Variation In Content Research Articles

Variation in Phenolic Content, Antioxidant Activity and Alpha-amylase and Acetylcholinesterase Inhibitory Capacities of Different Extracts from Tunisian Satureja barceloi (Willk) L.

The antioxidant activity and the anti-α-amylase and anti-acetylcholinesterase capacities of secondary metabolites from different organs (roots, stems, leaves and flowers) of Tunisian Satureja barceloi were determined. The variation in the distribution of phenolic metabolites among roots, stems, leaves and flowers extracts of S. barceloi with various solvent systems (methanol, ethyl acetate, hexane and distilled water) has not been characterized before. Significant variation of phenolic compounds was observed according to organs rather than to extracting solvents. The analyzed organs show a high level of phenolic compounds although the stems contains the highest total polyphenols (132.53±0.48 mg AGE/g Ex), flavonoids (48.99±0.65 mg RE/g Ex) and flavonols (34.93±0.29 mg QE/g Ex) contents. The phenolic fraction was dominated by sagerinic acid, caffeic acid glucoside and epigallocatechin, detected using HPLC-PDA/ESI-MS. The antioxidant activity of all extracts, evaluated by four in vitro tests, was high and varied significantly according to the type of solvent used and the plant organ. The aqueous extracts of leaves exhibited the greatest inhibitory effect on alpha-amylase while the methanolic extract of leaves and stems revealed the most important acetylcholinesterase inhibitory effect. Hence, S. barceloi extracts could be used as a source of various bioactive molecules in pharmaceutical industry.

Patient information leaflets and package inserts of ibuprofen provided in the UK and Thailand: a comparative assessment.

Written medicine information (WMI) is important for ensuring patients understand and use their medicines optimally, but relatively little research has assessed the quality of available WMI. This study assessed the quality of WMI using a sample of leaflets for ibuprofen in the UK and Thailand. Leaflets were obtained by purchasing a product from retail outlets or community pharmacies, 18 from each country. In the UK, these were patient information leaflets (PILs); in Thailand, they were package inserts PIs not specifically designed for patients. Leaflets were assessed for content, layout, and readability using standard methods and compared to relevant guidelines. The UK PILs were uniform and conformed to EU regulatory requirements for content, whereas Thai PIs varied considerably, many failing to include important information required by Thai regulations. Several forms of Thai PIs were found, including some very short leaflets, containing minimal information. The readability of both was rated as poor, all used small font size and had less than desirable white space. Fewer Thai PIs than UK PILs met the Keystone Criteria for ibuprofen. The extent of variation in format and content of Thai WMI could potentially cause confusion and reduce willingness to read it. PILs, conforming to Thai regulatory guidelines, should be provided with medicines instead. Leaflets in both countries would benefit from improved readability and layout.

Effect of different light intensities on agronomic characteristics and antioxidant compounds of Brassicaceae microgreens in a vertical farm system

Microgreens are vegetable or edible herb shoots harvested in the early stages of development. They have an important number of bioactive compounds and add color, texture, and flavor to dishes and salads. Given their benefits, small size, and high market prices, they can grow in indoor systems, where light is determinant. This study aimed to evaluate the effect of different light intensities on agronomic characteristics, color, chlorophylls and carotenoids content, and antioxidant activity represented by total phenolic content (TPC), eliminate, and antioxidant capacity (AC) in four Brassicaceae species in two colors (green and red). The experiment was conducted in a controlled light-emitting diode (LED) environment growth chamber (day/night temperatures of 25/20 ± 1.2°C, 16 h photoperiod, and 79 ± 2% relative humidity). Three light intensities were used for microgreen growth with the same LED light spectrum: low (120 ± 5.1 μmol m−2 s−1), medium (160 ± 3.6 μmol m−2 s−1), and high (210 ± 5.9 μmol m−2 s−1). Eight g of the seeds of green and red cultivars of cabbage, kale, mizuna, and mustard were sown in a plastic tray (64 cm x 35 cm x 6 cm) with a mixture of peat and perlite (1:2 = v: v). Overall, the high intensity increased dry matter percentage and dry weight, except in green and red kale and green cabbage cultivars. In contrast, low intensity promoted a larger hypocotyl in all species than with high intensity; moreover, it enhanced the cotyledon area in green and red mizuna. Cabbage, kale, and mustard green cultivars were greener under medium intensity, whereas the low intensity enhanced the purple color of mizuna. In addition, chlorophyll a and b increased under low intensity in most species except the red kale and mustard cultivars. The high intensity raises the antioxidant activity, promoting a higher TPC and AC. The findings revealed that the light intensity generated variations in agronomic characteristics, color, chlorophyll content, and antioxidant activity of Brassicaceae microgreens, and the changes were based on the specific species and cultivars.

Variation and Correlation among Fine Root Traits of Desert Plants in Arid Areas of Northwest China

Variation and Correlation among Fine Root Traits of Desert Plants in Arid Areas of Northwest China

Zinc-protoporphyrin formation in nitrite-free Parma Ham and its relationship with intrinsic parameters and red color profile of processed hams

A total of 134 fresh hams, assayed for Ferrochelatase (FeCH) activity and ultimate pH (pH48), were processed in compliance with the procedures established for PDO Parma ham and finally, analyzed for salt, moisture, Zinc Protoporphyrin IX (ZnPP), heme, iron and zinc contents, and proteolysis index (PI). The variation in ZnPP content was related to the intrinsic parameters of fresh and matured hams by a Partial Least Square Regression model. The most favorable factors on the formation of ZnPP were total iron content (representative of the initial hemoprotein content), and FeCH activity, demonstrating the main role played by these raw matter-specific predictors in the long matured dry-cured hams. To a lesser extent, zinc content and pH48 were involved with a positive and negative role, respectively. Salt content and PI of matured hams showed an inhibitory and a favorable influence, respectively, toward the ZnPP formation. Principal Component Analysis showed the associations between the sensory red color profile and the physicochemical traits of matured hams. The red color intensity increased in agreement with the red-violet and red-pink hues scores. The formation of a high amount of ZnPP was associated with the increased perception of the red-violet shade, with a lower lightness (L*) and Hue angle (h°). Moisture increase contributed to the shift in color perception to red-pink, while marked progress in PI strengthened the perception of the red-brown shade. ZnPP and final heme favored the red color of matured hams, although a high concentration of these pigments increased in particular the red-violet perception.

Thermo-Hydric Study of Wood-Based Materials under Thermal Comfort Conditions.

This paper tackles the issue of moisture variation in wood-based materials, explicitly focusing on melamine-coated particleboard (hereafter referred to as melamine) and medium-density fiberboard (MDF) used in the third phase of wood industry transformation. The approach involves a comprehensive strategy for predicting moisture content variation, incorporating numerical simulation, experimental testing, and the application of artificial neural network (ANN) technology to enhance accuracy in furniture manufacturing. The developed ANN models are tailored to predict moisture content changes under specific thermal comfort conditions. Remarkably, these models demonstrate high precision, with an average error margin of only 1.40% for 8% moisture content (MC) and 2.85% for 12% MC in melamine, as well as 1.42% for 8% MC and 2.25% for 12% MC in MDF. These levels of precision surpass traditional models, emphasizing this study's novelty and practical relevance to the industrial context. The findings indicate that ANN models adapt to diverse environmental conditions, presenting a robust tool for optimizing moisture management in wood-based materials. This research contributes valuable insights for improving the reliability and efficiency of moisture content predictions in the wood industry.

Tissue-specific variations of piperine in ten populations of Piper longum L.: bioactivities and toxicological profile

P. longum L., one of the most significant species of the genus Piperaceae, is most frequently employed in Indian-Ayurvedic and other traditional medicinal-systems for treating a variety of illnesses. The alkaloid piperine, is the key phytoconstituent of the plant, primarily responsible for its’ pharmacological-impacts. The aim of the study is to analyse the intra-specific variation in piperine content among different chemotypes (PL1 to PL 30) and identify high piperine yielding chemotype (elite-chemotype) collected from 10 different geographical regions of West Bengal by validated HPTLC chromatography method. The study also focused on the pharmacological-screening to better understand the antioxidant activity of the methanol extracts of P. longum by DPPH and ABTS radical-scavenging activity and genotoxic activity by Allium cepa root tip assay. It was found that the P. longum fruit chemotypes contain high amount piperine (highest 16.362 mg/g in chemotype PL9) than the stem and leaf chemotypes. Both DPPH and ABTS antioxidant assays revealed that P. longum showed moderate radical-scavenging activity and the highest activity was found in PL9 (fruit) chemotype with IC50 values of 124.2 ±0.97\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pm 0.97$$\\end{document} and 104 ±0.78\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pm 0.78$$\\end{document} µg/ml respectively. The A. cepa root tip assay showed no such significant genotoxic-effect and change in mitotic-index. The quick, reproducible, and validated HPTLC approach offers a useful tool for determining quantitative variations of piperine among P. longum chemotypes from different geographical-regions and also according to the different tissues and choose elite genotypes with high piperine production for continued propagation and commercialization for the pharmaceutical sector. Additionally, the plant's in-vitro antioxidant property and lack of genotoxicity directly supports its’ widespread and long history of use as a medicinal and culinary plant.

Estimation model of potassium content in cotton leaves based on hyperspectral information of multileaf position

Potassium (K) is a highly mobile nutrient element that continuously adjusts its demand strategy among and within cotton leaves through redistribution. This indirectly leads to variations in the leaf potassium content (LKC, %) at different leaf positions. However, owing to the interaction between light and leaf age, leaf sensitivity at different positions to this change varies, including the reflection and absorption of the spectrum. How to selecting the optimal monitoring leaf position is an important factor in quickly and accurately evaluation of cotton LKC using spectral remote sensing technology. Therefore, this study proposes a comprehensive multileaf position estimation model based on the vertical distribution characteristics of LKC from top to bottom. This is aimed at achieving an accurate estimation of cotton LKC and optimizing the strategy for selecting the monitored leaf position. Between 2020 and 2021, we collected hyperspectral imaging data of the main stem leaves at different positions from top to bottom (Li, i=1, 2, 3, …, n), during the cotton budding, flowering, and boll setting stages. Vertical distribution characteristics, sensitivity differences, and spectral correlations of LKC at different leaf positions were investigated. Additionally, the optimal range of the dominant leaf position for monitoring was determined. Partial least squares regression (PLSR), random forest regression (RFR), support vector machine regression (SVR), and the entropy weight method (EWM) were used to establish LKC estimation models for single leaf and multileaf positions. The results showed a vertical heterogeneous distribution of cotton LKC, with LKC initially increasing and then gradually decreasing from top to bottom, and the average LKC of cotton reaches its maximum value at flowering stage. The upper leaf position demonstrated greater sensitivity to K and exhibited a stronger correlation with the spectrum. The selected dominant leaf positions for the three growth stages were L1–L5, L1–L4, and L1–L2, respectively. Based on the dominant leaf position monitoring range, the optimal single leaf position models for estimating LKC during the three growth stages were PLSR-L4, PLSR-L1, and SVR-L2, with The coefficient of determination of the validation set (R2val) of 0.786, 0.580, and 0.768, and the root-mean-square error of the validation set (RMSEval) of 0.168, 0.197, and 0.191, respectively. The multileaf position LKC estimation model was constructed by EWM with R2val of 0.887, 0.728, and 0.703, and RMSEval of 0.134, 0.172, and 0.209, respectively. In contrast, the newly developed multileaf position comprehensive estimation model yielded superior results, improving the stability of the model on the basis of high accuracy, especially during the budding and flowering stages. These findings hold significant importance for investigating cotton LKC spectral models and selecting suitable leaf positions for field monitoring.

Predictive tools for the cooling rate-dependent microstructure evolution of AISI 316L stainless steel in additive manufacturing

This study presents a thorough evaluation of advanced predictive tools for the solidification microstructure of AISI 316L stainless steel, taking into account both chemical composition and cooling rate. In order to achieve a broad range of cooling rates comparable to prominent additive manufacturing processes, autogenous laser welds were carried out on the steel plate by means of powderless directed energy deposition (DED) and selective laser melting (SLM) machines. Computational analysis of cooling rates and metallographic investigations revealed that DED welds solidify at moderate rates, exhibiting a primary ferrite (FA) solidification mode. Conversely, SLM welds solidify at significantly higher rates, showing dual solidification modes: initial austenite (A) at the fusion boundary and subsequent ferrite (F) at the interior. The WRC-1992 constitution diagram predicts the FA mode in accordance with the findings in the DED welds. An implicated Schaeffler diagram, proposed for a comparable cooling rate, also predicts the same mode. An artificial neural network model, referred to as ORFN, consistently predicts the variation of ferrite content within the DED welds based on the cooling rate variation. The dual mode observed in the SLM welds aligns with established knowledge regarding the alteration of stainless steel solidification under extremely high cooling rates. While the occurrence of the A mode at the fusion boundary is anticipated according to implicated Schaeffler diagrams for extremely high cooling rates, the transition to the F mode is not addressed explicitly.

Genome-wide association and co-expression uncovered ZmMYB71 controls kernel starch content in maize

Starch plays a crucial role as a storage component, greatly affecting the grain yield and quality of maize (Zea mays L.). To meet future demands, it is essential to understand the genetic basis of the natural variation in kernel starch content (SC) for maize breeding. Through a genome-wide association study (GWAS), we identified 84 and 96 loci associated with kernel SC within two years that overlapped with 185 candidate genes. The candidate gene ZmMYB71, which encodes a myeloblastosis (MYB)-related transcription factor, exhibited the highest co-expression frequency with starch synthesis genes. We demonstrated that ZmMYB71 functions as a nuclear located transcription repressor, and the kernel SC of mutants increased by over 2.32%, with a minor effect on amylose content or 100-grain weight. Sh1, Sh2, and GBSSI showed up-regulation in mutants by 1.56-, 1.45- and 1.32-fold, respectively, consistently with the RNA sequencing result; their promoter activities may be directly repressed by ZmMYB71 through the GATATC and TTAGGG motifs. Furthermore, the ZmMYB71 elite haplotype Hap1 was present in over 55% of the high-starch maize sub-populations BSSS and PB but only in 7.14% of the low-starch sub-population PA. Comparing the Hap1 haplotype frequencies in different breeding stages found that its frequency in the inbred group released after 2010 is significantly higher at 40.28%, in contrast to 28.57% and 27.94% in the years 1980 and 1990, and 2000, respectively. The finding provides valuable information on the natural variation in SC of the maize kernel and suggests that ZmMYB71 serves as a negative regulator with the potential to be used to improve SC in the kernels.

Modelling of the variation of granular base materials resilient modulus with material characteristics and humidity conditions

This study aims to quantify the susceptibility of granular materials used in pavements to changes in moisture content and propose a correlation model to incorporate this susceptibility into seasonal analyses. The fines content and the percentage of fractured coarse aggregates were identified as direct indicators of the resilient modulus susceptibility to changes in water content. The results showed that the percentage of fractured coarse aggregates particles (FR) has a more significant impact on the resilient modulus (Er) of crushed granular materials used in pavement construction than the combined indicator of the fines content and sample volumetrics (nf). Crushed granular materials with a higher percentage of fractured coarse aggregates are relatively insensitive to changes in the degree of saturation, but become more sensitive as the fine fraction porosity decreases. An adjusted model was proposed based on the existing formulation, but considers a complex parameter to describe and adjust the sensitivity of base granular materials to variations in moisture content with respect to fabrication characteristics, fines content and volumetric properties. The model shows that the variation of Er values is below ±10% for fully crushed granular materials. However, it reaches approximately ±12% for materials with 75% of crushed coarse aggregates and +40% and −25% for materials with FR ​= ​50%. This model could help select good aggregates characteristics and adjust grain-size distribution for environments where significant moisture content variations can occur in the pavement system, such as in the Province of Quebec (Canada). As it is based on parameters that can be easily determined or estimated, it also represents a valuable tool for detailed design and analysis that can consider material characteristics.

Extraction of phenolic compounds from spent coffee ground using natural deep eutectic solvents: New modeling approach

AbstractThe extraction of bioactive compounds from food wastes or by‐products with natural deep eutectic solvents (NADES) could be an attractive alternative to traditional hydroalcoholic extraction but needs to be optimized taking advantage of modeling. This work aims to propose, develop, and discuss a new model for the extraction of phenolic compounds from spent coffee grounds (SCGs) using NADES to overcome some gaps related to the kinetic extraction models and the surface response methodology. The model presented is based on the same assumption as the kinetic model, but improving it to be able to predict phenolic extraction changing different process parameters (e.g., water content, time of extraction, temperature, etc.) using betaine: triethylene glycol (molar ratio 1:2). The model was validated on the extraction of total phenolic compounds from SCG as a function of water content of NADES ranging from 30 to 60% v/v. There was good agreement between experimental and simulated data and even, in some cases, better than with the second‐order kinetic models. In addition, the new model needs fewer parameters to be regressed concerning the specific case investigated in this work. This model and methodology can be the basis for further modeling applicable to other bioactives, and/or other NADES and feedstocks.Practical ApplicationsNatural deep eutectic solvents (NADES) can be a potential sustainable solvent for the valorization of food by‐products as they can be used to extract bioactive compounds with high added value. This extraction process needs to be optimized depending on several factors like water content in NADES solution, solids ratio, extraction time, and temperature. The model validated in this work on spent coffee ground (SCG) could be used for this purpose, improving the gaps related to the kinetic extraction models and the surface response methodology (RSM). The new model enables predicting the behavior of the process as a function of the parameters previously mentioned and reduces the number of experimental trials required compared with RSM. In particular, the new model was validated on the variation of water content in NADES solution. Certainly, this model will need to be further validated, but, once further studies are conducted, this model could be used for scale‐up calculation and design optimization of the industrial process.

Large TEC Variations Between Mars and Earth: Simulation and Observation Comparisons

AbstractLarge total electron content (TEC) variations along the line from Mars to Earth have been demonstrated by analyzing the ground received Tianwen‐1 differential one‐way range (DOR) signals when corona mass ejections (CMEs) and co‐rotating interaction regions (CIRs) pass through the signal path. Here, the TEC variations along the line from Mars to Earth are calculated from the Wang‐Sheeley‐Arge (WSA)‐Enlil space weather forecast model. The results are compared with the Tianwen‐1 line of sight (LOS) observations as well as the STEREO‐A in situ solar wind density measurements. It is found that the TEC variations calculated from the WSA‐Enlil model are usually much smaller in amplitude, especially in the cases of CIRs passing through the signal path. In addition, the timings of CMEs and CIRs passing through the DOR signal path in the WSA‐Enlil model can be half a day earlier or later than the observed ones. In comparison with in situ solar wind measurements, the ground received Tianwen‐1 DOR signals carry solar wind density information over a large spatial region along the signal path. Such remote sensing measurement can be valuable for constraining and improving global solar wind forecast models.

Mechanical strength distribution in Geminid meteoroids derived via fireball modeling

Context. Geminids are the most active annual meteor shower observed on Earth. Their parent is an active asteroid, (3200) Phaethon, which is a target of the planned DESTINY+ mission of the Japan Aerospace Exploration Agency (JAXA). The exact physical nature of (3200) Phaethon and Geminids is still debated. Aims. This paper is devoted to fragmentation modeling of bright Geminid fireballs, which should reveal information about the structure of centimeter-sized Geminid meteoroids. These fireballs were observed by the European Fireball Network (EN) over the past few years. We aim to describe their disintegration cascade in the atmosphere and their mechanical properties, and to derive their precise initial masses and velocities. Methods. We used a semi-empirical fragmentation model that employs an automatic procedure based on parallel genetic algorithms to determine the aerodynamic pressures at which a meteoroid and its parts fragment. This serves as a proxy for the mechanical strength of the body and its subsequent fragments. It enabled us to derive the minimum, median, and maximum mechanical strength and the strength distribution inside the meteoroid and reveal its internal structure. Results. We find that the Geminids begin to crumble at pressures 1–100 kPa, with the strongest parts reaching pressures of between 0.4 and 1.55 MPa before fragmenting. Knowing the spectral type of (3200) Phaethon (a B-type asteroid, part of the C complex), we conclude that the Geminids are made of compact and coherent carbonaceous material. We also find that the minimum aerodynamic pressure that causes the fragmentation of Geminids increases with increasing entry mass of Geminids. In contrast, the median aerodynamic pressure decreases as their entry mass increases. The spectra of all the observed Geminid fireballs show normal content and little variation in terms of sodium.

GC-MS-based Metabolomics Unravels Metabolites across Larval Development and Diapause of a Specialist Insect.

Plant-insect interactions are a driving force into ecosystem evolution and community dynamics. Many insect herbivores enter diapause, a developmental arrest stage in anticipation of adverse conditions, to survive and thrive through seasonal changes. Herein, we investigated the roles of medium- to non-polar metabolites during larval development and diapause in a specialist insect herbivore, Chlosyne lacinia, reared on Aldama robusta leaves. Varying metabolites were determined using gas chromatography-mass spectrometry (GC-MS)-based metabolomics. Sesquiterpenes and steroids were the main metabolites putatively identified in A. robusta leaves, whereas C. lacinia caterpillars were characterized by triterpenes, steroids, fatty acids, and long-chain alkanes. We found out that C. lacinia caterpillars biosynthesized most of the identified steroids and fatty acids from plant-derived ingested metabolites, as well as all triterpenes and long-chain alkanes. Steroids, fatty acids, and long-chain alkanes were detected across all C. lacinia instars and in diapausing caterpillars. Sesquiterpenes and triterpenes were also detected across larval development, yet they were not detected in diapausing caterpillars, which suggested that these metabolites were converted to other molecules prior to the diapause stage. Our findings shed light on the chemical content variation across C. lacinia development and diapause, providing insights into the roles of metabolites in plant-insect interactions.

Structure, dielectric and magnetic properties of hydrothermally synthesized Sn1−x Fe x O2 nanoparticles

Abstract Sn1−x Fe x O2 (x = 0, 1, 2, 3, and 4 %) of the diamagnetic/ferromagnetic phase were synthesized by the conventional hydrothermal method. X-ray diffraction spectra confirm that all the samples have a tetragonal structure. Electronic distribution over the unit cell of Sn1−x Fe x O2 showed the dependence of electronic density on the x. The crystallite size of the obtained samples was in the range of 42–72 nm. Impedance spectroscopy was employed to investigate the variation of the electrical impedance and some related parameters as frequency functions in the range of 75 k Hz–10 MHz at room temperature. The dielectric behavior was explained using the Maxwell–Wagner model of interfacial polarization. The ac conductivity results were used to evaluate the maximum barrier height, the minimum hopping distance, and the density of the localized states at the Fermi level. The effect of adding the iron ion into the tin dioxide compound was apparent, as the electrical and magnetic properties as well as the morphology were affected, although the crystal structure phase still has the same tetragonal crystal system for the different iron concentration (Fe from x = 0 up to x = 0.04) with slight variation in the lattice constants. The magnetic measurements illustrated that the Fe-doped SnO2 nanoparticles exhibit ferromagnetic ordering at room temperature. Variation of the Fe content affects the ferromagnetic characteristics of the samples.

Flexural Strength of Kenaf Fibers/Epoxy Bio-Composites: Content of Kenaf Fiber, Curing Times and Curing Temperatures

Kenaf fiber possesses the capability for application in bio-composite materials, owing to its appealing mechanical and physical properties. This research aimed to achieve the optimum flexural strength of kenaf fiber/epoxy bio-composites materials with variations in kenaf fiber content, curing time, and curing temperature using a casting process. This study found that kenaf fiber addition increased the flexural strength of kenaf fiber/epoxy bio-composite, by varying curing time (30, 45, and 60 minutes) and curing temperature (60, 90, and 150 °C). The results showed that the highest flexural strength was obtained at 90°C (72.5 MPa) at 20/80 kenaf fiber content, at various curing temperatures. Meanwhile, the same highest flexural strength value (72.5 MPa) was also obtained for 20/80 kenaf fiber content, 45 minutes at various curing times. SEM image shows that 20 Wt.% kenaf fiber content has a better dispersion compared with 10 Wt.% so that affects the flexural strength value.

Nutritional Analysis of Three Commercially Important Dried Fish (Otolithoides Pama, Trichiurus Haumela, Harpodon Nehereus) of Three Different Countries

The study aimed to compare the nutritional and fatty acid composition of three dried fish species, Otolithoides pama, Trichiurus haumela, and Harpodon nehereus, of Bangladesh and imported sample of India and Myanmar. Proximate compositions were analyzed using the AOAC method with modifications, and fatty acid analyses were conducted via Gas Chromatography Mass Spectrometry (GCMS). Overall, the quality of fish samples from all three countries was deemed excellent. The dried Harpodon nehereus from Myanmar stood out with the highest protein content (62.81±2.83%) among the species, while also exhibiting the highest lipid content (11.03±0.39%). Indian Harpodon nehereus had the highest ash content (10.18±0.72%), and Bangladesh’s dried Harpodon nehereus had higher moisture and fiber content. For Trichiurus haumela, the Bangladeshi sample had the highest protein and lipid content, whereas Myanmar’s sample had the highest ash concentration. Moisture and fiber content were higher in Myanmar and Bangladesh. Otolithoides pama displayed variations in protein, ash, moisture, and fiber content across countries, with India having the highest moisture content. The major fatty acids identified included Methyl Palmitate, Methyl Palmitpleate, Methyl Laurate, Methyl Arachidonate, and Methyl Stearate, with notable levels of Methyl Linoleate in all three species, particularly in Bangladeshi Trichiurus haumela. In summary, the study revealed significant compositional variations in dried fish from different countries.

Variation of Nitrogen, Phosphorus, and Potassium Contents in Drip-Irrigated Cotton at Different Yield Levels under Combined Effects of Nitrogen, Phosphorus and Potassium

To elucidate the variation characteristics of nitrogen (N), phosphorus (P), and potassium (K) content and accumulation in cotton at different yield levels, a two-year experiment was conducted using cotton variety Lumianyan 24 under four N treatments (506, 402.5, 299, and 195.5 kg ha−1, designated as N1, N2, N3, and N4, respectively). The four P and K fertilization ratios were (PK-M1, 25% P and K applied at squaring stage (SS) and 75% at the bloom-bolling stages (BS)), 50%:50% (PK-M2, 50% P and K applied at each stage), 75%:25% (PK-M3, 75% P and K applied at SS and 25% at the BS) and 100%:0% (PK-M4, total P and K applied at SS). The results showed that the N content (Nc), P content (Pc), and K content (Kc) of cotton plants at high yield levels were 23.3%, 44.2%, and 31.6% higher than those at low yield levels. In addition, the reproductive organs maintained higher Pc and Kc at high yield levels, and the Nc, Pc, and Kc exhibited positive linear correlations with yield, while Nc/Pc, Nc/Kc, and Kc/Pc had significant negative correlations with yield. In conclusion, seed cotton yield was mainly limited by Nc at low yield levels and affected by Pc and Kc at high yield levels. Then, when 0.85 < Nc/Kc < 1.0 at the full squaring stage (FS), 0.8 < Nc/Kc < 1.0 at the full flowering stage (FF), 4.3 < Nc/Pc < 6.7 at the early-full bolling stage (EFB) and 4.9 < Nc/Pc < 7.1 at the late-full bolling stage (LFB), there is a high yield potential of 7000–9000 kg ha−1. Furthermore, yields can be improved by reducing the application of N during the growing period and increasing the application of P fertilizer during the later growth period.

Transcriptome and comparative chloroplast genome analysis of Taxus yunnanensis individuals with high and low paclitaxel yield

Paclitaxel is a potent anti-cancer drug that is mainly produced through semi-synthesis, which still requires plant materials as precursors. The content of paclitaxel and 10-deacetyl baccatin III (10-DAB) in Taxus yunnanensis has been found to differ from that of other Taxus species, but there is little research on the mechanism underlying the variation in paclitaxel content in T. yunnanensis of different provenances. In this experiment, the contents of taxoids and precursors in twigs between a high paclitaxel-yielding individual (TG) and a low paclitaxel-yielding individual (TD) of T. yunnanensis were compared, and comparative analyses of transcriptomes as well as chloroplast genomes were performed. High-performance liquid chromatography (HPLC) detection showed that 10-DAB and baccatin III contents in TG were 18 and 47 times those in TD, respectively. Transcriptomic analysis results indicated that genes encoding key enzymes in the paclitaxel biosynthesis pathway, such as taxane 10-β-hydroxylase (T10βH), 10-deacetylbaccatin III 10-O-acetyltransferase (DBAT), and debenzoyl paclitaxel N-benzoyl transferase (DBTNBT), exhibited higher expression levels in TG. Additionally, qRT-PCR showed that the relative expression level of T10βH and DBAT in TG were 29 and 13 times those in TD, respectively. In addition, six putative transcription factors were identified that may be involved in paclitaxel biosynthesis from transcriptome data. Comparative analysis of plastid genomes showed that the TD chloroplast contained a duplicate of rps12, leading to a longer plastid genome length in TD relative to TG. Fifteen mutation hotspot regions were identified between the two plastid genomes that can serve as candidate DNA barcodes for identifying high-paclitaxel-yield individuals. This experiment provides insight into the difference in paclitaxel accumulation among different provenances of T. yunnanensis individuals.