Search Results (12,067)

Phalaenopsis hybrids are the most popular potted flowers in flower markets worldwide because they exhibit various flower colors, including yellow, green, white and red-purple. A thorough assessment of petal color polymorphism in Phalaenopsis enables the promotion of mechanistic studies on floral coloration regulation. In this study, we collected 156 Phalaenopsis germplasms to assess their chromativity value (L*, a* and b*), and then divided them into six groups according to their petal color: white (21), green (11), yellow-orange (37), pink (40), purplish-red (25) and dark red (22). Significant correlations were detected between petal color chromaticity indices and both the total concentration and the compositional ratio of the two primary anthocyanin components: cyanidin 3,5-O-diglucoside (Cy3G5G) and delphinidin 3,5-O-diglucoside (Dp3G5G). The red petal phenotype was largely determined by high accumulations of Cy3G5G and Dp3G5G, as well as a high Cy3G5G/Dp3G5G ratio. By integrating CIELab color parameters with anthocyanin composition and gene expression analyses, a quantitative regulatory model for Phalaenopsis flower color was established. We have revealed that the phenotypic traits of high a* and low L* values are directly associated with the high expression of key structural genes (PhF3′H, PhDFR, PhF3′5′H). These results provide molecular markers and a screening basis for screening, enabling directional flower color breeding, and significantly enhancing the predictability and accuracy of breeding programs. Full article

This study presents the development of a natural hair dye based on Coreopsis tinctoria Nutt. plant extract with and without subsequent mordanting. The dye molecules behind the color development have been investigated to gain better understanding of the relationship between flavonoid structure and color on hair. Yak hair was dyed under different conditions and wash fastness tests were carried out to evaluate the performance of the new hair dye. Analysis of Coreopsis tinctoria Nutt. plant extract was performed to assess the chemical constitution of hair dye. Coreopsis tinctoria Nutt. extract solely led to yellow colors (as represented within L*a*b* color space: L* = 65.5; a* = 0.7; b* = 46.6), whereas the treatment combined with ferrous lactate led to dark brown colors (L* = 26.4; a* = 2.3; b* = 10.0). Wash fastness demonstrated a very good color stability with a maximum loss in color intensity of ΔE = 12.4 after 24 hair washes. Dyeing experiments using the most abundant flavonoids marein, flavanomarein, okanin, and isookanin gave insight into the responsible flavonoids for color outcome. In combination with ferrous lactate, chalcones led to brown colors and flavanones to gray colors. The chalcone okanin presented itself as the most powerful dye, leading to intense colors in combination with ferrous lactate (ΔE = 56.6), at low dye concentrations of 0.1 mg mL⁻¹. Full article

Self-incompatibility (SI) is an important plant mechanism that prevents inbreeding depression by recognizing and rejecting self-pollen, thereby promoting outcrossing. However, SI can also act as a barrier in breeding programs, presenting significant challenges to breeders. Passion fruit (Passiflora edulis), a tropical fruit species of substantial economic importance, also serves as a valuable system for investigating SI mechanisms within the Passifloraceae. Nevertheless, the molecular basis of SI in passion fruit has not yet been elucidated. In this study, we investigated the SI system in yellow passion fruit (P. edulis f. flavicarpa) and employed transcriptomic analysis to examine the time-course transcriptional responses following different pollination treatments. Transcriptomic analysis revealed distinct gene expression dynamics under different pollination treatments: self-pollinated samples exhibited stronger and earlier transcriptional changes, whereas the number of differentially expressed genes (DEGs) in cross-pollinated samples was relatively lower. Numerous pathways previously associated with sporophytic self-incompatibility (SSI) were enriched in the stigma samples after self-pollination. Reactive oxygen species (ROS) are crucial signaling molecules involved in pollen germination and pollen tube growth during SI responses. Our results showed that ROS-related pathways were enriched in stigma tissues after self-pollination. In addition, oxidative stress-related responses were detected in the style shortly after self-pollination, suggesting that plastid-associated or general oxidative stress processes may also be involved, although the precise source of ROS requires further validation. FERONIA, ROP9, and ARC1 are key genes related to the SI system in Brassica. In the passion fruit SI response, the expression levels of these genes increased in the style, indicating a spatial expression pattern different from that reported in classical Brassicaceae SSI systems. Together with cytological observations showing that self-pollen rejection occurs at the stigma surface, our results suggest that yellow passion fruit may employ an SSI-like regulatory framework while exhibiting a lineage-specific spatial deployment of SI-related regulators. Overall, this study provides new transcriptomic insights into the SI mechanism of yellow passion fruit, establishes a molecular framework for understanding SI in P. edulis f. flavicarpa, and offers novel insights into the diversity of plant SI systems. Full article

Smartphone colorimetry has emerged as a low-cost and accessible approach for participatory environmental monitoring. In this feasibility study, mangrove soil samples collected at two depths (approximately 0 and 30 cm) and three distances from the shoreline (−10, 0, and 10 m) were analyzed using smartphone colorimetry. The redness (a*) and yellowness (b*) tended to decrease from the seaward side toward the landward side. The lightness (L*) showed a strong agreement with measurements obtained from a standard spectrophotometer, whereas systematic deviations were observed for chromatic coordinates, with underestimation of a* and overestimation of b* by the smartphone measurements. Soil colors were further examined alongside mineral composition determined by X-ray fluorescence (XRF) and organic matter characteristics obtained from thermogravimetric analysis (TGA). No systematic relationships were identified between color parameters and mineral composition or organic matter weight loss, highlighting the complex and multi-factorial nature of mangrove soil color. Although wetting generally reduced L* and b* values, the responses to increasing water content were not monotonic. These findings indicate that smartphone colorimetry is effective for capturing relative variations in soil lightness under controlled conditions, while emphasizing the need for calibration and cautious interpretation. The accessibility of smartphone-based measurements also suggests potential in public engagement. Full article

Tomato yellow leaf curl virus (TYLCV) is one of the most destructive viral diseases causing severe yield losses in tomato production worldwide. This study investigated the effects of TYLCV infection on plant growth, photosynthetic physiological responses, and yield formation in greenhouse-grown tomatoes and evaluated the applicability of physiological trait-based yield prediction models. Two large-fruited tomato cultivars widely cultivated in Korean protected horticulture systems, ‘Daphnis’ and ‘Pink Star’, were inoculated with TYLCV under greenhouse conditions, and their growth, physiological responses, and yield characteristics were compared under high- and low-temperature growing seasons. TYLCV infection significantly reduced leaf length, leaf width, and leaf area index (LAI), and decreased both flowering truss number and fruit-setting truss number, resulting in reduced total yield. Physiological analyses showed that infected plants exhibited decreases in the OJIP fluorescence rise curve and Fv/Fm values, indicating a reduced photochemical efficiency in photosystem II. In addition, A–Ci response curve analysis revealed a reduction in net photosynthetic rate, suggesting limited carbon assimilation capacity. Total yield showed significant positive correlations with maximum net photosynthetic rate (Amax), Fv/Fm, and Ci300. GGE and GT biplot analyses further indicated that yield was closely associated with photosynthetic performance and canopy development traits. A multiple regression model based on physiological traits and virus infection status explained a significant proportion of the variation in tomato yield (R² = 0.367), indicating that TYLCV infection acts as a key limiting factor for yield reduction. These findings demonstrate that TYLCV infection restricts tomato productivity through reduced photosynthetic efficiency and altered canopy structure. Moreover, physiological trait-based yield prediction approaches may provide a useful framework for evaluating productivity under viral infection conditions and for developing data-driven crop management strategies in greenhouse tomato production systems. Full article

Down quality is the core evaluation indicator of thermal insulation products, and its grade determination strictly complies with the down content index specified in the national standard GB/T 17685-2016 Feather and Down. Traditional down quality inspection adopts manual sorting and weighing methods, which are plagued by low efficiency, strong subjectivity and high error rates, thereby restricting the intelligent upgrading of the down industry. This study aims to develop an automatic down detection and quantitative grading method conforming to national standards based on deep learning. A down dataset consisting of 632 RGB images is constructed, with each image containing 5–10 individual down samples and covering five categories: mature down clusters, immature down clusters, down filaments, feathers, and yellow-tail down. Three mainstream frameworks including YOLOv8, YOLOv11 and YOLOv26 are trained for performance comparison. Precision, recall, mAP@50 and mAP@50-95 are adopted as evaluation metrics. In addition, this paper proposes a research idea for down content calculation and automatic classification and grading of down quality in accordance with relevant national standards. The experimental results demonstrate that the latest models do not necessarily achieve the optimal performance. The newly released YOLOv26n and YOLOv26m exhibit relatively low accuracy in the down detection task, with mAP@50 values of only 0.98556 and 0.99077, and recall rates of 0.95032 and 0.97848, respectively, failing to outperform their previous-generation counterparts. In contrast, YOLOv11n achieves the best comprehensive performance, with an mAP@50 of 0.99416, a precision of 0.99544, a recall of 0.99722, and an mAP@50-95 of 0.63464. Meanwhile, the model has only 2.58 M parameters, a computational complexity of 6.3 GFLOPs, and a single training time of approximately 6.7 min, achieving an optimal balance between detection accuracy and computational efficiency. All models show the highest detection accuracy for mature down clusters and yellow-tailed down, while slight confusion exists between immature down clusters and down filaments. This study verifies the feasibility of the YOLO series models in down quality inspection in accordance with national standards, and reveals that model architecture iteration does not necessarily lead to performance improvement on specific industrial datasets. The lightweight and robustly designed YOLOv11n presents greater practical value. The intelligent detection scheme proposed in this paper can assist in optimizing the traditional manual quality inspection workflow, alleviating the burden of manual counting and reducing subjective errors. It provides new ideas and technical references for the rapid screening and objective determination of down quality. Furthermore, the proposed research framework for automatic classification and grading of down quality is expected to promote the development of down quality inspection toward standardization, intelligence, and automation in the future. Full article

Accurate, high-resolution irrigation-related spatial information is paramount to diverse applications, including water resources management, food security, and agricultural planning. To address this need, our study leveraged machine learning algorithms and integrated multi-source data to extract and analyze land use types and spatiotemporal dynamics of irrigated farmland across provinces in the lower reaches of the Yellow River Basin over the 2008–2022 period. The results indicate that cultivated land remained dominant and largely stable, although localized losses occurred in peri-urban areas due to urban expansion. Construction land increased significantly, particularly in Shandong where it expanded by more than 15%, while forest and grassland areas grew under national ecological programs. The Random Forest (RF) algorithm achieved robust performance in identifying irrigated farmland, with overall accuracy exceeding 85% and regression with statistical irrigation data yielding R² values above 0.9 over the past 15 years at the city level. Spatiotemporal analysis showed strong variability in Henan, with irrigated area declining by 8–12% during drought years and recovering in wetter years, while Shandong experienced relative stability but a gradual 5% decline since 2015, driven by groundwater depletion and stricter regulation. The findings suggest irrigation expansion has reached near-saturation, given stable cultivated land and continuous improvements in water use efficiency. Future strategies should prioritize water use efficiency, water saving technologies, and equitable allocation to ensure sustainable agricultural development. Full article

This study evaluated a post-cut treatment combining sanitization, carboxymethylcellulose (CMC) coating, and chokeberry pomace extract for preserving fresh-cut sweet peppers during 7 days of refrigerated storage. Sliced peppers of two cultivars, Sunny F₁ (yellow) and Yecla F₁ (red), were assigned to five treatments: water washing (control), BioActiW 2000 Food sanitizer (BAW), BAW followed by CMC coating (BAW + CMC), CMC coating with 3.5% chokeberry extract (CMC + AE), and 3.5% aqueous chokeberry extract (AAE). Samples were stored at 5 ± 1 °C and assessed for physicochemical, microbiological, sensory, and postharvest quality attributes. The response was cultivar-dependent. Coating-based treatments reduced polyphenol and L-ascorbic acid contents, although chokeberry-containing formulations mitigated these losses relative to BAW + CMC. Total sugars and carotenoids were not significantly affected. In both cultivars, BAW and BAW + CMC best limited mesophilic bacteria and yeast growth, reduced softening, and decreased weight loss. AAE applied without prior sanitization increased microbial counts in Sunny F₁. Sensory analysis showed cultivar-specific acceptance: Sunny F₁ tolerated CMC + AE and BAW + CMC better, whereas Yecla F₁ was more sensitive to off-flavors linked to the extract. These results indicate that sanitization is essential for microbiological stability, while CMC can provide an additional barrier effect. Chokeberry pomace extract showed mixed effects and appears to be a formulation component whose usefulness depends on cultivar and treatment conditions. Full article

The first yellow-leafed crabapple variety developed in China is Malus ‘Duojiao’. The light level affects its leaf color. (1) Background: Plants are frequently shaded by photovoltaic panels and green buildings. It is unknown how genetic regulation and partial shadowing regulate leaf color. (2) Methods: Four 28-day shading treatments were used for ‘Duojiao’ crabapple and its maternal ‘Xifu’ crabapple. Virus-induced gene silencing (VIGS), overexpression transgenic validation experiments, and physiological index analysis were employed to identify the expression levels of significant candidate genes. (3) Results: Improvements in chlorophyll synthesis, mineral metabolism, and antioxidant status were observed. The net photosynthetic rate was 39.29% higher under double-layer shade than in the control. (4) Conclusions: Partial double-layer shading exhibited the optimal effect. MsCPOX was the key gene controlling leaf color. Our results provide a theoretical basis for analyzing light responses and determining genes regulating leaf color in crabapple. Full article

Forest tourism represents an important pathway for promoting green consumption, with forest parks serving as the primary platform for its development. The coordinated development of forest parks is therefore essential for achieving integrated economic, social, and ecological benefits. Investigating the coordination and coupling between ecological resilience and tourism economy in forest parks of the Yellow River Basin along with driving factors carried substantial practical significance for balancing regional economic development with ecological conservation. The present research developed an indicator system that was comprehensive and dynamic for assessing ecological resilience across forest parks in nine provinces of the Yellow River Basin during 2013–2023. To investigate patterns of spatiotemporal evolution and uncover underlying driving mechanisms, exploratory spatial data analysis was combined with a spatiotemporal geographically weighted regression model. The main findings are as follows: (1) The integrated levels of ecological resilience and tourism economy across the Yellow River Basin showed significant spatiotemporal heterogeneity. From north to south, a high–low–high spatial pattern was exhibited by ecological resilience, while a core concentration and gradient diffusion pattern was demonstrated by the tourism economy. (2) The coupling coordination level between forest park ecosystems and the tourism economy increased, with a growing number of provinces transitioning toward coordinated and near–dysregulated states, although pronounced regional disparities persisted. (3) Kernel density analysis indicated an overall improvement in coordination, accompanied by strong regional differentiation. The upper reaches displayed a unipolar leading pattern, while the middle and lower reaches showed multipolar differentiation and a pronounced “Matthew effect”. (4) Technological innovation emerged as the core driving factor, though its influence varied considerably across regions. Overall, these findings provide theoretical support and empirical evidence for policy formulation aimed at achieving a balance between ecological conservation and economic development in forest park systems. Full article

In this paper, we present the result of the study conducted on aging tests carried out by the artist Emile Claus (1849–1924), composed of oil paint samples from three manufacturers: Blockx, Lefranc Bourgeois and Fritz Behrendt. These colors were applied neat and mixed with white on wooden panels prepared with white ground layer. A non-invasive analytical protocol, combining imaging techniques and physico-chemical analyses, was used to characterize potential differences between manufacturers for nominally identical colors. The differences highlight in this study include variations in nickel content in cobalt blue colors and aluminum content in madder lakes. It also discusses the intrinsic and extrinsic factors that led to the degradation of certain colors. Hyperspectral imaging further demonstrated that the addition of lead white induces a systematic shift of spectral inflection points toward shorter wavelengths, consistent with the optical dilution effect in pigment-white mixtures, while the altered colors do not follow the same trend. Full article

The Source Region of the Yellow River (YRSR) is a key ecological barrier and a major water supply area, where water conservation is highly sensitive to ongoing climate change (CC) and land use/cover change (LUCC). However, the relative roles of CC and LUCC in regulating water conservation remain insufficiently quantified. In this study, we applied the Soil and Water Assessment Tool (SWAT) to simulate the spatiotemporal dynamics of water conservation in the YRSR and to disentangle the respective contributions of CC and LUCC using a fixing–changing approach, in which one driver is fixed and the other is varied across paired scenarios, followed by projections driven by CMIP6 forcing under SSP2–4.5 and SSP5–8.5. Water conservation showed a pronounced southeast–northwest contrast and increased over 2000–2019 (+4.56 mm/year). Attribution analysis revealed that CC dominated changes in water conservation, whereas LUCC exerted a weak net negative influence. Most increasing regions were precipitation-driven, whereas declining regions were concentrated where evapotranspiration and surface runoff increased concurrently. Under SSP2–4.5, water conservation is projected to continue increasing (+1.16 mm/year). In contrast, under SSP5–8.5, water conservation is projected to slightly decline (−0.26 mm/year). These findings highlight the primary role of climate in regulating water conservation in the YRSR and provide scientific support for adaptive watershed management under a changing climate. Full article

Eye care and eyewear centers now offer glasses designed for individuals with color vision deficiencies (CVDs). The present work involves a detailed analysis of the optical properties of glasses enhancing color discrimination in individuals with red CVD known as protanopia. Eleven models of such glasses with optical filters were subjected to spectrophotometric studies to determine parameters such as luminous transmittance in the spectral range of 380–780 nm (mean values for daylight and night vision), signal light transmittance, and reduction quotients for red, yellow, green, and blue signal lights. The light sources included traditional incandescent illuminants and LEDs. Analysis of spectrophotometric results indicates that the use of the studied glasses may impair blue-green discrimination. An experiment on a human subject was conducted to evaluate the application feasibility of such glasses for the performance of tasks involving discrimination between blue and green colors. This study should be treated as a proof-of-concept or pilot investigation. A purpose-built system providing additional illumination of the observed objects with white, blue, and green light was also used. The experimental results were consistent with the findings of the spectrophotometric study. It was shown that the use of glasses enhancing color discrimination by individuals diagnosed with protanopia may prevent blue-green discrimination, which has significant implications for the performance of tasks involving color-coded information. In particular, this concerns color-based comparative applications involving gradable or absolute evaluations as to whether the colors in question are identical. It was found that the illumination of test objects with green or blue light during experiments restored blue-green discrimination ability in a human subject wearing glasses designed for individuals with red CVD. Full article

Tomato is widely produced in Burkina Faso for its culinary, nutritional, and economic value. Tens of thousands of farmers are involved in its production throughout the country. However, they face significant biotic constraints that limit yields and income. In particular, tomato yellow leaf curl virus (TYLCV), a begomovirus transmitted by whiteflies (Bemisia tabaci), severely affects tomato production. This study evaluated the response of 13 tomato genotypes to tomato yellow leaf curl disease (TYLCD), including eight lines with different Ty resistance gene combinations; three local improved varieties, and two commercial varieties in western and central Burkina Faso. All genotypes developed TYLCD symptoms with considerable variability in genotypic responses. Four genotypes carrying a single gene, namely CLN4279O (Ty2), CLN4270I (Ty1/Ty3), CLN4270F (Ty1/Ty3), and CLN4018G (Ty2), exhibited the best field tolerance, with lower disease incidence and severity across sites. In contrast, genotype CLN4078A carrying two resistance genes (Ty1/Ty3 + Ty2), and the checks PETOMECH and ROMA VF were highly susceptible. Hierarchical clustering grouped the genotypes into four classes based on tolerance level and yield. These findings highlight the variability in resistance expression under field conditions and suggest possible interactions between host genotype, environmental factors, and virus populations. Broader multi-site evaluations, supported by molecular diagnostics to identify endemic TYLCV strains, are needed to refine the selection process. Full article

Groundwater storage is vital for managing water resources, especially as global water scarcity intensifies. Estimating groundwater levels regionally is challenging due to natural heterogeneity. We employed a large groundwater observation sample, along with Global Land Data Assimilation System (GLDAS) and Gravity Recovery and Climate Experiments (GRACE) datasets, to develop a random forest model for predicting groundwater levels in China’s Yellow River Basin. The model showed robustness, achieving an R² of 0.95 in calibration and an R² of 0.91 ± 0.009 in 10-fold cross-validation with 100 repetitions. Temporal predictability was lower, with an R² of 0.72 for April–May 2023; however, the temporal prediction is preliminary and limited by the short validation period (April–May 2023), which should be interpreted with caution. Spatial maps revealed significant seasonal declines in fall and winter, particularly in the middle and lower reaches. This study highlights the potential of machine learning with extensive observations to estimate regional groundwater levels and supports groundwater analysis with robust data. Full article