In plants, carbon (C) molecules provide building blocks for biomass production, fuel for energy, and exert signalling roles to shape development and metabolism. Accordingly, plant growth is well correlated with light interception and energy conversion through photosynthesis. Because water deficits close stomata and thus reduce C entry, it has been hypothesised that droughted plants are under C starvation and their growth under C limitation. In this review, these points are questioned by combining literature review with experimental and modelling illustrations in various plant organs and species. First, converging evidence is gathered from the literature that water deficit generally increases C concentration in plant organs. The hypothesis is raised that this could be due to organ expansion (as a major C sink) being affected earlier and more intensively than photosynthesis (C source) and metabolism. How such an increase is likely to interact with C signalling is not known. Hence, the literature is reviewed for possible links between C and stress signalling that could take part in this interaction. Finally, the possible impact of water deficit-induced C accumulation on growth is questioned for various sink organs of several species by combining published as well as new experimental data or data generated using a modelling approach. To this aim, robust correlations between C availability and sink organ growth are reported in the absence of water deficit. Under water deficit, relationships weaken or are modified suggesting release of the influence of C availability on sink organ growth. These results are interpreted as the signature of a transition from source to sink growth limitation under water deficit.

Temperature fluctuates rapidly and affects all developmental and metabolic processes. This often obscures the effects of developmental trends or of other environmental conditions when temperature fluctuates naturally. A method is proposed for modelling temperature-compensated rates, based on the coordination of temperature responses of developmental processes. In a data set comprising 41 experiments in the greenhouse, growth chamber, or the field, the temperature responses in the range of 6–36 °C for different processes were compared in three species, maize, rice, and Arabidopsis thaliana. Germination, cell division, expansive growth rate, leaf initiation, and phenology showed coordinated temperature responses and followed common laws within each species. The activities of 10 enzymes involved in carbon metabolism exhibited monotonous exponential responses across the whole range 10–40 °C. Hence, the temperature dependence of developmental processes is not explained by a simple relationship to central metabolism. Temperature-compensated rates of development were calculated from the equations of response curve, by expressing rates per unit equivalent time at 20 °C. This resulted in stable rates when temperatures fluctuated over a large range (for which classical thermal time was inefficient), and in time courses of leaf development which were common to several experiments with different temperature scenarios.

In crop species, the impact of temperature on plant development is classically modelled using thermal time. We examined whether this method could be used in a non‐crop species, Arabidopsis thaliana, to analyse the response to temperature of leaf initiation rate and of the development of two leaves of the rosette. The results confirmed the large plant‐to‐plant variability in the studied isogenic line of the Columbia ecotype: 100‐fold differences in leaf area among plants sown on the same date were commonly observed at a given date. These differences disappeared in mature leaves, suggesting that they were due to a variability in plant developmental stage. The whole population could therefore be represented by any group of synchronous plants labelled at the two‐leaf stage and followed during their development. Leaf initiation rate, duration of leaf expansion and maximal relative leaf expansion rate varied considerably among experiments performed at different temperatures (from 6 to 26 °C) but they were linearly related to temperature in the range 6–26 °C, with a common x‐intercept of 3 °C. Expressing time in thermal time with a threshold temperature of 3 °C unified the time courses of leaf initiation and of individual leaf development for plants grown at different temperatures and experimental conditions. The two leaves studied (leaf 2 and leaf 6) had a two‐phase development, with an exponential phase followed by a phase with decreasing relative elongation rate. Both phases had constant durations for a given leaf position if expressed in thermal time. Changes in temperature caused changes in both the rate of development and in the expansion rate which mutually compensated such that they had no consequence on leaf area at a given thermal time. The resulting model of leaf development was applied to ten experiments carried out in a glasshouse or in a growth chamber, with plants grown in soil or hydroponically. Because it predicts accurately the stage of development and the relative expansion rate of any leaf of the rosette, this model facilitates precise planning of sampling procedures and the comparison of treatments in growth analyses.

We have followed the expansion of individual pea leaves from initiation to maximum area, over two markedly different periods. During the first one (2/3 of total leaf development time), cell production occurred while cell and leaf expansions were slow. Rapid expansion (95% of total) occurred for a second period lasting 1/3 of total development time, whereas cell division was virtually completed. Water deficits of 15 d were applied during either slow or rapid expansion, and characterized by measurements of soil water potential, stomatal conductance, leaf water potential and xylem [ABA]. Plants which experienced water deficit during the slow expansion period had markedly reduced expansion during the second period (i.e. 1 or 2 weeks after cessation of deficit), while all variables characterizing water status were returned to the level of the control. This ‘after effect’ was accounted for by a reduced cell number per leaf, while individual cell area was not affected. In contrast, water deficit occurring during rapid leaf expansion immediately reduced leaf expansion via cell area, without affecting cell number per leaf. These experiments indicate a role, in the response to water deficits, for events occurring very early in the development of pea leaves, while leaf expansion is too slow to be measured with macroscopic methods. This role would be accounted for by cell production during the first 2/3 of leaf development while cell expansion would account for changes in the area of leaves experiencing a later stress. These results suggest that long-term temporal analysis may be essential in the study of dicot leaf expansion compared to monocot leaves where temporal analysis can be inferred from spatial analysis.

In maize, silks are hundreds of filaments that simultaneously emerge from the ear for collecting pollen over a period of 1–7 days, which largely determines grain number especially under water deficit. Silk growth is a major trait for drought tolerance in maize, but its phenotyping is difficult at throughputs needed for genetic analyses. We have developed a reproducible pipeline that follows ear and silk growths every day for hundreds of plants, based on an ear detection algorithm that drives a robotized camera for obtaining detailed images of ears and silks. We first select, among 12 whole-plant side views, those best suited for detecting ear position. Images are segmented, the stem pixels are labelled and the ear position is identified based on changes in width along the stem. A mobile camera is then automatically positioned in real time at 30 cm from the ear, for a detailed picture in which silks are identified based on texture and colour. This allows analysis of the time course of ear and silk growths of thousands of plants. The pipeline was tested on a panel of 60 maize hybrids in the PHENOARCH phenotyping platform. Over 360 plants, ear position was correctly estimated in 86% of cases, before it could be visually assessed. Silk growth rate, estimated on all plants, decreased with time consistent with literature. The pipeline allowed clear identification of the effects of genotypes and water deficit on the rate and duration of silk growth. The pipeline presented here, which combines computer vision, machine learning and robotics, provides a powerful tool for large-scale genetic analyses of the control of reproductive growth to changes in environmental conditions in a non-invasive and automatized way. It is available as Open Source software in the OpenAlea platform.