Search Results (248)

Sea fennel (Crithmum maritimum L.) is an emerging crop valued for its nutritional and sensory properties and has been reported to exert health-promoting effects, including antioxidant, anti-inflammatory, antimicrobial, and cardioprotective activities, as well as potential benefits for gut health and metabolic regulation. Building on these features, the present study aimed to unlock the potential of sea fennel to produce novel pickles. Two independent batches were prepared using young leaves and stems of sea fennel fermented in brine. After fermentation, salt concentration was standardized in all prototypes, and two types of vinegar (apple and wine) were added at four acetic acid levels (0.05%, 0.2%, 0.5%, and 0.7%). All prototypes were subsequently subjected to mild pasteurization. During fermentation, physicochemical and microbiological parameters were monitored, while after pasteurization additional physicochemical, microbiological, volatile organic compound (VOCs), and sensory analyses were performed during storage. In both batches and across all prototypes, fermentation resulted in a significant pH decrease, dominance of lactic acid bacteria, inhibition of Enterobacteriaceae, and a gradual increase in yeasts. Following vinegar addition and pasteurization, pH, titratable acidity, and salt content remained stable over six months of storage in most prototypes, particularly those with 0.2% acetic acid. Pasteurization effectively inactivated lactic acid bacteria and Enterobacteriaceae in all prototypes, whereas yeasts and mesophilic bacteria persisted in low-acidity samples (0.05%). Therefore, the 0.05% acidity samples were later excluded due to mid-stage microbial spoilage. Batch-dependent differences were observed in color and sensory attributes, with batch 2 showing higher overall stability mainly in acidic flavor and aroma, particularly in prototypes with 0.2% acidity. VOCs analysis revealed profiles primarily driven by batch variation, with secondary modulation by vinegar type: sesquiterpenes remained stable, while γ-terpinene, limonene, and p-cymene were the dominant compounds, with greater stability observed in batch 2. Overall, the combined use of lactic acid fermentation, vinegar pickling, and mild pasteurization represents a promising strategy for preserving sea fennel and supports its potential as a vegetable crop. Full article

This study evaluated the effects of different light-emitting diode (LED) spectral qualities on the early growth of kale at the baby-leaf harvest stage in a plant factory with artificial lighting (PFAL) by integrating morphological traits, biomass accumulation, plant quality indices, vegetation indices, and chlorophyll a fluorescence. Two kale (Brassica oleracea L.) cultivars, ‘Jellujon’ and ‘Manchoo Collard’, were grown for four weeks under monochromatic red, green, and blue LEDs, a purple composite LED with far-red wavelengths, and three white LEDs with different correlated color temperatures (3000, 4100, and 6500 K). Blue LED increased shoot height by approximately 14–28%, depending on cultivar and comparison among the white LED treatments, but this elongation did not translate into superior biomass production. In contrast, white LEDs, particularly at 3000–4100 K, increased leaf area to 24.2–24.9 cm² and SPAD units to 47.3–50.2, whereas blue or green LEDs generally resulted in smaller leaves and lower SPAD units. Shoot dry weight under 3000–4100 K white LEDs reached 0.25–0.26 g in ‘Jellujon’ and 0.26–0.29 g in ‘Manchoo Collard’, approximately twofold higher than under blue or green LEDs. Compactness, Dickson quality index, root investment ratio, and leaf efficiency index were also more favorable under white LEDs, indicating improved plant sturdiness and structural stability. Green LED light was associated with lower maximum photochemical efficiency (Φ_Po) and greater energy dissipation (Φ_Do and DI_o/RC), whereas photochemical reflectance index and PI_ABS tended to be more favorable under selected white LED treatments, although these responses were partly cultivar- and treatment-dependent. Taken together, among the LED spectral quality treatments tested, 3000–4100 K white LEDs provided the most consistently favorable conditions for producing structurally robust, high-quality kale at the early growth stage in PFAL systems. The purple LED showed partial advantages in leaf development and selected physiological responses, but these effects were less consistent across cultivars and indices. Full article

We developed an automated system for detecting Fusarium infection in pineapple leaves and fruits using a two-input onvolutional neural network. Implemented on a Raspberry Pi 5 with a high-quality camera, the system analyzes image pairs, fruit, and leaves of healthy and infected samples. To build the dataset, pineapple images were inoculated with Fusarium, photographed daily for 15 days, then augmented through geometric and color transformations, producing 1500 image pairs. Model transparency was enhanced by using local interpretable model-agnostic explanations (LIME). Evaluated with a confusion matrix, the model achieved an 89.61% accuracy using 77 infected and 77 non-infected image pairs for testing. Full article

Liquidambar formosana Hance, a tree species in subtropical broad-leaved forests, exhibits a striking autumn leaf coloration. However, how drought stress during this period influences leaf color change remains poorly understood. In this study, two-year-old seedlings were subjected to four drought gradients. Leaf color parameters, pigment contents, cellular structure, photosynthetic physiology, and hydraulic properties were systematically measured throughout the leaf color transition period. The results show that, with increasing drought severity, leaf red-green coordinate a* increased significantly during early-to-middle stress (S1–S3), while lightness L* and yellow-blue coordinate b* increased at late stress (S4). Chlorophyll (Chl) content continuously decreased, anthocyanins (Ant) peaked at mid-stress, and carotenoids (Car) became enriched at late stress. Leaf cellular structure and hydraulic parameters declined, photosynthetic function was inhibited, and antioxidant enzyme activities showed an initial increase followed by a decrease. Correlation analysis and Random Forest models revealed that L* was strongly associated with superoxide dismutase (SOD) activity, carotenoid-to-chlorophyll (Car/Chl) ratio, and net photosynthetic rate (P_n); a* was closely linked to osmotic potential at full saturation (Ψ_sat), relative water content at the turgor loss point (RWCtlp), SOD activity, Car/Chl ratio, anthocyanin-to-chlorophyll (Ant/Chl) ratio, Ant content, transpiration rate (T_r), P_n, and main vein thickness (Mvt), while b* was primarily correlated with Ψ_sat, Car/Chl ratio, SOD activity, Ant/Chl ratio, and P_n. These statistical associations suggest multiple physiological processes are involved in leaf color change. Based on these findings, we propose a hypothetical sequence: drought initially disrupts leaf water status, leading to structural atrophy and hydraulic decline, followed by photosynthetic inhibition, activated antioxidant defense, and altered pigment accumulation, which are correlated with the sequential leaf color transition from green to red to yellow-orange in this species. Full article

Background: Chlorophyll degradation is a characteristic sign of fruit ripening. However, the chlorophyll degradation pathway during pitaya fruit development remains unexplored. Methods and Results: Here, chlorophyll contents showed a downward trend across the five developmental stages of ‘Jindu No.1’ pitaya peels. Based on the pitaya genome data, twenty chlorophyll degradation genes were identified, including two NYCs, three CLHs, five SGRs, six PAOs, and four RCCRs, spread across eight pitaya chromosomes. In addition, their phylogenetic relationships, conserved motifs, and domains were analyzed using homologous genes from beet and Arabidopsis species. Transcriptomic data and RT-qPCR analyses of these genes suggested that three HuSGRs demonstrated a significant upward trend during pitaya peel maturation. Indeed, the HuSGR1 has the complete gene structure, including the chloroplast transit peptide, SGR domain, and variable C-terminal region. However, HuSGR2 and HuSGR3 contained the N- and C-terminal sequences, respectively, of HuSGR1. They were separated by a 690 bp distance on chromosome 8, forming a gene cluster. Overexpressed HuSGR2 or HuSGR3 alone resulted in a significant decrease in chlorophyll contents in tobacco leaves. Notably, a more obvious reduction of chlorophyll contents was observed when overexpressing them together. Conclusions: Our results show that HuSGR2 and HuSGR3 were involved in accelerating the chlorophyll degradation process, providing new insights into the molecular basis of color formation in pitaya peels. Full article

Cassava (Manihot esculenta Crantz) is a nitrogen-efficient crop that can achieve high biomass production on poor soils. However, the mechanisms underlying the response of cassava to nitrogen-deficiency signals and the regulation of nitrogen use efficiency remain unclear. Here, we found that MeCEPD (MeGRXC1) was specifically induced by CEP6 peptides and low nitrate, and showed higher expression in leaves and stems. Overexpression of MeCEPD enhanced cassava’s tolerance to nitrate deficiency by upregulating the expression of MeNRT2.1, MeNRT2.4, and MeRBCS1A, which was manifested as increased root biomass, greater lateral root number, and darker leaf coloration. In contrast, the MeCEPD-edited lines exhibited a statistically significant reduction in root length, plant height, and biomass compared to the wild-type. Additionally, nitrate deficiency accelerated leaf senescence. Furthermore, yeast two-hybrid (Y2H) assay revealed that MeCEPD interacts with the photosynthesis-related MeRBCS1A and lateral root development-related MeLHW, which may regulate nitrogen use efficiency. Unlike its Arabidopsis thaliana homologs AtCEPD1/2 and AtCEPDL2, which interact with AtTGA1/4, MeCEPD does not interact with MeTGA1 yet still upregulates MeNRT2.1 expression. These findings contribute to our understanding of the complex regulatory mechanisms underlying cassava’s adaptation to low-nitrogen conditions and could provide new information for genetic improvement in nitrogen use efficiency in cassava. Full article

This study evaluates the ability of three classification procedures to distinguish areas with different levels of atmospheric pollution, based on biomonitoring carried out by analyzing the color and spectral characteristics of mulberry (Morus L.) and linden (Tilia L.) leaves. Sampling was carried out in areas that were grouped into four classes according to the concentrations of fine particulate matter (PM2.5, PM10) and gaseous pollutants (TVOC, NOx, SOx, CO, and eCO₂), measured using a specialized multisensor device. A total of 57 informative features were analyzed, representing indices obtained from two color models (RGB and Lab), as well as from VIS and NIR spectral characteristics measured for the adaxial and abaxial leaf surfaces. The data processing methodology includes feature selection using the ReliefF method and a comparative analysis between two approaches to dimensionality reduction—principal components (PC) and latent variables (LV). The results indicate that data reduction using PC provides significantly higher accuracy and better class separability, regardless of the classifier used, compared to LV, where errors exceed 40%. The comparison between classifiers shows a clear superiority of nonlinear models. While linear discriminant analysis demonstrates low efficiency, quadratic discriminant analysis (Q and DQ) and SVM with radial basis function (RBF) achieve high accuracy of class separability, reaching 100% in the SVM-RBF model for both tree species. The study also reveals functional asymmetry: the adaxial side of the leaves is more informative for spectral indices, while the abaxial side is more sensitive to color changes. The results confirm that the combined optical characteristics obtained from the leaf surface of bioindicators form a reliable method for ecological monitoring of air quality in urban areas. Full article

In classical explicit Runge–Kutta methods for solving initial value problems (IVPs) of the form $y^{\prime }\left(x\right)=f(x,y),y\left(x_0\right)=y_0$, the first stage is typically given by evaluating the right-hand side at the initial point, i.e., $f_1=f(x_0,y_0)$. However, this approach becomes inefficient or even ill-posed when the $f(x_0,y_0)$ exhibits a singularity at $x_0$, as is common in many physically motivated problems such as the Lane–Emden equation or Thomas–Fermi model. To address this issue, we propose an alternative approach that was originally introduced by Oliver for low-order methods. In this formulation, the first stage is shifted away from the singular point and is instead evaluated at a shifted location: $f_1=f(x_0+c_1\tau ,y_0)$, where $\tau$ is the step size and $c_1\ne 0$ is a nonzero coefficient. This allows the method to bypass the singularity while preserving consistency with the IVP. We derive the corresponding order conditions for algebraic order six and construct an eight-stage scheme satisfying these constraints. The resulting method demonstrates significantly improved efficiency when applied to problems with initial-point singularities, outperforming classical Runge–Kutta pairs of orders $6\left(5\right)$ and even $8\left(7\right)$. Full article

Marijuana (Cannabis sativa L.) has a great economic potential due to its phytotherapeutic properties. Its propagation, however, faces numerous challenges due to the limited availability of standardized technical protocols for the crop. Vegetative propagation represents a, or even the, viable method for multiplying the genetically identical individuals while preserving their phytochemical profile, at lower costs and with shorter production times. This study investigated the morphological and colorimetric attributes associated with vegetative propagation success, aiming to develop sustainable cultivation strategies. Four cutting lengths (5, 10, 15 and 20 cm) were evaluated after 21 days of rooting, considering fresh mass, basal diameter, presence of apical meristem, number of root primordia, root length, and foliar and stem color parameters. Logistic regressions indicated that longer cuttings (p = 0.0101), greater fresh mass (p = 0.073) and the presence of apical meristem (p = 0.065), as well as greener leaves (p = 0.089), were positively associated with rooting probability (p < 0.10). Positive correlations between morphological and colorimetric variables were confirmed by Principal Component Analysis, with the first two principal components explaining 31.2% of the total variance in the dataset. The results provide support for the development of more efficient and low-cost vegetative propagation protocols, promoting uniformity and autonomy in local cutting production of marijuana. Full article

Fruit quality is determined by multiple metabolites, which are mainly affected by plant hormones. In this study, two genes, ethylene-related gene SlACO1 and gibberellin-related gene SlGARP, were overexpressed (OE) and knocked down through RNAi in tomato, and the profiles of carotenoids, flavonoids, volatiles, and hormones were detected in the leaves and fruit. The color index significantly increased in SlACO1-OE fruit but significantly decreased in the SlACO1-RNAi line. Similarly, total carotenoids, volatiles, salicylic acid, and ethylene significantly increased in the fruits of SlACO1-OE and SlGARP-OE, whereas ABA decreased significantly. Some compounds, such as lycopene, 3-hexenal, and d-limonene, significantly increased in the fruit of SlACO1-OE but decreased in the SlACO1-RNAi line, indicating that SlACO1 might play an important role in the accumulation of these compounds. The functional characterization of SlACO1 and SlGARP would facilitate the improvement in tomato fruit quality. Full article

Zanthoxylum bungeanum leaves (ZBL) are a phytogenic feed resource, but their energy value and functional effects in laying hens are not well defined. Two experiments were conducted. In Exp. 1, 96 healthy 38-week-old Roman Pink laying hens were allotted to either a control diet or a diet containing 5% ZBL (eight replicates, six hens per replicate) to determine apparent metabolizable energy (AME) using an indicator method (7 d adaptation, 3 d collection). The AME and nitrogen-corrected AME of ZBL were 5.46 and 5.33 MJ/kg, respectively. In Exp. 2, 832 healthy 41-week-old hens were randomly assigned to diets supplemented with 0, 1%, 2%, or 3% ZBL (8 replicates, 26 hens per replicate) for 8 weeks after 1 week adaptation. Dietary ZBL at 1% to 3% did not affect production performance (p > 0.05), but increased albumen height linearly (p < 0.05) and improved yolk color at 2% and 3% (p < 0.05). ZBL increased serum albumin (p < 0.05) with a linear tendency (p = 0.065), and elevated serum IgA and IgM linearly (p < 0.05). Serum total antioxidant capacity and total superoxide dismutase were increased (p < 0.05) with significant linear and quadratic responses (p < 0.05), while serum malondialdehyde was reduced (p < 0.05). In the liver, 3% ZBL increased total antioxidant capacity (p < 0.05), hepatic catalase activity was decreased in all ZBL groups (p < 0.05), and hepatic malondialdehyde was reduced (p < 0.05). Cecal acetate increased linearly (p < 0.05), and propionate and butyrate increased with both linear and quadratic dose responses (p < 0.05). ZBL improved small intestinal morphology, especially duodenal villus height (p < 0.05). Gut microbiota was remodeled, with a marked reduction in norank_o__WCHB1-41 and increases in Ruminococcus, Pseudoflavonifractor, and several Coriobacteriales and Erysipelatoclostridiaceae taxa. Overall, ZBL provides usable energy and, at 2–3% inclusion, enhances egg quality, antioxidant status, humoral immunity, short-chain-fatty-acid production, and intestinal health without compromising laying performance. Full article

Leaves are the primary photosynthetic organs, and alterations in leaf color can affect photosynthesis and plant biomass. In an EMS-mutagenized SN9816 population, we identified two white-striped mutants, ws21-1 and ws21-2. Both mutants showed severely reduced pigment content, defective chloroplasts, and elevated reactive oxygen species. The ws21-2 allele caused a near-complete albino phenotype, while ws21-1 resulted in milder striping. Genetic mapping and cloning identified causal mutations in OsRNRS1, encoding the small subunit of ribonucleotide reductase. The G583R (ws21-1) and Y365F (ws21-2) mutations likely impair enzyme activity, disrupting the dNTP pool for plastid genome replication and causing aberrant chloroplast development. Correspondingly, the expression of genes for chlorophyll synthesis, photosynthesis, and ROS metabolism was altered. Our findings directly link nuclear-encoded nucleotide metabolism to chloroplast biogenesis and demonstrate that dNTP homeostasis is critical for maintaining photosynthetic capacity and redox balance in plants. Full article

Tropaeolum majus L. is a popular ornamental plant. All parts of T. majus plant (flowers, leaves, and seeds) are edible and are appreciated for their pungent taste, although their chemical composition varies. T. majus is known for its many health benefits. It is a source of trace elements and bioactive compounds that are easily absorbed by the human body. The flowers of T. majus contain flavonoids from the flavone and flavonol groups, as well as their glycosides, which exhibit antibacterial, antifungal and antiviral activity. They also inhibit the activity of certain enzymes. Among the flavonoids, the flowers and leaves of T. majus contain derivatives of kaempferol and quercetin. Flavonoids also include anthocyanins, which are responsible for the color of T. majus flowers. In red flowers, delphinidin predominates; in orange flowers, pelargonidin; and in yellow flowers, pelargonidin and delphinidin are present in similar amounts. In the flowers of T. majus, seven carotenoids have been identified: violaxanthin, antheraxanthin, lutein, zeaxanthin, α, β and γ-carotene. In the leaves, however, lutein, violaxanthin, β-carotene and neoxanthin were detected. In T. majus, the presence of two glucosinolates has been reported: glucotropaeolin and sinalbin. The flowers and leaves of T. majus also contain both macroelements (N, P, K, Ca, Mg, Na) and microelements (Fe, Mn, Cu, Zn, Mo), and essential oils which have anti-cancer, antibacterial, and antiviral properties. The quality and flowering of T. majus are enhanced by fungi of the Trichoderma genus, which is important both ecologically and in terms of increasing the yield of raw material extracted from the plant. T. aureoviride, T. hamatum, and T. harzianum stimulated the flowering of the T. majus ‘Spitfire’. The plants treated with T. harzianum after being planted in pots flowered the most abundantly. Trichoderma spp. caused the plants to grow more intensively, producing longer and more leafy shoots with a greater number of offshoots. Trichoderma spp. stimulated the uptake of macronutrients, except for P. In the case of Ca and Na, this phenomenon was only observed in plants treated with T. aureoviride and T. hamatum, and for Mg, only when T. hamatum was applied to sown seeds. As for the developed root systems, as far as the micronutrients are concerned, Trichoderma spp. stimulated the uptake of Zn and Mn. Additionally, there was a higher Fe content in the plants treated with T. harzianum on both dates and T. aureoviride after planting the plants in pots. Full article

Background/Objectives: The biogenic synthesis of silver nanoparticles (AgNPs) is a promising alternative method, driven by the presence of metabolites in plant matrices capable of acting as reducing and stabilizing agents. Seasonality is a key factor that influences the phytochemical composition of plants and can directly impact the yield, physicochemical characteristics, stability, and bioactivities of the obtained AgNPs. This study aimed to synthesize AgNPs using aqueous extracts from Paullinia cupana leaves collected during dry and rainy seasons, prepared by two different methods (agitation or infusion), to evaluate the impact of these variables on the biosynthesis and properties of the nanostructures. Methods: The extracts were characterized by UHPLC-HRMS/MS, and their total phenolic compound (TPC) content and antioxidant potential against DPPH and ABTS radicals were determined. The AgNPs were characterized by UV/Vis spectrophotometry, dynamic light scattering (DLS), zeta potential (ZP), nano-particle tracking analysis (NTA), transmission electron microscopy (TEM), and energy-dispersive X-ray spectroscopy (EDX). Results: The metabolic profile results showed a predominance of alkaloids and flavonoids in all extracts, with greater phytochemical diversity in samples prepared by infusion. TPC indicated superior phenolic extraction in extracts prepared by infusion during the rainy season, correlating with greater antioxidant potential via the elimination of free radicals. The evolution of AgNP synthesis was accompanied by a gradual change in the color of the suspensions and the formation of plasmon bands between 410 and 430 nm, characteristic of spherical AgNPs. The nanostructures presented hydrodynamic diameters between 37.49 and 145.5 nm, PdI between 0.222 and 0.755, and Zeta potential between −11.3 and −39.9 mV, suggesting satisfactory colloidal stability. Morphological analyses revealed predominantly spherical particles with average diameters ranging from 33.61 to 48.86 nm and uniform distribution, while EDX spectra confirmed the presence of silver. Conclusions: Thus, our results demonstrate that both seasonality and the method of extract preparation influence the phytochemical composition and, consequently, the morphology, stability, and optical properties of AgNPs, with subtle emphasis on collections made during the rainy season and extracts prepared by infusion. Such knowledge contributes to the advancement of more reproducible and purpose-oriented syntheses in the field of green nanotechnology, enabling applications in various sectors. Full article

Nowadays, dried Moringa leaves (M. oleifera) are increasingly in demand due to their health benefits. High-quality ones have shown remarkable positive effects as antioxidants, antidiabetics, and anti-inflammatory agents. However, in the industry, the quality classification process into six categories is performed manually by farmers, which is time-consuming and error-prone. Particularly, the two highest categories of Class A and Class B are hard to distinguish, since they are visually similar. In this paper, to automate the classification process, we introduce a new high-resolution dataset, extract color and texture features using the Gray-Level Co-occurrence Matrix (GLCM) method, and present a two-stage classification method using the Light Gradient Boosting Machine (LightGBM) algorithm with them. The experimental results show that the proposal improved classification accuracy from 82% by the baseline algorithm to 90% while maintaining high processing efficiency, demonstrating its potential for real-time and scalable industrial applications in dried Moringa leaves quality grading. Full article