Genetic Variation of Morphological Traits and Transpiration in an Apple Core Collection under Well-Watered Conditions: Towards the Identification of Morphotypes with High Water Use Efficiency

Water use efficiency (WUE) is a quantitative measurement which improvement is a major issue in the context of global warming and restrictions in water availability for agriculture. In this study, we aimed at studying the variation and genetic control of WUE and the respective role of its components (plant biomass and transpiration) in a perennial fruit crop. We explored an INRA apple core collection grown in a phenotyping platform to screen one-year-old scions for their accumulated biomass, transpiration and WUE under optimal growing conditions. Plant biomass was decompose into morphological components related to either growth or organ expansion. For each trait, nine mixed models were evaluated to account for the genetic effect and spatial heterogeneity inside the platform. The Best Linear Unbiased Predictors of genetic values were estimated after model selection. Mean broad-sense heritabilities were calculated from variance estimates. Heritability values indicated that biomass (0.76) and WUE (0.73) were under genetic control. This genetic control was lower in plant transpiration with an heritability of 0.54. Across the collection, biomass accounted for 70% of the WUE variability. A Hierarchical Ascendant Classification of the core collection indicated the existence of six groups of genotypes with contrasting morphology and WUE. Differences between morphotypes were interpreted as resulting from differences in the main processes responsible for plant growth: cell division leading to the generation of new organs and cell elongation leading to organ dimension. Although further studies will be necessary on mature trees with more complex architecture and multiple sinks such as fruits, this study is a first step for improving apple plant material for the use of water.     

Parameter stability of the functional-structural plant model GREENLAB as affected by variation within populations, among seasons and among growth stages

BACKGROUND AND AIMS: It is increasingly accepted that crop models, if they are to simulate genotype-specific behaviour accurately, should simulate the morphogenetic process generating plant architecture. A functional-structural plant model, GREENLAB, was previously presented and validated for maize. The model is based on a recursive mathematical process, with parameters whose values cannot be measured directly and need to be optimized statistically. This study aims at evaluating the stability of GREENLAB parameters in response to three types of phenotype variability: (1) among individuals from a common population; (2) among populations subjected to different environments (seasons); and (3) among different development stages of the same plants. METHODS: Five field experiments were conducted in the course of 4 years on irrigated fields near Beijing, China. Detailed observations were conducted throughout the seasons on the dimensions and fresh biomass of all above-ground plant organs for each metamer. Growth stage-specific target files were assembled from the data for GREENLAB parameter optimization. Optimization was conducted for specific developmental stages or the entire growth cycle, for individual plants (replicates), and for different seasons. Parameter stability was evaluated by comparing their CV with that of phenotype observation for the different sources of variability. A reduced data set was developed for easier model parameterization using one season, and validated for the four other seasons. KEY RESULTS AND CONCLUSIONS: The analysis of parameter stability among plants sharing the same environment and among populations grown in different environments indicated that the model explains some of the inter-seasonal variability of phenotype (parameters varied less than the phenotype itself), but not inter-plant variability (parameter and phenotype variability were similar). Parameter variability among developmental stages was small, indicating that parameter values were largely development-stage independent. The authors suggest that the high level of parameter stability observed in GREENLAB can be used to conduct comparisons among genotypes and, ultimately, genetic analyses.     

Parameter optimization and field validation of the functional-structural model GREENLAB for maize

BACKGROUND AND AIMS: There are three reasons for the increasing demand for crop models that build the plant on the basis of architectural principles and organogenetic processes: (1) realistic concepts for developing new crops need to be guided by such models; (2) there is an increasing interest in crop phenotypic plasticity, based on variable architecture and morphology; and (3) engineering of mechanized cropping systems requires information on crop architecture. The functional-structural model GREENLAB was recently presented that simulates resource-dependent plasticity of plant architecture. This study introduces a new methodology for crop parameter optimization against measured data called multi-fitting, validates the calibrated model for maize with independent field data, and describes a technique for 3D visualization of outputs. METHODS: Maize was grown near Beijing during the 2000, 2001 and 2003 (two sowing dates) summer seasons in a block design with four to five replications. Detailed morphological and topological observations were made on the plant architecture throughout the development of the four crops. Data obtained in 2000 was used to establish target files for parameter optimization using the generalized least square method, and parameter accuracy was evaluated by coefficient of variance. In situ plant digitization was used to establish 3D symbol files for organs that were then used to translate model outputs directly into 3D representations for each time step of model execution. KEY RESULTS AND CONCLUSIONS: Multi-fitting against several target files obtained at different growth stages gave better parameter accuracy than single fitting at maturity only, and permitted extracting generic organ expansion kinetics from the static observations. The 2000 model gave excellent predictions of plant architecture and vegetative growth for the other three seasons having different temperature regimes, but predictions of inter-seasonal variability of biomass partitioning during grain filling were less accurate. This was probably due to insufficient consideration of processes governing cob sink size and terminal leaf senescence. Further perspectives for model improvement are discussed.     

基于器官生物量构建植株形态的玉米虚拟模型

探讨了基于玉米器官生物量模拟其形态的方法,并应用2000年田间试验数据提取了玉米节间、叶鞘和叶片的形态构建参数。基于玉米虚拟模型生物量分配模块模拟的器官生物量积累和建立的形态构建方法与提取的参数,模拟了2001年玉米不同生长阶段的器官形态,模拟结果与田间试验数据吻合较好。应用本模型实现了玉米生长过程中植株各个器官形态变化以及植株高度、叶面积动态的模拟,并实现了植株形态的可视化。     

Correlation between dynamic tomato fruit-set and source–sink ratio: a common relationship for different plant densities and seasons?

Background and Aims

It is widely accepted that fruit-set in plants is related to source–sink ratio. Despite its critical importance to yield, prediction of fruit-set remains an ongoing problem in crop models. Functional–structural plant models are potentially able to simulate organ-level plasticity of plants. To predict fruit-set, the quantitative link between source–sink ratio and fruit-set probability is analysed here via a functional–structural plant model, GreenLab.

Methods

Two experiments, each with four plant densities, were carried out in a solar greenhouse during two growth seasons (started in spring and autumn). Dynamic fruit-set probability was estimated by frequent observation on inflorescences. Source and sink parameter values were obtained by fitting GreenLab outputs for the biomass of plant parts (lamina, petiole, internode, fruit), at both organ and plant level, to corresponding destructive measurements at six dates from real plants. The dynamic source–sink ratio was calculated as the ratio between biomass production and plant demand (sum of all organ sink strength) per growth cycle, both being outputs of the model.

Key Results and Conclusions

Most sink parameters were stable over multiple planting densities and seasons. From planting, source–sink ratio increased in the vegetative stage and reached a peak after fruit-set commenced, followed by a decrease of leaf appearance rate. Fruit-set probability was correlated with the source–sink ratio after the appearance of flower buds. The relationship between fruit-set probability and the most correlated source–sink ratio could be quantified by a single regression line for both experiments. The current work paves the way to predicting dynamic fruit-set using a functional structure model.     

基于植株拓扑结构的生物量分配的玉米虚拟模型

依据植物结构—功能相互作用机理,建立了能模拟玉米生长发育与形态结构建成的虚拟模型。该模型的重要部分为基于植株拓扑结构的生物量分配模块。叙述了该模块的构建原理,以2000年田间试验数据提取了玉米的发育、生物量生产和生物量分配参数。模型模拟了2001年的玉米生长发育与生物量分配过程,模拟结果与田间试验结果比较吻合。应用该模型模拟了2001年玉米不同生育阶段植株的生物量分配和各器官生物量积累动态。     

Does the Structure–Function Model GREENLAB Deal with Crop Phenotypic Plasticity Induced by Plant Spacing? A Case Study on Tomato

BACKGROUND AND AIMS: Plant growth models able to simulate phenotypic plasticity are increasingly required because (1) they should enable better predictions of the observed variations in crop production, yield and quality, and (2) their parameters are expected to have a more robust genetic basis, with possible implications for selection of quantitative traits such as growth- and allocation-related processes. The structure-function plant model, GREENLAB, simulates resource-dependent plasticity of plant architecture. Evidence for its generality has been previously reported, but always for plants grown in a limited range of environments. This paper aims to test the model concept to its limits by using plant spacing as a means to generate a gradient of competition for light, and by using a new crop species, tomato, known to exhibit a strong photomorphogenetic response. METHODS: A greenhouse experiment was carried out with three homogeneous planting densities (plant spacing = 0.3, 0.6 and 1 m). Detailed records of plant development, plant architecture and organ growth were made throughout the growing period. Model calibration was performed for each situation using a statistical optimization procedure (multi-fitting). KEY RESULTS AND CONCLUSIONS: Obvious limitations of the present version of the model appeared to account fully for the plant plasticity induced by inter-plant competition for light. A lack of stability was identified for some model parameters at very high planting density. In particular, those parameters characterizing organ sink strengths and governing light interception proved to be environment-dependent. Remarkably, however, responses of the parameter values concerned were consistent with actual growth measurements and with previously reported results. Furthermore, modifications of total biomass production and of allocation patterns induced by the planting-density treatments were accurately simulated using the sets of optimized parameters. These results demonstrate that the overall model structure is potentially able to reproduce the observed plant plasticity and suggest that sound biologically based adaptations could overcome the present model limitations. Potential options for model improvement are proposed, and the possibility of using the kernel algorithm currently available as a fitting tool to build up more sophisticated model versions is advocated.     

Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: an integrated modelling approach in maize

Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.     

Oxygen isotope enrichment (delta18O) as a measure of time-averaged transpiration rate

Experimental evidence is presented to show that the 18O enrichment in the leaf biomass and the mean (time-averaged) transpiration rate are positively correlated in groundnut and rice genotypes. The relationship between oxygen isotope enrichment and stomatal conductance (g(s)) was determined by altering g(s) through ABA and subsequently using contrasting genotypes of cowpea and groundnut. The Peclet model for the 18O enrichment of leaf water relative to the source water is able to predict the mean observed values well, while it cannot reproduce the full range of measured isotopic values. Further, it fails to explain the observed positive correlation between transpiration rate and 18O enrichment in leaf biomass. Transpiration rate is influenced by the prevailing environmental conditions besides the intrinsic genetic variability. As all the genotypes of both species experienced similar environmental conditions, the differences in transpiration rate could mostly be dependent on intrinsic g(s). Therefore, it appears that the delta18O of leaf biomass can be used as an effective surrogate for mean transpiration rate. Further, at a given vapour pressure difference, delta18O can serve as a measure of stomatal conductance as well.     

叶片结构的水力学特性对植物生理功能影响的研究进展

叶片是植物进行光合、呼吸、蒸腾作用的主要器官, 早期的研究主要集中于水分在叶片中的运输路径, 而对叶脉结构及其生态学意义研究甚少。近年来关于叶片叶脉结构、气孔结构的功能及叶片水力学特性的意义研究已经成为植物生理生态的研究热点。该文综述了叶脉的结构性状的指标(叶脉密度、直径、间距等), 叶片水力学结构特性对植物生长、水分运输、气体交换、光合作用等生理功能的影响, 及其与植物对干旱适应性之间的关系。叶脉结构是决定叶片生理功能的基础, 因此在未来的工作中应分析比较不同种类植物叶脉结构形态与导水、光合、呼吸、同化作用之间的关系, 建立植物茎干-枝-叶系统水力传导的机理性模型, 用以探索不同植物功能结构和高效用水生理生态学机制, 据此评估不同种类植物在未来气候情景下的地位。     

Harnessing Genetic Variation in Leaf Angle to Increase Productivity of Sorghum bicolor

The efficiency with which a plant intercepts solar radiation is determined primarily by its architecture. Understanding the genetic regulation of plant architecture and how changes in architecture affect performance can be used to improve plant productivity. Leaf inclination angle, the angle at which a leaf emerges with respect to the stem, is a feature of plant architecture that influences how a plant canopy intercepts solar radiation. Here we identify extensive genetic variation for leaf inclination angle in the crop plant Sorghum bicolor, a C4 grass species used for the production of grain, forage, and bioenergy. Multiple genetic loci that regulate leaf inclination angle were identified in recombinant inbred line populations of grain and bioenergy sorghum. Alleles of sorghum dwarf-3, a gene encoding a P-glycoprotein involved in polar auxin transport, are shown to change leaf inclination angle by up to 34° (0.59 rad). The impact of heritable variation in leaf inclination angle on light interception in sorghum canopies was assessed using functional-structural plant models and field experiments. Smaller leaf inclination angles caused solar radiation to penetrate deeper into the canopy, and the resulting redistribution of light is predicted to increase the biomass yield potential of bioenergy sorghum by at least 3%. These results show that sorghum leaf angle is a heritable trait regulated by multiple loci and that genetic variation in leaf angle can be used to modify plant architecture to improve sorghum crop performance.     

Plant growth-form alters the relationship between foliar morphology and species shade-tolerance ranking in temperate woody taxa

Variation in leaf size (area per leaf) and leaf dry weight per area (LWA) in relation to species shade- and drought-tolerance, characterised by Ellenberg's light (ELD) and water demand (EWD) values, respectively, were examined in 60 temperate woody taxa at constant relative irradiance. LWA was independent of plant size, but leaf size increased with total plant height at constant ELD. Canopy position also affected leaf morphology: leaves from the upper crown third had higher LWA and were larger than leaves from the lower third. Leaf size and LWA were negatively correlated, and leaf size decreased and LWA increased with decreasing species shade-tolerance. Mean LWA was similar for trees and shrubs, but trees had larger leaves than shrubs. Furthermore, all relationships were altered by plant growth-form: none of the qualitative tendencies was significant for trees. This implies the considerably lower plasticity of foliar parameters in trees than those in shrubs. Accordingly, shade-tolerance of trees, having relatively constant leaf structure, may be most affected by the variability in biomass partitioning and crown geometry which influence foliage distribution and spacing and finally determine canopy light absorptance. Alteration of leaf form and investment pattern for construction of unit foliar surface area which change the efficiency of light interception per unit biomass investment in leaves, is a competitive strategy inherent to shrubs. EWD as well as wood anatomy did not control LWA and leaf size, though there was a trend of ring-porous tree species to be more shade-tolerant than diffuse-porous trees. Since ring-porous species are more vulnerable to cavitation than diffuse-porous species, they may be constrained to environments where irradiances and consequently evaporative demand is lower.     

Phenomics allows identification of genomic regions affecting maize stomatal conductance with conditional effects of water deficit and evaporative demand

Stomatal conductance is central for the trades‐off between hydraulics and photosynthesis. We aimed at deciphering its genetic control and that of its responses to evaporative demand and water deficit, a nearly impossible task with gas exchanges measurements. Whole‐plant stomatal conductance was estimated via inversion of the Penman–Monteith equation from data of transpiration and plant architecture collected in a phenotyping platform. We have analysed jointly 4 experiments with contrasting environmental conditions imposed to a panel of 254 maize hybrids. Estimated whole‐plant stomatal conductance closely correlated with gas‐exchange measurements and biomass accumulation rate. Sixteen robust quantitative trait loci (QTLs) were identified by genome wide association studies and co‐located with QTLs of transpiration and biomass. Light, vapour pressure deficit, or soil water potential largely accounted for the differences in allelic effects between experiments, thereby providing strong hypotheses for mechanisms of stomatal control and a way to select relevant candidate genes among the 1–19 genes harboured by QTLs. The combination of allelic effects, as affected by environmental conditions, accounted for the variability of stomatal conductance across a range of hybrids and environmental conditions. This approach may therefore contribute to genetic analysis and prediction of stomatal control in diverse environments.     

Linking water stress effects on carbon partitioning by introducing a xylem circuit into L-PEACH

Background and Aims

Many physiological processes such as photosynthesis, respiration and transpiration can be strongly influenced by the diurnal patterns of within-tree water potential. Despite numerous experiments showing the effect of water potential on fruit-tree development and growth, there are very few models combining carbohydrate allocation with water transport. The aim of this work was to include a xylem circuit into the functional–structural L-PEACH model.

Methods

The xylem modelling was based on an electrical circuit analogy and the Hagen–Poisseuille law for hydraulic conductance. Sub-models for leaf transpiration, soil water potential and the soil–plant interface were also incorporated to provide the driving force and pathway for water flow. The model was assessed by comparing model outputs to field measurements and published knowledge.

Key Results

The model was able to simulate both the water uptake over a season and the effect of different irrigation treatments on tree development, growth and fruit yield.

Conclusions

This work opens the way to a new field of modelling where complex interactions between water transport, carbohydrate allocation and physiological functions can be simulated at the organ level and describe functioning and behaviour at the tree scale.     

The Heat and Mass Transfer Analysis of a Leaf

Understanding the heat and mass transfer processes of plant leaves is essential for plant bionic engineering. A general thermophysical model was established for a plant leaf with particular emphasis on the transpiration process. The model was verified by the field measured stomatal resistance and temperature of a camphor leaf. A dynamical simulation revealed that diurnal transpiration water consumption is dominated by the solar irradiance and the day-average temperature of the leaf is dominated by the ambient air temperature; transpiration plays an important role in the cooling of the leaf, in average it could dissipate around 32.9% of the total solar energy absorbed by the leaf in summer. To imitate the thermal infared characteristic of the real leaf, the up surface of the bionic leaf must have emissivity and solar absorptivity close to those of a real leaf and its shape and surface roughness must be similar to those of the real leaf. The key point is that the bionic leaf must be able to evaporate water to simulate the transpiration of a plant leaf, appropriate adsorbent can be used to realize this function.     

Quantitative genetics and functional-structural plant growth models: simulation of quantitative trait loci detection for model parameters and application to potential yield optimization

BACKGROUND AND AIMS: Prediction of phenotypic traits from new genotypes under untested environmental conditions is crucial to build simulations of breeding strategies to improve target traits. Although the plant response to environmental stresses is characterized by both architectural and functional plasticity, recent attempts to integrate biological knowledge into genetics models have mainly concerned specific physiological processes or crop models without architecture, and thus may prove limited when studying genotype x environment interactions. Consequently, this paper presents a simulation study introducing genetics into a functional-structural growth model, which gives access to more fundamental traits for quantitative trait loci (QTL) detection and thus to promising tools for yield optimization. METHODS: The GREENLAB model was selected as a reasonable choice to link growth model parameters to QTL. Virtual genes and virtual chromosomes were defined to build a simple genetic model that drove the settings of the species-specific parameters of the model. The QTL Cartographer software was used to study QTL detection of simulated plant traits. A genetic algorithm was implemented to define the ideotype for yield maximization based on the model parameters and the associated allelic combination. KEY RESULTS AND CONCLUSIONS: By keeping the environmental factors constant and using a virtual population with a large number of individuals generated by a Mendelian genetic model, results for an ideal case could be simulated. Virtual QTL detection was compared in the case of phenotypic traits--such as cob weight--and when traits were model parameters, and was found to be more accurate in the latter case. The practical interest of this approach is illustrated by calculating the parameters (and the corresponding genotype) associated with yield optimization of a GREENLAB maize model. The paper discusses the potentials of GREENLAB to represent environment x genotype interactions, in particular through its main state variable, the ratio of biomass supply over demand.     

A common genetic determinism for sensitivities to soil water deficit and evaporative demand: meta-analysis of quantitative trait Loci and introgression lines of maize

Evaporative demand and soil water deficit equally contribute to water stress and to its effect on plant growth. We have compared the genetic architectures of the sensitivities of maize (Zea mays) leaf elongation rate with evaporative demand and soil water deficit. The former was measured via the response to leaf-to-air vapor pressure deficit in well-watered plants, the latter via the response to soil water potential in the absence of evaporative demand. Genetic analyses of each sensitivity were performed over 21 independent experiments with (1) three mapping populations, with temperate or tropical materials, (2) one population resulting from the introgression of a tropical drought-tolerant line in a temperate line, and (3) two introgression libraries genetically independent from mapping populations. A very large genetic variability was observed for both sensitivities. Some lines maintained leaf elongation at very high evaporative demand or water deficit, while others stopped elongation in mild conditions. A complex architecture arose from analyses of mapping populations, with 19 major meta-quantitative trait loci involving strong effects and/or more than one mapping population. A total of 68% of those quantitative trait loci affected sensitivities to both evaporative demand and soil water deficit. In introgressed lines, 73% of the tested genomic regions affected both sensitivities. To our knowledge, this study is the first genetic demonstration that hydraulic processes, which drive the response to evaporative demand, also have a large contribution to the genetic variability of plant growth under water deficit in a large range of genetic material.     

Growth and water-use efficiency of 10 Triticum aestivum cultivars at different water availability in relation to allocation of biomass

In environments where the amount of water is limiting growth, water-use efficiency (biomass production per unit water use) is an important trait. We studied the relationships of plant growth and water use efficiency with the pattern of biomass allocation, using 10 wheat cultivars, grown at two soil moisture levels in a growth chamber. Allocation pattern and relative growth rate were not correlated, whereas allocation pattern and water use efficiency were. Variation in transpiration per plant resulted from variation in the rate of transpiration per unit leaf area or root weight, rather than from differences in leaf area or root weight per plant. Transpiration per unit leaf area or root weight was lower when the leaf area or root weight per unit plant weight was larger. Also, the efficiency of water use at the plant and leaf levels was higher for plants with a higher leaf area per unit plant weight, and it was not correlated with the plant's growth rate. Differences in water-use efficiency at the leaf level were related to variation in stomatal conductance, rather than in the rate of photosynthesis. A high photosynthetic water-use efficiency was associated with a low efficiency of nitrogen use for photosynthesis.