Rosette Plants Research Articles

Accelerated reproduction of the parental lines of white cabbage using rosette plants (steckling) and artificial climate chambers

Relevance. The technology of producing cabbage seeds with the traditional method takes almost 2 years. Its high labor intensity caused the need to search for cheaper methods of selection and seed production. One of the ways to speed up the stages of the selection process is the use of artificial climate chambers. The aim of research is to obtain seeds of promising inbred lines of late maturing white cabbage and hybrid combinations with their participation using rosette plants (steckling) in artificial climate chambers. Materials and Methods. The material was inbred pure lines of 5-6 generations of inbreeding, obtained from promising hybrid combinations of domestic and foreign breeding. The research was conducted in 2023-2024. Sowing in Plantek 64 cassettes was carried out on July 10, then the seedlings were transplanted into vegetative vessels with an optimal volume of 5-6 liters and installed in the open ground for the growth of a leaf outlet. In the phase 10-13 of real leaves, the plugs were placed in an artificial climate chamber. During the growth and development period, biometric and phenological observations were carried out, and an analysis of seed setting was carried out during the hybridization of inbred lines.Results. As a result of research in the study of hybrid seed production under artificial climate chamber conditions, high rates of seed setting in buds under cross-pollination of rosette plants of white cabbage were revealed. Genotypes with high seed set rate under geitenogamous bud pollination were also identified. The weight of 1000 seeds of the studied plants was within the range of 2.5-5.14 g. Genotypes 383-3, 384-2 and 384-7 were selected, which had the highest percentage of seeds in the fractional composition with size more than 2 mm 80.3%, 43.5% and 59.4%, respectively. When genotypes 384-2 and 384-7 were used in hybrid combinations as a maternal component, high quality indicators of the obtained seeds were revealed.Conclusion. For the studied genotypes of white cabbage, when grown in an artificial climate chamber, no significant effect on seed quality was found; the genotype had a greater effect on seed quality indicators.

The polyphyletic Caucasus-centred Campanula subg. Scapiflorae (Campanulaceae) revisited with a newly circumscribed C. sect. Tridentatae for its core clade.

Campanula L. is among the genera with the highest number of endemics in the Caucasus ecoregion. A group of attractive alpine and subalpine perennial rosette plants with short single-flowered stems centred in the Caucasus has been treated as Campanulasubg.Scapiflorae or at other ranks, with considerably varying circumscription and classification. Molecular phylogenetic analysis of three plastid DNA regions (trnK/matK, petD, rpl16) of a strongly extended sampling, comprising 23 of the 27 commonly accepted taxa (85%) with 330 accessions built on and guided by the results of our previous study of the group, confirmed the polyphyly of C.subg.Scapiflorae in any of its circumscriptions. The core clade of the group comprises exclusively endemics and near-endemics of the Caucasus and is treated here as C.sect.Tridentatae in a revised circumscription. The phylogenetic relationships of the disparate other elements of the Scapiflorae group are outlined.

Strands of connection: unraveling livestock grazing effects on orb-weaver spiders

Studies on the effects of grazing disturbances in grasslands have shown mixed results for spider diversity, mainly regarding their guilds. While ungrazing, low, and moderate grazing potentially enhance the diversity of orb-weavers in spider communities, heavy grazing seems to reduce species’ richness. On the population level though, studies of orb-weavers are scarce, and the effects of grazing in natural grasslands are unknown. In this way, we investigated the effects of different grazing levels on population persistence of orb-weaver spiders, hypothesizing that low to intermediate disturbances benefit populations. We predict that high grazing, due to the removal of vegetation structure, will negatively affect the occupancy and abundance of orb-weavers. For that, we experimentally controlled grazing pressure and obtained population occurrence and counts of two orb-weaver spider species, Argiope argentata and Alpaida quadrilorata. We found that A. argentata was negatively affected by grazing, as it relies on higher vegetation for web-building. In contrast, A. quadrilorata, which occurs in cattle-resistant rosette plants, showed no effects of grazing. Implications for insect conservation: Our study emphasizes the need for balanced grazing practices and habitat conservation to protect orb-weaver spiders and other arthropods, as well as species-specific effects for species from the same guild, underscoring their ecological significance in maintaining ecosystem stability.

A CNN-based model to count the leaves of rosette plants (LC-Net)

Plant image analysis is a significant tool for plant phenotyping. Image analysis has been used to assess plant trails, forecast plant growth, and offer geographical information about images. The area segmentation and counting of the leaf is a major component of plant phenotyping, which can be used to measure the growth of the plant. Therefore, this paper developed a convolutional neural network-based leaf counting model called LC-Net. The original plant image and segmented leaf parts are fed as input because the segmented leaf part provides additional information to the proposed LC-Net. The well-known SegNet model has been utilised to obtain segmented leaf parts because it outperforms four other popular Convolutional Neural Network (CNN) models, namely DeepLab V3+, Fast FCN with Pyramid Scene Parsing (PSP), U-Net, and Refine Net. The proposed LC-Net is compared to the other recent CNN-based leaf counting models over the combined Computer Vision Problems in Plant Phenotyping (CVPPP) and KOMATSUNA datasets. The subjective and numerical evaluations of the experimental results demonstrate the superiority of the LC-Net to other tested models.

Leaf-Counting in Monocot Plants Using Deep Regression Models.

Leaf numbers are vital in estimating the yield of crops. Traditional manual leaf-counting is tedious, costly, and an enormous job. Recent convolutional neural network-based approaches achieve promising results for rosette plants. However, there is a lack of effective solutions to tackle leaf counting for monocot plants, such as sorghum and maize. The existing approaches often require substantial training datasets and annotations, thus incurring significant overheads for labeling. Moreover, these approaches can easily fail when leaf structures are occluded in images. To address these issues, we present a new deep neural network-based method that does not require any effort to label leaf structures explicitly and achieves superior performance even with severe leaf occlusions in images. Our method extracts leaf skeletons to gain more topological information and applies augmentation to enhance structural variety in the original images. Then, we feed the combination of original images, derived skeletons, and augmentations into a regression model, transferred from Inception-Resnet-V2, for leaf-counting. We find that leaf tips are important in our regression model through an input modification method and a Grad-CAM method. The superiority of the proposed method is validated via comparison with the existing approaches conducted on a similar dataset. The results show that our method does not only improve the accuracy of leaf-counting, with overlaps and occlusions, but also lower the training cost, with fewer annotations compared to the previous state-of-the-art approaches.The robustness of the proposed method against the noise effect is also verified by removing the environmental noises during the image preprocessing and reducing the effect of the noises introduced by skeletonization, with satisfactory outcomes.

LS-Net: a convolutional neural network for leaf segmentation of rosette plants

LS-Net: a convolutional neural network for leaf segmentation of rosette plants

The enigmatic tropical alpine flora on the African sky islands is young, disturbed, and unsaturated

Tropical alpine floras are renowned for high endemism, spectacular giant rosette plants testifying to convergent adaptation to harsh climates with nightly frosts, and recruitment dominated by long-distance dispersal from remote areas. In contrast to the larger, more recent (late Miocene onward) and contiguous expanses of tropical alpine habitat in South America, the tropical alpine flora in Africa is extremely fragmented across small patches on distant mountains of variable age (Oligocene onward). How this has affected the colonization and diversification history of the highly endemic but species-poor afroalpine flora is not well known. Here we infer phylogenetic relationships of ∼20% of its species using novel genome skimming data and published matrices and infer a timeframe for species origins in the afroalpine region using fossil-calibrated molecular clocks. Although some of the mountains are old, and although stem node ages may substantially predate colonization, most lineages appear to have colonized the afroalpine during the last 5 or 10 My. The accumulation of species increased exponentially toward the present. Taken together with recent reports of extremely low intrapopulation genetic diversity and recent intermountain population divergence, this points to a young, unsaturated, and dynamic island scenario. Habitat disturbance caused by the Pleistocene climate oscillations likely induced cycles of colonization, speciation, extinction, and recolonization. This study contributes to our understanding of differences in the histories of recruitment on different tropical sky islands and on oceanic islands, providing insight into the general processes shaping their remarkable floras.

The complete chloroplast genome of Isatis cappadocica Desv. (Brassicaceae)

Isatis cappadocica Desv. is a vigorous perennial rosette plant and it can grow in highly arsenic-contaminated areas. In this study, the complete chloroplast genome of I. cappadocica was assembled and annotated. The total length of this genome is 153,800 bp and the GC content is 36.48%. It has a typical four-part structure: a pair of inverted repeat sequences (26,270 bp each), a small single-copy region (17,715 bp), and a large single-copy region (83,545 bp). The annotation results show that it contains 132 genes. The phylogenetic analysis of I. cappadocica and other 18 representative plants indicates that I. cappadocica is closely related to Isatis tinctoria.

Active space garnering by leaves of a rosette plant

Near-ground growth offers low-statured plants many benefits but also exposes them to the risk of being overtopped and losing access to sunlight. Plant community development is often portrayed as a process of serial dominance by successively taller species, but here we describe a mechanism by which a low-growing rosette species alters community spatial structure. Elephantopus elatus (Asteraceae), an herbaceous savanna plant with low-growing leaves that emerge radially from a central bud, pushes neighboring plants away and thereby avoids being overtopped. Active pushing is possible because the leaves have stout petioles that are basally anchored rather than attached to flexible twigs or stems. This growth-mediated leaf pushing introduces a novel example of active plant interactions that is likely important for other rosette plants.

A Comparative Study among Clustering Techniques for Leaf Segmentation in Rosette Plants

A Comparative Study among Clustering Techniques for Leaf Segmentation in Rosette Plants

Mapping the páramo land-cover in the Northern Andes

ABSTRACT The Andean páramo is a biodiverse and vulnerable tropical high-mountain region, whose spatio-ecological patterns remain understudied. The lack of general characterization of its overall extent, land-cover classes, and treeline spatial features hinders our capacity to understand its responses to human impacts and predict future land-system changes. To address this knowledge gap, we classified the land-cover of the páramo in the Northern Andes. Moreover, we estimated (1) the páramo’s total extent and its distribution among the Andean countries, (2) the relative extent of 12 of its main land-cover classes, categorized into natural vegetation, natural abiotic and anthropogenic groups, and (3) the preliminary position and anthropogenic influence of its bordering treeline. Relying on Landsat 8 imagery, we performed hybrid manual-automated classifications using the Maximum Likelihood and Random Forest algorithms. The two resulting final classifications were manually checked for errors compared to Google Earth and VegPáramo data, and used to produce the expert classification. Finally, we delimited the treeline based on regional forest connectivity, and applied it to the expert classification to evaluate páramo elevations, surface areas and land-cover classes above the Andean treeline. The páramo extent was estimated at 24,301 km2, distributed between Ecuador (47%), Colombia (43%), Venezuela (8%) and Peru (2%). Natural vegetation, especially shrublands, rosette plant communities and grasslands were dominant (altogether, 65%), whereas classes reflecting intense land-use covered 12% overall. The average treeline reached 3546 m and was bordered uphill at 16% with anthropogenic land-cover classes. The páramo’s extent is smaller than previously suggested. It remains a (semi-) natural region, yet the expansion of crops and pastures towards high elevations is a critical concern for long-term sustainability. Future research can build on our findings to predict land-system changes and assess priority areas for conservation. We recommend for future research to focus on remnant forest patches and treeline connectivity in priority.

Effects of Water Depth on the Growth of the Submerged Macrophytes Vallisneria natans and Hydrilla verticillata: Implications for Water Level Management

Water level is one of the most important factors affecting the growth of submerged macrophytes in aquatic ecosystems. The rosette plant Vallisneria natans and the erect plant Hydrilla verticillata are two common submerged macrophytes in lakes of the middle and lower reaches of the Yangtze River, China. How water level fluctuations affect their growth and competition is still unknown. In this study, three water depths (50 cm, 150 cm, and 250 cm) were established to explore the responses in growth and competitive patterns of the two plant species to water depth under mixed planting conditions. The results show that, compared with shallow water conditions (50 cm), the growth of both submerged macrophytes was severely suppressed in deep water depth (250 cm), while only V. natans was inhibited under intermediate water depth (150 cm). Moreover, the ratio of biomass of V. natans to H. verticillata gradually increased with increasing water depth, indicating that deep water enhanced the competitive advantage of V. natans over H.verticillata. Morphological adaptation of the two submerged macrophytes to water depth was different. With increasing water depth, H. verticillata increased its height, at the cost of reduced plant numbers to adapt to poor light conditions. A similar strategy was also observed in V. natans, when water depth increased from 50 cm to 150 cm. However, both the plant height and number were reduced at deep water depth (250 cm). Our study suggests that water level reduction in lake restoration efforts could increase the total biomass of submerged macrophytes, but the domination of key plants, such as V. natans, may decrease.

Plant structure specialization in Paraphidippus basalis (Araneae: Salticidae), a jumping spider of the Madrean Sky Islands

Paraphidippus basalis (Banks, 1904) is a large jumping spider that occurs in the sky islands of the southwestern United States and northern Mexico. To date, P. basalis has only been incidentally reported on rosette-forming plants in the family Asparagaceae (yucca, agave, and sotol), even though the sky islands support a rich and diverse vegetation community. This apparent specialization is unusual because jumping spiders do not typically have strong associations with the plants on which they live. However, given that the ecology of P. basalis has yet to be studied, the microhabitat preferences of P. basalis remain unclear. We investigated microhabitat choice in P. basalis in the Patagonia Mountains of southeastern Arizona, to determine whether these spiders were specifically associated with rosette-forming plants. We surveyed 160 plots for jumping spiders, 80 with rosette-forming plants and 80 without. P. basalis was found only in rosette-forming plants, whereas other species of jumping spiders showed no preference for rosette or control plots. Larger rosette plants were more likely to contain P. basalis. This study provides an unusual example of host plant structural specificity in a jumping spider.

The role of a rosette‐shaped plant (Eryngium horridum, Apiaceae) on grassland spiders along a grazing intensity gradient

Abstract Rosette‐shaped plants can amplify the diversity of predator arthropods and act as potential shelters for these animals in grassland ecosystems under grazing effect. Here we evaluated the contribution of a vertical rosette‐shaped plant (Eryngium horridum) to patterns of spider diversity and functional traits in subtropical grasslands under different grazing intensities. We used a common sub‐shrub (Baccharis crispa) and the herbaceous vegetation as reference microhabitats. Sampling was conducted in 23 plots described according to grazing intensity based on environmental co‐variables. Spiders were sampled with D‐Vac suction within patches of E. horridum, B. crispa, and the herbaceous vegetation. Compared to the reference microhabitats, E. horridum harboured distinct community composition with a subset of exclusive species, and morphologically adapted spiders. Spider richness increased in Eryngium plants as grazing pressure increased and the grassland became more simplified. Abundance of runners and space web‐builders responded in a similar fashion, while orb‐web builders were more abundant in E. horridum regardless of grazing intensity. Our results indicate that these rosette plants positively affect top invertebrate predators, with a special role for sites with high grazing intensities where it promotes microhabitat complexity and aggregates more individuals and species. Thus, grassland management that alter Eryngium's occurrence must be conducted cautiously.

Afro-alpine flagships revisited: Parallel adaptation, intermountain admixture and shallow genetic structuring in the giant senecios (Dendrosenecio).

Distantly related lineages of the enigmatic giant rosette plants of tropical alpine environments provide classical examples of convergent adaptation. For the giant senecios (Dendrosenecio), the endemic landmarks of the East African sky islands, it has also been suggested that parallel adaptation has been important for within-lineage differentiation. To test this hypothesis and to address potential gene flow and hybridization among the isolated sky islands, we organized field expeditions to all major mountains. We sampled all currently accepted species and all but one subspecies and genotyped 460 plants representing 109 populations. We tested whether genetic structuring corresponds to geography, as predicted by a parallel adaptation hypothesis, or to altitudinal belt and habitat rather than mountains, as predicted by a hypothesis of a single origin of adaptations. Bayesian and Neighbor-Net analyses showed that the main genetic structure is shallow and largely corresponds to geography, supporting a hypothesis of recent, rapid radiation via parallel altitude/habitat adaptation on different mountains. We also found evidence for intermountain admixture, suggesting several long-distance dispersals by wind across vast areas of unsuitable habitat. The combination of parallel adaptation, secondary contact, and hybridization may explain the complex patterns of morphological variation and the contradicting taxonomic treatments of these rare enigmatic giants, supporting the use of wide taxonomic concepts. Notably, the within-population genetic diversity was very low and calls for increased conservation efforts.

Dendrological inventory of plants and development of the arrangement system for restoration and development of the Park named after Prince of Oldenburg in Gagra

The article presents the results of a dendrological inventory and development of arrangement system for restoration and agrotechnical care of plants in the Park named after Prince of Oldenburg, one of the remarkable places on the Black Sea coast of the Caucasus (BSCC). A list of the assortment of ornamental woody plants for replenishment is also provided. 158 plant species grow in the Park, 49 - families, 42 - conifers, 97 - deciduous, 10 - palm trees, I - bamboos, 4 - rosette plants, 4 - arge herbaceous plants. Including: evergreen trees - 67 names, evergreen shrubs - 15, evergreen liana - 3, deciduous trees - 37, deciduous shrubs - 15, semi-evergreen shrubs - 2, perennial grass plants - 4, palm trees - 10, rosette plants - 4, bamboos - I. Among woody plants, 32 species and 2 - garden forms are classified as unique. The necessity of assigning a new status to the Park is substantiated.

Correction to: Rosette plant segmentation with leaf count using orthogonal transform and deep convolutional neural network

Correction to: Rosette plant segmentation with leaf count using orthogonal transform and deep convolutional neural network

Rosette plant segmentation with leaf count using orthogonal transform and deep convolutional neural network

Plant image analysis plays an important role in agriculture. It is used to record the morphological plant traits regularly and accurately. The plant growth is one of the key traits to be analyzed, which relies on leaf area (i.e., leaf region or plant region) and leaf count. One of the ways to find the leaf count is counting the leaves using segmented plant region. In this paper, a new plant region segmentation scheme is proposed in the orthogonal transform domain based on orthogonal transform coefficients. Initially, an analysis of orthogonal transform coefficients is carried out in terms of the response of orthogonal basis vectors to extract the plant region. After extracting the plant region, the L*a*b and CMYK color spaces are used for noise removal in the segmentation scheme. Finally, the leaves are counted using fine-tuned deep convolutional neural network models. The proposed scheme is experimented on CVPPP benchmark datasets and also tested with the images taken from mobile phone to ensure its reliability and cross-platform applicability. The experiment results on CVPPP benchmark datasets are promising.

Altitudinal variation in butterfly community associated with climate and vegetation.

Elevation creates a variety of physical conditions in a relatively short distance, which makes mountains suitable for studying the effects of climate change on biodiversity. We investigated the importance of climate and vegetation for the distribution of butterflies from 800 to 1400 m elevation. We sampled butterflies, and woody and rosette plants and measured air temperature and humidity, wind speed and gust, and solar radiation. We partitioned diversity to assess the processes underlying community shifts across altitudes - species loss versus replacement. We assessed the strength of the association among butterfly, vegetation, and climate. Butterfly richness and abundance decreased with altitude, and species composition changed along the elevation. Changes in butterfly composition with altitude were mainly through species replacement and by abundance increases in some species being compensated by decreases in others. Since the floristic diversity decreased with altitude due to soil conditions, and butterflies are closely related to their host plants, this could explain species replacement with altitude. Overall, we found a stronger association of butterfly community with vegetation than climate, but plant community and climate were also strongly associated between them. Butterfly richness was more strongly associated with plant richness than with temperature, while the reverse was true for butterfly abundance, which was more strongly associated with temperature than with plant richness. We must consider the complementary roles of resource and conditions in species distribution.

Reducing Preharvest Bolting in Open-field-grown Cilantro (Coriandrum sativum L. cv. Santo) through Use of Growth Regulators

Cilantro (Coriandrum sativum L.), also called coriander, is an herbaceous, annual plant that is cultivated worldwide for its leaves and seeds. Cilantro has a strong propensity to bolt quickly in hot weather and under long-day (LD) conditions, which affects the flavor and renders the crop unmarketable. High incidence of preharvest bolting in open-field production can cause significant economic loss. The phytohormone gibberellic acid (GA) regulates stem elongation and floral initiation in many LD rosette plants. In pilot experiments, we found that GA induced bolting in greenhouse-grown cilantro and that plant growth regulators (PGRs) with anti-GA activity can delay this process. We then explored the effects of different GA inhibitors on reducing the incidence of bolting in cilantro grown in a commercial open-field environment. Four field trials were conducted on a commercial farm near Clewiston in Florida between Fall 2016 and Spring 2018. Different growth regulators were applied at different times, ranging from 5 to 8 weeks after seeding (WAS), and plants were harvested 2 to 3 weeks thereafter. Applications of GA inhibitors significantly reduced the incidence of bolting in three of the four trials, but the extent depended on the type of inhibitor used. The results from one trial were inconclusive due to changes in weather that prevented bolting in the entire field. Overall, plots treated with prohexadione calcium and paclobutrazol were most effective and reduced bolting by up to 78%. Applying the PGRs at 5 and 6 WAS was more effective than at 7 or 8 WAS.