A Novel Image-Based Screening Method to Study Water-Deficit Response and Recovery of Barley Populations Using Canopy Dynamics Phenotyping and Simple Metabolite Profiling

Abstract

Plant phenotyping platforms offer automated, fast scoring of traits that simplify the selection of varieties that are more competitive under stress conditions. However, indoor phenotyping methods are frequently based on the analysis of plant growth in individual pots. We present a reproducible indoor phenotyping method for screening young barley populations under water stress conditions and after subsequent rewatering. The method is based on a simple read-out of data using RGB imaging, projected canopy height, as a useful feature for indirectly following the kinetics of growth and water loss in a population of barley. A total of 47 variables including 15 traits and 32 biochemical metabolites measured (morphometric parameters, chlorophyll fluorescence imaging, quantification of stress-related metabolites; amino acids and polyamines, and enzymatic activities) were used to validate the method. The study allowed the identification of metabolites related to water stress response and recovery. Specifically, we found that cadaverine (Cad), 1,3-aminopropane (DAP), tryptamine (Tryp), and tyramine (Tyra) were the major contributors to the water stress response, whereas Cad, DAP, and Tyra, but not Tryp, remained at higher levels in the stressed plants even after rewatering. In this work, we designed, optimized and validated a non-invasive image-based method for automated screening of potential water stress tolerance genotypes in barley populations. We demonstrated the applicability of the method using transgenic barley lines with different sensitivity to drought stress showing that combining canopy height and the metabolite profile we can discriminate tolerant from sensitive genotypes. We showed that the projected canopy height a sensitive trait that truly reflects other invasively studied morphological, physiological, and metabolic traits and that our presented methodological setup can be easily applicable for large-scale screenings in low-cost systems equipped with a simple RGB camera. We believe that our approach will contribute to accelerate the study and understanding of the plant water stress response and recovery capacity in crops, such as barley.

Keywords: Hordeum vulgare; amino acids; antioxidative enzymes; blue (RGB) imaging; canopy height; fluorescence; green; indoor phenotyping; polyamines; red.

Figure 1

Scheme of the protocol used for non-invasive phenotyping of barley (Hordeum vulgare) seedlings growing under water stress conditions. (A) Barley seeds were germinated on filter paper and 50 seedlings of similar radicle size were transplanted into soil in standardized PlantScreen™ measuring trays. (B) The trays were transferred to an XYZ PlantScreen™ chamber with a conveyor system for automatic image acquisition. (C) The canopy height was analyzed using an in-house software routine implemented in MatLab R2015, and the data were evaluated by multivariate statistical analyses using Phyton version 3.6.5 and R version 3.5.1.

Figure 2

Analysis of the reproducibility of canopy height estimation in barley (Hordeum vulgare) seedlings from two independent experiments. (A) The reproducibility of projected canopy height dynamics (in pixels) in barley seedlings (n = 100) grown under control conditions in December 2017 and July 2018. (B) The correlation between canopy height and fresh aerial biomass (g) (n = 5) determined for replicates measured at day 16 and day 19 in barley seedlings from the two independent experiments. The regression curve and significance calculated from three independent trays is shown. ***P ≤ 0.001.

Figure 3

Dynamics of soil moisture and projected canopy height in barley seedlings growing under water stress conditions with subsequent rewatering. (A) Changes in substrate water content (%) of non-stressed (W, continuous lines) and stressed (D, discontinuous lines) barley seedlings (n = 50) from three independent trays (Barley 1, 2, and 3) grown for 13 days under water deficit conditions (with the endpoint at day 16) and subsequently rewatered for 4 days (with the endpoint at day 19). The watering regime consisted in an initial 100% field capacity (FC) after sowing and subsequent constant 80% FC for W variants, and irrigation interruption from day 3 to day 16 for the D variants and posterior rewatering for 4 days. Blue arrows represent the watering regime and red arrow the stop of the irrigation moment in the D variant. (B) Changes in projected canopy height (in pixels) and (C) side view images of the D and W variants from the three independent replicates along the experiment. Asterisks indicate the significance level relative to the control variant after Kruskal-Wallis test. *P≤ 0.05.

Figure 4

Linear curve of the projected canopy height and the extracted traits. (A) The average canopy height, regression curve and significance calculated from three independent trays (with 50 plants each) growing under water deficit conditions for 13 days (with the endpoint at day 16) and with subsequent rewatering for 4 days (with the endpoint at day 19). (B) Max is the maximum and Min the minimum canopy height reached by the stressed plants from replicate 1 or 2 (n = 50) under water deficit conditions, and the slope of the linear model curve is shown. (C) MaxR is the maximum canopy height from replicate 1 or 2 (n = 50) attained after 4 days of rewatering, and the slope of the line (SlopeR) is also shown in the equation.

Figure 5

Variation in chlorophyll parameters in barley (Hordeum vulgare) seedlings grown under water stress conditions and after subsequent rewatering. (A) Imaging of chlorophyll fluorescence (Φ_Po and Φ_PSII) in barley seedlings under well-water, water stress, and rewatering. Stressed and non-stressed plants labeled as D (left) and W (right), respectively. (B) Chlorophyll fluorescence parameters from three independent trays (Barley 1, 2, and 3) (n = 50) and the average values. D and W variants are represented by discontinuous and continuous lines, respectively. Statistical analyses were performed via ANOVA. Asterisks indicate the significance level relative to the control variant; *P≤ 0.05.

Figure 6

Developmental stages of barley seedlings (Hordeum vulgare) under water stress and after subsequent rewatering. Developmental stages of leaves in stressed (D) and non-stressed (W) plants from two independent trays (1 or 2) at the end of the water stress period (n = 8) (Left panel) and after rewatering (n = 5) (Right panel).

Figure 7

Morphometric and physiological changes in barley (Hordeum vulgare) seedlings under water stress conditions and after subsequent rewatering. (A) Aerial biomass (FW, g), (B) leaf length (cm) and (C) width (cm) of the last fully expanded (FE) leaf, (D) the ratio between length and width, (E) the relative water content (%), (F) the index of the chlorophyll content, and the activity of the antioxidative enzymes (G) guaiacol peroxidase (POX, µmol s_–1 mg_–1 protein), (H) catalase (CAT, mmol s_–1 mg_–1 protein) and (I) ascorbate peroxidase (APX, µmol s_–1 mg_–1 protein), in stressed (D, color bars) and non-stressed (W, black bars) barley seedlings from two independent trays at the end of the water stress period (n = 8) and after subsequent rewatering (n = 5). Three independent pools containing five plants each were used for the quantification of the antioxidant enzyme activity. Different letters mean significant differences according to Tukey HSD test after ANOVA.

Figure 8

Metabolic profiles of barley (Hordeum vulgare) seedlings under water deficit and after subsequent rewatering. Fold changes (presented as log₂ ratio) in the content (pmol mg^-1 DW) of free polyamines (PAs) and amino acids (AAs) between stressed (D) and non-stressed (W) barley seedlings (three independent pools containing five plants from two independent trays, n = 6) at the end of the stress period (red bars) and after subsequent rewatering (gray bars).

Figure 9

Multivariate statistical analyses of the traits in barley seedlings related to the water stress response and subsequent rewatering. (A) Principal component (PC) analysis (B) contribution of the loadings to each PC (Dim) and (C) a correlation matrix of 47 variables, including 15 traits and 32 biochemical metabolites obtained from different biological replicates of two independent trays with barley seedlings at the end of the water stress period and after subsequent rewatering.

Figure 10

Projected canopy height in barley seedlings from different transgenic lines growing under water stress conditions with subsequent rewatering. Changes in projected canopy height (in pixels) and side view images of the D (left) and W (right) variants of three transgenic lines with silencing transgene A (transgenic lines 1, 2, and 3) and wt during a water stress period and subsequent rewatering.

Figure 11

Multivariate statistical analyses of the traits in barley seedlings from different transgenic lines related to the water stress response and subsequent rewatering. Principal component (PC = Dim) analysis at the end of the water stress period (A) and after subsequent rewatering (B).