Principal Component Cluster Research Articles

Phenotypic variation of local rice in West Java, Indonesia

Rice is the leading staple food in Indonesia and one of the largest production centers in West Java Province. Of the wide local varieties of rice in West Java, only a few have been inventoried and characterized for their morphological characteristics. This study aims to determine West Java’s phenotypic diversity of rice plants. Inventory and morphological characterization of local rice plants was carried out from 2018 to 2021 in seven districts in West Java (Sukabumi, Subang, Cianjur, Sumedang, Bogor, Tasikmalaya, and Bandung). A total of 30 accessions of local rice were observed based on Rice Descriptors. Data analysis used Principal Component Analysis (PCA) and Cluster Analysis with Minitab 21. The results showed that the seven main components contributed to the proportion of diversity of 83.7%. The local rice varieties in the five groups had a degree of similarity of 30%. The characters of leaf blade length, ligule length, ligule color, stem diameter, panicle extrusion, and the presence of awn contributed the most to the total diversity.

Local Morphological Variety of Avocado: West Java, Indonesia

Avocado (Persea americana Mill.) is a fruit that originated in southern Mexico and Central America and has since expanded far to many nations, including Indonesia in Southeast Asia. In Indonesia, one fruit product with a great economic worth is the avocado. One of the generating regions is West Java. This study aims to examine the morphological variety of avocados in several West Java locations. The study was carried out between 2019 and 2022. The West Javan regions of Bogor and Depok Regency were noted for their avocado farming. As described by the avocado descriptor, the tree, leaves, fruit, and seed were observed. Principal Component Analysis (PCA) and Cluster Analysis were employed in the data analysis by Minitab 16. The findings revealed that 81.3% of the variety was contributed by the five main factors. The diversity of avocado varieties was divided into three groups with a 31% degree of similarity. Morphological characteristics such as fruit shape, skin color, fruit flesh color, fruit flesh thickness, and seed shape, including tree shape, leaf shape, and fruit neck, contributed the most to the total diversity.

Assessing coastal outfall impact on shallow enclosed bays water quality: Field and statistical analysis

Shallow bays, valued for their environmental, economic, and social significance, face increasing threats from anthropogenic stressors, primarily wastewater discharge through coastal outfalls. The slow tidal currents in these bays hinder the effective dispersion of pollutants to deeper waters, exacerbating their impact. This study assesses the spatial effects of wastewater and brine discharges on Sulaibikhat Bay's water quality. The approach combines fieldwork, laboratory analysis, and statistical techniques to identify pollutant types, sources, and concentrations near outfalls, nearshore, and offshore areas. Throughout the study, high water temperatures were observed consistently, exceeding 30 °C in summer and 18.6 °C in winter near most outfalls, with a maximum deviation from the ambient water of 11.1 °C recorded in December. In addition to elevated electrical conductivity (EC) levels peaking at 60,700 μs/cm, these elevated temperatures significantly reduce dissolved oxygen levels and have been linked to fish kill events in the Bay. NH3-N, TSS, COD, BOD5, FC, and FS concentrations exceeded allowable limits in 56.4 %, 92.25 %, 40.30 %, 32.1 %, 70 %, and 63.36 % of samples, respectively, often reaching extreme levels. Also, the BOD5/COD ratios suggest the presence of non-biodegradable organic matter, mainly from industrial sewage, and the FC/FS levels implicate human and animal waste. These results indicate a mix of domestic, industrial, and commercial wastewater discharges and underscore the severe threat coastal outfalls pose to ecosystem health and water quality in Sulaibikhat Bay. Principal Component Analysis (PCA) and Cluster Analysis (CA) delineate two distinct environmental zones with varying characteristics and contamination levels, necessitating expanded monitoring. Finally, substantial field research, numerical modeling, and establishing a sustainable environmental management system are needed to protect this fragile ecosystem. Also, converting outfalls into offshore may mitigate the environmental status of the bay by enhancing pollutant dilution and dispersion.

Hydrogeochemistry, ionic speciation, controlling processes and agricultural suitability of groundwaters in sections of the semi-arid basement complex of north–central Nigeria

In order to ascertain the governing mechanisms, sources, and speciation of ionic species, identify hydrochemical facies, and assess their appropriateness for agricultural use, groundwaters from several portions of the semi-arid basement complex of north–central Nigeria were analyzed based on chemistry. Basement aquifers made of gneiss-migmatites, metasediments, and granitoids store groundwater. Standard analytical techniques were used to analyze the fluids for main cations, anions, and physical characteristics. The results showed that the waters were slightly acidic (with a mean pH of 5.38, below the permissible range of 6.5–8.5), and that the predominant cations and anions were Na+ >Ca2+ >K+ >Mg2+ and Cl− > NO3- > HCO3- > SO42−, respectively. Analysis of the ions' stoichiometric ratios reveals that alkali elements predominate, making up about 55.3% of the ions and being connected to silicate weathering. Based on ionic ratio calculations, it was determined that ion exchange was a key factor controlling water chemistry. Ionic species cross plots show that silicate weathering (sodic and calcic plagioclase) predominates. Hydrochemical facies, Gibbs plots, and principal component (correlation, cluster and factor) studies all show that ionic elements are geogenic, essentially coming from the weathering of silicates with ion exchanges. Based on predicted saturation indices, hydrochemical modeling by the computer program VISUAL-MINTEQ reveals that the majority of main ions occur in free mobile states with associated mineral species, all at undersaturated levels. Based on measurements of the sodium adsorption ratio (SAR), sodium percentage (% Na), and chloro-alkaline indices (CAI), the waters have been evaluated for their suitability for agricultural use.

Classification of Skeletal Phenotypes of Preadolescent Patients With Isolated Cleft Palate Using Principal Component Analysis and Cluster Analysis.

This study aimed to classify the skeletal phenotypes of preadolescent patients with isolated cleft palate using principal component analysis and cluster analysis. Sixty-four preadolescent female patients with isolated cleft palate (incomplete hard palate and complete soft palate cleft group, n=51; complete cleft of the hard and soft palate group, n=13; the mean age when lateral cephalograms were taken, 7.08±0.76y) were included. Ten angular and 2 ratio cephalometric variables were measured on a lateral cephalogram. Cluster analysis was performed using 3 representative variables obtained from principal component analysis (SN-GoMe, SNA, and SNB). The differences in the variables among the clusters were characterized using the Kruskal-Wallis test. As a result of the analysis, 6 clusters were obtained from 3 groups: the retrusive maxilla and mandible group: cluster 3 (14.1%, moderately hyperdivergent pattern), cluster 5 (17.2%, severely hyperdivergent pattern); the normal maxilla and mandible group: cluster 1 (23.4%, normodivergent pattern), cluster 4 (12.5%, moderately hyperdivergent pattern), cluster 6 (20.3%, severely hyperdivergent pattern); the normal maxilla and protrusive mandible group: cluster 2 (12.5%, normodivergent pattern). The distribution of isolated cleft palate types did not differ among the 6 clusters ( P >0.05). Two thirds of the patients (68.7%, clusters 1, 2, 4, and 6) had a normal anteroposterior position of the maxilla, while one third of the patients (31.3%, clusters 3 and 5) showed a retrusive mandible. These results indicate that isolated cleft palate patients have diverse maxillo-mandibular growth patterns compared with patients with cleft lip and palate.

Research Trends on Functional Data Analysis Using Scopus Database: A Bibliometric Analysis

Functional data analysis (FDA) has received significant attention from researchers due to its flexibility and diverse applications in various fields. FDA provides a comprehensive framework for analysing and extracting information from complex and high-dimensional datasets, enabling researchers to obtain insights into the underlying processes, improve modelling, and make accurate predictions. Therefore, understanding the FDA topic and its features and tools, as well as identifying the collaborative networks, are crucial for the development of its research areas. The objective of the present bibliometric study is to analyse the global research trend in FDA areas based on publication outputs, authorships, co-authorships, affiliated countries, and the co-occurrence of author keywords, which will enable researchers to assess the existing knowledge environment, future trends, potential research gaps, and collaboration opportunities. The publications from the year 1989 to 2021 were retrieved from the Scopus database, resulting in 1712 articles in journals after screening. Results have shown that articles published in the Journal of the American Statistical Association received the highest citations. Nearly 43% of the published articles were contributed by the leading authors from the USA, followed by China (11.5%) and Spain (9.4%). According to the QS World University Ranking 2021, eight of the top 20 productive institutions were ranked among the top 100 best universities. The findings indicated that researchers had intensively developed and applied FDA tools and features, such as smoothing, principal component analysis, regression, and clustering, in various domains. In addition, the expansion of FDA tools could be seen based on the recent progress in author keywords. New keywords, including function-on-function regression, function-on-scalar regression, scalar-on-function regression, outlier detection, structural health monitoring, and COVID-19, have arisen recently. Due to public concern about emerging diseases, future FDA work is expected to rise, particularly in the health sciences and biomedical fields.

Multifunctional agriculture in a peri-urban fringe: Chinese farmers’ responses to shifts in policy and changing socio-economic conditions

Recent Five-Year Plans and No. 1 Central Documents have emphasised the need for Chinese agriculture to play multiple functions to enhance rural development, alleviate rural poverty and increase agricultural productivity. The concept of Chinese agriculture as multifunctional is explored, linking it to specific policy aims, with three key historical phases of the development of multifunctional agriculture (MFA) recognised. MFA has progressed rapidly in rural-urban fringes across China, and its recent evolution is investigated herewith within two case-study districts (Baqiao and Lintong) in the megacity of Xi’an, Shaanxi Province. Since the economic reforms of the late 1970s, farmers in the area have greatly increased horticultural production to supply the substantial local urban market, displacing traditional grain cultivation, although much high-quality farmland has been lost to urban development, especially in Baqiao. The city has also supplied tourists for farm-based tourism activities (nong jia le), including pick-your-own fruit. A questionnaire survey of sample farm households in 17 villages in the two districts generated detailed information on land management, including farm-based enterprises, participation in co-operatives, marketing, and both recent and future planned changes to farms. Factor analysis of mixed (qualitative and quantitative) data (FAMD) and hierarchical clustering of principal components (HCPC) were used to examine typical characteristics of MFA in the peri-urban fringe. This yielded five principal dimensions of farming, with on-farm environmental actions as a key characteristic. There were also three different clusters of farmers, differentiated between commercial horticultural production, contrasting less intensive part-time farmers with farmers in co-operatives and/or producing for ‘dragonhead’ enterprises. Renewed government support for grain cultivation to increase food availability has led to a minor reversion to cereal production, while multifunctionality has been impacted negatively by the Covid pandemic, with reduced tourist numbers. Loss of revenue from tourism is prompting farmers to search for other income streams via increased agricultural outputs, new marketing outlets, and contributions to a more diversified rural economy involving value-adding to agricultural products.

Evaluation of bioactive compounds, antioxidant capacity and mineral elements in the leaves of guava (Psidium guajava L.) genotypes from China

Guava (Psidium guajava L.) is a medicinal tree species and its leaves are rich in beneficial bioactive compounds with antioxidant capacity. China has the second-largest planting area in the world however a comprehensive evaluation of the antioxidant capacity of guava genotypes in China has not yet been conducted yet. To identify the desirable genotypes with the greatest antioxidant capacity, 18 guava genotypes widely cultivated in China were collected in a germplasm garden. In this study, the antioxidant capacity, bioactive compound contents and mineral element contents of guava leaves were assessed. Genotypic variation was observed for antioxidant capacity, bioactive compound contents and mineral element contents in guava leaves. The bioactive compound contents were all significantly and positively correlated with the antioxidant capacity in guava leaves. Correlation analysis indicated that the total phenolic total triterpenoid contents were significantly related to the total phosphorus content. Principal component analysis and cluster analysis showed that DW was superior in antioxidant capacity (radical scavenging abilities of DPPH and ABTS) and total phenolic, total flavonoid and total triterpenoid contents, and the medicinal quality of superior guava genotypes was regulated by the leaf mineral element contents, especially phosphorus. This study is not only helpful for developing guava genotypes with superior medicinal quality in the future but can also provide theoretical support for fertilization management in the cultivation of superior guava genotypes to achieve higher medicinal quality.

Characterizing the lavage and serum cytokine profiles of interstitial pneumonia with autoimmune features and their implications for progressive fibrosis.

To explore whether cytokines could be potential biomarkers to predict the occurrence of the progressive fibrosis (PF) phenotype among patients with interstitial pneumonia with autoimmune features (IPAF). This study prospectively collected 51 IPAF and 15 idiopathic pulmonary fibrosis (IPF) patients who were diagnosed at the First Affiliated Hospital of Guangzhou Medical University from July 2020 to June 2021. All IPAF patients were followed up for 1 year to assess the development of PF phenotype. Paired bronchoalveolar lavage fluid (BALF) and serum samples were collected at enrolment and analysed for differences in 39 cytokines expression. Principal component analysis (PCA) and cluster analysis were conducted to identify a subgroup of IPAF patients at high risk for developing the PF phenotype. Finally, cytokine differences were compared between subgroups to identify potential biomarkers for PF-IPAF occurrence. According to the PCA analysis, 81.25% of PF-IPAF patients share overlapped BALF cytokine profiles with IPF. Cluster analysis indicated that IPAF patients in subtype 2 had a higher risk of developing the PF phenotype within 1 year (P = 0.048), characterized by higher levels of CCL2 and CXCL12, and lower lymphocyte proportion (LYM%) in BALF. Elevated levels of BALF CCL2 (>299.16 pg/ml) or CXCL12 (>660.115 pg/ml)were associated with a significantly higher risk of developing PF phenotype within the 1-year follow-up period (P = 0.009, 0.001, respectively). PF-IPAF phenotype exhibits similar inflammatory cytokine profiles to IPF. Cytokine CCL2 and CXCL12, and LYM% in BALF serveas potential biomarkers for predicting the PF phenotype in IPAF patients. Register: Qian Han, Website: http://www.chictr.org.cn/showproj.aspx?proj=61619, Registration number: ChiCTR2000040998.

GENETIC DIVERSITY OF THE BC2 POPULATION OF ALFALFA MULTIFOLIATE LEAVES BASED ON MORPHOLOGICAL TRAITS USING CORRELATION, PRINCIPAL COMPONENT, AND CLUSTERING ANALYSIS

The current research aimed to assess the 179 BC2 population of alfalfa (Medicago sativa L. cv. Huaiyin) and PL34HQ multifoliate leaves and their parents to select genotypes based on morphological traits for future alfalfa breeding programs. A backcross breeding was carried out between the recurrent male parent and alfalfa PL34HQ as the non-recurrent female parent of alfalfa. In the pod setting stage, morphological traits were measured in the BC2 populations. Data were analyzed for descriptive statistics, correlation, principal component (PCA), and agglomerative hierarchical cluster analyses. The result of descriptive statistics revealed high variation in the means, minimum, and maximum values for most of the morphological traits. Therefore, high variability was observed in plant height (PH) 26-98 cm, number of branches per plant (NBP) 6-74, stem diameter (SD) 1.46-5.46 mm, second branch length SBL 0-62 cm, number of multifoliate leaves per plant (NMFLP) 0-95.7%, number of multifoliate leaves on the main branch (NMFLMB) 0-90.6%, number of nodes (NN) 12-24, fresh shoot weight (FSW) 3.10-359.4 g, and dry shoot weight (DSW) 0.40-108.6 g. The results showed that the comprehensive traits of the BC2 population tended to the recurrent parent, about 32.40% of the total population. However, many plants tended to the non-recurrent parent, about 67.40% of the total population, with a high multifoliate rate. Correlation analysis revealed a significant positive association of plant height with stem diameter, fresh shoot weight, dry shoot weight, second branch length, number of nodes, and branch number. Principal component analysis (PCA) discovered the first three components with an eigenvalue greater than one, contributing 78.98% of total variability for different traits. The PC1 showed favorable factor loading for all morphological traits. The contribution of dry shoot weight, fresh shoot weight, stem diameter, and plant height was highest in principal component 1. The average hierarchical cluster analysis method grouped all the genotypes into four main clusters. Alfalfa multifoliate leaf genotype clustering based on morphological traits would help identify potential genotypes for future breeding research and programs. Keywords: - Alfalfa multifoliate leaves, Principal component analysis, Correlation, Cluster analysis.

Learning preference among accounting students of the University of Mindanao

Learning preferences are a way to enhance the learning experiences. Students can adjust learning processes and techniques if they understand the impact of different experiences. This study utilized cluster analysis to categorize the learning dimensions on the index of learning preferences of first-year accounting students at the University of Mindanao. A survey was conducted on accounting students, and a method of quantitative correlation was employed. Data were collected using a modified research questionnaire. To determine the learning preferences of first-year accounting students, the researchers use gender, age, and socio-economic status as indicators. The statistical treatments used to analyze and interpret data were principal component analysis and clustering analysis. The study's results indicated the following: (a) most students gain the most knowledge from what they hear; (b) the method that the students utilized is Auditory and Visual. In contrast, group and kinesthetic learning preferences are the students' least preferred.

Evaluation of the water quality and the eutrophication risk in Ramsar site on Moroccan northern Mediterranean (Marchica lagoon): A multivariate statistical approach

This study aimed to assess the extent of eutrophication in the Marchica lagoon, using the trophic index (TRIX), trophic status index (TSI) and Redfield ratio (N/P). Seawater samples were collected monthly from March 2018 to February 2019 from ten locations in the lagoon. The TRIX index ranged from 1.25 to 8.87, indicating oligotrophic to eutrophic conditions. TSI values ranged from 28.4 to 65.1, indicating ultraoligotrophic to supereutrophic seawater. The Redfield ratio consistently showed N/P values below 16, designating phosphorus as the limiting factor for algal growth. Principal component analysis (PCA) and cluster analysis (CA) revealed distinct coastal water masses based on seasons and sampling regions. Given these findings, urgent conservation and management measures are recommended to address the eutrophication issues threatening the delicate balance of the Marchica lagoon.

Design and Implementation of a Fuzzy Classifier for FDI Applied to Industrial Machinery.

In the present work, the design and the implementation of a Fault Detection and Isolation (FDI) system for an industrial machinery is proposed. The case study is represented by a multishaft centrifugal compressor used for the syngas manufacturing. The system has been conceived for the monitoring of the faults which may damage the multishaft centrifugal compressor: instrument single and multiple faults have been considered as well as process faults like fouling of the compressor stages and break of the thrust bearing. A new approach that combines Principal Component Analysis (PCA), Cluster Analysis and Pattern Recognition is developed. A novel procedure based on the statistical test ANOVA (ANalysis Of VAriance) is applied to determine the most suitable number of Principal Components (PCs). A key design issue of the proposed fault isolation scheme is the data Cluster Analysis performed to solve the practical issue of the complexity growth experienced when analyzing process faults, which typically involve many variables. In addition, an automatic online Pattern Recognition procedure for finding the most probable faults is proposed. Clustering procedure and Pattern Recognition are implemented within a Fuzzy Faults Classifier module. Experimental results on real plant data illustrate the validity of the approach. The main benefits produced by the FDI system concern the improvement of the maintenance operations, the enhancement of the reliability and availability of the compressor, the increase in the plant safety while achieving reduction in plant functioning costs.

Abstract P2089: Myocardial Long Non-Coding RNAs Expression Signatures In Heart Failure With Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) accounts for greater than half of all HF cases and has 5 year mortality rates on par with HF with reduced ejection fraction (HFrEF). Unlike HFrEF, however, HFpEF patients have limited therapeutic options. Improved understanding of myocardial epigenetics are needed to develop novel therapeutics. We have previously conducted myocardial transcriptomics in HFpEF and found several thousand differentially expressed genes between HFpEF vs Controls. Targeting a single gene or pathway will likely not address the many abnormalities seen in HFpEF, highlighting the need for epigenetic approaches. Long non-coding RNAs (lncRNAs) exert epigenetic control over large numbers of transcripts and represent potential therapeutic targets in HFpEF.We measured lncRNA expression from myocardial tissue from HFpEF (n=41), HFrEF (n=30), and control (CON, n=24). Agnostic principal component and hierarchical gene clustering analyses separated HFpEF, HFrEF and CON with minimal overlap. LncRNA’s differentially expressed in HFpEF were predicted to control pathways related to neurotransmitter release, cytoskeleton, and muscle cell development. Three lncRNA-derived HFpEF subgroups were identified with distinct clinical correlates and clinical outcomes, and a subset of these predicted a poor prognosis. Differential expression analysis using DESeq2 revealed 95 upregulated and 342 downregulated lncRNAs.Our findings suggest that HFpEF has a lncRNA profile distinct from HFrEF and controls, highlighting potential epigenetic therapeutic targets for HFpEF.

Taxonomic Comparison, Antioxidant and Antibacterial Activities of Three Ebenus pinnata Ait. ecotypes (Fabaceae) from Algeria

Ebenus pinnata is not known as a traditional medicinal plant, but modern research has revealed its richness in components of medicinal value. Yet, the species remains understudied. Here, we assess the climate effect on its morphology, pollen grains size, chromosome numbers, pollen fertility, and antioxidant and antibacterial activities. Plant material was collected from the humid, sub-humid, and semi-arid areas of Northeastern Algeria. Data treatment by principal component analysis and/or cluster analysis and ANOVA post hoc tests revealed three significantly discriminated ecotypes correlated with the climate stage. Significant differences were detected for whole plant morphology, pollen size, and antioxidant activity. No differences were revealed for chromosome numbers, pollen fertility, and antibacterial activity. The studied material showed a chromosome number of 2n = 14, high pollen fertility (94.04 ± 2.64–95.01 ± 2.02%), small pollen grains (polar axis: 17.95 ± 1.10–19.47 ± 1.27 µm; equatorial axis: 12.80 ± 1.18–13.03 ± 0.99 µm), high antioxidant activity (TPC: 50.79 ± 0.51–56.89 ± 0.46 mg/g; DPPH: 71.18 ± 2.24–95.67 ± 2.02 mg/g; RP: 11.09 ± 1.24–25.88 ± 0.26 mg/g), and efficient antibacterial activity (Inhibition area diameter: 9.25 ± 1.06–12.00 ± 1.41 mm). The climate seems to exert a significant impact on multiple aspects of the plant’s biology. It would be interesting to assess the genetic basis of this phenomenon in E. pinnata and other species.

Happiness and its relationship to expectations of change and sustainable behavior in a post-COVID-19 world

PurposeThis study aims to analyze the relationship between expectations of change after a crisis, such as that generated by COVID-19, people's levels of happiness and the propensity for pro-sustainable behavior.Design/methodology/approachSurveys were conducted using 1,130 observations. The aim was to measure expectations of change during the pandemic. Furthermore, the relationship between these expectations, happiness levels, and attitudes towards sustainability was analyzed for various elements of daily life. Statistical techniques such as principal component analysis (PCA), cluster analysis, variance analysis and correlation analysis were utilized to explore the underlying patterns and relationships.FindingsOptimistic expectations for post-pandemic change are associated with a greater likelihood of engaging in environmentally beneficial behaviors, leading to higher levels of life satisfaction. This correlation is particularly significant when individuals envision broader transformations in the collective behavior of humanity. These findings suggest a strong link between beliefs in positive societal transformations and both pro-environmental actions and personal well-being.Research limitations/implicationsThe unique circumstances of the pandemic, characterized by heightened media consumption, likely influenced the expectations of individuals, particularly fostering pessimistic outlooks in critical situations. Clear and solid variables were utilized despite not employing validated scales to measure expectations. However, it has been proven that there is a clear link between change expectations, happiness, and the propensity for a more sustainable daily life.Practical implicationsThis study identifies guidelines that strengthen brands' communication strategies based on individuals' sustainability profiles and visions of the future.Social implicationsThere is a need to target skeptical, change-resistant segments of the population with a more convincing and solid discourse to promote sustainable consumption and behavior.Originality/valueThis is the first study to simultaneously address the relationship between individuals' expectations of change following traumatic events such as the pandemic, their engagement in sustainable behavior, and their increased levels of happiness.

Principal Component and Cluster Analyses of 20 Genotypes of Chilli (Capsicum sp.) Planted on Peatlands

This research aims to obtain information about the qualitative and quantitative characteristics of the genetic diversity of 20 chili genotypes and to analyze their similarity as the basis for selecting parental crossbreeds in peatland assembly chili varieties. This research was conducted in the peatlands of Tuah Karya Village, Tampan District, Pekanbaru City, Riau Province and analyzed at the Plant Breeding Laboratory of the Faculty of Agriculture, Riau University from November 2020-April 2021. The study used a randomized block design consisting of 20 genotypes (Agronomy and Horticulture IPB University’s collection) with three replications, so there were 60 experimental units. There are 22 qualitative characters and 13 quantitative characters identified. Qualitative data was transformed into quantitative data based on International Plant Genetic Resource Institute (IPGRI) and quantitative data was the average data. Principal component and cluster analyses were conducted using SPSS Statistics 20 software. Results show that large chili plants based on principal component analysis and cluster analysis were grouped into four clusters at level of similarity 82.5% and a proportion of diversity of 57.53%. The closest similarity of large chili is CG4 and CG6. Based on the principal component analysis and cluster analysis cayenne pepper plants are grouped into two clusters at a 90% similarity level and 72.80% diversity proportion. The closest similarity of cayenne pepper is CG16 and CG19.

Morpho-molecular exploration and selection of elite genotypes from indigenous Syzygium cumini L. Skeels (jamun) diversity of North-Western Indian Himalayas

AbstractEfficiently distinguishing various Syzygium cumini L. Skeels (jamun) accessions holds practical significance for selection purposes. This study concentrated on 15 superior genotypes of jamun from the North Western Indian Himalayas, selected for their pivotal horticultural traits. Drawn from a pool of 82 collected genotypes and assessed across two consecutive years (2019 and 2020), these genotypes underwent morphological evaluations utilizing a randomized block design replicated thrice. Concurrently, random amplified polymorphic DNA (RAPD) and inter simple sequence repeat (ISSR) markers were employed for molecular analysis. Substantial variations surfaced among genotypes, both in morphological traits and fruit biochemistry. Notably, tree 43 exhibited promise across multiple horticultural facets, encompassing fruit weight, length, pulp weight, pulp-to-seed ratio and pulp percentage. Conversely, tree 49 excelled in elevated levels of total soluble solids, total sugar and reducing sugar. While principal component analysis and cluster analysis unveiled modest genetic variability, RAPD and ISSR markers unveiled pronounced molecular-level polymorphism. Agglomerative hierarchical clustering delineated the genotypes into five distinct clusters. Cluster I encompassed two genotypes, cluster II embraced five while the largest group, cluster III, included six genotypes. Clusters IV and V highlighted individual genotypes, trees 43 and 54 respectively. In the molecular analysis, UPGMA clustering yielded two primary clusters, spotlighting the noteworthy similarity between genotypes trees 49 and 52 whereas, trees 40, 43, 44 and 48 stood distinct. The observed genetic diversity stands as a valuable resource with substantial potential to enrich diverse breeding initiatives. These salient genetic variations underscore the richness within the studied population, offering a valuable asset for focused future pursuits.

Modeling Central Asia’s Choices in Containing COVID-19: A Multivariate Study

Different countries have adopted different policies in their fight against the COVID-19 outbreak. In this work we aim to model these approaches with respect to the first wave of COVID-19 (from January to October 2020) in the five Central Asian republics (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan). By means of a multivariate approach based on principal component analysis and cluster analysis, we derived three clusters. Each of these represents a different strategy adopted by a group of governments in a given period of the first wave: pre-pandemic, initial reaction, and emergency scenarios. The contribution of these results is two-fold: on the one hand they may help us to understand differences and similarities among Central Asian republics during the first wave of the COVID-19 outbreak and guide future quantitative or qualitative studies; on the other hand, our findings suggest that, with the exception of Turkmenistan, the different countries adopted very similar strategies and that deaths, more than cases, pushed governments to impose restrictions.

Trophic transfer of heavy metals through aquatic food web in the largest mangrove reserve of China

Understanding the mechanism of trophic transfer of heavy metal through the aquatic food web is critical to ecological exposure risk assessments in mangrove ecosystems. Zhanjiang Mangrove National Nature Reserve (ZMNNR) is the largest and biologically richest mangrove reserve in China, but has been exposed to heavy metal pollutants caused by the progressive industrialization and urbanization. We collected a variety of aquatic consumers, and primary producers, as well as sediments from the ZMNNR and analyzed them for heavy metal (Cd, Cr, Cu, Ni, Pb and Zn) concentrations, and for both δ13C and δ15N values to establish the trophic levels.The trophic magnification factors (TMF) of Cd, Cu and Zn are 0.19 (p < 0.01), 0.07 (p < 0.01) and 0.33 (p < 0.05), respectively, indicating significant biodilution in a simplified food web composed of bivalves, crustaceans and fish. There are also potential tendencies of biodilution for Cr, Ni and Pb. Comparison of heavy metals in representative fish and shrimp in the ZMNNR with those in worldwide mangroves indicate a low risk level for aquatic consumers in our ecosystem. Quantitative source tracking is conducted based on principal component analysis and cluster analysis, which indicate that Cr, Ni and Pb are mainly originated from natural geological processes, Cu and Zn from shrimp farming and agriculture activities, and Cd from the deposition of aerosol released by regional metal smelting industry.