Principal Component Cluster Analysis Research Articles

Evaluation of Water Quality of Groundwater of Sanghar District, Sindh, Pakistan: Chemical and Multivariate Analysis

Sanghar District is located in the central part of Sindh Province and shares a boarder with India to the east. This work examines the water quality of the groundwater of three subdistricts, Sanghar, Khipro, and Jan Nawaz Ali, mostly used for human consumption, cattle farming, and irrigation. A total of 74 representative samples were collected and analyzed for 26 different parameters, including anions, cations, trace, and toxic elements. The total dissolved salts (TDSs) contained in 41 samples (55.4%), the major cations, K, Na, Mg, and Ca, in 44.6–93.2% of samples, and the major anions, Cl, HCO3, and SO4, in 68.6–81.0% of samples were within the permissible guidelines of the World Health Organization (WHO). The samples containing elements Cr (24.0%), Pb (29.7%), Ni (39.2%), Cd (40.5%), As (10.8%), and F (39.18%) were above the permissible limits of the WHO. The groundwater samples were examined for water quality index (WQI), contamination index (Cd), chronic daily intake indices (CDIs), hazard quotient indices (HQ), principal component analysis (PCA), piper diagrams, Gibbs diagrams, and cluster analysis to ascertain nature of the groundwater present in the study area. The samples were also examined for suitability for irrigation by sodium percentage (Na%), sodium adsorption ratio (SAR), Kelly’s index (KI), permeability index (PI), and Wilcox diagrams. Samples in the range of 0 to 58.33% were inappropriate for irrigation.

Evaluating the Path to the European Commission’s Organic Agriculture Goal: A Multivariate Analysis of Changes in EU Countries (2004–2021) and Socio-Economic Relationships

This study comprehensively analyzed the dynamic landscape of organic farming in the European Union (EU) from 2004 to 2021, investigating the shifts in dedicated agricultural areas influenced by evolving preferences and the priorities of farmers and consumers. Examining the impact of socio-economic factors, including gross domestic product (GDP) per capita, the human development index (HDI), and human population density, this study established multivariate relationships through country-level analyses based on correlations, principal component analysis, cluster analysis, and panel analysis. Despite a universal increase in the organic agriculture areas across all the EU countries during the study period, the production levels exhibited negative correlations with the human population density, GDP per capita, and HDI. Notably, the Baltic countries and Austria led in organic farming production, while Malta, the Netherlands, Belgium, Ireland, and Luxemburg formed a distinct group in the cluster analysis with less intensive organic agriculture per capita. These insights are crucial for supporting the resilience and sustainability of organic farming as it continues to evolve. Predictions of organic agriculture share for 2030 based on trends evaluated using linear regression in the years 2004–2021 estimated about 12% of utilized agricultural area, which was much lower than the target share of the European Commission at 25%. Predictions based on linear regression showed that achieving the European Green Deal target of a 25% share of organic agriculture in unlikely in most EU countries by 2030. The target is only highly probable to be obtained in Austria, Estonia, and Sweden. The EU countries varied significantly across various indices characterizing organic agriculture, including organic agriculture area share. It should be noted that the study was conducted on the data obtained prior to the outbreak of the war in Ukraine, which could potentially alter the previous trends in the development of organic agriculture in the EU.

Working cycle condition construction for electric wheel loader based on principal component analysis and cluster analysis

With the rapid development of new energy technology, cycle condition is significant for the design of powertrain system, whole machine economy, endurance, and other performance parameters of pure electric drive machines. Many cycle conditions of the passenger car industry have been defined. While that for the loader which has complex operation modes and working conditions, has less research on this aspect. Cycle conditions suitable for loader have not been constructed. To support the research and development of electric loader power system, the cycle conditions that can reflect the driving characteristics of electric loader are studied in this paper. According to the typical “V” cycle condition of loader, the actual driving condition data are collected and the kinematic segments are divided. The kinematic segments are grouped into five categories by using principal component analysis and K-means clustering algorithm to obtain the clustering center of each category. The working cycle condition is formed by extracting the combination of segments closest to the clustering center. Finally, based on AMESim simulation and whole machine test analysis, the error between the simulation and vehicle test results of the energy consumption is 3.4%. The accuracy and effectiveness of the proposed constructed cycle conditions are verified.

Health risk assessment of heavy metals in soil and vegetables from major agricultural sites of Ohio and West Virginia

Contamination of soil and crops with heavy metals (HMs) poses a significant environmental challenge in the United States, while the status of metal contamination and associated health risks have been merely studied. Hence, this study aimed to assess metal contamination in major agricultural sites of Ohio and West Virginia, and evaluate the potential health risks associated with consuming metal-contaminated vegetables. Among the agricultural sites studied, Fe was the most predominant contaminant in all the sampling sites, ranging from 28,410 to 67,306 mg/kg of soil, exceeding the permissible limit of the US-EPA. Whereas Cd was the least contaminant, exceeding the permissible limit only in three sampling sites (ME1, ME3, and ME6), ranging from 0.13 to 2.91 mg/kg of soil. Interestingly, range of metals in vegetable samples were within the permissible limits. Principal component and hierarchical cluster analysis indicated the different natural and anthropogenic sources of metals in soil. In noncarcinogenic health risk assessment, the values of EDI, TEDI, THQ and HI levels for all the metals were lower than their daily uptake. However, CR and TCR assessment reveal significant risks associated with Ni exposure for both adults and children, with values of 3.487E-4 and 1.172E-3, and 5.362E-4 and 1.286E-3, respectively, within these agricultural sites. Therefore, regular monitoring of metal concentrations in soil and vegetables, as well as associated health risks, is strongly recommended to prevent potential health hazards in the future.

The marine conservation deposits of Monte San Giorgio (Switzerland, Italy): the prototype of Triassic black shale Lagerstätten

Marine conservation deposits (‘Konservat-Lagerstätten’) are characterized by their mode of fossil preservation, faunal composition and sedimentary facies. Here, we review these characteristics with respect to the famous conservation deposit of the Besano Formation (formerly Grenzbitumenzone; including the Anisian–Ladinian boundary), and the successively younger fossil-bearing units Cava inferiore, Cava superiore, Cassina beds and the Kalkschieferzone of Monte San Giorgio (Switzerland and Italy). We compare these units to a selection of important black shale-type Lagerstätten of the global Phanerozoic plus the Ediacaran in order to detect commonalities in their facies, genesis, and fossil content using principal component and hierarchical cluster analyses. Further, we put the Monte San Giorgio type Fossillagerstätten into the context of other comparable Triassic deposits worldwide based on their fossil content. The results of the principal component and cluster analyses allow a subdivision of the 45 analysed Lagerstätten into four groups, for which we suggest the use of the corresponding pioneering localities: Burgess type for the early Palaeozoic black shales, Monte San Giorgio type for the Triassic black shales, Holzmaden type for the pyrite-rich black shales and Solnhofen type for platy limestones.

Hydrochemical, hydrogeological, and cancer health risk analysis of groundwater due to anthropogenic activities, Hasilpur, Pakistan.

Drinking water quality deteriorates rapidly due to anthropogenic activities and rapid population growth. These activities, in developing countries, will lead to water scarcity. In Pakistan, 70% of the population has no access to safe water, and people use canal water to drink. This study performed hydrochemical, hydrogeological, and cancer risk analyses on Tahsil Hasilpur, Bahawalpur, Pakistan. Thirteen tube wells were selected for groundwater and borehole log study. Twenty-two drinking water quality parameters were analyzed using standard methods and quality checks. The borehole data (2D and 3D) shows the abundance of sand (fine and coarse) with some uniformities, which changes the groundwater quality. The results of water quality parameters show that the concentration of TDS (2064-11,159 mg/L), Cl-1 (213-4917 mg/L), As+3 (0.048-0.158 mg/L), Pb+2 (1.294-1.673 mg/L), and Cd+2 (0.008-0.053 mg/L) were beyond guideline values. The statistical analysis showed that the parameters have a moderate to strong correlation (Pearson correlation), which may be due to the same origin (ANOVA). The principal component analysis and cluster analysis confirm the multiple sources of pollutants in the groundwater of the study area. The Piper, Durov, Stiff, and Scholler diagrams confirm that the groundwater system has an abundance of Ca+2 and Mg+2 with Cl-1. The Gibbs diagram showed that the groundwater is not saturated and tends to dissolve more minerals. The hazard quotient values are above 1.0, which indicates noncancer risk severity. The HQ trend was As+3 > Pb+2 > Cd+2 > Ni+2 > Cu+2 > Cr+2 > Zn+2 > Fe+2. The cancer risk values showed that 3-5 people/100 population were exposed to cancer risk. The trend of CR was As+3 > Cd+2 > Cr+2 > Pb+2 > Ni+2. The GIP mapping of pollutants showed that the concentration of pollutants near the canals was high compared to the locations away from the canal. The overall groundwater quality is alarming and needs immediate government attention.

Chemical compositions of the essential oils of endemic wild Origanum majorana var. tenuifolium collected from three different locations during flowering and post-flowering phases in North Cyprus, Multivariate Statistical Analyses

Wild growing Origanum majorana L. var. tenuifolium Weston was collected from three different locations (Om1: Avtepe, Om2: Alevkayası, Om3: Kozanköy) in North Cyprus. The essential oils were hydrodistilled and chemical composition analyses were simultaneously performed by GC-FID and GC-MS. The average yields of essential oils were 5.46-8.14%. Major compounds of flowering Om1 oil were cis-sabinene hydrate (45.0%) and terpinen-4-ol (11.1%) while those of Om3 (Kozanköy) oil were cis-sabinene hydrate (33.3%), terpinen-4-ol (12.3%) and α-terpineol (11.5%). In the post-flowering stage, the major compounds for Om1 and Om3, respectively, were cis-sabinene hydrate (16.7% and 18.8%), terpinen-4-ol (18.1% and 14.5%) and α-terpineol (23.9% and 20.0%). However, the main compound of the essential oils of the flowering and post-flowering oil of Om2 was α-terpineol (76.9% and 51.6%). Statistical Principal Component (PCA) and Hierarchical Cluster Analyses (HCA) tools demonstrated the composition variations of the essential oils at different times and locations. Om1 and Om3 (HCA similarity level: 98.98%) were similar while Om2 (HCA similarity level: 46.32%) was discordant.

Determination, distribution, and health risk assessment of 12 heavy metals in various edible oils in Taiwan

AbstractBackgroundMinimizing the risk of heavy metal pollution is of utmost importance to ensure consumer safety. In this research, we utilized inductively coupled plasma‐mass spectrometry to determine the presence of 12 heavy metals in Taiwanese commercial edible oils, both refined and unrefined.ResultsOur analytical findings revealed significantly lower levels of heavy metals in refined oils compared with unrefined oils. Through principal component analysis and cluster analysis of 19 types of edible oils, we identified Cd, Ba, Fe, Pb, and Co as the primary variables influencing heavy metal levels in edible oils. Notably, the heavy metal contents in the edible oils did not surpass international standards. Risk assessment results indicated that unrefined oils carried higher risk levels than refined oils. The incremental lifetime cancer risk values calculated for unrefined oils exceeded 10−6 in all age groups except for the 19 ~ 65 years category, while the noncarcinogenic risks remained well below 1, regardless of refined or unrefined oils.ConclusionsOur study sheds light on the distribution characteristics of heavy metal contents in edible oils, highlighting higher levels of heavy metals and associated risks in non‐refined oils compared with refined oils. Ultimately, the presence of heavy metals in edible oils poses low health risks to the human body.

Evaluation of the impact of coal mining on surface water in the Boesmanspruit, Mpumalanga, South Africa

Surface water quality has major environmental and socioeconomic consequences, notably in terms of the country’s long-term fresh water supply. This study aimed at assessing the current state of water quality and status of the Boesmanspruit in a coal mining environment. The study used historical water quality data for a period of five years from 2017 to 2021. Aluminum, calcium, iron, manganese, magnesium, sodium, sulfate, electrical conductivity, pH, and total dissolved solids were the water quality variables selected for the study; the chosen variables were chosen based on the available secondary data. The water quality was evaluated against South African resource quality objectives, the South African water quality guidelines, and the Canadian Council of Ministers of the Environment water quality index (CCME-WQI). The data were analyzed using such as the CCME-WQI, the comprehensive pollution index (CPI), and multivariate statistics. The following parameters were above the prescribed thresholds: pH, total dissolved solids, electrical conductivity, sulfate, manganese, and iron. The CCME-WQI results showed that monitoring locations GR S26 and GR S21 near mining activities had poor water quality (40–44), whereas comprehensive pollution index (CPI) also had similar category results for the monitoring points, indicating that they were heavily polluted (2.4–4.8). The WQI showed that if certain variables, such as aluminum, iron, magnesium, sulfate, electrical conductivity, and total dissolved solids, exceed the permissible range, the water quality would deteriorate in accordance with the CPI classification. Therefore, the CPI was the best way to categorize the water quality. The principal component analysis and cluster analysis identified two primary sources of pollution which are anthropogenic and natural. The utilization of statistical analysis proved to be effective in determining the ideal quantity of significant variables within the study area. The study recommends low-cost options for reducing the effects of acid mine drainage, which includes passive mine water treatment methods using artificial wetlands.

Ecological risk assessment, source identification and spatial distribution of organic contaminants in terms of mucilage threat in streams of Çanakkale Strait Basin (Türkiye)

In this study, the spatial distributions of organic contamination stressors in water of fluvial habitats in the Çanakkale Strait (ÇS) watershed were investigated and the data were assessed in terms of human health and mucilage threat. Seven significant riverine ecosystems flowing into the ÇS were defined in the basin. Water samples were taken in the spring season (2023), when the phytoplankton communities reach their highest densities. Then they were tested for a total of 8 limnological parameters.The Nutrient Pollution Index (NPI) and Water Quality Index (WQI) were applied to assess the comprehensive quality characteristics of waters. The Hazard Quotient (HQ) and Hazard Index (HI) were applied to indicate the prospective non-carcinogenic human health risks of organic stressors. Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied to categorize the investigated habitats and define the sources of investigated contamination parameters. Also, Geographic Information System (GIS) was used to make an effective assessment through visualization.The determined spatial mean values of the measured variables in ÇS watershed as follows: 18.21 °C for temperature, 8.51 mg/L for DO, 4.57 NTU for turbidity, 3.95 mg/L for suspended solids, 1.11 mg/L for NO3–N, 0.012 mg/L for NO2–N; 0.173 mg/L for PO4–P and 2.32 mg/L for BOD. It has been determined that the organic pollution loads and water temperature values of the investigated sub-basins increase from the upstream to the downstream locations and Çanakkale Stream was recorded as the riskiest fluvial habitat for the ÇS watershed. According to the results of health risk assessment indices, non-carcinogenic risks of organic pollutants would not be expected for all age groups.

Three-dimensional Analysis of Maxillary Morphology in Infants with Unilateral Cleft Lip and Palate.

To three-dimensionally (3D) analyze the maxillary morphology of infants with unilateral cleft lip and palate (UCLP) and preliminarily classify the alveolar arch to assist in personalization of sequence therapy. Retrospective study. Patients with UCLP referred to outpatients' clinic. 84 nonsyndromic infants with complete UCLP were recruited (58 boys, 26 girls, mean age 29.48 days). Morphometric analysis was conducted on 3D maxillary models. Principal component analysis (PCA) and cluster analysis were combined to classify maxillary phenotypes preliminarily. The Wilcoxon Signed Rank test and the Kruskal-Wallis test were used to compare differences between variables. A P value less than .05 was considered statistically significant. The maxilla was divided into three types: narrow, homogenous and broad, accounting for 9.52%, 23.81% and 66.67% respectively. The alveolar cleft site (median value) was located in 61% of the total length of the alveolar arch. In the comparison of anterior and total alveolar lengths, the non-cleft side had longer alveolar bone than the affected side, a difference of approximately 2 mm. Pairwise comparisons of variables describing alveolar symmetry revealed significant differences in all subjects; whereas type C had poorer arch symmetry than types A and B, mainly in terms of anterior and overall symmetry. In infants with UCLP, the maxillary alveolar arch was inherently asymmetrical with partially bone missing (about 2 mm). Significant differences in alveolar bone morphology and symmetry exist between different types of infants, with individuals with broad clefts (type C, the largest proportion) having the worst maxillary development.

Deciphering Genetic Diversity in Advanced Wheat Lines (Triticum aestivum L.) for Yield and Other Yield Contributing Traits Across the Locations

Twenty advanced wheat genotypes were evaluated for yield and yield-contributing traits in six field trials over two cropping seasons (Rabi 2020-21 and 2021-22) using a completely randomized block design (RBD) at two locations: the N.E. Borlaug Crop Research Centre (NEBCRC), G.B.P.U.A&T, Pantnagar, U.S. Nagar district, and the Agriculture Research Center Majhera, Nainital, Uttarakhand. The study aimed to assess genetic diversity among the genotypes via principal component analysis (PCA) and cluster analysis, offering insights into genetic variations. Three clusters were formed, with the maximum number of genotypes occurring in the second cluster. A lower p-value indicates that the clusters are statistically significant, suggesting that the observed diversity is not random. High estimates of cophenetic distance (.79) specify a high genetic distance between clusters, indicating that diverse genetic material is under study. The maximum genetic distance observed was 144.9 between genotypes G5 and G11. These findings suggest that these two genotypes are the most genetically diverse among all the studied genotypes and can be used as parents to develop high genetic variation in the studied traits. The PCA results yielded 18 principal components, with the first seven components accounting for approximately 83% of the total variance, indicating significant genetic diversity. The scree plot affirmed the robustness of the study’s results by suggesting that the first eight principal components accounted for a substantial portion of the variance.The findings of current study could be exploited in planning and execution of future breeding programme in wheat.

Forest Adaptation to Climate Change: Altitudinal Response and Wood Variation in Natural-Growth Cunninghamia lanceolata in the Context of Climate Change

This research delves into the impact of climate change on the wood traits of Cunninghamia lanceolata across various altitudinal gradients, aiming to understand the influence of altitude and climatic factors like temperature and precipitation on key wood characteristics. Employing a comprehensive approach, samples were collected from different altitudes for detailed phenotypic analysis. Methods included Pearson correlation, principal component analysis, cluster analysis, and random forest analysis. Results revealed significant variations in wood traits such as heartwood ratio, tracheid length, and width across altitudes. Notably, wood traits in lower- and middle-elevation populations exhibited higher variability compared to higher elevations, indicating greater environmental diversity and genetic adaptability at these altitudes. Climatic factors, particularly temperature and precipitation, were found to increasingly influence wood trait variation with altitude. The research concludes that the adaptation of Cunninghamia lanceolata to climate change is significantly influenced by both altitudinal and climatic factors, highlighting their importance in forest genetic breeding and conservation strategies amidst global climate change.

Water Quality Assessment of Groundwater Using Multivariate Statistical Techniques: A Case Study of Mogadishu, Banadir Region, Somalia

This study was carried out to assess the groundwater quality around the Mogadishu area, Banadir region, Somalia. Multivariate statistical techniques such as factor analysis (FA), principal component analysis (PCA) and cluster analysis (CA)were applied to 22 groundwater samples collected from boreholes and dug wells in the coastal line districts namely: Wadajir, Kaxda and Dharkinley districts of Banadir region, Somalia. Correlations among 14 hydrochemical parameters were statistically examined. A two-factor model is suggested and explains over 82.4% of the total groundwater quality variation. Factor Analysis (FA) revealed significant variables including electrical conductivity (EC), pH value and other parameters such as K<sup>+</sup>, Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup>, SO<sub>4</sub><sup>2-</sup> and hardness expressed as CaCO<sub>3</sub>, Chlorine, Fluoride, B, S, Si, and NO<sub>3</sub> which are responsible for variations in groundwater quality and affect water chemistry. The results were compared with the World Health Organization (WHO) standard guidelines. Geographic Information System (GIS) was used to create the spatial distribution maps of water quality parameters. Cluster Analysis (CA) grouped all sites into three zones based on spatial similarities and dissimilarities of physiochemical properties. The pH value and Boron, fluoride calcium, magnesium, sulfide, potassium, and Silica are well within the desirable limit at all locations. However, the concentration of conductivity chloride, hardness as CaCO<sub>3</sub>, sulfate, nitrate, and Sodium in all samples exceeded the desirable WHO maximum permissible limit. The study reveals that the groundwater quality changed due to anthropogenic and natural influences such as natural weathering processes. As a result of this the qualities of the boreholes and dug well water samples were therefore not suitable for human consumption without adequate treatment. Regular monitoring of groundwater quality, abolishing unhealthy waste disposal practices, and introducing modern techniques are recommended.

Identification of aging fingerprint of base asphalt by ATR-FTIR combined with chemometrics

In this work, attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) combined with chemometric analysis was used to classify and characterise aged asphalt. The full spectra of asphalt samples with 5 types at 6 aging states (30 samples) were determined using ATR-FTIR and the data matrix of the full spectra was analysed chemometrically. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) outcomes demonstrate that the asphalts of five oil sources are divided into three major categories. The samples of asphalt prior to and following aging with comparable oil sources are still grouped into one category. With up to 100% accuracy, one can discriminate between the asphalt samples from these three oil sources using Fisher's discriminant function based on PCA and HCA cluster analysis.This indicates that the aging characteristics of asphalt depend on the oil source, and the "genetic framework" of asphalt will not change with aging.

Assessment of Popcorn's Bioactive Status in Response to Popping.

Popcorn is a specialty maize variety with popping abilities. Although considered a snack, popcorn flakes provide a variety of benefits for the human diet. To evaluate the change in content of bioactive compounds in response to microwave popping, the kernels and flakes of twelve popcorn hybrids were assayed. Accordingly, the content of phytic acid, glutathione, phenolic compounds, carotenoids, and tocopherols, as well as the antioxidant activity, were evaluated. In all evaluated popcorn hybrids, the most pronounced significant average decrease of 71.94% was observed for GSH content, followed by 57.72% and 16.12% decreases for lutein + zeaxanthin and phytic acid content, respectively. In response to popping, in the majority of the evaluated hybrids, the most pronounced significant average changes of a 63.42% increase and a 27.61% decrease were observed for DPPH, followed by a 51.52% increase and a 24.48% decrease for β-carotene, as well as, a 48.62% increase and a 16.71% decrease for α-Tocopherol content, respectively. The applied principal component and hierarchical cluster analyses revealed the distinct separation of popcorn hybrids' kernels and flakes, indicating the existence of a unique linkage of changes in bioactive compound content in response to popping.

Sustainable and healthy food consumption in Europe: an analysis of consumer purchase patterns, motivations and barriers towards foods from SFSCs

PurposeThe aim of this paper is to better understand European consumers' behaviour in relation to Short Food Supply Chains (SFSCs), so as to provide insights to support their development as part of a sustainable food system. Specifically, it aims to analyse consumer purchase patterns, motivations and perceived barriers and to identify patterns of behaviour amongst different consumer groups.Design/methodology/approachAn online consumer survey was conducted in 12 European countries (n = 2,419). Quantitative data analysis, including principal component analysis (PCA) and cluster analysis, was undertaken using SPSS.FindingsFour consumer clusters are named according to their behavioural stage in terms of SFSC engagement: Unaware Unengaged, Aware Unengaged, Motivationally Engaged and Executively Engaged. Unaware Unengaged and Aware Unengaged are in the non-engagement phase of behaviour. Motivationally Engaged are motivationally activated to engage in the behaviour but fail to do so consistently. Executively Engaged is the fully engaged cluster, being motivated to act and purchasing local food on a frequent basis. The results show an interesting interplay between motivations and barriers, i.e. higher scores for motivations and lower scores for barriers do not necessarily translate into higher purchase frequency.Originality/valueThe research gleans insights into the contextual factors that may inhibit SFSC purchases in different consumer segments. It offers practical implications for policymakers and others seeking to develop SFSCs as part of a sustainable food system.

Bioinformatic Analysis of Codon Usage Bias of HSP20 Genes in Four Cruciferous Species.

Heat shock protein 20 (HSP20) serves as a chaperone and plays roles in numerous biological processes, but the codon usage bias (CUB) of its genes has remained unexplored. This study identified 140 HSP20 genes from four cruciferous species, Arabidopsis thaliana, Brassica napus, Brassica rapa, and Camelina sativa, that were identified from the Ensembl plants database, and we subsequently investigated their CUB. As a result, the base composition analysis revealed that the overall GC content of HSP20 genes was below 50%. The overall GC content significantly correlated with the constituents at three codon positions, implying that both mutation pressure and natural selection might contribute to the CUB. The relatively high ENc values suggested that the CUB of the HSP20 genes in four cruciferous species was relatively weak. Subsequently, ENc exhibited a negative correlation with gene expression levels. Analyses, including ENc-plot analysis, neutral analysis, and PR2 bias, revealed that natural selection mainly shaped the CUB patterns of HSP20 genes in these species. In addition, a total of 12 optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified across the four species. A neighbor-joining phylogenetic analysis based on coding sequences (CDS) showed that the 140 HSP20 genes were strictly and distinctly clustered into 12 subfamilies. Principal component analysis and cluster analysis based on relative synonymous codon usage (RSCU) values supported the fact that the CUB pattern was consistent with the genetic relationship at the gene level and (or) species levels. These results will not only enrich the HSP20 gene resource but also advance our understanding of the CUB of HSP20 genes, which may underlie the theoretical basis for exploration of their genetic and evolutionary pattern.

Explorative study for the rapid detection of Fritillaria using gas chromatography-ion mobility spectrometry.

Fritillaria is a well-known health-promoting food, but it has many varieties and its market circulation is chaotic. In order to explore the differences in volatile organic compounds (VOCs) among different varieties of Fritillaria and quickly and accurately determine the variety of Fritillaria, this study selected six varieties of Fritillaria and identified and analyzed their volatile components using gas chromatography-ion mobility spectrometry (GC-IMS), establishing the characteristic fingerprints of VOCs in Fritillaria. In all samples, a total of 76 peaks were detected and 67 VOCs were identified. It was found that the composition of VOCs in different varieties of Fritillaria was similar, but the content was different. Combined with chemometric analysis, the differences between VOCs were clearly shown after principal component analysis, cluster analysis, and partial least-squares discriminant analysis. This may provide theoretical guidance for the identification and authenticity determination of different varieties of Fritillaria.

Transcriptomic analysis reveals the molecular basis of photoperiod-regulated sex differentiation in tropical pumpkins (Cucurbita moschata Duch.)

BackgroundPhotoperiod, or the length of the day, has a significant impact on the flowering and sex differentiation of photoperiod-sensitive crops. The “miben” pumpkin (the main type of Cucurbita moschata Duch.) is well-known for its high yield and strong disease resistance. However, its cultivation has been limited due to its sensitivity to photoperiod. This sensitivity imposes challenges on its widespread cultivation and may result in suboptimal yields in regions with specific daylength conditions. As a consequence, efforts are being made to explore potential strategies or breeding techniques to enhance its adaptability to a broader range of photoperiods, thus unlocking its full cultivation potential and further promoting its valuable traits in agriculture.ResultsThis study aimed to identify photoperiod-insensitive germplasm exhibiting no difference in sex differentiation under different day-length conditions. The investigation involved a phenotypic analysis of photoperiod-sensitive (PPS) and photoperiod-insensitive (PPIS) pumpkin materials exposed to different day lengths, including long days (LDs) and short days (SDs). The results revealed that female flower differentiation was significantly inhibited in PPS_LD, while no differences were observed in the other three groups (PPS_SD, PPIS_LD, and PPIS_SD). Transcriptome analysis was carried out for these four groups to explore the main-effect genes of sex differentiation responsive to photoperiod. The main-effect gene subclusters were identified based on the principal component and hierarchical cluster analyses. Further, functional annotations and enrichment analysis revealed significant upregulation of photoreceptors (CmCRY1, F-box/kelch-repeat protein), circadian rhythm-related genes (CmGI, CmPRR9, etc.), and CONSTANS (CO) in PPS_LD. Conversely, a significant downregulation was observed in most Nuclear Factor Y (NF-Y) transcription factors. Regarding the gibberellic acid (GA) signal transduction pathway, positive regulators of GA signaling (CmSCL3, CmSCL13, and so forth) displayed higher expression levels, while the negative regulators of GA signaling, CmGAI, exhibited lower expression levels in PPS_LD. Notably, this effect was not observed in the synthetic pathway genes. Furthermore, genes associated with ethylene synthesis and signal transduction (CmACO3, CmACO1, CmERF118, CmERF118-like1,2, CmWIN1-like, and CmRAP2-7-like) showed significant downregulation.ConclusionsThis study offered a crucial theoretical and genetic basis for understanding how photoperiod influences the mechanism of female flower differentiation in pumpkins.