Hierarchy Cluster Analysis Research Articles

Comparative Study on Handheld, Modular, and Laboratory Raman Instruments for the Analysis of Colon Tissues and Colorectal Polyps

Portable Raman spectrometers may offer advantages for clinical medical diagnostics over laboratory instruments by allowing for quick measurements in the field and provision of data suitable for screening analyses. This work evaluates the potential of using available handheld, modular, and laboratory Raman spectrometers for screening normal colon tissues and benign and malignant colon polyps. The Raman spectra of tissue samples and reference biological macromolecules were measured with these instruments and analyzed using curve fitting and multivariate statistics. The spectra of calf thymus DNA measured with portable devices showed suitable signal-to-noise levels and half-widths of the prominent bands. Band positions, resolution, and relative intensities in the Raman spectra of colon tissues and reference compounds varied for the instruments, and the laboratory device demonstrated the best spectral feature. The principal component analysis (PCA) of the spectra obtained with all Raman devices showed well discrimination of normal colon tissue, adenomatous polyp, and adenocarcinoma. Dendrograms of similarity obtained using hierarchy cluster analysis (HCA) for the Raman spectra of all three devices also showed good separation of these samples. The soft independent modeling of class analogy (SIMCA) and support vector machine (SVM) models efficiently classified normal colon tissues and benign/malignant colorectal polyps based on the Raman data from all three devices. Despite its less pronounced spectral characteristics, the handheld Raman spectrometer can be used in early diagnosis of colorectal carcinoma, comparable to the modular and laboratory instruments.

Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India

The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water quality of the study area, an esteemed Ramsar site in North Eastern India, using a combined application of multivariable statistical and geospatial techniques. In this study, 24 water samples were designed based on their use and collected along the periphery and the inner areas of the lake employing the Latin Square Matrix. This research also examines the spatial variations of water quality involving quartile-based water quality categorization of parameters, with Pearson’s Correlation analysis, Principal Component Analysis (PCA), and Hierarchy Cluster Analysis (HCA) applied for dimension reduction. The analysis involved quartile-based water quality categorization of parameters, with PCA and HCA applied for dimension reduction. Meanwhile, the Inverse distance weighted (IDW) approach was used to interpolate the spatial distribution of the quartile score using the ArcGIS platform. The Bureau of Indian Standards (BIS) was followed for water quality assessment. The results revealed significant spatial variation, providing valuable insights for future water management strategies. PCA indicates 57.26% of the variance in the dataset, whereas samples were classified into three subgroups and two groups in a dendrogram representing the result of the HCA. This study demonstrates the utility of PCA, HCA, and IDW interpolation in water quality assessment, highlighting the effect of human-induced activities in the lake’s vicinity.

Fractional order ATR-FTIR differential spectroscopy for detection of weak bands and assessing the radiation modifications in gamma sterilized UHMWPE.

This study presents a new method for identifying radiation modifications in UHMWPE polymer samples. The method involves using a mathematical technique called fractional order differential transformation on IR spectra obtained through ATR-FTIR spectroscopy. This new method was compared to existing techniques such as FTIR, XRD, and DSC, and it was found to be more sensitive and accurate in detecting radiation-induced changes in the polymer. The study focused on identifying changes in weak IR bands in the UHMWPE samples caused by gamma sterilization while simulating IR spectra using different orders of fractional derivatives and compared them to experimental spectra. It was found that applying a lower order of differentiation was more suitable for identifying radiation-induced changes in the UHMWPE samples. Using this method, they were able to identify specific changes in the gamma irradiated structure, such as the splitting of a single absorption peak into a doublet, which was only present in the 50 kGy irradiated sample. The study also used correlation index analysis, principal component analysis, and hierarchy cluster analysis to analyze the simulated and experimental spectra. These techniques allowed to confirm the effectiveness of the fractional order differential transformation method and to identify the specific regions of the IR spectra that were affected by radiation-induced changes in the UHMWPE samples. Overall, this study presents a new method for identifying radiation-induced changes in UHMWPE polymer samples that is more sensitive and accurate than existing techniques. By identifying these changes, researchers can better understand the effects of gamma sterilization on medical equipment and potentially develop new methods for sterilization that do not damage the equipment.

Hybrid analytic network process (ANP)-Entropy model, time series analysis for predicting nitrate and fluoride in groundwater and cumulative health risk assessment

The study focused on groundwater evaluation of the trans-Himalayan region using a novel concept of Hybrid Analytic Network Process (ANP) - entropy and Holt's exponential smoothing model for short-term prediction of groundwater quality. Hierarchy cluster analysis of groundwater was performed to identify the sources and spatial distribution of water quality. The PCA coupled with multivariate analysis dictated a high correlation of various ions i.e., NO3−, K+, F−, Cl−, SO42−, PO42−, and Na+ with the lithology of the area and helped in identification of various polluting sources i.e., excessive use of fertilizers, wastewater discharges and agrochemicals. The hybrid ANP-entropy technique offered a holistic approach to provide a more accurate and complete understanding of groundwater quality and revealed that groundwater quality in 21.43% (in winter) and 42.86% (in summer) of the locations fall into the poor category. The non-carcinogenic health risk analysis revealed that fluoride poses a major potential health risk followed by nitrate, primarily via the oral pathway while it was negligible through the dermal pathway. The total hazard index was observed highest in children (1.99) followed by infants (1.64). 95th percentile of the probable risk obtained through Monte Carlo simulation also dictated highest risk to infants than child. The predicted values of the Holt's exponential smoothing model for the year 2021 and 2022 was varied within ±5 % of the observed values. The proposed model effectively treats uncertainties in groundwater quality assessment and considers average and incremental increase both hence, can be used for short-term prediction and trend analysis of groundwater quality.

Temperature Induction Response and Multivariate Analysis Approaches to Screen Blackgram (Vigna mungo L.) Genotypes for Thermotolerance

Background: In the current climate change scenario, high temperature stress is one of the major constraints limiting the yield of blackgram severely. The increasing global temperature is targeting the yield of blackgram by causing severe reproductive failures. In order to combat this problem, it is important and inevitable to screen blackgram genotypes that can withstand to high temperature and produce better yield even under adverse climatic conditions. Keeping this in view, the present investigation was carried out. Methods: Hundred blackgram genotypes were subjected to Temperature induction response technique, in which lethal temperature was standardized as 54°C for 3 hours and optimum induction temperature as 36-46°C. The selected genotypes from temperature induction response technique were further evaluated for biochemical traits using hierarchial clustering and principal component analysis. Result: The cellular level tolerance was assessed in blackgram genotypes using standardized lethal and optimum induction temperature. Based on the percent reduction in the seedling growth of induced over control and survival percentage, 27 blackgram genotypes were categorized as highly tolerant, 54 genotypes as moderately tolerant and 19 genotypes as susceptible. Biochemical characters such as antioxidant defence activity, lipid peroxidation and free radicals were analyzed in TIR induced 27 thermotolerant and 3 susceptible genotypes. The results indicated that all the traits such as total seedling length and antioxidant defence enzymes except malondialdehyde and free radicals showed a prominent increase under heat stress. Based on hierarchial clustering, 30 genotypes were clustered as 5 groups: tolerant (cluster-3,4), moderately tolerant (cluster-1,2) and susceptible (cluster-5). Principal component analysis showed that first five components showed 75.8% of total variation in control, whereas 63.3% of the total variance was covered by the first two PCs in heat induced conditions. The information generated from the study would help the breeders in developing heat tolerant varieties that perform better even under extreme high temperatures.

Linking morphological features to anammox communities in a partial nitritation and anammox (PN/A) biofilm reactor

Partial nitritation/anammox (PN/A) has been recognized as a cost-efficient process for wastewater nitrogen removal. The addition of carriers could help achieve biomass retention and enhance the treatment efficiency by forming the dense biofilm. However, accurately determining the abundance of anammox bacteria (AnAOB) to evaluate the biofilm development still remains challenging in practice without access to specialized facilities and experimental skills. In this study, we explored the feasibility of utilizing the morphological features of anammox biofilm as an indication of the biofilm development progression, and its correlation with microbial communities was also revealed. The time-series biofilms from an integrated fixed-film activated sludge (IFAS) system with stable PN/A performance were sampled representing the different biofilm development stages. The biofilm morphological features including color and texture were respectively quantified by red (R) coordinate and Local binary pattern (LBP) descriptor via image processing. Hierarchy clustering analysis proved that the extracted morphological descriptors could well distinguish the different stages (colonization, succession, and maturation) of biofilm development. The microbial community dynamics of time-series anammox biofilms were investigated using the amplicon sequence variant (ASV) analysis. Candidatus Brocadia, as the typical AnAOB, dominated in the whole communities of 16.3%–20.0%, moreover, the biofilm development was found to be driven by distinct Brocadia species. Linear regression evidenced that the Brocadia abundance could be directly correlated to the value of R and LBP, and the total variation of microbial communities could be significantly explained by the morphological features via redundancy analysis. This study demonstrates a new way to monitor the biofilm development by extracting the visible features of anammox aggregates, which can help facilitate the automated control of anammox-based bioprocess.

Expectation based types of voluntary sports clubs in regional sports federations and the perspectives for professionalisation

Sports clubs in different levels of professionalisation show different organisational problems (Lang et al., 2022). At the same time, one part of the key responsibilities of sports federations as umbrella organisations is the needs-based support of voluntary sports clubs (VSC) as their members. However, different professionalisation levels and heterogeneous organisational problems of member clubs are increasingly challenging the design of appropriate service offerings by sports federations. Thus, services provided by sports federations should be adapted in relation to the expectations and needs of its member clubs. In this way sports clubs also effects with their expectations developments within sports federations to optimise their supporting services in a more targeted manner. This study addresses these challenges by analysing VSCs’ expectations and identify distinct expectation types. The empirical study was carried out in a regional sports federation in tennis, the Bavarian Tennis Federation (BTV). This leads to the research questions: What expectations do VSCs as members generally address to the BTV? To what extent can VSCs be classified in terms of their expectations regarding BTV services? To address these expectations, the performance measurement literature provides a fruitful theoretical frame. In order to base appropriate performance parameters, stakeholders’ expectations need to be identified ex ante (Bayle & Madella, 2002). In the literature it is consensus that measuring the performance of sports federations requires a multidimensional approach (e.g., Winand et al., 2010). To analyse expectations of VSCs an online survey was conducted. Access to the survey was given to BTV member club representatives in a leadership position. For operationalisation, an exploratory factor analysis was performed, which shows the best solution with six reliable factors. The identified factors were used for Ward’s hierarchy cluster analysis with squared Euclidean distances. The analysis showed that an optimal cluster solution can be determined with four clusters. Based on the z-standardised factor values the identified clusters were labelled as follows: (1) “People developer” (n = 57, 32%); (2) “Mass sports clubs” (n = 39, 22%); (3) “Self-governmenters” (n = 40, 23%) and (4) “High expecting communicators” (n = 41, 23%). For validation, the extracted clusters are also reflected by other characteristics of the organisations. The findings reveal that there are heterogeneous expectations of VSCs that need to be addressed more individually by sport federations. The extracted types provide a first empirical step to identify different expectation schemes. These schemes enable managers of sports federations to professionalise their service offer portfolio and at the same time, to design targeted services to contribute to the development and professionalisation of sports clubs.

Discrimination of Chinese green tea according to tea polyphenols using fluorescence sensor array based on Tb (III) and Eu (III) doped Zr (IV) metal–organic frameworks

A facile and rapid fluorescence sensor array based on Tb (III) and Eu (III) doped Zr (IV) metal–organic frameworks was proposed for Chinese green tea discrimination. According to large porosity of Tb@UiO-66-(COOH)2 and Eu@UiO-66-(COOH)2, phenolic hydroxyl groups of tea polyphenols could coordinate with free carboxylic acid groups and was captured into the pores, which led to the disturbance of electronic structure of ligand and inhibited the energy transfer efficiency from ligand to Tb (III) and Eu (III) center, causing the fluorescence quenching effect. Based on Hierarchy Cluster Analysis and Linear Discrimination Analysis, the fluorescence sensor array was employed for successful tea polyphenols classification through the analysis of different fluorescence quenching effect to tea polyphenols. Green tea samples within different categories and grades were also successfully discriminated using this assay according to tea polyphenols, providing a new method for Chinese green tea identification.

Is ecological vulnerability assessment based on the VSD model and AHP-Entropy method useful for loessial forest landscape protection and adaptative management? A case study of Ziwuling Mountain Region, China

• Ecological vulnerability was assessed and mapped via the AHP-entropy method and VSD model. • Spatiotemporal changes existed in the exposure, sensitivity, and adaptive capacity. • Apparent spatial cluster patterns of ecological vulnerability existed. • An integrated method was developed for adaptive management to dryland sustainability. Ecological vulnerability assessment is an effective tool to aid decision-makers in understanding the impact of natural and anthropogenic variables on ecosystems. Yet, we know little about incorporating ecological vulnerability into accurate decision-making for climate change adaptation and human activities governance. This study proposes a comprehensive framework to link the Vulnerability Scoping Diagram (VSD) model, Analytic Hierarchy Process-Entropy method, hot spot and cluster analysis into ecological vulnerability assessment and management in the Ziwuling Mountain Region (ZMR), a typical loessial forest landscape in arid China. There were significant spatial and temporal changes in the exposure, sensitivity, and adaptive capacity index in the ZMR from 1990 to 2017. The exposure and adaptive capacity index increased from 1990 to 2017. The subareas with a high exposure value were distributed in the north and south ZMR, and the subareas with a high adaptive capacity value were distributed in the east ZMR. The ecological vulnerability declined during the study period, with the smaller value subareas allocated in the middle and south ZMR and higher value in the north and southwest. Significant spatial clustering patterns on the hot and cold spots of ecological vulnerability existed in the ZMR. The clustering subareas of hot spots on ecological vulnerability were mainly characterized by dry steppe, less precipitation, and less vegetation coverage. The subareas of cold spots of ecological vulnerability were dominated by forestry and forestry-agricultural landscapes. Some suggestions and countermeasures were put forward for adaptive management and sustainability enhancement. Our results provide integrative methods linking the VSD model, AHP-entropy method, hot spot and cluster analysis to ecological vulnerability reduction and adaptive management for dryland sustainability, especially for the forest social-ecological systems in the Chinese Loess Plateau.

The Potential of Phyllanthus Niruri Plant Secondary Metabolites in Providing Antiviral Protection Against Sars-Cov-2: A Literature Review

Covid-19 is a disease that causes respiratory tract infections in humans. The Covid-19 pandemic has spread throughout the world. Meniran (Phyllanthus niruri) is a plant that has been empirically shown to be an antiviral. This study aimed to determine the potential of Phyllanthus niruri and its compounds as an antiviral for SARS-CoV-2 through a literature review. The data were analyzed descriptively using the NVIVO 12 Plus software. The parameters used were the hierarchy chart, cluster analysis, and world cloud. The results showed that two secondary metabolites of Phyllanthus niruri have the potential to provide antiviral protection against SARS-CoV-2, namely quercetin and rutin. Further research is needed to examine the validity of these findings through triangulation of the scientific reports and research in the laboratory.
 Keywords: antivirus, Phyllanthus niruri, SARS-CoV-2

Assessment of groundwater quality with analytic hierarchy process, Boolean logic and clustering analysis using GIS platform in the Kebili’s complex terminal groundwater, SW Tunisia

Assessment of groundwater quality with analytic hierarchy process, Boolean logic and clustering analysis using GIS platform in the Kebili’s complex terminal groundwater, SW Tunisia

Physical and Microbiological Characteristics and Antioxidant Activity of Honey Bee Pollen

This study aimed to evaluate the physical, chemical, and microbiological characteristics of bee-collected pollen, with special consideration to the antimicrobial resistance of the isolated microorganisms to the selected antibiotics. A hierarchy cluster analysis was conducted, in which bee pollen samples were divided into four groups by their colour. The highest antioxidant activity among monofloral bee pollen was found for the autumn raspberry pollen and the lowest for the clover pollen, using the ABTS test. The total phenol content in rapeseed bee pollen was the second-highest among all samples analysed, which might indicate a correlation between high phenol content and strong antioxidant activity. Our study indicated a moderate correlation between bee pollen moisture content and Enterobacteriaceae counts, as well as a correlation between moisture content and total bacterial count. Among all bacteria (n = 34) isolated from pollen, the highest prevalence was found in Bacillus spp. and coagulase-negative staphylococci. The resistance of isolated microorganisms was identified in 18 cases. The high number of antimicrobial resistance cases, i.e., when isolates were resistant to ampicillin (seven cases) and penicillin (eight cases), indicates an environmental effect because, for this study, no antibiotics were used in the apiaries harvesting pollen. This indicates the need for improved safety procedures in bee pollen production for human consumption.

A Multi-Attribute Decision-Making Model for the Selection of Polymer-Based Biomaterial for Orthopedic Industrial Applications.

The potential of quantifying the variations in IR active bands was explored while using the chemometric analysis of FTIR spectra for selecting orthopedic biomaterial of industrial scale i.e., ultra-high molecular weight PE (UHMWPE). The nano composites UHMWPE with multi-walled carbon nano-tubes (MWCNTs) and Mg-silicate were prepared and irradiated with 25 kGy and 50 kGy of gamma dose. Principal component analysis (PCA) revealed that first three principal components (PCs) are responsible for explaining the >99% of variance in FTIR data of UHMWPE on addition of fillers and/or irradiation. The factor loadings plots revealed that PC-1 was responsible for explaining the variance in polyethylene characteristics bands and the IR active region induced by fillers i.e., 440 cm−1, 456 cm−1, from 900–1200 cm−1, 1210 cm−1, 1596 cm−1, PC-2 was responsible for explaining the variance in spectra due to radiation-induced oxidation and cross linking, while the PC-3 is responsible for explaining the variance induced because of IR active bands of MWCNTs. Hierarchy cluster analysis (HCA) was employed to classify the samples into four clusters with respect to similarity in their IR active bands which is further confirmed by PCA. According to multi attribute analysis with PCA and HCA, 65 kGy irradiated sample is optimum choice from the existing alternatives in the group of irradiated pristine UHMWPE, UHMWPE/Mg-silicate irradiated with 25 kGy of gamma dose was the optimum choice for UHWMPE/Mg-silicate nano composites, and UHMWPE/γMWCNTs composites containing 1.0% dof γ MWCNTs for UHMWPE/MWCNTs nanocomposites, respectively. The results show the effectiveness of quantifying the variance for decision as far as optimization of biomaterials in orthopedic industrial applications is concerned.

Expression profiles of long noncoding RNAs in human corneal epithelial cells exposed to fine particulate matter

PurposeThe aim of this study was to investigate the expression profiles of long noncoding RNAs (lncRNAs) in human corneal epithelial cells (HCECs) exposed to fine particulate matter (PM2.5) and to identify potential biological pathways involved in PM2.5-induced toxicity in HCECs. MethodsUsing RNA sequencing (RNA-seq) and hierarchy clustering analysis, lncRNA expression profiles in PM2.5-treated and untreated HCECs were examined. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to predict the role of altered lncRNAs in biological processes and pathways. A quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) assay was conducted to verify the RNA-seq results in HCECs and human corneal epithelial cell sheets. ResultsIn total, 65 lncRNAs were altered in the PM2.5-treated HCECs, including 41 upregulated and 24 downregulated lncRNAs. The results of the qRT-PCR assay were consistent with those of the RNA-seq analysis. The expression of two significantly upregulated lncRNAs was confirmed in human corneal epithelial cell sheets. The GO analysis demonstrated that altered lncRNAs in the PM2.5-treated HCECs were significantly enriched in three domains: cellular component, molecular function, and biological process. The KEGG pathway analysis revealed enriched pathways of lncRNA co-expressed mRNAs, including cancer, RNA transport, and Rap1 signaling. ConclusionsOur results suggest that lncRNAs are involved in the pathogenesis of PM2.5-induced ocular diseases, exerting their effects through biological processes and pathogenic pathways. Among the altered lncRNAs, RP3-406P24.3 and RP11-285E9.5 may play significant roles in PM2.5-induced ocular surface injury.

Evaluation of Tourism Developing Level of Yangtze Delta Cities Basing on Analytic Hierarchy Process Analysis and Clustering Analysis

Tourism data of 26 cities in the Yangtze River Delta of 2017 are summarized and counted. Method of Analytic Hierarchy Process is used to construct a three-level indicator system, including three secondary indicators such as scale of the tourism industry, number of tourists and tourism income and a number of three-level indicators. And then weight of each indicator is determined, the original data are standardized, and tourism development level score of each city is calculated. Finally, 26 cities are divided into 5 types by cluster analysis and characteristics of each type of cities are analyzed and evaluated.

Risk Assessment of Snow Disaster in Guoluo Prefecture of Southern Qinghai Province Based on GIS

We evaluated snow disaster risk in 44 towns of Guoluo Prefecture by combining the methods of Analytic Hierarchy Process (AHP) and cluster analysis. Data were gathered from meteorological stations in Qinghai and Sichuan Provinces with GIS and RS tools. We considered snow depth, the duration of snow days, the area ratio of snow as three indicators for such evaluation, we can say Guoluo Prefecture is a higher hazard area of snow disaster. From the spatial distribution, we can see that the mild grade areas are Huashixia town in Maduo county, Zhalinghu village and Dongqinggou village, Lajia town in Maqin county; the moderate and minor severe grade areas are distributed basically in every county. And the minor severe grade areas cover almost every town in Dari county and Gande county However, the severe grade areas only distribute in Sanrima village, Tehetu village of Dari County and Dangluo village of Maqin county.

Systematical exploration of the common solvent toxicity at whole organism level by behavioral phenomics in adult zebrafish

Common solvents are frequently used as carriers to dissolve chemicals with a hydrophobic property that is extensively applied in the industrial and biomedical fields. In this study, we aimed to systematically study the sub-chronic effect of ten common solvents at low concentration exposure in adult zebrafish and perform neurobehavioral assessments for mechanistic exploration. After exposed to ten common solvents, including methanol, ethanol (EtOH), dimethyl sulfoxide (DMSO), isopropanol, acetone, polyethylene glycol-400 (PEG-400), glycerol, butanol, pentane, and tetrahydrofuran for continuous 10 day at 0.1% concentration level, adult zebrafish were subjected to perform a serial of behavioral tests, such as novel tank, mirror biting, predator avoidance, social interaction and shoaling. Later, 20 behavioral endpoints obtained from these five tests were transformed into a scoring matrix. Principal component analysis (PCA) and hierarchy clustering were performed to evaluate and compare the zebrafish behavior profiling. By using this phenomic approach, we were able to systematically evaluate the toxicity of the common solvents in zebrafish at a neurobehavioral level for the first time and found each common solvent-induced unique behavioral alteration to produce fingerprint-like patterns in hierarchy clustering and heatmap analysis. Among all tested common solvents, acetone and PEG-400 displayed better biocompatibility and less toxicity since they triggered less behavioral and biochemical alterations while methanol and DMSO caused severe behavior alterations in zebrafish after chronic exposure of these solvents. We conclude the behavioral phenomic approach conducted in this study providing a powerful tool to a systematical exploration of the common solvent toxicity at the whole organism level.

Meta-Transcriptomic Analysis of RNAseq Data Reveals Pacu and Loach Fish with Unusually High Levels of Myoglobin Expression in Skeletal Muscles.

Simple SummaryOxygen-binding proteins that mediate oxygen-binding for storage and consumption, to reduce energy, are very diverse in fish, depending on their habitats. In the present study, oxygen-binding protein gene expression in the skeletal muscle of 25 diverse fish species was examined by a meta-transcriptomic approach. By using RNAseq data, this is the first study to examine the high level of myoglobin, one of the oxygen-binding proteins, transcripts in pacu and loach fish that might be related to their high tolerance for the oxygen-deficient environment. In addition, this study presents the power of the current method to compare the fish oxygen-binding protein expression and its putative gene expansion event.Oxygen-binding proteins, such as myoglobin, hemoglobin, neuroglobin, and cytoglobin, play a role in oxygen binding and delivery to tissues. In icefish, the loss of myoglobin and hemoglobin genes has been reported to be an adaptive evolution event. This interesting finding prompted us to exam oxygen-binding protein expression in diverse fish species. Taking advantage of substantial RNAseq data deposited in the NCBI (National Center for Biotechnology Information) database, we adopted a meta-transcriptomic approach to explore and compare four oxygen-binding protein gene expression levels in the skeletal muscle of 25 diverse fish species for the first time. RNAseq data were downloaded from the NCBI Sequence Read Archive (SRA) database, and de novo assembly was performed to generate transcript contigs. The genes encoding oxygen-binding proteins were then identified by the BLAST search, and the relative expression level of oxygen-binding protein genes was normalized by the RPKM (Reads per Kilobase Million) method. By performing expression profiling, hierarchy clustering, and principal component analysis, pacu and loach fish were noticed by their high myoglobin expression levels in skeletal muscle tissues among 25 diverse fish species. In conclusion, we demonstrated that meta-transcriptomic analysis of RNAseq data is an informative approach to compare the oxygen-binding protein expression and putative gene expansion event in fish.

Driving force analysis of irrigation water consumption using principal component regression analysis

The effective management of irrigation water consumption is one of the main countermeasures to combat water shortages. This paper introduced an integrated approach to determine the major factors influencing irrigation water consumption in China. It combined multiple linear regression and principal component analysis to analyze the relationship between irrigation water consumption and influencing factors and then applied analytic hierarchy process and cluster analysis to analyze the spatial variation in driving factors of irrigation water consumption. Based on statistical data from the 31 provinces of China from 2000 to 2015, the results showed that irrigation water consumption was positively affected by the planting size, the ratio of surface water in water consumption (RSW), the planting structure, the annual ET0 (AE) and the annual average temperature (AAT); in contrast, consumption was generally negatively affected by irrigation technique, economic development, and annual rainfall (AR). The water consumption structure, irrigation technique and planting structure were major influential factors in most provinces of China, and there were significant differences in different regions; thus, regions should be restructured to be studied as subregions. For the total consumption of irrigation water, Central China was mainly affected by the water consumption structure, irrigation technique and climatic conditions, and North and Northwest China were hardly influenced by planting structure. Northeast, Southwest and southeastern coastal China were slightly affected by climatic conditions. For the per unit area irrigation water consumption, Central China was mainly affected by the water consumption structure, irrigation technique, planting size and climatic conditions, Southwest, South, East and Northeast China were mainly affected by the planting structure and planting size, and Northwest and North China were mainly influenced by the irrigation technique, water consumption structure and planting size.

Characterisation of flaxseed cultivars based on NIR diffusion reflectance spectra of whole seeds and derived samples

Discrimination of yellow and brown flaxseed cultivars was made based on diffusion reflectance FT-NIR spectra of whole seeds. The spectra of flaxseed kernels, hulls, defatted flours, and oils were also measured for comparison. Hierarchy cluster analysis (HCA) and principal component analysis (PCA) were used for the discrimination. Multivariate analyses of FT-NIR spectra led to satisfactory discrimination of all flaxseed cultivars of this study mainly according to the nutritionally important fatty acid composition that was confirmed by comparison with the corresponding spectra of flaxseed kernel and oil. By contrast, spectral features of proteins, polysaccharides, and tannins predominated in the FT-NIR spectra of flaxseed hulls and defatted flours.