Single Plot Research Articles

Physicochemical Rationale of Matrix Effects Involved in the Response of Hydrogel-Embedded Luminescent Metal Biosensors

There is currently a critical need for understanding how the response and activity of whole-cell bacterial reporters positioned in a complex biological or environmental matrix are impacted by the physicochemical properties of their micro-environment. Accordingly, a comprehensive analysis of the bioluminescence response of Cd(II)-inducible PzntA-luxCDABE Escherichia coli biosensors embedded in silica-based hydrogels is reported to decipher how metal bioavailability, cell photoactivity and ensuing light bioproduction are impacted by the hydrogel environment and the associated matrix effects. The analysis includes the account of (i) Cd speciation and accumulation in the host hydrogels, in connection with their reactivity and electrostatic properties, and (ii) the reduced bioavailability of resources for the biosensors confined (deep) inside the hydrogels. The measurements of the bioluminescence response of the Cd(II) inducible-lux biosensors in both hydrogels and free-floating cell suspensions are completed by those of the constitutive rrnB P1-luxCDABE E. coli so as to probe cell metabolic activity in these two situations. The approach contributes to unraveling the connections between the electrostatic hydrogel charge, the nutrient/metal bioavailabilities and the resulting Cd-triggered bioluminescence output. Biosensors are hosted in hydrogels with thickness varying between 0 mm (the free-floating cell situation) and 1.6 mm, and are exposed to total Cd concentrations from 0 to 400 nM. The partitioning of bioavailable metals at the hydrogel/solution interface following intertwined metal speciation, diffusion and Boltzmann electrostatic accumulation is addressed by stripping chronopotentiometry. In turn, we detail how the bioluminescence maxima generated by the Cd-responsive cells under all tested Cd concentration and hydrogel thickness conditions collapse remarkably well on a single plot featuring the dependence of bioluminescence on free Cd concentration at the individual cell level. Overall, the construction of this master curve integrates the contributions of key and often overlooked processes that govern the bioavailability properties of metals in 3D matrices. Accordingly, the work opens perspectives for quantitative and mechanistic monitoring of metals by biosensors in environmental systems like biofilms or sediments.

The Digital Superhero: Conspiracy and Convergence

ABSTRACT The superhero is a popular figure in contemporary media: not just single characters, plots and movies, but entire universes and ‘phases’ spread across multiple protagonists, narrative arcs, devices, mediums and formats, from films and television shows to video games and books. Across much content, a reliance on conspiracy is evident: to motivate characters, link together plots, and move them across time and space. This article articulates paranoia and conspiracy as an emergent aesthetic bound up with the affordances of digital technology. It thus articulates these aesthetic impulses as the outcome of a cultural logic of convergence embodied in the affordances and demands of digital technologies and ecosystems. Considering the three aspects of convergence culture identified by Henry Jenkins (technology, culture, participation), and how they operate within superhero media under the aegis of digitization, this article discusses their penumbra: conspiratorial technology, conspiratorial culture, and conspiratorial participation.

Collapsible tree: interactive web app to present collapsible hierarchies.

A crucial component of intuitive data visualization is presenting a hierarchical tree structure with interactive functions. For example, single-cell transcriptomics studies may generate gene expression values with developmental trajectories or cell lineage structures. Two common visualization methods, t-SNE and UMAP, require two separate figures to depict the distribution of cell types and gene expression data, with low-dimension projections that may not capture the hierarchical structures among cells. Here, we present a JavaScript framework and an interactive web app named Collapsible Tree, which presents values jointly with interactive, expandable, and collapsible lineage structures. For example, the Collapsible Tree presents cellular states and gene expression from single-cell transcriptomics within a single hierarchical plot, enabling comparisons of gene expression across lineages and subtle patterns between sub-lineages. Our framework can facilitate the exploration of complicated value patterns that are not evident in UMAP or t-SNE plots. The Collapsible Tree web interface is available at https://collapsibletree.data2in.net. The JavaScript library source code is available at https://github.com/data2intelligence/collapsible_tree.

Microbial Fertilizing Products Impact on Productivity and Profitability of Organic Strawberry Cultivars

Poland is a major producer of various fruits, including strawberries. As growing consumer awareness of food quality, health, and wellbeing is increasing, farmers are receiving a new market opportunity for organic products of good quality. The integration of microbial solutions into agricultural practices can foster the transition of agricultural farms towards more resilient and sustainable production of quality food. The objective of this study was to assess the influence of novel microbial biopreparations (microbial fertilizing products) containing Bacillus sp., humic acids, and other organic compounds on the economic viability of three strawberry cultivars (‘Honeoye’, ‘Vibrant’, and ‘Rumba’) under organic farming conditions. This study was conducted in 2021 as a field experiment. Irrigated and non-irrigated strawberries were treated with five microbial fertilizing products (K2–K6). The single plot area was 16 m2, with a total of 144 plots. The adopted planting density of strawberries was 30,052 per hectare. K3 treatment was found to be the most universal microbial treatment in terms of positive impact on yields, with significant yield increase on both the non-irrigated (yield increase of 3.76 t·ha−1) and irrigated experiments (yield increase of 5.78 t·ha−1). The K4 treatment on the non-irrigated strawberries resulted in a yield increase of 4.96 t·ha−1, which at the same time had no effect on the yield of the irrigated experiment. On average, application of the K2–K6 combinations on the non-irrigated strawberries resulted in a yield increase from 13.4% (K2) to 33.5% (K4). The irrigated strawberries showed a yield increase from 3.9% (K4—non-significant yield increase) to as much as 36.1% (K3). The highest direct surplus for the non-irrigated strawberries was recorded for the K4 treatment (38,603 PLN·ha−1) and for K3 for the irrigated experiment (42,945 PLN·ha−1). The direct surplus for ‘Rumba’ and ‘Vibrant’ was higher than for ‘Honeoye’ on both the irrigated (22% and 53%, respectively) and non-irrigated (19% and 18%, respectively) experiments. The average profitability index for all tested non-irrigated and irrigated varieties improved when treated with microbial fertilizer products, with profitability indexes of 143.3–168.8% on the non-irrigated plantation and 129.2–169.7% on the irrigated plantation. The tested microbial fertilizing products proved to be valuable products to improve the productivity and economic effectiveness of organic strawberry production. At the same time, their use needs to be adapted to local plantation conditions.

The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests

Abstract. Process-based ecosystem models are increasingly important for predicting forest dynamics under future environmental conditions, which may encompass non-analogous climate coupled with unprecedented disturbance regimes. However, challenges persist due to the extensive number of model parameters, scarce calibration data, and trade-offs between the local precision and the applicability of the model over a wide range of environmental conditions. In this paper, we describe a protocol that allows a modeller to collect transferable ecosystem properties based on ecosystem characteristic criteria and to compile the parameters that need to be described in the field. We applied the procedure to develop a new parameterisation for European beech (Fagus sylvatica L.) for the Biome-BGCMuSo model, the most advanced member of the Biome-BGC family. For model calibration and testing, we utilised multiyear forest carbon data from 87 plots distributed across five European countries. The initial values of 48 new ecophysiological parameters were defined based on a literature review. The final values of six calibrated parameters were optimised for single sites as well as for multiple sites using generalised likelihood uncertainty estimation (GLUE) and model output conditioning that ensured plausible simulations based on user-defined ranges of carbon stock output variables (carbon stock in aboveground wood biomass, soil, and litter) and finding the intersections of site-specific plausible parameter hyperspaces. To support the model use, we tested the model performance by simulating aboveground tree wood, soil, and litter carbon across a large geographical gradient of central Europe and evaluated the trade-offs between parameters tailored to single plots and parameters estimated using multiple sites. Our findings indicated that parameter sets derived from single sites provided an improved local accuracy of simulations of aboveground wood, soil, and litter carbon stocks by 35 %, 55 %, and 11 % in comparison to the a priori parameter set. However, their broader applicability was very limited. A multi-site optimised parameter set, on the other hand, performed satisfactorily across the entire geographical domain studied here, including on sites not involved in the parameter estimation, but the errors were, on average, 26 %, 35 % and 9 % greater for the aboveground wood, soil, and litter carbon stocks than those obtained with the site-specific parameter sets. Importantly, model simulations demonstrated plausible responses across large-scale environmental gradients, featuring a clear production optimum of beech that aligns with empirical studies. These findings suggest that the model is capable of accurately simulating the dynamics of European beech across its range and can be used for more comprehensive experimentations.

Evaluation of Banana Varieties through Farmer’s Participatory Selection at Teppi, Southwestern Ethiopia

Participatory varietal selection was conducted in Southwestern part of Ethiopia to evaluate the performance of banana cultivars and to identify farmers’ preference and selection criteria in the study area. Seven banana cultivars collected from Melkassa agricultural research center were evaluated in single plot in 2020-2023 main cropping season. Farmers’ evaluation was made at two different stages of the crop, namely at vegetative and at maturity using both direct-matrix and pair-wise ranking methods of selection scheme. Farmers’ set; plant height, disease resistance/tolerance, fruit size and yield as selection criteria to evaluate and identify their preferred cultivars. The results of analysis of variance indicated the existence of highly significant differences among cultivars for all traits measured at 5% probability level. From the previous experiments, the highest mean yield was obtained from the cultivar William I (45.32 t/ha), Dinke-1 (45.1 t/ha), Lady Finger (40.16 t/ha) and Poyo (40 t/ha). Likewise, these three cultivars (William, Dinke-1, and Lady Finger) were identified as farmers preferred cultivars from both pair-wise and direct matrix ranking evaluations. Thus, these cultivars were chosen for their performance in the field and from farmers' evaluation perspective. Moreover, this study indicated participatory varietal selection is a viable method to gain greater insight into farmers’ perceptions, preferences, merits and shortcomings of banana cultivars. Therefore, based on the results of this study, William I, Dinke-1 and Lady Finger cultivars are recommended for multiplication and distribution to farmers in the area and similar agro-ecologies.

Evaluation of Hot Pepper Varieties through Farmer’s Participatory Selection at Teppi area, Southwestern Ethiopia

Three hot pepper varieties were evaluated in single plot in 2022/23 main cropping season. Farmers’ evaluation was made at two different stages of the crop, namely at vegetative and at maturity using both direct-matrix and pair-wise ranking methods of selection scheme. Farmers’ set; green pod yield, disease tolerance, pod color and size as selection criteria to evaluate and identify their preferred varieties. The results of analysis of variance indicated the existence of highly significant differences among varieties for all traits measured at 5% probability level. The highest mean green pod yield was obtained from the variety Melka Awaze (11.39 t/ha) and Melka Zala (8.39 t/ha). Likewise, these two varieties were identified as farmers preferred varieties from both pair-wise and direct matrix ranking evaluations. Thus, the varieties Melka Awaze and Melka Zala were chosen for their performance in the field and from farmers' evaluation perspective. Moreover, this study indicated participatory varietal selection is a viable method to gain greater insight into farmers’ perceptions, preferences, merits and shortcomings of hot pepper varieties. Therefore, based on the results of this study, Melka Awaze and Melka Zala varieties are recommended for multiplication and distribution to farmers in the area.

Numerical and Symbolic Analysis for Mathematical Problem-Solving with Maple

This study explores the versatile capabilities of Maple, a widely used mathematical software, in addressing a wide range of numerical and symbolic computations essential for scientific and engineering applications. The researchers investigated Maple's diverse suite of tools, including numerical integration, nonlinear equation solving, polynomial interpolation, symbolic integration, and various numerical methods. Through an in-depth literature review, illustrated case studies, and detailed performance evaluations, the paper demonstrates the effectiveness and accuracy of Maple's computational approaches in dealing with complex problems in various areas of applied mathematics. This study's findings underscored Maple's tremendous value as a reliable and comprehensive software package for researchers, scientists, and professionals involved in advanced mathematical analysis and scientific computing. Furthermore, the paper highlighted Maple's versatility in creating high-quality three-dimensional plots, crucial for visualizing and analyzing complex mathematical and scientific data. Using either sets or lists, the ability to display multiple surfaces in a single three-dimensional plot showcases Maple's power in data visualization and communicating complex ideas. By positioning Maple as a powerful platform for solving versatile mathematical problems, this study highlights the software's indispensable role in advancing scientific discoveries and engineering innovations.

Improving Project Forecasting Accuracy by Developing the Normalised Project Management Baseline

Periodic project reporting using Earned Value Management (EVM) and Earned Duration Management (EDM) uses performance metrics to communicate current and forecast future project performance. The likely accuracy ranges of schedule and cost forecasts are commonly expressed as a simple plus or minus percentage or value. This paper introduces the Normalised Project Management Baseline (NPMB), a single (x, y) plot of the normalised EDM and EVM Project Management Baselines to identify whether periodic project forecasts are optimistic (low) or pessimistic (high), as well as informing the magnitude of variation in the forecast. The NPMB is tested using six real-life completed projects and it is shown to be highly suited to identifying schedule forecast optimism, pessimism, and variations, whilst results for cost are highly promising and warrant further investigation. For project practice the NPMB increases awareness of performance variations, improving forecasting accuracy and confidence in final forecast ranges. For academia, the NPMB introduces new research directions by improving forecasting accuracy and early warning processes by improving the accuracy of periodic project performance observations. This paper contributes to project management literature as the NPMB is the first attempt to improve forecasting accuracy by identifying variations in the periodic project performance observations themselves.

Multiscale spatial variability in land and water productivity across the Gezira irrigation scheme, Sudan

Agricultural performance assessment spans various spatial scales, from single plots to entire irrigation systems. A multi-scale analysis is thus crucial for informed decision-making. The Gezira irrigation sScheme in Sudan is a longstanding large-scale irrigation system experiencing severe water management challenges, manifested by low land productivity, water productivity, and irrigation efficiency. Recognizing the interdependence of decision-making, this research focuses on variations in water and land productivity at different spatial scales within the Gezira irrigation scheme. As one of the world’s largest gravity-irrigated systems, covering 2.1 million feddan (1 feddan = 0.42 ha ∼ 1 acre), the scheme serves as an interesting case to study head-tail performance variations across four spatial scales: tertiary, secondary, and major units, and the whole scheme. This study is centered on the winter season wheat cultivation 2022–2023, and employs the FAO’s Water Productivity Open Access Portal (WaPOR v2.1) datasets, with 100 m resolution, for computing land and water productivity. Ground-observed yield data from nine tertiary units (nimras) in the Wadelbur irrigation division were used to validate WaPOR. The results showed a systematic underestimation of WaPOR derived land productivity by about 40 % compared to the ground dataset. The head-tail analysis of land and water productivity reveal contrasting results at different scales. At tertiary and secondary scales, no correlation exists between distance from offtake and productivity. At the major unit (irrigation division), a moderate correlation is observed: 0.7 for land productivity, and 0.6 for water productivity. At the scheme scale, the correlation factors are somewhat lower for land productivity (0.4) and the same for water productivity (0.6). At the largest scale, the productivity appears to increase from head to tail divisions, suggesting potential overirrigation and waterlogging in the head parts leading to reduced productivity. Another possibility is the presence of better agricultural practices in the tail areas compared to the head.

Multidimensional data visualization and synchronization for revealing hidden pandemic information

Visualization is integral to uncovering hidden information in data and providing users with intuitive feedback for decision-making. Data visualization is crucial for transforming complex data into actionable insights across various domains. In recent years, coronavirus disease vaccines have become increasingly available to much of the population. However, the CDC (Centers for Disease Control and Prevention) often fails to consider multidimensional coronavirus pandemic data from a side-by-side perspective, limiting the ability of medical professionals and individuals to compare and interact with comprehensive data visualizations. Effectively displaying coronavirus and vaccination data collected from multiple sources is essential for interpreting pandemic transmission patterns and vaccine efficiency. This paper presents a new platform for innovative data visualizations that offers users intuitive feedback and a complete data story. We designed algorithms to seamlessly combine multiple parameters, synchronize attributes, and dynamically visualize data over time on a single webpage. Instead of integrating all attributes into a single plot, which can be overwhelming due to space limitations and make it difficult to extract crucial information from overcrowded display components, we developed algorithms to classify, enhance, and group all parameters based on their relationships and similarities. Furthermore, a side-by-side visualization method was created to dynamically link all parameters in multiple images for data exploration, trend comparison, hidden information detection, and correspondence analysis. Our platform provides real-time performance, enabling healthcare professionals to make informed decisions, communicate findings effectively, and uncover patterns that might not be apparent in raw data. The proposed multidimensional data visualization algorithms have broad applications in general data exploration and revealing hidden information.

Utility-based performance evaluation of biometric sample quality measures

The quality score of a biometric sample is intended to predict the sample’s degree of utility for biometric recognition. Different authors proposed different definitions for utility. A harmonized definition of utility would be useful to facilitate the comparison of biometric sample quality assessment algorithms. In this article, we compare different definitions of utility and apply them to both face image and fingerprint image data sets containing multiple samples per biometric instance and covering a wide range of potential quality issues. The results differ only slightly. We show that discarding samples with low utility scores results in rapidly declining false non-match rates. The obtained utility scores can be used as target labels for training biometric sample quality assessment algorithms and as baseline when summarizing utility-prediction performance in a single plot or even in a single figure of merit.

Transmission anomalies in 2D photonic crystals from the checkerboard family: from broken to hidden symmetries and plasmon “spoofing”

In a field representation, the main symmetry of the electromagnetic response of complementary metal film structures is described by the Babinet principle, which is expected to be strictly obeyed by structures in vanishingly thin films of a perfect electric conductor. On the other hand, a softer version of this based on transmittance, the transmittance Babinet principle (TBP), is not so restrictive. The goal of this work is to study how severely this broken symmetry affects the optical response of such structures. We consider two geometrically distinct series of planar complementary structures from the checkerboard family: regular and bowtie. The self-complementary structure of these series is known to be very singular and breaks even the rigorous Babinet principle. Here, we study complete simulated transmittance spectral maps (T-Maps), which accumulate the whole spectral response of an entire series of structures in a single plot. The ab initio simulated T-Maps of these 2D photonic crystals were simulated for linearly polarized waves propagating perpendicular to these planar structures, made in a vanishingly thin film of a perfect electric conductor. While we confirm the expected long wavelength validity of the TBP, we show that in the frequency range where diffraction effects dominate, the standard derivation of the TBP no longer applies, and with the help of our T-Maps, we demonstrate a total collapse of the TBP in the structures considered. We show that this broken symmetry practically eliminates all but one transmission band on the hole side of the T-Maps and that the remaining strong band is a “spoof” plasmon, free of multiple frequency replicas, an important feature for optical filter applications. In addition, by symmetry arguments and simulations, we discovered that the T-Maps for bowtie and doubled-period regular structures are identical. We discuss how this hidden symmetry can benefit various applications by providing a convenient scaling, whereby simplified structures can deliver a tailored response.

New Zealand's planted forests–Carbon stocks and yield in fast growing exotic tree plantations of the Southern Hemisphere

Every year New Zealand measures 1/5th of the permanent sample plots of the National Planted Forest Inventory administered by the Ministry for the Environment (MFE). This means that all plots are measured once during a five-year cycle to provide the full inventory, while each measurement year in its own right provides a random nationally-representative sample of New Zealand's plantation forests.Land-use change and planted forest area are highly dynamic in New Zealand compared to forests in many northern hemisphere countries and every year new plots are added to the inventory due to new afforestation areas. Over time, old plot data representing stands that have been recently harvested will be replaced with measurements of the new forests growing on these sites or will drop out altogether due to improvements in mapping or deforestation. This means that estimates from a single year's plot measurements can give different results from the previous year due to the changes that the plantation forest estate experiences from year to year.In this paper we analyse results for the latest measurement cycle (Panels 2016 - 2020) and identify any issues or trends in carbon stocks. We use all panel data plus data from previous periodic forest inventories to generate a fully representative yield table for all plantation forests in the sub-categories of Kyoto Protocol-compliant afforestation and other planted forests (“non-Kyoto”). Furthermore, we use an imputation approach to provide a statistically accurate representation of stock changes over time. The yield tables generated are used in MFE's Land Use Carbon Analysis System (LUCAS) to generate estimates of carbon stocks and stock changes for international reporting.The estimated mean carbon sequestration rate over the typical rotation for New Zealand's dominant plantation species is higher than the default range provided by the IPCC (Intergovernmental Panel on Climate Change). Predicted carbon sequestration in non-Kyoto planted forests (10.5 tC ha−1 yr−1) exceeds the estimated carbon sequestration in Kyoto-compliant planted forests (9.8 tC ha−1 yr−1) with both at the upper range of estimates for temperate plantation forests (IPCC). Current mean carbon stocks are significantly larger in Kyoto-compliant plantation forests (169 tC ha−1) than in non-Kyoto planted forests (108 tC ha−1) across New Zealand, largely because they are on average five years older. Estimated Mean annual increment, m3 ha−1 yr−1 expressed as a comparable index (“300Index”) indicates that Kyoto-compliant forest land has slightly higher productivity than non-Kyoto planted forests, but because the latter are composed of younger stands, greater carbon sequestration rates but lower current stocks are estimated. Plots with slower growing tree species such as Douglas-fir, cypresses and coastal redwood are now an increasing part of the Kyoto-compliant estate, reducing the overall sequestration rates for this forest type.

Simulation of functional additive and non-additive genetic effects using statistical estimates from quantitative genetic models

Stochastic simulation software is commonly used to aid breeders designing cost-effective breeding programs and to validate statistical models used in genetic evaluation. An essential feature of the software is the ability to simulate populations with desired genetic and non-genetic parameters. However, this feature often fails when non-additive effects due to dominance or epistasis are modeled, as the desired properties of simulated populations are estimated from classical quantitative genetic statistical models formulated at the population level. The software simulates underlying functional effects for genotypic values at the individual level, which are not necessarily the same as effects from statistical models in which dominance and epistasis are included. This paper provides the theoretical basis and mathematical formulas for the transformation between functional and statistical effects in such simulations. The transformation is demonstrated with two statistical models analyzing individual phenotypes in a single population (common in animal breeding) and plot phenotypes of three-way hybrids involving two inbred populations (observed in some crop breeding programs). We also describe different methods for the simulation of functional effects for additive genetics, dominance, and epistasis to achieve the desired levels of variance components in classical statistical models used in quantitative genetics.

Evaluation of sugar content and bioethanol production of Ethiopian local varieties “Nech Tinkish” and “Hawaye” sweet sorghum (Sorghum bicolor (L.))

Diversifying the use of climate-smart crops such as sweet sorghum has the potential to solve integrated food, bioenergy, feed, and land management problems. The study’s purpose is to quantify the sugar content of Nech Tinkish (v1) and Hawaye (v2) Ethiopian sweet sorghum varieties and investigate the interaction effect of fermentation parameters to determine their capacity for ethanol production. Sweet sorghum varieties were analyzed to determine their difference in °Brix content by extracting their juices. The juice was clarified using milk lime. Its total soluble sugars, total carbohydrates, and reducing sugars were determined using a digital refractometer, phenol sulfuric acid, and 3,5-dinitrosalicylic acid, respectively. A completely randomized factorial was employed to evaluate ethanol production capacity, and the ethanol content was estimated using a potassium dichromate solution. The °Brix results revealed that v2 had a higher sugar concentration than v1. Additionally, the estimated carbohydrate content of the juice ranged from 37.402 to 157.641 g/L. The estimated reducing sugar also varied from 4.644 to 33.412 g/L. Therefore, the estimated reducing sugar showed the hydrolysis of sweet sorghum juice by invertase and sulfuric acid produced more fermentable sugars. Fermentation at 30 °C with pH 4.5 incubated for 4 days yields the highest ethanol, and v2 yields higher (15.31%) ethanol, compared to v1 produced 14.85%. This study showed a basis for the existence of two sugar-rich climate smart sweet sorghum varieties with an extraordinary amount of sugar used as a source of biofuel and food simultaneously in a single plot of land.

Comparison of toxicity of some synthetic insecticides against thrips (Thrips tabaci) on cotton crop under different irrigation regimes

Cotton is the main cash crop and back bone of agriculture. However, its yield is decreasing due to insect pests attack. Among them, sucking insect pests are serious problem in cotton and various agricultural crops. Hence, present research work was executed to assess the toxicity of some synthetic insecticides against Thrips tabaci in cotton crop. The research trial was executed with varied planting geometry under different irrigation regimes. Sowing of the cotton crop was done with plant to plant distance of 30 and 60 cm while row to row distance was 4 ft. apart. The plants were irrigated under single lateral and double lateral arrangements of drip irrigation while control plot was irrigated through conventional surface irrigation method. Results of relative incidence of thrips population on different irrigation plots showed that highest thrips population (19.43/plant) was noted in case of flood irrigated plot having plant to plant distance of 30 cm followed by in double lateral drip irrigation plot (15/plant) and single lateral plot (13.10 thrips/plant). Comparatively lower mean thrips population values; 16.30, 12.40 and 10.56 thrips/plant, respectively were recorded in experimental plot under 60 cm plant to plant distance. Toxicity bioassays revealed that highest reduction (75.27%) was recorded in spinetoram while lowest thrips population reduction (28.18%) was recorded in case of spinosad. It can be concluded that spinetoram can be effective tool for efficient control of thrips leading to augmentation in cotton crop yield.

Soil structure and solute transport pathways in biogas digestate-amended soils

Here, we investigated the effects of biogas digestate application on flow pathways and soil properties in a sandy soil aiming at unraveling phosphorus accumulation and depletion processes in fertilized soils. Dye tracer experiments were conducted to visualize and distinguish between various flow pathways, while X-ray tomography was utilized to characterize the soil structure. The dye tracer experiments revealed differences between the control and the digestate-treated group of soil profiles in the top-soils although no statistical verification was possible amid a single plot per treatment. The stained soil profiles in both treatments indicate extensive areas of homogeneous and heterogeneous matrix flow. However, the digestate-treated group showed a decrease in homogeneous matrix flow and a notable presence of preferential flow with low interaction. The application of biogas digestate impacted various soil properties, including organic carbon content, water drop penetration time, and pH levels. Accordingly, the topsoil experienced an increase in soil organic carbon, water repellency, and a decrease in pH levels. The fraction of macropores also increased in the topsoil of the digestate-treated group, accompanied by an increase in tortuosity.Double lactate-extractable phosphorus (DL-P) distribution varied across the different flow pathways, with higher concentrations detected in matrix flow and a depletion observed in preferential flow regions in both treatments. These findings confirm the close relationship between the type of flow pathway and phosphorus distribution in soils. Additionally, a significant correlation was observed between pH levels and DL-P in the digestate-treated group, indicating potential implications for phosphorus availability. Overall, the results of this study suggest that the long-term application of biogas digestate is likely to improve soil properties as related to soil organic matter content, particularly in the topsoil of sandy soils. The study highlights the significance of the prevailing flow and transport pattern on nutrient distribution, with potential implications for nutrient management in agricultural systems. While the study design presented prevents the unequivocal assignment of differences to treatment effects, our data likely illustrate the impacts of biogas digestate amendment on the investigated sandy soil.Further research should focus on assessing the long-term effects of digestate application in loamy and clayey soils.

Alur Cerpen Karya Siswa Kelas XI SMA Negeri 9 Makassar

This study aims to describe the realisation of plot used in short stories by students of class XI SMA Negeri 9 Makassar. The data in this study are in the form of words, phrases, sentences in short stories, especially plot and characteristics, as the basic material for analytical studies. The source of data in this research is students' works in the form of short story texts. Data collection techniques were carried out by writing, documentation, and reading and recording. Data analysis techniques were identification, classification, analysis, and description. The results showed that the form of plot in the short stories of students of class XI SMA Negeri 9 Makassar consisted of straight plot, back-and-forth plot, mixed plot, single plot, sub-subplot plot, dense plot, loose plot, plot of fortune, plot of character, and plot of thought

Ash dieback assessments on intensive monitoring plots in Germany: influence of stand, site and time on disease progression

AbstractSince 2002, ash dieback caused by the invasive fungus Hymenoscyphus fraxineus has been observed in Germany. The pathogen and its associated symptoms have fatal consequences for the vitality and survival of European ash (Fraxinus excelsior L.), an economically and ecologically important tree species. This study analyses the ash monitoring results of eleven intensive monitoring plots of the FraxForFuture research network distributed across Germany and focuses on within-stand differences of symptoms in dependence of small-scale site and tree properties. A cohort of 1365 ash trees was surveyed six times over three years, testing and applying a summer and a winter version of a nationally standardised ash dieback assessment key. The main disease symptoms (crown dieback and basal lesions) were more pronounced in areas with higher ash density, in edaphically moist areas (hydromorphic soils), on younger/smaller ash trees, and generally increased over time. However, the trend over time differed between single plots. In case of considering only the surviving part of the ash populations, crown condition even improved in 6/11 plots, indicating a selection process. Large basal lesions at the beginning of the observation period were a very good predictor for deadfall probability, especially on trees with lower stem diameter. Generally, ash dieback related symptoms at stem and crown were highly correlated. Silvicultural management practice in the past that actively pushed ash towards the moister end of its water demand spectrum has to be questioned in the light of ash dieback. Cost-intensive ash re-cultivation in the future—possibly with less dieback-susceptible progenies—should avoid pure ash stands and hydromorphic soil conditions.