Permalink for this collection
Browse
Recent Submissions
Publication Open Access Testing the reproducibility of active-distributed temperature sensing for measuring groundwater specific discharge beneath a braided river(Elsevier B.V., 2024-04) Sai Louie, AJ; Morgan, LK; Banks, EW; Dempsey, D; Wilson, SBraided rivers are a major contributor of groundwater recharge, yet little is known about how recharge rates vary in time. Existing methods for estimating groundwater recharge from rivers (i.e., river loss) are inadequate for studying highly heterogeneous braided river systems at a sufficient spatiotemporal resolution. To do so, active-distributed temperature sensing (A-DTS) is employed, which combines fibre optic temperature measurements with an active heat source, enabling high-resolution quantification of water fluxes. In this study, twelve successive A-DTS surveys were conducted during a 24-hour experiment on a 100 m horizontal subsurface hybrid fibre optic cable installed at 5 m depth beneath a braided river. The experiment was carried out under conditions where the river stage and flow were relatively stable to demonstrate the reproducibility and effectiveness of the A-DTS method for measuring groundwater specific discharge. This foundational work will provide a high level of confidence in the method for future studies aimed at evaluating temporal variations in groundwater recharge. The median groundwater specific discharge values calculated over the 24-hour period had a very narrow range from 3.5 to 4.0 m d‾¹ across the wetted footprint of the river, which is within the measurement error of the installation (6 %), indicating relatively stable groundwater recharge during the experiment. This provides confidence in the repeatability of the A-DTS method as an effective technology for quantifying river loss over longer time periods, to understand seasonal variability of groundwater recharge in braided river systems.Publication Open Access Conceptualising surface water-groundwater exchange in braided river systems(Copernicus Publications, 2023-12-13) Wilson, S; Hoyle, J; Measures, R; Di Ciacca, A; Morgan, LK; Banks, EW; Robb, L; Wohling, TBraided rivers can provide substantial recharge to regional aquifers, with flow exchange between surface water and groundwater occurring at a range of spatial and temporal scales. However, the difficulty of measuring and modelling these complex and dynamic river systems has hampered process understanding and the upscaling necessary to quantify these fluxes. This is due to an incomplete understanding of the hydrogeological structures which control river-groundwater exchange. In this paper, we present a new conceptualisation of subsurface processes in braided rivers based on observations of the main losing reaches of three braided rivers in New Zealand. The conceptual model is based on a range of data including: lidar, bathymetry, coring, particle size distribution, groundwater, temperature monitoring, radon-222, electrical resistivity tomography, and fibre optic cables. The combined results indicate that sediments within the recently active river braidplain are distinctive, with sediments that are poorly consolidated and better sorted compared to adjacent deposits from the historical braidplain, which become successively consolidated and intermixed with flood silt deposits due to overbank flow. A distinct sedimentary unconformity, combined with the presence of geomorphologically distinct lateral boundaries, suggests that a “braidplain aquifer” forms within the active river braidplain through the process of sediment mobilisation during flood events. This braidplain aquifer concept introduces a shallow storage reservoir to the river system, which is distinct from the regional aquifer system, and mediates the exchange of flow between individual river channels and the regional aquifer. The implication of the new concept is that surface water-groundwater exchange occurs at two spatial scales. The first is hyporheic and parafluvial exchange between the river and braidplain aquifer. The second is exchange between the braidplain aquifer and regional aquifer system. Exchange at both scales is influenced by the state of hydraulic connection between the respective water bodies. This conceptualisation acknowledges braided rivers as whole “river systems”, consisting of channels, and gravel aquifer. This work has important implications for understanding how changes in river management (e.g., surface water extraction, bank modification and gravel extraction) and morphology may impact groundwater recharge, and potentially river flow, temperature attenuation, and ecological resilience during dry conditions.Publication Open Access The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia(Springer Nature, 2023-10-05) Blasch, G; Anberbir, T; Negash, T; Tilahun, L; Belayineh, FY; Alemayehu, Y; Mamo, G; Hodson, DP; Rodrigues, FAVery high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties’ response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS–NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.Publication Open Access Determination of the oxidative stability of olive oil using an integrated system based on dielectric spectroscopy and computer vision(Elsevier on behalf of KeAi and China Agricultural University, 2019-03) Sanaeifar, A; Jafari, ADuring storage, olive oil may suffer degradation leading to an inferior quality level when purchased and consumed. Oxidative stability is one of the most important parameters for maintaining the quality of olive oil, which affects its acceptability and market value. The current methods of predicting the oxidative stability of edible oils are costly and time-consuming. The aim of the present research is to demonstrate the use of dielectric spectroscopy integrated with computer vision for determining the oxidative stability index (OSI) of olive oil. The most effective features were selected from the extracted dielectric and visual features for each olive oil sample. Three machine learning techniques were employed to process the raw data to develop an oxidative stability prediction algorithm, including artificial neural network (ANN), support vector machine (SVM) and multiple linear regression (MLR). The predictive models showed a great agreement with the results obtained by the Rancimat instrument that was used as a reference method. The best result for modelling the oxidative stability of olive oil was obtained using SVM technique with the R-value of 0.979. It can be concluded that this new approach may be utilized as a perfect replacement for quicker and cheaper assessment of olive oil oxidation.Publication Open Access Improving accuracy of quantifying nitrate removal performance and enhancing understanding of processes in woodchip bioreactors using high-frequency data(Elsevier, 2023-07-01) Rivas, A; Barkle, G; Sarris, T; Park, J; Kenny, A; Maxwell, B; Stenger, R; Moorhead, B; Schipper, L; Clague, JWoodchip bioreactors have gained popularity in many countries as a conservation practice for reducing nitrate load to freshwater. However, current methods for assessing their performance may be inadequate when nitrate removal rates (RR) are determined from low-frequency (e.g., weekly) concurrent sampling at the inlet and outlet. We hypothesised that high-frequency monitoring data at multiple locations can help improve the accuracy of quantifying nitrate removal performance, enhance the understanding of processes occurring within a bioreactor, and therefore improve the design practice for bioreactors. Accordingly, the objectives of this study were to compare RRs calculated using high- and low-frequency sampling and assess the spatiotemporal variability of the nitrate removal within a bioreactor to unravel the processes occurring within a bioreactor. For two drainage seasons, we monitored nitrate concentrations at 21 locations on an hourly or two-hourly basis within a pilot-scale woodchip bioreactor in Tatuanui, New Zealand. A novel method was developed to account for the variable lag time between entry and exit of a parcel of sampled drainage water. Our results showed that this method not only enabled lag time to be accounted for but also helped quantify volumetric inefficiencies (e.g., dead zone) within the bioreactor. The average RR calculated using this method was significantly higher than the average RR calculated using conventional low-frequency methods. The average RRs of each of the quarter sections within the bioreactor were found to be different. 1-D transport modelling confirmed the effect of nitrate loading on the removal process as nitrate reduction followed Michaelis-Menten (MM) kinetics. These results demonstrate that high-frequency temporal and spatial monitoring of nitrate concentrations in the field allows improved description of bioreactor performance and better understanding of processes occurring within woodchip bioreactors. Thus, insights gained from this study can be used to optimise the design of future field bioreactors.Publication Open Access Optimal sample size and composition for crop classification with Sen2-Agri’s random forest classifier(MPDI, 2023-02-01) Schulthess, U; Rodrigues Jr, F; Taymans, M; Bellemans, N; Bontemps, S; Ortiz-Monasterio, I; Gérard, B; Defourny, PSen2-Agri is a software system that was developed to facilitate the use of multi-temporal satellite data for crop classification with a random forest (RF) classifier in an operational setting. It automatically ingests and processes Sentinel-2 and LandSat 8 images. Our goal was to provide practitioners with recommendations for the best sample size and composition. The study area was located in the Yaqui Valley in Mexico. Using polygons of more than 6000 labeled crop fields, we prepared data sets for training, in which the nine crops had an equal or proportional representation, called Equal or Ratio, respectively. Increasing the size of the training set improved the overall accuracy (OA). Gains became marginal once the total number of fields approximated 500 or 40 to 45 fields per crop type. Equal achieved slightly higher OAs than Ratio for a given number of fields. However, recall and F-scores of the individual crops tended to be higher for Ratio than for Equal. The high number of wheat fields in the Ratio scenarios, ranging from 275 to 2128, produced a more accurate classification of wheat than the maximal 80 fields of Equal. This resulted in a higher recall for wheat in the Ratio than in the Equal scenarios, which in turn limited the errors of commission of the non-wheat crops. Thus, a proportional representation of the crops in the training data is preferable and yields better accuracies, even for the minority crops.Publication Open Access Diverse approaches to learning with immersive Virtual Reality identified from a systematic review(Elsevier, 2023-04) Won, M; Ungu, DAK; Matovu, H; Treagust, DF; Tsai, C-C; Park, J; Mocerino, M; Tasker, RTo investigate how learning in immersive Virtual Reality was designed in contemporary educational studies, this systematic literature review identified nine design features and analysed 219 empirical studies on the designs of learning activities with immersive Virtual Reality. Overall, the technological features for physical presence were more readily implemented and investigated than pedagogical features for learning engagement. Further analysis with k-means clustering revealed five approaches with varying levels of interactivity and openness in learning tasks, from watching virtual worlds passively to responding to personalised prompts. Such differences in the design appeared to stem from different practical and educational priorities, such as accessibility, interactivity, and engagement. This review highlights the diversity in the learning task designs in immersive Virtual Reality and illustrates how researchers are navigating practical and educational concerns. We recommend future empirical studies recognise the different approaches and priorities when designing and evaluating learning with immersive Virtual Reality. We also recommend that future systematic reviews investigate immersive Virtual Reality-based learning not only by learning topics or learner demographics, but also by task designs and learning experiences.Publication Open Access Simulating water and nitrogen runoff with APSIM(Elsevier, 2023-03) Vogeler, I; Cichota, R; Langer, S; Thomas, S; Ekanayake, D; Werner, ATo determine the impact of potential reductions of terrain-targeted nitrogen (N) fertilisation rates on N losses a simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). To simulate N runoff a simple approach was used, in which runoff is based on the N concentration in the soil solution and an extraction coefficient. Firstly, APSIM parameters that have the largest effect on runoff of water and N were determined for terrains with different slopes for a poorly drained silt loam. A sensitivity analysis was then conducted to assess the effect of soil hydraulic properties and soil organic carbon content on runoff losses. Finally, APSIM was set up to simulate pasture production and water and N dynamics (including pasture N uptake, leaching and N runoff) for a farm on rolling hills in South Canterbury, New Zealand. Two different fertilisation approaches were used, either scheduled or based on the aboveground N concentration of the pasture. For the poorly drained silt loam, the rainfall intensity and the surface conductance had the highest effect on the amount of water lost by runoff. Soil hydraulic conductivity at saturation and field capacity, as well as plant available water content also controlled runoff of water and N, while the organic carbon content of the topsoil had less effect on N runoff. Both the extraction coefficient and the depth considered to exchange N with the runoff water affected the amount of N lost via runoff. Using the aboveground pasture N concentration prior to fertilisation had positive effects on pasture yield and reduced N runoff losses.Publication Open Access Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning(Copernicus Publications on behalf of the European Geosciences Union, 2023) Di Ciacca, A; Wilson, S; Kang, J; Wöhling, TTransmission losses are the loss in the flow volume of a river as water moves downstream. These losses provide crucial ecosystem services, particularly in ephemeral and intermittent river systems. Transmission losses can be quantified at many scales using different measurement techniques. One of the most common methods is differential gauging of river flow at two locations. An alternative method for non-perennial rivers is to replace the downstream gauging location by visual assessments of the wetted river length on satellite images. The transmission losses are then calculated as the flow gauged at the upstream location divided by the wetted river length. We used this approach to estimate the transmission losses in the Selwyn River (Canterbury, New Zealand) using 147 satellite images collected between March 2020 and May 2021. The location of the river drying front was verified in the field on six occasions and seven differential gauging campaigns were conducted to ground-truth the losses estimated from the satellite images. The transmission loss point data obtained using the wetted river lengths and differential gauging campaigns were used to train an ensemble of random forest models to predict the continuous hourly time series of transmission losses and their uncertainties. Our results show that the Selwyn River transmission losses ranged between 0.25 and 0.65 m³ s‾¹ km‾¹ during most of the 1-year study period. However, shortly after a flood peak the losses could reach up to 1.5 m³ s‾¹ km‾¹. These results enabled us to improve our understanding of the Selwyn River groundwater-surface water interactions and provide valuable data to support water management. We argue that our framework can easily be adapted to other ephemeral rivers and to longer time series.Publication Open Access Bayesian modelling of phosphorus content in wheat grain using hyperspectral reflectance data(BMC, 2023-01-20) Pacheco-Gil, RA; Velasco-Cruz, C; Pérez-Rodríguez, P; Burgueño, J; Pérez-Elizalde, S; Rodrigues, F; Ortiz-Monasterio, I; del Valle-Paniagua, DH; Toledo, FBackground: As a result of the technological progress, the use of sensors for crop survey has substantially increased, generating valuable information for modelling agricultural data. Plant spectroscopy jointly with statistical modeling can potentially help to assess certain chemical components of interest present in plants, which may be laborious and expensive to obtain by direct measurements. In this research, the phosphorus content in wheat grain is modeled using reflectance information measured by a hyperspectral sensor at different wavelengths. A Bayesian procedure for selecting variables was used to identify the set of the most important spectral bands. Additionally, three different models were evaluated: the first model assumes that the observations are independent, the other two models assume that the observations are spatially correlated: one of the proposed models, assumes spatial dependence using a Conditionally Autoregressive Model (CAR), and the other through an exponential correlogram. The goodness of fit of the models was evaluated by means of the Deviance Information Criterion, and the predictive power is evaluated using cross validation. Results: We have found that CAR was the model that best fits and predicts the data. Additionally, the selection variable procedure in the CAR model reveals which wavelengths in the range of 500–690 nm are the most important. Comparing the vegetative indices with the CAR model, it was observed that the average correlation of the CAR model exceeded that of the vegetative indices by 23.26%, − 1.2% and 22.78% for the year 2010, 2011 and 2012 respectively; therefore, the use of the proposed methodology outperformed the vegetative indices in prediction. Conclusions: The proposal to predict the phosphorus content in wheat grain using Bayesian approach, reflect with the results as a good alternative.Publication Open Access Impact of anomalous surface boundary conditions on the planar negative-refractive index lens(John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology, 2023-02) Eccleston, KWIt is shown that anomalous boundary conditions at the surface of a negative-refractive-index metamaterial planar lens severely diminishes the resolution of the lens when its relative permittivity and permeability are both −1. Anomalous boundary conditions arise in practical microwave metamaterials that are typically a periodic array of identical unit cells comprising dielectric and conducting elements. For a unit-cell size much smaller than the wavelength, homogenised permittivity and permeability are the constituent parameters of the average fields. Average fields vary on a scale larger than the unit cell size compared to localised fields associated with the constituent elements. Unlike the tangential components of the localised field, tangential components of the average fields are discontinuous across the surface of such materials. This anomalous boundary condition at the lens surface must be described by generalised sheet transition conditions. This study develops expressions for the negative-refractive-index lens optical transfer functions, as a function of spatial frequency, for transverse-electric waves, that account for anomalous surface boundary conditions. Both the simulations and experimental data are used to verify the expressions at a frequency of 3 GHz.Publication Open Access Fuzzy logic classification of mature tomatoes based on physical properties fusion(Elsevier BV on behalf of the China Agricultural University and KeAi Communications Co. Ltd., 2021-09-16) Nassiri, SM; Tahavoor, A; Jafari, AGrading of fruits and vegetables is an initial step after harvesting. It is also an essential operation before packaging. In the present study, different fuzzy algorithms for classification of mature tomato were applied and evaluated based on combinations of fruit color, size and hardness. Fuzzy membership functions of hardness were established by subjecting samples to Instron compression test as well as the rates of panelists. Each sample was also used for image processing to determine the color and size of fruit using Matlab image processing toolbox. Color and size fuzzy membership functions were established by published standard. The fuzzy If-Then rules were applied to classify the samples within five group outputs viz. “grade I”, “grade II”, “grade I-far market”, “processing”, and “storage”. Eighty-one fuzzy rules were reduced to 25 rules by combining the compatible rules. Six fuzzy algorithms with different fuzzifiers (zmf, sigmf, gbellmf) and defuzzifiers (bisector, mom, and centroid) were applied, and the outputs were compared to the panelists’ classifications in cross tables. According to the classification results, fuzzy algorithms grouped the fruits into correct classes with 90.9%, 92.3%, 88.7%, 87.4%, 92.4% and 93.3% accuracy for 6 models, respectively. The best result was observed with zmf and sigmf, and gbellmf as fuzzifier and mom as defuzzifier with 93.3% accuracy. Overly, the results revealed that the fusion of aforementioned tomato properties based on fuzzy membership functions could accurately classify the tomatoes in correct groups for different markets.Publication Open Access Radiative transfer model inversion using high-resolution hyperspectral airborne imagery – Retrieving maize LAI to access biomass and grain yield(Elsevier, 2022-06-01) Kayad, A; Rodrigues, FA; Naranjo, S; Sozzi, M; Pirotti, F; Marinello, F; Schulthess, U; Defourny, P; Gerard, B; Weiss, MMapping crop within-field yield variability provide an essential piece of information for precision agriculture applications. Leaf Area Index (LAI) is an important parameter that describes maize growth, vegetation structure, light absorption and subsequently maize biomass and grain yield (GY). The main goal for this study was to estimate maize biomass and GY through LAI retrieved from hyperspectral aerial images using a PROSAIL model inversion and compare its performance with biomass and GY estimations through simple vegetation index approaches. This study was conducted in two separate maize fields of 12 and 20 ha located in north-west Mexico. Both fields were cultivated with the same hybrid. One field was irrigated by a linear pivot and the other by a furrow irrigation system. Ground LAI data were collected at different crop growth stages followed by maize biomass and GY at the harvesting time. Through a weekly/biweekly airborne flight campaign, a total of 19 mosaics were acquired between both fields with a micro-hyperspectral Vis-NIR imaging sensor ranging from 400 to 850 nanometres (nm) at different crop growth stages. The PROSAIL model was calibrated and validated for retrieving maize LAI by simulating maize canopy spectral reflectance based on crop-specific parameters. The model was used to retrieve LAI from both fields and to subsequently estimate maize biomass and GY. Additionally, different vegetation indices were calculated from the aerial images to also estimate maize yield and compare the indices with PROSAIL based estimations. The PROSAIL validation to retrieve LAI from hyperspectral imagery showed a R² value of 0.5 against ground LAI with RMSE of 0.8 m²/m². Maize biomass and GY estimation based on NDRE showed the highest accuracies, followed by retrieved LAI, GNDVI and NDVI with R² value of 0.81, 0.73, 0.73 and 0.65 for biomass, and 0.83, 0.69, 0.73 and 0.62 for GY estimation, respectively. Furthermore, the late vegetative growth stage at V16 was found to be the best stage for maize yield prediction for all studied indices.Publication Open Access Detecting the cause of change using uncertain data: Natural and anthropogenic factors contributing to declining groundwater levels and flows of the Wairau Plain aquifer, New Zealand(Elsevier, 2020-10) Wöhling, T; Wilson, S; Wadsworth, V; Davidson, P1 Study Region: The unconfined Wairau Aquifer in the Marlborough District of New Zealand is almost exclusively recharged by the Wairau River and serves as the major resource for drinking water and irrigation in the region. A declining trend in aquifer levels and low-land spring flows has been observed for the past decades. 2 Study Focus: The aim of this study is to identify and analyse natural and anthropogenic factors controlling the hydrological regime of the Wairau Aquifer. Concurrent trends in the long-term water balance components for the Wairau catchment and in low-flow statistics as well as the correlation between hydro-meteorological drivers and the Interdecadal Pacific Oscillation (IPO) index were investigated. The impact of river morphology changes on river recharge rates was studied using a previously developed groundwater flow model. 3 New Hydrological Insights for the Region: Our study found that long-term trends in declining catchment-scale precipitation are superimposed on climate oscillation and a strong annual variability. Jointly, these processes have resulted in lower than average river flows, increased low-flow periods, and consequently in lower rates of aquifer recharge. River engineering caused erosion of the braided river morphology, leading to a possibly permanent loss of aquifer storage. Groundwater abstraction is not accurately known which is a limitation of this study. This additional information and adaptation strategies are required for sustainable management of the groundwater resources.Publication Open Access Effects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca, Mexico(Copernicus Publications on behalf of the European Geosciences Union, 2021-10-25) Naranjo, S; Rodrigues, FA; Cadisch, G; Lopez-Ridaura, S; Fuentes Ponce, M; Marohn, CThe effect of the spatial resolution of digital terrain models (DTMs) on topography and soil erosion modelling is well documented for low resolutions. Nowadays, the availability of high spatial resolution DTMs from unmanned aerial vehicles (UAVs) opens new horizons for detailed assessment of soil erosion with hydrological models, but the effects of DTM resolution on model outputs at this scale have not been systematically tested. This study combines plot-scale soil erosion measurements, UAV-derived DTMs, and spatially explicit soil erosion modelling to select an appropriate spatial resolution based on allowable loss of information. During 39 precipitation events, sediment and soil samples were collected on five bounded and unbounded plots and four land covers (forest, fallow, maize, and eroded bare land). Additional soil samples were collected across a 220ha watershed to generate soil maps. Precipitation was collected by two rain gauges and vegetation was mapped. A total of two UAV campaigns over the watershed resulted in a 0.60m spatial-resolution DTM used for resampling to 1, 2, 4, 8, and 15m and a multispectral orthomosaic to generate a land cover map. The OpenLISEM model was calibrated at plot level at 1m resolution and then extended to the watershed level at the different DTM resolutions. Resampling the 1m DTM to lower resolutions resulted in an overall reduction in slope. This reduction was driven by migration of pixels from higher to lower slope values; its magnitude was proportional to resolution. At the watershed outlet, 1 and 2m resolution models exhibited the largest hydrograph and sedigraph peaks, total runoff, and soil loss; they proportionally decreased with resolution. Sedigraphs were more sensitive than hydrographs to spatial resolution, particularly at the highest resolutions. The highest-resolution models exhibited a wider range of predicted soil loss due to their larger number of pixels and steeper slopes. The proposed evaluation method was shown to be appropriate and transferable for soil erosion modelling studies, indicating that 4m resolution (<5% loss of slope information) was sufficient for describing soil erosion variability at the study site.Publication Open Access Variable-rate application of fertiliser – A tool for improving farm systems and environmental performance?(New Zealand Grassland Association, 2022-03-08) King, WM; Pletnyakov, P; Taylor, A; Werner, A; Ekanayake, DNitrogenous fertilisers – especially urea – are key inputs into many farming systems. In New Zealand, increasing restrictions on nitrogen application on pastures means there is an urgent need to ensure that it is used effectively. One technology that has been developed that may contribute to this challenge is variable-rate application (VRA) of fertiliser. This trial used VRA technology to apply N fertiliser as a function of the pasture mass present at the time of application. The effect of VRA of N fertiliser on pasture production on five farms over one season was examined, and the impact of those changes on farm system metrics, including environmental performance, was estimated. Averaged over all five farms, there was no statistically significant difference between VRA and blanket-rate application of fertiliser on pasture production. However, one farm did show a significant difference. Although the absolute difference was small, this suggested that VRA could be a useful tool in addressing the challenge of driving better farm performance with reduced environmental impact.Publication Open Access Spectral CT imaging of human osteoarthritic cartilage via quantitative assessment of glycosaminoglycan content using multiple contrast agents(AIP Publishing, 2021-06) Baer, K; Kieser, S; Schon, B; Rajendran, K; ten Harkel, T; Ramyar, M; Löbker, C; Bateman, C; Butler, A; Raja, A; Hooper, G; Anderson, N; Woodfield, TDetection of early osteoarthritis to stabilize or reverse the damage to articular cartilage would improve patient function, reduce disability, and limit the need for joint replacement. In this study, we investigated nondestructive photon-processing spectral computed tomography (CT) for the quantitative measurement of the glycosaminoglycan (GAG) content compared to destructive histological and biochemical assay techniques in normal and osteoarthritic tissues. Cartilage-bone cores from healthy bovine stifles were incubated in 50% ioxaglate (Hexabrix®) or 100% gadobenate dimeglumine (MultiHance®). A photon-processing spectral CT (MARS) scanner with a CdTe-Medipix3RX detector imaged samples. Calibration phantoms of ioxaglate and gadobenate dimeglumine were used to determine iodine and gadolinium concentrations from photon-processing spectral CT images to correlate with the GAG content measured using a dimethylmethylene blue assay. The zonal distribution of GAG was compared between photon-processing spectral CT images and histological sections. Furthermore, discrimination and quantification of GAG in osteoarthritic human tibial plateau tissue using the same contrast agents were demonstrated. Contrast agent concentrations were inversely related to the GAG content. The GAG concentration increased from 25 μg/ml (85 mg/ml iodine or 43 mg/ml gadolinium) in the superficial layer to 75 μg/ml (65 mg/ml iodine or 37 mg/ml gadolinium) in the deep layer of healthy bovine cartilage. Deep zone articular cartilage could be distinguished from subchondral bone by utilizing the material decomposition technique. Photon-processing spectral CT images correlated with histological sections in healthy and osteoarthritic tissues. Post-imaging material decomposition was able to quantify the GAG content and distribution throughout healthy and osteoarthritic cartilage using Hexabrix® and MultiHance® while differentiating the underlying subchondral bone.Publication Open Access Effects of Canada goldenrod invasion on soil extracellular enzyme activities and ecoenzymatic stoichiometry(MDPI, 2021-04) Hu, Z; Li, J; Shi, K; Ren, G; Dai, Z; Sun, J; Zheng, X; Zhou, Y; Zhang, J; Li, G; Du, DThe rapid expansion of Canada goldenrod (Solidago canadensis L.) in China has drawn considerable attention as it may not only decrease vegetation diversity but also alter soil nutrient cycling in the affected ecosystems. Soil extracellular enzymes mediate nutrient cycling by catalyzing the organic matter decomposition; however, the mechanisms by which alien plant invasion may affect soil extracellular enzymes remain unclear. The objective of this study was to investigate the responses of soil extracellular enzyme activities and ecoenzymatic stoichiometry to S. canadensis invasion. Several extracellular enzymatic activities related to carbon, nitrogen, and phosphorus cycling were measured using a fluorometric method. Ecoenzymatic stoichiometry was used as a proxy of soil microbial metabolic limitations. S. canadensis invasion appeared to be associated with decreased activities of enzymes and with substantial conversions of microbial metabolic carbon and nitrogen limitations. The changes in the activities of extracellular enzymes and the limitations of microbial metabolism were correlated with the alterations in the nutrient availability and resource stoichiometry in the soil. These findings reveal that the alterations in soil available nutrients associated with S. canadensis invasion may regulate extracellular enzymatic activities and cause microbial metabolic limitations, suggesting that S. canadensis invasion considerably affects biogeochemical cycling processes.Publication Open Access A review of the effects of droplet size and flow rate on the chargeability of spray droplets in electrostatic agricultural sprays(American Society of Agricultural and Biological Engineers, 2018) Post, SL; Roten, RLThe chargeability of liquid sprays is an important factor in determining the deposition efficiency of electrostatic pesticide sprays. The Rayleigh limit provides information on the maximum amount of charge a spray droplet can carry as a function of droplet size and liquid properties. This article reviews the literature to determine what fraction of the Rayleigh limit is achievable. Typically, less than 10% of the Rayleigh limit charge is obtained. The droplet charge per unit mass decreases with increasing droplet size and liquid flow rate. A correlation equation is derived from published data to predict spray droplet charge per unit mass from droplet size, flow rate, and charging voltage.Publication Open Access Flat-fan spray atomization model(American Society of Agricultural and Biological Engineers, 2018) Post, SL; Hewitt, AJIn pesticide application, the lack of a suitable theoretical atomization model for flat-fan spray nozzles forces a reliance on empirical data and correlations, even for computational simulations. There is considerable difficulty in the theoretical analysis of the liquid sheet emanating from flat-fan nozzles because no simplification to a two-dimensional analysis can be employed, as is done for cylindrical jets. Nonetheless, 50 years ago, Dombrowski and co-workers used linear stability analysis to analyze the breakup of flat-fan spray sheets into ligaments and from ligaments to droplets. Their correlations have not found use because they include parameters that are difficult, if not impossible, to measure. In this work, the Dombrowski model is simplified using dimensional analysis, resulting in a correlation to predict the volume median diameter of flat-fan sprays in terms of common user parameters, i.e., the nozzle size and operating pressure.