiency (i.e., leafet photosynthesis per water loss) are now called C4 plants, afterhe discovery of their unique C4 dicarboxylic acid pathway. The firstiochemical evidence on the C4 system was apparently noted inid 1950s by the Hawaiian researchers in sugarcane (Kortschak et

l., 1965), and by the Russian researchers in maize (Karpilov, 1960).ater, elucidation of the carboxylation reaction and sugar formationas done by the Australian researchers in sugarcane (Hatch and

lack, 1966) (see also reviews by Hatch and Slack, 1970, by Laetsch,974, and by El-Sharkawy, 2009). Private companies developed andold portable infrared gas analysis equipments based on Gaastra’sodel that could be used to duplicate easily what he and others did

sing field-grown plants.At Mississippi State University, the first major crop modeling

ffort was initiated in late 1960s. Researchers (Baker et al., 1971,983) used information from their field-grown cotton research touild a photosynthesis model for a cotton crop. Since then, it haseen shown by Larson et al. (1981), at the University of Illinois,

rbana, that soybean crop canopy photosynthetic rates declinet the higher light levels; which was confirmed by the Climatehange research group (Kimball et al., 2002; Long et al., 2006).t one point both groups lacked a crop physiological water stressodel to predict the decline in photosynthesis found at high light

s 103 (2011) 205–211 207

intensities; also any feedback control effect of accumulated photo-synthate could not be accounted for. Baker and coworkers resultssuggested that there could not have been much of a feedback con-trol effect. Ritchie (1972) working in TX developed a crop waterbudget model based upon Agricultural Meteorological water bud-get modeling tradition and field data. His model was unique in thatit separated plant transpiration from soil evaporation. For soil evap-oration, one had to determine somehow how much sunlight thesoil surface intercepted. Ritchie’s model lacked a crop physiologi-cal water stress model. Moreover, in such plant–water–atmospheremodels, the direct response of stomata to air humidity that wasobserved in many crop species at both single leaf and canopy levels,without large changes in bulk leaf water potential and in both wetand dry soils (Farquhar, 1978; Bunce, 1981, 1982; El-Sharkawy andCock, 1984; El-Sharkawy et al., 1984; Cock et al., 1985, Oguntundeand Alatise, 2007; Pieruschka et al., 2010) must be accounted for(see for example, Choudhury and Monteith, 1986; but also see otheranalysis by Mott and Parkhurst, 1991; Monteith, 1995). Kiniry et al.(1998) reported significant variations in radiation-use efficiency(RUE) of cereal crops grown at various locations in hot summerat TX, USA, in response to atmospheric vapor pressure deficits(VPD). RUE of maize and grain sorghum decreased with increasingVPD. Similar effects of VPD on RUE were observed in well-wateredsorghum grown in controlled-environment glasshouses (Hamdiet al., 1987) and in eucalyptus plantations in Western Australia(Landsberg and Hingston, 1996). Across well-watered 19 herba-ceous (including grain sorghum and maize) and woody (includingeucalyptus) warm-climate species, the degree of stomatal responseto VPD was positively associated with maximum stomatal conduc-tance and with stomatal density (El-Sharkawy et al., 1985). Thisfinding may indicate the role of localized water stress caused byevaporation at the stomatal apparatus and surrounding exposedepidermal cells.

A start on a water stress model was made at Mississippi StateUniversity by the modeling group there using water-protectedplots at the experimental farm. At three irrigation levels: none, 1/2and normal, plants grew small, medium and large leaves resultingin small, medium and large yields, without all the excessive wiltingshown in potted plant research. Plants in some of the non-irrigatedplots did go into a permanent extreme wilt while others producedcotton. Presumably the wilted plants met a sandy barrier in thesoil profile. Data from potted plant research may well predict howplants growing in sandy soils behave, but the point of the Missis-sippi State University research was that potted plant data couldnot predict how the plants behaved. Perhaps potted plant culturecould be modified to predict how the field-grown plants behave, bysupplying a steady amount of adequate and limited water to largepots.

Working with the team at Mississippi State University, Jones etal. (1974) developed the software for the original cotton model,resulting in SIMCOT II, which included soil/crop nitrogen budget.With this new work, the Mississippi State University cotton modelused the carbon, water and nitrogen budget approach to predictyield.

In collaboration with the Mississippi State University group,Quinby et al. (1973), Bernard (1971), and Buzzell (1971), in Canada,tested their photoperiod × temperature genes at the Duke Univer-sity Phytotron. At the somewhat lower temperature treatment usedin those experiments, plants did not respond to photoperiod. Plantsgrowing in the field often are planted in early spring, being exposedto much lower temperatures as a result. The Canadian workers and

Bernard, taking data at their two field sites at different plantingdates – Bernard’s site being close to the Mason Dixon line or thelower border of PA – could not find a photoperiod effect. They builta flowering model based upon the data they took in the field at theirtwo locations. Boote et al. (2003) did the same at the University of

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lorida, where at some planting dates plants are exposed to warmemperatures at the time the decision to flower is made. This groupsed Bernard’s data to construct their model for flowering at lati-udes between Urbana IL and Gainesville FL. Bernard’s group couldot account for periods of unusually warm or cold weather duringoral initiation on photoperiod response. Zhang et al. (2001) didnd small photoperiod effects in their date-of-planting studies athe University of Illinois site, during the warm part of the growingeason. Pan (1997) had to calibrate the phytotron phenological datahey were using by taking data in the field using degree-days. Aslobal temperatures increase, the kind of plant behavior simulateday become more important.A dramatic discovery which revealed a big information gap in

he soil physics models was achieved at the University of Illinois,rbana (Wang et al., 1986). These authors excavated a soil profile,ttempting to quantify numbers and dimensions of animal burrowsnd soil cracks, and found the major roots of plants growing in theoles, deep into the soil profile. Obviously water flowed into theoil profile following these holes, with O2 and CO2 gases flowingn and out of the soil profile via the same routes. A soil model forhis should include a relationship between soil moisture contentnd hole dimensions, particularly those of cracks. Effects of sand,ilt and clay composition on cracking need to be accounted for.oreover, El-Sharkawy (1975) working at the great Sahara desert

f North Africa, found that in sandy soils depth of fibrous root sys-em of cereal crops was severely limited by a fine sand layer whichllowed water and nutrients leaching beyond rooting zones. Sub-oiling significantly increased rooting depth, biomass and grainield of spring wheat under irrigation. Therefore, effects of soil hardans on crop growth and productivity must be taken into accounthen modeling plant-soil-atmosphere interactions.

A major crop modeler in all the above was the Japaneseesearcher E. Inoue who in the early 1960s published papers onow to use aerodynamic methods in the field to quantify energy,ater vapor and CO2 exchange between the crop canopy and the

tmosphere. His work was based upon the aerodynamic researchone to produce the incredible ‘Zero airplane’ (a Japan-made single-ilot fighter which was an incredibly good airplane compared to theompetition during WWII. Besides its lightweight, it had three keytrengths: speed, maneuverability and range).

The point of all the above is that the crop modeling effort atississippi State University initiated a multidisciplinary effort to

uantify how plants behave growing under field conditions, whiched to methods for properly taking data to quantify such behavior.n the process major gaps in knowledge were encountered within

any disciplines, some rendering the disciplines as they existedrrelevant. Effects of soil moisture on hole dimensions in the soilrofile need to be quantified. An effort needs to be made to quan-ify effects of water stress at the plant physiological level on plantehavior. Other knowledge gaps need to be found and rectified.

ntegrating information from many disciplines for a crop modelroved difficult, but the end result justified the effort, saving tax-ayer’s money and helping farmers in solving relevant problems.

The eradication of the boll weevil done at Mississippi State Uni-ersity, with major contributions by a Chemistry graduate studentnd private enterprise, shows what can be done by governmentupport research. A genetically engineered cotton plant resistant tohe boll worm or the corn ear worm, greatly reduced the amountf insecticide needed to mature a crop. The latter was done mainlyy private enterprise for profit.

A recent book (Kirkham, 2011) is concerned with the effects

f elevated levels of carbon dioxide on soil and plant water rela-ions. The author considers plants under both well watered androught conditions. Water stress is an important factor in howlobal climate change will affect food production in the world andow ecosystems will survive or evolve. Soil factors affecting plant

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growth and development while interacting with climatic condi-tions must be elucidated in quantitative manners for inclusion incrop simulators. The early soil physicists who have done the mostin pioneering theoretical modeling in the field of soil–plant–waterrelations are Wilford R. Gardner, at the University of Wisconsin,Don Kirkham at Iowa State University, and John Philip in Australia.In 1984, Don Kirkham shared the prestigious Wolf Prize in Agri-culture with Cornelius de Wit, as he was recognized for theoreticalwork and de Wit for development of numerical models. Any stu-dent studying aspects of the above needs to be aware of the peopleinvolved in making major associated scientific discoveries and howthey did it.

Much of the above was discussed in recent papers in Photo-synthetica (El-Sharkawy, 2005; Begonia and Begonia, 2007). Theconclusion of these papers was that innovative research on subsys-tem gaps in crop systems greatly contributed to progress in cropsystem modeling.

Similar conclusion was reached where gaps in research informa-tion were identified in the area of drought and heat stresses thatmight affect the quality and validity of crop models (Prasad et al.,2008).

In a recent comprehensive review of agro-climatic research,Steiner and Hatfield (2008) elegantly summarized the history ofhow this important research had evolved since early 20th century.These authors emphasized modeling the many biophysical aspectsof soil–plant–atmosphere interactions, including edaphic and cli-matic factors controlling canopy photosynthesis. Such modelingefforts play an important role in integrating knowledge into cropgrowth and agronomic models. Moreover, remote sensing providescapacity to gain theoretical and practical understanding of ecosys-tems at regional scale. Several modeling-related scientific paperspublished during the second half of the 20th century, which con-tributed significantly to the advancement of agro-climatic research,became Citation Classics. It was recommended that “solutionsto today’s problems require interdisciplinary and multi-sectoralteams. While needs have never been greater, fewer universitiesmaintain critical mass required to offer advance degrees in agro-climatology. It will be increasingly important that agro-climatologyattract top students and provide training and practical experiencein conducting integrated systems research, communications, andteam skills” (Steiner and Hatfield, 2008). That review is a good ref-erence for biology students, agroclimatologists, agronomists, cropphysiologists, plant ecologists and biosystems modelers.

In sum a model without research but based upon a review ofthe literature – is only a hypothesis of how large complex systemsbehave without any hypothesis testing. ‘Calibrating’ such modelsagainst final yields or phenological and physiological measure-ments during the year is only coming up with ‘an experimentallyuntested factor’ to make the model work, defeating the purpose of amodel, which is to understand how different parts of a complex sys-tem interact to ultimately produce a final product. It was suggestedthat the scientists studying how plants responded to increasing CO2in the atmosphere as well as associated increasing temperaturesmight well reach their goal sooner if they improved the water stresssub-model of any crop or ecosystem model. Experiments for thispurpose under the rain-protected plots at Mississippi State Univer-sity used the Gaastra’s model and associated scientific equipmentto quantify stomatal resistance, as well as a pressure bomb etc.to quantify leaf water potential. Root behavior was not studied, afatal flaw to that piece of research with respect to modeling whatwas going on. Under water stress, besides acclimating leaf area to

what can be supported by the plant’s ability to supply water to it,the plant also must divert photosynthate to strengthen the rootsystem so it can supply more water to the shoot. As pointed outabove, then there are the pests eating leaves, clogging water con-ducting tissue, and eating roots. Hopefully a new book due out will

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eveal some progress in getting all this done. Frankly agronomistsnvolved might develop a strong understanding of how horticul-uralists handle some of these problems in growing plants in largeontainers, to ensure ample oxygen and water for the root system.mong other things they use crystals that form small clumps of ael, tying up water in the rooting zone but releasing it when needed,t the same time keeping oxygen levels adequate for root function.ffects of soil cracks and animal burrows and research needed toredict such effects – on all this was discussed above. There areodels for crack and burrow behavior, but without the research

eeded such models so far have been extremely superficial.

. Conclusions

To enhance benefit/cost ratio from simulating natural ecosys-ems and from crop systems modeling, more emphasis have toe directed towards the experimental research needed to closeany knowledge gaps instead of relying on ineffective and arbi-

rary factors applied in computational processes. This research haso be conducted under field/natural conditions as much as possi-le since using results from pot-grown plants left outdoors or inontainers often fall short of predicting reality (El-Sharkawy, 2005;ong et al., 2006; Begonia and Begonia, 2007). So far, and withnly few exceptions, most of crop growth and canopy photosyn-hetic models are used mainly as research tools by the same modeluilders and/or by the scientific community (Penning de Vries etl., 1989). However, they are useful in integrating available knowl-dge, in identifying gaps that require further research and in fewases predicting potential crop productivity as well as influencef environments. The current observed trends in global climatehange would certainly enhance the role of modeling for managedgro-ecosystems and for natural bio-systems in relation to theirotentials for greenhouse gas emissions and sequestrations (IPCC,007). The modern genomic research must add another dimen-ion to mechanistic crop simulation modeling. This genome-basedesearch should strengthen models via reducing, or even elimi-ating, dependence on arbitrary or adjustable factors, and hence,

mproving model’s potential ability to match experimental findingss well as its predictions of future research observations (Moreno-isueno et al., 2010).

cknowledgement

I am grateful to anonymous reviewers and editors of BioSystemsor the many constructive comments and additions on original ver-ion that were incorporated in the text and references. Receptionf reprints from several authors of published as well as in pressapers are appreciated. Thanks are extended to Farah El-Sharkawyavarro for typing the manuscript several times and for searching

he internet for relevant information and references.

eferences

cock, B., 1991. Modeling canopy photosynthetic response to carbon dioxide, lightinterception, temperature and leaf traits. In: Boote, K.J., Loomis, R.S. (Eds.), Mod-eling Crop Photosynthesis—from Biochemistry to Canopy. Crop Science Societyof America, American Society of Agronomy, Madison, pp. 41–55.

dler, P.B., Leiker, J., Levine, J.M., 2009. Direct and indirect effects of cli-mate change on prairie plant community. PLoS ONE 4 (9), e6887.doi:10.1371/journal.pone.0006887 (open access journal).

mthor, J.S., 2000. The McCree-de Wit-Penning de Vries-Thornley respirationparadigms: 30 years later. Ann. Bot. 86, 1–20.

aker, D.N., Musgrave, R.S., 1964. Photosynthesis under field conditions V. Furtherplant chamber studies of the effects of light on corn (Zea mays L.). Crop Sci. 2,

127–131.

aker, D.N., Hesketh, J.D., Duncan, W.G., 1971. The simulation of growth and yield incotton I. Gross photosynthesis, respiration and growth. Crop Sci. 12, 431–435.

aker, D.N., Lambert, J.R., McKinion, J.M., 1983. GOSSYM: a simulator of cotton cropgrowth and yield. Technical Bulletin No. 1089, South Carolina Experiment Sta-tion.

s 103 (2011) 205–211 209

Begonia, G.B, Begonia, M.T., 2007. Plant photosynthetic production as controlled byleaf growth, phenology and behavior. Photosynthetica 45, 321–333.

Begonia, G.B., Begonia, M.F.T., Ousby, B.R., Johnson, M., 1999. Vegetative and repro-ductive responses of cotton to stage specific CO2 enrichment and drought stress.J. Miss. Acad. Sci. 44, 190–196.

Begonia, G.B., Russ, B., Cunningham, S.G., Moore, R., 1996. Evidence of no photosyn-thetic acclimation to cotton exposed to stage-specific CO2 enrichment. J. Miss.Acad. Sci. 41, 94–98.

Bernard, R.L., 1971. Two major genes for time to flowering and maturity in soybean.Crop Sci. 11, 242–244.

Blackman, F.F., 1905. Optima and limiting factors. Ann. Bot. 19, 281–295.Blackman, V.H., 1919. The compound interest law and plant growth. Ann. Bot. 33,

353–360.Boote, K.J., Loomis, R.S. (Eds.), 1991. Modeling Crop Photosynthesis—from Bio-

chemistry to Canopy. Crop Science Society of America and American Societyof Agronomy, Madison.

Boote, K., Jones, J., Batchelor, W., Nafsiger, E., Myers, O., 2003. Genetic coefficients inthe CROPGRO-Soybean model: links to field performance and genomics. Agron.J. 95, 32–51.

Böhm, W., 1979. Methods of Studying Root Systems. Springer-Verlag, Berlin.Bunce, J.A., 1981. Comparative responses of leaf conductance to humidity in single

attached leaves. J. Exp. Bot. 32, 629–634.Bunce, J.A., 1982. Photosynthesis at ambient and elevated humidity over a growing

season in soybean. Photosynth. Res. 3, 307–311.Bunce, J.A., 1986. Measurements and modeling of photosynthesis in field crops. CRC

Crit. Rev. Plant Sci. 4, 47–77.Buzzell, R.I., 1971. Inheritance of a soybean flowering response to fluorescent-

daylength conditions. Can. J. Genet. Cytol. 13, 703–707.Choudhury, B.J., Monteith, J.L., 1986. Implications of stomatal response to saturation

deficit for the heat balance of vegetation. Agric. Forest Meteorol. 36, 215–225.Cock, J.H., Porto, M.C.M., El-Sharkawy, M.A., 1985. Water use efficiency of cassava

III. Influence of air humidity and water stress on gas exchange of field growncassava. Crop Sci. 25, 265–272.

Dale, J.E., 1988. The control of leaf expansion. Annu. Rev. Plant Physiol. Plant Mol.Biol. 39, 267–295.

Dastur, R.H., 1925. The relation between water content and photosynthesis. Ann.Bot. 39, 769–786.

de Wit, C.T., 1965. Photosynthesis of leaf canopies. Agric. Res. Report No. 663. PUDOC,Wageningen, The Netherlands.

Decker, J.P., 1947. The effect of air supply on apparent photosynthesis. Plant Physiol.22, 561–571.

Duncan, W.G., Loomis, R.S., Williams, W.A., Hanau, R., 1967. A model for simulatingphotosynthesis in plant communities. Hilgardia 38, 181–205.

El-Sharkawy, M.A., 1975. Crop Research in Kufra Oasis, Libya. Agric. Dev. Council,Tripoli.

El-Sharkawy, M.A., 2005. How can calibrated research-based models be improvedfor use as a tool in identifying genes controlling crop tolerance to environ-mental stresses in the era of genomics-from and experimentalist’s perspective.Photosynthetica 43 (2), 161–176.

El-Sharkawy, M.A., 2009. Pioneering research on C4 leaf anatomical, physiologi-cal, and agronomic characteristics of tropical monocot and dicot plant species:implications for crop water relations and productivity in comparison to C3 crop-ping systems. Photosynthetica 47 (2), 163–183.

El-Sharkawy, M.A., Cock, J.H., 1984. Water use efficiency of cassava I. Effects of airhumidity and water stress on stomatal conductance and gas exchange. Crop Sci.24, 497–502.

El-Sharkawy, M., Hesketh, J., 1965. Photosynthesis among species in relation to char-acteristics of leaf anatomy and CO2 diffusion resistances. Crop Sci. 5, 517–521.

El-Sharkawy, M.A., Hesketh, J.D., 1986. Citation ClassicCommentary—photosynthesis among species in relation to characteris-tics of leaf anatomy and CO2 diffusion resistances. Curr. Cont./Agr. Biol. Environ.27, 14, www.garfield.library.upenn.edu/classics1986/A1986C891300001.pdf.

El-Sharkawy, M.A., Cock, J.H., Held, A.A., 1984. Water use efficiency of cassava II. Dif-fering sensitivity of stomata to air humidity in cassava and other warm-climatespecies. Crop Sci. 24, 503–507.

El-Sharkawy, M.A., Cock, J.H., Hernandez, A.D.P., 1985. Stomatal response to airhumidity and its relation to stomatal density in a wide range of warm climatespecies. Photosynth. Res. 7, 137–149.

El-Sharkawy, M.A., Loomis, R.S., Williams, W.A., 1967. Apparent reassimilation ofrespiratory carbon dioxide by different plant species. Physiol. Plant. 20, 171–186.

Ewers, R.M., Scharlemann, J.P.W., Balmford, A., Green, R.E., 2009. Do increase inagricultural yield spare land for nature? Global Change Biol. 15, 1716–1726,doi:10.1111/j.1365-2486.2009.01849.x.

Farazdaghi, H., 2009. Modeling the kinetics of activation and reaction of Rubiscofrom gas exchange. In: Laisk, A., Nedbal, L., Govindjee (Eds.), Photosynthesisin Silico: Understanding Complexity from Molecules to Ecosystems. SpringerScience+Business Media B.V., pp. 275–294.

Farquhar, G.D., 1978. Feedforward responses of stomata to humidity. Aust. J. PlantPhysiol. 5, 787–800.

Farquhar, G.D., von Caemmerer, S., Berry, J.A., 1980. A biochemical model of photo-

synthetic CO2 fixation in leaves of C3 species. Planta 149, 78–90.

Gaastra, P., 1959. Photosynthesis of crop plants as influenced by light, carbondioxide, temperature and stomatal diffusion resistance. Mededelingen van deLandbouwhogeschool te Wageningen, Nederland 59 (13), 1–68.

Gregory, P., 2006. Roots: Growth, Activity and Interactions with Soils. Wiley-Blackwell Press, Hoboken, NJ.

2 System

G

H

H

H

H

H

H

H

H

I

I

I

J

K

K

K

K

K

K

K

L

L

L

L

L

M

M

M

M

M

M

M

M

M

M

M

10 M.A. El-Sharkawy / Bio

rodzinskii, D.M., 1972. Biofizika rasteniya. Izdatel’stvo “Naukova Dumka”, Kiev,USSSR (Grodzinskii, D.M., 1976. Plant Biophysics. Israel Program for ScientificTranslation, Jerusalem).

amdi, Q.A., Harris, D., Clark, A., 1987. Saturation deficit, canopy formation andfunction in Sorghum bicolor (L.). J. Exp. Bot. 38, 1272–1283.

atch, M.D., Slack, C.R., 1966. Photosynthesis in sugarcane leaves: a new carboxyla-tion reaction and the pathway of sugar formation. Biochem. J. 101, 103–111.

atch, M.D., Slack, C.R., 1970. Photosynthetic CO2-fixation pathways. Annu. Rev.Plant Physiol. 21, 141–162.

einicke, A.J., 1933. A special air chamber for studying photosynthesis under naturalconditions. Science 77, 516–517, doi:10.1126/science.77.2004.516.

einicke, A.J., Childers, N.F., 1936. The influence of water deficiency in photosyn-thesis and transpiration of apple leaves. Proc. Am. Soc. Hort. Sci. 33, 155–159.

esketh, J.D., Baker, D., 1967. Light and carbon assimilation by plant communities.Crop sci. 7, 285–293.

esketh, J.D., Jones, J.W. (Eds.), 1980. Predicting photosynthesis for ecosystem mod-els, vols. I and II. CRC Press, Boca Raton, FL.

esketh, J.D., Musgrave, R.B., 1962. Photosynthesis under field conditions IV. Lightstudies with individual corn leaves. Crop Sci. 2, 311–315.

noue, E., Tani, N., Imai, K., Isobe, S., 1958. The aerodynamic measurement of photo-synthesis over the wheat field. J. Agr. Meteorol. (Tokyo) 13, 121–125.

PCC, 2007. Summary for policymakers. In: Metz, B., et al. (Eds.), Climate Change2007: Mitigation. Contribution of Working Group III to the Fourth AssessmentReport of the Intergovernmental Panel on Climate Change. Cambridge UniversityPress, Cambridge, UK, and New York.

shida, A., Yazaki, K., Hoe, A.L., 2005. Ontogenetic transition of leaf physiology andanatomy from seedlings to mature trees of a rain forest pioneer tree Macarangagigantea. Tree Physiol. 25, 513–522.

ones, J.W., Hesketh, J.D., Kamprath, E.J., Bowen, H.D., 1974. Development of a nitro-gen balance for cotton growth models. Crop Sci. 14, 541–546.

arpilov, Y.S., 1960. The distribution of radioactivity in carbon 14 among the prod-ucts of photosynthesis in maize. Proc. Kazan Agric. Inst. 41, 15–24 (in Russian).

ijne, J.W., Barker, R., Molden, D.J. (Eds.), 2003. Water Productivity in Agriculture:Limits and Opportunities for Improvement. CABI, Publishing, Wallingford, UK.

imball, B.A., Kobayashi, K., Bindi, M., 2002. Responses of agricultural crops to free-air CO2 enrichment. Adv. Agron. 77, 293–368.

iniry, J.R., Landivar, J.A., Witt, M., Gerik, T.J., Cavero, J., Wade, L.J., 1998. Radiation-use efficiency response to vapor pressure deficit for maize and sorghum. FieldCrops Res. 56, 265–270.

irkham, M.B., 2011. Elevated Carbon Dioxide: Impacts on Soil and Plant WaterRelations. CRC Press of Taylor and Francis Group, Boca Raton, FL.

lepper, B., Rickman, R.W., 1991. Predicting root development of crop plants. In:Hodges, T. (Ed.), Predicting Crop Phenology, 85–99. CRC Press, Boca Raton, FL.

ortschak, H.P., Hartt, C.E., Burr, G.O., 1965. Carbon dioxide fixation in sugarcaneleaves. Plant Physiol. 40, 209–213.

aetsch, W.M., 1974. The C4 syndrome: a structural analysis. Annu. Rev. Plant Physiol.25, 27–52.

andsberg, J.J., Hingston, F.J., 1996. Evaluating a simple radiation/dry matter conver-sion model using data from Eucalyptus globulus plantations in Western Australia.Tree Physiol. 16, 801–808.

arson, E.M., Hesketh, J.D., Woolley, J.T., Peters, D.B., 1981. Seasonal variations inapparent photosynthesis among plant stands of different soybean cultivars.Photosynth. Res. 2, 3–20.

ong, S.P., Ainsworth, E.A., Leakey, A.D.B., Nosberger, J., Ort, D.R., 2006. Food forthought: lower-than-expected crop yield stimulation with rising CO2 concen-trations. Science 312, 1918–1921.

oomis, R.S., Rabbinge, R., Ng, E., 1979. Explanatory models in crop physiology. Annu.Rev. Plant Physiol. 30, 339–367.

cCree, K.J., 1974. Equations for the rate of dark respiration of white clover and grainsorghum, as functions of dry weight, photosynthetic rate and temperature. CropSci. 14, 509–514.

cDermitt, D.K., Loomis, R.S., 1981. Elemental composition of biomass and itsrelation to energy content, growth efficiency, and growth yield. Ann. Bot. 48,275–290.

onsi, M., Saeki, T., 1953. Über den Lickhfaktor in den Pflanzengesellschaften und-seine Bedeutung für die Stoffproduktion. Jpn. J. Bot. 14, 22–52.

onsi, M., Uchijima, Z., Oikawa, T., 1973. Structure of foliage canopiesand photosynthesis. Annu. Rev. Ecol. Systemat. 4, 301–327,doi:10.1146/annurev.es.04.110173.001505.

onteith, J.L., 1965. Light distribution and photosynthesis in field crops. Ann. Bot.N.S. 29, 17–37.

onteith, J.L., 1995. A reinterpretation of stomatal responses to humidity. Plant CellEnviron. 18, 357–364.

onteith, J.L., Szeicz, G., Yabuki, J., 1964. Crop photosynthesis and flux of carbondioxide below the canopy. J. Appl. Ecol. 1, 321–337.

oreno-Risueno, M.A., Van Norman, J.M., Moreno, A., Zhang, J., Ahnert, S.E.,Benfey, P.N., 2010. Oscillating gene expression determines competencefor periodic Arabidopsis root branching. Science 329 (5997), 1306–1311,doi:10.1126/science.1191937.

oss, D.N., Musgrave, R.B., Lemon, E.R., 1961. Photosynthesis under field condi-

tions. III. Some effects of light, carbon dioxide, temperature, and soil moistureon photosynthesis, respiration, and transpiration of corn. Crop Sci. 1, 83–87.

oss, D.N., Musgrave, R.B., 1971. Photosynthesis and crop production. Adv. Agron.23:, 317–336.

ott, K.A., Parkhurst, D.F., 1991. Stomatal response to humidity in air and helox.Plant Cell Environ. 14, 509–515.

s 103 (2011) 205–211

Musgrave, R.B., Moss, D.N., 1961. Photosynthesis under field conditions I. A portable,closed system for determining net assimilation and respiration of corn. Crop Sci.1, 37–41.

Nichiporovich, A.A., Strogonova, L.E., Chmora, S.N., Vlasova, M.P., 1961. Fotosin-teticheskaya Deyatel’ nost’ Rsteniï v Posevakh. Izdat. Akad. Nauk SSSR, Moskva.

Oguntunde, P.G., Alatise, M.O., 2007. Environmental regulation and modelling ofcassava canopy conductance under drying root-zone soil water. Meteorol. Appl.14, 245–252.

Pan, X., 1997. Modeling degree day effects on plant leaf and internode phenologicalevents. MS Thesis. University of Illinois, Urbana’ Champaign.

Passioura, J.B., 1988. Water transport in and to roots. Annu. Rev. Plant Physiol. PlantMol. Biol. 39, 245–265.

Penning de Vries, F.W.T., 1975. The cost of maintenance processes in plant cells. Ann.Bot. 39, 77–92.

Penning de Vries, F.W.T., Jansen, D.M., ten Berge, H.F.M., Bakema, A., 1989. Simu-lation of ecophysiological processes of growth in several annual crops. PUDOC,Wageningen.

Pessarakli, M. (Ed.), 2005. Handbook of Photosynthesis, 2nd ed. CRC Press, BocaRaton, FL.

Peterhansel, C., Horst, I., Niessen, M., Blume, C., Kebeish, R., Kürkcüoglu, S., Kreuza-ler, F., 2010. Photorespiration. The Arabidopsis Book. American Society of PlantBiologists, Rockville, MD, doi:10.1199/tab.0130.

Pieruschka, R., Huber, G., Berry, J.A., 2010. Control of transpiration by radiation. PNAS107 (30), 13372–13377.

Postma, J. A., Lynch, J. P., 2010. Theoretical evidence for the functional benefit ofroot cortical aerenchyma in soils with low phosphorus availability. Ann. Bot., inpress.

Prasad, P.V.V., Stagenborg, S.A., Ristic, Z., 2008. Impacts of drought and/or heat stresson physiological, developmental, growth, and yield processes of crop plants. In:Responses of Crops to Limited Water: Understanding and Modeling Water StressEffects on Plant Growth Processes. Advances in Agricultural Systems ModelingsSeries 1. ASA, CSSA, SSSA, Madison, WI, pp. 301–355.

Quinby, J.R., Hesketh, J.D., Voight, R.L., 1973. Influence of temperature and pho-toperiod on floral initiation and leaf number in sorghum. Crop Sci. 13, 243–276.

Ritchie, J.T., 1972. Model for predicting evaporation from a row crop with incompletecover. Water Resour. Res. 8 (12–4), 1213.

Ross, J., 1981. The Radiation Regime and Architecture of Plant Stands, Tasks forVegetative Sciences no. 3. Junk, The Hague.

Saad, S.I., 1954a. Studies on the physiology of the cotton plant IV. Photo-synthesis of cotton leaves under natural conditions. Egypt. Acad. Sc. 10,73–88.

Saad, S.I., 1954b. Studies on the physiology of the cotton plant V. The effect of shad-ing, debudding and watering upon the rate of photosynthesis of cotton leaves.Egypt. Acad. Sci. 10, 94–106.

Sage, T.L., Sage, R.F., 2009. The functional anatomy of rice leaves: implications forrefixation of photorespiratory CO2 and efforts to engineer C4 photosynthesisinto rice. Plant Cell Physiol. 50 (4), 756–772, doi:10.1093/pcp/pcp033.

Schneider, G.W., Childers, N.F., 1941. Influence of soil moisture on photosyn-thesis, respiration, and transpiration of apple leaves. Plant Physiol. 16, 565–583.

Sesták, Z. (Ed.), 1985. Photosynthesis During Leaf Development.Academia/Dr W. Junk N.V. Publishers, Praha/Dordrecht-Bosyon-Lancaster,the Netherlands.

Sesták, Z., Catsky, J., Jarvis, P.G. (Eds.), 1971. Plant Photosynthetic Production. Manualof Methods. Dr W. Junk N.V. Publishers, The Hague, the Netherlands.

Sharkey, T.D., 1985. Photosynthesis in intact leaves of C3 plants: physics, physiologyand rate limitations. The Bot. Rev. 51, 53–105.

Singh, B.N., Lal, K.N., 1935. Limitations of Blackman’s law of limiting factors andHarder’s concept of relative minimum as applied to photosynthesis. Plant Phys-iol. 10, 245–268.

Somerville, C.R., Ogren, W.L., 1979. A phosphoglycolate phosphatase deficientmutant of Arabidopsis. Nature 280, 833–836.

Sprengel, K., 1839. Die Lehre vom Dünger oder Beschreibung aller bei der Land-wirthschaft gebräuchlicher vegetablilischer, animalischer und mineralischerDüngermaterialien, nebst Erklärung ihrer Wirkungsart. Leipzig.

Steiner, J.L., Hatfield, J.L., 2008. Winds of change: a century of agroclimate research.Agron. J. 100, S-132–S-152, doi:10.2134/agronj2006.0372c.

Stige, L.C., Stave, J., Chan, K.-S., Ciannelli, L., Pettorelli, N., Glantz, M., Herren, H.R.,Stenseth, N.C., 2006. The effect of climate variation on agro-pastoral productionin Africa. PNAS 103 (9), 3049–3053.

Stitt, M., Schulze, D., 1994. Does Rubisco control the rate of photosynthesis andplant growth? An exercise in molecular ecophysiology. Plant Cell Environ. 17,465–487.

Taylor, H.M., Klepper, B., 1978. The role of rooting characteristics in the supply ofwater to plants. Adv. Agron. 30, 99–128.

UN NEWS (United Nations System, Standing Committee on Nutrition), 2010. ClimateChange-food and nutrition security implications. SCN NEWS, N0. 38 early-2010.Available from: <http://www.unscn.org>.

von Caemmerer, S., Farquhar, G.D., 1981. Some relationships between the bio-

chemistry of photosynthesis and the gas exchange of leaves. Planta 153,376–387.

Wang, J., Hesketh, J.D., Woolley, J.T., 1986. Preexisting channels and soybean rootingpatterns. Soil Sci. 141, 432–437.

Watson, D.J., 1952. The physiological basis of variation in yield. Adv. Agron. 4,101–145.

System

W

W

M.A. El-Sharkawy / Bio

hisler, F.D., Acock, B., Baker, D.N., Fye, R.E., Hodges, H.F., Lambert, J.R., Lemmon,H.E., McKinion, J.M., Reddy, V.R., 1986. Crop simulation models in agronomicsystems. Adv. Agron. 40, 141–208.

oodrow, I.E., Berry, J.A., 1988. Enzymatic regulation of photosynthetic CO2 fixationin C3 plants. Annu. Rev. Plant Physiol. Plant Mol. Biol. 39, 533–594.

s 103 (2011) 205–211 211

Yuncker, T.G., 1916. A study of the relation of soil moisture to transpiration andphotosynthesis in the corn plant. Plant World 19, 151–161.

Zhang, L.X., Wang, R., Hesketh, J.D., 2001. Effects of photoperiod on growthand development of soybean floral bud in different maturity. Agron. J. 93,944–948.