Multivariate Principal Component Analysis Research Articles

Multivariate spatiotemporal functional principal component analysis for modeling hospitalization and mortality rates in the dialysis population.

Dialysis patients experience frequent hospitalizations and a higher mortality rate compared to other Medicare populations, in whom hospitalizations are a major contributor to morbidity, mortality, and healthcare costs. Patients also typically remain on dialysis for the duration of their lives or until kidney transplantation. Hence, there is growing interest in studying the spatiotemporal trends in the correlated outcomes of hospitalization and mortality among dialysis patients as a function of time starting from transition to dialysis across the United States Utilizing national data from the United States Renal Data System (USRDS), we propose a novel multivariate spatiotemporal functional principal component analysis model to study the joint spatiotemporal patterns of hospitalization and mortality rates among dialysis patients. The proposal is based on a multivariate Karhunen-Loéve expansion that describes leading directions of variation across time and induces spatial correlations among region-specific scores. An efficient estimation procedure is proposed using only univariate principal components decompositions and a Markov Chain Monte Carlo framework for targeting the spatial correlations. The finite sample performance of the proposed method is studied through simulations. Novel applications to the USRDS data highlight hot spots across the United States with higher hospitalization and/or mortality rates and time periods of elevated risk.

Physico-Chemical Properties of Brazilian Eastern Amazon Honey Assessed by Multivariate Principal Components Analysis

Honey from the Apis mellifera bee (Hymenoptera, Apidae) is one of the most consumed beehive products in the world, mainly due to its nutritional and therapeutic value. In poorer regions, its commercialization can be an essential source of income for families and communities. However, the quality of honey can change both during harvesting and processing, as well as by climatic conditionsand the type of vegetation. Therefore, implementing good production practices, with quality control in collection and processing, can add value to this product, promoting the development of the region in which it is produced. Thus, the objectives of this work were to characterize the honey of Africanized honeybees produced in the Eastern Amazon region in the cities of Nova Olinda do Maranhão(NO), Santa Luzia do Paruá (SL) and verify its correlation with a commercial honey sample (CH) – from São Luiz-MA. The physicochemical properties (color, moisture, solids insoluble in water, minerals, and ash, hydroxymethylfurfural, acidity, anddiastatic activity) were analyzed according to the methods of CODEX Alimentarius and the Association of Official Analytical Chemists, and these data were evaluated by the Principal Component Analysis (PCA). The results showed that commercial honey presented higher levels of insoluble solids, HMF, minerals, and ash than samples from NO and SL. Variables that differentiated NO and SL honey were HMF, moisture, and diastase index. Although the samples have different characteristics, the data comply with Brazilian legislation, which can strengthen the development of apiculture in the region.

Longitudinal Morphometric Changes in the Corticospinal Tract Shape After Hemorrhagic Stroke.

Deep intracerebral hemorrhage (ICH) exerts a direct force on corticospinal tracts (CST) causing shape deformation. Using serial MRI, Generalized Procrustes Analysis (GPA), and Principal Components Analysis (PCA), we temporally evaluated the change in CST shape. Thirty-five deep ICH patients with ipsilesional-CST deformation were serially imaged on a 3T-MRI with a median imaging time of day-2 and 84 of onset. Anatomical and diffusion tensor images (DTI) were acquired. Using DTI color-coded maps, 15 landmarks were drawn on each CST and the centroids were computed in 3 dimensions. The contralesional-CST landmarks were used as a reference. The GPA outlined the shape coordinates and we superimposed the ipsilesional-CST shape at the two-time points. A multivariate PCA was applied to identify eigenvectors associated with the highest percentile of change. The first three principal components representing CST deformation along the left-right (PC1), anterior-posterior (PC2), and superior-inferior (PC3) respectively were responsible for 57.9% of shape variance. The PC1 (36.1%, p < 0.0001) and PC3 (9.58%, p < 0.01) showed a significant deformation between the two-time points. Compared to the contralesional-CST, the ipsilesional PC scores were significantly (p < 0.0001) different only at the first-timepoint. A significant positive association between the ipsilesional-CST deformation and hematoma volume was observed. We present a novel method to quantify CST deformation caused by ICH. Deformation most often occurs in left-right axis (PC1) and superior-inferior (PC3) directions. As compared to the reference, the significant temporal difference at the first time point suggests CST restoration over time.

Petroleum Geochemistry of the Central and Eastern Onshore Niger Delta Basin: Oil-Oil Correlation Using Biomarkers and Multi-Variate Statistics

Petroleum geochemistry of oils in several depobelts of the world has been well documented based on biomarkers. However, there is paucity of data regarding the use of multi-variate statistics in oil-oil correlation study, particularly in the Sub-Saharan African region. The purpose of the study was to gain an insight into the geochemical differences and identify their cause(s) through the application of bulk properties, biomarker indices and multi-variate statistics. Correlation of oils from eight wellheads of three stratigraphic units within the Central and Eastern onshore Niger Delta Basin fields (AG and AS) were undertaken by gas chromatography-flame ionization detector. Utilization of bulk properties, biomarker indices and cross plot parameters somewhat separated the mature AG1-4, AS3 and AS4 oils deposited in oxic/suboxicshaly environment from AS2 oil deposited in anoxic fluvio deltaic environment. In-reservoir alteration and migration differences were the major factors responsible for the observed slight geochemical variability in the studied oils. Nevertheless, multi-variate principal component analysis indicated that the Central and Eastern onshore Niger Delta Basin oils were principally generated from similar organic matter sources. The implication here was that the geochemical variations in the studied oils were not significant, a conclusion corroborated by Pearson correlation model data.

Alteration of metabolic profile during the progression of Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of how altered metabolism involves AD pathology are poorly understood. This study intends to provide novel insights into the role of metabolic alteration in the pathology and identify potential metabolic biomarkers for AD diagnosisMethodThe Gas chromatography‐mass spectrometry (GC‐MS) was used to measure the concentrations of serum metabolites in a cohort of subjects with AD (n = 88) and cognitively normal control (CN) (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). Serum metabolic profiles were analyzed by multivariate (principal component analysis) and univariate approaches (t‐tests, false discovery, receiver operating characteristic curves, and correlation analysis). The artificial neural network model (ANN) was applied to identify potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes.ResultThe results revealed considerable separation between the AD and CN patients. Edetic acid, (S)‐3,4‐Dihydroxybutyric acid, and arachidonic acid were identified as potential AD diagnostic biomarkers using an ANN model. And the classification model could predict the risk for AD with high accuracy (AUC = 0.93). The most significant changes in the metabolite’s composition occur during the very mild to the mild stage. The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and disturbance of amino acids, fatty acids, and lipids metabolism are involved in AD progression. Especially, pathway analysis highlighted that l−glutamate participated in four crucial nervous system pathways (including GABAergic synapse, glutamatergic synapse, retrograde endocannabinoid signaling and synaptic vesicle cycle).ConclusionSerum metabolomic analysis demonstrated that the metabolic alterations had already arisen at the very mild stages of dementia. Disrupt energy metabolism may be the core of the vicious cycle in AD, resulting in a wide range of metabolic disorders, including abnormal glucose metabolism, TCA cycle impairments, amino acids, fatty acids, and lipids dysregulation. Furthermore, a metabolic diagnostic model of AD was constructed using ANN, which could robustly differentiate AD patients from CN. Our study identified new markers for AD diagnosis and highlighted the roles of metabolic changes on the progression of AD.

Investigating the Urinary Metabolome in the First Year of Life and Its Association with Later Diagnosis of Autism Spectrum Disorder or Non-Typical Neurodevelopment in the MARBLES Study.

Developmental disabilities are often associated with alterations in metabolism. However, it remains unknown how early these metabolic issues may arise. This study included a subset of children from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) prospective cohort study. In this analysis, 109 urine samples collected at 3, 6, and/or 12 months of age from 70 children with a family history of ASD who went on to develop autism spectrum disorder (ASD n = 17), non-typical development (Non-TD n = 11), or typical development (TD n = 42) were investigated by nuclear magnetic resonance (NMR) spectroscopy to measure urinary metabolites. Multivariate principal component analysis and a generalized estimating equation were performed with the objective of exploring the associations between urinary metabolite levels in the first year of life and later adverse neurodevelopment. We found that children who were later diagnosed with ASD tended to have decreased urinary dimethylamine, guanidoacetate, hippurate, and serine, while children who were later diagnosed with Non-TD tended to have elevated urinary ethanolamine and hypoxanthine but lower methionine and homovanillate. Children later diagnosed with ASD or Non-TD both tended to have decreased urinary 3-aminoisobutyrate. Our results suggest subtle alterations in one-carbon metabolism, gut-microbial co-metabolism, and neurotransmitter precursors observed in the first year of life may be associated with later adverse neurodevelopment.

Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions

ABSTRACT This article investigates a physics-informed statistical approach capable of (i) learning nonlinear system dynamics by using data generated from a nonlinear system as well as the underlying governing physics, and (ii) predicting system dynamics with reasonable accuracy and a computational speed much faster than numerical methods. The proposed approach obtains the reduced-order model from the full-order governing equations. A function-to-function regression, based on multivariate Functional Principal Component Analysis, establishes the mapping between external forcing and system dynamics, while a multivariate Gaussian Process is used to capture the relationship between parameters and external forcing. In the application, the proposed approach is applied to predict aircraft nose skin deformation after Unmanned Aerial Vehicle (UAV) collisions at different impact attitudes (i.e., pitch, yaw and roll degrees). We show that the proposed physics-informed statistical model can achieve a 12% out-of-sample mean relative error, and is more than 103 times faster than Finite Element Analysis (FEA). Computer code and sample data are available on GitHub.

Liming and micronutrient application improves soil properties and productivity of the groundnut‐rapeseed cropping system in an acidic Inceptisol of India's eastern Himalayas

AbstractAluminum toxicity, nutrient imbalance, and reduced microbial activity are the most limiting factors for optimum agronomic productivity in acid soils. A field study was conducted to investigate the impact of micronutrient and liming on soil properties and productivity of groundnut‐rapeseed system in an acidic Inceptisol. The impact of six micronutrient (control or no micronutrient, Zn at 5 kg ha−1, B at 1 kg ha−1, Mo at 0.5 kg ha−1, Zn + Mo, and Zn + B + Mo) and two soil amendment (furrow liming at 500 kg ha−1 and no lime addition) treatments were first tested in groundnut and theirs residual effects were assessed on soil properties of succeeding rapeseed crop. Results indicated that liming significantly improved soil pH, soil organic carbon (SOC), available N, P and K, and diethylene triamine penta acetate (DTPA)‐extractable micronutrients, soil microbial biomass C and dehydrogenase activity as compared to no‐lime. After harvesting groundnut, Mo + Zn + B treated plots maintained the highest SOC content, whereas sole B and Mo treatment had the highest SOC content after harvesting rapeseed. Further, Mo + Zn + B treated plots showed higher contents of soil DTPA‐extractable micronutrients as compared to others. The highest groundnut equivalent yield (GEY) of the cropping system (pooled data of 2 years) was obtained with Mo + Zn + B (2.12 Mg ha−1) but remained at par with Zn + Mo (2.02 Mg ha−1). Multivariate principal component analysis indicated that available P was the most prominent soil nutrient with a strong effect on GEY. The results indicated that integrated application of Zn + B + Mo along with liming improves soil properties and agronomic productivity of groundnut‐rapeseed cropping system.

Application of Lipidomics in Psychiatry: Plasma-Based Potential Biomarkers in Schizophrenia and Bipolar Disorder

In this study, we obtained a lipidomic profile of plasma samples from drug-naïve patients with schizophrenia (SZ) and bipolar disorder (BD) in comparison to healthy controls. The sample cohort consisted of 30 BD and 30 SZ patients and 30 control individuals. An untargeted lipidomics strategy using liquid chromatography coupled with high-resolution mass spectrometry was employed to obtain the lipid profiles. Data were preprocessed, then univariate (t-test) and multivariate (principal component analysis and orthogonal partial least squares discriminant analysis) statistical tools were applied to select differential lipids, which were putatively identified. Afterward, multivariate receiver operating characteristic tests were performed, and metabolic pathway networks were constructed, considering the differential lipids. Our results demonstrate alterations in distinct lipid pathways, especially in glycerophospholipids, sphingolipids and glycerolipids, between SZ and BD patients. The results obtained in this study may serve as a basis for differential diagnosis, which is crucial for effective treatment and improving the quality of life of patients with psychotic disorders.

Investigating lactation curve characteristics of dairy cows

The main goal of this study was to analysis of the main characteristics (latent variables) of lactation curve in dairy cows using multivariate Principal Component Analysis. This work used primary database from the milk production of Holstein cows (n = 238 heads) in the PJSC “Pedigree farm ‘Stepnoy’ Kamianka-Dniprovska Raion of Zaporizhzhia Oblast over a 4-yr period (2014-2017). Recording is done with an interval of 30 days for 10 test-days (TD1-TD10), i.e., TD1 is milk production recorded on milking day 30th, TD2 is day 60th, TD3 is day 90th, etc., and 305-day milk yield records (Y305) were used also. High significant correlations were found between daily milk yields for certain test-days. The Principal Component Analysis performed on the variance-correlation matrix of TD1-TD10 records are able to explain about 90.33 % of the total variance. The first principal component (PC1) explained 66.32 % of the total variance and was highly-positively correlated with TD2-TD10 records. Thus, PC1 were defined as “total milk production”. The second principal component (PC2) explained 19.06 % of the total variance and was highly-positively correlated with TD1-TD2 records and highly-negatively correlated with TD9-TD10 records. Thus, PC2 were defined as “lactation curve persistency”. Finally, the third principal component (PC3) explained 4.95 % of the total variance and was highly-positively correlated with TD1 and TD10 records and highly-negatively correlated with TD4-TD5 records. Thus, PC3 were defined as “lactation curve type”. The use of a multivariate method (namely, the PCA) for the analysis of lactation curve characteristics based on monthly test-day records gave very close results of the analysis of milk productivity in different groups of domestic animals (cattle, goats and sheep). In all cases, the first principal component (PC1) described the absolute level of milk productivity during lactation, and the second principal component (PC2) described the persistency of the lactation curve. Significant influence on the PC1-PC3 factor scores was revealed to the greatest extent for such non-genetic factors as age of cow (in lactations), year and month of calving. Of the genetic factors, the greatest influence on the shape of the lactation curve was not so much the differences between the bull lines (Bell, Valiant, Elevation, Starbuck and Chief), but differences between individual bulls within some lines.

Influence of pre‐gelatinization in conjunction with guar gum addition on texture functionality, bioactive profile, in vitro nutrient digestibility, morphology and secondary structure of protein of quality protein maize pasta

SummaryThe current investigation aimed to develop quality protein maize (QPM) specialty pasta (partial: 50% QPM and full replacement of semolina: 100% QPM) and study the influence of pre‐gelatinization in conjunction with guar gum addition (1.5% or 3%) on bio‐techno‐functional properties of pasta. Scanning electron microscopy depicted the encapsulation of swollen starch within a protective sheet developed as a result of gum addition and starch gelatinisation. The Fourier transform infrared spectra denoted a shift from crystalline towards amorphous state in starch as a consequence of partial gelatinisation. The secondary structure of protein signified a drop in the alpha‐helix structure and thereby enhanced the in vitro protein digestibility of the pregelatinised samples. Multivariate principal component analysis was utilised to validate the differences between the parameters. The overall study inferred that the QPM owned an excellent potentiality for the development of nutrient‐dense pasta by employing the functionality of gums and pre‐gelatinisation treatment.

The Effect of Drying Methods on Chemical Profiling of Zingiberaceae Herbs Production

Background: Drying method is one of the important steps in post-harvesting in herbal production in order to prolong the shelf-life of herbal medicine and to ensure the good quality. Objective: This research aimed to profile and quantify the metabolites changing using metabolomic based on 1H-NMR Spectroscopy on Curcuma and Zingiber genus due to the drying process. Material and Methods: Five species of the Curcuma and Zingiber genus were Curcuma longa L., Curcuma aeruginosa Roxb., Curcuma xanthorrhiza Roxb., Zingiber officinale Roscoe. and Zingiber amaricans BI. The drying method applied were freeze drying and oven drying method at -1080C and 500C, respectively. Samples were extracted using buffer phosphate and deuterated methanol (3:7). The analysis was performed using 1H-NMR spectroscopy 400 MHz with TSP as an internal standard. The 1H-NMR spectra were analysed with multivariate (Principal Component Analysis). Results: The relative concentrations of sucrose and fructose at 5 samples in freeze drying method showed significant higher content than those in oven drying. On the other hands, glucose was mostly significant higher concentration in oven drying at 5 samples. Fructose and sucrose were significantly higher in freeze drying method than those in oven drying in Curcuma and Zingiber genera. Relative glucose content was higher in oven drying at Curcuma genus Conclusion: Therefore, oven drying method which applied heating at 500C is an appropriate method for herbal medicine production, especially in Curcuma and Zingiber genus, for maintaining the major secondary metabolites.

Does the initial C/N ratio interfere with the performance of sewage sludge composting and cotton waste?

ABSTRACT The effects of the initial C/N ratio on the composting of sewage sludge and cotton residues are not reported in the literature. Understanding the main composting control parameters is essential for the good stabilization of these wastes. Therefore, this study sought to evaluate different initial C/N ratios for the composting of sewage sludge and cotton waste, aiming to find the ranges with the best performance for the process and quality of the final organic compost. In this sense, five mixtures of sewage sludge (S) and cotton residues (C) were prepared and composted with three replications for each treatment in a completely randomized design. Physicochemical parameters were evaluated during composting and in the final organic compounds. A Multivariate Principal Component Analysis (PCA) was applied to evaluate the agronomic quality of organic compounds. The thermal behaviour of the mixtures presented differences. The treatments 90C10S, 80C20S and 67C33S showed the highest EXI² index (3566.64, 3448.39 and 2738.89), longer duration of thermophilic phase (12 and 13 days) and better potential for maximum degradation (A) of organic matter (67.5, 61.2 and 65.6%C). The final compounds of 90C10S and 80C20S showed higher pH values (7.9 and 7.5) and higher CEC (123.6 and 114.0 meq/100 g OM). PCA showed similarity in the agronomic quality of organic compounds for 90C10S, 80C20S and 67C33S. The treatment 28C72S (initial C/N ratio of 16.6) presented final pH of 5.3 and did not meet the minimum limit required by Brazilian regulations. Initial C/N relations between 24.9 and 35.2 showed better stabilization of waste and final organic compound with better agronomic quality.

Virulence Phenotyping and Molecular Genotyping Reveal High Diversity Within and Strong Gene Flow Between the Puccinia striiformis f. sp. tritici Populations Collected from Barberry and Wheat in Shaanxi Province of China.

Emergence of new Puccinia striiformis f. sp. tritici races that overcome resistance of wheat cultivars is a challenging issue for wheat production. Although sexual reproduction of the fungus on barberry plants under field conditions in the spring in China has been reported, the diversity of the pathogen on barberry plants and the relationship to the population in wheat fields have not been determined. In the present study, two P. striiformis f. sp. tritici populations collected in western Shaanxi Province in May 2016, one from barberry plants (103 isolates) and the other from nearby wheat crops (107 isolates), were phenotyped for virulence and genotyped with simple sequence repeat (SSR) markers. The phenotypic and genotypic data of the two populations were compared to determine their relationships. A total of 120 races, including 29 previously known races (seven were shared by the two populations) and 91 new races (35 from barberry and 56 from wheat), were identified. Similarly, a total of 132 multilocus genotypes, including 51 only from barberry, 77 only from wheat, and four from both, were detected using the SSR markers. Analyses of molecular variance identified high (93%) genetic variance within populations and low but still significant variance (7%) between the populations. Nonparametric multivariate discriminant analysis of principal components and STRUCTURE analysis showed that the two populations had a close relationship with little genetic differentiation (FST = 0.038) and strong gene flow (Nm = 6.34, P = 0.001) between them. Although the analysis of linkage disequilibrium indicated clonal populations, the isolation of P. striiformis f. sp. tritici from barberry plants and the high genetic diversities in the barberry and wheat populations suggest that barberry plants provide aeciospores to infect wheat crops in the area. The information is useful for understanding stripe rust epidemiology and management of the disease.

Comparative Morphometric Analysis of the Azov Anchovy (&lt;i&gt;Engraulis encrasicolus maeoticus&lt;/i&gt; Pusanov, 1926) and the Black Sea Anchovy (&lt;i&gt;E. encrasicolus ponticus&lt;/i&gt; Alexandrov, 1927) Based on the Body Shape

A comparative analysis of body shape was performed on 841 specimens of anchovy collected from 21 catches from the Sea of Azov, the Kerch Strait, and the Black Sea off the Crimea and the northeastern coast of the Caucasus in 2006–2007 and 2016–2017. Twenty-three measurements between 12 homologous landmarks of the body of each specimen according to the “Truss Network System” served as characters for analysis. Fifteen characters showed significant differences between the Azov anchovy Engraulis encrasicolus maeoticus Pusa-nov, 1926 and the Black Sea anchovy E. encrasicolus ponticus Alexandrov, 1927. Specimens of the Azov subspecies had larger relative values for all characters of the head region, the height of the trunk region, the re-lative length of the bases of the dorsal and anal fins, and the height of the base of the caudal fin. Specimens of the Black Sea subspecies had a greater postdorsal length and a larger distance from the end of the dorsal fin base to the end of the anal fin base. A multivariate principal component analysis revealed the highest variabi-lity of characters of body height, which depends on the fatness of the fish and demonstrates seasonal dyna-mics. The second group combines characters that do not have a seasonal component (dimensions of the head region, lengths of the bases of the dorsal and anal fins, and postdorsal distance) and can be used for distinguishing the shape of the Azov and Black Sea anchovies. The success rate of classification of Azov and Black Sea anchovies according to the body shape measurement characters using the discriminant analysis was 83.4%.

Identification of the Backsheet Type of Silicon Photovoltaic Modules from Encapsulant Fluorescence Images

Feasibility of the identification of backsheet (BS) composition of field-aged Si photovoltaic (PV) modules based on the analysis of characteristic patterns of UV-excited fluorescence (UVF) of ethylene vinyl acetate copolymer encapsulant is shown. The approach includes BS identification by vibrational spectroscopies and the formation of a database of BS-related characteristic UVF patterns. A multivariate principal component analysis of the UVF images of unknown samples combined with the UVF pattern database allows the BS type to be identified only from UVF images. The geometric place of particular samples in the principal component plots is indicative of the general degradation status of PV modules. The proposed method can be applied for high-throughput noncontact characterization of solar PV plants.

Adaptive Sampling for Monitoring Multi-Profile Data with Within-and-between Profile Correlation

Multi-profile data can provide within-and-between profile information for efficiently modeling and monitoring system status. In practice, however, acquisition of such data requires large number of sensors, which raises various concerns and difficulties, for example, cost, energy, and data transmission bandwidth, in accessing the full data from each sensor. In this article, we propose an adaptive sampling strategy for multi-profile monitoring by using limited portion of data. The proposed sampling and monitoring scheme incorporates the within-and-between profile correlation and features the balance between random search and greedy search in identifying the most informative profiles. More specifically, the multivariate functional principal component analysis (MFPCA) is used to capture the within-and-between profile correlation, and the MFPC scores are augmented for unobservable profiles to feed into a multivariate CUSUM chart. Two properties of the proposed method for allocating sampling resources among sensors are investigated. Numerical and case studies are conducted under various scenarios to demonstrate the effectiveness of the method.

Chemical diversity of wild fennel essential oils (Foeniculum vulgare Mill.): A source of antimicrobial and antioxidant activities

This study aims to provide useful information for the evaluation of wild fennel in terms of their nutritional potential and medicinal values. It is therefore important to bio-prospect the variability of molecules production and the biological properties according to plant georaphical origin. Essential oils (EOs) obtained from leaves of 12 Foeniculum vulgare Mill. populations, growing wild in Tunisia, were analyzed by GC-MS. In addition, their antimicrobial activity was evaluated against eight pathogenic bacteria and fungi. The antioxidant potential of tested oils was evaluated by four different tests: Total antioxidant activity (TAA), DPPH, ABTS and reducing power assay (RPA). In addition, relationships between studied EOs by using Hiearchical Clustering Analysis (HCA) based on Euclidean distance matrix and the multivariate Principal Component Analysis (PCA) were provided. All EOs were found to be rich in monoterpenes hydrocarbons (41.56-63.13%) and phenylpropanoids (35.87-55.29%). Moreover, Limonene (8.40-50.34%) and Methyl Chavicol (35.87%-54.28%) were the main compounds. EOs from Zaghouan displayed the best antioxidant activity (8.5±0.05 mg GAE/g DW). While, EOs from Oued Zarga exhibited the highest DPPH radical scavenging activity (IC50 = 7.7±0.43 mg/mL), and those from Ain Ghlel and Badar regions showed the highest ABTS radical scavenging activity (IC50 = 86.86±0.23 µg/mL and 87.33±0.17 µg/mL, respectively). The most important reducing power assay was found in Ain Ghlel and Charchara EOs (EC50 of 70.46±0.17 and 71.31±0.61µg/mL respectively). Results displayed the sensitivity of the tested strains to fennel EOs especially against Gram-positive strain, and EOs from Zaghouan population exhibited the highest effect against Micrococcus luteus and Staphylococcus aureus. Overall, these results can extend our knowledge of the chemical diversity of wild fennel among geographical origin and pedoclimatic conditions indicating that Tunisian natural populations of F. vulgare had different chemotypes of EOs. In this way, the current study will provide new data and encourage the use of this plant as food. Wild fennel leaf EOs were rich in phenylpropanoids and endowed with significant antibacterial and antioxidant potential, which opens a new prospect for industrial and agronomical exploitation of this species.

Morphometric indices of native sheep breeds of the Himalayan region of India using multivariate principal component analysis.

This study was performed to analyze the morphometric traits and indices in 3000 animals of five registered sheep breeds in the Himalayan region under a multivariate approach. Data were recorded under field conditions with equal coverage of the five breeds, viz., Karnah, Gurez, Poonchi, Bakerwal and Changthangi on body length (BL), height at withers (HW), chest girth (CG), ear length (EL), and tail length (TL). Furthermore, four derived traits (indices) were studied, which included an index of body frame (IBF), an index of thorax development (ITD), a Baron-Crevat index (BCI), and an index of body weight (IBW). Multivariate principal component analysis (PCA) was undertaken on nine morphometric traits. Kaiser's criterion was used to reduce the number of principal components for further analysis and interpretation. The adequacy of sampling was evaluated using Kaiser-Meyer-Olkin (KMO) test and Bartlett's test of sphericity. The mean BL ranged from 52.15 (Changthangi) to 71.13 (Gurez). The estimates of HW, CG, EL and TL were highest in Gurez (63.49), Bakerwal (84.82), Bakerwal (7.26), and Karnah (8.18) breeds, respectively. Among the derived traits, the highest IBF was observed in the Gurez breed with an estimate of 112.22. Upon multivariate PCA on the dataset, the first four principal components were able to explain 92.117% of the total variance. The KMO test, Bartlett's test of sphericity and estimated communalities showed the appropriateness of PCA on the evaluated traits. Four eigenvalues were greater than one and were extracted for further analysis. Morphometric traits were highly correlated, except for EL and TL that showed lower correlation estimates with other traits. The Changthangi population showed the lowest estimates of BL, HW, CG and rectangular body frame. The present study ascertained important morphometric traits/indices that can help in developing selection criteria and formulating sustainable breeding and conservation plans vis-à-vis the unique sheep breeds of the temperate Himalayas.

High temperature events shape the broadscale distribution of juvenile Atlantic salmon (Salmo salar)

Abstract Summer water temperatures within many temperate rivers regularly surpass the incipient lethal temperature for juvenile Atlantic salmon (c. 27°C), causing widescale abandonment of territory in favour of areas of cooler water (thermal refuges). This study aims to highlight the influence of thermal refuges on river‐scale abundance patterns. That is, do salmon parr adjust their distribution over time according to proximity to thermal refuges? Twelve reaches (seven reference: five refuge) were chosen along a 17‐km section of the Little Southwest Miramichi River in Canada. Reaches were sampled throughout the 2011 and 2012 summer periods; high temperature events were recorded during summer 2012 but not summer 2011. Multivariate principal component analyses indicated no discernible difference in habitat characteristics between the reach‐types under normal thermal conditions. However, reaches containing a thermal refuge had a significant increase in relative abundance of parr immediately after a series of high temperature events (water temperature &gt;26°C) in 2012 (p = 0.034). This increase in relative abundance in refuge reaches was not present during the summer of 2011 when no temperature events occurred (p = 0.088), prior to the event of 2012 (p = 0.999), or at the late autumn survey following the 2012 event (p = 0.999). Difference in temperature between refuge and mainstem reaches significantly influenced the suitability of a tributary as a thermal refuge habitat (R2 = 0.84), with preference shown for cooler refuges. River‐wide thermal heterogeneity therefore plays a critical role in survival of juvenile salmon throughout summer months and is likely to become necessary under future climate change scenarios.