This study was conducted to assess particulate matter pollution and the accumulation of airborne toxic metals by studying the foliar deposition pattern in an urban environment. To this end, two commonly growing plants (Senna siamea (Lam.) H.S.Irwin & Barneby and Alstonia scholaris (L.) R.Br.) from the busiest traffic squares of the city (Nehru Chowk) in Bilaspur, India, were selected for detailed study. For this purpose, plant leaf samples of both plant species were collected from pollution-affected areas and a reference site (unpolluted) in the city and examined by scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDS) to estimate the accumulation of PM-bound toxic metals at the leaf surfaces. The results of this study showed that the leaves of both plants accumulate PM in different size ranges. Although both plant leaves showed accumulation of PM from respirable suspended particulate matter (RSPM) to ultra-fine particles (UFPs: < 0.1: less than 100 nm) range along with toxic metals, S. siamea retained a higher level of PM than A. scholaris due to better micro-morphological properties on both leaf surfaces. The size of some PM was found to be smaller than the stoma openings. The EDS study proved the presence of harmful airborne toxic metals (Pb, Cd, Cu, Zr, Al, Co, etc.) in these PMs of ambient air. This indicates that toxic metals can enter the leaves through stomatal openings. The results of this study recommended that both plants can be used as a tool to minimise PM pollution.

Ginkgo biloba L. is a rare dioecious species that is valued for its diverse applications and is cultivated globally. This study aimed to develop a rapid and effective method for determining the sex of a Ginkgo biloba. Green and yellow leaves representing annual growth stages were scanned with a hyperspectral imager, and classification models for RGB images, spectral features, and a fusion of spectral and image features were established. Initially, a ResNet101 model classified the RGB dataset using the proportional scaling-background expansion preprocessing method, achieving an accuracy of 90.27%. Further, machine learning algorithms like support vector machine (SVM), linear discriminant analysis (LDA), and subspace discriminant analysis (SDA) were applied. Optimal results were achieved with SVM and SDA in the green leaf stage and LDA in the yellow leaf stage, with prediction accuracies of 87.35% and 98.85%, respectively. To fully utilize the optimal model, a two-stage Period-Predetermined (PP) method was proposed, and a fusion dataset was built using the spectral and image features. The overall accuracy for the prediction set was as high as 96.30%. This is the first study to establish a standard technique framework for Ginkgo sex classification using hyperspectral imaging, offering an efficient tool for industrial and ecological applications and the potential for classifying other dioecious plants.

TOPLESS/TOPLESS-RELATED (TPL/TPR) proteins belong to the Groucho (Gro)/Tup1 family co-repressors and act as broad co-repressors that modulate multiple phytohormone signalling pathways and various developmental processes in plant. However, TPL/TPR co-repressors so far are poorly understood in the rapeseed, one of the world-wide important oilseed crops. In this study, we comprehensively characterized eighteen TPL/TPR genes into five groups in the rapeseed genome. Members of TPL/TPR1/TPR4 and TPR2/TPR3 had close evolutionary relationship, respectively. All TPL/TPRs had similar expression patterns and encode conserved protein domain. In addition, we demonstrated that BnaA9.TPL interacted with all known plant repression domain (RD) sequences, which were distributed in non-redundant 24,238 (22.6 %) genes and significantly enriched in transcription factors in the rapeseed genome. These transcription factors were largely co-expressed with the TPL/TPR genes and involved in diverse pathway, including phytohormone signal transduction, protein kinases and circadian rhythm. Furthermore, BnaA9.TPL was revealed to regulate apical embryonic fate by interaction with Bna.IAA12 and suppression of PLETHORA1/2. BnaA9.TPL was also identified to regulate leaf morphology by interaction with Bna.AS1 (Asymmetric leaves 1) and suppression of KNOTTED-like homeobox genes and YABBY5. These data not only suggest the rapeseed TPL/TPRs play broad roles in different processes, but also provide useful information to uncover more TPL/TPR-mediated control of plant development in rapeseed.

Abscisic acid (ABA) signaling interacts frequently with auxin signaling when it regulates plant development, affecting multiple physiological processes; however, to the best of our knowledge, their interaction during tomato development has not yet been reported. Here, we found that type 2C protein phosphatase (SlPP2C2) interacts with both flavin monooxygenase FZY, an indole-3-acetic acid (IAA) biosynthetic enzyme, and small auxin upregulated RNA (SAUR) of an IAA signaling protein and regulates their activity, thereby affecting the expression of IAA-responsive genes. The expression level of SlPP2C2 was increased by exogenous ABA, IAA, NaCl, or dehydration treatment of fruits, leaves, and seeds, and it decreased in imbibed seeds. Manipulating SlPP2C2 with overexpression, RNA interference, and CRISPR/Cas9-mediated genome editing resulted in pleiotropic changes, such as morphological changes in leaves, stem trichomes, floral organs and fruits, accompanied by alterations in IAA and ABA levels. Furthermore, the RNA-seq analysis indicated that SlPP2C2 regulates the expression of auxin-/IAA-responsive genes in different tissues of tomato. The results demonstrate that SlPP2C2-mediated ABA signaling regulates the development of both vegetative and reproductive organs via interaction with FZY/SAUR, which integrates the cross-talk of ABA and auxin signals during development and affects the expressions of development-related genes in tomato.

The iconic, palmately compound leaves of Cannabis have attracted significant attention in the past. However, investigations into the genetic basis of leaf shape or its connections to phytochemical composition have yielded inconclusive results. This is partly due to prominent changes in leaflet number within a single plant during development, which has so far prevented the proper use of common morphometric techniques. Here, we present a new method that overcomes the challenge of nonhomologous landmarks in palmate, pinnate, and lobed leaves, using Cannabis as an example. We model corresponding pseudo-landmarks for each leaflet as angle-radius coordinates and model them as a function of leaflet to create continuous polynomial models, bypassing the problems associated with variable number of leaflets between leaves. We analyze 341 leaves from 24 individuals from nine Cannabis accessions. Using 3591 pseudo-landmarks in modeled leaves, we accurately predict accession identity, leaflet number, and relative node number. Intra-leaf modeling offers a rapid, cost-effective means of identifying Cannabis accessions, making it a valuable tool for future taxonomic studies, cultivar recognition, and possibly chemical content analysis and sex identification, in addition to permitting the morphometric analysis of leaves in any species with variable numbers of leaflets or lobes.

Leaf morphology plays a crucial role in plant classification and provides a significant model for studying plant diversity while directly impacting photosynthetic efficiency. In the case of melons, leaf shape not only influences production and classification but also represents a key genetic trait that requires further exploration. In this study, we utilized forward genetics to pinpoint a recessive locus, dubbed Cmrl (Round leaf), which is responsible for regulating melon leaf shape. Through bulked segregant analysis sequencing and extensive evaluation of a two-year F2 population, we successfully mapped the Cmrl locus to a 537.07 kb region on chromosome 8 of the melon genome. Subsequent genetic fine-mapping efforts, leveraging a larger F2 population encompassing 1322 plants and incorporating F2:3 phenotypic data, further refined the locus to an 80.27 kb interval housing five candidate genes. Promoter analysis and coding sequence cloning confirmed that one of these candidates, MELO3C019152.2 (Cmppr encoding a pentatricopeptide repeat-containing family protein, Cmppr), stands out as a strong candidate gene for the Cmrl locus. Notably, comparisons of Cmrl expressions across various stages of leaf development and different leaf regions suggest a pivotal role of Cmrl in the morphogenesis of melon leaves.

Landmark-based geometric morphometrics (GM) was used to examine, for the first time, spontaneous hybridization between Alnus incana (L.) Moench and Alnus rohlenae Vít, Douda and Mandák, and to assess inter- and intrapopulation variability in leaf shape, leaf size and venation in natural populations in Serbia (Western Balkans). Two geographically distant (30 km) and two close (1.2 km) populations were selected to examine hybridization. The variability in leaf shapes was assessed by canonical variate analysis and linear discriminant analysis performed on the symmetric component of variation. Covariation between the symmetric component of shape variation and the number of pairs of secondary leaf veins was investigated with partial least squares analysis. Static allometry was examined for the first time in the genus Alnus Mill. A higher proportion of A. incana leaves was classified as A. rohlenae in geographically close populations, which is in accordance with the hypothesis about spontaneous hybridization. No single leaf of A. rohlenae was classified as A. incana, indicating that putative hybrids can only be found in grey alder populations. This study demonstrates that GM is a powerful tool for species delimitation and hybrid detection in the genus Alnus and it can be used for preliminary screening in hybrid zones.

Leaf traits were affected by soil factors and displayed varietal differences in forest. However, few examples have been reported on the Island ecosystems. We comprehensively investigated 9 leaf traits (leaf length, leaf width, leaf area, SLA, leaf fresh weight, leaf C content, leaf N content, leaf K content, leaf C:N ratio) of 54 main subtropical woody species and soil parameters (soil pH, total C content, total N content, total K content, available N content, available P content, available K content and soil moisture) in Neilingding Island, Shenzhen, southern China. Intra-and interspecific variation of leaf traits were measured and their correlations with soil parameters were explored. The interspecific variations of leaf C:N ratio, leaf N content and leaf fresh weight were higher than their intraspecific variations. The intraspecific variation of leaf K content was larger than that of interspecific one, accounting for 80.69% of the total variance. Positive correlations were found among intraspecific coefficients of variations in leaf morphological traits. The correlation analysis between the variation of intraspecific traits and the variation of soil parameters showed that changes in soil factors affected leaf morphology and stoichiometry. The interaction between soil moisture and soil available P content was the key factor on intraspecific variations of leaf traits including leaf area, leaf fresh weight, leaf C and leaf K content. We concluded that leaf traits of plants in the island were tightly related to soil parameters. Soil parameters, especially soil moisture and available P content, affected plant leaf morphology and stoichiometry at the local scale.

D-borneol is a double-loop monoterpene with a wide use in the pharmaceutical, food, and cosmetics industries. Natural D-borneol can be extracted from branches and leaves of D-borneol resource plants. With the widespread use of natural D-borneol, the identification of D-borneol resource plants and the protection of germplasm resources have become the focus of research. In this study, plant leaf morphology, chemical composition, and simple sequence repeat (SSR) molecular marker analysis were used to analyze and cluster 5 species of D-borneol resource plants and their closely related species. It was found that all three analysis methods could distinguish and cluster these D-borneol resource plants to some degree. The result of SSR analysis using capillary electrophoresis was the best, and it could distinguish Mei Pian tree from Yin Xiang as well as Longnao Zhang from An Zhang. The correlation analysis between SSR similarity matrix and leaf morphology analysis and between SSR similarity matrix and chemical composition similarity matrix revealed that they both had significant correlations (P < 0.0001) and the correlation (r = 0.588) between SSR and leaf morphology was a little higher than that (r = 0.519) between SSR and chemical composition. This indicated that the environment had a greater impact on the chemical composition than on leaf morphology. The research findings will offer efficient techniques to cluster natural D-borneol resource plants and establish a theoretical basis for their future development and utilization.

Adaptation to changing conditions is one of the strategies plants may use to survive in the face of climate change. We aimed to determine whether plants\' leaf morphological and physiological traits/gas exchange variables have changed in response to recent, anthropogenic climate change. We grew seedlings from resurrected historic seeds from ex-situ seed banks and paired modern seeds in a common-garden experiment. Species pairs were collected from regions that had undergone differing levels of climate change using an emerging framework-Climate Contrast Resurrection Ecology, allowing us to hypothesise that regions with greater changes in climate (including temperature, precipitation, climate variability and climatic extremes) would be greater trait responses in leaf morphology and physiology over time. Our study found that in regions where there were greater changes in climate, there were greater changes in average leaf area, leaf margin complexity, leaf thickness and leaf intrinsic water use efficiency. Changes in leaf roundness, photosynthetic rate, stomatal density and the leaf economic strategy of our species were not correlated with changes in climate. Our results show that leaves do have the ability to respond to changes in climate, however, there are greater inherited responses in morphological leaf traits than in physiological traits/variables and greater responses to extreme measures of climate than gradual changes in climatic means. It is vital for accurate predictions of species\' responses to impending climate change to ensure that future climate change ecology studies utilise knowledge about the difference in both leaf trait and gas exchange responses and the climate variables that they respond to.