OBJECTIVE: Five species of cotton (Gossypium) were exposed to 38°C days during early vegetative development. Commercial cotton (Gossypium hirsutum) was contrasted with four wild cotton species (G. australe, G. bickii, G. robinsonii and G. sturtianum) that are endemic to central and northern Australia.
METHODS: Plants were grown at daytime maxima of 30°C or 38°C for 25 d, commencing at the four-leaf stage. Leaf areas and shoot biomass were used to calculate relative rates of growth and specific leaf areas. Leaf gas exchange measurements revealed assimilation and transpiration rates, as well as electron transport rates (ETR) and carboxylation efficiency (CE) in steady-state conditions. Finally, leaf morphological traits (mean leaf area and leaf shape were quantified), along with leaf surface decorations, imaged using scanning electron microscopy.
RESULTS: Shoot morphology was differentially affected by heat, with three of the four wild species growing faster at 38°C than at 30°C, whereas early growth in G. hirsutum was severely inhibited by heat. Areas of individual leaves and leaf numbers both contributed to these contrasting growth responses, with fewer, smaller leaves at 38°C in G. hirsutum. CO2 assimilation and transpiration rates of G. hirsutum were also dramatically reduced by heat. Cultivated cotton failed to achieve evaporative cooling, contrasting with the transpiration-driven cooling in the wild species. Heat substantially reduced ETR and CE in G. hirsutum, with much smaller effects in the wild species. We speculate that leaf shape, as assessed by invaginations of leaf margins, and leaf size contributed to heat dispersal differentially among the five species. Similarly, reflectance of light radiation was also highly distinctive for each species.
CONCLUSIONS: These four wild Australian relatives of cotton have adapted to hot days that are inhibitory to commercial cotton, deploying a range of physiological and structural adaptations to achieve accelerated growth at 38°C.

Host-associated microbiomes are shaped by both their environment and host genetics, and often impact host performance. The scale of host genetic variation important to microbes is largely unknown yet fundamental to the community assembly of host-associated microbiomes, with implications for the eco-evolutionary dynamics of microbes and hosts. Using Ipomoea hederacea, ivyleaf morning glory, we generated matrilines differing in quantitative genetic variation and leaf shape, which is controlled by a single Mendelian locus. We then investigated the relative roles of Mendelian and quantitative genetic variation in structuring the leaf microbiome and how these two sources of genetic variation contributed to microbe heritability. We found that despite large effects of the environment, both Mendelian and quantitative genetic host variation contribute to microbe heritability and that the cumulative small effect genomic differences due to matriline explained as much or more microbial variation than a single large effect Mendelian locus. Furthermore, our results are the first to suggest that leaf shape itself contributes to variation in the abundances of some phyllosphere microbes.IMPORTANCEWe investigated how host genetic variation affects the assembly of Ipomoea hederacea\'s natural microbiome. We found that the genetic architecture of leaf-associated microbiomes involves both quantitative genetic variation and Mendelian traits, with similar contributions to microbe heritability. The existence of Mendelian and quantitative genetic variation for host-associated microbes means that plant evolution at the leaf shape locus or other quantitative genetic loci has the potential to shape microbial abundance and community composition.

OBJECTIVE: Leaf area (A) is a crucial indicator of the photosynthetic capacity of plants. The Montgomery equation (ME), which hypothesizes that A is proportional to the product of leaf length (L) and width (W), is a valid tool for non-destructively measuring A for many broadleaved plants. At present, the methods used to compute L and W for the ME can be broadly divided into two kinds: using computer recognition and measuring manually. However, the potential difference in the prediction accuracy using either method has not been thoroughly examined in previous studies.
METHODS: In the present study, we measured 540 Alangium chinense leaves, 489 Liquidambar formosana leaves and 215 Liriodendron × sinoamericanum leaves, utilizing computer recognition and manual measurement methods to determine L and W. The ME was used to fit the data determined by the two methods, and the goodness of fits were compared. The prediction errors of A were analysed by examining the correlations with two leaf symmetry indices (areal ratio of the left side to the right side, and standardized index for bilateral asymmetry), as well as the leaf shape complexity index (the leaf dissection index).
RESULTS: The results indicate that there is a neglectable difference in the estimation of A between the two methods. This further validates that the ME is an effective method for estimating A in broadleaved tree species, including those with lobes. Additionally, leaf shape complexity significantly influenced the estimation of A.
CONCLUSIONS: These results show that the use of computer recognition and manual measurement in the field are both effective and feasible, although the influence of leaf shape complexity should be considered when applying the ME to estimate A in the future.

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.

The first TALE homeodomain transcription factor gene to be described in plants was maize knotted1 (kn1). Dominant mutations in kn1 disrupt leaf development, with abnormal knots of tissue forming in the leaf blade. kn1 was found to be expressed in the shoot meristem but not in a peripheral region that gives rise to leaves. Furthermore, KN1 and closely related proteins were excluded from initiating and developing leaves. These findings were a prelude to a large body of work wherein TALE homeodomain proteins have been identified as vital regulators of meristem homeostasis and organ development in plants. KN1 homologues are widely represented across land plant taxa. Thus, studying the regulation and mechanistic action of this gene class has allowed investigations into the evolution of diverse plant morphologies. This review will focus on the function of TALE homeodomain transcription factors in leaf development in eudicots. Here, we discuss how TALE homeodomain proteins contribute to a spectrum of leaf forms, from the simple leaves of Arabidopsis thaliana to the compound leaves of Cardamine hirsuta and species beyond the Brassicaceae.

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.

Plant phenotypic characteristics, especially leaf morphology of leaves, are an important indicator for species identification. However, leaf shape can be extraordinarily complex in some species, such as oaks. The great variation in leaf morphology and difficulty of species identification in oaks have attracted the attention of scientists since Charles Darwin. Recent advances in discrimination technology have provided opportunities to understand leaf morphology variation in oaks. Here, we aimed to compare the accuracy and efficiency of species identification in two closely related deciduous oaks by geometric morphometric method (GMM) and deep learning using preliminary identification of simple sequence repeats (nSSRs) as a prior. A total of 538 Asian deciduous oak trees, 16 Q. aliena and 23 Q. dentata populations, were firstly assigned by nSSRs Bayesian clustering analysis to one of the two species or admixture and this grouping served as a priori identification of these trees. Then we analyzed the shapes of 2328 leaves from the 538 trees in terms of 13 characters (landmarks) by GMM. Finally, we trained and classified 2221 leaf-scanned images with Xception architecture using deep learning. The two species can be identified by GMM and deep learning using genetic analysis as a priori. Deep learning is the most cost-efficient method in terms of time-consuming, while GMM can confirm the admixture individuals\' leaf shape. These various methods provide high classification accuracy, highlight the application in plant classification research, and are ready to be applied to other morphology analysis.

Leaf growth initiates in the peripheral region of the meristem at the apex of the stem, eventually forming flat structures. Leaves are pivotal organs in plants, serving as the primary sites for photosynthesis, respiration, and transpiration. Their development is intricately governed by complex regulatory networks. Leaf development encompasses five processes: the leaf primordium initiation, the leaf polarity establishment, leaf size expansion, shaping of leaf, and leaf senescence. The leaf primordia starts from the side of the growth cone at the apex of the stem. Under the precise regulation of a series of genes, the leaf primordia establishes adaxial-abaxial axes, proximal-distal axes and medio-lateral axes polarity, guides the primordia cells to divide and differentiate in a specific direction, and finally develops into leaves of a certain shape and size. Leaf senescence is a kind of programmed cell death that occurs in plants, and as it is the last stage of leaf development. Each of these processes is meticulously coordinated through the intricate interplay among transcriptional regulatory factors, microRNAs, and plant hormones. This review is dedicated to examining the regulatory influences of major regulatory factors and plant hormones on these five developmental aspects of leaves.

Mulberry plants (Morus alba) have leaf shapes, ranging from unlobed to lobed, which are crucial for yield, growth, and adaptability, indicating their ability to adapt to their environment. Competing endogenous RNAs (ceRNAs) constitute a web of RNAs within the organism\'s transcriptional regulatory system, including protein-coding genes (mRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and others. In this study, samples for ceRNA sequencing were categorized into two groups: whole leaves and lobed leaves, each group with three replicates. In addition, we isolated, cloned, and characterized the precursor miRNA (miR156x) from the leaves of M. alba. miR156x precursor had a length of 107 base pairs and a minimum folding free energy of 50.27 kcal/mol. We constructed a pCAMBIA-35S-GUS-miR156x dual overexpression vector and established a transient transformation system for mulberry. At an optimal transformation solution (OD600 = 0.7), the GUS gene showed a higher expression in the leaves of transiently transformed mulberry with miR156x overexpression, four days after transformation, while the target genes of miR156x had decreased expression in the same leaves. Investigations into the transgenic mulberry plants uncovered various modifications to physio-chemical parameters including POD, SOD, PRO, MDA, soluble proteins and sugars, and chlorophyl content. miRNAs in the plants were found to act as negative regulators of gene expression in response to changes in leaf shape regulation, which was confirmed in vitro using dual-luciferase reporter assays. Subsequently, we cloned Maspl3 in vitro and conducted GST-Pull down assays, obtaining multiple proteins that interacted with the Maspl3 gene. This indicates that the miR156x/Maspl3/MSTRG.25812.1 regulatory module contributes to the differences in mulberry leaf shape.

When attempting to maximize the crop yield from field-grown soybean (Glycine max (L.) Merr.) by means of improving the light conditions for photosynthesis in the canopy, it is crucial to find the optimal planting density and nitrogen application rate. The soybean plants that were the subject of our experiment were cultivated in N-dense mutual pairs, and included two cultivars with different leaf shapes; one cultivar sported ovate leaves (O-type) and the other lanceolate leaves (L-type). We analyzed the results quantitatively to determine the amount of spatial variation in light distribution and photosynthetic efficiency across the canopy, and to gauge the effect of the experimental parameters on the yield as well as the photosynthetic light and nitrogen use efficiency of the crop. Results indicate that the different leaf shapes were responsible for significant disparities between the photosynthetic utilization of direct and diffuse light. As the nitrogen fertilizer rate and the planting density increased, the soybean plants responded by adjusting leaf morphology in order to maximize the canopy apparent photosynthetic light use efficiency, which in turn affected the leaf nitrogen distribution in the canopy. Despite the fact that the light interception rate of the canopy of the L-type cultivar was lower than that of the canopy of the O-type cultivar, we found its canopy apparent photosynthetic nitrogen and light use efficiency were higher. It was interesting to note, however, that the nitrogen and light use efficiency contributions associated with exposure to diffuse light were greater for the latter than for the former.