Francois Tardieu

Drought‐induced changes in anthesis‐silking interval are related to silk expansion: a spatio‐temporal growth analysis in maize plants subjected to soil water deficit

The growth and emergence of maize silks has a considerable importance in yield determination under drought conditions. Spatial and temporal patterns of the rates of tissue expansion and of cell division were characterized in silks of plants subjected to different soil water potentials. In all cases, silk development consisted of four phases: (1) cell division and tissue expansion occurred together uniformly all along the silk; (2) cell division progressively ceased from tip to base, while expansion remained spatially uniform including during the phase (3) after the cessation of cell division; and (4) as the silk emerged from the husks, expansion ceased in the emerged portion, probably because of direct evaporative demand, while the relative growth rate progressively decreased in the enclosed part. The rates of tissue expansion and cell division were reduced with water deficit, resulting in delayed silk emergence. The duration of cell division was not affected, and in all cases, the end of cell division in the silk coincided with anther dehiscence. The duration of phase 3, between the end of cell division and the arrest of cell growth in silk apex, considerably increased with water deficit. It corresponded to the anthesis-silking interval used by breeders to characterize the response of cultivars to stress.

High-throughput estimation of incident light, light interception and radiation-use efficiency of thousands of plants in a phenotyping platform

Light interception and radiation-use efficiency (RUE) are essential components of plant performance. Their genetic dissections require novel high-throughput phenotyping methods. We have developed a suite of methods to evaluate the spatial distribution of incident light, as experienced by hundreds of plants in a glasshouse, by simulating sunbeam trajectories through glasshouse structures every day of the year; the amount of light intercepted by maize (Zea mays) plants via a functional-structural model using three-dimensional (3D) reconstructions of each plant placed in a virtual scene reproducing the canopy in the glasshouse; and RUE, as the ratio of plant biomass to intercepted light. The spatial variation of direct and diffuse incident light in the glasshouse (up to 24%) was correctly predicted at the single-plant scale. Light interception largely varied between maize lines that differed in leaf angles (nearly stable between experiments) and area (highly variable between experiments). Estimated RUEs varied between maize lines, but were similar in two experiments with contrasting incident light. They closely correlated with measured gas exchanges. The methods proposed here identified reproducible traits that might be used in further field studies, thereby opening up the way for large-scale genetic analyses of the components of plant performance.

Fortune telling: metabolic markers of plant performance

Background In the last decade, metabolomics has emerged as a powerful diagnostic and predictive tool in many branches of science. Researchers in microbes, animal, food, medical and plant science have generated a large number of targeted or non-targeted metabolic profiles by using a vast array of analytical methods (GC–MS, LC–MS, 1H-NMR….). Comprehensive analysis of such profiles using adapted statistical methods and modeling has opened up the possibility of using single or combinations of metabolites as markers. Metabolic markers have been proposed as proxy, diagnostic or predictors of key traits in a range of model species and accurate predictions of disease outbreak frequency, developmental stages, food sensory evaluation and crop yield have been obtained.Aim of review(i) To provide a definition of plant performance and metabolic markers, (ii) to highlight recent key applications involving metabolic markers as tools for monitoring or predicting plant performance, and (iii) to propose a workable and cost-efficient pipeline to generate and use metabolic markers with a special focus on plant breeding.Key messageUsing examples in other models and domains, the review proposes that metabolic markers are tending to complement and possibly replace traditional molecular markers in plant science as efficient estimators of performance.

Do pH changes in the leaf apoplast contribute to rapid inhibition of leaf elongation rate by water stress? Comparison of stress responses induced by polyethylene glycol and down-regulation of root hydraulic conductivity

We have dissected the influences of apoplastic pH and cell turgor on short-term responses of leaf growth to plant water status, by using a combination of a double-barrelled pH-selective microelectrodes and a cell pressure probe. These techniques were used, together with continuous measurements of leaf elongation rate (LER), in the (hidden) elongating zone of the leaves of intact maize plants while exposing roots to various treatments. Polyethylene glycol (PEG) reduced water availability to roots, while acid load and anoxia decreased root hydraulic conductivity. During the first 30 min, acid load and anoxia induced moderate reductions in leaf growth and turgor, with no effect on leaf apoplastic pH. PEG stopped leaf growth, while turgor was only partially reduced. Rapid alkalinization of the apoplast, from pH 4.9 ± 0.3 to pH 5.8 ± 0.2 within 30 min, may have participated to this rapid growth reduction. After 60 min, leaf growth inhibition correlated well with turgor reduction across all treatments, supporting a growth limitation by hydraulics. We conclude that apoplastic alkalinization may transiently impair the control of leaf growth by cell turgor upon abrupt water stress, whereas direct hydraulic control of growth predominates under moderate conditions and after a 30-60 min delay following imposition of water stress.

The growth of vegetative and reproductive structures (leaves and silks) respond similarly to hydraulic cues in maize.

The elongation of styles and stigma (silks) of maize (Zea mays) flowers is rapid (1-3xa0mmxa0h(-1) ), occurs over a short period and plays a pivotal role in reproductive success in adverse environments. Silk elongation rate was measured using displacement transducers in 350 plants of eight genotypes during eight experiments with varying evaporative demand and soil water status. Measured time courses revealed that silk elongation rate closely followed changes in soil water status and evaporative demand, with day-night alternations similar to those in leaves. Day-night alternations were steeper with high than with low plant transpiration rate, manipulated via evaporative demand or by covering part of the leaf area. Half times of changes in silk elongation rate upon changes in evaporative demand or soil water status were 10-30xa0min, similar to those in leaves. The sensitivity of silk elongation rate to xylem water potential was genetically linked to that of leaf elongation rate. Lines greatly differed for these sensitivities. These results are consistent with a common hydraulic control of expansive growth in vegetative and reproductive structures upon changes in environmental conditions via a close connection with the xylem water potential. They have important implications for breeding, modelling and phenotyping.

A robot-assisted imaging pipeline for tracking the growths of maize ear and silks in a high-throughput phenotyping platform

AbstractBackgroundIn maize, silks are hundreds of filaments that simultaneously emerge from the ear for collecting pollen over a period of 1–7xa0days, 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.ResultsWe 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 30xa0cm 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.ConclusionsThe 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.n

Drought affects abortion of reproductive organs by exacerbating developmentally driven processes via expansive growth and hydraulics

Abortion of reproductive organs is a major limiting factor of yield under water deficit, but is also a trait selected for by evolutionary processes. The youngest reproductive organs must be prone to abortion so older organs can finish their development in case of limited resources. Water deficit increases natural abortion via two developmentally driven processes, namely a signal from the first fertilized ovaries and a simultaneous arrest of the expansive growth of all ovaries at a precise stage. In maize (Zea mays) subjected to water deficits typically encountered in dryland agriculture, these developmental mechanisms account for 90% of drought-associated abortion and are irreversible 3 d after silk emergence. Consistently, transcripts and enzyme activities suggest that the molecular events associated with abortion affect expansive growth in silks whereas ovaries maintain a favourable carbon status. Abortion due to carbon starvation is only observed for severe drought scenarios occurring after silking. Both kinetic and genetic evidence indicates that vegetative and reproductive structures share a partly common hydraulic control of expansive growth. Hence, the control of expansive growth of reproductive structures probably has a prominent effect on abortion for mild water deficits occurring at flowering time, while carbon starvation dominates in severe post-flowering drought scenarios.