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"Flowering plants"
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Relatively stable response of fruiting stage to warming and cooling relative to other phenological events
The timing of the fruit-set stage (i.e., start and end of fruit set) is crucial in a plant's life cycle, but its response to temperature change is still unclear. We investigated the timing of seven phenological events, including fruit-set dates during 3 yr for six alpine plants transplanted to warmer (approximately +3.5 °C in soils) and cooler (approximately -3.5 °C in soils) locations along an altitudinal gradient in the Tibetan area. We found that fruit-set dates remained relatively stable under both warming and cooling during the 3-yr transplant experiment. Three earlier phenological events (emergence of first leaf, first bud set, and first flowering) and two later phenological events (first leaf coloring and complete leaf coloring) were earlier by 4.8-8.2 d/°C and later by 3.2-7.1 d/°C in response to warming. Conversely, cooling delayed the three earlier events by 3.8-6.9 d/°C and advanced the two later events by 3.2-8.1 d/°C for all plant species. The timing of the first and/or last fruit-set dates, however, did not change significantly compared to earlier and later phenological events. Statistical analyses also showed that the dates of fruit set were not significantly correlated or had lower correlations with changes of soil temperature relative to the earlier and later phenological events. Alpine plants may thus acclimate to changes in temperature for their fruiting function by maintaining relatively stable timings of fruit set compared with other phenological events to maximize the success of seed maturation and dispersal in response to short-term warming or cooling.
Journal Article
The water lily genome and the early evolution of flowering plants
Water lilies belong to the angiosperm order Nymphaeales. Amborellales, Nymphaeales and Austrobaileyales together form the so-called ANA-grade of angiosperms, which are extant representatives of lineages that diverged the earliest from the lineage leading to the extant mesangiosperms
1
–
3
. Here we report the 409-megabase genome sequence of the blue-petal water lily (
Nymphaea colorata
). Our phylogenomic analyses support Amborellales and Nymphaeales as successive sister lineages to all other extant angiosperms. The
N. colorata
genome and 19 other water lily transcriptomes reveal a Nymphaealean whole-genome duplication event, which is shared by Nymphaeaceae and possibly Cabombaceae. Among the genes retained from this whole-genome duplication are homologues of genes that regulate flowering transition and flower development. The broad expression of homologues of floral ABCE genes in
N. colorata
might support a similarly broadly active ancestral ABCE model of floral organ determination in early angiosperms. Water lilies have evolved attractive floral scents and colours, which are features shared with mesangiosperms, and we identified their putative biosynthetic genes in
N. colorata
. The chemical compounds and biosynthetic genes behind floral scents suggest that they have evolved in parallel to those in mesangiosperms. Because of its unique phylogenetic position, the
N. colorata
genome sheds light on the early evolution of angiosperms.
The genome of the tropical blue-petal water lily
Nymphaea colorata
and the transcriptomes from 19 other Nymphaeales species provide insights into the early evolution of angiosperms.
Journal Article
Asymmetric winter warming advanced plant phenology to a greater extent than symmetric warming in an alpine meadow
The warming of terrestrial high‐latitude ecosystems, while increasing, will likely be asymmetric across seasons—where winter non‐growing seasons will warm more than summer‐growing seasons. Asymmetric winter warming in temperature‐sensitive ecosystems may delay spring phenological events by reducing the opportunity that a plants’ chilling requirement is met. Similarly, symmetric warming can advance spring phenology.
To explore the impact of asymmetric warming on plant phenology, we applied a year‐round warming and a winter warming treatment to our experimental plots. Over a 2‐year period, we monitored leaf‐out and flowering phenology for 11 plant species.
There was variation among species, however, both winter and year‐round warming, advanced the leaf‐out day and the first flowering day relative to the control treatment. Winter warming advanced leaf‐out and flowering phenology by 11.1 (±2.4) and 12.6 (±2.9) days respectively. However, year‐round warming had less of an impact advancing leaf‐out and flowering phenology by 5.1 (±2.1) and 10.0 (±3.0) days respectively.
Our study provides direct evidence that asymmetric winter warming has a larger impact on plant phenology than symmetric year‐round warming. Increasing soil temperature in the winter from below to above freezing temperatures advanced the spring phenology of alpine plants. Winter warming increased soil temperature more than year‐round warming, which explains why phenology advanced under winter warming more than under year‐round warming. In addition, early or mid‐season flowering plant species displayed different phenology strategies in warmer winters.
Relative to other ecosystems, alpine ecosystems such as the Tibetan Plateau will likely respond to asymmetric warming given the higher amplitude of winter temperature increases due to climatic warming. Our data indicate that seasonal variation in warming should be considered when predicting and modelling the response of alpine ecosystems to climatic change.
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Journal Article
The sugar transporter SWEET10 acts downstream of FLOWERING LOCUS T during floral transition of Arabidopsis thaliana
Background
Floral transition initiates reproductive development of plants and occurs in response to environmental and endogenous signals. In
Arabidopsis thaliana
, this process is accelerated by several environmental cues, including exposure to long days. The photoperiod-dependent promotion of flowering involves the transcriptional induction of
FLOWERING LOCUS T
(
FT
) in the phloem of the leaf.
FT
encodes a mobile protein that is transported from the leaves to the shoot apical meristem, where it forms part of a regulatory complex that induces flowering. Whether FT also has biological functions in leaves of wild-type plants remains unclear.
Results
In order to address this issue, we first studied the leaf transcriptomic changes associated with FT overexpression in the companion cells of the phloem. We found that FT induces the transcription of
SWEET10
, which encodes a bidirectional sucrose transporter, specifically in the leaf veins. Moreover,
SWEET10
is transcriptionally activated by long photoperiods, and this activation depends on FT and one of its earliest target genes
SUPPRESSOR OF CONSTANS OVEREXPRESSION 1
(
SOC1
). The ectopic expression of
SWEET10
causes early flowering and leads to higher levels of transcription of flowering-time related genes in the shoot apex.
Conclusions
Collectively, our results suggest that the FT-signaling pathway activates the transcription of a sucrose uptake/efflux carrier during floral transition, indicating that it alters the metabolism of flowering plants as well as reprogramming the transcription of floral regulators in the shoot meristem.
Journal Article
Late‐acting self‐incompatibility – the pariah breeding system in flowering plants
CONTENTS: 717 I. 717 II. 718 III. 718 IV. 720 V. 722 VI. 722 VII. 728 730 References 730 SUMMARY: It is estimated that around half of all species of flowering plants show self‐incompatibility (SI). However, the great majority of species alleged to have SI simply comply with ‘the inability of a fully fertile hermaphrodite plant to produce zygotes when self‐pollinated’ – a definition that is neutral as to cause. Surprisingly few species have been investigated experimentally to determine whether their SI has the type of genetic control found in one of the three established mechanisms, that is, homomorphic gametophytic, homomorphic sporophytic or heteromorphic SI. Furthermore, our knowledge of the molecular basis of homomorphic SI derives from a few species in just five families – a small sample that has nevertheless revealed the existence of three different molecular mechanisms. Importantly, a sizeable cohort of species are self‐sterile despite the fact that self‐pollen tubes reach the ovary and in most cases penetrate ovules, a phenomenon called late‐acting self‐incompatibility (LSI). This review draws attention to the confusion between species that show ‘self‐incompatibility’ and those that possess one of the ‘conventional SI mechanisms’ and to argue the case for recognition of LSI as having a widespread occurrence and as a mechanism that inhibits selfing and promotes outbreeding in many plant species.
Journal Article
Quantifying bee assemblages and attractiveness of flowering woody landscape plants for urban pollinator conservation
Urban and suburban landscapes can be refuges for biodiversity of bees and other pollinators. Public awareness of declining pollinator populations has increased interest in growing plants that provide floral resources for bees. Various publications and websites list \"bee-friendly\" plants, but such lists are rarely based on empirical data, nor do they emphasize flowering trees and shrubs, which are a major component of urban landscapes. We quantified bee visitation to 72 species of flowering woody landscape plants across 373 urban and suburban sites in Kentucky and southern Ohio, USA, sampling and identifying the bee assemblages associated with 45 of the most bee-attractive species. We found strong plant species effects and variation in seasonal activity of particular bee taxa, but no overall differences in extent of bee visitation or bee genus diversity between native and non-native species, trees and shrubs, or early-, mid-, and late-season blooming plants. Horticulturally-modified varieties of Hydrangea, Prunus, and Rosa with double petals or clusters of showy sterile sepals attracted few bees compared to related plants with more accessible floral rewards. Some of the non-native woody plant species bloomed when floral resources from native plants were scarce and were highly bee-attractive, so their use in landscapes could help extend the flowering season for bees. These data will help city foresters, landscape managers, and the public make informed decisions to create bee-friendly urban and suburban landscapes.
Journal Article
FloralArea: AI-powered algorithm for automated calculation of floral area from flower images to support plant and pollinator research
Floral area is a major predictor of the attractiveness of a flowering plant for pollinators, yet the measurement of floral area is time-consuming and inconsistent across studies. Here, we developed an AI-powered algorithm, FloralArea, to automate floral area measurement from an image. The FloralArea algorithm has two main components: an object segmentation module and an area estimation module. The object segmentation module extracts the pixels of flowers and the reference object in an image. The area estimation module predicts floral area based on the ratio between flower and reference object pixels. We fine-tuned two YOLOv8 segmentation models for flower and reference object segmentation. The flower segmentation model achieved moderate precision, recall, mAP0.5, and mAP0.5-0.95 of 0.794, 0.68, 0.741, and 0.455 on the test dataset, while the reference object model achieved an impressive performance of 0.907, 0.940, 0.933, and 0.832. We evaluated FloralArea using 75 images of flowering plants. We used ImageJ to calculate the actual floral area for all the images and compared them with the predicted floral area from FloralArea. The predicted floral area correlated well with the measured floral area with a coefficient of determination (R 2 ) of 0.93 and a root mean square error of 20.58 cm 2 . The FloralArea algorithm reduced the time it takes to calculate floral area from an image by 99.24% compared with traditional methods with image processing tools like ImageJ. By streamlining floral area estimation, the FloralArea algorithm provides a scalable, efficient, consistent, and accessible tool for researchers, particularly to aid in assessing plant attractiveness to different pollinator groups.
Journal Article
DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field
Background
Flowering is one of the most important processes for flowering plants such as cotton, reflecting the transition from vegetative to reproductive growth and is of central importance to crop yield and adaptability. Conventionally, categorical scoring systems have been widely used to study flowering patterns, which are laborious and subjective to apply. The goal of this study was to develop a deep learning-based approach to characterize flowering patterns for cotton plants that flower progressively over several weeks, with flowers distributed across much of the plant.
Results
A ground mobile system (GPhenoVision) was modified with a multi-view color imaging module, to acquire images of a plant from four viewing angles at a time. A total of 116 plants from 23 genotypes were imaged during an approximately 2-month period with an average scanning interval of 2–3 days, yielding a dataset containing 8666 images. A subset (475) of the images were randomly selected and manually annotated to form datasets for training and selecting the best object detection model. With the best model, a deep learning-based approach (DeepFlower) was developed to detect and count individual emerging blooms for a plant on a given date. The DeepFlower was used to process all images to obtain bloom counts for individual plants over the flowering period, using the resulting counts to derive flowering curves (and thus flowering characteristics). Regression analyses showed that the DeepFlower method could accurately (R
2
= 0.88 and RMSE = 0.79) detect and count emerging blooms on cotton plants, and statistical analyses showed that imaging-derived flowering characteristics had similar effectiveness as manual assessment for identifying differences among genetic categories or genotypes.
Conclusions
The developed approach could thus be an effective and efficient tool to characterize flowering patterns for flowering plants (such as cotton) with complex canopy architecture.
Journal Article