Plant Structure Research Articles

High-intensity light promotes adaptive divergence of photosynthetic traits between sun-exposed and shaded populations in Saxifraga fortunei.

Light is essential for plants, and local populations exhibit adaptive photosynthetic traits depending on their habitats. Although plastic responses in morphological and/or physiological characteristics to different light intensities are well known, adaptive divergence with genetic variation remains to be explored. This study focused on Saxifraga fortunei (Saxifragaceae) growing in sun-exposed and shaded habitats. We measured the leaf anatomical structure and photosynthetic rate of plants grown in their natural habitats and in a common greenhouse (high- and low-intensity light experimental sites). To assess differences in ecophysiological tolerance to high-intensity light between the sun and shade types, we evaluated the level of photoinhibition of photosystem II and the leaf mortality rate under high-intensity light conditions. In addition, population genetic analysis was conducted to investigate phylogenetic origins. Clear phenotypic differences were found between the sun and shade types despite their recent phylogenetic origin. The leaf anatomical structure and photosynthetic rate showed plastic changes in response to growing conditions. Moreover, the sun type had a well-developed palisade parenchyma and a higher photosynthetic rate, which were genetically fixed, and a lower level of photoinhibition under high-intensity light. Our findings demonstrate that light intensity is a selective pressure that can rapidly promote phenotypic divergence between the sun and shade types. While phenotypic changes in multiple photosynthetic traits were plastic, genetic divergence in specific traits related to adaptation to high-intensity light would be fundamental for ecotypic divergence to different light regimes.

Study on seismic performance of SRC frame-bent structures in CAP1400 nuclear power plants

With the conventional island turbine plant project of a CAP1400 nuclear power plant (NPP) as the research background, this paper proposed to apply steel reinforced concrete (SRC) frame-bent structure system to the main building of the NPP. Substructures comprising three frames and two spans from the prototype structure were identified for testing, and a test model was constructed at a scale ratio of 1/7 to test the dynamic and pseudo-dynamic characteristics of the substructures. On the basis of the test results, the structure was further verified using the finite element analysis method. The results showed that the first three modes of substructure were respectively lateral translation with torsion, longitudinal translation with torsion and torsion; The ratio between the third-order and first-order mode cycles was 0.72, indicating that the torsional stiffness of the structure was relatively small and the torsional effect was obvious. When the maximum acceleration peak was 2200 gal, the maximum inter-story drift ratio of the model structure reached 1/31. Ultimately, when the structure was finally destroyed, the concrete at the bottom of each SRC column was crushed and peeled off.

A dataset of the sugarcane planting distribution with the spatial resolution of 10 m in Guangxi from 2018 to 2020

The extraction of sugarcane planting distribution is the basis of crop monitoring. The extraction of timely and accurate sugarcane planting distribution is of great significance for monitoring sugarcane crops and making adjustments to the planting structure. Based on Sentinel-1 and Sentinel-2 data, in this paper, we adopted the active and passive remote sensing collaborative method and decision tree classification method to carry out research on the extraction method of sugarcane planting distribution in Guangxi. Then we verified the data by referring to multi-year survey ground sample data. On this basis, we produced dataset of the sugarcane planting distribution with the spatial resolution of 10 m in Guangxi from 2018 to 2020. The remote sensing extraction-based method yielded an overall accuracy of 92% for sugarcane planting distribution in Guangxi in 2018, with a Kappa coefficient of 0.8. The overall accuracy of sugarcane planting distribution in Guangxi in 2019 is 94%, with a Kappa coefficient 0.88; the overall accuracy of sugarcane planting distribution in Guangxi in 2020 is 94%, with a Kappa coefficient of 0.88. This dataset can be used as the basic data for the analysis of temporal and spatial changes of sugarcane in Guangxi. And it can also provide basic data support for the optimization and adjustment of sugarcane production management and planting structure in Guangxi.

Методика проведения агротехнических исследований в опытах с кукурузой

There are stated methodic peculiarities of observations in field experiments with corn. There are presented observations and accounts in field experiments with corn by following indicators: plant structure, growth, and development; phenology and biometrics; diagnostics of mineral nutrition of corn; elements of yield structure; analytic observations in laboratory; yield account and the calculation of the nutrients consumption, protein yield. The article is based on a published book “Methodology of agricultural and technical investigations in experiments with main field crops” by Lukomets V.M., Tishkov N.M., and Semerenko S.A. (Krasnodar, 2022).

Floristic Inventory, Diversity, and Community Structure of the Riparian and Coastal Sand Dune Landscapes in the Lower Padsan River Basin, Laoag City, Ilocos Norte, Philippines

Padsan River basin, the largest river system in Laoag City, Ilocos Norte, encompasses two vital ecological landscapes: coastal sand dunes and riparian areas. Despite its ecological importance, the floristic diversity of these landscapes still needs to be better understood and documented. A vegetation assessment was conducted to characterize the composition, diversity, and community structure of plants in the lower Padsan River landscapes. Eighteen 10 m x 10 m nested quadrats were established across six sampling stations. The study recorded 82 species of vascular plants from 80 genera and 41 families. Fifty-two percent are introduced species, 48% are native species, and 27% are invasive species. The plant life forms are composed of trees (34 spp.), herbs (17 spp.), vines (13 spp.) and grasses (9 spp.). Fabaceae and poaceae were the most species-rich plant families. Prosopis juliflora (Candaroma) was the most dominant tree species, comprising 29% of the entire population. The lower Padsan River basin landscapes exhibits moderate tree diversity (H’ = 2.7), with Shannon diversity indices ranging from 0.89 to 2.43 across sampling locations. The riparian areas showed higher tree Shannon diversity, richness, and evenness, while the coastal sand dune areas had higher tree dominance but lower Shannon diversity. The plant community structure varies between the two types of ecological landscapes (ANOSIM Global R=0.7, p<0.05). P. juliflora dominates the coastal sand dune, while a mix of the Leucaena-Pithecellobium-Terminalia community characterizes the riparian area. This study provides essential baseline information on the floristic diversity and community structure, serving as a foundation for developing an integrated river management plan and strategies for conserving important ecological landscapes in the downstream section of the Padsan River Basin.

A dataset of UAV multispectral images for a banana Fusarium wilt survey

Banana Fusarium wilt, also known as "banana cancer", currently poses a significant threat to banana production worldwide. Timely and accurate identification of Fusarium wilt disease is crucial for effective disease control and optimizing agricultural planting structure. To explore the use of unmanned aerial vehicle (UAV) remote sensing for identifying banana wilt disease, in this study, we obtained comprehensive experimental data on wilted banana plants in a banana plantation in Long'an County, Guangxi. The dataset includes UAV multispectral reflectance data and ground survey data on the incidence of banana wilt disease. The UAV multispectral imagery was acquired under clear, cloud-free, and well-illuminated weather conditions, at a flying altitude of 120 meters with a spatial resolution of 8 cm/pixel. The ground sample points survey on the occurrence of banana wilt disease was conducted using a high-precision handheld GPS unit to collect latitude and longitude information for each sample point, and the positions were matched with the corresponding center positions of banana plants in the UAV imagery indoors. The dataset provides high- spatial-resolution UAV multispectral imagery data and accurate ground sample point survey data. It can be applied in the research and monitoring of UAV remote sensing identification and surveillance of banana wilt disease. It plays a crucial role in advancing research and application of remote sensing monitoring for agricultural crop diseases.

Методика проведения агротехнических исследований в опытах с сахарной свёклой

There are stated methodic peculiarities of observations and accounts in field experiments with sugar beet. There are presented plant structure, growth, and development; necessary observations and accounts by following indicators: phenology and biometrics; elements of yield structure; analytic observations in laboratory; yield account and the calculation of the consumption of nutrients. The article is based on a published book “Methodology of agricultural and technical investigations in experiments with main field crops” by Lukomets V.M., Tishkov N.M., and Semerenko S.A. (Krasnodar, 2022).

Leaf area predicts conspecific spatial aggregation of woody species

AbstractAimAddressing how woody plant species are distributed in space can reveal inconspicuous drivers that structure plant communities. The spatial structure of conspecifics varies not only at local scales across co‐existing plant species but also at larger biogeographical scales with climatic parameters and habitat properties. The possibility that biogeographical drivers shape the spatial structure of plants, however, has not received sufficient attention.LocationGlobal synthesis.Time Period1997–2022.Major Taxa StudiedWoody angiosperms and conifers.MethodsWe carried out a quantitative synthesis to capture the interplay between local scale and larger scale drivers. We modelled conspecific spatial aggregation as a binary response through logistic models and Ripley's L statistics and the distance at which the point process was least random with mixed effects linear models. Our predictors covered a range of plant traits, climatic predictors and descriptors of the habitat.ResultsWe hypothesized that plant traits, when summarized by local scale predictors, exceed in importance biogeographical drivers in determining the spatial structure of conspecifics across woody systems. This was only the case in relation to the frequency with which we observed aggregated distributions. The probability of observing spatial aggregation and the intensity of it was higher for plant species with large leaves but further depended on climatic parameters and mycorrhiza.Main ConclusionsCompared to climate variables, plant traits perform poorly in explaining the spatial structure of woody plant species, even though leaf area is a decisive plant trait that is related to whether we observe homogenous spatial aggregation and its intensity. Despite the limited variance explained by our models, we found that the spatial structure of woody plants is subject to consistent biogeographical constraints and that these exceed beyond descriptors of individual species, which we captured here through leaf area.

Computational and Experimental Substantiation of Strengthening Reinforced Concrete Structures with Composite Materials of Power Plants under Seismic Action

In Russia, a significant number of power facilities built in the 1960s and 1970s are located in regions where seismic effects were revised upward. This has led to an increase in the seismicity of the sites of facilities’ locations by magnitude 1–2 (MSK-64) in comparison with the data of design documentation. During the long-term operating period of power facilities, the load-bearing capacity of building structures, as a rule, decreases. This article presents the results of computational and experimental studies of reinforced concrete structures of thermal power plants and hydroelectric power plants for seismic effects in the range of magnitude 4–10 (MSK-64). The computational studies were carried out using ANSYS 16.0 software, and experimental studies were carried out on stands modeling seismic impacts with the help of hydraulic cylinders. The results of the studies showed that cracking of reinforced concrete structures without strengthening occurs at magnitude 6.0 (MSK-64) of seismic impact, and destruction occurs at magnitude 7.5. Thus, the seismic resistance of structures without reinforcement does not meet the requirements for seismic resistance, and strengthening is required. This study considers a variant of strengthening based on external composite reinforcement with CFRP. It is shown that the strengthening of structures with composite material increases their earthquake resistance up to magnitude 9–10 (MSK-64). This article presents recommendations on the CFRP strengthening of building structures of power facilities, both after receiving damage under seismic impact and in a planned manner to increase seismic resistance. The novelty of this work lies in the fact that quantitative results of increasing the seismic resistance of structures depending on the placement and number of layers of composite material are given.

Effects of climate change on plant-pollinator interactions and its multitrophic consequences

AbstractThere is wide consensus that climate change will seriously impact flowering plants and their pollinators. Shifts in flowering phenology and insect emergence as well as changes in the functional traits involved can cause alterations in plant-pollinator interactions, pollination success and plant reproductive output. Effects of rising temperatures, advanced snowmelt and altered precipitation patterns are expected to be particularly severe in alpine habitats due to the constrained season and upper range margins. Yet, our understanding of the magnitude and consequences of such changes in life history events and functional diversity in high elevation environments is incomplete.This special issue collects novel insights into the effects of climate change on plant-pollinator interactions in individual plant species and on network structure of entire plant and pollinator communities in alpine ecosystems. Using simulated changes of earlier snowmelt, natural gradients of variation in temperature, precipitation and snowmelt, or a long-term monitoring approach, these studies illustrate how plant species, plant communities, and pollinators respond to variation in environmental conditions associated with scenarios of ongoing climate change.The collection of papers presented here clearly demonstrates how spatial or temporal variation in the environmental climatic context affects flower abundances and plant community composition, and the consequences of these changes for pollinator visitation, pollination network structure, pollen transfer dynamics, or seed production. As changes in the availability of flowers, fruits, and seeds are likely to impact on other trophic levels, the time is ripe and pressing for a holistic multitrophic view of the effects of climate change on biotic interactions in alpine ecological communities.

Enhancing the AC network stability with a grid-forming control for single-stage PV inverter

This article proposes a PLL-less grid-forming (GFor) control for a PV central power plant topology designed to maintain the DC voltage and improve the AC voltage stability. The PV single-stage or central topology stands as the most widely adopted power plant structure. However, no GFor control capable of regulating the DC bus has yet been proposed for this layout. This work presents a PLL-less GFor control that can effectively control the DC voltage for a single-stage PV inverter, whether it operates at the Maximum Power Point (MPP) or with reserve. Moreover, this control can incorporate Maximum Power Point Tracking (MPPT) controls typically employed in grid-following structures. The primary advantage of this GFor control is the voltage support and stability it provides and the capability of working with a low Short Circuit Ratio (SCR). The performance and viability of the proposed control was analysed with several simulations of various faults (symmetrical and asymmetrical), frequency (large phase jump and frequency excursion with high ROCOF) and resource events (irradiation changes and DC voltage reference tracking analysis). The results demonstrate that the proposed GFor control presented not only meets the grid-code requirements but also exhibits the behaviour expected during the different analysed events.

Formation of the structure of common sainfoin plants depending on the elements of technology

Formation of the structure of common sainfoin plants depending on the elements of technology

How does land consolidation affect nongrain production? Evidence from county-level data in Jiangsu Province, China

Using county-level panel data for Jiangsu Province from 2008 to 2018, this study adopted a fixed effect model to analyze the impact of land consolidation on crop planting structure, also considering the moderating effect of distance from the city center and the heterogeneous effect of various types of land consolidation. The results revealed that farmland consolidation and land reclamation had a negative impact on the proportion of grain crops (rice, wheat, and corn) cultivated, which declined by 0.0051 % (0.0069 %), 0.0055 % (0.0124 %), and 0.0101 % (0.0123 %) for every 1 % increase in investment, construction area, and newly added arable land from farmland consolidation (land reclamation), respectively, demonstrating that land consolidation has not prevented, or even encouraged nongrain production expansion. The production conditions of reclaimed arable land and land transfer practices following consolidation may be factors affecting these declines. Notably, the negative effect of land consolidation on crop planting structure weakens when the land is further away from the city center. To ensure food security, priority should be given to follow-up management after land consolidation and rational oversight and guidance following land transfer.

Enhancing the groundwater storage estimates by integrating MT-InSAR, GRACE/GRACE-FO, and hydraulic head measurements in Henan Plain (China)

Aquifers supporting irrigated agriculture in Henan Plain in China (HNP) are under immense stress due to scarcity of surface water and over-pumping of groundwater. To assist in establishing a crop planting structure in this region that aligns more with the capacity of water resources, we have developed an enhanced methodology for estimating Groundwater Storage change (GWSC). This method integrates Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) inversion, Gravity Recovery and Climate Experiment (and Follow-on)/Global Land Data Assimilation System (GRACE/GLDAS) modelling, and hydraulic head measurements. The time-series comparisons based on well water levels and residual statistics of equivalent water thickness (EWT) validate the reliability of both MT-InSAR- and GRACE/GLDAS-derived GWSC, exhibiting a mean R-square of 0.8288 and an RMSE of 7.5 cm. The corrected and integrated GWSC significantly enhances the equal lon-lat tile of 1/4-degree (∼27 km) from CSR GRACE/GRACE-FO Mascon solution (CSR-M) to within 1 km in aquifers with known prior hydrogeological information. Furthermore, the geographic patterns analysis of GWSC in HNP using standard deviational ellipse (SDE) reveals that the central regions in HNP between the Yellow River and the Huaihe River suffer the most severe regional groundwater depletion. The depletion center has shifted to the northwest by 87 km, showing a trend of easing in the north-south direction and expanding in the east-west direction.

Deer exclusion is necessary to promote post‐fire herbaceous regeneration in the understorey of a Mediterranean forest

The frequency of severe wildfires is on the rise in the Mediterranean Basin as a result of climate change and land abandonment. Recurrent wildfires may retard or impede ecosystem recovery, frequently requiring the implementation of restoration practices. In that context, a post‐fire deer exclusion experiment was conducted in a Mediterranean mixed forest ecosystem with high population densities of deer species (Fallow deer and Red deer). A deer exclusion area was established as a form of restoration intervention to promote post‐fire vegetation recovery. We surveyed plant species during the second and third springs after fire in both deer‐excluded and deer‐allowed areas in order to detect changes in the community. We analyzed the plant species composition, species diversity, and structure of herbaceous and woody plant communities. We also compared the frequency of annual and perennial herb species, functional groups, and post‐fire plant regeneration strategies. The main differences were due to differences between springs rather than of deer‐excluded and deer‐allowed plots. Deer consumed both woody and herbaceous species, favoring the assemblage of herbaceous over woody species. Deer favored the establishment of annual forbs, including unpalatable and/or exotic species, while limiting the abundance of graminoids. Observed deer impacts could have been magnified during the second spring by a drought. Our study demonstrates that deer exclusion can be an effective restoration practice for promoting post‐fire herbaceous regeneration in forests with significant densities of wild ungulates, although seasonal effects may override restoration practice effects.

Installation of portals in the sections of the column demolition during the re-equipment of Tagmet JSC workshops

Introduction. The article presents the materials on the activities, carried out in the pipe rolling shops of the Tagmet JSC during the modernization period, starting from 2007. The Research Institute of Building Constructions named after V.A. Koucherenko, conducted prolonged surveys of plant workshop structures in order to issue conclusions on their industrial safety and recommendations for the repair and strengthening of damaged elements in building structures for their further safe operation, including workshops, where the technological process has been changed due to the installation of new equipment.Aim. To demonstrate one of the ways to reconstruct industrial buildings using the example of workshops, located in the territory of the Tagmet JSC, based on a survey of combined structures, calculations and analyzes of their bearing capacity margins.Materials. The article provides the drawings of original metal structures and photographs of steel structures, already built to reinforce them and change the existing parameters of the building frame to suitable ones for new operating conditions.Results. Recommendations for structural strengthening, applicable for similar activities, are given. Due to the scientific and technical support for the design and construction of three modernized Tagmet workshops, the plant continuously increased its productivity in subsequent years.Conclusions. No defects and damage, which exceed the values, established by the current regulatory documents, and affect the operational suitability of buildings, were revealed during the inspection and operational safety examination of Tagmet plant structures. The results of the calculations, performed to the portal structures at the column demolition sections of the plant workshop building frames, proved the assurance of their strength and stability. The design solutions were successfully implemented during the reconstruction of workshops at the Tagmet JSC.

Metabolic engineering of Oryza sativa for lignin augmentation and structural simplification.

The sustainable production and utilization of lignocellulose biomass are indispensable for establishing sustainable societies. Trees and large-sized grasses are the major sources of lignocellulose biomass, while large-sized grasses greatly surpass trees in terms of lignocellulose biomass productivity. With an overall aim to improve lignocellulose usability, it is important to increase the lignin content and simplify lignin structures in biomass plants via lignin metabolic engineering. Rice (Oryza sativa) is not only a representative and important grass crop, but also is a model for large-sized grasses in biotechnology. This review outlines progress in lignin metabolic engineering in grasses, mainly rice, including characterization of the lignocellulose properties, the augmentation of lignin content and the simplification of lignin structures. These findings have broad applicability for the metabolic engineering of lignin in large-sized grass biomass plants.

A multi-scale semantic feature fusion method for remote sensing crop classification

The efficient and accurate acquisition of crop spatial planting structure information is of great significance to ensure national food security. Current crop classification studies have still not achieved optimal results in accurate crop classification identification due to the complex heterogeneous details of clear images and insufficient analysis and utilization of information. This study takes the Yuncheng-Linfen Basin in Shanxi, China as the study area and uses the ReliefF-RFE feature selection algorithm to achieve data dimensionality reduction. Contextual semantic feature aggregation, spatial channel attention mechanism, and hierarchical refinement strategy are used to fuse the multi-scale feature information in the extracted remote sensing images from the top down and bottom up. This study shows that 1) the ReliefF-RFE algorithm can effectively reduce the dimensionality of 224-dimensional multisource features and generate a 31-dimensional optimal feature space subset with strong interpretation to improve the computational efficiency of the model; 2) the multi-scale feature fusion model constructed in this study is better than UNet, ResNet, DeepLabv3+, HRNet and Swin Transformer in classification recognition of winter wheat and corn, with an overall accuracy of 95.76% and 93.44%; 3) A multiple feature fusion strategy designed through ablation experiments was evaluated to evaluate the reasonableness of each module and validate the irreplaceability and superiority of the model for improving crop accuracy in complex and heterogeneous terrain; 4) the multi-scale feature fusion model converts deep abstract features into local detail information by cross-scale contextual aggregation of deep and shallow multi-scale features, it obtains good extraction effect on fragmented small plots, and the reduction of local fine details of features is significantly better than other models. The multi-scale feature fusion classification model constructed in this study fully considers the interpretability of the input features and fuses the semantic features at different scales to eliminate the “semantic gap”, which shows that the model has strong stability and robustness and provides a reference for fast and accurate mapping of Sentinel-2 images of crops in large areas.

Analysis and prediction of crop water footprints in the Fen River Basin of Shanxi Province, China

In China, the major water user is agriculture. Under the background of climate change and with the pressure of scarce water resources, the study of crop water footprints serves as a theoretical basis for regional optimization of water resource management, fine-tuning crop planting structures and actively addressing the negative impacts of climate change on agricultural production, among other critical issues. Leveraging meteorological and agricultural data, we employed Taiyuan which is situated in Fen River Basin as our focal research subject and calculated and analyzed the water footprint variations concerning six major food crops—wheat, corn, grain, sorghum, soybean, and potato—from 2000 to 2020. Through meticulous examination, we identified the predominant contribution of blue water (45 %) to the total water footprint, followed by green water (39 %), with grey water playing the smallest role (16 %), indicating that the use of water for crops in the Fen River Basin mainly consumes surface water and groundwater. Our investigation reveals a complementary association between blue water and green water, while both blue water and grey water exhibit an overall declining tendency from 2000 to 2020. Moreover, our predictive modeling of food crop water footprints, considering various SSPs-RCPs scenarios refered from IPCC, points towards a peak within the coming 10–20 years, with a growth rate of 16.2 % to 33.0 %, followed by a subsequent decline. Particularly, in SSP3-7.0 scenario, the water footprint of food crops presents the highest, with a growth rate of up to 33.0 % because of the continuous growth of population and the increase of crop sowing area, while in SSP1-2.6 scenario, the water footprint of food crops shows the lowest, with a growth rate of 16.2 % because of the decrease in population and crop sowing area, before the middle of the current century.

Identification and Analysis of Long-Term Land Use and Planting Structure Dynamics in the Lower Yellow River Basin

Accurate identification of the spatio-temporal planting structure and analysis of its driving factors in an irrigation district are the important bases for scientific and reasonable utilization of irrigation water resources. In pursuit of this goal, the training sample migration method combined with the random forest algorithm were used to classify land use and planting structure over 2001–2022 in the lower Yellow River Basin. Moreover, an econometric regression model was applied to quantify the driving factors of the change in the crop-planted area. The results illustrated that the identification method has relatively high accuracy in identifying historical periods of land use and planting structures, with the average kappa coefficient equating to 0.953. From 2001 to 2022, the area of cultivated land was the largest, with the proportion of the total area increasing from 45.72% to 58.12%. The planted area of winter wheat–summer maize rotation increased from 74.84% to 88.11% of the cultivated land. While the planted area of cotton declined by 96.36%, about 50% of cotton planting was converted to the winter wheat–summer maize rotation planting. The government policies about grain purchase and storage were the dominant factors for the change in the crop-planted area. This resulted in an increase of 63.32 × 103 ha and 63.98 × 103 ha in the planted area of winter wheat and summer maize, respectively. The findings are of great significance to the allocation of water resources in irrigation districts of the lower Yellow River Basin.