Characteristics and correlations of leaf stomata in different Aleurites montana provenances

Investigation of a Perspective Urban Tree Species, Ginkgo biloba L., by Scientific Analysis of Historical Old Specimens

In this study, we examined over 200-year-old Ginkgo biloba L. specimens under different environmental conditions. The overall aim was to explore which factors influence their vitality and general fitness in urban environments and thus their ability to tolerate stressful habitats. In order to determine this, we used a number of different methods, including histological examinations (stomatal density and size) and physiological measurements (peroxidase enzyme activity), as well as assessing the air pollution tolerance index (APTI). The investigation of the genetic relationships between individuals was performed using flow cytometry and miRNA marker methods. The genetic tests revealed that all individuals are diploid, whereas the lus-miR168 and lus-miR408 markers indicated a kinship relation between them. These results show that the effect of different habitat characteristics can be detected through morphological and physiological responses, thus indicating relatively higher stress values for all studied individuals. A significant correlation can be found between the level of adaptability and the relatedness of the examined individuals. These results suggest that Ginkgo biloba L. is well adapted to an environment with increased stress factors and therefore suitable for use in urban areas.

Measuring stomatal and guard cell metrics for plant physiology and growth using StoManager1

Automated guard cell detection and measurement are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Most current methods for measuring guard cells and stomata are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing geometrical, mathematical algorithms, and convolutional neural networks to automatically detect, count, and measure over 30 guard cell and stomatal metrics, including guard cell and stomatal area, length, width, stomatal aperture area/guard cell area, orientation, stomatal evenness, divergence, and aggregation index. Combined with leaf functional traits, some of these StoManager1-measured guard cell and stomatal metrics explained 90% and 82% of tree biomass and intrinsic water use efficiency (iWUE) variances in hardwoods, making them substantial factors in leaf physiology and tree growth. StoManager1 demonstrated exceptional precision and recall (mAP@0.5 over 0.96), effectively capturing diverse stomatal properties across over 100 species. StoManager1 facilitates the automation of measuring leaf stomatal and guard cells, enabling broader exploration of stomatal control in plant growth and adaptation to environmental stress and climate change. This has implications for global gross primary productivity (GPP) modeling and estimation, as integrating stomatal metrics can enhance predictions of plant growth and resource usage worldwide. Easily accessible open-source code and standalone Windows executable applications are available on a GitHub repository (https://github.com/JiaxinWang123/StoManager1) and Zenodo (https://doi.org/10.5281/zenodo.7686022).

Photosynthetic Plasticity and Stomata Adjustment in Chromosome Segment Substitution Lines of Rice Cultivar KDML105 under Drought Stress

The impact of increasing drought periods on crop yields as a result of global climate change is a major concern in modern agriculture. Thus, a greater understanding of crop physiological responses under drought stress can guide breeders to develop new cultivars with enhanced drought tolerance. In this study, selected chromosome segment substitution lines of KDML105 (KDML105-CSSL) were grown in the Plant Phenomics Center of Kasetsart University in Thailand under well-watered and drought-stressed conditions. Physiological traits were measured by observing gas exchange dynamics and using a high-throughput phenotyping platform. Furthermore, because of its impact on plant internal gas and water regulation, stomatal morphological trait variation was recorded. The results show that KDML105-CSS lines exhibited plasticity responses to enhance water-use efficiency which increased by 3.62%. Moreover, photosynthesis, stomatal conductance and transpiration decreased by approximately 40% and plant height was reduced by 17.69%. Stomatal density tended to decrease and was negatively correlated with stomatal size, and stomata on different sides of the leaves responded differently under drought stress. Under drought stress, top-performing KDML105-CSS lines with high net photosynthesis had shorter plant height and improved IWUE, as influenced by an increase in stomatal density on the upper leaf side and a decrease on the lower leaf side.

Contrasting responses to soil and water salinity in stomata and canopy traits produced convergence of water-use in tomatoes (Solanum esculentum) and okra (Abelmoschus esculentus): application to water management

BACKGROUND

Salinity constrains agricultural sustainability and crops differ in their response. We tested the hypothesis that contrasting responses in canopy and stomatal traits to salinity will cause convergence of water-use in okra and tomato.

RESULTS

Stomata were found almost exclusively (>90%) on the lower leaf surface of tomato, but okra produced ~30% of stomata on the upper leaf surface. While salinity reduced the magnitudes of canopy and stomata traits in tomato, stomata traits were either unaffected or enhanced in okra. Salinity reduced the rates and duration of stomatal conductance (g_s ) in both crops, more severely in tomato, in which g_s was restricted to early mornings in contrast to its bell-shape trend in okra. The superiority of okra in its stomata traits was compensated by the larger plant canopies in tomato, resulting in both daytime canopy transpiration and total plant water-use within 17% and 28%, respectively, of each other for the two crops. A tight stomatal control of transpiration that minimised use of water and its uptake from the soil conferred a superior salinity tolerance on tomato over okra. In both crops, stomata density (D) was inversely correlated with stomata area (A), while water-use was positively correlated with plant leaf area, in addition to D and A in tomato; g_s was also correlated with stomata area index in tomato.

CONCLUSION

Differences in water-use for both crops were relatively narrow, despite the several-fold differences in their canopy and stomata traits. Under saline conditions, irrigation intervals should be long for tomato but short for okra. © 2021 Society of Chemical Industry.

From leaves to roots: Biophysical models of transport of substances in plants

The transport processes of substances in various plant tissues are extremely diverse. However, models aimed at elucidating the mechanisms of such processes are almost absent in the literature. A unified view of all these transport processes is necessary, considering the laws of statistical physics and thermodynamics. A model of active ion transport was constructed based on the laws of statistical physics. Using this model, we traced the entire pathway of substances and energy in a plant. The pathway included aspects of the production of energy in the process of photosynthesis, consumption of energy to obtain nutrients from the soil, transport of such substances to the main organelles of all types of plant cells, the rise of water with dissolved substances along the trunk to the leaves, and the evaporation of water, accompanied by a change in the percentage of isotopes caused by different rates of evaporation. Models of ion transport in the chloroplasts and mitochondria of plant cells have been constructed. A generalized model comprising plant cells and their vacuoles was analyzed. A model of the transport of substances in the roots of plants was also developed. Based on this model, the problem of transport of substances in tall trees has been considered. The calculated concentrations of ions in the vacuoles of cells and resting potentials agreed well with the experimental data.

Stomatal size and density trade-off varies with leaf phenology and species shade tolerance in a South Asian moist tropical forest

The density and guard cell length of stomata regulate the physiological processes in plants. Yet, the variation of stomatal characteristics among different functional groups of trees is not been well understood. Particularly, a comprehensive understanding of stomatal behaviour in Bangladeshi moist forest trees is lacking. The study investigated how abaxial stomatal density (SD) and guard cell length (GCL) vary among tree functional types and leaf phenological groups in a moist tropical forest of Bangladesh. Cluster dendrogram revealed three groups of species based on SD and GCL. The independent sample t -test showed that there was a significant difference in SD between evergreen and deciduous tree species (t =4.18, P <0.001) but no significant difference in GCL between the two phenological groups. ANOVA revealed no significant difference in SD among the light demanding, intermediate shade tolerant and shade tolerant species (F =0.76, P =0.47). However, GCL significantly differed among the three functional groups (F =3.3, P <0.05). Maximum theoretical stomatal conductance (g max ) varied between evergreen and deciduous species but did not vary with species shade tolerance. In general, there was a significant trade-off between SD and GCL. However, the inverse relationship was stronger in deciduous and shade tolerant species than in evergreen and shade intolerant species. Leaf dry matter content was positively related with SD and negatively related with GCL. Specific leaf area and leaf thickness were not related to the stomatal traits. Our analyses suggest that leaf phenology and species shade tolerance need to be considered while estimating gas exchange through the stomata in tropical moist forests.

Variation of phenotypic and physiological traits of Robinia pseudoacacia L. from 20 provenances

To select elite Robinia pseudoacacia L. germplasm resources for production, 13 phenotypes and three physiological indicators of 214 seedlings from 20 provenances were systematically evaluated and analyzed. The leaf phenotypic and physiological coefficients of variation among the genotypes ranged from 3.741% to 19.599% and from 8.260% to 42.363%, respectively. The Kentucky provenance had the largest coefficient of variation (18.541%). The average differentiation coefficients between and within provenances were 34.161% and 38.756%, respectively. These close percentages showed that R. pseudoacacia presented high genetic variation among and within provenances, which can be useful for assisted migration and breeding programs. Furthermore, based on the results of correlations, principal component analysis and cluster analysis, breeding improvements targeting R. pseudoacacia’s ornamental value, food value, and stress resistance of were performed. Forty and 30 excellent individuals, accounting for 18.692% and 14.019%, respectively, of the total resources. They were ultimately screened, after comprehensively taking into considering leaf phenotypic traits including compound leaf length, leaflet number and leaflet area and physiological characteristics including proline and soluble protein contents. These selected individuals could provide a base material for improved variety conservation and selection.

Estimating aboveground net primary productivity of reforested trees in an urban landscape using biophysical variables and remotely sensed data

Recently, urban reforestation programs have emerged as potential carbon sinks and climate mitigates in urban landscapes. Thus, spatially explicit information on net primary productivity (NPP) of reforested trees in urban environments is central to understanding the value of reforestation initiatives in the global carbon budget and climate regulation potential. To date, numerous studies have mainly focused on natural and commercial forests NPP at a regional scale based on coarse spatial resolution remotely sensed data. Generally, local scale NPP studies based on fine spatial resolution data are limited. Therefore, this study sought to estimate aboveground NPP of an urban reforested landscape using biophysical and Sentinel-2 Multispectral Imager data derived variables. Using the MOD17 model, results showed that mean NPP ranged between 6.24 Mg C ha^-1 with high coefficient of determination (R²: 0.92) and low RMSE (0.82 Mg ha^-1) across all reforested trees within the study area. Results also showed a considerable variation in NPP among the reforested trees, with deciduous Acacia and Dalbergia obovate species showing the highest NPP (7.62 Mg C ha^-1 and 7.58 Mg C ha^-1, respectively), while the evergreen Syzygium cordatum and shrub Artemisia afra had the lowest NPP (4.54 Mg C ha^-1 and 5.26 Mg C ha^-1). Furthermore, the multiple linear regression analysis showed that vegetation specific biophysical variables (i.e. leaf area index, Normalized Difference Vegetation Index and Fraction of Photosynthetically Active Radiation) significantly improved the estimation of reforested aboveground NPP at a fine-scale resolution. These findings demonstrate the effectiveness of biophysical and remotely sensed variables in determining NPP (as carbon sequestration surrogate) at fine-scaled reforested urban landscape. Furthermore, the utility of species biometric measurements and MOD17 model offers unprecedented opportunity for improved local scale reforestation assessment and monitoring schedules.

Optimizing the Experimental Method for Stomata-Profiling Automation of Soybean Leaves Based on Deep Learning

Stomatal observation and automatic stomatal detection are useful analyses of stomata for taxonomic, biological, physiological, and eco-physiological studies. We present a new clearing method for improved microscopic imaging of stomata in soybean followed by automated stomatal detection by deep learning. We tested eight clearing agent formulations based upon different ethanol and sodium hypochlorite (NaOCl) concentrations in order to improve the transparency in leaves. An optimal formulation-a 1:1 (v/v) mixture of 95% ethanol and NaOCl (6-14%)-produced better quality images of soybean stomata. Additionally, we evaluated fixatives and dehydrating agents and selected absolute ethanol for both fixation and dehydration. This is a good substitute for formaldehyde, which is more toxic to handle. Using imaging data from this clearing method, we developed an automatic stomatal detector using deep learning and improved a deep-learning algorithm that automatically analyzes stomata through an object detection model using YOLO. The YOLO deep-learning model successfully recognized stomata with high mAP (~0.99). A web-based interface is provided to apply the model of stomatal detection for any soybean data that makes use of the new clearing protocol.

The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape

The transformation of the natural landscape into an impervious surface due to urbanization has often been considered an important driver of environmental change, affecting essential urban ecological processes and ecosystem services. Continuous forest degradation and deforestation due to urbanization have led to an increase in atmospheric carbon emissions, risks, and impacts associated with climate change within urban landscapes and beyond them. Hence, urban reforestation has become a reliable long-term alternative for carbon sink and climate change mitigation. However, there is an urgent need for spatially accurate and concise quantification of these forest carbon stocks in order to understand and effectively monitor the accumulation and progress on such ecosystem services. Hence, this study sought to examine the prospect of Sentinel-2 spectral data in quantifying carbon stock in a reforested urban landscape using the random forest ensemble. Results show that Sentinel-2 spectral data estimated reforested forest carbon stock to an RMSE between 0.378 and 0.466 t·ha−1 and R2 of 79.82 and 77.96% using calibration and validation datasets. Based on random forest variable selection and backward elimination approaches, the red-edge normalized difference vegetation index, enhanced vegetation index, modified simple ratio index, and normalized difference vegetation index were the best subset of predictor variables of carbon stock. These findings demonstrate the value and prospects of Sentinel-2 spectral data for predicting carbon stock in reforested urban landscapes. This information is critical for adopting informed management policies and plans for optimizing urban reforested landscapes carbon sequestration capacity and improving their climate change mitigation potential.

The Morphological and Anatomical Traits of the Leaf in Representative Vinca Species Observed on Indoor- and Outdoor-Grown Plants

Morphological and anatomical traits of the Vinca leaf were examined using microscopy techniques. Outdoor Vinca minor and V. herbacea plants and greenhouse cultivated V. major and V. major var. variegata plants had interspecific variations. All Vinca species leaves are hypostomatic. However, except for V. minor leaf, few stomata were also present on the upper epidermis. V. minor leaf had the highest stomatal index and V. major had the lowest, while the distribution of trichomes on the upper epidermis was species-specific. Differentiated palisade and spongy parenchyma tissues were present in all Vinca species' leaves. However, V. minor and V. herbacea leaves had a more organized anatomical aspect, compared to V. major and V. major var. variegata leaves. Additionally, as a novelty, the cellular to intercellular space ratio of the Vinca leaf's mesophyll was revealed herein with the help of computational analysis. Lipid droplets of different sizes and aspects were localized in the spongy parenchyma cells. Ultrastructural characteristics of the cuticle and its epicuticular waxes were described for the first time. Moreover, thick layers of cutin seemed to be characteristic of the outdoor plants only. This could be an adaptation to the unpredictable environmental conditions, but nevertheless, it might influence the chemical composition of plants.