Purity Index Research Articles

Optimization of the DNA isolation procedure for assessing the genetic diversity of essential oil roses (Rosa L.)

Background. High content of organic compounds that worsen nucleic acid purification in aromatic plants, as well as the use of such toxic substances as phenol and mercaptoethanol in many protocols for plant DNA isolation, make it advisable to take the above disadvantages into account when optimizing the DNA extraction technique for the work with essential oil rose plants. Material and methods. Rose accessions from the Crimean Federal University’s Botanical Garden, and those from the collection held by the Research Institute of Agriculture of Crimea were included in the study. DNA extraction was done according to a modified CTAB protocol. Effectiveness of the technique was assessed using spectrophotometry, horizontal electrophoresis, and ISSR-PCR. Results. DNA preparations extracted with the modified technique were well visualized on the electropherogram and demonstrated high spectrophotometric values. DNA content was twice as high in preparations isolated with an extraction buffer with PVP, compared to a PVP-free buffer. The concentration was also higher in DNA extracts from stems than that from leaves. Purity parameters expressed by the absorption ratios at wavelengths A260/280 and A260/230 were again higher for DNA extracts from stems isolated with an enriched buffer, the A260/230 ratio falling within the normal range only in DNA extracted from stems in the presence of PVP. Besides, DNA extracts were effectively purified from proteins without phenol or mercaptoethanol, due to double rinsing with a chloroform/isoamyl alcohol (24 : 1) mixture. Conclusion. Using rose stem tissues as the research material, adding 2% PVP to the extraction buffer, and twofold rinsing with a chloroform/isoamyl alcohol mixture made it possible to obtain DNA extracts with high concentrations and purity indices within normal ranges suitable for the ISSR analysis of essential oil rose genetic diversity.

Hyperspectral endmember extraction using convexity based purity index

The endmember extraction is a challenging problem in spectral unmixing (SU) of a mixed pixel in hyperspectral imagery. There are plenty of attempts to solve the endmember extraction problem. Still, the pure pixel assumption-based algorithms have probably been used most in solving the endmember extraction of SU due to the light computational burden. These pure pixel assumption-based algorithms usually follow one of the criteria: (1) Maximum simplex volume or (2) Extreme projection on a subspace. We propose a novel integrated framework that uses both the criteria mentioned above and the proposed one is referred to as the Convexity-based Pure Index (CPI) algorithm. The CPI generates a fixed number of convex sets based on the number of available bands in the hyperspectral image. The algorithm defines the purity score based on the availability of pixels in the convex sets for the two-band data. The CPI has been compared with contemporary algorithms such as Automatic Target Generation Process (ATGP), Vertex Component Analysis (VCA), Pixel Purity Index (PPI), Successive Volume MAXimization (SVMAX), Alternating Volume MAXimization (AVMAX), TRIple-P: P-norm based Pure Pixel identification (TRIP), Successive Decoupled Volume Max–Min (SDVMM), Negative ABundance-Oriented (NABO), and Entropy-based Convex Set Optimization (ECSO). The metrics, Spectral Angle Distance (SAD) and Spectral Information Divergence (SID) used in the comparison were improved up to 5.9% and 9%, respectively. The CPI outperforms prevailing algorithms on real benchmark data and new AVIRIS-NG data. The robustness of the CPI is also tested for various noisy synthetic data. The efficacy of the proposed algorithm is also tested by using qualitative analysis by visualizing the spectra comparison, and abundance maps for all real data.

PoLambRimetry: a multispectral polarimetric atlas of lamb brain.

Mueller matrix imaging (MMI) is a comprehensive form of polarization imaging useful for assessing structural changes. However, there is limited literature on the polarimetric properties of brain specimens, especially with multispectral analysis. We aim to employ multispectral MMI for an exhaustive polarimetric analysis of brain structures, providing a reference dataset for future studies and enhancing the understanding of brain anatomy for clinicians and researchers. A multispectral wide-field MMI system was used to measure six fresh lamb brain specimens. Multiple decomposition methods (forward polar, symmetric, and differential) and polarization invariants (indices of polarimetric purity and anisotropy coefficients) have been calculated to obtain a complete polarimetric description of the samples. A total of 16 labels based on major brain structures, including grey matter (GM) and white matter (WM), were identified. -nearest neighbors classification was used to distinguish between GM and WM and validate the feasibility of MMI for WM identification. As the wavelength increases, both depolarization and retardance increase, suggesting enhanced tissue penetration into deeper layers. Moreover, utilizing multiple wavelengths allowed us to track dynamic shifts in the optical axis of retardance within the brain tissue, providing insights into morphological changes in WM beneath the cortical surface. The use of multispectral data for classification outperformed all results obtained with single-wavelength data and provided over 95% accuracy for the test dataset. The consistency of these observations highlights the potential of multispectral wide-field MMI as a non-invasive and effective technique for investigating the brain's architecture.

Optimization of phycobiliprotein biosynthesis in thermotolerant cyanobacteria through light parameter adjustment

This study addressed the optimization of biomass and C-phycocyanin (C-PC) concentration and its purity in the thermotolerant cyanobacterium Potamosiphon sp by adjusting key light quality parameters. Custom design and Central Composite Design experimental designs were employed, using LEDs light intensity, wavelength, and photoperiod. The results demonstrated that these lighting parameters significantly influence biomass and C-phycocyanin production, achieving up to a 100 % increase in phycocyanin accumulation and biomass production and a 50 % improvement in purity index compared to conventional white light under optimal conditions of Red:Blue light (3:1), Intensity (283 μmol m−2 s−1), and photoperiod (17.8 H light). The findings support the use of specific LEDs wavelengths that optimize the performance of production processes and the quality of products derived from cyanobacteria, such as high-value phycobiliproteins.

Synthesis and properties of naphthylamine derivative functionalized spiro-[fluorene-9,9′-xanthene] for single-component white light-emitting diodes

White light-emitting diodes (LEDs) with high color purity and color-rendering index have elicited much interest in many fields. In this work, a spirotype molecule SFX-PNA was designed and synthesized by combining a spiro[fluorene-9,9′-xanthene] (SFX) core with naphthylamine derivative functionalized at the 2,3′,6′,7-positions. Studies revealed that the highly twisted configuration allowed SFX-PNA to exhibit good thermal stability and a broad blue-emissive band (λem = 466 nm) in the solid state. In combination with the intrinsic yellow luminescence (λem = 556 nm) of commercially available GaN ultraviolet LED chips, a white LED with SFX-PNA as the phosphor was successfully obtained, which showed high color purity with Commission Internationale de L’Éclairage coordinates of (0.30, 0.33) and a color-rendering index of 86.

The use of real-time polymerase chain reaction for detection of raw rat meat (Rattus norvegicus) with species-specific primer for halal authentication

Rat meat (RM) can be obtained freely from farmers and can be used as a potential adulterant in meat-based food products. The presence of RM in any food products is prohibited by the Muslim community and is considered non-halal meat. Therefore, an analytical method capable of analysing RM specifically is very urgent. In this study, a real -time polymerase chain reaction using a species-specific primer targeting NADH dehydrogenase subunit 6 (ND6) is applied to analyze RM. DNA extraction was carried out using FavorPrepTM Tissue Genomic DNA Extraction Mini Kit, and the extracted DNA was subjected to purity index using NANO-Quant SPARK TECAN. The annealing temperature (Ta) used for PCR analysis was optimized to get the best Ta capable of providing the optimum amplification reaction. Furthermore, some performance characteristics were evaluated for Real-Time PCR, including sensitivity, efficiency and repeatability. The results exhibited that the designed primer is specific to rat DNA extracted toward other DNAs from meats typically used in food products. For quantitative evaluation, the limit of detection found was 0.39 ng with an efficiency of amplification (E) of 94.4% with a coefficient of determination (R2 ) of 0.986 for the relationship between log concentrations of DNA and cycle threshold (Ct) values. The repeatability assay was acceptable with an RSD value ≤ 25%. The developed method was reliable, provided high sensitivity for the analysis of RM. Therefore, this method is suitable to be used as a standard method for halal authentication analysis.

Development of an efficient process to extract C‐phycocyanin from marine cyanobacterial strains and evaluation of its bioactive potential

AbstractBACKGROUNDPhycocyanin (PC), a natural blue photosynthetic pigment found in cyanobacteria, rhodophyta and cryptophyta has numerous applications in biotechnology and the food industry. The phycocyanin extraction method has a significant impact on its bioactivities, purity index, cost and potential applications; thus, the development of an efficient extraction strategy continues to be a primary research goal.RESULTSThis study evaluated the efficacy of different methods for the extraction of cyanobacterial phycocyanin (C‐PC) from three marine cyanobacterial isolates, namely Arthrospira platensis, Phormidium sp. and Pseudoscillatoria sp. wet biomass. The pretreatment step of soaking biomass in extraction buffer for 60 min, followed by a combination of freeze–thaw (one cycle; 2 h) and sonication (2 min) treatment was found to be the most effective extraction strategy, producing the highest C‐PC yield (16.19 ± 0.34%, 15.89 ± 0.61% and 15.56 ± 0.69% dry cell weight for strains A. platensis, Phormidium sp. and Pseudoscillatoria sp., respectively). Furthermore, a biomass‐to‐solvent ratio of 0.02 g mL−1 was optimal to attain food‐grade purity ((A620/A280) ≥ 0.7). Bioactivity evaluation of crude and purified C‐PC exhibited its potential as antioxidant compounds and as an antimicrobial agent with significant inhibitory effects against various pathogenic microorganisms.CONCLUSIONThe study proposed an efficient and cost‐effective C‐PC extraction process for cyanobacteria and highlighted the potential of C‐PC as a valuable bioactive compound with various applications. © 2024 Society of Chemical Industry (SCI).

Single-step extraction/pre-formulation process for B-phycoerythrin using glycerol-based eutectic solvents: A step toward more sustainable production of phycobiliproteins

B-Phycoerythrin (B-PE) is a protein pigment of significant interest to the food and cosmetic industries. B-PE is obtained from algal or microalgal biomass, such as Porphyridium cruentum, after complex pre-treatment, extraction, and pre-formulation schemes. This work investigated the use of a single step process for the extraction and pre-formulation of B-PE from P. cruentum without complex biomass pretreatment. Five hydrophilic NaDES based on glycerol with varying water contents (20–40%) were implemented by ultrasound-assisted extraction using a one-step extraction procedure. The yields obtained were satisfaying, ranging from 5 to 15 mg of B-PE per gram of dry matter. Additionally, a purity index suitable for use in cosmetics and food products was achieved, with an average of >1.5. Furthermore, the extracts obtained in a eutectic medium demonstrated enhanced stability for B-PE, with an average loss of 10% after accelerated aging, allowing storage at room temperature without loss of quality. In particular, NaDES based on glycerol and glucose and/or betaine appeared to be the most effective in preserving the integrity and antioxidant activity of B-PE, with a range of 15–30% quenched DPPH. The ComplexGAPI tool demonstrated that our single-step NaDES process is more environmentally friendly than conventional extraction processes, thanks to lower energy consumption, reduced unitary operations, and less waste production. These results provide a solid foundation for sustainable management of the valorization of P-BE for cosmetic or food industries.

SUnSeT: spectral unmixing of hyperspectral images for phenotyping soybean seed traits

Key messageHyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes.Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this necessity. In a validation test involving 420 seed accessions from the Korean Soybean Core Collections, the pixel purity index algorithm identified seed- specific hyperspectral endmembers to facilitate segmentation. Various metrics extracted from ventral and lateral side images facilitated the categorization of seeds into three size groups and four shape groups. Additionally, quantitative RGB triplets representing seven seed coat colors, averaged reflectance spectra, and pigment indices were acquired. Machine learning models, trained on a dataset comprising 420 accession seeds and 199 predictors encompassing seed size, shape, and reflectance spectra, achieved accuracy rates of 95.8% for linear discriminant analysis model. Furthermore, a genome-wide association study utilizing hyperspectral features uncovered associations between seed traits and genes governing seed pigmentation and shapes. This comprehensive approach underscores the effectiveness of SUnSet in advancing precision agriculture through meticulous seed trait analysis.

Assessing Tunisia's urban air quality using combined lichens and Sentinel-5 satellite integration.

In Tunisia, urban air pollution is becoming a bigger problem. This study used a combined strategy of biomonitoring with lichens and satellite mapping with Sentinel-5 satellite data processed in Google Earth Engine (GEE) to assess the air quality over metropolitan Tunis. Lichen diversity was surveyed across the green spaces of the Faculty of Science of Tunisia sites, revealing 15 species with a predominance of pollution-tolerant genera. The Index of Atmospheric Purity (IAP) calculated from the lichen data indicated poor air quality. Spatial patterns of pollutants sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), carbon monoxide (CO), and aerosol index across Greater Tunis were analyzed from Sentinel-5 datasets on the GEE platform. The higher values of these indices in the research area indicate that it may be impacted by industrial activity and highlight the considerable role that vehicle traffic plays in air pollution. The results of the IAP, IBL, and the combined ground-based biomonitoring and satellite mapping techniques confirm poor air quality and an environment affected by atmospheric pollutants which will enable proactive air quality management strategies to be put in place in Tunisia's rapidly expanding cities.

Development of an electroanalytical methodology for the identification and quantification of cocaine in samples seized using a carbon paste electrode modified with multi-walled carbon nanotubes

Among the drugs of abuse, cocaine (COC) is the second most commonly used worldwide due to its stimulating and psychoactive effects. Currently, this drug is classified, according to the World Drug Report (WDR), as an illicit substance and is frequently seized by law enforcement agencies. Additionally, it can cause social problems due to its abusive use. This study describes the development of an electroanalytical methodology using square wave voltammetry (SWV) associated with a single electrode of carbon paste modified with 10 % MWCNTs (multi-walled carbon nanotubes) to quantify COC in seized samples containing up to 20% cocaine (low purity index) in the state of Espírito Santo (Brazil). SWV parameters, including Es = 10 mV, a = 30 mV, and f = 15 Hz, were optimized utilizing a Britton-Robinson buffer solution of 0.1 mol/L (pH 10) as a supporting electrolyte through the implementation of experimental design (CCD). COC showed an oxidation peak at approximately 1.0 V, with low limits of quantification and detection (1.90 × 10−6 mol L−1 and 5.75 × 10−7 mol L−1, respectively), in the linear range from 2.36 × 10−6 mol L−1 to 1.38 × 10−5 mol L−1, with the proposed methodology. Thus, this research develops a fast and low-cost technique in favor of the police, allowing the R2 = 99%. The results obtained in the intraday calibration curves present a relatively low standard deviation (RSD < 8%), indicating a good repetition of the value production of an electrode for less than USD 1.42 per analysis.

Quantitative Analysis of Swertiamarin Content from Fagraea fragrans Leaf Extract using HPLC Technique and its Correlation to Antibacterial Activity

The rise in drug resistance poses escalating challenges for antibacterial medications, leading to an urgent demand for the exploration and innovation of new antibacterial drugs. Fagraea fragrans Roxb., belonging to the Gentianaceae family, is one of the common herbal medicines which can be found abundantly in Southeast Asia. The secoiridoid glucoside swertiamarin, one of the major compounds in F. fragrans leaf, exhibits antimicrobial effects. To guarantee the medicinal effectiveness of F. fragrans leaves, it is essential to identify a standardized analytical method for quantifying the active compound. In this study, the optimized HPLC method following ICH guideline was validated for the quantitative analysis of swertiamarin content in F. fragrans leaf in terms of linearity (y = 5733.5x - 369.1; R2 = 0.9999), accuracy (93.57-96.39% recovery), precision (0.91% RSD for repeatability precision; 1.19% RSD for intermediate precision), limit of detection (0.73 µg/mL), limit of quantitation (2.23 µg/mL), specificity (peak purity index = 0.999995) and robustness (% RSD &lt;1).The maximum wavelength of swertiamarin was found to be at 238 nm. The amount of swertiamarin content in F. fragrans leaf extract conducted from the validated HPLC method was found to be 0.0259 ± 0.0005 g/100 g crude drug. The leaf extract exhibited antimicrobial activity against clinical isolates of Enterobacter cloacae, Klebsiella pneumonia, and Escherichia coli at 0.125 mg/mL, and Pseudomonas aeruginosa at 0.5, showing minimum inhibitory concentration (MIC) values. Whereas swertiamarin exhibited even lower MIC values. The developed HPLC analysis effectively determines swertiamarin content as a chemical marker to ensure the antimicrobial potential of F. fragrans leaves.

Shadow Detection in Remote Sensing Images Based on Spectral Radiance Separability Enhancement.

Shadow detection is a basic task of remote sensing image analysis, but it is often seriously disturbed by vegetation, water bodies, and black objects. It is observed that vegetation and dark objects often show a dark look in visible bands but brighter in the near-infrared (NIR), and is also noticed that the reflection of inland water bodies in the green band is stronger than that in the blue band. Taking advantage of these physical properties and combining them with the bluish and dark appearance of shadows, we propose a simple but effective shadow detection method for multispectral remote sensing images. These physical properties are used to create transformation models that suppress features such as vegetation, water bodies, etc., but at the same time enhance shadows. Then, we transform the shadow representation into a color space to generate candidate shadows using dominant color components. To separate shadows from the others, we propose two indexes, the normalized Color Difference Composite Index (CDCI) and Color Purity Index (CPI), and fuse them to achieve shadows and their confidence. The experimental results indicate that the proposed method can effectively detect the shadows in multispectral images and outperforms the state-of-the-art approaches.

Abstract 7417: SpatialCS: A tool to effectively integrate histological annotations and spatial transcriptomics analysis

Abstract Spatial transcriptomics is revolutionizing our understanding of tumor ecosystems, providing insights into the spatial dimensions of cell locations, their organization, and interactions within tissues. A key challenge in this field is integrating histological annotations with spatial domains identified through unsupervised clustering methods like SpaGCN. This integration is crucial for accurate spatial domain identification and further analyses. However, clustering results often vary based on parameters such as resolution, leading to inconsistencies with histological annotations. This variation necessitates optimized parameter selection to achieve the best clustering outcomes. We here introduce SpatialCS, a novel tool specifically designed to both visualize and quantify the alignment between histological annotations and the clustering results obtained from spatial transcriptomics data. SpatialCS employs a new index based on the asymmetric Wallace indices. This index penalizes spot pairs that are clustered together but do not share the same histology annotation type, with penalties scaled according to their transcriptional similarity. Additionally, we propose a purity index, derived by calculating the average transcriptional entropy of all clusters. This index serves as a measure of the homogeneity within each cluster. Furthermore, SpatialCS includes a unique visualization function. This function projects histological annotations onto the clustering results as outlines, making it easier to assess the consistency between histology annotations and clustering outcomes. We have applied SpatialCS to Visium spatial transcriptomics data generated on four colorectal cancer liver metastases, each accompanied by comprehensive spot-level histological annotations in both tumor and normal compartments. The histologic annotations include but not limited to are tumor cells, tumor cell cluster subtypes, tumor stroma, tumor in the vessels, portal tract, individual bile ducts, portal vein and liver cell plates and non-neoplastic stroma. The application of SpatialCS has proven its effectiveness in identifying the most consistent clustering results, which were further confirmed by experienced pathologists. Notably, the output of SpatialCS offers helpful guidance for improving histological annotations. Together, SpatialCS not only provides a quantitative approach to evaluate the consistency between histological annotations and unsupervised clustering analysis but also showcases its potential to significantly enhance histological annotations. Citation Format: Yanshuo Chu, Kyung Serk Cho, Isha Khanduri, Tieling Zhou, Jiahui Jiang, Yunhe Liu, Xinmiao Yan, Guangsheng Pei, Yibo Dai, Yang Liu, Ruiping Wang, Akshaya S Jadhav, Sharia Hernandez, Humam Kadara, Luisa Maren Solis Soto, Scott Kopetz, Dipen Maheshbhai Maru, Linghua Wang. SpatialCS: A tool to effectively integrate histological annotations and spatial transcriptomics analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7417.

Development and Validation of a New Reversed Phase HPLC Method for the Quantitation of Azithromycin and Rifampicin in a Capsule Formulation.

This research aimed to develop a new method for simultaneously estimating the presence of azithromycin (AZT) and rifampicin (RIF) in a capsule formulation using reverse-phase high-performance liquid chromatography. The developed method utilized a Gemini column with a 60:40% v/v acetonitrile and potassium dihydrogen phosphate mobile phase, a flow rate of 1mL/min, and an injection volume of 20μL. The detection wavelengths of 210 and 254nm for AZT and RIF, respectively, were used. Validation ensures specificity with a peak purity index > 0.99999 for AZT and >0.99995 for RIF, affirming unambiguous analyte detection. The system suitability test, within acceptable limits, validates method reliability. Linearity calibration curves (R2 = 0.998) cover a 25-150% target concentration range. Accuracy studies employing the standard addition method yield recovery values between 96.6 and 103.9% for both drugs, confirming method accuracy. Precision studies reveal % relative standard deviation values consistently below 2%, highlighting reproducibility. Robustness testing supports method reliability under varying conditions. Application to a pharmaceutical capsule formulation demonstrates the method's practicality, accurately quantifying AZT (98.30%) and RIF (99.37%). This study provides a validated analytical approach for simultaneous quantification in commercial pharmaceutical products containing both drugs, enhancing pharmaceutical quality control for critical antibiotics in complex formulations.

Physicochemical Characterization of ‘Moroccan Picholine’ Olive (Olea europaea L.) Oil Produced in Southern Morocco Using Multivariate Statistical Analysis

This study focuses on evaluating the characteristics of olive oil produced in the Taroudant province (southern Morocco), making this the first comprehensive study focusing on olive oil from the ‘Moroccan Picholine’ cultivar. Our objective was to elucidate the distinctive qualities of olive oil from this region, providing valuable insights into its potential contributions to the country’s olive oil sector. For this purpose, several quality criteria (free fatty acids, moisture content, saponification value, and iodine value), oxidation indices (peroxide value, specific UV extinction coefficients, and oxidizability value), and purity indices (fatty acids and sterol composition) were evaluated. Our results reveal minor-to-significant variations (p &lt; 0.05) in the quality and oxidation parameters. Specifically, our results indicate diverse ranges for free fatty acids (0.33–3.62 g/100 g), peroxide values (0.85–4.01 mEq O2/kg oil), K232 (1.68 to 2.73), and K270 (0.09–0.34). Furthermore, consistently high levels of oleic acid (55.8 to 73.1%) and β-sitosterol (94.2 to 97%) were observed in the studied samples. These outcomes were confirmed through the use principal component analysis and hierarchical cluster analysis. Likewise, important correlations were outlined among the studied parameters. Multidimensional analyses not only highlight inherent variations, but also facilitate the classification of the analyzed olive oils into distinct categories. The results suggest that the Taroudant province exhibits favorable conditions for producing high-quality olive oil.

MCMSTStream: applying minimum spanning tree to KD-tree-based micro-clusters to define arbitrary-shaped clusters in streaming data

Stream clustering has emerged as a vital area for processing streaming data in real-time, facilitating the extraction of meaningful information. While efficient approaches for defining and updating clusters based on similarity criteria have been proposed, outliers and noisy data within stream clustering areas pose a significant threat to the overall performance of clustering algorithms. Moreover, the limitation of existing methods in generating non-spherical clusters underscores the need for improved clustering quality. As a new methodology, we propose a new stream clustering approach, MCMSTStream, to overcome the abovementioned challenges. The algorithm applies MST to micro-clusters defined by using the KD-Tree data structure to define macro-clusters. MCMSTStream is robust against outliers and noisy data and has the ability to define clusters with arbitrary shapes. Furthermore, the proposed algorithm exhibits notable speed and can handling high-dimensional data. ARI and Purity indices are used to prove the clustering success of the MCMSTStream. The evaluation results reveal the superior performance of MCMSTStream compared to state-of-the-art stream clustering algorithms such as DenStream, DBSTREAM, and KD-AR Stream. The proposed method obtained a Purity value of 0.9780 and an ARI value of 0.7509, the highest scores for the KDD dataset. In the other 11 datasets, it obtained much higher results than its competitors. As a result, the proposed method is an effective stream clustering algorithm on datasets with outliers, high-dimensional, and arbitrary-shaped clusters. In addition, its runtime performance is also quite reasonable.

Extraction of Phycocyanin and Chlorophyll from Spirulina by “Green Methods”

Phycocyanin is a pigment–protein complex from the group of phycobiliproteins obtained from Spirulina (Arthrospira platensis), with possibilities for various applications in food and pharmaceutical technologies. It is a natural colorant for food and cosmetic products. This study aimed to investigate the effect of ultrasonic and microwave extraction conditions on antioxidant activity (AOA), chlorophyll content, and the content and purity index of phycocyanin in aqueous and alcoholic extracts of Spirulina (Arthrospira platensis). For this purpose, ultrasonic extraction with water or ethanol was performed at 20 °C, 30 °C, and 40 °C for 1, 2, and 3 h at an ultrasonic frequency of 36 kHz, 40 kHz, and 45 kHz. Microwave water extraction was performed for 60 s, 120 s, and 180 s. For each of the obtained samples, three parallel measurements of antioxidant activity were made by DPPH and FRAP methods, and chlorophyll content and phycocyanin yield and purity index were determined spectrophotometrically. Ultrasonic extraction resulted in a higher yield and purity index of phycocyanin compared to microwave extraction. The highest yield of 14.88 mg g−1 with a purity index of 1.60 was achieved at a temperature of 40 °C for one hour and an ultrasonic wave frequency of 40 kHz. A relatively low yield of 4.21 mg g−1, but with a purity index of 2.67, was obtained at a temperature of 30 °C, a time of two hours, and an ultrasonic frequency of 40 kHz. Chlorophyll b content at 20 °C, for two hours and ultrasonic frequency 40 kHz was 1.400 mg g−1. The study proposes ultrasonic extraction as a green method to obtain phycocyanin of varying purity index that may be used for food, cosmetic, or biomedical purposes.

True hybridity analysis using genome-wide hypervariable SSR markers in pomegranate

A total of 25 SSR primers were screened on 37 putative F1s derived from the five different crosses. Identified cross specific highly informative SSRs primers, i.e., 14 for the first cross, 10 for the second, 12 for the third and 6 each for fourth and fifth crosses. For the first cross Bhagwa × Daru 17, four primers (HvSSRT_375, NRCP_SSR9, NRCP_SSR12 and NRCP_SSR92) were found to be highly informative with higher 100% hybrid purity index (HPI), PIC (~0.52), and observed heterozygosity (Ho, range 0.87–0.93) values, and two F1s namely H1 and H2 were found to be highly heterotic with a heterozygosity index (HI) of 92.85%. Similarly, for Bhagwa × Nana, three primers (HvSSRT_375, HvSSRT_605 and NRCP_SSR19) had higher HPI (70%–100%), PIC (0.52–0.69), and Ho (0.75–0.33) values, and three F1s H1, H2, and H4 had 70% (HI). For Bhagwa × IC318712, four SSRs (HvSSRT_254, HvSSRT_348, HvSSRT_826 and NRCP_SSR95) had higher Ho (~0.83), HPI (100%) and PIC (~0.52) values, and four F1s H2, H7, H9, and H10 showed 91.66% (HI). For Bhagwa × Nayana, HvSSRT_605, HvSSRT_826, and HvSSRT_432, and for Ganesh × Nayana, HVSSRT_375, HVSSRT_605, and HvSSRT_826 were found informative. These markers will be highly useful in developing maps of populations.

Granite Exposure Mapping Through Sentinel‐2 Visible and Short Wave Infrared Bands

AbstractNonmetallic minerals like granite and limestone have calcite and biotitic ingredients as their major part which exhibit wonderful absorption features in the visible and short wave range of the electromagnetic spectrum. This research puts emphasis on delineating granite and limestone deposits of the Mardan district through the latest multispectral Landsat‐9 and Sentinel‐2 sensors of which the latter provided 94% mapping accuracy in delineating granites (biotitic bearing minerals) and limestone (calcite‐bearing minerals). The Image processing techniques of minimum noise fraction, which is double cascaded principal components analysis and pixel purity index algorithms proved helpful to bring significant improvements in classification results and in the reduction of noise and data size. The outcomes of the research study show that supervised machine learning algorithms are impactful to map such minerals provided that the data must be well organized and limited in size. The results achieved were verified through validation steps like, (a) Independent reference data of high‐resolution Google Earth maps and (b) Ground survey reports. Arc GIS 10.2 and Envi 5.3 software suite were used to create (a) ground truth points at random for accuracy assessment (b) portraying study area maps (c) Image Processing and Preprocessing tools and (d) implementation of machine learning algorithms. Access to the data and software suite is being provided for open research work.