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Revising crop and architectural models of maize canopy development for rainfed cropping conditions

Youhong Song1, Colin Birch1, 4, Shanshan Qu2, Jim Hanan3

Emails: y.song@uq.edu.au; c.birch@uq.edu.au; shanshanqu@sohu.com; j.hanan@uq.edu.au
1
The University of Queensland, School of Land, Crop and Food Sciences, Gatton Campus, Gatton, 4343, Australia
2
Agricultural Science and Technology Extension Station of Qingdao, 266071, China
3
The University of Queensland, Centre for Biological Information Technology, Brisbane, 4072, Australia
4
Present Address: The University of Tasmania, Cradle Coast Campus, Burnie, 7320, Tasmania

Abstract

The ability to precisely predict the effects of water stress on crop production is vital to improved risk assessment in water-limited conditions. A crop model and a crop architectural model were revised to enhance their ability to simulate canopy development under water limitation. A field trial with three water regimes was conducted in 2006-07 to calibrate both models and test the revision. Leaf initiation and appearance rates and area of the largest leaf for the recently released cultivar Pioneer 31H50 under non-stressed conditions differed from cultivars included in APSIM-Maize. We reconfigured the genetic-context parameters for Pioneer 31H50 in APSIM-Maize under well-watered conditions. LAI growth and biomass accumulation under three water regimes were accurately predicted by APSIM-Maize once configured for Pioneer 31H50, indicating that revision for the new cultivar was successful and that the stress index used by APSIM-Maize produces appropriate adjustments to leaf area. Meanwhile, changes in the sensitivity of processes such as leaf extension to water stress were also successfully introduced to the plant architectural model ADEL-Maize, with accurate prediction of an independent data set. This study enhances capability to model the impact of water stress on canopy development and function for this recently released maize cultivar.

Key Words

Zea mays, drought, APSIM-Maize, ADEL-Maize, canopy development

Introduction

Drought is a critical limitation to crop production in arid and semi-arid areas and water is expected to be increasingly scarce under global climate change. The ability to precisely predict the effects of water stress on crop production is vital to improve risk assessment and management and evaluate new genotypes for tolerance of water-limited conditions. Thus, it is imperative for the models to provide accurate predictions for extensive drought conditions for a wide range of genotypes (Carberry et al. 1989; Cavero et al. 2000; Nouna et al. 2000, 2003; Mastrorilli et al. 2003). The crop model APSIM-Maize provides a framework to account for new genotypes and environments by using cultivar and site specific parameters, and stress indices to adjust leaf area in response to stresses. ADEL-Maize has been developed to simulate three-dimensional architectural development driven by thermal time under a non-stressed environment (Fournier and Andrieu 1999). It provides an interface to consider new cultivars by modifying genetic parameters but did not account for water stress. Birch et al (2008) undertook a preliminary study of the effects of water stress on maize canopy architecture and revised the ADEL-Maize model. This paper will revise the crop model APSIM-Maize and the architectural crop model ADEL-Maize to enhance capacity to simulate canopy development for a recently released cultivar grown under water limitation.

Methods

Experiment

A field experiment with maize was carried out at The University of Queensland, Gatton Campus, Southeast Queensland, Australia in 2006-07 as detailed in Song et al. (2007), so only a brief outline of the experiment is presented here. The maize hybrid P31H50, which has a maximum of ~21 leaves, was sown on 6th September, 2006 in rows 75 cm apart at a density of 60,000 plants ha-1. Three water regimes were imposed by combining irrigation and rainfed scenarios: (i) rainfed, RF, dependent on rainfall; (ii) irrigated, then rainfed, IRF, irrigated until the 12th leaf was fully expanded, then rainfed; and (iii) fully irrigated FI, fully irrigated. Two replicates were used, and daily minimum and maximum temperature, solar radiation and rainfall were recorded by a weather station near the field site. Data on leaf dimension, internode length and biomass of individual organs were collected using destructive sampling at 2-3 day intervals.

Data analysis

Extension of organs was scaled by thermal time with 8C base temperature. Linear extension rates (LER) of organs or groups of organs were obtained by regressing individual leaf and internode extension on thermal time from emergence. The effect of reduced water availability on LER was assessed by regressing the difference of LER and the average difference of fraction of extractable soil water produced by APSIM-Maize (Song et al. 2007) between FI and RF treatments over the period of linear extension of specific organs.

Modelling studies

Leaf development and production in APSIM-Maize was calibrated for the cultivar Pioneer 31H50. The module controlling organ extension in ADEL-Maize was revised by inserting a linear representation of organ extension and a new response function to modify organ extension rates under water stress (Song et al. 2007). The revised models were then used to simulate maize canopy development. The validation was implemented by comparing fitted (dependant data, which were used to derive relationships or constants used in simulation), simulated (independent data, which retained only for validation) and observed leaf area index (LAI, both models), biomass (APSIM-Maize only).

Results and discussion

Rate of leaf production and appearance under non-limiting conditions

The thermal time interval between the initiation of successive leaves was found to be 26.5Cd calculated by dividing accumulated thermal time at tassel initiation by number of initiated leaves (15) (final leaf number 21 minus 6 (embryonic leaves in seed)). Leaf appearance rate was calculated for two groups: lower leaves (up to and including the leaf subtending the ear, here leaf 13) and leaves above the ear, the point of changes was determined by minimum least squares techniques. The appearance rates were 0.02Cd-1 for leaves up to leaf 13 and 0.034Cd-1 for leaves above the ear. The largest leaf area of 90050 cm2 was found at the ear position (leaf 13, the leaf subtending the ear).

Figure 1. Comparisons of fitted, simulated and observed LAI after emergence for fully irrigated, FI, rainfed, RF and irrigated, then rainfed, IRF. Vertical bars indicate 95% confidence intervals.

Figure 2. Comparisons of fitted, simulated and observed biomass accumulation after emergence for fully irrigated, FI, rainfed, RF and irrigated, then rainfed, IRF. Vertical bars indicate 95% confidence intervals.

Testing of LAI and biomass growth using APSIM-Maize

Figure 1 presents comparisons of fitted (FI, used to calibrate cultivar relevant parameters), simulated (IRF, RF) and observed LAI during the vegetative stage of maize development. Simulated LAI was close to observed data, thus the modifications of leaf initiation, leaf appearance and leaf area for the new cultivar were suitable under optimal irrigation and the approach using stress indices (Song et al. 2007) to produce appropriate adjustments to leaf area was sound. Figure 2 presents the comparisons of fitted (FI) and predicted (IRF, RF) and observed biomass accumulation during vegetative growth. The prediction of biomass accumulation was close to observed data, indicating that the module calculating biomass is robust under fully watered and stressed conditions.

Crop architectural model

The reduction in linear extension rates (LER) of leaf and internode in response to water stress was linearly related to the difference of fraction of extractable soil water between fully irrigated (FI) and water stressed (RF) plants (Figure 3). The introduction of these relationships to ADEL-Maize further improved the simulation of the effect of water stress on leaf and internode extension, plant height and plant leaf area during canopy development. The close agreement between fitted (FI and RF used to derive functions), simulated and observed LAI (without considering leaf senescence) is shown in Figure 4. Biomass production was not considered, as it is not included in the present version of the ADEL-Maize model. Modelling light distribution and interception within the canopy in ADEL-Maize is now underway, which will enable the model to predict light use efficiency (RUE) and biomass growth under water non-limited and water stressed conditions.

a

b

Figure 3. Relationship between reduction in LER for (a) leaves, (b) internodes and average difference in FESW during extension of organs (from Song et al (2007)).

Figure 4. Comparisons of fitted, simulated and observed LAI growth after emergence for fully irrigated, FI, rainfed, RF and irrigated, then rainfed, IRF (drawn from leaf area of individual plant). Vertical bars indicate 95% confidence intervals.

Conclusion

Temporal increase in LAI during vegetative stage were simulated by both models and verified with independent datasets. This validation showed that the revisions on leaf area production in both models for Pioneer 31H50 were successful and stress indices to reduce leaf area in response to water stress in APSIM-Maize and introduction of new response function into ADEL-Maize were successful. Simulation of biomass production by APSIM-Maize was accurate, and an approach to biomass simulation by ADEL-Maize is proposed to enhance its functionality. The successful revisions to existing models will provide valuable tools to assist the assessment of maize canopy development in the areas of water limitation.

References

Birch CJ, Thornby D, Adkins S, Andrieu B, Hanan J, 2008. Architectural modelling of maize under water stress. Australian Journal of Experimental Agriculture 48, 335-341.

Carberry PS, Muchow RC and McCown RL (1989) Testing the CERES-Maize simulation model in a semi-arid tropical environment. Field Crops Research 20, 297-315.

Cavero J, Farre I, Debaeke P, Faci JM (2000) Simulation of Maize Yield under Water Stress with the EPICphase and CROPWAT Models. Agronomy Journal 92, 679-690.

Fournier C, Andrieu B (1999) ADEL-maize: an L-system based model for the integration of growth processes from the organ to the canopy. Application to regulation of morphogenesis by light availability. Agronomie 19, 313-327.

Nouna BB, Katerji N, Mastrorilli M (2000) Using the CERES-Maize model in a semi-arid Mediterranean environment. Evaluation of model performance. European Journal of Agronomy 13, 309-322.

Nouna BB, Katerji N, Mastrorilli (2003) Using the CERES-Maize model in a semi-arid Mediterranean environment. New modeling of leaf area and water stress functions. European Journal of Agronomy 19, 115-123.

Song Y, Birch C, Hanan J (2007) Architectural analysis and modelling of maize growth and development under water stress. 5th International Workshop on Functional Structural Plant Models (FSPM07), Napier New Zealand, 04-10, Nov, 2007.

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