Spatial heterogeneity in stomatal features during leaf elongation: an analysis using Rosa hybrida

A Nonlinear Fitting Method Provides Strong Support for Geometric Series of Stomatal Area in 12 Magnoliaceae Species

Stomatal pore area and density determine the capacity for gas exchange between the leaf interior and the atmosphere. Stomatal area is given by the profile formed by two guard cells, and the cumulative stomatal area characterizes the area of leaf surface occupied by stomata. The areas of all stomata captured in a micrograph are sorted in ascending order to form a sequence, which is referred to as a sequence of stomatal area here. In total, 360 leaves of 12 Magnoliaceae species with 30 leaves for each species were sampled. For each leaf, two 662 μm × 444 μm fields of view (micrographs) of stomata were captured on the right leaf width axis. In each micrograph, the length and width of each stoma were measured, and the area of the stoma was determined using the product of stomatal length and width multiplied by a proportionality coefficient. Stomatal area sequences of Magnoliaceae in the constant field of view were found to follow a geometric series (GS). Prior studies estimated the common ratio of the GS as the mean of the quotients of any two adjacent terms, and estimated the first term as the mean of the first terms (i.e., the smallest stomatal area) represented by the quotient of each term and the estimated common ratio to a power of the order of the term minus 1, which is referred to as Method-1. However, it produced large prediction errors for some stomatal area sequences. In the present study, the nonlinear regression was used to fit the stomatal area sequences using the common ratio and the first term as two model parameters (Method-2). We compared the two methods using the mean absolute percent error (MAPE, ≤5% considered as a good fit) values of the 720 stomatal micrographs from the 12 Magnoliaceae species. The goodness of fit of Method-2 was better than that of Method-1 (52.4% MAPE values were ≤5% for Method-1 and 99.6% for Method-2). There were significant variations in the estimated common ratios, as well as the estimated first terms and the MAPE values across the 12 Magnoliaceae species, but overall, the interspecific differences in the MAPE values were small. We conclude that the GS hypothesis for the stomatal area sequences of the 12 Magnoliaceae species was further strengthened by the new method. This method further provides a valuable approach for the calculation of total stomatal area per unit leaf area.

Rotating Stomata Measurement Based on Anchor-Free Object Detection and Stomata Conductance Calculation

Stomata play an essential role in regulating water and carbon dioxide levels in plant leaves, which is important for photosynthesis. Previous deep learning-based plant stomata detection methods are based on horizontal detection. The detection anchor boxes of deep learning model are horizontal, while the angle of stomata is randomized, so it is not possible to calculate stomata traits directly from the detection anchor boxes. Additional processing of image (e.g., rotating image) is required before detecting stomata and calculating stomata traits. This paper proposes a novel approach, named DeepRSD (deep learning-based rotating stomata detection), for detecting rotating stomata and calculating stomata basic traits at the same time. Simultaneously, the stomata conductance loss function is introduced in the DeepRSD model training, which improves the efficiency of stomata detection and conductance calculation. The experimental results demonstrate that the DeepRSD model reaches 94.3% recognition accuracy for stomata of maize leaf. The proposed method can help researchers conduct large-scale studies on stomata morphology, structure, and stomata conductance models.

Automatic Stomatal Segmentation Based on Delaunay-Rayleigh Frequency Distance

The CO₂ and water vapor exchange between leaf and atmosphere are relevant for plant physiology. This process is done through the stomata. These structures are fundamental in the study of plants since their properties are linked to the evolutionary process of the plant, as well as its environmental and phytohormonal conditions. Stomatal detection is a complex task due to the noise and morphology of the microscopic images. Although in recent years segmentation algorithms have been developed that automate this process, they all use techniques that explore chromatic characteristics. This research explores a unique feature in plants, which corresponds to the stomatal spatial distribution within the leaf structure. Unlike segmentation techniques based on deep learning tools, we emphasize the search for an optimal threshold level, so that a high percentage of stomata can be detected, independent of the size and shape of the stomata. This last feature has not been reported in the literature, except for those results of geometric structure formation in the salt formation and other biological formations.

An Automatic Method for Stomatal Pore Detection and Measurement in Microscope Images of Plant Leaf Based on a Convolutional Neural Network Model

Stomata are microscopic pores on the plant epidermis that regulate the water content and CO2 levels in leaves. Thus, they play an important role in plant growth and development. Currently, most of the common methods for the measurement of pore anatomy parameters involve manual measurement or semi-automatic analysis technology, which makes it difficult to achieve high-throughput and automated processing. This paper presents a method for the automatic segmentation and parameter calculation of stomatal pores in microscope images of plant leaves based on deep convolutional neural networks. The proposed method uses a type of convolutional neural network model (Mask R-CNN (region-based convolutional neural network)) to obtain the contour coordinates of the pore regions in microscope images of leaves. The anatomy parameters of pores are then obtained by ellipse fitting technology, and the quantitative analysis of pore parameters is implemented. Stomatal microscope image datasets for black poplar leaves were obtained using a large depth-of-field microscope observation system, the VHX-2000, from Keyence Corporation. The images used in the training, validation, and test sets were taken randomly from the datasets (562, 188, and 188 images, respectively). After 10-fold cross validation, the 188 test images were found to contain an average of 2278 pores (pore widths smaller than 0.34 μm (1.65 pixels) were considered to be closed stomata), and an average of 2201 pores were detected by our network with a detection accuracy of 96.6%, and the intersection of union (IoU) of the pores was 0.82. The segmentation results of 2201 stomatal pores of black poplar leaves showed that the average measurement accuracies of the (a) pore length, (b) pore width, (c) area, (d) eccentricity, and (e) degree of stomatal opening, with a ratio of width-to-maximum length of a stomatal pore, were (a) 94.66%, (b) 93.54%, (c) 90.73%, (d) 99.09%, and (e) 92.95%, respectively. The proposed stomatal pore detection and measurement method based on the Mask R-CNN can automatically measure the anatomy parameters of pores in plants, thus helping researchers to obtain accurate stomatal pore information for leaves in an efficient and simple way.

Natural Diversity in Stomatal Features of Cultivated and Wild Oryza Species

BACKGROUND

Stomata in rice control a number of physiological processes by regulating gas and water exchange between the atmosphere and plant tissues. The impact of the structural diversity of these micropores on its conductance level is an important area to explore before introducing stomatal traits into any breeding program in order to increase photosynthesis and crop yield. Therefore, an intensive measurement of structural components of stomatal complex (SC) of twenty three Oryza species spanning the primary, secondary and tertiary gene pools of rice has been conducted.

RESULTS

Extensive diversity was found in stomatal number and size in different Oryza species and Oryza complexes. Interestingly, the dynamics of stomatal traits in Oryza family varies differently within different Oryza genetic complexes. Example, the Sativa complex exhibits the greatest diversity in stomatal number, while the Officinalis complex is more diverse for its stomatal size. Combining the structural information with the Oryza phylogeny revealed that speciation has tended towards increasing stomatal density rather than stomatal size in rice family. Thus, the most recent species (i.e. the domesticated rice) eventually has developed smaller yet numerous stomata. Along with this, speciation has also resulted in a steady increase in stomatal conductance (anatomical, gmax) in different Oryza species. These two results unambiguously prove that increasing stomatal number (which results in stomatal size reduction) has increased the stomatal conductance in rice. Correlations of structural traits with the anatomical conductance, leaf carbon isotope discrimination (∆13C) and major leaf morphological and anatomical traits provide strong supports to untangle the ever mysterious dependencies of these traits in rice. The result displayed an expected negative correlation in the number and size of stomata; and positive correlations among the stomatal length, width and area with guard cell length, width on both abaxial and adaxial leaf surfaces. In addition, gmax is found to be positively correlated with stomatal number and guard cell length. The ∆13C values of rice species showed a positive correlation with stomatal number, which suggest an increased water loss with increased stomatal number. Interestingly, in contrast, the ∆13C consistently shows a negative relationship with stomatal and guard cell size, which suggests that the water loss is less when the stomata are larger. Therefore, we hypothesize that increasing stomatal size, instead of numbers, is a better approach for breeding programs in order to minimize the water loss through stomata in rice.

CONCLUSION

Current paper generates useful data on stomatal profile of wild rice that is hitherto unknown for the rice science community. It has been proved here that the speciation has resulted in an increased stomatal number accompanied by size reduction during Oryza's evolutionary course; this has resulted in an increased gmax but reduced water use efficiency. Although may not be the sole driver of water use efficiency in rice, our data suggests that stomata are a potential target for modifying the currently low water use efficiency in domesticated rice. It is proposed that Oryza barthii can be used in traditional breeding programs in enhancing the stomatal size of elite rice cultivars.

Stomatal behavior following mid- or long-term exposure to high relative air humidity: A review

High relative air humidity (RH ≥ 85%) is frequent in controlled environments, and not uncommon in nature. In this review, we examine the high RH effects on plants with a special focus on stomatal characters. All aspects of stomatal physiology are attenuated by elevated RH during leaf expansion (long-term) in C₃ species. These include impaired opening and closing response, as well as weak diel oscillations. Consequently, the high RH-grown plants are not only vulnerable to biotic and abiotic stress, but also undergo a deregulation between CO₂ uptake and water loss. Stomatal behavior of a single leaf is determined by the local microclimate during expansion, and may be different than the remaining leaves of the same plant. No effect of high RH is apparent in C₄ and CAM species, while the same is expected for species with hydropassive stomatal closure. Formation of bigger stomata with larger pores is a universal response to high RH during leaf expansion, whereas the effect on stomatal density appears to be species- and leaf side-specific. Compelling evidence suggests that ABA mediates the high RH-induced stomatal malfunction, as well as the stomatal size increase. Although high RH stimulates leaf ethylene evolution, it remains elusive whether or not this contributes to stomatal malfunction. Most species lose stomatal function following mid-term (4-7 d) exposure to high RH following leaf expansion. Consequently, the regulatory role of ambient humidity on stomatal functionality is not limited to the period of leaf expansion, but holds throughout the leaf life span.

Heterogeneity of Stomatal Pore Area Is Suppressed by Ambient Aerosol in the Homobaric Species, Vicia faba

Stomatal pore area is heterogeneous across leaf surfaces. This has been considered as "patchy stomatal conductance," and may have substantial implications for photosynthetic efficiency. Aerosols have always been important elements of plant environments, but their effects on stomatal control of plant water relations, and stomatal heterogeneity specifically, have not been considered. Here we evaluate the spatial coordination of pore area in the glabrous and homobaric leaves of Vicia faba grown under two aerosol treatments and measured at four levels of VPD. We construct a large dataset (n > 88,000 discrete comparisons) of paired pore areas and distances between the pores. Plants were grown in ambient urban air and in filtered air (FA) to determine the effect of ambient aerosol on stomatal properties. Pore area exhibited spatial organization, as well as considerable variability among closely co-located pores. The difference between pore areas was positively correlated with the distance between the pores, in both aerosol treatments and at all VPDs. However, aerosol deposition reduced both the magnitude of variability between pores and the rate at which this variability increased with pore separation distance. These data support previous conclusions that deposition of hygroscopic aerosol may create a thin aqueous film across the leaf surface that connects neighboring stomata to each other and to the leaf interior. Aerosol impacts on stomatal heterogeneity and gas exchange are not adequately considered in current assessments of stomatal control.

The Response of Water Dynamics to Long-Term High Vapor Pressure Deficit Is Mediated by Anatomical Adaptations in Plants

Vapor pressure deficit (VPD) is the driver of water movement in plants. However, little is known about how anatomical adaptations determine the acclimation of plant water dynamics to elevated VPD, especially at the whole plant level. Here, we examined the responses of transpiration, stomatal conductance (g_s), hydraulic partitioning, and anatomical traits in two tomato cultivars (Jinpeng and Zhongza) to long-term high (2.2-2.6 kPa) and low (1.1-1.5 kPa) VPD. Compared to plants growing under low VPD, no variation in g_s was found for Jinpeng under high VPD conditions; however, high VPD induced an increase in whole plant hydraulic conductance (K_plant), which was responsible for the maintenance of high transpiration. In contrast, transpiration was not influenced by high VPD in Zhongza, which was primarily attributed to a coordinated decline in g_s and K_plant. The changes in g_s were closely related to stomatal density and size. Furthermore, high VPD altered hydraulic partitioning among the leaf, stem, and root for both cultivars via adjustments in anatomy. The increase in lumen area of vessels in veins and large roots in Jinpeng under high VPD conditions improved water transport efficiency in the leaf and root, thus resulting in a high K_plant. However, the decreased K_plant for Zhongza under high VPD was the result of a decline of water transport efficiency in the leaf that was caused by a reduction in vein density. Overall, we concluded that the tradeoff in anatomical acclimations among plant tissues results in different water relations in plants under high VPD conditions.

The Role of Proteases in Determining Stomatal Development and Tuning Pore Aperture: A Review

Plant proteases, the proteolytic enzymes that catalyze protein breakdown and recycling, play an essential role in a variety of biological processes including stomatal development and distribution, as well as, systemic stress responses. In this review, we summarize what is known about the participation of proteases in both stomatal organogenesis and on the stomatal pore aperture tuning, with particular emphasis on their involvement in numerous signaling pathways triggered by abiotic and biotic stressors. There is a compelling body of evidence demonstrating that several proteases are directly or indirectly implicated in the process of stomatal development, affecting stomatal index, density, spacing, as well as, size. In addition, proteases are reported to be involved in a transient adjustment of stomatal aperture, thus orchestrating gas exchange. Consequently, the proteases-mediated regulation of stomatal movements considerably affects plants' ability to cope not only with abiotic stressors, but also to perceive and respond to biotic stimuli. Even though the determining role of proteases on stomatal development and functioning is just beginning to unfold, our understanding of the underlying processes and cellular mechanisms still remains far from being completed.

Quantitative Estimation of Leaf Heat Transfer Coefficients by Active Thermography at Varying Boundary Layer Conditions

Quantifying heat and mass exchanges processes of plant leaves is crucial for detailed understanding of dynamic plant-environment interactions. The two main components of these processes, convective heat transfer, and transpiration, are inevitably coupled as both processes are restricted by the leaf boundary layer. To measure leaf heat capacity and leaf heat transfer coefficient, we thoroughly tested and applied an active thermography method that uses a transient heat pulse to compute τ, the time constant of leaf cooling after release of the pulse. We validated our approach in the laboratory on intact leaves of spring barley (Hordeum vulgare) and common bean (Phaseolus vulgaris), and measured τ-changes at different boundary layer conditions.By modeling the leaf heat transfer coefficient with dimensionless numbers, we could demonstrate that τ improves our ability to close the energy budget of plant leaves and that modeling of transpiration requires considerations of convection. Applying our approach to thermal images we obtained spatio-temporal maps of τ, providing observations of local differences in thermal responsiveness of leaf surfaces. We propose that active thermography is an informative methodology to measure leaf heat transfer and derive spatial maps of thermal responsiveness of leaves contributing to improve models of leaf heat transfer processes.

Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data

Leaf attribute estimation is crucial for understanding photosynthesis, respiration, transpiration, and carbon and nutrient cycling in vegetation and evaluating the biological parameters of plants or forests. Terrestrial laser scanning (TLS) has the capability to provide detailed characterisations of individual trees at both the branch and leaf scales and to extract accurate structural parameters of stems and crowns. In this paper, we developed a computer graphic-based 3D point cloud segmentation approach for accurately and efficiently detecting tree leaves and their morphological features (i.e., leaf area and leaf angle distributions (leaf azimuthal angle and leaf inclination angle)) from single leaves. To this end, we adopted a sphere neighbourhood model with an adaptive radius to extract the central area points of individual leaves with different morphological structures and complex spatial distributions; meanwhile, four auxiliary criteria were defined to ensure the accuracy of the extracted central area points of individual leaf surfaces. Then, the density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to cluster the central area points of leaves and to obtain the centre point corresponding to each leaf surface. We also achieved segmentation of individual leaf blades using an advanced 3D watershed algorithm based on the extracted centre point of each leaf surface and two morphology-related parameters. Finally, the leaf attributes (leaf area and leaf angle distributions) were calculated and assessed by analysing the segmented single-leaf point cloud. To validate the final results, the actual leaf area, leaf inclination and azimuthal angle data of designated leaves on the experimental trees were manually measured during field activities. In addition, a sensitivity analysis investigated the effect of the parameters in our segmentation algorithm. The results demonstrated that the segmentation accuracy of Ehretia macrophylla (94.0%) was higher than that of crape myrtle (90.6%) and Fatsia japonica (88.8%). The segmentation accuracy of Fatsia japonica was the lowest of the three experimental trees. In addition, the single-leaf area estimation accuracy for Ehretia macrophylla (95.39%) was still the highest among the three experimental trees, and the single-leaf area estimation accuracy for crape myrtle (91.92%) was lower than that for Ehretia macrophylla (95.39%) and Fatsia japonica (92.48%). Third, the method proposed in this paper provided accurate leaf inclination and azimuthal angles for the three experimental trees (Ehretia macrophylla: leaf inclination angle: R 2 = 0.908, RMSE = 6.806° and leaf azimuth angle: R 2 = 0.981, RMSE = 7.680°; crape myrtle: leaf inclination angle: R 2 = 0.901, RMSE = 8.365° and leaf azimuth angle: R 2 = 0.938, RMSE = 7.573°; Fatsia japonica: leaf inclination angle: R 2 = 0.849, RMSE = 6.158° and leaf azimuth angle: R 2 = 0.947, RMSE = 3.946°). The results indicate that the proposed method is effective and operational for providing accurate, detailed information on single leaves and vegetation structure from scanned data. This capability facilitates improvements in applications such as the estimation of leaf area, leaf angle distribution and biomass.

Temperature Variation under Continuous Light Restores Tomato Leaf Photosynthesis and Maintains the Diurnal Pattern in Stomatal Conductance

The response of tomato plants (Solanum lycopersicum L. cv. Aromata) to continuous light (CL) in relation to photosynthesis, abscisic acid (ABA) and reactive oxygen species (ROS) was investigated to improve the understanding of the development and/or alleviation of CL-induced leaf injury in constant and diurnal temperature fluctuations with similar daily light integral and daily mean temperature. The plants were grown in three photoperiodic treatments for 15 days; One treatment with a 16/8 h light/dark period and a light/dark temperature of 27/17°C (Control), two CL treatments with 24 h photoperiods, one with a constant temperature of 24°C (CLCT) and the other one with variable temperature of 27/17°C for 16/8 ho, respectively (CLVT). A diurnal pattern of stomatal conductance (gs ) and [ABA] was observed in the plants grown in the control and CLVT conditions, while the plants in CLCT conditions experienced a significant decrease in stomatal conductance aligned with an increase in ABA. The net photosynthesis (A) was significantly reduced in CLCT, aligned with a significant decrease in the maximum rate of Rubisco carboxylation (Vcmax), the maximum rate of electron transport (Jmax) and mesophyll diffusion conductance to CO2 (gm) in comparison to the control and CLVT. An increased production of H2O2 and O2•- linked with increased activities of antioxidative enzymes was seen in both CL treatments, but despite of this, leaf injuries were only observed in the CLCT treatment. The results suggest that the diurnal temperature fluctuations alleviated the CL injury symptoms, probably because the diurnal cycles of cellular mechanisms were maintained. The ROS were shown not to be directly involved in CL-induced leaf injury, since both ROS production and scavenging was highest in CLVT without leaf chlorotic symptoms.

Size matters: point pattern analysis biases the estimation of spatial properties of stomata distribution

Stomata distribution is an example of biological patterning. Formal methods used to study stomata patterning are generally based on point-pattern analysis, which assumes that stomata are points and ignores the constraints imposed by size on the placement of neighbors. The inclusion of size in the analysis requires the use of a null model based on finite-size object geometry. In this study, we compare the results obtained by analyzing samples from several species using point and disc null models. The results show that depending on the null model used, there was a 20% reduction in the number of samples classified as uniform; these results suggest that stomata patterning is not as general as currently reported. Some samples changed drastically from being classified as uniform to being classified as clustered. In samples of Arabidopsis thaliana, only the disc model identified clustering at high densities of stomata. This reinforces the importance of selecting an appropriate null model to avoid incorrect inferences about underlying biological mechanisms. Based on the results gathered here, we encourage researchers to abandon point-pattern analysis when studying stomata patterning; more realistic conclusions can be drawn from finite-size object analysis.

Improving stomatal functioning at elevated growth air humidity: A review

Plants grown at high relative air humidity (RH≥85%) are prone to lethal wilting upon transfer to conditions of high evaporative demand. The reduced survival of these plants is related to (i) increased cuticular permeability, (ii) changed anatomical features (i.e., longer pore length and higher stomatal density), (iii) reduced rehydration ability, (iv) impaired water potential sensitivity to leaf dehydration and, most importantly, (v) compromised stomatal closing ability. This review presents a critical analysis of the strategies which stimulate stomatal functioning during plant development at high RH. These include (a) breeding for tolerant cultivars, (b) interventions with respect to the belowground environment (i.e., water deficit, increased salinity, nutrient culture and grafting) as well as (c) manipulation of the aerial environment [i.e., increased proportion of blue light, increased air movement, temporal temperature rise, and spraying with abscisic acid (ABA)]. Root hypoxia, mechanical disturbance, as well as spraying with compounds mimicking ABA, lessening its inactivation or stimulating its within-leaf redistribution are also expected to improve stomatal functioning of leaves expanded in humid air. Available evidence leaves little doubt that genotypic and phenotypic differences in stomatal functioning following cultivation at high RH are realized through the intermediacy of ABA.

Gene expression and physiological responses associated to stomatal functioning in Rosa×hybrida grown at high relative air humidity

High relative air humidity (RH≥85%) during growth disturbs stomatal functioning, resulting in excessive water loss in conditions of high evaporative demand. We investigated the expression of nine abscisic acid (ABA)-related genes (involved in ABA biosynthesis, oxidation and conjugation) and two non-ABA related genes (involved in the water stress response) aiming to better understand the mechanisms underlying contrasting stomatal functioning in plants grown at high RH. Four rose genotypes with contrasting sensitivity to high RH (one sensitive, one tolerant and two intermediate) were grown at moderate (62±3%) or high (89±4%) RH. The sensitive genotype grown at high RH showed a significantly higher stomatal conductance (g_s) and water loss in response to closing stimuli as compared to the other genotypes. Moreover, high RH reduced the leaf ABA concentration and its metabolites to a greater extent in the sensitive genotype as compared to the tolerant one. The large majority of the studied genes had a relevant role on stomatal functioning (NCED1, UGT75B2, BG2, OST1, ABF3 and Rh-APX) while two others showed a minor contribution (CYP707A3 and BG1) and AAO3, CYP707A1 and DREB1B did not contribute to the tolerance trait. These results show that multiple genes form a highly complex regulatory network acting together towards the genotypic tolerance to high RH.