Fungal fermentation of Fuzhuan brick tea: A comprehensive evaluation of sensory properties using chemometrics, visible near-infrared spectroscopy, and electronic nose.

Fuzhuan brick tea (FBT) fungal fermentation is a key factor in achieving its unique dark color, aroma, and taste. Therefore, it is essential to develop a rapid and reliable method that could assess its quality during FBT fermentation process. This study focused on using electronic nose (e-nose) and spectroscopy combination with sensory evaluations and physicochemical measurements for building machine learning (ML) models of FBT. The results showed that the fused data achieved 100 % accuracy in classifying the FBT fermentation process. The SPA-MLR method was the best prediction model for FBT quality (R2 = 0.95, RMSEP = 0.07, RPD = 4.23), and the fermentation process was visualized. Where, it was effectively detecting the degree of fermentation relationship with the quality characteristics. In conclusion, the current study's novelty comes from the established real-time method that could sensitively detect the unique post-fermentation quality components based on the integration of spectral, and e-nose and ML approaches.

Evaluation of Sechium edule fruit attenuation impact on the cardiomyopathy of the STZ-induced diabetic rats.

Sechium edule, commonly known as chayote is known for its low glycemic index, high fiber content, and rich nutritional profile, which suggests it may be beneficial for individuals with diabetes. While research specifically examining the impact of chayote on diabetes is limited, this study screened its biological impacts by using different biomarkers on streptozotocin-induced diabetic (STZ-ID) rats. The ethanolic extract of the Sechium edule fruits was assessed for different phytochemical, biochemical, and anti-diabetic properties. In the results, chayote extract had high phenolic and flavonoid contents respectively (39.25 ± 0.65 mg/mL and 12.16 ± 0.50 mg/mL). These high phenolic and flavonoid contents showed high implications on STZ-ID rats. Altogether 200 and 400 mg/kg of the extract considerably reduced the blood sugar level and enhanced the lipid profile of the STZ-ID rats. Additionally, they have decreased blood urea and serum creatinine levels. Besides, the levels of SGOT, SGPT, LDH, sodium, and potassium ions were significantly lowered after the administration period. More importantly, the electrocardiogram (ECG) parameters such as QT, RR, and QTc which were prolonged in the diabetic rats were downregulated after 35 days of administration of S. edule extract (400 mg/kg). And, the histological examination of the pancreas and kidney showed marked improvement in structural features of 200 and 400 mg/kg groups when compared to the diabetic control group. Where the increase in the glucose levels was positively correlated with QT, RR, and QTc (r2 = 0.76, r2 = 0.76, and r2 = 0.43) which means that ECG could significantly reflect the diabetes glucose levels. In conclusion, our findings showed that the fruit extract exerts a high potential to reduce artifacts secondary to diabetes which can be strongly suggested for diabetic candidates. However, there is a need to study the molecular mechanisms of the extract in combating artifacts secondary to diabetes in experimental animals.

Advanced deep learning algorithm for instant discriminating of tea leave stress symptoms by smartphone-based detection.

The primary challenges in tea production under multiple stress exposures have negatively affected its global market sustainability, so introducing an infield fast technique for monitoring tea leaves' stresses has tremendous urgent needs. Therefore, this study aimed to propose an efficient method for the detection of stress symptoms based on a portable smartphone with deep learning models. Firstly, a database containing over 10,000 images of tea garden canopies in complex natural scenes was developed, which included healthy (no stress) and three types of stress (tea anthracnose (TA), tea blister blight (TB) and sunburn (SB)). Then, YOLOv5m and YOLOv8m algorithms were adapted to discriminate the four types of stress symptoms; where the YOLOv8m algorithm achieved better performance in the identification of healthy leaves (98%), TA (92.0%), TB (68.4%) and SB (75.5%). Furthermore, the YOLOv8m algorithm was used to construct a model for differentiation of disease severity of TA, and a satisfactory result was obtained with the accuracy of mild, moderate, and severe TA infections were 94%, 96%, and 91%, respectively. Besides, we found that CNN kernels of YOLOv8m could efficiently extract the texture characteristics of the images at layer 2, and these characteristics can clearly distinguish different types of stress symptoms. This makes great contributions to the YOLOv8m model to achieve high-precision differentiation of four types of stress symptoms. In conclusion, our study provided an effective system to achieve low-cost, high-precision, fast, and infield diagnosis of tea stress symptoms in complex natural scenes based on smartphone and deep learning algorithms.

Synthesis and characterization of magnesium ferrite-activated carbon composites derived from orange peels for enhanced supercapacitor performance.

Supercapacitors have emerged as highly efficient energy storage devices, relying on electrochemical processes. The performance of these devices can be influenced by several factors, with key considerations including the selection of electrode materials and the type of electrolyte utilized. Transition metal oxide electrodes are commonly used in supercapacitors, as they greatly influence the electrochemical performance of these devices. Nonetheless, ferrites' low energy density poses a limitation. Hence, it is crucial to create electrode materials featuring unique and distinct structures, while also exploring the ideal electrolyte types, to enhance the electrochemical performance of supercapacitors incorporating magnesium ferrites (MF). In this study, we effectively prepared magnesium ferrites (MgFe2O4) supported on activated carbon (AC) derived from orange peels (OP) using a simple hydrothermal method. The resulting blends underwent comprehensive characterization employing various methods, including FTIR, XRD, TEM, SEM, EDX, and mapping analysis. Moreover, the electrochemical performance of MgFe2O4@AC composites was evaluated using GCD and CV techniques. Remarkably, the MF45-AC electrode material showed exceptional electrochemical behavior, demonstrating a specific capacitance of 870 F·g-1 within current density of 1.0 A g-1 and potential windows spanning from 0 to 0.5 V. Additionally, the prepared electrodes displayed exceptional cycling stability, with AC, MF, and MF45-AC retaining 89.6%, 94.2%, and 95.1% of their initial specific capacitance, respectively, even after 5000 cycles. These findings underscore the potential of MF-AC composites as superior electrode materials for supercapacitors. The development of such composites, combined with tailored electrolyte concentrations, holds significant promise for advancing the electrochemical performance and energy density of supercapacitor devices.

Predicting rice diseases using advanced technologies at different scales: present status and future perspectives.

The past few years have witnessed significant progress in emerging disease detection techniques for accurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focus on image processing techniques using machine learning (ML) and deep learning (DL) models related to multi-scale rice diseases. Furthermore, we summarize applications of different detection techniques, including genomic, physiological, and biochemical approaches. In addition, we also present the state-of-the-art in contemporary optical sensing applications of pathogen-plant interaction phenotypes. This review serves as a valuable resource for researchers seeking effective solutions to address the challenges of high-throughput data and model recognition for early detection of issues affecting rice crops through ML and DL models.

13C-metabolic flux analysis of lipid accumulation in the green microalgae Tetradesmus obliquus under nitrogen deficiency stress.

Metabolic fluxes (MF) serve as the functional phenotypes of biochemical processes and are crucial to describe the distribution of precursors within metabolic networks. There is a lack of experimental observations for carbon flux towards lipids, which is important for biodiesel generation. Here, the accumulation of lipid, and MF in Tetradesmus obliquus under nitrogen deficiency stress (NF) using a 13C isotope tracer at different time intervals was investigated. The 13C based MF showed enhanced de novo synthesis of G3P and PEP, indicating increased carbon flux from CO2 into lipid synthesis. An increase in palmitic acid (3500 µmol/mg), linoleic acid (2100 µmol/mg), and oleic acid (2000 µmol/mg) was observed. The accumulation of C16:0 under NF was mainly related to de novo synthesis while C18:3 was accumulated through a non de novo pathway. Under NF stress, T. obliquus had higher flux in PPP and glycolysis pathway, together, it might provide more NADPH and substrate acetyl-CoA for fatty acid synthesis.

The Recent Development of Acoustic Sensors as Effective Chemical Detecting Tools for Biological Cells and Their Bioactivities.

One of the most significant developed technologies is the use of acoustic waves to determine the chemical structures of biological tissues and their bioactivities. In addition, the use of new acoustic techniques for in vivo visualizing and imaging of animal and plant cellular chemical compositions could significantly help pave the way toward advanced analytical technologies. For instance, acoustic wave sensors (AWSs) based on quartz crystal microbalance (QCM) were used to identify the aromas of fermenting tea such as linalool, geraniol, and trans-2-hexenal. Therefore, this review focuses on the use of advanced acoustic technologies for tracking the composition changes in plant and animal tissues. In addition, a few key configurations of the AWS sensors and their different wave pattern applications in biomedical and microfluidic media progress are discussed.

Evaluation of carbon dioxide elevation on phenolic compounds and antioxidant activity of red onion (Allium cepa L.) during postharvest storage.

Carbon dioxide (CO2) is considered one of the eco-related key factors that negatively affect global climatic change. Also, CO2 can play an important role in the postharvest quality of the agri-products. In this study, the impact of CO2 on the quality of postharvest onions that were stored at 23 °C for 8 weeks was investigated. The weight loss, phenolic, flavonoid, flavanol, anthocyanin, antioxidant activity, and soluble sugar were analyzed during the study period. The results showed that 20% CO2 treatment was significantly (P > 0.05) more effective than 15% CO2 and control in inhibiting weight loss. Additionally, 20% CO2 treatment significantly retained higher antioxidant enzyme activities such as CAT, APX, and SOD than 15% CO2 and control. During storage, 20% CO2 treatment significantly (P < 0.05) improved glucose, fructose, and sucrose levels by more than 15% CO2 exposure and control groups. Besides the chlorogenic acid, kaempferol and quercetin were significantly (P < 0.05) higher in the 20% CO2 than in the 15% CO2 after 2 weeks of storage. In conclusion, this study's novelty comes from the broad prospects of using CO2 for maximizing the stored onion phytochemical functionality that is usually affected by the room temperature long storage. This will help in the onion shelf-life extension by considering the quality-related attributes.

Nano and fine colloids suspended in the soil solution regulate phosphorus desorption and lability in organic fertiliser-amended soils.

Mobile colloids impact phosphorus (P) binding and transport in agroecosystems. However, their relationship to P-lability and their relative importance to P-bioavailability is unclear. In soils amended with organic fertilisers, we investigated the effects of nano (NC; 1-20 nm), fine (FC; 20-220 nm), and medium (MC; 220-450 nm) colloids suspended in soil solution on soil P-desorption and lability. The underlying hypothesis is that mobile colloids of different sizes, i.e., NC, FC, and MC, may contribute differently to P-lability in soils enriched with organic fertiliser. NC- and FC-bound Pcoll were positively correlated with P-lability parameters from diffusive gradient in thin films (DGTA-labile P concentration, r ≥ 0.88; and DGTA-effective P concentration, r ≥ 0.87). The corresponding relations with MC-bound Pcoll are weaker (r values of 0.50 and 0.51). NC- and FC-bound Pcoll were also strongly correlated with soil P-resupply (r ≥ 0.64) and desorption (r ≥ 0.79) parameters during DGTA deployment, and the mobility of these colloids was corroborated by electron microscopy of DGTA gels. MC-bound Pcoll was negatively correlated with the solid-to-solution distribution coefficient (r = -0.42), indicating this fraction is unlikely to be the source of P-release from the solid phase after P-depletion from the soil solution. We conclude that NC and FC mainly contribute to regulating soil desorbable-P supply to the soil solution in the DGTA depletion zone (in vitro proxy for plant rhizosphere), and consequently may act as critical conditioners of P-bioavailability, whereas MC tends to form complexes that lead to P-occlusion rather than lability.

Potential bioactivity of Phoenix dactylifera fruits, leaves, and seeds against prostate and pancreatic cancer cells.

The use of functional foods' phytochemicals in the chemoprevention of different cancer diseases has become one of the hot scientific areas in the clinical nutrition field. For instance, the Khalas palm cultivar (KPC; Phoenix dactylifera) is one of the natural sustainable resources that have high bioactivity and functionality. This study aimed to investigate the antiproliferative activity and mode of action of KPC's different parts on prostate (Pc3) and pancreatic (panc1) cancer cells at a molecular level. In the methods, KPC's leaves, seeds, and fruits' chemical composition and phytochemical analysis were analyzed. Also, the cytotoxic effects of each extract were assessed against pc3 and panc1 cell lines. Besides, induction of apoptosis, cell cycle analysis, and gene expression of both Cap3 and Cap9 were studied. The obtained results indicated that KPC leaves extract exhibited the highest significant (P < 0.01) anti-proliferation activity against the utilized cancer cell lines compared to fruits and seeds extracts. Also, there were significant (P < 0.05) differences in the phenolic contents, flavonoid of compounds, and antioxidant power of the leaves when compared to the seeds and fruits. Additionally, the highest cytotoxic effect (lowest IC50) was recorded with leave extract than seeds and fruits. Meanwhile, the seeds extract induced (P < 0.05) the apoptosis and arrested cells in the G2/M phase as well as up-regulated the gene expression of the apoptotic-related genes (Casp3 and Casp9) compared to the control group. In conclusion, this study showed that the presence of bioactive components in the KPC different parts extracts have the significant ability to induce the apoptotic pathway that could down-regulate the proliferation of prostate (pc3) and pancreatic (panc1) cancer cells. The pathway mechanism of action was induced by the phytol molecule presented in its leaves extract.

Molecular Genomic Study of Inhibin Molecule Production through Granulosa Cell Gene Expression in Inhibin-Deficient Mice.

Inhibin is a molecule that belongs to peptide hormones and is excreted through pituitary gonadotropins stimulation action on the granulosa cells of the ovaries. However, the differential regulation of inhibin and follicle-stimulating hormone (FSH) on granulosa cell tumor growth in mice inhibin-deficient females is not yet well understood. The objective of this study was to evaluate the role of inhibin and FSH on the granulosa cells of ovarian follicles at the premature antral stage. This study stimulated immature wild-type (WT) and Inhibin-α knockout (Inha-/-) female mice with human chorionic gonadotropin (hCG) and examined hCG-induced gene expression changes in granulosa cells. Also, screening of differentially expressed genes (DEGs) was performed in the two groups under study. In addition, related modules to external traits and key gene drivers were determined through Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. The results identified a number of 1074 and 931 DEGs and 343 overlapping DEGs (ODEGs) were shared in the two groups. Some 341 ODEGs had high relevance and consistent expression direction, with a significant correlation coefficient (r2 = 0.9145). Additionally, the gene co-expression network of selected 153 genes showed 122 nodes enriched to 21 GO biological processes (BP) and reproduction and 3 genes related to genomic pathways. By using principal component analysis (PCA), the 14 genes in the regulatory network were fixed and the cumulative proportion of fitted top three principal components was 94.64%. In conclusion, this study revealed the novelty of using ODEGs for investigating the inhibin and FSH hormone pathways that might open the way toward gene therapy for granulosa cell tumors. Also, these genes could be used as biomarkers for tracking the changes in inhibin and FSH hormone from the changes in the nutrition pattern.

Evaluation of Proanthocyanidins from Kiwi Leaves (Actinidia chinensis) against Caco-2 Cells Oxidative Stress through Nrf2-ARE Signaling Pathway.

Proanthocyanidins (PAs) are considered to be effective natural byproduct and bioactive antioxidants. However, few studies have focused on their mode of action pathways. In this study, reactive oxygen species (ROS), oxidative stress indices, real-time PCR, Western blotting, confocal microscopy, and molecular docking were used to investigate the protective effect of purified kiwi leaves PAs (PKLPs) on Caco-2 cells' oxidative stress mechanisms. The results confirmed that pre-treatment with PKLPs significantly reduced H2O2-induced oxidative damage, accompanied by declining ROS levels and malondialdehyde (MDA) accumulation in the Caco-2 cells. The PKLPs upregulated the expression of antioxidative enzymes (GSH-px, CAT, T-SOD) and the relative mRNA (Nrf, HO-1, SOD-1, CAT) of the nuclear factor erythroid 2-related factor (Nrf2) signaling pathway. The protein-expressing level of the Nrf2 and its relative protein (NQO-1, HO-1, SOD-1) were significantly increased (p < 0.05) in the PKLPs pre-treatment group compared to the model group. In conclusion, the novelty of this study is that it explains how PKLPs' efficacy on the Nrf2-ARE signaling pathway, in protecting vital cells from oxidative stress, could be used for cleaner production.

Emerging Technologies for Detecting the Chemical Composition of Plant and Animal Tissues and Their Bioactivities: An Editorial.

Integrating physical and chemical technologies for the characterization and modification of plants and animal tissues has been used for several decades to improve their detection potency and quality [...].

Assess heavy metals-induced oxidative stress of microalgae by Electro-Raman combined technique.

Oxidative stress of aquatic microorganisms under heavy metal stress is closely reflected by metabolite changes in cells but it is very difficult to study due to the fast metabolism process and severe in-situ measurements hurdle. Herein, the oxidative stress of cadmium on Euglena gracilis was systematically studied through multi-combined techniques. In particular, for the first time electrochemical approach was associated with Raman spectroscopy imaging to vividly to investigate temporal-spatially varied oxidative stress and its effects on cells metabolism, in which former real-time measured a volcanic relation of extracellular hydrogen peroxide versus the increase of cadmium stress, while the latter shows the corresponding metabolic changes by Raman imaging of single cells. This work builds a bridge to unravel the mechanism of cellular oxidative stress under harsh conditions in a more systematic and holistic approach, while holding a great promise to construct heavy metal biosensors precisely monitoring high heavy metal tolerance strains for environmental modification.

Impacts of Gum Arabic and Polyvinylpyrrolidone (PVP) with Salicylic Acid on Peach Fruit (Prunus persica) Shelf Life.

Peaches are grown in many Egyptian orchards for local and global fresh market sales. The interior fruit tissue breakdown (IFTB), often resulting in decayed peaches, is a severe problem during marketing. Therefore, to minimize FTB of peaches, in this study, gum arabic (GA) and polyvinylpyrrolidone (PVP) were mixed with different concentrations of salicylic acid (SA) (0, 1, and 2 mM) and were applied as edible coating to extend the shelf life of peach fruits. Mature peaches were selected and harvested when peaches reached total soluble solid content (SSC: 8.5%) and fruit firmness of about 47 N. Fruits were coated and stored at room temperature (26 ± 1 °C and air humidity 51 ± 1%) for 10 days during two seasons: 2020 and 2021. Fruit coated with GA/PVP-SA 2 mM showed a significant (p < 0.05) inhibition in degrading enzyme activities (CWDEs), such as lipoxygenase (LOX), cellulase (CEL), and pectinase (PT), compared to uncoated and coated fruits during the shelf-life period. Hence, cell wall compartments were maintained. Consequently, there was a reduction in browning symptoms in fruits by inhibiting polyphenol oxidase (PPO) and phenylalanine ammonia-lyase (PAL) activities. Thus, the fruit skin browning index showed almost no symptoms. The lipid peroxidation process and ionic permeability declined as well. The result suggests that, by applying GA/PVP-SA 2 mM as an edible coating, fruit tissue breakdown can be minimized, and the shelf life of peach can be extended up to 10 days without symptoms of tissue breakdown.

Optimization of Platinum Nanoparticles (PtNPs) Synthesis by Acid Phosphatase Mediated Eco-Benign Combined with Photocatalytic and Bioactivity Assessments.

Noble metal nanoparticles (NMNPs) are viable alternative green sources compared to the chemical available methods in several approach like Food, medical, biotechnology, and textile industries. The biological synthesis of platinum nanoparticles (PtNPs), as a strong photocatalytic agent, has proved as more effective and safer method. In this study, PtNPs were synthesized at four different temperatures (25 °C, 50 °C, 70 °C, and 100 °C). PtNPs synthesized at 100 °C were smaller and exhibited spherical morphology with a high degree of dispersion. A series of physicochemical characterizations were applied to investigate the synthesis, particle size, crystalline nature, and surface morphology of PtNPs. The biosynthesized PtNPs were tested for the photodegradation of methylene blue (MB) under visible light irradiations. The results showed that PtNPs exhibited remarkable photocatalytic activity by degrading 98% of MB only in 40 min. The acid phosphatase mediated PtNPs showed strong bacterial inhibition efficiency against S. aureus and E. coli. Furthermore, it showed high antioxidant activity (88%) against 1,1-diphenyl-2-picryl-hydrazil (DPPH). In conclusion, this study provided an overview of the applications of PtNPs in food chemistry, biotechnology, and textile industries for the deterioration of the natural and synthetic dyes and its potential application in the suppression of pathogenic microbes of the biological systems. Thus, it could be used as a novel approach in the food microbiology, biomedical and environmental applications.

Microalgae Bioactive Carbohydrates as a Novel Sustainable and Eco-Friendly Source of Prebiotics: Emerging Health Functionality and Recent Technologies for Extraction and Detection.

There is a global interest in the novel consumption, nutritional trends, and the market of new prebiotic sources and their potential functional impacts. Commercially available nutritional supplements based on microalgae that are approved to be edible by FDA, like Arthrospira platensis (Cyanobacteria) and Chlorella vulgaris (Chlorophyta) become widely attractive. Microalgae are rich in carbohydrates, proteins, and polyunsaturated fatty acids that have high bioactivity. Recently, scientists are studying the microalgae polysaccharides (PS) or their derivatives (as dietary fibers) for their potential action as a novel prebiotic source for functional foods. Besides, the microalgae prebiotic polysaccharides are used for medication due to their antioxidant, anticancer, and antihypertensive bioactivities. This review provides an overview of microalgae prebiotics and other macromolecules' health benefits. The phytochemistry of various species as alternative future sources of novel polysaccharides were mentioned. The application as well as the production constraints and multidisciplinary approaches for evaluating microalgae phytochemistry were discussed. Additionally, the association between this potential of combining techniques like spectroscopic, chromatographic, and electrochemical analyses for microalgae sensation and analysis novelty compared to the chemical methods was emphasized.

Structure analysis and non-invasive detection of cadmium-phytochelatin2 complexes in plant by deep learning Raman spectrum.

Plants synthesize phytochelatins to chelate in vivo toxic heavy metal ions and produce nontoxic complexes for tolerating the stress. Detection of the complexes would simplify the identification of high phytoremediation cultivars, as well as assessment of plant food for safe consumption. Thus, a confocal Raman spectroscopy combined with density functional theory and deep learning was used for characterizing phytochelatin2 (PC2), and Cd-PC2 mixtures. Results showed the PC2 chelate Cd2+ in a 2:1 ratio to produce Cd(PC2)2; Cd-S bonds of the Cd(PC2)2 have signature Raman vibrations at 305 and 610 cm-1 which are the most distinctive spectral signatures for varieties of Cd-PCs complexes. The PC2 was used as a natural probe to stabilize the chemical status of Cd, and to enrich and magnify Raman signature of the trace Cd for deep learning models which enabled condition of the Cd(PC2)2 in pak choi leaf to be visualized, quantified, and classified by directly using raw spectra of the leaf. This study provides a general protocol by using Raman information for structure analysis and non-invasive detection of heavy metal-PCs complexes in plants and provides a novel idea for simplifying identification of high phytoremediation cultivars, as well as assessment of heavy metal related food safeties.