Structural Index Research Articles

Fuzzy Synthetic Evaluation of the Barriers and Sustainable Pathways for Women During the Transition from Higher Education to Empowerment in Pakistan

This study explores the barriers that impede women’s transition from higher education to empowerment in Pakistan. It uses Fuzzy Synthetic Evaluation (FSE). By integrating qualitative and quantitative data, this research identifies six primary barriers: sociocultural values, family-related issues, freedom and mobility, violence and harassment, economic factors, and gendered norms. Data were collected through a survey of 500 women across various regions of Pakistan, with a valid response rate of 79.8% (N = 399), providing a comprehensive analysis of the most significant obstacles to women’s empowerment. The findings reveal the intricate and pervasive nature of these challenges, with sociocultural values, family-related issues, and restrictions on freedom and mobility emerging as the most critical. These traditional norms and patriarchal structures (index 3.942) significantly hinder women’s educational and professional progress. Family-related issues (index 3.840) and restrictions on freedom and mobility (index 3.820) also play a substantial role. Violence and harassment (index 3.705) further deter women from pursuing their goals, while economic factors (index 3.695) and gendered norms (index 3.631) contribute to the persistent gender disparities. This study concludes with a call to action, emphasising the urgent need to address these barriers. To boost women’s empowerment and advance gender equality in Pakistan, comprehensive solutions comprising targeted interventions, societal change, and policy reforms are required. By prioritising these challenges, stakeholders can develop practical solutions. This research provides invaluable insights for policymakers, educators, and advocates, urging them to work towards creating an inclusive and equitable environment for women’s advancement.

Applicability of soil health assessment dominated by biological indicators in facility agriculture

The minimum data set (MDS) is widely used for soil health index (SHI) assessment, with the selection of indicators being crucial. However, biological indicators are less frequently used compared to physical and chemical indicators. This study aimed to establish a biologically-centered MDS for assessing soil health in tomato facility agriculture in Ningbo. Using biochemical, microbiological, and nematode data from 60 continuous cropping soils, we identified key indicators for the MDS. Principal component analysis revealed a strong correlation between the MDS and the total data set (TDS), with the final MDS including available phosphorus, electrical conductivity, β-glucosidase, urease, bacterial Chao1 index, bacterial Shannon index, Ralstonia solanacearum, nematode Shannon index, structure index, and channel index. Random forest modeling showed that the predicted SHI had a high fit with the MDS-SHI, with bacterial and nematode Shannon indices being the most influential predictors, emphasizing the critical role of biological communities in maintaining soil health. Furthermore, the study identified three distinct phases in soil health during long-term continuous cropping: healthy (0–10 years), sub-healthy (11–15 years), and recovery (16–20 years), demonstrating the soil's potential for self-recovery. By incorporating biodiversity as a core component, this biologically-focused MDS provides a more comprehensive and precise method for evaluating soil health in facility agriculture. The findings suggest that this MDS could inform future research and applications in similar agricultural systems. Moreover, the results highlight the vital role of biodiversity in agroecosystem stability, suggesting that future soil health assessments should place greater emphasis on biological indicators to better capture the complexity of soil functions.

Exploring changes in epibenthic food web structure after implementation of a water-sediment regulation scheme

The water-sediment regulation scheme (WSRS) in the Yellow River is a large-scale initiative to artificially regulate the flow of sediment to the sea, thereby increasing the flood-carrying capacity of the riverbed and reservoirs. Currently, systematic studies on ecological impacts of WSRS at ecosystem-level are still insufficient. This limitation hampers the pursuit of a ‘green’, healthy, ecosystem and sustainable fisheries. This study constructed the topological structure of food webs in the Yellow River Estuary (YRE) before, during, and after implementation of the WSRS, analyzing changes in food web complexity and key species based on fishery independent data collected in June, July, and August 2023. The results showed decreases from 59 to 52 in the number of trophic species, and from 539 to 395 in the number of feeding relationships after WSRS implementation. Increased node density, decreased link density, and decreased structural complexity index also indicated a simplification of the YRE food web structure after WSRS implementation. The relatively low value of the characteristic path length indicated that the YRE food web has high connectivity with short path lengths of trophic interaction. Based on the ranking of various topological indices, Japanese seabass (Lateolabrax japonicas) and mantis shrimp (Oratosquilla oratoria) persisted as the key species. Our research revealed limited potential ecological effects that WSRS may have on the YRE food web over a short period. The effects did not persist, and omnivorous key species were identified as being critical in contributing to overall system resilience. These omnivores with high complexity, connectivity and low path lengths allowed the food web to quickly dissipate the exogenous disruption from the WSRS. This provides a theoretical basis for assessing the future ecological health and scientific management of YRE fisheries and similar large estuaries for which sediment transport mitigation is under consideration.

Seismic Response Analysis of a Vibrating Stirred Steel Fiber Concrete Frame Structure Based on Probability Density Evolution

In this paper, an experimental study of steel fiber concrete using vibration mixing technology and the probability density evolution theory is applied to establish a nonlinear stochastic seismic response model for multistory concrete frame structures considering the randomness of structural parameters. The random evolution characteristics of the structural response are studied and analyzed, and a reliability analysis method for concrete frame structures based on PDEM theory is proposed. The equations are solved by the finite difference method in the TVD format, and the probability distribution of the deformation index of the concrete frame structure is obtained by summation, where the reliability is given according to the limit value of the index. The results confirm that the PDEM theory can accurately assess the functional reliability of the structure, and it is also found that the randomness of the structural parameters has a significant effect on its nonlinear dynamic response law, and that consideration of the randomness of the structural parameters at the early stage of the design can be of great help to the seismic resistance of the structure. This study not only provides a scientific basis for the optimization of the performance of steel fiber concrete but also provides a new perspective and tool for the analysis of probability density evolution in the field of structural earthquake engineering.

Factors governing crusting formation in soils in Southern Mali, West Africa: Evaluation of susceptibility indices

In Southern Mali and neighboring semi-arid Sahel regions, soil crusting and sealing are common and significant phenomena for people who depend on agriculture for their livelihoods. These processes form hard, impermeable layers on the soil surface, reducing water infiltration, increasing runoff and erosion, and hindering germination, seedling emergence, and productivity. Factors such as rainfall intensity, topography, soil attributes, and poor management practices contribute to these phenomena. Here, we aimed to analyze soil attributes affecting crust formation and evaluate them using indicators like the structural stability index (StI), particle separability index (PSI), and crusting susceptibility index (CSI). Soils samples from agricultural and native areas in Southern Mali were analyzed for physical, chemical, mineralogical, and micromorphological attributes. Results revealed that the soils in these regions have high silt and fine sand content and low organic carbon content. Poor soil management, leading to prolonged periods of bare soils, significantly contributes to crusting. Kaolinitic clays, Ca2+ and Mg2+ contents did not appear to affect crusting. The PSI revealed a high risk of aggregate disruption in both agricultural and native lands, demonstrating soil vulnerability to degradation. The StI showed limited risk of structural degradation in native lands, while agricultural soils were more susceptible to crusting. The CSI indicated moderate crusting susceptibility across the regions. By examining the three indices related to texture attributes and organic carbon, this study provides insights into estimating susceptibility to crusting through the evaluation of the risk of soil structural degradation, particle separation, and overall soil susceptibility to surface crusting, all of which underscore the need for improved soil attributes. It emphasizes the importance of implementing effective soil management strategies, particularly the adoption of cover crops, to enhance organic carbon content and increase vegetation cover. These measures are essential for improving soil health and minimizing the risk of crusting.

Beyond the mosaic model of brain evolution: Rearing environment defines local and global plasticity.

Comparative animal studies have identified a trend toward a more global structural organization as brains become larger, suggesting that brain regions grow in sync as predicted by the concerted model of brain evolution. At the same time, brain plasticity studies have identified a boost in local brain structure triggered by the environment, suggesting that brain regions grow independently, as predicted by the mosaic model. Nevertheless, it is unclear whether the environment can also trigger shifts toward a more global brain structure, that is, whether phenotypic plasticity proceeds in a concerted fashion. Here, we examined the impact of radically different rearing environments on brain organization in a teleost fish, the three-spined stickleback (Gasterosteus aculeatus). We computed novel indices of local and global brain structure across groups reared in the two environments and entered them as predictors of differences in brain and body sizes. Changes in local brain structure predicted differences in both body and brain sizes, whereas changes in global brain structure only predicted differences in brain size. Our findings highlight the emergence of brain plasticity in a population as local and global changes that are both compatible with the concerted model.

Reliability Index for Steel Structure’s Technical State and Residual Life Assessment

The article is dedicated to problem of technical state assessment of real steel truss under operation for residual life prediction after technical investigation. The reliability index is calculated based on design, real and prospective loads. Method of statistical data analysis adopted for stress-strain determination also for all kinds of applied loads. The residual life with the reliability index determined as a transition from satisfactory to emergency technical state. The method provides the possibility for estimation of future safety steel structures operation with technical investigation results only that exclude any subjective opinion.

Study of Protein Hydration Water with the V4S Structural Index: Focus on Binding Site Description.

V4S, a new structural indicator for water specially designed to be suitable for hydration and nanoconfined contexts, has been recently introduced and preliminarily applied for water in contact with self-assembled monolayers and graphene-like systems. This index enabled an accurate detection of defective high local density water molecules (called HDA-like given their structural resemblance with the high-density amorphous ice, HDA). In the present work, we shall apply this new metric to characterize protein hydration water with particular interest in protein binding sites. As a first result, we shall find that protein hydration water has a higher concentration of HDA-like molecular arrangements compared to the bulk. Significantly, we shall show that the concentration of HDA-like molecules sharply decreases beyond the first hydration layer. Finally, we shall also reveal a highly nonuniform spatial distribution of the V4S values for the first hydration shell on the protein surface, where the higher hydrophobicity inherent to the ligand binding site will be evident from an enrichment in HDA-like molecules as compared to the population exhibited by the global protein surface.

Group-selection system as alternative management of Scots pine (Pinus sylvestris L.) forests facing climate change

AbstractThe Scots pine (Pinus sylvestris L.) is economically and ecologically the most important forest tree species in Poland with its aerial share estimated at 59% and share in growing stock at 68%. Pine forests have been managed according to even-aged silviculture for decades, resulting in a simplified structure and increased vulnerability to climatic stress. Structurally simple forests also show low resilience and adaptability to the observed global changes. The growing awareness of the risks associated with global change is drawing particular attention to the need for alternative management of pine forests that meets the expectations of the public and foresters themselves. In 1992, an experiment with uneven-aged silviculture for pine forest was established in the Gubin Forest District (western Poland). Based on data collected from 49 permanent circular plots (size of 500 m2 each) covering approximately 30 ha of Scots pine forest, the effect of such silviculture on stand structure was analyzed. Dbh, total tree height, tree status, and tree coordinates (x, y) were measured on each plot. Measurements and observations were taken twice, in 1992 and 2019. Structural indices describing different aspects (size structure, vertical structure, spatial structure) were calculated. The dynamics of the stand structure were then analyzed over 27 years, during which the forest was managed under alternative management strategies. The results showed that group-selection cuttings promote strong differentiation of stand structure. The positive effect of such silviculture can be observed in each aspect of the stand structure. Together with other research findings, the results confirm the effectiveness of this alternative silviculture to diversify simplified pine forests to be better adapted to novel environmental conditions.

Abstract 4141485: Liver Steatosis in Women with Coronary Microvascular Dysfunction

Introduction: Metabolic dysfunction-associated steatotic liver disease (MASLD) has been previously associated with coronary microvascular dysfunction (CMD) and is closely related to metabolic syndrome among men and women. Data regarding the association of quantitative liver steatosis and CMD in women with ischemia and no obstructive coronary arteries (INOCA) are scarce. Aim: To evaluate the association of liver steatosis with myocardial perfusion in women with CMD and reference controls. Methods: Women with CMD and no obstructive coronary arteries (n=55) from 2 prospective cohort studies (R01HL146158, R01HL153500) and asymptomatic age- and sex-matched reference controls (n=10) underwent stress and rest cardiac magnetic resonance imaging (MRI), with a validated MRI quantification of liver fat by proton density fat fraction (PDFF), at a single center. CMD was confirmed by coronary function testing or prior diagnostic stress tests. Parameters of liver fat and LV structure, function and myocardial perfusion reserve index (MPRI, a measure of CMD) were compared between cases and controls. A threshold of PDFF ≥5.2% was used to define significant liver steatosis. Results: Other than higher prevalence of hypertension in the CMD group, age and cardiometabolic history were not significantly different between the groups, as were the PDFF and prevalence of liver steatosis (Table). PDFF directly correlated with body mass index (r=0.41, p<0.01). There was no correlation between PDFF and MPRI (Figure). Conclusions: In this pilot study, our results suggest similar prevalence of liver steatosis between women with CMD and reference controls. Interestingly, MPRI did not correlate with PDFF, suggesting that mechanisms other than metabolic health may play a significant role in the pathophysiology of CMD among women with INOCA.

Assessment of CCMP in Capturing High Winds with Respect to Individual Satellite Datasets

High-wind structures were identified in the Cross-Calibrated Multi-Platform (CCMP) ocean wind vector reanalysis for comparison with winds measured by satellite radiometers, scatterometers, and synthetic aperture radar (SAR) instruments from February to October 2023. The comparison aims to evaluate bias, uncertainty, and spatial correlations with the goal of enhancing the accuracy of ocean wind datasets during tropical cyclones (TCs). In 10° longitude × 10° latitude blocks, each containing a TC, Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) winds are 6.5 and 4.8% higher than CCMP, while Advanced Scatterometer (ASCATB) is 0.8% lower. For extratropical cyclones, AMSR2 and SMAP also show stronger winds with a 5% difference, and ASCATB is about 0.3% weaker compared to CCMP. The comparison between SAR and CCMP for TC winds, sampled at the locations and time frames of SAR tiles, indicates that SAR winds around TCs are about 9% higher than CCMP winds. Using empirically defined TC structural indices, we find that the TCs observed by CCMP are shifted in locations and lack a compact core region. A Random Forest (RF) regressor was applied to TCs in CCMP with corresponding SAR observations, nearly correcting the full magnitude of low bias in CCMP statistically, with a 15 m/s correction in the core region. The hierarchy of importance among the predictors is as follows: CCMP wind speed (62%), distance of SAR pixels to the eye region (21%) and eye center (7%), and distance of CCMP pixels to the eye region (5%) and eye center (5%).

Soil biological health assessment based on nematode communities under maize and peanut intercropping

BackgroundCereal/legume intercropping can enhance crop productivity and improve soil health in dryland farming. However, little is known about soil biological health under maize/peanut intercropping. The aim of this study was to assess soil biological health based on nematode communities in a maize/peanut intercropping system.MethodsWe conducted a field experiment with different planting patterns, including monoculture maize (M), monoculture peanut (P), and maize intercropped with peanut (IM, intercropped maize; IP, intercropped peanut) to determine the influence on soil biological health. We measured soil physicochemical properties and nematode communities, and employed exploratory factor analysis combined with cumulative normal distribution curve scoring to identify potential soil biological health traits.ResultsThe intercropped maize gave the highest plant parasitic nematode abundance, trophic diversity index, evenness index, and structure index. The monoculture peanut gave the highest enrichment index and least plant parasitic nematode abundance, trophic diversity index, Shannon diversity index, evenness index, structure index, and channel index. We identified four soil biological health traits, including basic nutrients and biodiversity, food web complexity, slow energy channel, and fast energy channel, mainly represented by soil ammonium nitrogen and Shannon diversity index, structural index and omnivore-predator nematode abundance, fungivorous nematode abundance and plant parasitic nematode abundance, microbial biomass carbon and bacterivorous nematode abundance, respectively. The intercropping systems improved the comprehensive score of soil biological health, especially maize intercropping soil. Intercropping maize and intercropping peanut significantly improved oil biological health traits representing the food web complexity compared with the corresponding monoculture soils.ConclusionsOur results indicate that soil nematode and physicochemical indicators reflect different soil biological health traits. Among those traits, the improvement of basic nutrients and biodiversity and the complexity of the food web were the main reasons for improving soil biological health through the intercropping system.

Localized Thermoresponsive Behavior in P(NIPAm‐co‐AAc) Copolymers: Structural Insights From Rheology and Small Angle X‐Ray Scattering

ABSTRACTStimuli‐responsive polymers stand out for their ability to respond to small environmental changes. One of the most representative thermo‐sensitive materials is poly(N‐isopropyl acrylamide) (PNIPAm), which presents reversible phase transitions close to the human body temperature. However, previous studies observed that the copolymerization of NIPAm with small quantities of different monomers like acrylic acid (AAc) results in copolymers with reduced or lost thermo‐responsivity. In this study, thermo‐sensitive PNIPAm, pH‐sensitive poly(acrylic acid) (PAAc), and various proportions of their copolymers P(NIPAm‐co‐AAc) were obtained by free radical polymerization and thoroughly characterized. Rheological and structural studies reveal the remaining thermosensitivity of the copolymers manifested at short molecular ranges. These alterations in short‐range interactions are observed in all samples containing NIPAm, and they are evidenced by changes in the fractality of their structure and flow index behavior of the Viscosity Ostwald–de Waele Model. Particularly, when the copolymer proportion of NIPAm/AAc is about 40/60, the Beaucage model reveals two structural levels, ~200 and ~10 nm. Furthermore, the model exhibits a thermal response of the lower‐size substructures, indicating possible segregation of NIPAm‐rich regions from copolymer chains. The evidence found in this work could contribute to the development of nanosystems, in which local thermoresponsive effects are sought, such as for active drug targeting.

Soil nematode communities differ across long-term land-use intensities in relation to soil physical, chemical, and biological parameters

Soil disturbance, reduced crop diversity, and decreased residue in intensively managed systems can negatively impact soil biological communities and soil health. This study examined the impact of long-term (>20 years) low- (forest, grassland), medium- (diversified annual cropping), and high-intensity (annual cropping, frequently to potatoes) land-use on soil nematode communities and soil health in 59 sites across Prince Edward Island, Canada. Soil samples (0–15 cm) were collected at five locations per site and analysed for soil biological (nematode communities, respiration, soil organic matter, permanganate oxidizable carbon (POXc), soil protein), chemical (pH, N, soil N supply, extractable nutrients), and physical (bulk density, texture) properties. Soil pH and extractable nutrients were lowest in the low-intensity sites, while total C and C:N ratios were highest and decreased with increasing land-use intensity (low > medium > high). Soil respiration, POXc, and protein were lowest for high-intensity sites. Low-intensity sites had greater nematode Shannon diversity and richness, and higher maturity and structure indices than the medium- and high-intensity sites ( p < 0.05), signifying a more structured nematode community. Nematode communities from the high-intensity sites were more degraded and had significantly higher basal indices compared to the low- and medium-intensity sites. At the trophic level, the low-intensity system had higher numbers of omnivores and lower abundance of bacterivores. These differences in nematode trophic composition may result in differences in ecosystem function, including nutrient cycling and biological control.

Exponential Wiener index of some silicate networks

Any graph that depicts a particular molecular structure can be given a topological graph index, also known as a molecular descriptor. This index can be used to examine numerical data and discover more about specific physical properties of molecules. Silicates are hard crystals that can be sliced into little pieces. Therefore, silicon play a vital role in many real time applications. It is the authentic material to make microchips which run in PDA, PC and other game tools. In the current study, we have determined the new topological index for a few silicate structures, including cyclic, single-chain, and Pyro silicates by grouping the vertices of the corresponding molecular graphs based on their distance sums. This index is known as the exponential Wiener index. It is expanded to include their line graphs as well. The numerical values of exponential Wiener index and multiplicative exponential Wiener index for the molecular graphs of cyclic silicates, single chain silicates and their line graphs with n vertices where n = 3, 4, 5 are explored.

Effect of Baduanjin exercise on acute myocardial infarction in patients with anxiety and depression after percutaneous coronary intervention: A randomized controlled trial.

Acute myocardial infarction (AMI) is the most severe type of coronary heart disease and patients often require percutaneous coronary intervention (PCI). However, anxiety and depression are common complications of PCI. This study conducted a prospective randomized controlled trial to investigate the effectiveness of Baduanjin exercise in improving cardiac function and alleviating symptoms of anxiety and depression in patients who underwent PCI for AMI. Patients with AMI (n = 120) who underwent PCI at the Cardiology Department of The First Affiliated Hospital of Guangzhou University of Chinese Medicine between September 2020 and June 2021 were included. Participants were divided into a control group (moderate intensity walking) and a Baduanjin exercise group. The treatment period was 8 weeks, with follow-ups at weeks 4 and 8. Improvement of cardiac structure and function indices was measured by echocardiography. Physical function was assessed using the 6-minute walk test. Mental state was assessed using the Seattle Angina Questionnaire, Hamilton Anxiety Scale, and Hamilton Depression Scale before and after exercise. Compared to the control group, the Baduanjin exercise group showed improvement in change in left ventricular end-diastolic diameter (-1.0 ± 3.4 vs -2.3 ± 2.7 mm, respectively; P = .02), left ventricular ejection fraction (6.8 ± 4.2 vs 4.5 ± 4.3%, respectively; P = .002), angina stability (42.5 ± 31.7 vs 33.3 ± 29.7, respectively; P = .11), 6-minute walk test (118.4 ± 49.1 vs 88.3 ± 40.2 m, respectively; P < .001), and Hamilton Anxiety Scale (6.7 ± 2.6 vs 5.3 ± 2.6, respectively; P = .003), and Hamilton Depression Scale (7.6 ± 4.1 vs 4.8 ± 2.1, respectively; P < .001) scores. Baduanjin exercise for 8 weeks improved the cardiac function and mental state of patients with anxiety and depression after PCI for AMI. Through this study, we aim to provide reliable evidence in support of the beneficial effects of Baduanjin exercise on cardiac function and anxiety-depression, contributing to evidence-based medicine.

Unravelling spatial scale effects on elevational diversity gradients: insights from montane small mammals in Kenya

BackgroundMontane ecosystems play crucial roles as global biodiversity hotspots. However, climatic changes and anthropogenic pressure increasingly threaten the stability of montane community dynamics, such as diversity-elevation interactions, creating a challenge in understanding species biogeography and community ecology dynamics in these crucial conservation areas. We examined how varying sampling spatial grains influence small mammal diversity patterns within Kenya’s tallest montane ecosystems.MethodsEmploying a combination of multidimensional alpha diversity metrics and multisite beta diversity characteristics (species richness, phylogenetic and functional diversity and divergence, and multisite beta diversity) alongside spatial generalized additive multivariate regression analyses, we tested how spatial scaling influences elevational diversity gradient patterns and their associations with environmental and human activity variables.ResultsThe diversity-elevation associations were generally homogeneous across spatial grains; however, idiosyncratic patterns emerged across mountains. The total (taxonomic, phylogenetic, and functional) beta diversity, nestedness, and turnover resultant components monotonically increased or decreased with varying spatial grains. The associations between the diversity patterns and the environmental and human footprint variables increased with spatial grain size but also presented variations across mountains and indices. Species richness and phylogenetic and functional richness indices were more strongly influenced by spatial scale variations than were the divergence and community structure indices in both the diversity distribution patterns and their associations with the environmental and human variables.ConclusionsThe diversity-elevation and diversity-environment (including human activity pressure) relationships across spatial grains suggest that montane small mammal diversity patterns portray subtle but systematic sensitivity to sampling spatial grain variation and underscore the importance of geographical context in shaping these elevational diversity gradients. For improved effectiveness, conservation efforts should consider these spatial effects and the unique geographical background of individual montane ecosystems.

Multi-feature driven seismic damage state identification for reinforced concrete shear walls using computer vision and machine learning

In this paper, an image-based methodology using machine learning algorithms is developed for earthquake-induced damage state prediction in rectangular reinforced concrete shear walls. The machine learning models are developed using a database including experimental data points of 285 surface crack maps of damaged reinforced concrete shear walls collected from the literature. Eight different machine learning algorithms are utilized to train the damage-level classification models. The damage levels are defined according to the FEMA P-58 damage categories. In addition to the structural and geometric properties of the reinforced concrete shear walls with rectangular cross-section, three image-based indices including Succolarity, Lacunarity, and generalized fractal dimensions are measured as input features of the predictive models. Nine groups of features are selected as input for the machine learning algorithms. Using the GridsearchCV function, the hyperparameters resulting in the best algorithmic performance are chosen from a set of possible parameters. A five-fold cross-validation technique is applied to evaluate the models by resampling procedure. According to the results, the predictive model that uses the Extreme Gradient Boosting (XGB) algorithm with inputs that include both structural parameters and image indices performs best in terms of both overfitting prevention and classification accuracy. The outcomes of the damage state identification can be employed for safety assessment of the reinforced concrete buildings as well as repair/demolish decision-making after an earthquake.

Use of Hyperpectral Data For Chlorophyll Estimation Based on Leaf Area Indices (LAI) in Wheat

Spectral Indexes are frequently used in the estimation of green parts of plants, usually developed to reduce the spectral effects of external factors such as atmosphere and soil. The aim of this study was to evaluate the ability of different spectral indices to estimate chlorophyll in wheat according to phenological developmental stages and to calculate their optimal band combinations. In this study, chlorophyll-pigment related indices primarily used in chlorophyll estimation, as well as structural and red edge indices were used. Spectral reflectance values obtained for different phenological periods were correlated with SPAD (Minolta-502) values and Partial Least Square (PLS) model was used to calculate the prominent hyperspectral indices and their optimal band combinations. Hyperspectral multispectral data were used to calculate the amount of chlorophyll in wheat according to phenological periods, and the correlation (R²), standard error (RMSE), relative error (% RE) values obtained by evaluating the old and newly developed spectral indices together to calculate the amount of chlorophyll according to phenological periods. Many vegetation indices are strongly influenced by the unfavourable reflection properties of the soil at low LAI. As the Leaf Area Index (LAI) increases, the predictive power of the spectral index increases as the saturation effect decreases. In this study, the responses and sensitivities of different spectral indices for chlorophyll estimation against LAI change in phenological periods were investigated. As a result, the indices that were least and most affected by saturation changes were revealed. Thus, the power of the indices to predict the chlorophyll content of the canopy was demonstrated. Leaf Area Index values obtained from the experimental area in Haymanada between 2013-2014 varied between 1.08-2.81 in the early period (13 May 2014). In chlorophyll estimation, NDVI (705,750) was the least affected by the saturation change due to the increasing LAI value in the early period and showed a high correlation (LAI= 2.63, R²= 0.554). This was followed by Red Edge (740-720), (LAI= 2.63,1.722), NDVI (550,780), (LAI= 2.63,0.733), SRPI (430,680) (LAI= 2.63,0.661), LCCI (705,750) (LAI= 2.63,0.554), and NPCI (430,680) (LAI= 2.63, 0.203). These indices, which showed high correlation in the early period, were in the range of R2=0.836-0.761. In Haymana in the late period between 2013-2014 (26 May,04-12-24 June 2014) LAI values vary between 0.63-3.38 and correlation values are between R2 =0.892-0.862. MSR (705,750) was the least affected by the saturation change due to the increasing LAI value in the late period and showed high correlation (LAI=1.904, 0.906). This was followed by NDVI670 (LAI=1.904,0.703), NDVI550 (LAI=1.904,0.651) and LCCI (LAI=1.904,0.448).

Sugarcane bagasse derived biochar potential to improve soil structure and water availability in texturally different soils

Low organic matter content is one of the main constraints in arid and semiarid regions. This constraint and its negative influences on soils and plant growth may be alleviated by biochar (BC). Furthermore, improving soil physical and hydraulic attributes by application of biochar has received increased attention. Therefore, in the present study, the effects of sugarcane bagasse-derived biochar on the structural stability, water availability, and pore-size distribution (PSD) of three texturally different calcareous soils collected from different agro-climatologically regions were examined during a long-term experiment. Low and high-temperature biochars, produced in a muffle furnace by the traditional slow pyrolysis method at 300 °C (BC300) and 600 °C (BC600) were evaluated. Pots (15 kg) were filled with three different silty-clay Inceptisols (SCInc), silty-clay-loam Alfisols (SCLAlf), and loam Aridisols (LArid) soils mixed with 0 (control), 1, 2, and 3 w/w% of BC300 and BC600 during 540 days of incubation. The high energy moisture characteristic (HEMC) data was modeled using a modified van Genuchten function to quantify aggregate stability through stability ratio (SR) and structural stability index (SSI). The plant available water (PAW), least limiting water range (LLWR), and integral water capacity (IWC) were calculated with two matric suctions (h) of 330 cm for field capacity (FC) and 15,000 cm for permanent wilting point (PWP). Then the integral energy (EI) values were calculated (EIIWC). Results indicated that the incorporation of 3 w/w% biochar significantly (p < 0.01) increased SR (35 to 100%) and SSI (21 to 28%) indices in all three soils. Biochar significantly increased modal suction (MS) in LArid soils (5 to 158%); whereas, decreased MS of the other soils (3 to 43%). MS, SR, and SSI of BC300 and BC600-treated soils were not significantly different. PAW, LLWR, and IWC significantly decreased in the SCInc (18 to 61%, 8 to 44%, and 6 to 35%) and SCLAlf (8 to 44%, 18 to 35%, and 20 to 47%) soils and increased in LArid (4 to 54%, 3 to 61%, and 24 to 111%) soil with increasing biochar doses. There were no changes in EIIWC in biochar-treated LArid soil where PAW, LLWR, and IWC increased. Biochar increased EIIWC across the studied soil from 1% to 3.38 folds, thereby increasing the gradient of water potential to absorb the available water. Soil and soil-biochar mixtures exhibited heterogeneous and multimodal pore-size distribution (PSD). Biochar promoted the PSD peaks related to water-transmitting pores in SCInc and SCLAlf soils while decreased in LArid soil. In conclusion, results indicated that among the applied levels of biochar, the application of 3 w/w% biochar is suggested as a suitable way to improve soil physical behavior and structural stability.