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Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split plot arrangement and four replications. Main plots received shallow tillage and deep tillage. Subplots were treated with nitrogen (120 kg ha−1) from farmyard manure (FYM) and urea, including control, 33% FYM + 67% urea (MU), and 80% FYM + 20% urea (MF). Acidified hydrochar treatments H0 (no hydrochar) and H1 (with hydrochar, 2 t ha−1) were applied to sub-sub plots. Deep tillage significantly increased plant height, biological yield, grain yield, ear length, grains ear−1, thousand-grain weight, and nitrogen content compared to shallow tillage. MU and MF improved growth parameters and yield over the control. Hydrochar effects varied; H1 enhanced yield components and soil properties such as soil organic matter and nitrogen availability compared to H0. Canonical discriminant analysis linked deep tillage and MU/MF nitrogen management with improved yield and soil characteristics. In conclusion, deep tillage combined with integrated nitrogen management enhances maize productivity and soil properties. These findings highlight the importance of selecting appropriate tillage and nitrogen strategies for sustainable maize production along with hydrochar addition. These insights guide policymakers, agronomists, and agricultural extension services in adopting evidence-based strategies for sustainable agriculture, enhancing food production, and mitigating environmental impacts. The implication of this study suggests to undertake long-term application of hydrochar for further clarification and validation. [ABSTRACT FROM AUTHOR]

Hair colour is a valuable feature in forensic hair analysis and hair comparisons. Five hundred microscopic images of hair shafts were taken and for each image and colour model (RGB, CIE XYZ and CIE L*a*b*) values for each image were determined. The discriminating power of the three colour model values using statistical and unsupervised machine learning methods was evaluated. Additionally, the discriminating power of the images of the same hair shafts using unsupervised machine learning methods was evaluated. All methods were compared to determine which method had the greatest discriminating power to best distinguished between participants and accurately assigned hair to an individual and assist in forensic hair comparisons. The RGB colour model demonstrated the highest discriminating power of the colour model values while the CIE L*a*b* model achieved complete discrimination with a reduced number of participants. The unsupervised k-means model yielded similar results. Unsupervised PCA/k-means and agglomerative clustering models demonstrated low discrimination power of the images, suggesting the existence of additional features within the data beyond colour. This research highlights the significance of the incorporation of colour values in forensic hair comparisons and for further exploration of the incorporation of other hair features, beyond colour values. [ABSTRACT FROM AUTHOR]

The multivariate technique analysis was utilized for assigning and discriminating three Saudi sheep breeds, Naemi, Najdi and Hari based on live body and carcass traits. The traits were body height at wither and rump, body length, heart girth, body depth, head length, ear length, body weight at slaughtering, empty body, dressing percentage, hot carcass, cold carcass, and head weight which had a significant effect on breed. The phenotypic associations between the traits were also studied and strong associations between economically important traits were reported. The analyses of principal components were efficient in showing the total variation of 13 traits accumulated in linear combinations of four traits of most discriminant power body depth, ear length, body height at the rump, and head length. About 77% of the total variation between the breeds. Overall, the analysis of canonical discriminant was very successful in verifying the carcass of each breed considering thus previously mentioned 13 traits. It is recommended to disseminate the findings of this study as a guideline to assign slaughtered sheep and its carcass to its own breed when other means impossible to take place. [ABSTRACT FROM AUTHOR]

The pulque maguey is a perennial plant that provides several environmental benefits. Although its plantation has been drastically reduced, its primary economic and cultural use is the production of fermented, low-cost beverages. In this study, morphological and chemical analyses were conducted, which contribute to the knowledge that allows for the extraction of high-value products from pulque maguey biomass. The Agave salmiana varieties studied were Ayoteco (Ayo), Púa Larga (PL), Manso (Man), Chalqueño (Chal), Blanco Cenizo (BC), and Sha'mini (Sha), as well as a "Verde" variety known as Cosmimaco (VC). The data was analyzed using the Shapiro-Wilk test (α = 0.05), followed by multiple means comparison using the Tukey procedure (α = 0.05), the Kruskal-Wallis non-parametric test, and the Dunn-Bonferroni test (α = 0.05). In order to differentiate the agave varieties by their chemical compositions, a canonical discriminant analysis (CDA) was applied. The lipid percentage (1.1-1.7 %) and the cellulose content (61-71 %) were higher than those reported for other Agave species. The BC variety contains a high concentration of cellulose and the least amount of lignin, making it a viable option for the energy industry. The CDA identified two discriminant functions that explained 95 % of the variance between the A. salmiana species in this study: ash content and lignin content. The results indicate that the amount of cellulose in pulque maguey leaves is an option to obtain products with a higher commercial value. [ABSTRACT FROM AUTHOR]

Significance: Burn injuries represent a global public health problem that kills an estimated 180,000 people annually. Non-fatal burns result in prolonged hospitalization, disfigurement, and disability. The most common, convenient, and widely used method for assessing burn depth is physical or visual examination, but the accuracy of this method is reportedly poor (60% to 75%). Rapid, correct assessment of burn depth is very important for the optimal management and treatment of burn patients. New methods of burn depth assessment that are inexpensive, simple, rapid, non-contact, and non-invasive are therefore needed. Aim: The aim of this study was to propose an approach to visualize the spatial distribution of burn depth using hemoglobin parameters estimated from spectral diffuse reflectance imaging and to demonstrate the feasibility of the proposed approach for differentiating burn depth in a rat model of scald burn injury. Approach: The new approach to creating a spatial map of burn depth was based on canonical discriminant analysis (CDA) of total hemoglobin concentration, tissue oxygen saturation, and methemoglobin saturation as estimated from spectral diffuse reflectance images. Burns of three different degrees of severity were created in rat dorsal skin by 10-s exposure to water maintained at 70℃, 78℃, and 98℃, respectively. Spectral images for dorsal regions were acquired under anesthesia immediately after burn injury and at 24 h, 48 h, and 72 h after injury. Results: Most areas of images in the group with skin exposed to 70℃ water and 98° C water were classified as 70℃ burn and 98℃ burn, respectively. In contrast, no significant difference between areas classified as 78℃ burn and 98℃ burn from 24 h to 72 h was evident in the group with skin exposed to 78℃ water, suggesting that burn depth was heterogeneous. Conclusions: The proposed approach combining diffuse reflectance spectral imaging and CDA appears promising for differentiating 70℃ burns from 78℃ burns and 98℃ burns, and 98℃ burns from 70℃ burns and 78℃ burns at 24 to 72 h after burn injury in a rat model of scald burn injury. [ABSTRACT FROM AUTHOR]

Cluster analysis has been applied to a wide range of problems as an exploratory tool to enhance knowledge discovery. Clustering aids disease subtyping, i.e. identifying homogeneous patient subgroups, in medical data. Missing data is a common problem in medical research and could bias clustering results if not properly handled. Yet, multiple imputation has been under-utilized to address missingness, when clustering medical data. Its limited integration in clustering of medical data, despite the known advantages and benefits of multiple imputation, could be attributed to many factors. This includes methodological complexity, difficulties in pooling results to obtain a consensus clustering, uncertainty regarding quality metrics, and a lack of accepted pipelines. A few studies have examined the feasibility of implementing multiple imputation for cluster analysis on simulated/small datasets. While these studies have begun to address how to pool imputed values and quantify uncertainty in clustering due to imputation, a need remains for a complete framework that integrates MI in the clustering of complex medical data and sophisticated cluster algorithms. We propose a cluster analysis framework that mitigates bias and addresses these limitations. It includes methods to pool multiple imputed datasets, create a consensus cluster solution by ensemble methods, and select an optimal number of clusters based on validity indices. It also estimates uncertainty about cluster membership attributable to the imputation and identifies features that characterize the derived clusters. The utility of this framework is illustrated by its application to a traumatic brain injury dataset with missing data. Our analysis revealed six multifaceted clusters that differed with respect to Glasgow Coma Score (GCS), mechanism of injury, sociodemographics, vitals, lab values, and radiological presentation. The most severe cluster consisted of single, relatively young patients injured by motor accident, with higher GCS severity scores. Comparative analysis with the miclust R package, along with statistical validation of cluster characterization, demonstrates its robust performance.

Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split plot arrangement and four replications. Main plots received shallow tillage and deep tillage. Subplots were treated with nitrogen (120 kg ha−1) from farmyard manure (FYM) and urea, including control, 33% FYM + 67% urea (MU), and 80% FYM + 20% urea (MF). Acidified hydrochar treatments H0 (no hydrochar) and H1 (with hydrochar, 2 t ha−1) were applied to sub-sub plots. Deep tillage significantly increased plant height, biological yield, grain yield, ear length, grains ear−1, thousand-grain weight, and nitrogen content compared to shallow tillage. MU and MF improved growth parameters and yield over the control. Hydrochar effects varied; H1 enhanced yield components and soil properties such as soil organic matter and nitrogen availability compared to H0. Canonical discriminant analysis linked deep tillage and MU/MF nitrogen management with improved yield and soil characteristics. In conclusion, deep tillage combined with integrated nitrogen management enhances maize productivity and soil properties. These findings highlight the importance of selecting appropriate tillage and nitrogen strategies for sustainable maize production along with hydrochar addition. These insights guide policymakers, agronomists, and agricultural extension services in adopting evidence-based strategies for sustainable agriculture, enhancing food production, and mitigating environmental impacts. The implication of this study suggests to undertake long-term application of hydrochar for further clarification and validation.

Trichinellosis is a parasitic foodborne zoonotic disease transmitted by ingestion of raw or undercooked meat containing the first larval stage (L1) of the nematode. To ensure the quality and safety of food intended for human consumption, meat inspection for detection of Trichinella spp. larvae is a mandatory procedure according to EU regulations. The implementation of quality assurance practices in laboratories that are responsible for Trichinella spp. detection is essential given that the detection of this parasite is still a pivotal threat to public health, and it is included in list A of Annex I, Directive 2003/99/EC, which determines the agents to be monitored on a mandatory basis. A Quality Management System (QMS) was applied to slaughterhouses and game handling establishments conducting Trichinella spp. testing without official accreditation but under the supervision of the relevant authority. This study aims to retrospectively analyze the outcomes of implementing the QMS in slaughterhouses and game handling establishments involved in Trichinella testing in southern Spain. Canonical discriminant analyses (CDAs) were performed to design a tool enabling the classification of SLs while determining whether linear combinations of measures of quality-assurance-related traits describe within- and between-SL clustering patterns. The participation of two or more auditors improves the homogeneity of the results deriving from audits. However, when training expertise ensures that such levels of inter-/intralaboratory homogeneity are reached, auditors can perform single audits and act as potential trainers for other auditors. Additionally, technical procedure issues were the primary risk factors identified during audits, which suggests that they should be considered a critical control point within the QMS. [ABSTRACT FROM AUTHOR]

Genetic diversity and population structure were analyzed using the historical and current pedigree information of the Arabian (PRá), Spanish Purebred (PRE), and Hispano-Arabian (Há) horse breeds. Genetic diversity parameters were computed and a canonical discriminant analysis was used to determine the contributions of ancestor breeds to the genetic diversity of the Há horse. Pedigree records were available for 207,100 animals born between 1884 and 2019. Nei's distances and the equivalent subpopulations number indicated the existence of a highly structured, integrated population for the Há breed, which is more closely genetically related to PRá than PRE horses. An increase in the length of the generation interval might be an effective solution to reduce the increase in inbreeding found in the studied breeds (8.44%, 8.50%, and 2.89%, for PRá, PRE, and Há, respectively). Wright's fixation statistics indicated slight interherd inbreeding. Pedigree completeness suggested genetic parameters were highly reliable. High GCI levels found for number of founders and non-founders and their relationship to the evolution of inbreeding permit controlling potential deleterious negative effects from excessively frequent mating between interrelated individuals. For instance, the use of individuals presenting high GCI may balance founders' gene contributions and consequently preserve genetic diversity levels (current genetic diversity loss in PRá, PRE, and Há is 6%, 7%, and 4%, respectively).

Genetic diversity and population structure were analyzed using the historical and current pedigree information of the Arabian (PRá), Spanish Purebred (PRE), and Hispano-Arabian (Há) horse breeds. Genetic diversity parameters were computed and a canonical discriminant analysis was used to determine the contributions of ancestor breeds to the genetic diversity of the Há horse. Pedigree records were available for 207,100 animals born between 1884 and 2019. Nei's distances and the equivalent subpopulations number indicated the existence of a highly structured, integrated population for the Há breed, which is more closely genetically related to PRá than PRE horses. An increase in the length of the generation interval might be an effective solution to reduce the increase in inbreeding found in the studied breeds (8.44%, 8.50%, and 2.89%, for PRá, PRE, and Há, respectively). Wright's fixation statistics indicated slight interherd inbreeding. Pedigree completeness suggested genetic parameters were highly reliable. High GCI levels found for number of founders and non-founders and their relationship to the evolution of inbreeding permit controlling potential deleterious negative effects from excessively frequent mating between interrelated individuals. For instance, the use of individuals presenting high GCI may balance founders' gene contributions and consequently preserve genetic diversity levels (current genetic diversity loss in PRá, PRE, and Há is 6%, 7%, and 4%, respectively).

Bearing failures are the most frequent causes of breakdowns in rotating machinery. Different levels of severity in these failures exhibit distinct fault characteristics in the vibration signal. This paper presents a bearing fault diagnosis method that considers different severity levels, involving the selection of statistics detection index symptom parameter and the application of canonical discriminant analysis (CDA). Initially, kurtosis is employed to detect abnormalities in the bearing. Subsequently, statistical analysis theory is utilized to extract efficient symptom parameters from the time domain and frequency domain vibration signals. As a statistical analysis method, CDA can discriminate between different signals by maximizing the between-group difference and minimizing the inter-group difference. By analyzing the distribution of CDA canonical scores, bearing faults can be intuitively diagnosed. The proposed method is validated using vibration signals obtained from an experimental bench with three different bearing conditions (normal, inner race fault, outer race fault) exhibiting varying severity levels. The results demonstrate the effectiveness and feasibility of diagnosing faults under different severity levels.

The Atlantic cod was listed as 'vulnerable' by the International Union for Conservation of Nature, a condition that persists today. Fishing pressure on the Atlantic cod could be partially transferred to the Pacific cod, since the two cod species share genetic and phenotypic similarities. The aim of this study is to expand knowledge of the composition of dried salted cod obtained from Atlantic and Pacific cod species, with the Atlantic cod being from two different harvesting locations. The comparison of these cod species revealed the existence of nine significant differences among individual FAs (accountable for 63.2% of total FAs), which was at a similar level to that observed between different harvesting locations for the Atlantic cod (ten significant differences among individual FAs, accountable for 61.6% of total FAs). Canonical discriminant analysis and cross-validation achieved full discrimination of the cod's origin and 100% accuracy in the cod's origin classification. The amount of EPA plus DHA in dried salted cod reached its higher value among the Pacific cod (302.3 mg/100 g), while the Atlantic cod averaged 284.1 g/100 g of edible portion. The Pacific cod presented a higher α-tocopherol content than its Atlantic counterpart (8.04 vs. 4.94 µg/g). [ABSTRACT FROM AUTHOR]

Trichinellosis is a parasitic foodborne zoonotic disease transmitted by ingestion of raw or undercooked meat containing the first larval stage (L1) of the nematode. To ensure the quality and safety of food intended for human consumption, meat inspection for detection of Trichinella spp. larvae is a mandatory procedure according to EU regulations. The implementation of quality assurance practices in laboratories that are responsible for Trichinella spp. detection is essential given that the detection of this parasite is still a pivotal threat to public health, and it is included in list A of Annex I, Directive 2003/99/EC, which determines the agents to be monitored on a mandatory basis. A Quality Management System (QMS) was applied to slaughterhouses and game handling establishments conducting Trichinella spp. testing without official accreditation but under the supervision of the relevant authority. This study aims to retrospectively analyze the outcomes of implementing the QMS in slaughterhouses and game handling establishments involved in Trichinella testing in southern Spain. Canonical discriminant analyses (CDAs) were performed to design a tool enabling the classification of SLs while determining whether linear combinations of measures of quality-assurance-related traits describe within- and between-SL clustering patterns. The participation of two or more auditors improves the homogeneity of the results deriving from audits. However, when training expertise ensures that such levels of inter-/intralaboratory homogeneity are reached, auditors can perform single audits and act as potential trainers for other auditors. Additionally, technical procedure issues were the primary risk factors identified during audits, which suggests that they should be considered a critical control point within the QMS.

In this study we have reported the chemical composition of the essential oils obtained from the needles of twelve Pinus taxa, belonging to the subgenera Pinus (sections Pinus and Trifoliae) and Strobus (sect. Quinquefoliae). Monoterpenes dominated over sesquiterpenes in most of the investigated taxa of both subgenera, except in representatives of the subsection Pinaster, subgenus Pinus. α-Pinene was the most abundant terpene in eight pines, but other dominant terpenes were found in some taxa - trans-caryophyllene, germacrene D, abietadiene and β-pinene. In the subsect. Pinaster, the most dominant compounds varied from species to species. In addition, P. halepensis and P. pinaster had the highest percentage of diterpenes, while P. heldreichii was the richest in germacrene D. In the PCA and cluster analyses, three species from the subsect. Pinaster emerged as the most distant: P. halepensis, P. pinaster, and P. heldreichii. In addition, the possible taxonomic implications of the terpene profile in the analysed Pinus taxa were also discussed.

This study presents a method for discriminating the geographical origin of dried chili peppers using femtosecond laser ablation-inductively coupled plasma-mass spectrometry (fsLA-ICP-MS) and multivariate analysis, such as orthogonal partial least squares discriminant analysis (OPLS-DA), heatmap analysis, and canonical discriminant analysis (CDA). Herein, 102 samples were analyzed for the content of 33 elements using optimized conditions of 200 Hz (repetition rate), 50 μm (spot size), and 90% (energy). Significant differences in count per second (cps) values of the elements were observed between domestic and imported peppers, with variations of up to 5.66 times (133Cs). The OPLS-DA model accuracy achieved an R2 of 0.811 and a Q2 of 0.733 for distinguishing dried chili peppers of different geographical origins. The variable importance in projection (VIP) and s-plot identified elements 10 and 3 as key to the OPLS-DA model, and in the heatmap, six elements were estimated to be significant in discriminating between domestic and imported samples. Furthermore, CDA showed a high accuracy of 99.02%. This method can ensure food safety for consumers, and accurately determine the geographic origin of agricultural products.

Bee pollen is currently one of the most commonly consumed food supplements, as it is considered to be a good source of bioactive substances and energy. It contains various health-promoting compounds, such as proteins, amino acids, lipids, as well as glucosinolates. In the present study, the glucosinolate content was determined, by means of ultra-performance liquid chromatography coupled to a quadrupole time-of-flight mass detector, in 72 bee pollen samples from four different apiaries in Guadalajara (Spain), harvested in three different periods. In addition, 11 commercial multifloral samples from different Spanish regions were also analyzed. The aim was to verify the suitability of these compounds as biomarkers of their geographical origin, and to test their potential for distinguishing the harvesting period. By means of a canonical discriminant analysis, it was possible to differentiate the apiary of origin of most of the samples, and these could also be clearly differentiated from the commercial ones, simply as a result of the glucosinolate content. In addition, it was also demonstrated for the first time that bee pollen samples were capable of being differentiated according to the time of harvesting and their glucosinolate content. [ABSTRACT FROM AUTHOR]

Drought stress has been well documented as an effective parameter in reducing crop production. Hence, developing and releasing new genotypes adapted to water deficit conditions can be a constructive way to overcome to unsuitable environmental conditions. Canonical discriminant analysis (CDA) was used in combination with cluster analysis to evaluate the response of 14 rice genotypes using the drought stress tolerance indices under two conditions of irrigation and discontinued irrigation at a specific time. The CDA results revealed that the first canonical variable was under the influence of high coefficients for the stress tolerance index (STI), harmonic mean (HM), mean production (MP), geometric mean production (GMP), yield in normal conditions (Yp), and yield in stress condition (Ys).The canonical coefficients of the stress sensitivity index (SSI) and tolerance index (TOL) were significant in the second canonical variable. Accordingly, the first canonical variable distinguished the genotypes based on yield potential and stress tolerance, while the second one segregated the susceptible and tolerant genotypes. The scatter plot chart of two significant canonical variables distinguished three groups, and all pairs of Mahalanobis distances between groups were significant. The second group was recognized as the best group, since its genotypes had the maximum value for the first canonical variable, while most of these genotypes had low values for the second one. Therefore, the genotypes of this group (831, Fajr, Sepidrood and Sahel) can be selected as suitable genotypes for stress and non-stress conditions.

This study focuses on discriminating the seed content in red pepper powders using 1H NMR and second‐derivative FT‐IR Spectroscopy with canonical discriminant and multiple linear regression analyses. We used 165 test samples prepared by varying the seed content for spectroscopic analyses. The canonical discriminant functions derived from 21 peak variables were used to properly discriminate the red pepper powder samples based on their seed content with a 97.6% hit ratio. Additionally, we observed an average error of 7.0% while discriminating 42 blind samples. Multiple linear regression analysis was performed to directly determine the seed content of new samples without running a statistical program. The best regression model constructed with only two variables showed an average error of 6.2% when applied to the blind samples. These results verify the feasibility of using 1H NMR and FT‐IR Spectroscopy with statistical analyses to determine the seed content in red pepper powders. [ABSTRACT FROM AUTHOR]

This article demonstrates an approach to digital mapping of soil drainage in Vladimir Opolie controlled by topographic conditions. Topographic conditions of the key area are described by a digital terrain model and morphometric parameters with resolution of 30 m. The variety of soil drainage is represented by soil survey data of the RSFSR Goskomzem, which includes 170 soil observations with morphological characteristic of the degree of soil hydromorphism. Linear combination of the most significant morphometric parameters is calculated by the means of canonical discriminant analysis. This combination also interpreted as topographically induced soil drainage explains 70% of spatial variation of soil hydromorphism. Scores above 0.5 relate to gray forest soils of well drained moraine-erosional plains, gently and steep slopes of valleys. Scores below 0.5 relate to gleyic grey forest soils of shallow slopes of plains, deep valleys and depressions with poor soil drainage conditions.

Bali cattle (Bos javanicus) is an important livestock for the farmers at Jambi Province of Indonesia for meat production purposes. This research was aimed to classify adult Bali cattle (about 3.5 years age) based on their body measurements (morphometrics). The animals in this study were collected from two different altitude areas (lowland and midland) of Jambi province. A canonical discriminant analysis (CDA) was computed in this study for discrimination of animals. A total of 480 animals collected from lowland (180 animals) and midland (300 animals) areas were used in the present study. Thus, seven (7) morphometrical measurements of body length (BL), withers height (WH), chest girth (CG), chest depth (CD), shoulder width (SW), canon circumference (CC) and rump height (RH) were measured in each animal. Research showed that four (4) body measurements, viz. BL, CG, SW and RH were described as the discriminating variables with a canonical correlation of 0.83 (very high). In conclusion, about 90% of Bali cattle at lowland and midland areas could be classified using body measurements.

The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes.Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010 to 2012 for oiled and non-oiled shorelines.CDA discriminated dominant species with a high level of accuracy (overall accuracy=82%, kappa=0.78) and consistency over three imaging dates (overall2010=82%, overall2011=82%, overall2012=88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (≤28m from shore) for all three dates (2010=79%, 2011=61%, 2012=63%), followed by Juncus roemerianus (2010=11%, 2011=19%, 2012=17%) and Distichlis spicata (2010=4%, 2011=10%, 2012=7%).Marshes that were heavily contaminated with oil exhibited variable responses from 2010 to 2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only S. alterniflora dominated marshes were extensively degraded, losing 15% (354,604m2) cover in oiled shoreline zones, suggesting that S. alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position.

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We present a framework for an explainable and statistically validated ensemble clustering model applied to Traumatic Brain Injury (TBI). The objective of our analysis is to identify patient injury severity subgroups and key phenotypes that delineate these subgroups using varied clinical and computed tomography data. Explainable and statistically-validated models are essential because a data-driven identification of subgroups is an inherently multidisciplinary undertaking. In our case, this procedure yielded six distinct patient subgroups with respect to mechanism of injury, severity of presentation, anatomy, psychometric, and functional outcome. This framework for ensemble cluster analysis fully integrates statistical methods at several stages of analysis to enhance the quality and the explainability of results. This methodology is applicable to other clinical data sets that exhibit significant heterogeneity as well as other diverse data science applications in biomedicine and elsewhere.

Objective: To determine the morphological characteristics of variations in populations of female adult sand fly, Sergentomyia anodontis Quate and Fairchild, 1961 in caves in southern Thailand using morphometric analysis. Methods: A total of 107 female Sergentomyia anodontis were isolated from 651 sand flies captured by CDC light traps overnight in caves in Surat Thani, Nakhon Si Thammarat, Satun and Songkhla provinces from February to December 2017. Measurement of 23 external and internal morphological characteristics was conducted. Data were tested with preliminary statistics (Kolmogorov-Smirnov test, Levene’s test and Box’s test of equality of covariance matrices) and by one-way ANOVA or Kruskal-Wallis test. Measurements were analyzed using canonical discriminant analysis. Results: There were 11 morphological characteristics with high variability while two characteristics exhibited low variation. The sand fly populations from Nakhon Si Thammarat, Satun and Songkhla provinces were very similar but were separate from that in Surat Thani province based on canonical discriminant analysis data. This indicates that the morphological variation founding is a result of the diversity of habitats in each population and the geographic features of caves in each area, such as their altitude above sea level. Conclusions: There is a certain variation in the morphology of Sergentomyia anodontis sand flies at the population level which may be used for future classification of sand flies.

Breed characterization in the livestock is important to obtain the breed standard of livestock for selection program. This research was aimed to characterize the Begait cows (Bos indicus) reared in two different farming systems (on-farm and ranch) in Ethiopia using 15 body measurements. A total of 344 adult Begait cows kept in on-farm (n = 237) and ranch (n = 107) systems were involved in this study. The principal component analysis (PCA) was performed to describe the morphostucture of the animal study. Thus, the canonical discriminant analysis (CDA) was performed to classify the animals from two different farming systems. The PCA and CDA analyses were performed using SPSS 16.0 computer program. The results revealed three principal components (PC's) in animals reared in on-farm system, and four PC's were found in animals reared in the ranch system. Thus, the PCA in this study able to explain the morphostructure of cows about 52.01 % (on-farm) and 63.26 % (ranch). Morever, seven body measurements were detected as the discriminant variables for Begait cows with canonical correlation (rc ) of 0.57 (moderate). In addition, the discriminant analysis of body measurements able to classify Begait cows about 77.6 % (on-farm) and 82.2 % (ranch system) into their original farming system. It can be concluded that the morphostructure of Begait cows appears to be affected by the differences in management systems, indicating their usefulness for breeding programs in the future. [ABSTRACT FROM AUTHOR]

Many aspects concerning the role of arbuscular mycorrhizal (AM) fungi in plant nutrient uptake from organic sources remain unclear. Here, we investigated the contribution of AM symbiosis to N and P uptake by durum wheat after the addition of a high C:N biomass to a P-limited soil. Plants were grown in pots in the presence or absence of a multispecies AM inoculum, with (Org) or without (Ctr) the addition of 15N-labelled organic matter (OM). A further treatment, in which 15N was applied in mineral form (Ctr+N) in the same amount as that supplied in the Org treatment, was also included. Inoculation with AM had positive effects on plant growth in both control treatments (Ctr and Ctr+N), mainly linked to an increase in plant P uptake. The addition of OM, increasing the P available in the soil for the plants, resulted in a marked decrease in the contribution of AM symbiosis to plant growth and nutrient uptake, although the percentage of mycorrhization was higher in the Org treatment than in the controls. In addition, mycorrhization drastically reduced the recovery of 15N from the OM added to the soil whereas it slightly increased the N recovery from the mineral fertiliser. This suggests that plants and AM fungi probably exert a differential competition for different sources of N available in the soil. On the whole, our results provide a contribution to a better understanding of the conditions under which AM fungi can play an effective role in mitigating the negative effects of nutritional stresses in plants. [ABSTRACT FROM AUTHOR]

Morphometry of 53 stingless bees of the genus Lisotrigona collected from seven places in India by using 36 morphological parameters was studied. The data set also included morphometry data of primary types of L. cacciae, L. chandrai and L. revanai for comparison and was subjected to Factor and Canonical Discriminant analysis. All the bees collected from seven places formed two distinct clusters in the Factor analysis and five clusters in Canonical Discriminant analysis. In both the methods of analysis primary types of L. cacciae, L. chandrai and L. revanai were placed well separated from each other as well as from other bees. The bees from seven places also differed from the three known species in morphometry and ratios of length and width of parts of the body. Based on these results it is concluded that Indian stingless bees of the genus Lisotrigona consists of more than one species besides L. cacciae. The action of synonymizing L. mohandasi, L. chandrai and L. revanai with L. cacciae appears arbitrary; these three species should be considered valid until supported by male genital morphology or molecular characters. [ABSTRACT FROM AUTHOR]

Differentiating between subcortical ischemic vascular disease (SIVD), Alzheimer's disease (AD), and normal cognition (NC) remains a challenge, and reliable neuroimaging biomarkers are needed. The current study, therefore, investigated the discriminative ability of diffusion kurtosis imaging (DKI) metrics in segregated thalamic regions and compare with diffusion tensor imaging (DTI) metrics. Twenty‐three SIVD patients, 30 AD patients, and 24 NC participants underwent brain magnetic resonance imaging. The DKI metrics including mean kurtosis (MK), axial kurtosis (Kaxial) and radial kurtosis (Kradial) and the DTI metrics including diffusivity and fractional anisotropy (FA) were measured within the whole thalamus and segregated thalamic subregions. Strategic correlations by group, thalamo‐frontal connectivity, and canonical discriminant analysis (CDA) were used to demonstrate the discriminative ability of DKI for SIVD, AD, and NC. Whole and segregated thalamus analysis suggested that DKI metrics are less affected by white matter hyperintensities compared to DTI metrics. Segregated thalamic analysis showed that MK and Kradial were notably different between SIVD and AD/NC. The correlation analysis between Kaxial and MK showed a nonsignificant relationship in SIVD group, a trend of negative relationship in AD group, and a significant positive relationship in NC group. A wider spatial distribution of thalamo‐frontal connectivity differences across groups was shown by MK compared to FA. CDA showed a discriminant power of 97.4% correct classification using all DKI metrics. Our findings support that DKI metrics could be more sensitive than DTI metrics to reflect microstructural changes within the gray matter, hence providing complementary information for currently outlined pathogenesis of SIVD and AD. [ABSTRACT FROM AUTHOR]

Bee pollen is currently one of the most commonly consumed food supplements, as it is considered to be a good source of bioactive substances and energy. It contains various health-promoting compounds, such as proteins, amino acids, lipids, as well as glucosinolates. In the present study, the glucosinolate content was determined, by means of ultra-performance liquid chromatography coupled to a quadrupole time-of-flight mass detector, in 72 bee pollen samples from four different apiaries in Guadalajara (Spain), harvested in three different periods. In addition, 11 commercial multifloral samples from different Spanish regions were also analyzed. The aim was to verify the suitability of these compounds as biomarkers of their geographical origin, and to test their potential for distinguishing the harvesting period. By means of a canonical discriminant analysis, it was possible to differentiate the apiary of origin of most of the samples, and these could also be clearly differentiated from the commercial ones, simply as a result of the glucosinolate content. In addition, it was also demonstrated for the first time that bee pollen samples were capable of being differentiated according to the time of harvesting and their glucosinolate content.

Abstract The soil tillage practiced over a long period of time impacts soil quality. The first step in soil quality assessment is to select which indicators should be used. The objective of this study was to identify the soil attributes that discriminate soil tillage systems and can be used as indicators for soil quality assessments. Sixteen soil physical and chemical attributes were evaluated: macroporosity (MaP), microporosity (MiP), total porosity (TP), bulk density (BD), field-saturated hydraulic conductivity (Kfs), soil resistance to penetration (SRP), pH (H2O), pH (CaCl2), aluminium (Al), calcium (Ca), magnesium (Mg), potassium (K), available phosphorus (P), total organic carbon (TOC), cation exchange capacity (CEC) and base saturation (BS), of a very clayey Red Latosol, cultivated for a long period in no-till (NT), conventional tillage (CT) and minimum tillage (MT). The soil attributes (indicators) were selected using canonical discriminant analysis. MiP, Kfs, pH (CaCl2), Ca, Mg, CEC e BS were the most efficient indicators to discriminate soil tillage systems. In the indicator interpretation step was sustained MiP as the indicator that represents the function of physical stability and support, Kfs as the indicator that represents the function of water relations, BS as the indicator that represents the function of nutrient cycling and pH (CaCl2) as the indicator that represents the function of filtering and buffering. These indicators can be used for future soil quality assessment and monitoring of tillage systems in similar regions and conditions.

Objectives Near-infrared (NIR) spectroscopy is a rapid technique able to assess meat quality even if its capability to determine the shelf life of chicken fresh cuts is still debated, especially for portable devices. The aim of the study was to compare bench-top and portable NIR instruments in discriminating between four chicken breast refrigeration times (RT), coupled with multivariate classifier models. Materials and Methods Ninety-six samples were analysed by both NIR tools at 2, 6, 10 and 14 days post mortem. NIR data were subsequently submitted to partial least squares discriminant analysis (PLS-DA) and canonical discriminant analysis (CDA). The latter was preceded by double feature selection based on Boruta and Stepwise procedures. Results PLS-DA sorted moderate separation of RT theses, while shelf life assessment was more accurate on application of Stepwise-CDA. Bench-top tool had better performance than portable one, probably because it captured more informative spectral data as shown by the variable importance in projection (VIP) and restricted pool of Stepwise-CDA predictive scores (SPS). Conclusions NIR tools coupled with a multivariate model provide deep insight into the physicochemical processes occurring during storage. Spectroscopy showed reliable effectiveness to recognise a 7-day shelf life threshold of breasts, suitable for routine at-line application for screening of meat quality. [ABSTRACT FROM AUTHOR]

Bee pollen may be contaminated with pyrrolizidine alkaloids (PAs) and their N-oxides (PANOs), which are mainly detected by liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS), even though the use of fast near-infrared (NIR) spectroscopy is an ongoing alternative. Therefore, the main challenge of this study was to assess the feasibility of both a lab-stationary (Foss) and a portable (Polispec) NIR spectrometer in 60 dehydrated bee pollen samples. After an ANOVA-feature selection of the most informative NIR spectral data, canonical discriminant analysis (CDA) was performed to distinguish three quantitative PA/PANO classes (µg/kg): < LOQ (0.4), low; 0.4–400, moderate; > 400, high. According to the LC–MS/MS analysis, 77% of the samples were contaminated with PAs/PANOs and the sum content of the 17 target analytes was higher than 400 µg/kg in 28% of the samples. CDA was carried out on a pool of 18 (Foss) and 22 (Polispec) selected spectral variables and allowed accurate classification of samples from the low class as confirmed by the high values of Matthews correlation coefficient (≥ 0.91) for both NIR spectrometers. Leave-one-out cross-validation highlighted precise recognition of samples characterised by a high PA/PANO content with a low misclassification rate (0.02) as false negatives. The most informative wavelengths were within the < 1000, 1000–1660 and > 2400 nm regions for Foss and > 1500 nm for Polispec that could be associated with cyclic amines, and epoxide chemical structures of PAs/PANOs. In sum, both lab-stationary and portable NIR systems are reliable and fast techniques for detecting PA/PANO contamination in bee pollen. [ABSTRACT FROM AUTHOR]

This study was conducted to clarify relationship between putter head motions of golf and ball hitting direction, distance with use of statistical techniques. Measurement was carried out by measuring systems for golf putting which composed of 3D gyro sensor and infrared sensors. From the measurement data, 27 parameters related to putting were selected. From the 27 parameters, 10 parameters related to hitting distance and direction were selected by analysis of variance. 10 parameters were applied principal component analysis to eliminate data redundancy. Using the first to forth principal components obtained by principal component analysis, the hitting distance and direction were learned and identified by the neural network. In addition, it was shown from the principal component analysis, angle around y axis, z axis at impact, angle about z axis, maximum of angular velocity, angular velocity around z axis at impact,the maximum and minimum angles around the y axis are important parameter for expressing the ball hitting result. Moreover it was shown that the parameter that most influence the estimation of the hit ballistic result are the angle around the y axis at the time of impact, and the angular velocity around the z axis at the time of impact.

Grain amaranth refers to three species of genus Amaranthus (Amaranthus cruentus, A. hypochondriacus, and A. caudatus), which show a high morphological diversity, which is why it is treated since the 1990s to differentiate landraces and to contribute to the breeding programs. The aim of this investigation was to evaluate 53 genotypes within the native landraces: Aztec, Mercado, Mixtec, Nepal (A. hypochondriacus), African, Guatemalan, Mexican (A. cruentus), and South American (A. caudatus) using morphological and phenological traits. INIFAPCEVAMEX accessions were used and planted at Santa Lucía de Prías, México (2013 spring-summer growing cycle) in order to record phenological and morphological data. Seeds were digitalized and analysed on ImageTool. Then, the Mahalanobis distance, a canonical discriminant analysis using landraces as classificatory variable, a MANOVA, and a Tukey mean comparison for canonical roots were performed; all analyses were processed on SAS. The canonical discriminant analysis perfectly distinguished the landraces, which was grouped according to the species. The main traits to distinguish the groups for Canonical Root 1 were traits related to phenology and plant morphology; for Canonical Root 2, traits related to shape of the seed, and for Canonical Root 3, traits related to size of the seed. Classification by landraces of the Mexican species of grain amaranth may be an alternative for systematics, conservation, management, and germplasm ordination for crop improvement. [ABSTRACT FROM AUTHOR]

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The pollinating weevil, Elaeidobius kamerunicus was introduced to Malaysia as an oil palm pollinator agent in 1981. After the introduction, the weevil has distributed widely in the oil palm plantation around Malaysia. This study aims to investigate the morphometric differences in Elaeidobius kamerunicus population within Malaysia, as well as from its originating country, Cameroon. A total of 540 weevils were collected from eight localities in Malaysia, and 60 from Cameroon, Africa. The five morphological measurements were taken ie. total body length (TL), elytra length (EL), pronotum length (PL), body width (BW) and the snout length (SL) using the Portable Capture Pro v2.1 Dinolite. The one-way ANOVA indicated significant differences amongst the five morphological characteristics between the weevil populations for both males and females from the eight localities (P < 0.05), respectively. For the male and female populations at different localities, the Principal Component Analysis explained 79.0% and 76.6%, respectively. Moreover, the Canonical Discriminant Function explained 95.5% and 90.2% of the variance for male and female population, respectively. Both the result of PCA and CDA conducted showed little variation between the eight localities for male and female weevil populations in Malaysia respectively. This study showed slight differences in morphometric characters for the weevil population in Malaysia. [ABSTRACT FROM AUTHOR]

Recognize water stress constraints on common bean growth may help to select tolerant genotypes, manage irrigation based on plant necessity and predict losses. This manuscript aims to select key traits that discriminate magnitudes of water stress on common bean and indicates plant growth constrains. To do so, an experiment was set in a greenhouse with two factors: crop evapotranspiration replenishment and cultivars. First factor was composed of 25%, 50%, 75%, 100%, 125% and 150% of crop evapotranspiration replenishment starting at flowering (32 days after germination), and second factor of the cultivars BRS Estilo and IPR Campos Gerais. A randomized block scheme with five replications was used, totalizing 60 experimental units. On the 55th day after germination, we analysed morphological (steam diameter, leaf area, and number of trifoliolates) and physiological (net assimilation of CO2, stomatal conductance, leaf transpiration, and total content of chlorophyll) traits. A multivariate analysis of variance indicated single effect of crop evapotranspiration replenishment. Then, a canonical discriminant analysis was applied and the discrimination was confirmed by the Scott-Knott hierarchical clustering. We harvested the plants to correlate the selected traits with the aerial dry weight to determine its ability to assess plant growth indirectly. The traits related to leaf gas exchanges were the strongest discriminators of levels of water stress and had moderated correlation with common bean growth. For instance, when assessing the net assimilation of CO2 during most stressful periods of the day, it was the most promisor trait that can be used singly that integrate both objectives. [ABSTRACT FROM AUTHOR]

The present study aimed to valorize olive mill wastewater (OMW) as biofertilizers to improve plant growth and soil properties. We investigated purple beans (Phaseolus vulgaris L.) subjected to OMW application at two moderate doses (50 and 100 m³ ha–1) once at the time of beans sowing under field conditions. Our results showed that both OMW doses greatly improved plant growth. Moreover, nutrient contents also increased using 50 m³ ha–1 dose of OMW. Physiological parameters as stomatal conductance increased significantly in plants treated with OMW, while electrolyte leakage (EL) was decreased in irrigated plants with OMW. Application of OMW at rate of 100 m³ ha–1 significantly increased peroxidase, polyphenoloxidase, endogenous peroxide hydrogen, and total phenols. Moreover, the catalase and lipid peroxidation activities were significantly increased at both doses of OMW. According to the canonical discriminant analysis (CDA), the three treatments were separated by the following growth, nutrient uptake, physiological, and biochemical traits: Shoot height, dry, and shoot weight, available P, gs, K+, Ca2+, total phenols, number of fruits, EL, and malonyldialdehyde activity. [ABSTRACT FROM AUTHOR]

Pteridium aquilinum subsp. pinetorum is one of two morphologically distinct taxa of the genus Pteridium identified in Poland. In order to confirm their distinctively recognizable morphology, nine features defining each of these taxa were subjected to a morphometric analysis. These features, including taxonomic characters of vegetative structures, were measured or counted for their most comprehensive descriptions. The measurements were also expressed as ratios of two characters (length of the first and second pairs of leaflets) to prevent the size of fronds from influencing the results. Unique features of bracken, such as: frond and pinnae shape and orientation; basal pinna structure; ultimate segment of pinnae and pinnula shape and size; frond expansion sequencing; frond lamina texture, shape and pubescence were treated descriptively. Canonical discriminant analysis was employed for a morphometric study of quantitative characters. On their basis, two taxa – P. aquilinum subsp. aquilinum and P. a. subsp. pinetorum were determined. [ABSTRACT FROM AUTHOR]

Here, we describe a new species of the genus Hynobius from Chugoku, Japan. In populations from central to eastern Shimane Prefecture, the Izumo Lineage of Hynobius utsunomiyaorum was clearly distinguished from the true Hynobius utsunomiyaorum based on morphological and molecular evidence. Thus, we describe the former lineage as a new species, Hynobius kunibiki sp. nov. Morphological comparisons revealed that H. utsunomiyaorum lacks a distinct yellow line on the ventral side of its tail, whereas the new species possesses this yellow line; most H. utsunomiyaorum individuals have distinct white spots on the lateral sides of their body and lack a fifth toe, whereas the new species largely lacks these spots, and all examined individuals had a fifth toe. The two species also differed significantly by several other morphological characteristics. The lentic species Hynobius setoi is morphologically similar to H. kunibiki sp. nov., but they differ significantly by various morphological characteristics. Despite their partial morphological similarity, these two species differed substantially in terms of their genetics. Finally, we show, in a phylogenetic tree including all Japanese Hynobius species, that the subgenus Hynobius can be divided into four genetic clades. Overall, this information will help develop conservation management strategies and policies for these species.

Salt stress is a major constraint of crop productivity because it reduces yield and limits the expansion of agriculture. This study investigated salt tolerance in 26 cultivars of cut lilies (Lilium hybrids) by examining the effect of salt stress on the growth and morphological characteristics of flowers and leaves and their physiological properties (chlorophyll a fluorescence). Salt stress significantly affected the growth and development of cut lilies. Canonical discriminant analysis indicates that the middle leaf width, number of flowers, first flower diameter, petal width, and chlorophyll a fluorescence were correlated with salt stress, whereas plant height, the middle leaf length, days to flowering, and sepal width were less affected by the stress. The cultivars examined were divided into three groups: Group 1 included the salt-sensitive cultivars, which failed to develop normal flowers; Group 2 included cultivars sensitive to salt stress but tolerant to osmotic stress; and Group 3 was the salt-tolerant group, which developed commercially valuable flowers. In conclusion, the cultivars contained a variable range of cut flower characteristics and growth traits that can be employed for lily breeding programs and as material for molecular mechanisms and signaling networks under salt stress.

Writers are often viewed as having an inherent style which can serve as a literary fingerprint. By quantifying relevant features related to literary style, one may hope to classify written works and even attribute authorship to newly discovered texts. Beyond its intrinsic interest, the study of literary styles presents the opportunity to introduce and motivate many standard multivariate statistical techniques. Today the statisti- cal analysis of literary styles is made much simpler by the wealth of real data readily available from the Internet. This paper presents an overview and brief history of the analysis of literary styles. In addition we use canonical discriminant analyis and prin- cipal component analysis to identify structure in the data and distinguish authorship.

Writers are often viewed as having an inherent style which can serve as a literary fingerprint. By quantifying relevant features related to literary style, one may hope to classify written works and even attribute authorship to newly discovered texts. Beyond its intrinsic interest, the study of literary styles presents the opportunity to introduce and motivate many standard multivariate statistical techniques. Today the statistical analysis of literary styles is made much simpler by the wealth of real data readily available from the Internet. This paper presents an overview and brief history of the analysis of literary styles. In addition we use canonical discriminant analysis and principal component analysis to identify structure in the data and distinguish authorship.