Simulating daily field crop canopy photosynthesis: an integrated software package
Alex Wu A C D , Al Doherty A C , Graham D. Farquhar B C and Graeme L. Hammer A C
+ Author Affiliations
- Author Affiliations
A Centre for Plant Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Qld 4072, Australia.
B Research School of Biology, Australian National University, Canberra, ACT 2601, Australia.
C ARC Centre of Excellence for Translational Photosynthesis, Australia.
D Corresponding author. Email: c.wu1@uq.edu.au
Functional Plant Biology 45(3) 362-377 https://doi.org/10.1071/FP17225
Submitted: 9 August 2017 Accepted: 29 September 2017 Published: 13 November 2017
Abstract
Photosynthetic manipulation is seen as a promising avenue for advancing field crop productivity. However, progress is constrained by the lack of connection between leaf-level photosynthetic manipulation and crop performance. Here we report on the development of a model of diurnal canopy photosynthesis for well watered conditions by using biochemical models of C3 and C4 photosynthesis upscaled to the canopy level using the simple and robust sun–shade leaves representation of the canopy. The canopy model was integrated over the time course of the day for diurnal canopy photosynthesis simulation. Rationality analysis of the model showed that it simulated the expected responses in diurnal canopy photosynthesis and daily biomass accumulation to key environmental factors (i.e. radiation, temperature and CO2), canopy attributes (e.g. leaf area index and leaf angle) and canopy nitrogen status (i.e. specific leaf nitrogen and its profile through the canopy). This Diurnal Canopy Photosynthesis Simulator (DCaPS) was developed into a web-based application to enhance usability of the model. Applications of the DCaPS package for assessing likely canopy-level consequences of changes in photosynthetic properties and its implications for connecting photosynthesis with crop growth and development modelling are discussed.
Additional keywords: CO2 partial pressure, dry matter accumulation, modeling, modelling, radiation, temperature effects.
References
Ainsworth EA, Long SP (2005) What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytologist 165, 351–372.| What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2.Crossref | GoogleScholarGoogle Scholar |
Ball JT, Woodrow I, Berry J (1987) A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions. In ‘Progress in photosynthesis research’. (Ed. J Biggins) pp. 221–224. (Martinus Nijhoff Publishers: Dordrecht, The Netherlands)
Bernacchi CJ, Singsaas EL, Pimentel C, Portis AR, Long SP (2001) Improved temperature response functions for models of Rubisco-limited photosynthesis. Plant, Cell & Environment 24, 253–259.
| Improved temperature response functions for models of Rubisco-limited photosynthesis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3MXhsFGrt7k%3D&md5=6409d4c27cdeb7d2ab0dc2ffcf1f98a7CAS |
Bernacchi CJ, Portis AR, Nakano H, von Caemmerer S, Long SP (2002) Temperature response of mesophyll conductance. Implications for the determination of Rubisco enzyme kinetics and for limitations to photosynthesis in vivo. Plant Physiology 130, 1992–1998.
| Temperature response of mesophyll conductance. Implications for the determination of Rubisco enzyme kinetics and for limitations to photosynthesis in vivo.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXktlOj&md5=1a29283064c28fa71fde6bd9c92cb31dCAS |
Boyd RA, Gandin A, Cousins AB (2015) Temperature response of C4 photosynthesis: biochemical analysis of Rubisco, phosphoenolpyruvate carboxylase and carbonic anhydrase in Setaria viridis. Plant Physiology 169, 1850–1861.
Braune H, Mueller J, Diepenbrock W (2009) Integrating effects of leaf nitrogen, age, rank, and growth temperature into the photosynthesis-stomatal conductance model LEAFC3-N parameterised for barley (Hordeum vulgare L.). Ecological Modelling 220, 1599–1612.
| Integrating effects of leaf nitrogen, age, rank, and growth temperature into the photosynthesis-stomatal conductance model LEAFC3-N parameterised for barley (Hordeum vulgare L.).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXntVyltrs%3D&md5=dd29306a87d1652eb4bb02225720be9bCAS |
Damour G, Simonneau T, Cochard H, Urban L (2010) An overview of models of stomatal conductance at the leaf level. Plant, Cell & Environment 33, 1419–1438.
de Pury DGG, Farquhar GD (1997) Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models. Plant, Cell & Environment 20, 537–557.
| Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models.Crossref | GoogleScholarGoogle Scholar |
Duncan WG, Loomis RS, Williams WA, Hanau R (1967) A model for simulating photosynthesis in plant communities. Hilgardia 38, 181–205.
| A model for simulating photosynthesis in plant communities.Crossref | GoogleScholarGoogle Scholar |
Evans JR (2013) Improving photosynthesis. Plant Physiology 162, 1780–1793.
| Improving photosynthesis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtlWlt7zE&md5=7d83be5dba892356e03ac61919ba57c5CAS |
Farquhar GD, von Caemmerer S, Berry JA (1980) A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149, 78–90.
| A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL3cXksVWrt7w%3D&md5=6db882a9dac8dc5a797c6c3206d6450cCAS |
Fischer T, Byerlee D, Greg E (2014) Crop yields and global food security: will yield increase continue to feed the world? ACIAR Monograph 158. Australian Centre for International Agricultural Research, Canberra, Australia.
Flexas J, Barbour MM, Brendel O, Cabrera HM, Carriqui M, Diaz-Espejo A, Douthe C, Dreyer E, Ferrio JP, Gago J, Galle A, Galmes J, Kodama N, Medrano H, Niinemets U, Peguero-Pina JJ, Pou A, Ribas-Carbo M, Tomas M, Tosens T, Warren CR (2012) Mesophyll diffusion conductance to CO2: an unappreciated central player in photosynthesis. Plant Science 193–194, 70–84.
| Mesophyll diffusion conductance to CO2: an unappreciated central player in photosynthesis.Crossref | GoogleScholarGoogle Scholar |
George-Jaeggli B, Jordan DR, van Oosterom EJ, Broad IJ, Hammer GL (2013) Sorghum dwarfing genes can affect radiation capture and radiation use efficiency. Field Crops Research 149, 283–290.
| Sorghum dwarfing genes can affect radiation capture and radiation use efficiency.Crossref | GoogleScholarGoogle Scholar |
Gifford RM (2003) Plant respiration in productivity models: conceptualisation, representation and issues for global terrestrial carbon-cycle research. Functional Plant Biology 30, 171–186.
| Plant respiration in productivity models: conceptualisation, representation and issues for global terrestrial carbon-cycle research.Crossref | GoogleScholarGoogle Scholar |
Goudriaan J, van Laar HH (1994) ‘Modelling potential crop growth processes: textbook with exercises.’ (Kluwer Academic Publishers: Dordrecht, The Netherlands)
Grant RF, Peters DB, Larson EM, Huck MG (1989) Simulation of canopy photosynthesis in maize and soybean. Agricultural and Forest Meteorology 48, 75–92.
| Simulation of canopy photosynthesis in maize and soybean.Crossref | GoogleScholarGoogle Scholar |
Hammer GL, Wright GC (1994) A theoretical-analysis of nitrogen and radiation effects on radiation use efficiency in peanut. Australian Journal of Agricultural Research 45, 575–589.
| A theoretical-analysis of nitrogen and radiation effects on radiation use efficiency in peanut.Crossref | GoogleScholarGoogle Scholar |
Hammer GL, Dong Z, McLean G, Doherty A, Messina C, Schussler J, Zinselmeier C, Paszkiewicz S, Cooper M (2009) Can changes in canopy and/or root system architecture explain historical maize yield trends in the US corn belt? Crop Science 49, 299–312.
| Can changes in canopy and/or root system architecture explain historical maize yield trends in the US corn belt?Crossref | GoogleScholarGoogle Scholar |
Hammer GL, van Oosterom E, McLean G, Chapman SC, Broad I, Harland P, Muchow RC (2010) Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops. Journal of Experimental Botany 61, 2185–2202.
| Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXmsVGnsr0%3D&md5=7da0847d4bd8ddd66075e8d8b8d38b46CAS |
Humphries SW, Long SP (1995) WIMOVAC – a software package for modeling the dynamics of plant leaf and canopy photosynthesis. Computer Applications in the Biosciences 11, 361–371.
Jarvis PG (1976) Interpretation of variations in leaf water potential and stomatal conductance found in canopies in field. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 273, 593–610.
| Interpretation of variations in leaf water potential and stomatal conductance found in canopies in field.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaE28XhslKlt70%3D&md5=ac664590527ab722e127870458b59622CAS |
June T, Evans JR, Farquhar GD (2004) A simple new equation for the reversible temperature dependence of photosynthetic electron transport: a study on soybean leaf. Functional Plant Biology 31, 275–283.
| A simple new equation for the reversible temperature dependence of photosynthetic electron transport: a study on soybean leaf.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXjt1ejurs%3D&md5=60323fd262d736493ea757b7386f60f3CAS |
Kimball BA, Kobayashi K, Bindi M (2002) Responses of agricultural crops to free-air CO2 enrichment. In ‘Advances in agronomy. Vol. 77’. (Ed. LS Donald) pp. 293–368. (Academic Press: Cambridge, MA, USA)
Leakey ADB, Uribelarrea M, Ainsworth EA, Naidu SL, Rogers A, Ort DR, Long SP (2006) Photosynthesis, productivity, and yield of maize are not affected by open-air elevation of CO2 concentration in the absence of drought. Plant Physiology 140, 779–790.
| Photosynthesis, productivity, and yield of maize are not affected by open-air elevation of CO2 concentration in the absence of drought.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XjsV2iu7k%3D&md5=71af44347fbcb0ab5233defbdacb0b4aCAS |
Leuning R (1995) A critical-appraisal of a combined stomatal-photosynthesis model for C3 plants. Plant, Cell & Environment 18, 339–355.
| A critical-appraisal of a combined stomatal-photosynthesis model for C3 plants.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2MXlslCksbs%3D&md5=17b66cdd361087ceb56b8c2ddfc65c92CAS |
Leuning R, Kelliher FM, De Pury DGG, Schulze ED (1995) Leaf nitrogen, photosynthesis, conductance and transpiration: scaling from leaves to canopies. Plant, Cell & Environment 18, 1183–1200.
| Leaf nitrogen, photosynthesis, conductance and transpiration: scaling from leaves to canopies.Crossref | GoogleScholarGoogle Scholar |
Li G, Lin L, Dong Y, An D, Li Y, Luo W, Yin X, Li W, Shao J, Zhou Y, Dai J, Chen W, Zhao C (2012) Testing two models for the estimation of leaf stomatal conductance in four greenhouse crops cucumber, chrysanthemum, tulip and lilium. Agricultural and Forest Meteorology 165, 92–103.
| Testing two models for the estimation of leaf stomatal conductance in four greenhouse crops cucumber, chrysanthemum, tulip and lilium.Crossref | GoogleScholarGoogle Scholar |
Lobell DB, Hammer GL, Chenu K, Zheng B, McLean G, Chapman SC (2015) The shifting influence of drought and heat stress for crops in northeast Australia. Global Change Biology 21, 4115–4127.
| The shifting influence of drought and heat stress for crops in northeast Australia.Crossref | GoogleScholarGoogle Scholar |
Long SP, Marshall-Colon A, Zhu X-G (2015) Meeting the global food demand of the future by engineering crop photosynthesis and yield potential. Cell 161, 56–66.
| Meeting the global food demand of the future by engineering crop photosynthesis and yield potential.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXls1ags7g%3D&md5=0f52bae8cd18fe3840a531dbee8e58d2CAS |
Ludlow MM (1981) Effect of temperature on light utilization efficiency of leaves in C3 legumes and C4 grasses. Photosynthesis Research 1, 243–249.
| Effect of temperature on light utilization efficiency of leaves in C3 legumes and C4 grasses.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC2czps1ygtg%3D%3D&md5=b2e9366f0e2602b0260a61cf94349533CAS |
Massad R-S, Tuzet A, Bethenod O (2007) The effect of temperature on C4-type leaf photosynthesis parameters. Plant, Cell & Environment 30, 1191–1204.
| The effect of temperature on C4-type leaf photosynthesis parameters.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtVeiurrF&md5=07aadfeec5ae3a75ca7f11d9ec54ad54CAS |
Massignam AM (2003) Quantifying nitrogen effects on crop growth processes in maize and sunflower. PhD thesis. School of Land, Crop and Food Sciences, University of Queensland, St Lucia, Qld, Australia.
Monsi M, Saeki T (1953) Über den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion. Japanese Journal of Botany 14, 22–52.
Muchow RC, Sinclair TR (1994) Nitrogen response of leaf photosynthesis and canopy radiation use efficiency in field-grown maize and sorghum. Crop Science 34, 721–727.
| Nitrogen response of leaf photosynthesis and canopy radiation use efficiency in field-grown maize and sorghum.Crossref | GoogleScholarGoogle Scholar |
Nagai T, Makino A (2009) Differences between rice and wheat in temperature responses of photosynthesis and plant growth. Plant & Cell Physiology 50, 744–755.
| Differences between rice and wheat in temperature responses of photosynthesis and plant growth.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXkslKhuro%3D&md5=228c2b63ead328cc73968f01a6500544CAS |
O’Leary GJ, Christy B, Nuttall J, Huth N, Cammarano D, Stöckle C, Basso B, Shcherbak I, Fitzgerald G, Luo Q, Farre-Codina I, Palta J, Asseng S (2015) Response of wheat growth, grain yield and water use to elevated CO2 under a free-air CO2 enrichment (FACE) experiment and modelling in a semi-arid environment. Global Change Biology 21, 2670–2686.
| Response of wheat growth, grain yield and water use to elevated CO2 under a free-air CO2 enrichment (FACE) experiment and modelling in a semi-arid environment.Crossref | GoogleScholarGoogle Scholar |
Olson SN, Ritter K, Rooney W, Kemanian A, McCarl BA, Zhang Y, Hall S, Packer D, Mullet J (2012) High biomass yield energy sorghum: developing a genetic model for C4 grass bioenergy crops. Biofuels, Bioproducts & Biorefining 6, 640–655.
| High biomass yield energy sorghum: developing a genetic model for C4 grass bioenergy crops.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhtlKjurvL&md5=5199cf04791891500323058941754a9bCAS |
Parton WJ, Logan JA (1981) A model for diurnal variation in soil and air temperature. Agricultural Meteorology 23, 205–216.
| A model for diurnal variation in soil and air temperature.Crossref | GoogleScholarGoogle Scholar |
Pons TL, Flexas J, von Caemmerer S, Evans JR, Genty B, Ribas-Carbo M, Brugnoli E (2009) Estimating mesophyll conductance to CO2: methodology, potential errors, and recommendations. Journal of Experimental Botany 60, 2217–2234.
| Estimating mesophyll conductance to CO2: methodology, potential errors, and recommendations.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXmtlyitbk%3D&md5=0f0dce6b6cd5b91a3270d419e64a7a03CAS |
Reyenga PJ, Howden SM, Meinke H, McKeon GM (1999) Modelling global change impacts on wheat cropping in south-east Queensland, Australia. Environmental Modelling & Software 14, 297–306.
| Modelling global change impacts on wheat cropping in south-east Queensland, Australia.Crossref | GoogleScholarGoogle Scholar |
Sands P (1995) Modelling Canopy Production. II. From single-leaf photosynthesis parameters to daily canopy photosynthesis. Functional Plant Biology 22, 603–614.
Sellers PJ, Berry JA, Collatz GJ, Field CB, Hall FG (1992) Canopy reflectance, photosynthesis, and transpiration. 3. A reanalysis using improved leaf models and a new canopy integration scheme. Remote Sensing of Environment 42, 187–216.
| Canopy reflectance, photosynthesis, and transpiration. 3. A reanalysis using improved leaf models and a new canopy integration scheme.Crossref | GoogleScholarGoogle Scholar |
Sharkey TD, Bernacchi CJ, Farquhar GD, Singsaas EL (2007) Fitting photosynthetic carbon dioxide response curves for C3 leaves. Plant, Cell & Environment 30, 1035–1040.
| Fitting photosynthetic carbon dioxide response curves for C3 leaves.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtVeiur3F&md5=6e09ee70f54fef63acd184d4920e8411CAS |
Sharwood RE, Ghannoum O, Whitney SM (2016) Prospects for improving CO2 fixation in C3-crops through understanding C4-Rubisco biogenesis and catalytic diversity. Current Opinion in Plant Biology 31, 135–142.
| Prospects for improving CO2 fixation in C3-crops through understanding C4-Rubisco biogenesis and catalytic diversity.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC28XmslKqt7s%3D&md5=74bd6921192cf36162dd5b2c4c4a8aedCAS |
Sinclair TR, Horie T (1989) Leaf nitrogen, photosynthesis, and crop radiation use efficiency – a review. Crop Science 29, 90–98.
| Leaf nitrogen, photosynthesis, and crop radiation use efficiency – a review.Crossref | GoogleScholarGoogle Scholar |
Sinclair TR, Muchow RC (1999) Radiation use efficiency. Advances in Agronomy 65, 215–265.
| Radiation use efficiency.Crossref | GoogleScholarGoogle Scholar |
Tubiello F, Volk T, Bugbee B (1997) Diffuse light and wheat radiation-use efficiency in a controlled environment. Life Support & Biosphere Science 4, 77–85.
van Oosterom EJ, Borrell AK, Chapman SC, Broad IJ, Hammer GL (2010) Functional dynamics of the nitrogen balance of sorghum: I. N demand of vegetative plant parts. Field Crops Research 115, 19–28.
| Functional dynamics of the nitrogen balance of sorghum: I. N demand of vegetative plant parts.Crossref | GoogleScholarGoogle Scholar |
von Caemmerer S (2000) ‘Biochemical models of leaf photosynthesis. Vol. 2.’ (CSIRO Publishing: Melbourne)
von Caemmerer S (2013) Steady-state models of photosynthesis. Plant, Cell & Environment 36, 1617–1630.
| Steady-state models of photosynthesis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXht1Cht7fN&md5=4de7a1493d1534fa7b10a67151a24a9aCAS |
Vos J, Evers JB, Buck-Sorlin GH, Andrieu B, Chelle M, de Visser PHB (2010) Functional–structural plant modelling: a new versatile tool in crop science. Journal of Experimental Botany 61, 2101–2115.
| Functional–structural plant modelling: a new versatile tool in crop science.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXmsVGgu7g%3D&md5=a1f35a31d3e9a6460499de7af45b651fCAS |
Wong SC, Cowan IR, Farquhar GD (1979) Stomatal conductance correlates with photosynthetic capacity. Nature 282, 424–426.
| Stomatal conductance correlates with photosynthetic capacity.Crossref | GoogleScholarGoogle Scholar |
Wu A, Song Y, van Oosterom EJ, Hammer GL (2016) Connecting biochemical photosynthesis models with crop models to support crop improvement. Frontiers in Plant Science 7, 1518
| Connecting biochemical photosynthesis models with crop models to support crop improvement.Crossref | GoogleScholarGoogle Scholar |
Yan W, Hunt LA (1999) An equation for modelling the temperature response of plants using only the cardinal temperatures. Annals of Botany 84, 607–614.
| An equation for modelling the temperature response of plants using only the cardinal temperatures.Crossref | GoogleScholarGoogle Scholar |
Yin X, Struik PC (2008) Applying modelling experiences from the past to shape crop systems biology: the need to converge crop physiology and functional genomics. New Phytologist 179, 629–642.
| Applying modelling experiences from the past to shape crop systems biology: the need to converge crop physiology and functional genomics.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhtVKns7zJ&md5=71af747d6b4e8fd8db75ff7fad708fcaCAS |
Yin X, Struik PC (2009) C3 and C4 photosynthesis models: an overview from the perspective of crop modelling. NJAS Wageningen Journal of Life Sciences 57, 27–38.
| C3 and C4 photosynthesis models: an overview from the perspective of crop modelling.Crossref | GoogleScholarGoogle Scholar |
Yin X, van Laar HH (2005) ‘Crop systems dynamics: an ecophysiological simulation model for genotype-by-environment interactions.’ (Wageningen Academic Publishers: Wageningen, The Netherlands)
Zhang H, Nobel P (1996) Dependency of C i/C a and leaf transpiration efficiency on the vapour pressure deficit. Functional Plant Biology 23, 561–568.
