Predictable 'meta-mechanisms' emerge from feedbacks between transpiration and plant growth and cannot be simply deduced from short-term mechanisms

Genotype × environment × management analysis to define allometric rules between leaves and stems in wheat

Allometric rules provide insights into structure-function relationships across species and scales and are commonly used in ecology. The fields of agronomy, plant phenotyping, and modeling also need simplifications such as those provided by allometric rules to reconcile data at different temporal and spatial levels (organs/canopy). This study explores the variations in relationships for wheat in terms of the distribution of crop green area between leaves and stems, and the allocation of above-ground biomass between leaves and stems during the vegetative period, using a large dataset covering different years, countries, genotypes, and management practices. The results showed that the relationship between leaf and stem area was linear, genotype-specific, and sensitive to radiation. The relationship between leaf and stem biomass depended on genotype and nitrogen fertilization. The mass per area, associating area and biomass for both leaf and stem, varied strongly by developmental stage and was significantly affected by environment and genotype. These allometric rules were evaluated and shown to have satisfactory performance, and their potential use is discussed with regard to current phenotyping techniques and plant/crop models. Our results enable the definition of models and minimum datasets required for characterizing diversity panels and making predictions in various genotype × environment × management contexts.

Are high-throughput root phenotyping platforms suitable for informing root system architecture models with genotype-specific parameters? An evaluation based on the root model ArchiSimple and a small panel of wheat cultivars

Given the difficulties in accessing plant roots in situ, high-throughput root phenotyping (HTRP) platforms under controlled conditions have been developed to meet the growing demand for characterizing root system architecture (RSA) for genetic analyses. However, a proper evaluation of their capacity to provide the same estimates for strictly identical root traits across platforms has never been achieved. In this study, we performed such an evaluation based on six major parameters of the RSA model ArchiSimple, using a diversity panel of 14 bread wheat cultivars in two HTRP platforms that had different growth media and non-destructive imaging systems together with a conventional set-up that had a solid growth medium and destructive sampling. Significant effects of the experimental set-up were found for all the parameters and no significant correlations across the diversity panel among the three set-ups could be detected. Differences in temperature, irradiance, and/or the medium in which the plants were growing might partly explain both the differences in the parameter values across the experiments as well as the genotype × set-up interactions. Furthermore, the values and the rankings across genotypes of only a subset of parameters were conserved between contrasting growth stages. As the parameters chosen for our analysis are root traits that have strong impacts on RSA and are close to parameters used in a majority of RSA models, our results highlight the need to carefully consider both developmental and environmental drivers in root phenomics studies.

Differences in mucilage properties and stomatal sensitivity of locally adapted Zea mays in relation with precipitation seasonality and vapour pressure deficit regime of their native environment

With ongoing climate change and the increase in extreme weather events, especially droughts, the challenge of maintaining food security is becoming ever greater. Locally adapted landraces of crops represent a valuable source of adaptation to stressful environments. In the light of future droughts-both by altered soil water supply and increasing atmospheric water demand (vapor pressure deficit [VPD])-plants need to improve their water efficiency. To do so, plants can enhance their access to soil water by improving rhizosphere hydraulic conductivity via the exudation of mucilage. Furthermore, plants can reduce transpirational water loss via stomatal regulation. Although the role of mucilage and stomata regulation on plant water management have been extensively studied, little is known about a possible coordination between root mucilage properties and stomatal sensitivity as well as abiotic drivers shaping the development of drought resistant trait suits within landraces. Mucilage properties and stomatal sensitivity of eight Mexican landraces of Zea mays in contrast with one inbred line were first quantified under controlled conditions and second related to water demand and supply at their respective site of origin. Mucilage physical properties-namely, viscosity, contact angle, and surface tension-differed between the investigated maize varieties. We found strong influences of precipitation seasonality, thus plant water availability, on mucilage production (R 2 = .88, p < .01) and mucilage viscosity (R 2 = .93, p < .01). Further, stomatal sensitivity to increased atmospheric water demand was related to mucilage viscosity and contact angle, both of which are crucial in determining mucilage's water repellent, thus maladaptive, behavior upon soil drying. The identification of landraces with pre-adapted suitable trait sets with regard to drought resistance is of utmost importance, for example, trait combinations such as exhibited in one of the here investigated landraces. Our results suggest a strong environmental selective force of seasonality in plant water availability on mucilage properties as well as regulatory stomatal effects to avoid mucilage's maladaptive potential upon drying and likely delay critical levels of hydraulic dysfunction. By this, landraces from highly seasonal climates may exhibit beneficial mucilage and stomatal traits to prolong plant functioning under edaphic drought. These findings may help breeders to efficiently screen for local landraces with pre-adaptations to drought to ultimately increase crop yield resistance under future climatic variability.

Effects of superhydrophobic sand mulching on evapotranspiration and phenotypic responses in tomato (Solanum lycopersicum) plants under normal and reduced irrigation

Irrigated agriculture in arid and semi-arid regions is a vital contributor to the global food supply. However, these regions endure massive evaporative losses that are compensated by exploiting limited freshwater resources. To increase water-use efficiency in these giga-scale operations, plastic mulches are utilized; however, their non-biodegradability and eventual land-filling renders them unsustainable. In response, we have developed superhydrophobic sand (SHS) mulching technology that is comprised of sand grains or sandy soils with a nanoscale coating of paraffin wax. Here, we investigate the effects of 1 cm-thick SHS mulching on the evapotranspiration and phenotypic responses of tomato (Solanum lycopersicum) plants as a model system under normal and reduced irrigation inside controlled growth chambers. Experimental results reveal that under either irrigation scenario, SHS mulching suppresses evaporation and enhances transpiration by 78% and 17%, respectively relative to the unmulched soil. Comprehensive phenotyping revealed that SHS mulching enhanced root xylem vessel diameter, stomatal aperture, stomatal conductance, and chlorophyll content index by 21%, 25%, 28%, and 23%, respectively, in comparison with the unmulched soil. Consequently, total fruit yields, total dry mass, and harvest index increased in SHS-mulched plants by 33%, 20%, and 16%, respectively compared with the unmulched soil. We also provide mechanistic insights into the effects of SHS mulching on plant physiological processes. These results underscore the potential of SHS for realizing food-water security and greening initiatives in arid regions.

Optimizing Crop Water Use for Drought and Climate Change Adaptation Requires a Multi-Scale Approach

Selection criteria that co-optimize water use efficiency and yield are needed to promote plant productivity in increasingly challenging and variable drought scenarios, particularly dryland cereals in the semi-arid tropics. Optimizing water use efficiency and yield fundamentally involves transpiration dynamics, where restriction of maximum transpiration rate helps to avoid early crop failure, while maximizing grain filling. Transpiration restriction can be regulated by multiple mechanisms and involves cross-organ coordination. This coordination involves complex feedbacks and feedforwards over time scales ranging from minutes to weeks, and from spatial scales ranging from cell membrane to crop canopy. Aquaporins have direct effect but various compensation and coordination pathways involve phenology, relative root and shoot growth, shoot architecture, root length distribution profile, as well as other architectural and anatomical aspects of plant form and function. We propose gravimetric phenotyping as an integrative, cross-scale solution to understand the dynamic, interwoven, and context-dependent coordination of transpiration regulation. The most fruitful breeding strategy is likely to be that which maintains focus on the phene of interest, namely, daily and season level transpiration dynamics. This direct selection approach is more precise than yield-based selection but sufficiently integrative to capture attenuating and complementary factors.

New drought-adaptive loci underlying candidate genes on wheat chromosome 4B with improved photosynthesis and yield responses

Flag leaf serves as an essential source of assimilates during grain filling, thereby contributing to grain yield up to 48%. Thus, high-throughput phenotyping of flag leaves is crucial to determine their physiological and genetic basis of yield formation and drought adaptation. Here, we utilized 200 wheat cultivars to identify drought-adaptive loci underlying candidate genes associated with flag leaf biomass and photosynthesis-related traits using a genome-wide association study (GWAS). GWAS revealed 21 significant marker-trait associations for key photosynthetic traits in response to drought stress. Analysis of linkage disequilibrium (LD) in these SNPs intervals discovered 103 significant SNPs that established distinct LD blocks containing a total of 382 candidate genes putatively involved in physiological processes, including photosynthesis and water responses. Further, in silico transcript analysis identified two candidate genes in locus AX-580365925 on chromosome 4B, those were found to be highly expressed under drought and associated with proton-transporting ATP synthase activity and stress response pathways. Accordingly, we identified significant allelic haplotype differences on this same locus. The tolerant haplotype (higher chlorophyll content under drought) representing major allele was more abundant and stably increased photosynthetic efficiency and yield under drought scenarios. Collectively, this study offers new adaptive loci and beneficial alleles to reshape the flag leaf physiological and associated photosynthetic components for better yield and sustainability to water-deficit stress.

Sensitivities to temperature and evaporative demand in wheat relatives

There is potential sources of alleles and genes currently locked into wheat-related species that could be introduced into wheat breeding programs for current and future hot and dry climates. However, neither the intra- nor the inter-specific diversity of the responses of leaf growth and transpiration to temperature and evaporative demand have been investigated in a large diversity of wheat-related species. By analysing 12 groups of wheat-related sub-species, we questioned the n-dimensional structure of the genetic diversity for traits linked to plant vegetative structures and development, leaf expansion and transpiration together with their responses to "non-stressing" range of temperature and evaporative demand. In addition to provide new insight on how genome type, ploidy level, phylogeny and breeding pressure together structure this genetic diversity, this study provides new mathematical formalisms and the associated parameters of trait responses in the large genetic diversity of wheat-related species. This potentially allow crop models predicting the impact of this diversity on yield, and indicate potential sources of varietal improvement for modern wheat germplasms, through interspecific crosses.

Importance of the description of light interception in crop growth models

Canopy light interception determines the amount of energy captured by a crop, and is thus critical to modeling crop growth and yield, and may substantially contribute to the prediction uncertainty of crop growth models (CGMs). We thus analyzed the canopy light interception models of the 26 wheat (Triticum aestivum) CGMs used by the Agricultural Model Intercomparison and Improvement Project (AgMIP). Twenty-one CGMs assume that the light extinction coefficient (K) is constant, varying from 0.37 to 0.80 depending on the model. The other models take into account the illumination conditions and assume either that all green surfaces in the canopy have the same inclination angle (θ) or that θ distribution follows a spherical distribution. These assumptions have not yet been evaluated due to a lack of experimental data. Therefore, we conducted a field experiment with five cultivars with contrasting leaf stature sown at normal and double row spacing, and analyzed θ distribution in the canopies from three-dimensional canopy reconstructions. In all the canopies, θ distribution was well represented by an ellipsoidal distribution. We thus carried out an intercomparison between the light interception models of the AgMIP-Wheat CGMs ensemble and a physically based K model with ellipsoidal leaf angle distribution and canopy clumping (KellC). Results showed that the KellC model outperformed current approaches under most illumination conditions and that the uncertainty in simulated wheat growth and final grain yield due to light models could be as high as 45%. Therefore, our results call for an overhaul of light interception models in CGMs.

Crop adaptation to climate change as a consequence of long-term breeding

Major global crops in high-yielding, temperate cropping regions are facing increasing threats from the impact of climate change, particularly from drought and heat at critical developmental timepoints during the crop lifecycle. Research to address this concern is frequently focused on attempts to identify exotic genetic diversity showing pronounced stress tolerance or avoidance, to elucidate and introgress the responsible genetic factors or to discover underlying genes as a basis for targeted genetic modification. Although such approaches are occasionally successful in imparting a positive effect on performance in specific stress environments, for example through modulation of root depth, major-gene modifications of plant architecture or function tend to be highly context-dependent. In contrast, long-term genetic gain through conventional breeding has incrementally increased yields of modern crops through accumulation of beneficial, small-effect variants which also confer yield stability via stress adaptation. Here we reflect on retrospective breeding progress in major crops and the impact of long-term, conventional breeding on climate adaptation and yield stability under abiotic stress constraints. Looking forward, we outline how new approaches might complement conventional breeding to maintain and accelerate breeding progress, despite the challenges of climate change, as a prerequisite to sustainable future crop productivity.

Turgor-time controls grass leaf elongation rate and duration under drought stress

The process of leaf elongation in grasses is characterized by the creation and transformation of distinct cell zones. The prevailing turgor pressure within these cells is one of the key drivers for the rate at which these cells divide, expand and differentiate, processes that are heavily impacted by drought stress. In this article, a turgor-driven growth model for grass leaf elongation is presented, which combines mechanistic growth from the basis of turgor pressure with the ontogeny of the leaf. Drought-induced reductions in leaf turgor pressure result in a simultaneous inhibition of both cell expansion and differentiation, lowering elongation rate but increasing elongation duration due to the slower transitioning of cells from the dividing and elongating zone to mature cells. Leaf elongation is, therefore, governed by the magnitude of, and time spent under, growth-enabling turgor pressure, a metric which we introduce as turgor-time. Turgor-time is able to normalize growth patterns in terms of varying water availability, similar to how thermal time is used to do so under varying temperatures. Moreover, additional inclusion of temperature dependencies within our model pioneers a novel concept enabling the general expression of growth regardless of water availability or temperature.

A Method for Performing Reforestation to Effectively Recover Soil Water Content in Extremely Degraded Tropical Rain Forests

Deforestation continues to be extensive in the tropics, resulting in reduced soil water content. Reforestation is an effective way to recover soil water content, but the recovery depends on the type of reforestation efforts that are implemented. Monoculture of fast-growing species is a common reforestation strategy, because it is an effective means of preventing landslides resulting from the frequent typhoons and heavy rains in the tropics and easy to implement. To quantify whether monoculture plantings can help recover soil water content, we initiated a reforestation project within a 0.2 km2 area of an extremely degraded tropical monsoon forest. We hypothesized that much higher transpiration rate of fast-growing tree species would deplete soil water more than the dominant slow-growing species in the adjacent secondary tropical rain forest during both wet and dry seasons, thereby resulting in much lower soil water content. To test this hypothesis, we compared transpiration rates and key functional traits that can distinguish transpiration rates between fast-growing and dominant slow-growing species in both wet and dry seasons. We also quantified whether soil water content around these species differed. We found that fast-growing species had transpiration rate and transpiration-related trait values that were 5–10 times greater than the dominant slow-growing species in both seasons. We also found that soil water content around dominant slow-growing species was 1.5–3 times greater than for fast-growing species in both seasons. Therefore, reforestation based on monoculture plantings of fast-growing species seems difficult to effectively recover the soil water content. We also provide a simple method for guiding the use of reforestation efforts to recover soil water content in extremely degraded tropical rain forests. We expect that this simple method can be an effective means to restore extremely degraded tropical rain forests in other parts of the world.

Simulating the effect of flowering time on maize individual leaf area in contrasting environmental scenarios

The quality of yield prediction is linked to that of leaf area. We first analysed the consequences of flowering time and environmental conditions on the area of individual leaves in 127 genotypes presenting contrasting flowering times in fields of Europe, Mexico, and Kenya. Flowering time was the strongest determinant of leaf area. Combined with a detailed field experiment, this experiment showed a large effect of flowering time on the final leaf number and on the distribution of leaf growth rate and growth duration along leaf ranks, in terms of both length and width. Equations with a limited number of genetic parameters predicted the beginning, end, and maximum growth rate (length and width) for each leaf rank. The genotype-specific environmental effects were analysed with datasets in phenotyping platforms that assessed the effects (i) of the amount of intercepted light on leaf width, and (ii) of temperature, evaporative demand, and soil water potential on leaf elongation rate. The resulting model was successfully tested for 31 hybrids in 15 European and Mexican fields. It potentially allows prediction of the vertical distribution of leaf area of a large number of genotypes in contrasting field conditions, based on phenomics and on sensor networks.

Over-accumulation of abscisic acid in transgenic tomato plants increases the risk of hydraulic failure

Climate change threatens food security, and plant science researchers have investigated methods of sustaining crop yield under drought. One approach has been to overproduce abscisic acid (ABA) to enhance water use efficiency. However, the concomitant effects of ABA overproduction on plant vascular system functioning are critical as it influences vulnerability to xylem hydraulic failure. We investigated these effects by comparing physiological and hydraulic responses to water deficit between a tomato (Solanum lycopersicum) wild type control (WT) and a transgenic line overproducing ABA (sp12). Under well-watered conditions, the sp12 line displayed similar growth rate and greater water use efficiency by operating at lower maximum stomatal conductance. X-ray microtomography revealed that sp12 was significantly more vulnerable to xylem embolism, resulting in a reduced hydraulic safety margin. We also observed a significant ontogenic effect on vulnerability to xylem embolism for both WT and sp12. This study demonstrates that the greater water use efficiency in the tomato ABA overproducing line is associated with higher vulnerability of the vascular system to embolism and a higher risk of hydraulic failure. Integrating hydraulic traits into breeding programmes represents a critical step for effectively managing a crop's ability to maintain hydraulic conductivity and productivity under water deficit.

Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding

New types of phenotyping tools generate large amounts of data on many aspects of plant physiology and morphology with high spatial and temporal resolution. These new phenotyping data are potentially useful to improve understanding and prediction of complex traits, like yield, that are characterized by strong environmental context dependencies, i.e., genotype by environment interactions. For an evaluation of the utility of new phenotyping information, we will look at how this information can be incorporated in different classes of genotype-to-phenotype (G2P) models. G2P models predict phenotypic traits as functions of genotypic and environmental inputs. In the last decade, access to high-density single nucleotide polymorphism markers (SNPs) and sequence information has boosted the development of a class of G2P models called genomic prediction models that predict phenotypes from genome wide marker profiles. The challenge now is to build G2P models that incorporate simultaneously extensive genomic information alongside with new phenotypic information. Beyond the modification of existing G2P models, new G2P paradigms are required. We present candidate G2P models for the integration of genomic and new phenotyping information and illustrate their use in examples. Special attention will be given to the modelling of genotype by environment interactions. The G2P models provide a framework for model based phenotyping and the evaluation of the utility of phenotyping information in the context of breeding programs.

Plant Phenomics, From Sensors to Knowledge

Major improvements in crop yield are needed to keep pace with population growth and climate change. While plant breeding efforts have greatly benefited from advances in genomics, profiling the crop phenome (i.e., the structure and function of plants) associated with allelic variants and environments remains a major technical bottleneck. Here, we review the conceptual and technical challenges facing plant phenomics. We first discuss how, given plants' high levels of morphological plasticity, crop phenomics presents distinct challenges compared with studies in animals. Next, we present strategies for multi-scale phenomics, and describe how major improvements in imaging, sensor technologies and data analysis are now making high-throughput root, shoot, whole-plant and canopy phenomic studies possible. We then suggest that research in this area is entering a new stage of development, in which phenomic pipelines can help researchers transform large numbers of images and sensor data into knowledge, necessitating novel methods of data handling and modelling. Collectively, these innovations are helping accelerate the selection of the next generation of crops more sustainable and resilient to climate change, and whose benefits promise to scale from physiology to breeding and to deliver real world impact for ongoing global food security efforts.

Dissecting the rootstock control of scion transpiration using model-assisted analyses in grapevine

How rootstocks contribute to the control of scion transpiration under drought is poorly understood. We investigated the role of root characteristics, hydraulic conductance and chemical signals (abscisic acid, ABA) in the response of stomatal conductance (gs) and transpiration (E) to drought in Cabernet Sauvignon (Vitis vinifera) grafted onto drought-sensitive (Vitis riparia) and drought-tolerant (Vitis berlandieri × Vitis rupestris 110R) rootstocks. All combinations showed a concomitant reduction in gs and E, and an increase in xylem sap ABA concentration during the drought cycle. Cabernet Sauvignon grafted onto 110R exhibited higher gs and E under well-watered and moderate water deficit, but all combinations converged as water deficit increased. These results were integrated into three permutations of a whole-plant transpiration model that couples both chemical (i.e., ABA) and hydraulic signals in the modelling of stomatal control. Model comparisons revealed that both hydraulic and chemical signals were important for rootstock-specific stomatal regulation. Moreover, model parameter comparison and sensitivity analysis highlighted two major parameters differentiating the rootstocks: (i) ABA biosynthetic activity and (ii) the hydraulic conductance between the rhizosphere and soil-root interface determined by root system architecture. These differences in root architecture, specifically a higher root length area in 110R, likely explain its higher E and gs observed at low and moderate water deficit.

Loci That Control Nonlinear, Interdependent Responses to Combinations of Drought and Nitrogen Limitation

Crop improvement must accelerate to feed an increasing human population in the face of environmental changes. Including anticipated climatic changes with genetic architecture in breeding programs could better optimize improvement strategies. Combinations of drought and nitrogen limitation already occur world-wide. We therefore analyzed the genetic architecture underlying the response of Zea mays to combinations of water and nitrogen stresses. Recombinant inbreds were subjected to nine combinations of the two stresses using an optimized response surface design, and their growth was measured. Three-dimensional response surfaces were fit globally and to each polymorphic allele to determine which genetic markers were associated with different response surfaces. Three quantitative trait loci that produced nonlinear surfaces were mapped. To better understand the physiology of the response, we developed a model that reproduced the shapes of the surfaces, their most characteristic feature. The model contains two components that each combine the nitrogen and water inputs. The relative weighting of the two components and the inputs is governed by five parameters, and each QTL affects all five parameters.

We estimated the model’s parameter values for the experimental surfaces using a mesh of points that covered the surfaces’ most distinctive regions. Surfaces computed using these values reproduced the experimental surfaces well, as judged by three different criteria at the mesh points. The modeling and shape comparison techniques used here can be extended to other complex, high-dimensional, nonlinear phenotypes. We encourage the application of our findings and methods to experiments that mix crop protection measures, stresses, or both, on elite and landrace germplasm.

The Physiological Basis of Drought Tolerance in Crop Plants: A Scenario-Dependent Probabilistic Approach

Drought tolerance involves mechanisms operating at different spatial and temporal scales, from rapid stomatal closure to maintenance of crop yield. We review how short-term mechanisms are controlled for stabilizing shoot water potential and how long-term processes have been constrained by evolution or breeding to fit into acclimation strategies for specific drought scenarios. These short- or long-term feedback processes participate in trade-offs between carbon accumulation and the risk of deleterious soil water depletion. Corresponding traits and alleles may therefore have positive or negative effects on crop yield depending on drought scenarios. We propose an approach that analyzes the genetic architecture of traits in phenotyping platforms and of yield in tens of field experiments. A combination of modeling and genomic prediction is then used to estimate the comparative interests of combinations of alleles depending on drought scenarios. Hence, drought tolerance is understood probabilistically by estimating the benefit and risk of each combination of alleles.

A 3-D functional-structural grapevine model that couples the dynamics of water transport with leaf gas exchange

Background and Aims

Predicting both plant water status and leaf gas exchange under various environmental conditions is essential for anticipating the effects of climate change on plant growth and productivity. This study developed a functional-structural grapevine model which combines a mechanistic understanding of stomatal function and photosynthesis at the leaf level (i.e. extended Farqhuhar-von Caemmerer-Berry model) and the dynamics of water transport from soil to individual leaves (i.e. Tardieu-Davies model).

Methods

The model included novel features that account for the effects of xylem embolism (fPLC) on leaf hydraulic conductance and residual stomatal conductance (g0), variable root and leaf hydraulic conductance, and the microclimate of individual organs. The model was calibrated with detailed datasets of leaf photosynthesis, leaf water potential, xylem sap abscisic acid (ABA) concentration and hourly whole-plant transpiration observed within a soil drying period, and validated with independent datasets of whole-plant transpiration under both well-watered and water-stressed conditions.

Key Results

The model well captured the effects of radiation, temperature, CO2 and vapour pressure deficit on leaf photosynthesis, transpiration, stomatal conductance and leaf water potential, and correctly reproduced the diurnal pattern and decline of water flux within the soil drying period. In silico analyses revealed that decreases in g0 with increasing fPLC were essential to avoid unrealistic drops in leaf water potential under severe water stress. Additionally, by varying the hydraulic conductance along the pathway (e.g. root and leaves) and changing the sensitivity of stomatal conductance to ABA and leaf water potential, the model can produce different water use behaviours (i.e. iso- and anisohydric).

Conclusions

The robust performance of this model allows for modelling climate effects from individual plants to fields, and for modelling plants with complex, non-homogenous canopies. In addition, the model provides a basis for future modelling efforts aimed at describing the physiology and growth of individual organs in relation to water status.

Stomatal and growth responses to hydraulic and chemical changes induced by progressive soil drying

A better understanding of physiological responses of crops to drought stress is important for ensuring sustained crop productivity under climate change. Here, we studied the effect on 15-day-old maize (Zea mays L.) plants of a 6 d non-lethal period of soil drying [soil water potential (SWP) decreased from -0.20 MPa to -0.81 MPa]. Root growth was initially stimulated during drying (when SWP decreased from -0.31 MPa to -0.38 MPa, compared with -0.29 MPa in well-watered pots), followed by inhibition during Days 5-6 (SWP from -0.63 MPa to -0.81 MPa). Abscisic acid (ABA) in the root began to accumulate as the root water potential declined during Days 2-3. Leaf elongation was inhibited from Day 4 (SWP less than -0.51 MPa), just after leaf ABA content began to increase, but coinciding with a decline in leaf water potential. The stomatal conductance was restricted earlier in the younger leaf (fourth) (on Day 3) than in the older leaf (third). The ethylene content of leaves and roots decreased during drying, but after the respective increase in ABA contents. This work identified critical timing of hydraulic and chemical changes at the onset of soil drying, which can be important in initiating early stomatal and growth responses to drought.