Large Coefficient Of Variation Research Articles

Morphological characterisation of ethnomedicinally important Kaempferia L. (Zingiberaceae) and its present distribution status in Manipur, North-East India

Kaempferia L., a member of the Zingiberaceae family, is one of the most potent medicinal plants in India and requires proper attention. Our efforts to collect various species of Kaempferia in their natural habitat led to the collection of 30 accessions, including K. galanga, K. marginata, K. parviflora, K. rotunda, and five other unidentified Kaempferia species that are likely natural hybrids with no distinguishing features. It has been found that rhizomes are the most usable portion of the plant, and people in this region use them the most for medical purposes. The present study aimed to describe and evaluate the morphological structures of the plant, incorporating 52 phenotypic descriptors. Descriptive statistics and multivariate analysis were employed to explore diversity. The majority of the traits tested were highly variable. The elevation range (28704.02%) and plant height (at 648.03 %) had the largest coefficients of variation (CV %), whereas anther length (0.06 %) and corolla shape (0.19 %) had the lowest. Rhizome size has a high positive correlation with the odour of the aerial plant parts, growing, dormant, new shoots sprouting, and flowering seasons. However, it shows negative correlations with elevation, lifespan of the flower, and number of leaves. Principal component analysis (PCA), revealed that the first five components accounted for 89.90 % of the variability, and hierarchical grouping based on accession dissimilarity revealed two significant groupings. It was found that wild K. species populations were genetically diverse, suggesting that this diversity can be used for agronomic and horticultural purposes to isolate and characterise numerous important, well-adapted genotypes with the potential to significantly increase yields. Therefore, it is crucial to conserve the genetic material that is currently available.

Paralympic Versus Olympic Canoe Sprint: Comprehension of the Development Trajectory of the Kayak 200 Meters.

Improvements in race times for male and female Para canoe athletes across different sports classes have led to a reduction in relative differences between classes over time. However, there is a lack of research examining the comparative developmental trajectories between high-performance Paralympic (PCS) and Olympic (OCS) canoe sprint. In this study, we compared the developmental trajectories of 200-meter kayak performances among PCS and OCS athletes. In total, we analyzed 628 race results obtained from public online databases, for nine competitions between 2015 and 2023. Race times were reduced over the years except in specific sports classes (KL3-M, K1-M, and K1-F; KL: Kayak Level, M: male, F: female), with a poor positive correlation (r = 0.17 to 0.33) between time and the years. For the remaining sports classes, these correlations ranged from poor to fair (r = -0.58 to -0.13). OCS K1 athletes outperformed their Paralympic counterparts. Among Paralympic classes, KL1 had slower times than KL2 and KL3 (p ≤ .05), with KL2 times significantly lower than KL3 in the female category. OCS athletes exhibited less variability in race times compared to PCS athletes. In the male category, there were no significant differences in the coefficients of variation (CV) and amplitude of race times between sport classes, except for KL1-M, which had a larger CV than K1 (p ≤ .05). In the female category, the CV and amplitude of race times were significantly higher in KL1-F compared to KL3-F and K1-F. OCS times remained stable from 2015, with KL3-M following a similar trend. PCS displayed greater race time variability, particularly in higher impairment classes, notably KL1. This underscores the existence of distinct developmental stages within the canoe sprint modality, particularly emphasizing the early developmental phase of KL1. It also provides valuable insights for coaches and sports selection, especially concerning athletes with more severe impairments, including those in Rehabilitation Centers and during athlete recruitment.

Effect of shells number and machining on selected properties of 3D-printed PLA samples

Effect of shells number (1–5) on tensile properties of PLA samples printed using the FDM/FFF technique was investigated. The crack surface was also analyzed. The best properties were obtained for 4-shell sample. However, due to the large coefficient of variation (>> 10%) in the case of elongation, 3-shell sample was selected for testing the machining impact. Such a large coefficient of variation can be explained by the presence of voids between the layers. The greater the number of layers, the greater the structure defects. Machining increases surface smoothness while reducing tensile strength and practically unchanged elongation at break.

Towards personalized nicotinamide mononucleotide (NMN) supplementation: Nicotinamide adenine dinucleotide (NAD) concentration

Nicotinamide mononucleotide (NMN) is a precursor of nicotinamide adenine dinucleotide (NAD), which declines with age. Supplementation of NMN has been shown to improve blood NAD concentration. However, the optimal NMN dose remains unclear. This is a post-hoc analysis of a double-blinded clinical trial involving 80 generally healthy adults aged 40–65 years. The participants received a placebo or daily 300 mg, 600 mg, or 900 mg NMN for 60 days. Blood NAD concentration, blood biological age, homeostatic model assessment for insulin resistance, 6-minute walk test, and 36-item short-form survey (SF-36) were measured at baseline and after supplement. A significant dose-dependent increase in NAD concentration change (NADΔ) was observed following NMN supplementation, with a large coefficient of variation (29.2–113.3%) within group. The increase in NADΔ was associated with an improvement in the walking distance of 6-minute walk test and the SF-36 score. The median effect dose of NADΔ for the 6-minute walk test and SF-36 score was 15.7 nmol/L (95% CI: 10.9–20.5 nmol/L) and 13.5 nmol/L (95% CI; 10.5–16.5 nmol/L), respectively. Because of the high interindividual variability of the NADΔ after NMN supplementation, monitoring NAD concentration can provide valuable insights for tailoring personalized dosage regimens and optimizing NMN utilization.

Temporal phenotypic variation of spinach root traits and its relation to shoot performance

The root system is important for the growth and development of spinach. To reveal the temporal variability of the spinach root system, root traits of 40 spinach accessions were measured at three imaging times (20, 30, and 43 days after transplanting) in this study using a non-destructive and non-invasive root analysis system. Results showed that five root traits were reliably measured by this system (RootViz FS), and two of which were highly correlated with manually measured traits. Root traits had higher variations than shoot traits among spinach accessions, and the trait of mean growth rate of total root length had the largest coefficients of variation across the three imaging times. During the early stage, only tap root length was weakly correlated with shoot traits (plant height, leaf width, and object area (equivalent to plant surface area)), whereas in the third imaging, root fresh weight, total root length, and root area were strongly correlated with shoot biomass-related traits. Five root traits (total root length, tap root length, total root area, root tissue density, and maximal root width) showed high variations with coefficients of variation values (CV ≥ 0.3, except maximal root width) and high heritability (H2 > 0.6) among the three stages. The 40 spinach accessions were classified into five subgroups with different growth dynamics of the primary and lateral roots by cluster analysis. Our results demonstrated the potential of in-situ phenotyping to assess dynamic root growth in spinach and provide new perspectives for biomass breeding based on root system ideotypes.

Drainage ditches are significant sources of indirect N2O emissions regulated by available carbon to nitrogen substrates in salt-affected farmlands

Agriculture is a main source of nitrous oxide (N2O) emissions. In agricultural systems, direct N2O emissions from nitrogen (N) addition to soils have been widely investigated, whereas indirect emissions from aquatic ecosystems such as ditches are poorly known, with insufficient data available to refine the IPCC emission factor. In this contribution, in situ N2O emissions from two ditch water‒air interfaces based on a diffusion model were investigated (almost once per month) from June 2021 to December 2022 in an intensive arable catchment with high N inputs and salt-affected conditions in the Qingtongxia Irrigation District, northwestern China. Our results implied that agricultural ditches (mean 148 μg N m−2 h−1) were significant sources for N2O emissions, and were approximately 2.1 times greater than those of the Yellow River directly connected to ditches. Agronomic management strategies increased N2O fluxes in summer, while precipitation events decreased N2O fluxes. Agronomic management strategies, including fertilization (294–-540 kg N hm−2) and irrigation on farmland, resulted in enhanced diffuse N loads in drain water, whereas precipitation diluted the dissolved N2O concentration in ditches and accelerated the ditch flow rate, leading to changes in the residence time of N-containing substances in water. The spatial analysis showed that N2O fluxes (202–233 μg N m−2 h−1) in the headstream and upstream regions of ditches due to livestock and aquaculture pollution sources were relatively high compared to those in the midstream and downstream regions (100–114 μg N m−2 h−1). Furthermore, high available carbon (C) relative to N reduced N2O fluxes at low DOC:DIN ratio levels by inhibiting nitrification. Spatiotemporal variations in the N2O emission factor (EF5) across ditches with higher N resulted in lower EF5 and a large coefficient of variation (CV) range. EF5 was 0.0011 for the ditches in this region, while the EF5 (0.0025) currently adopted by the IPCC is relatively high. The EF5 variation was strongly controlled by the DOC:DIN ratio, TN, and NO3−-N, while salinity was also a nonnegligible factor regulating the EF5 variation. The regression model incorporating NO3−-N and the DOC:DIN ratio could greatly enhance the predictions of EF5 for agricultural ditches. Our study filled a key knowledge gap regarding EF5 from agricultural ditches in salt-affected farmland and offered a field investigation for refining the EF5 currently used by the IPCC.

Species-specific and generalized allometric equations for improving aboveground biomass estimations of 33 understory woody species in northeastern China forest ecosystems

Understory small trees and shrubs play a crucial role in the biogeochemical cycles in forest ecosystems. However, their biomass in northeastern China is still uncertain and has been heavily disregarded due to the limited number of available allometric equations. For this study, 782 plants from 33 species obtained by the destructive method were used to develop species-specific and generalized aboveground allometric biomass equations based on collar diameter ( D) and height ( H) using weighted nonlinear seemingly unrelated regression. Each biomass component was shown to be well predicted by D alone, with R2 adj. values mostly greater than 0.80. The majority of species performed better in the models for wood and aboveground biomass when H was included as D2 H. Furthermore, generalized equations for the two components showed a comparatively large coefficient of variation but comparable Bias to species-specific equations, especially for small trees. It is recommended to estimate biomass using generalized equations for mixed species only when species-specific equations are unavailable at a given site. However, in the event when precision is not the primary concern, generalized equations are also suggested. The developed equations will help to improve the accuracy of biomass assessment of understory woody plants in northeastern China forest ecosystems.

Integrated hydrological modelling of two contrasting watersheds with a terminal reservoir in the Upper Tapi River basin, India

Abstract The present study developed an integrated hydrologic model for sustainable utilisation and water management in two complex watersheds with varying physioclimatic features and reservoirs. The soil and water assessment tool (SWAT) is used for predicting integrated inflows into the Hatnur reservoir from the Burhanpur and Purna watersheds of the Upper Tapi River basin, while outflows are simulated using a rule curve. The influence of watershed complexities on hydrological model parameters and the watershed processes are investigated using extensive multisite and multivariable calibration (1998–2007) and validation (2008–2013) approaches, including sensitivity and uncertainty analyses. The sensitive parameters are related to curve number (CN), groundwater, slope, and main channel characteristics. The annual streamflow (m3/km2/mm of rainfall) in the Burhanpur watershed is 568.7, which is 4.2 times higher than the Purna watershed's streamflow of 136.2. The hypsometric analysis, areal rainfall, and flow duration curves revealed a substantially different streamflow pattern and a larger coefficient of variation in the spatial distribution of water balance components over sub-watersheds in the Burhanpur watershed compared to the Purna watershed due to diverse topographic features. The developed model would be useful for planning controlled releases from the terminal reservoir to mitigate hazards in the downstream reaches of the Tapi River basin.

Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network

Accurate soil quality evaluation is an important prerequisite for improving soil management systems and remediating soil pollution. However, traditional soil quality evaluation methods are cumbersome to calculate, and suffer from low efficiency and low accuracy, which often lead to large deviations in the evaluation results. This study aims to provide a new and accurate soil quality evaluation method based on graph convolution network (GCN). In this study, soil organic matter (SOM), alkaline hydrolysable nitrogen (AN), available potassium (AK), salinity, and heavy metals (iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn)) were determined and evaluated using the soil quality index (SQI). Then, the graph convolution network (GCN) was first introduced in the soil quality evaluation to construct an evaluation model, and its evaluation results were compared with those of the SQI. Finally, the spatial distribution of the evaluation results of the GCN model was displayed. The results showed that soil salinity had the largest coefficient of variation (86%), followed by soil heavy metals (67%) and nutrients (30.3%). The soil salinization and heavy metal pollution were at a low level in this area, and the soil nutrients and soil quality were at a high level. The evaluation accuracy of the GCN model for soil salinity/heavy metals, soil nutrients, and soil quality were 0.91, 0.84, and 0.90, respectively. Therefore, the GCN model has a high accuracy and is feasible to be applied in the soil quality evaluation. This study provides a new, simple, and highly accurate method for soil quality evaluation.

Yearly Fluctuations in Honey Production in Hokkaido, Northern Japan, with Special Reference to Weather Conditions and Masting Behavior

The factors controlling yearly fluctuations in honey production are poorly understood. To evaluate yearly fluctuations in honey production, the coefficient of variation (CV) and the autocorrelation analysis were used to determine the magnitude and periodicity of the fluctuations for seven major nectar-source plants (basswood, black locust, Amur cork tree, white clover, buckwheat, Kamchatka thistle, and horse chestnut) using 15-years of data obtained in Hokkaido, Japan. Regression analysis was conducted to evaluate the relationship between annual honey production and the corresponding weather conditions during the flowering month. The periodic synchronous flowering and fruiting observed in tree species is called masting or masting behavior. A masting model, based on the resource budget, was applied to tree species if periodicity was detected by an autocorrelation analysis. The CV differed markedly among species. Black locust and the Amur cork tree had the smallest and largest CVs, respectively, whereas basswood was periodic. A negative correlation was observed between monthly precipitation and honey production in black locust, white clover, thistle and the Amur cork tree. This result implies that rain inhibits honey bee foraging. Production of buckwheat honey, however, tended to increase with increasing mean temperature. It might be difficult to detect the effect of rain on the honey production using buckwheat presumably because of the long flowering period. Annual honey production in basswood could be described by the resource budget model, but not in horse chestnut. Some horse chestnut trees produce flowers even in non-mast year implying that it was difficult to detect the periodicity in this species. According to beekeepers, honey production in this last decade in Hokkaido has been disrupted by climate change and the transitioning of the industrial structure.

3D-OSEM versus FORE + OSEM: Optimal Reconstruction Algorithm for FDG PET with a Short Acquisition Time.

Objective In this study, we investigated the optimal reconstruction algorithm in fluorodeoxyglucose (FDG) positron emission tomography (PET) with a short acquisition time. Materials and Methods In the phantom study, six spheres filled with FDG solution (sphere size: 6.23-37 mm; radioactivity ratio of spheres to background = 8:1) and placed in a National Electrical Manufacturers Association phantom were evaluated. Image acquisition time was 15 to 180 seconds, and the obtained image data were reconstructed using each of the Fourier rebinning (FORE) + ordered subsets expectation-maximization (OSEM) and 3D-OSEM algorithms. In the clinical study, mid-abdominal images of 19 patients were evaluated using regions of interest placed on areas of low, intermediate, and high radioactivity. All obtained images were investigated visually, and quantitatively using maximum standardized uptake value (SUV) and coefficient of variation (CV). Results In the phantom study, FORE + OSEM images with a short acquisition time had large CVs (poor image quality) but comparatively constant maximum SUVs. 3D-OSEM images showed comparatively constant CVs (good image quality) but significantly low maximum SUVs. The results of visual evaluation were well correlated with those of quantitative evaluation. Small spheres were obscured on 3D-OSEM images with short acquisition time, but image quality was not greatly deteriorated. The clinical and phantom studies yielded similar results. Conclusion FDG PET images with a short acquisition time reconstructed by FORE + OSEM showed poorer image quality than by 3D-OSEM. However, images obtained with a short acquisition time and reconstructed with FORE + OSEM showed clearer FDG uptake and more useful than 3D-OSEM in the light of the detection of lesions.

Repetition velocity as a measure of loading intensity in the free weight and Smith machine Bulgarian split squat.

This study investigated the grouped and individualized load-velocity profile (GLVP vs. ILVP) in Bulgarian split squat using Smith machine and free weight. Seventy five recreational male lifters completed two incremental loading tests of Bulgarian split squat. Mean velocity was measured by a linear-position transducer (GymAware). Linear regression equation was applied to construct the GLVP and ILVP. The agreement of predicted %1RM and measured %1RM was assessed by a combination of intraclass correlation coefficient (ICC), coefficient of variation (CV), standard error of measurement (SEM) and Bland-Altman analysis. Acceptable validity was defined as ICC > 0.75, CV ≤ 10% and p≥0.05 (a paired Wilcoxon signed-rank test). A very high level of inverse load-velocity relationships were demonstrated in Bulgarian split squat (r=-0.92) with free weights and a Smith machine. ILVP (ICC ≥ 0.98, CV ≤ 8.73%, p≥0.56) was valid enough to predict the %1RM, but GLVP of both limbs revealed large CVs in free weights (CV: 15.4%,15.63%) and a Smith machine (CV: 11.24%, 12.25%). Cross-validation between the actual %1RM and predicted %1RM using free weights and a Smith machine ILVP was not acceptable (p≤0.03, CV ≥ 14.07%). A very high level of inverse relationship were observed between %1RM and MV in Bulgarian split squat using free weights and a Smith machine, indicating individualized load velocity properties, and the ILVP showed high between-devices variability in both scenarios. Using velocity as a measure of loading intensity in Bulgarian split squat needs to consider the individualized load velocity properties, and difference between free weights and a Smith machine.

Variability of in vivo potency assays of whole-cell pertussis, inactivated polio, and meningococcal B vaccines

For the batch release of vaccines, potency release assays are required. Non-animal in vitro tests have numerous advantages and are preferred; however, several vaccines are still released using in vivo assays. Their major drawback is the inherent variability with its practical implications. We quantified the variability of in vivo potency release assays for whole-cell pertussis, inactivated polio and meningococcal B (MenB) vaccines which showed large CV (Coefficient of Variation) ranging from 34% to 125%. As inherent variability might potentially be attributed to the highly variable immune system between individual animals, we evaluated the antibody titres to four MenB antigens in 344 individual outbred mice. These varied strongly, with more than 100-fold differences in antibody titres in responsive mice. Furthermore, within individual mice there was generally no correlation between the strengths of the responses to the four antigens. A mouse with a very low or no response to one antigen in many cases exhibited a strong response to another antigen. The large differences between individual animals is likely a considerable contributor to the inherent variability of in vivo potency assays. Our data again support the notion that it is preferred to move away from in vivo potency assays for monitoring batch to batch consistency as part of vaccine batch release testing.

Experimental modelling of spudcan penetration in spatially variable soils

ABSTRACT The influence of spatial variability of soils on spudcan penetration responses is found significant through numerical methods. However, due to the difficulty of preparing spatially variable soils, the penetration mechanism of the spudcan through random soils remains physically unclear. Therefore, this study aims to investigate the effects of the spatial variability of soils on the penetration behaviour of spudcan foundations by laboratory tests. A new method to prepare the spatially variable soils was proposed first. Then, three physical soil models with different scales of fluctuation and coefficients of variation were carefully prepared. The spudcan penetration was conducted in these three soil models and the penetration mechanism of the spudcan was investigated. The penetration resistances of the three cases were obtained and compared with that predicted by the methods suggested by ISO and SNAME standards. The results show that the predicted error of the penetration resistance can reach 50% when the soils have a large coefficient of variation and a small horizontal scale of fluctuation. The large difference is the significant spatial variability that has been ignored in the standards. This study paves the way to an accurate prediction of the spudcan penetration analysis in strong variable soil seabed.

1312-P: Relationship between Progression of Diabetic Nephropathy and Seasonal Fluctuation of Estimated GFR

Introduction: The seasonal fluctuation of estimated glomerular filtration rate (GFR) in type2 diabetes mellitus (T2DM) patients remains unknown. The present study is first to examine seasonal fluctuation of eGFR and its relationship to the progression of diabetic nephropathy (DN). Methods: This retrospective study initially analyzed data on 21,307 T2DM patients with hypertension (HT). Seasonal fluctuation of eGFR were evaluated using the intrapersonal coefficient of variation (CV) of 20 or more serial measurements of body weight, Blood pressure and HbA1c during a 5-year period from 2014-2018. The primary objective was to determine if there is seasonal fluctuation of eGFR or not. Secondary objective is to examine the relationship between progression of DN and seasonal fluctuation of eGFR. DN was assessed by eGFR and urinary albumin excretion (UAE) changes. Results: The figure shows the changes of eGFR monthly averages. eGFR is significantly lower in summer each year (vs winter, P<0.001). Classified into two groups based on median CV of eGFR, eGFR decrease was obvious in the group with large CV of eGFR (vs group with small CV, P<0.001). In addition, UAE increase was also obvious in the group with large CV of eGFR (vs group with small CV, P<0.001). Conclusion: This study suggests that eGFR is fluctuated by season in T2DM patients with HT. The seasonal fluctuation of eGFR was associated with the progression of DN. Disclosure M.Yuki: None. T.Yamazaki: None. K.Miyashita: None. M.Sakamoto: None.

Source analysis and health risk assessment of heavy metals in agricultural land of multi-mineral mining and smelting area in the Karst region – a case study of Jichangpo Town, Southwest China

In the Karst region of Southwest China, the content of soil heavy metals is generally high because of the geological background. Moreover, Southwest China is rich in mineral resources. A large number of mining and smelting activities discharge heavy metals into surrounding soil and cause superimposed pollution, which has drawn widespread concern. Due to the large variation coefficients of soil heavy metals in the Karst region, it is particularly essential to select appropriate analysis methods. In this paper, Jichangpo in Puding County, a Karst area with multi-mineral mining and smelting, is selected as the research object. A total of 368 pieces of agricultural topsoil in the study area are collected. The pollution level of heavy metals in agricultural soil is evaluated by the geological accumulation index (Igeo) and enrichment factor (EF). Absolute Factor Score/Multiple Linear Regression (APCS/MLR), geographic information system (GIS), self-organizing mapping (SOM), and random forest (RF) are used for the source allocation of soil heavy metals. Finally, the combination of APCS/MLR and health risk assessment model is adopted to evaluate the risks of heavy metal sources and determine the priority-control source. The results show that the average values of soil heavy metals in the study area (Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni) exceed the background values of corresponding elements in Guizhou Province. Three sources of heavy metals are identified by combining APCS/MLR, GIS, SOM, and RF. Zn (63.47%), Pb (55.77%), Cd (58.98%), Hg (32.17%), Cu (14.41%), and As (5.99%) are related to lead-zinc mining and smelting; Cr (98.14%), Ni (90.64%), Cu (76.93%), Pb (43.02%), Zn (35.22%), Cd (28.97%), Hg (22.44%), and As (5.84%) are mixed sources (natural and agricultural sources); As (88.17%), Hg (45.39%), Cd (12.04%), Cu (8.66%), and Ni (6.72%) are related to the mining and smelting of coal and iron. The results of health risk assessment show that only As poses a non-carcinogenic risk to human health. 3.31% of the sampling points of As have non-carcinogenic risks to adults and 10.22% to children. In terms of carcinogenic risks, As, Pb, and Cr pose carcinogenic risks to adults and children. Combined with APCS/MLR and the health risk assessment model, the mining and smelting of coal and iron is the priority-control pollution source. This paper provides a comprehensive method for studying the distribution of heavy metal sources in areas with large variation coefficients of soil heavy metals in the Karst region. Furthermore, it offers a theoretical basis for the management and assessment of heavy metal pollution in agricultural land in the study area, which is helpful for researchers to make strategic decisions on food security when selecting agricultural land.

Data-Driven Model for Predicting the Compressive Strengths of GFRP-Confined Reinforced Concrete Columns

This paper focuses on the compressive strength of Glass fiber reinforced polymer (GFRP)-confined reinforced concrete columns. Data from 114 sets of GFRP-confined reinforced concrete columns were collected to evaluate the researchers’ and proposed model. A data-driven machine learning model was used to model the compressive strength of the GFRP-confined reinforced concrete columns and investigate the importance and sensitivity of the parameters affecting the compressive strength. The results show that the researchers’ model facilitates the study of the compressive strength of confined columns but suffers from a large coefficient of variation and too high or conservative estimation of compressive strength. The back propagation (BP) neural network has the best accuracy and robustness in predicting the compressive strength of the confined columns, with the coefficient of variation of only 14.22%, and the goodness of fit for both the training and testing sets above 0.9. The parameters that have an enormous influence on compressive strength are the concrete strength and FRP thickness, and all the parameters, except the fracture strain of FRP, are positively or inversely related to the compressive strength.

178 A characterization of declared nutrient profiles of commercially available manufactured feeds for broodmares and growing horses

Commercially manufactured concentrates may be fed to broodmares and growing horses. While many aspects of the production and labeling of commercial feeds are guided by governmental requirements or recommendations from the American Association of Feed Control Officials (AAFCO), each manufacturer determines the nutrient profiles for individual feeds. This project characterized the nutrient profiles of commercially available manufactured feeds intended for broodmares and growing horses. The study was performed using an internet search (Chrome, Google LLC) beginning in April of 2020 and ending in September of 2021. Search terms included horse, equine, growth, weanling, yearling, broodmare, breeding, nursery, stud, feed, mill, concentrate, pellet, cube, textured and sweet feed, in various combinations. A search using the name of each state and the term “feed mill” was also conducted. Only feeds declared to be for broodmares, breeding stock, or growing horses were included. Feeds intended to be fed at low intakes, such as ration balancers, and feeds intended as the entire ration (without forage) were excluded. The final data set included the manufacturers’ reported nutrient concentrations for minimum crude protein (CP, n = 132), minimum calcium (Ca, n = 131), minimum phosphorus (P, n = 131), minimum copper (Cu, n = 125), minimum zinc (Zn, n = 125), minimum selenium (n = 127),minimum vitamin A (n = 125), minimum vitamin E (n = 121) and minimum vitamin D (n = 91). The Ca:P ratio was calculated using the minimum Ca concentration and the minimum P concentration. Mean, standard deviation (SD) and coefficient of variation (CV) were calculated for each nutrient. Mean and SD for the reported minimums for CP, Ca and P were 14.6 ± 1.44%, 0.9 ± 0.28 % and 0.64 ± 0.13%, respectively. The mean value for Ca:P ratio was 1.5:1. Mean and SD for the reported minimums for Cu, Zn and Se were 54 ± 16 ppm, 171 ± 52 ppm and 0.54 ± 0.15 ppm, respectively. Mean values for the reported minimums for vitamin A, vitamin E and vitamin D were 5453 ± 2030 IU/lb, 133 ± 66 IU/lb and 734 ± 395 IU/lb, respectively. The CV for reported minimums for the feeds in this survey ranged from lows of 10% for crude protein and 20% for phosphorus, to highs of 50% for vitamin E and 53% for vitamin D. The large coefficients of variation for vitamin E and vitamin D may suggest a lower level of consensus among manufacturers in regard to desirable fortification levels for these nutrients. Information from this survey may provide insight into areas where research is needed to define nutrient requirements of broodmares and growing horses.

Phenophase-based comparison of field observations to satellite-based actual evaporation estimates of a natural woodland: miombo woodland, southern Africa

Abstract. The trend and magnitude of actual evaporation across the phenophases of miombo woodlands are unknown. This is because estimating evaporation in African woodland ecosystems continues to be a challenge, as flux observation towers are scant if not completely lacking in most ecosystems. Furthermore, significant phenophase-based discrepancies in both trend and magnitude exist among the satellite-based evaporation estimates (i.e. Global Land Evaporation Amsterdam Model (GLEAM), moderate resolution imaging spectroradiometer (MODIS), operational simplified surface energy balance (SSEBop), and water productivity through open-access remotely sensed derived data (WaPOR)), making it difficult to ascertain which of the estimates are close to field conditions. Despite the many limitations with estimation of evaporation in woodlands, the development and application of the distributed temperature system (DTS) is providing deepened insights and improved accuracy in woodland energy partitioning for evaporation assessment. In this study, the Bowen ratio distributed temperature sensing (BR-DTS) approach is used to partition available energy and estimate actual evaporation across three canopy phenophases of the miombo woodland, covering the entire 2021 dry season (May–October) and early rain season (November–December) at a representative site in Mpika in Zambia, southern Africa. To complement the field experiment, four satellite-based evaporation estimates are compared to the field observations. Our results show that actual evaporation of the miombo woodland appears to follow the trend of the net radiation, with the lowest values observed during the phenophase with the lowest net radiation in the cool dry season and the highest values during the phenophase with peak net radiation in the early rainy season. It appears the continued transpiration during the driest period in the dormant phenophase (with lowest canopy cover and photosynthetic activities) may be influenced by the species-dependent adapted physiological attributes such as access to moisture in deep soils (i.e. due to deep rooting), plant water storage, and the simultaneous leaf fall and leaf flush among miombo plants. Of the four satellite-based evaporation estimates, only the WaPOR has a similar trend to the field observations across the three phenophases. However, all four satellite-based estimates underestimate the actual evaporation during the dormant and green-up phenophases. Large coefficients of variation in actual evaporation estimates among the satellite-based estimates exist in the dormant and green-up phenophases and are indicative of the difficulty in estimating actual evaporation in these phenophases. The differences between field observations and satellite-based evaporation estimates can be attributed to the model structure, processes, and inputs.

Identification of Closely Spaced Modes of a Long-Span Suspension Bridge Based on Bayesian Inference

Closely spaced modes commonly observed in long-span suspension bridges can greatly increase the difficulty of identifying and tracking modal parameters. Most existing studies generally focus on identifying the closely spaced modes and quantifying the uncertainties based on numerical and experimental models. Further research focusing on full-scale long-span bridges is still required. A case study on identifying the closely spaced modes of the Qixiashan Yangtze River Bridge, a long-span suspension bridge with a main span of 1 418 m, is conducted in this paper. The effectiveness of the generalized fast Bayesian fast Fourier transform (GFBFFT) method is verified by both the simulated and monitoring data. The results show that a larger coefficient of variation (COV) and higher uncertainty is typically contained in the closely spaced modes than the separated modes. Compared with the FDD and SSI methods, the GFBFFT method guarantees higher identification accuracy of modal parameters and can serve as a reliable tool to identify the closely spaced modes.