Towards grapevine root architectural models to adapt viticulture to drought.

To sustainably adapt viticultural production to drought, the planting of rootstock genotypes adapted to a changing climate is a promising means. Rootstocks contribute to the regulation of scion vigor and water consumption, modulate scion phenological development and determine resource availability by root system architecture development. There is, however, a lack of knowledge on spatio-temporal root system development of rootstock genotypes and its interactions with environment and management that prevents efficient knowledge transfer into practice. Hence, winegrowers take only limited advantage of the large variability of existing rootstock genotypes. Models of vineyard water balance combined with root architectural models, using both static and dynamic representations of the root system, seem promising tools to match rootstock genotypes to frequently occurring future drought stress scenarios and address scientific knowledge gaps. In this perspective, we discuss how current developments in vineyard water balance modeling may provide the background for a better understanding of the interplay of rootstock genotypes, environment and management. We argue that root architecture traits are key drivers of this interplay, but our knowledge on rootstock architectures in the field remains limited both qualitatively and quantitatively. We propose phenotyping methods to help close current knowledge gaps and discuss approaches to integrate phenotyping data into different models to advance our understanding of rootstock x environment x management interactions and predict rootstock genotype performance in a changing climate. This could also provide a valuable basis for optimizing breeding efforts to develop new grapevine rootstock cultivars with optimal trait configurations for future growing conditions.

Towards a Stochastic Model to Simulate Grapevine Architecture: A Case Study on Digitized Riesling Vines Considering Effects of Elevated CO2.

Modeling plant growth, in particular with functional-structural plant models, can provide tools to study impacts of changing environments in silico. Simulation studies can be used as pilot studies for reducing the on-field experimental effort when predictive capabilities are given. Robust model calibration leads to less fragile predictions, while introducing uncertainties in predictions allows accounting for natural variability, resulting in stochastic plant growth models. In this study, stochastic model components that can be implemented into the functional-structural plant model Virtual Riesling are developed relying on Bayesian model calibration with the goal to enhance the model towards a fully stochastic model. In this first step, model development targeting phenology, in particular budburst variability, phytomer development rate and internode growth are presented in detail. Multi-objective optimization is applied to estimate a single set of cardinal temperatures, which is used in phenology and growth modeling based on a development days approach. Measurements from two seasons of grapevines grown in a vineyard with free-air carbon dioxide enrichment (FACE) are used; thus, model building and selection are coupled with an investigation as to whether including effects of elevated CO2 conditions to be expected in 2050 would improve the models. The results show how natural variability complicates the detection of possible treatment effects, but demonstrate that Bayesian calibration in combination with mixed models can realistically recover natural shoot growth variability in predictions. We expect these and further stochastic model extensions to result in more realistic virtual plant simulations to study effects, which are used to conduct in silico studies of canopy microclimate and its effects on grape health and quality.

Missing Links in Predicting Berry Sunburn in Future Vineyards.

Sunburn in grapevine berries is known as a recurring disorder causing severe yield losses and a decline in berry quality. The transition from healthy to sunburnt along a temporal trajectory is not fully understood. It is driven by light-boosted local heat impact and modulated by, e.g., past environments of the berry and its developmental state. Events of berry sunburn are often associated with heatwaves, indicating a link to climate change. In addition, the sensitivity of grapevine architecture to changing environmental condition indicates an urgent need to investigate and adapt mitigation strategies of berry sunburn in future vineyards. In this perspective, we want to identify missing links in predicting berry sunburn in vineyards and propose a modeling framework that may help us to investigate berry sunburn in future vineyards. For this, we propose to address open issues in both developing a model of berry sunburn and considering dynamic canopy growth, and canopy interaction with the environment and plant management such as shoot positioning or leaf removal. Because local environmental conditions drive sunburn, we aim at showing that identifying sunburn-reducing strategies in a vineyard under future environmental conditions can be supported by a modeling approach that integrates effects of management practices over time and takes grapevine architecture explicitly into account. We argue that functional-structural plant models may address such complex tasks. Once open issues are solved, they might be a promising tool to advance our knowledge on reducing risks of berry sunburn in silico.

High light aggravates functional limitations of cucumber canopy photosynthesis under salinity.

Background and Aims: Most crop species are glycophytes, and salinity stress is one of the most severe abiotic stresses reducing crop yields worldwide. Salinity affects plant architecture and physiological functions by different mechanisms, which vary largely between crop species and determine the susceptibility or tolerance of a crop species to salinity. Methods: Experimental data from greenhouse cucumber (Cucumis sativus), a salt-sensitive species, grown under three salinity levels were interpreted by combining a functional-structural plant model and quantitative limitation analysis of photosynthesis. This approach allowed the quantitative dissection of canopy photosynthetic limitations into architectural and functional limitations. Functional limitations were further dissected into stomatal (Ls), mesophyll (Lm) and biochemical (Lb). Key Results: Architectural limitations increased rapidly after the start of the salinity treatment and became stronger than the sum of functional limitations (Ls + Lm + Lb) under high salinity. Stomatal limitations resulted from ionic effects and were much stronger than biochemical limitations, indicating that canopy photosynthesis was more limited by the effects of leaf sodium on stomatal regulation than on photosynthetic enzymes. Sensitivity analyses suggested that the relative importance of salinity effects on architectural and functional limitations depends on light conditions, with high light aggravating functional limitations through salinity effects on stomatal limitations. Conclusions: Salinity tolerance of cucumber is more likely to be improved by traits related to leaf growth and stomatal regulation than by traits related to tissue tolerance to ion toxicity, especially under high light conditions.

High temperature and vapor pressure deficit aggravate architectural effects but ameliorate non-architectural effects of salinity on dry mass production of tomato.

Tomato (Solanum lycopersicum L.) is an important vegetable crop and often cultivated in regions exposed to salinity and high temperatures (HT) which change plant architecture, decrease canopy light interception and disturb physiological functions. However, the long-term effects of salinity and HT combination (S+HT) on plant growth are still unclear. A dynamic functional-structural plant model (FSPM) of tomato was parameterized and evaluated for different levels of S+HT combinations. The evaluated model was used to quantify the contributions of morphological changes (architectural effects) and physiological disturbances (non-architectural effects) on the reduction of shoot dry mass under S+HT. The model predicted architectural variables with high accuracy (>85%), which ensured the reliability of the model analyses. HT enhanced architectural effects but reduced non-architectural effects of salinity on dry mass production. The stronger architectural effects of salinity under HT could not be counterbalanced by the smaller non-architectural effects. Therefore, long-term influences of HT on shoot dry mass under salinity were negative at the whole plant level. Our model analysis highlights the importance of plant architecture at canopy level in studying the plant responses to the environments and shows the merits of dynamic FSPMs as heuristic tools.

Predicting Plant Performance Under Simultaneously Changing Environmental Conditions-The Interplay Between Temperature, Light, and Internode Growth.

Plant performance is significantly influenced by prevailing light and temperature conditions during plant growth and development. For plants exposed to natural fluctuations in abiotic environmental conditions it is however laborious and cumbersome to experimentally assign any contribution of individual environmental factors to plant responses. This study aimed at analyzing the interplay between light, temperature and internode growth based on model approaches. We extended the light-sensitive virtual plant model L-Cucumber by implementing a common Arrhenius function for appearance rates, growth rates, and growth durations. For two greenhouse experiments, the temperature-sensitive model approach resulted in a precise prediction of cucumber mean internode lengths and number of internodes, as well as in accurately predicted patterns of individual internode lengths along the main stem. In addition, a system's analysis revealed that environmental data averaged over the experimental period were not necessarily related to internode performance. Finally, the need for a species-specific parameterization of the temperature response function and related aspects in modeling temperature effects on plant development and growth is discussed.

Disentangling the contributions of osmotic and ionic effects of salinity on stomatal, mesophyll, biochemical and light limitations to photosynthesis.

There are conflicting opinions on the relative importance of photosynthetic limitations under salinity. Quantitative limitation analysis of photosynthesis provides insight into the contributions of different photosynthetic limitations, but it has only been applied under saturating light conditions. Using experimental data and modelling approaches, we examined the influence of light intensity on photosynthetic limitations and quantified the osmotic and ionic effects of salinity on stomatal (LS ), mesophyll (LM ), biochemical (LB ) and light (LL ) limitations in cucumber (Cucumis sativus L.) under different light intensities. Non-linear dependencies of LS , LM and LL to light intensity were found. Osmotic effects on LS and LM increased with the salt concentration in the nutrient solution (Ss ) and the magnitude of LM depended on light intensity. LS increased with the Na(+) concentration in the leaf water (Sl ) and its magnitude depended on Ss . Biochemical capacity declined linearly with Sl but, surprisingly, the relationship between LB and Sl was influenced by Ss . Our results suggest that (1) improvement of stomatal regulation under ionic stress would be the most effective way to alleviate salinity stress in cucumber and (2) osmotic stress may alleviate the ionic effects on LB but aggravate the ionic effects on LS .

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model.

There is increasing interest in evaluating the environmental effects on crop architectural traits and yield improvement. However, crop models describing the dynamic changes in canopy structure with environmental conditions and the complex interactions between canopy structure, light interception, and dry mass production are only gradually emerging. Using tomato (Solanum lycopersicum L.) as a model crop, a dynamic functional-structural plant model (FSPM) was constructed, parameterized, and evaluated to analyse the effects of temperature on architectural traits, which strongly influence canopy light interception and shoot dry mass. The FSPM predicted the organ growth, organ size, and shoot dry mass over time with high accuracy (>85%). Analyses of this FSPM showed that, in comparison with the reference canopy, shoot dry mass may be affected by leaf angle by as much as 20%, leaf curvature by up to 7%, the leaf length:width ratio by up to 5%, internode length by up to 9%, and curvature ratios and leaf arrangement by up to 6%. Tomato canopies at low temperature had higher canopy density and were more clumped due to higher leaf area and shorter internodes. Interestingly, dry mass production and light interception of the clumped canopy were more sensitive to changes in architectural traits. The complex interactions between architectural traits, canopy light interception, dry mass production, and environmental conditions can be studied by the dynamic FSPM, which may serve as a tool for designing a canopy structure which is 'ideal' in a given environment.

What is the most prominent factor limiting photosynthesis in different layers of a greenhouse cucumber canopy?

BACKGROUND AND AIMS: Maximizing photosynthesis at the canopy level is important for enhancing crop yield, and this requires insights into the limiting factors of photosynthesis. Using greenhouse cucumber (Cucumis sativus) as an example, this study provides a novel approach to quantify different components of photosynthetic limitations at the leaf level and to upscale these limitations to different canopy layers and the whole plant. METHODS: A static virtual three-dimensional canopy structure was constructed using digitized plant data in GroIMP. Light interception of the leaves was simulated by a ray-tracer and used to compute leaf photosynthesis. Different components of photosynthetic limitations, namely stomatal (S(L)), mesophyll (M(L)), biochemical (B(L)) and light (L(L)) limitations, were calculated by a quantitative limitation analysis of photosynthesis under different light regimes. KEY RESULTS: In the virtual cucumber canopy, B(L) and L(L) were the most prominent factors limiting whole-plant photosynthesis. Diffusional limitations (S(L) + M(L)) contributed <15% to total limitation. Photosynthesis in the lower canopy was more limited by the biochemical capacity, and the upper canopy was more sensitive to light than other canopy parts. Although leaves in the upper canopy received more light, their photosynthesis was more light restricted than in the leaves of the lower canopy, especially when the light condition above the canopy was poor. An increase in whole-plant photosynthesis under diffuse light did not result from an improvement of light use efficiency but from an increase in light interception. Diffuse light increased the photosynthesis of leaves that were directly shaded by other leaves in the canopy by up to 55%. CONCLUSIONS: Based on the results, maintaining biochemical capacity of the middle-lower canopy and increasing the leaf area of the upper canopy would be promising strategies to improve canopy photosynthesis in a high-wire cucumber cropping system. Further analyses using the approach described in this study can be expected to provide insights into the influences of horticultural practices on canopy photosynthesis and the design of optimal crop canopies.

Dry matter partitioning models for the simulation of individual fruit growth in greenhouse cucumber canopies.

BACKGROUND AND AIMS: Growth imbalances between individual fruits are common in indeterminate plants such as cucumber (Cucumis sativus). In this species, these imbalances can be related to differences in two growth characteristics, fruit growth duration until reaching a given size and fruit abortion. Both are related to distribution, and environmental factors as well as canopy architecture play a key role in their differentiation. Furthermore, events leading to a fruit reaching its harvestable size before or simultaneously with a prior fruit can be observed. Functional-structural plant models (FSPMs) allow for interactions between environmental factors, canopy architecture and physiological processes. Here, we tested hypotheses which account for these interactions by introducing dominance and abortion thresholds for the partitioning of assimilates between growing fruits. METHODS: Using the L-System formalism, an FSPM was developed which combined a model for architectural development, a biochemical model of photosynthesis and a model for assimilate partitioning, the last including a fruit growth model based on a size-related potential growth rate (R(P)). Starting from a distribution proportional to R(P), the model was extended by including abortion and dominance. Abortion was related to source strength and dominance to sink strength. Both thresholds were varied to test their influence on fruit growth characteristics. Simulations were conducted for a dense row and a sparse isometric canopy. KEY RESULTS: The simple partitioning models failed to simulate individual fruit growth realistically. The introduction of abortion and dominance thresholds gave the best results. Simulations of fruit growth durations and abortion rates were in line with measurements, and events in which a fruit was harvestable earlier than an older fruit were reproduced. CONCLUSIONS: Dominance and abortion events need to be considered when simulating typical fruit growth traits. By integrating environmental factors, the FSPM can be a valuable tool to analyse and improve existing knowledge about the dynamics of assimilates partitioning.

Simplification of a light-based model for estimating final internode length in greenhouse cucumber canopies.

BACKGROUND AND AIMS: Light quantity and quality affect internode lengths in cucumber (Cucumis sativus), whereby leaf area and the optical properties of the leaves mainly control light quality within a cucumber plant community. This modelling study aimed at providing a simple, non-destructive method to predict final internode lengths (FILs) using light quantity and leaf area data. METHODS: Several simplifications of a light quantity and quality sensitive model for estimating FILs in cucumber have been tested. The direct simplifications substitute the term for the red : far-red (R : FR) ratios, by a term for (a) the leaf area index (LAI, m(2) m(-2)) or (b) partial LAI, the cumulative leaf area per m(2) ground, where leaf area per m(2) ground is accumulated from the top of each plant until a number, n, of leaves per plant is reached. The indirect simplifications estimate the input R : FR ratio based on partial leaf area and plant density. KEY RESULTS: In all models, simulated FILs were in line with the measured FILs over various canopy architectures and light conditions, but the prediction quality varied. The indirect simplification based on leaf area of ten leaves revealed the best fit with measured data. Its prediction quality was even higher than of the original model. CONCLUSIONS: This study showed that for vertically trained cucumber plants, leaf area data can substitute local light quality data for estimating FIL data. In unstressed canopies, leaf area over the upper ten ranks seems to represent the feedback of the growing architecture on internode elongation with respect to light quality. This highlights the role of this domain of leaves as the primary source for the specific R : FR signal controlling the final length of an internode and could therefore guide future research on up-scaling local processes to the crop level.

Modelling photo-modulated internode elongation in growing glasshouse cucumber canopies.

• Growing glasshouse plant canopies are exposed to natural fluctuations in light quantity, and the dynamically changing canopy architecture induces local variations in light quality. This modelling study aimed to analyse the importance of both light signals for an accurate prediction of individual internode lengths. • We conceptualized two model approaches for estimating final internode lengths (FILs). The first one is only photosynthetically active radiation (PAR)-sensitive and ignores canopy architecture, whereas the second approach uses a functional-structural growth model for considering variations in both PAR and red : far-red (R : FR) ratio (L-Cucumber). Internode lengths measured in three experiments were used for model parameterization and evaluation. • The overall trends for the simulated FILs using the exclusively PAR-sensitive model approach were already in line with the measured FILs, but they underestimated FILs at higher ranks. L-Cucumber provided considerably better FIL predictions under various light conditions and canopy architectures. • Both light signals are needed for an accurate estimation of the FILs, and only L-Cucumber is able to consider R : FR signals from the growing canopy. Yet this study highlights the significance of the PAR signal for predicting FILs as neighbour effects increase, which indicates a potential role of photosynthate signalling in internode elongation.

Modelling leaf phototropism in a cucumber canopy.

Leaf phototropism might have significant effects on the light interception, dry matter production and yield of cucumber (Cucumis sativus L.). The objective of the present study was to model the phototropism of leaves in a greenhouse cucumber canopy. The dynamic structural model of cucumber using a parametric L-system was extended to mimic the leaf movement induced by gradients in the local light environment of each leaf. The red to far-red (R : FR) ratio is known to be a driving force in shade avoidance reactions of plants. In the model, R : FR ratios on the left and right leaf half of each individual leaf lamina were calculated and the change in tropism angle per phyllochron was based on the R : FR gradient across the leaf halves. The tropism angle of a leaf describes the deviation of the present leaf azimuth from the initial leaf orientation, which is predefined by the phyllotaxis of the plant. Even in its simple form, the model simulated photo-morphogenic canopy responses.