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16 pages, 9025 KiB  
Article
Ozonation of Popcorn Kernels: Saturation Kinetics at Different Specific Flow Rates, Control of Aspergillus flavus Infection, and Grain Quality Analysis
by Marcus Vinícius Assis Silva, Lêda Rita D’Antonino Faroni, Ernandes Rodrigues de Alencar, José Marcelo Soriano Viana, Eugénio da Piedade Edmundo Sitoe, Davi Vittorazzi Salvador, Vivaldo Mason Filho and Carollayne Gonçalves Magalhães
Foods 2024, 13(20), 3301; https://doi.org/10.3390/foods13203301 (registering DOI) - 17 Oct 2024
Abstract
Ozone gas (O3) is a promising alternative for fungal inactivation in agricultural commodities. This study aimed to (i) investigate the influence of airflow on the saturation of popcorn kernels with ozone gas, (ii) evaluate its effectiveness in controlling Aspergillus flavus, [...] Read more.
Ozone gas (O3) is a promising alternative for fungal inactivation in agricultural commodities. This study aimed to (i) investigate the influence of airflow on the saturation of popcorn kernels with ozone gas, (ii) evaluate its effectiveness in controlling Aspergillus flavus, and (iii) analyze the quality of ozonated grains. Samples of 3.0 kg of kernels were exposed to oxygen (control) or ozone at specific flow rates of 0.15 or 1.00 m3 min−1 t−1, with an input ozone concentration of 16.0 mg L−1 for 0, 6, 12, 24, 36, or 48 h. Quality parameters assessed included expansion volume, water content, electrical conductivity, and color. At 0.15 m3 min−1 t−1, ozone consumption and saturation time were lower, with an 80% reduction in A. flavus infection after 6 h. This flow rate did not affect grain expansion or water content. Conversely, at 1.0 m3 min−1 t−1, reductions in water content and expansion were observed with extended exposure. Electrical conductivity increased in both treatments, more significantly at the lower flow rate. In conclusion, ozonation at 0.15 m3 min−1 t−1 effectively inactivated A. flavus without compromising grain quality. Full article
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Figure 1
<p>Prototype for popcorn kernel treatment with ozone gas displaying the arrangement of the containers with <span class="html-italic">A. flavus</span>-contaminated kernels within the grain mass (<b>a</b>). Longitudinal view with dimensions; the hatched area corresponds to the grain mass (<b>b</b>).</p>
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<p>Residual ozone gas concentration as a function of time during the saturation of popcorn kernels (<b>a</b>) and ozone consumption by the grain mass (<b>b</b>), considering an input concentration of 16 mg L<sup>−1</sup> and specific flow rates of 0.15 and 1.00 m<sup>3</sup> min<sup>−1</sup> t<sup>−1</sup>.</p>
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<p>Percentage of <span class="html-italic">A. flavus</span> infection in popcorn kernels as a function of the exposure duration to ozone gas at different specific flow rates, considering grains with surface disinfection (<b>a</b>) and grains without surface disinfection (<b>b</b>).</p>
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<p>This direct plating of popcorn kernels exposed to ozone or oxygen (control) for different exposure periods and at different flow rates of ozone gas.</p>
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<p>Expansion volume (<b>a</b>), flake volume (<b>b</b>), and unpopped kernel percentage (<b>c</b>) as a function of ozone or oxygen exposure at different exposure periods.</p>
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<p>Water content (<b>a</b>) and electrical conductivity (<b>b</b>) of popcorn kernels as a function of the exposure period to ozone gas.</p>
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<p>Popcorn flakes exposed to ozone or oxygen for different durations and flow rates.</p>
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16 pages, 1218 KiB  
Article
Active Modified Atmosphere Packaging Helps Preserve Quality of Edible Flowers
by Nicole Mélanie Falla, Negin Seif Zadeh, Stefania Stelluti, Valentina Guarino, Manuela Giordano, Vladimiro Cardenia, Giuseppe Zeppa and Valentina Scariot
Agronomy 2024, 14(10), 2409; https://doi.org/10.3390/agronomy14102409 - 17 Oct 2024
Abstract
Edible flowers are becoming increasingly popular as food products, since they give aroma, color, and visual appeal and are also health-promoting compounds. However, they are a highly perishable product, thus post-harvest technologies are needed to extend their marketability. In this study, active (N [...] Read more.
Edible flowers are becoming increasingly popular as food products, since they give aroma, color, and visual appeal and are also health-promoting compounds. However, they are a highly perishable product, thus post-harvest technologies are needed to extend their marketability. In this study, active (N2: 100%) and passive modified atmosphere packaging (MAP) technologies were applied to three edible flower species, namely Begonia grandiflora ‘Viking’, Tropaeolum majus, and Viola cornuta, stored at 4 °C. Even if the flowers’ quality decay occurred differently according to the species, active MAP better maintained petal colors and slowed down the edible flowers’ decay than passive MAP by decreasing flower respiration in all three species and sugars consumption in begonia; there was weight loss in nasturtium, and better preserved total phenolic content in begonia and viola. Coupling cold storage with active MAP can be an effective method to extend edible flowers’ post-harvest life. Full article
20 pages, 1856 KiB  
Article
Advances in Liquid-Phase Synthesis: Monitoring of Kinetics for Platinum Nanoparticles Formation, and Pt/C Electrocatalysts with Monodispersive Nanoparticles for Oxygen Reduction
by Vladimir Guterman, Kirill Paperzh, Irina Novomlinskaya, Ilya Kantsypa, Alina Khudoley, Yana Astravukh, Ilya Pankov and Alexey Nikulin
Catalysts 2024, 14(10), 728; https://doi.org/10.3390/catal14100728 - 17 Oct 2024
Abstract
The growing demand for hydrogen–air fuel cells with a proton-exchange membrane has increased interest in the development of scalable technologies for the synthesis of Pt/C catalysts that will allow us to fine-tune the microstructure of such materials. We have developed a new in [...] Read more.
The growing demand for hydrogen–air fuel cells with a proton-exchange membrane has increased interest in the development of scalable technologies for the synthesis of Pt/C catalysts that will allow us to fine-tune the microstructure of such materials. We have developed a new in situ technique for controlling the kinetics of the transformation of a platinum precursor into its nanoparticles and deposited Pt/C catalysts, which might be applicable during the liquid-phase synthesis in concentrated solutions and carbon suspensions. The technique is based on the analysis of changes in the redox potential and the reaction medium coloring during the synthesis. The application of the developed technique under conditions of scaled production has made it possible to obtain Pt/C catalysts with 20% and 40% platinum loading, containing ultra-small metal nanoparticles with a narrow size distribution. The electrochemically active surface area of platinum and the mass activity of synthesized catalysts in the oxygen electroreduction reaction have proved to be significantly higher than those of commonly used commercial analogs. At the same time, despite the small size of nanoparticles, the catalysts’ degradation rate turned out to be the same as that of commercial analogs. Full article
(This article belongs to the Section Catalytic Materials)
25 pages, 1749 KiB  
Article
Exploration of the Bioactivity of Pigmented Extracts from Streptomyces Strains Isolated Along the Banks of the Guaviare and Arauca Rivers (Colombia)
by Aixa A. Sarmiento-Tovar, Sara J. Prada-Rubio, Juliana Gonzalez-Ronseria, Ericsson Coy-Barrera and Luis Diaz
Fermentation 2024, 10(10), 529; https://doi.org/10.3390/fermentation10100529 - 17 Oct 2024
Abstract
Pigments are chemical compounds that impart color through mechanisms such as absorption, reflection, and refraction. While traditional natural pigments are derived from plant and insect tissues, microorganisms, including bacteria, yeasts, algae, and filamentous fungi, have emerged as promising sources for pigment production. In [...] Read more.
Pigments are chemical compounds that impart color through mechanisms such as absorption, reflection, and refraction. While traditional natural pigments are derived from plant and insect tissues, microorganisms, including bacteria, yeasts, algae, and filamentous fungi, have emerged as promising sources for pigment production. In this study, we focused on pigment production by 20 Streptomyces isolates from our in-house actinobacteria strain collection, sourced from the Guaviare and Arauca Rivers in Colombia. The isolates were identified via 16S rRNA gene sequencing, and the bioactivities—including antioxidant, antibacterial, and cytotoxic properties—of their extracts obtained across four different culture media were assessed. Promising pigmented hydroalcoholic extracts demonstrating these bioactivities were further analyzed using LC-MS, leading to the annotation of a variety of pigment-related compounds. This study revealed that culture media significantly influenced both pigment production and bioactivity outcomes. Notably, anthraquinones, phenazines, and naphthoquinones were predominant pigment classes associated with cytotoxic and antimicrobial activities, while carotenoids were linked to antioxidant effects. For instance, S. murinus 4C171 produced various compounds exhibiting both cytotoxic and antioxidant activities. These findings highlighted a growth medium-dependent effect, as pigment production, coloration, and bioactivity outcomes were influenced by growth media. These results demonstrate the significant potential of Streptomyces isolates as sources of bioactive pigments for diverse applications. Full article
(This article belongs to the Special Issue Pigment Production in Submerged Fermentation: Second Edition)
12 pages, 1868 KiB  
Article
Artificial Intelligence and Machine Learning in Ocular Oncology, Retinoblastoma (ArMOR): Experience with a Multiracial Cohort
by Vijitha S. Vempuluru, Rajiv Viriyala, Virinchi Ayyagari, Komal Bakal, Patanjali Bhamidipati, Krishna Kishore Dhara, Sandor R. Ferenczy, Carol L. Shields and Swathi Kaliki
Cancers 2024, 16(20), 3516; https://doi.org/10.3390/cancers16203516 - 17 Oct 2024
Abstract
Background: The color variation in fundus images from differences in melanin concentrations across races can affect the accuracy of artificial intelligence and machine learning (AI/ML) models. Hence, we studied the performance of our AI model (with proven efficacy in an Asian-Indian cohort) in [...] Read more.
Background: The color variation in fundus images from differences in melanin concentrations across races can affect the accuracy of artificial intelligence and machine learning (AI/ML) models. Hence, we studied the performance of our AI model (with proven efficacy in an Asian-Indian cohort) in a multiracial cohort for detecting and classifying intraocular RB (iRB). Methods: Retrospective observational study. Results: Of 210 eyes, 153 (73%) belonged to White, 37 (18%) to African American, 9 (4%) to Asian, 6 (3%) to Hispanic races, based on the U.S. Office of Management and Budget’s Statistical Policy Directive No.15 and 5 (2%) had no reported race. Of the 2473 images in 210 eyes, 427 had no tumor, and 2046 had iRB. After training the AI model based on race, the sensitivity and specificity for detection of RB in 2473 images were 93% and 96%, respectively. The sensitivity and specificity of the AI model were 74% and 100% for group A; 88% and 96% for group B; 88% and 100% for group C; 73% and 98% for group D, and 100% and 92% for group E, respectively. Conclusions: The AI models built on a single race do not work well for other races. When retrained for different races, our model exhibited high sensitivity and specificity in detecting RB and classifying RB. Full article
(This article belongs to the Collection Artificial Intelligence and Machine Learning in Cancer Research)
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Figure 1
<p>Overview of the methodology employed.</p>
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<p>Fundus photograph with subtle retinoblastoma (arrow).</p>
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<p>The three-step process employed in image processing. Illustration of the original image (<b>A</b>) that was pre-processed (<b>B</b>) to ensure uniformity in the identification of blood vessels/hemorrhages across races (<b>C</b>). Further, features such as the area covered by the tumor (<b>D</b>) were computed for grouping.</p>
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<p>Performance metrics of the AI model for detection and classification of RB depicted as matrices for 2473 images and 210 eyes.</p>
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<p>The AI model. The AI model detects optic disc (green bounding box with % confidence) and retinoblastoma (blue bounding box with % confidence) in ICRB groups A (<b>A</b>–<b>C</b>), B (<b>D</b>–<b>F</b>), C (<b>G</b>–<b>I</b>), D (<b>J</b>–<b>L</b>), and E (<b>M</b>–<b>O</b>) in White, African American, Hispanic, and Asian-Indian races.</p>
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16 pages, 16550 KiB  
Article
Melatonin Rinsing Treatment Associated with Storage in a Controlled Atmosphere Improves the Antioxidant Capacity and Overall Quality of Lemons
by Mengjiao Yang, Enlan Zheng, Ziqin Lin, Ze Miao, Yuhang Li, Shiting Hu, Yanan Gao, Yuqian Jiang, Lingling Pang and Xihong Li
Foods 2024, 13(20), 3298; https://doi.org/10.3390/foods13203298 - 17 Oct 2024
Abstract
Antioxidant capacity is one of the most important biological activities in fruits and vegetables and is closely related to human health. In this study, ‘Eureka’ lemons were used as experimental materials and stored at 7–8 °C MT (melatonin, 200 μmol, soaked for 15 [...] Read more.
Antioxidant capacity is one of the most important biological activities in fruits and vegetables and is closely related to human health. In this study, ‘Eureka’ lemons were used as experimental materials and stored at 7–8 °C MT (melatonin, 200 μmol, soaked for 15 min) and CA (controlled atmosphere, 2–3% O2 + 15–16% CO2) individually or in combination for 30 d. The changes in lemon fruits’ basic physicochemical properties, enzyme activities, and antioxidant capacities were studied. Comparing the combined treatment to the control, the outcomes demonstrated a significant reduction in weight loss, firmness, stomatal opening, and inhibition of polyphenol oxidase (PPO) and peroxidase (POD) activities. Additionally, the combined treatment maintained high levels of titratable acidity (TA), vitamin C (VC), total phenolic content (TPC), and antioxidant capacity and preserved the lemon aroma. Meanwhile, the correlation between fruit color, aroma compounds, and antioxidant capacity was revealed, providing valuable insights into the postharvest preservation of lemons. In conclusion, the combined treatment (MT + CA) was effective in maintaining the quality and antioxidant capacity of lemons. Full article
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<p>The visual appearance of lemons treated with MT and/or CA.</p>
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<p>Basic physicochemical properties of MT or/and CA-treated lemons during 30 d of cold storage at 7–8 °C versus control. (<b>A</b>) Weight loss; (<b>B</b>) SSC; (<b>C</b>) peel hardness; (<b>D</b>) flesh hardness; (<b>E</b>) TA; (<b>F</b>) VC. Values represent means ± SD in triplicate, and different letters denote significant differences compared to the control during the same storage time at the <span class="html-italic">p</span> &lt; 0.05 level.</p>
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<p>Effects of MT, CA, or combined treatments on ROS production and membrane peroxidation compared with the control within the same storage time. (<b>A</b>) TPC, (<b>B</b>) DPPH scavenging capacity, (<b>C</b>) H<sub>2</sub>O<sub>2</sub>, (<b>D</b>) CAT activity. Values were expressed in the mean ± SD (n = 3), and different letters suggest significant differences within different treatments compared with control at <span class="html-italic">p</span>  &lt;  0.05.</p>
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<p>Changes in enzyme activities and membrane peroxidation in MT or/and CA-treated lemons during 30 d of cold storage at 7–8 °C versus control. (<b>A</b>) POD; (<b>B</b>) PPO; (<b>C</b>) PAL; (<b>D</b>) MDA. Values represent means ± SD in triplicate, and different letters indicate significant differences at the <span class="html-italic">p</span> &lt; 0.05 level compared with the control during the same storage time.</p>
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<p>E-nose sensing on volatile organic compounds from MT, CA-treated, or mixed-treated lemons during storage at 7–8 °C compared to control. (<b>A</b>) E-nose sensing profiles on day 0, (<b>B</b>) day 5, (<b>C</b>) day 15, and (<b>D</b>) day 30. W1C: Aromatic, benzene; W5S: Broad range, oxynitride; W3C: Aromatic, ammoniac compounds; W6S: Hydrogen, hydride; W5C: Arom-aliph; W1S: Broad-methane; W1W: Sulfur-organic; W2S: Broad-alcohol; W2W: Sulph-chlor; W3S: Methane-aliph.</p>
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<p>SEM images of MT and/or CA-treated lemon fruits stored at 7–8 °C for 30 d stomata compared to control. The SEM used an analytical mode of secondary electrons with a magnification of 2.00 k, a spot size of 2.00 k × 20.0 μm–30.0 μm, and a working distance of 9.5 mm.</p>
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<p>Pearson correlation coefficients for lemon quality traits, including Chroma c*, Chlorophyll, weight loss, SSC, peel hardness, flesh hardness, TA, VC, POD, PPO, PAL, MDA, TPC, DPPH scavenging capacity, H<sub>2</sub>O<sub>2</sub>, CAT, and the following volatile substances: Aromatic (benzene), Broad alcohol, Arom-aliph, Broad oxynitride. Red and blue dots are positive and negative correlations, respectively, and the number shown is the correlation coefficient.</p>
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22 pages, 3101 KiB  
Article
Optimized Proportioning Techniques and Roadway Performance Evaluation of Colored Asphalt Pavement Materials
by Silin Fan, Shaopeng Zheng, Jian Ma, Liangliang Chen, Xiao Li and Cheng Cheng
Sustainability 2024, 16(20), 8996; https://doi.org/10.3390/su16208996 - 17 Oct 2024
Abstract
This study systematically investigated the formulation optimization, performance evaluation, and practical application of epoxy-based composite materials for colored asphalt pavement. By conducting comprehensive experiments, we optimized the composition of epoxy-based composites, verifying their excellent bonding performance, good heat resistance, and UV aging resistance [...] Read more.
This study systematically investigated the formulation optimization, performance evaluation, and practical application of epoxy-based composite materials for colored asphalt pavement. By conducting comprehensive experiments, we optimized the composition of epoxy-based composites, verifying their excellent bonding performance, good heat resistance, and UV aging resistance under various temperature conditions. The key optimized component ratios were determined as a 1:1 blend of Type I and Type II epoxy resins, 30 phr of curing agent, 10 phr of toughening agent, 5 phr of diluent, 10% filler, 12% flame retardant, and 10% pigment. At the recommended dosage of 2.0 kg/m2 of epoxy binder, the composite structure exhibited the best reinforcement effect, improving low-temperature performance significantly. Compared to ordinary asphalt mixtures, the colored pavement composite structure showed superior mechanical strength, deformation capacity, high-temperature stability (dynamic stability approximately three times higher), and water stability (TSR values up to 95.5%). Furthermore, its fatigue life decay rate was significantly lower, with fatigue limit loading frequencies more than three times those of ordinary asphalt mixtures, demonstrating excellent fatigue resistance. This study provides strong technical support and a theoretical basis for the development and practical application of colored asphalt pavement. Full article
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<p>Relationship between curing agent content and tensile properties.</p>
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<p>Relationship between the amount of toughener and tensile properties.</p>
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<p>Relationship between the amount of diluent and tensile properties and viscosity.</p>
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<p>The relationship between the amount of flame retardant and tensile properties.</p>
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<p>Dumbbell-shaped specimen after pouring.</p>
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<p>Tensile experiment.</p>
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<p>Results of epoxy binder pull-out tests with different paving amounts.</p>
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<p>Tensile and shear test results of epoxy binders at different curing temperatures.</p>
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<p>Rutting test results.</p>
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<p>Comparison of load stress between control group and color pavement fatigue test.</p>
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18 pages, 3908 KiB  
Article
Identification of New Cultivar and Different Provenances of Dendrocalamus brandisii (Poaceae: Bambusoideae) Using Simple Sequence Repeats Developed from the Whole Genome
by Ruiman Geng, Junlei Xu, Jutang Jiang, Zhanchao Cheng, Maosheng Sun, Nianhe Xia and Jian Gao
Plants 2024, 13(20), 2910; https://doi.org/10.3390/plants13202910 - 17 Oct 2024
Abstract
Dendrocalamus brandisii is a high-quality bamboo species that can be used for both bamboo shoots and wood. The nutritional components and flavors of D. brandisii vary from different geographical provenances. However, the unique biological characteristics of bamboo make morphological classification methods unsuitable for [...] Read more.
Dendrocalamus brandisii is a high-quality bamboo species that can be used for both bamboo shoots and wood. The nutritional components and flavors of D. brandisii vary from different geographical provenances. However, the unique biological characteristics of bamboo make morphological classification methods unsuitable for distinguishing them. Although the new cultivar ‘Manxie No.1’ has significant differences in the branch characteristics and the color of shoot sheaths compared to the D. brandisii, it still lacks precise genetic information at the molecular level. This study identified 231,789 microsatellite markers based on the whole genome of D. brandisii and analyzed their type composition and distribution on chromosomes in detail. Then, using TP-M13-SSR fluorescence-labeling technology, 34 pairs of polymorphic primers were screened to identify the new cultivar ‘Manxie No.1’ and 11 different geographical provenances of D. brandisii. We also constructed DNA fingerprinting profiles for them. At the same time, we mapped six polymorphic SSRs to the gene of D. brandisii, among which SSR673 was mapped to DhB10G011540, which is related to plant immunity. The specific markers selected in this study can rapidly identify the provenances and the new cultivar of D. brandisii and help explore candidate genes related to some important traits. Full article
(This article belongs to the Special Issue The Genetic Architecture of Bamboo Growth and Development)
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<p>The proportion of different types of microsatellites. (<b>A</b>) The number and proportion of different types of microsatellites. The black numbers and corresponding shapes represent the number and proportion of single and composite SSRs in all SSRs. The gray numbers and corresponding shapes represent the number and proportion of different types of perfect SSRs in all perfect SSRs. (<b>B</b>) Trends in the number of perfect SSRs with different repetitive motifs.</p>
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<p>Changes in the content of 2–6 nt motifs with different repetitions. The horizontal axis represents the number of repetitions of 2–6 nt motifs; the vertical axis represents the proportion of a certain type of motif with a certain number of repetitions.</p>
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<p>Localization of SSR on the <span class="html-italic">Dendrocalamus brandisii</span> chromosome. (<b>A</b>) The proportion of SSRs successfully located on chromosomes. (<b>B</b>) The proportion of SSR on 70 chromosomes. The right side of the two orange arrows represents the number of SSRs on DbrChrA01–A35 in a clockwise direction, while the left side of the two orange arrows represents the number of SSRs on DbrChrB01–B35 in a clockwise direction. (<b>C</b>) Localization of SSRs on the 5’UTR, 3’UTR, exon, intron, intergenic, and multi-mapped <span class="html-italic">D. brandisii</span>. (<b>D</b>) The distribution of SSR on 70 chromosomes of <span class="html-italic">D. brandisii</span>.</p>
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<p>Diagram of cis-acting elements in the promoters of <span class="html-italic">DhB21G011140</span>, <span class="html-italic">DhB31G002880</span>, <span class="html-italic">DhB31G019250</span>, <span class="html-italic">DhA19G015160</span>, <span class="html-italic">DhA19G013950</span>, and <span class="html-italic">DhB10G011540</span>.</p>
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<p>Cluster analysis of 12 materials based on SSR markers. * represents Cangyuan County, Lincang City, Yunnan Province, China, and ** represents Linxiang District, Lincang City, Yunnan Province, China.</p>
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<p>DNA fingerprinting of 12 materials constructed based on 34 pairs of SSR primers. On the right side of the image is the information of 12 materials, with the SSR name above. The number below the image represents the size of all fragments that the corresponding SSR can amplify. Blue and gray, respectively, represent the presence or absence of fragments. * represents Cangyuan County, Lincang City, Yunnan Province, China, and ** represents Linxiang District, Lincang City, Yunnan Province, China.</p>
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<p>Sampling site labeling diagram for 11 samples of <span class="html-italic">D. brandisii</span> and 1 sample of ‘Manxie No.1’. The figure above shows the location of the sampling sites on a world map. In the figure below, green, red, blue, and purple represent the sampling sites in Yunnan Province, China; Guangdong Province, China; Yenbai Province, Vietnam; and Chiang Mai Province, Thailand.</p>
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19 pages, 15466 KiB  
Article
Transcriptomic Analysis Reveals the Mechanism of Color Formation in the Peel of an Evergreen Pomegranate Cultivar ‘Danruo No.1’ During Fruit Development
by Xiaowen Wang, Chengkun Yang, Wencan Zhu, Zhongrui Weng, Feili Li, Yuanwen Teng, Kaibing Zhou, Minjie Qian and Qin Deng
Plants 2024, 13(20), 2903; https://doi.org/10.3390/plants13202903 - 17 Oct 2024
Abstract
Pomegranate (Punica granatum L.) is an ancient fruit crop that has been cultivated worldwide and is known for its attractive appearance and functional metabolites. Fruit color is an important index of fruit quality, but the color formation pattern in the peel of [...] Read more.
Pomegranate (Punica granatum L.) is an ancient fruit crop that has been cultivated worldwide and is known for its attractive appearance and functional metabolites. Fruit color is an important index of fruit quality, but the color formation pattern in the peel of evergreen pomegranate and the relevant molecular mechanism is still unknown. In this study, the contents of pigments including anthocyanins, carotenoids, and chlorophyll in the peel of ‘Danruo No. 1’ pomegranate fruit during three developmental stages were measured, and RNA-seq was conducted to screen key genes regulating fruit color formation. The results show that pomegranate fruit turned from green to red during development, with a dramatic increase in a* value, indicating redness and anthocyanins concentration, and a decrease of chlorophyll content. Moreover, carotenoids exhibited a decrease–increase accumulation pattern. Through RNA-seq, totals of 30, 18, and 17 structural genes related to anthocyanin biosynthesis, carotenoid biosynthesis and chlorophyll metabolism were identified from differentially expressed genes (DEGs), respectively. Transcription factors (TFs) such as MYB, bHLH, WRKY and AP2/ERF were identified as key candidates regulating pigment metabolism by K-means analysis and weighted gene co-expression network analysis (WGCNA). The results provide an insight into the theory of peel color formation in evergreen pomegranate fruit. Full article
(This article belongs to the Special Issue Recent Advances in Horticultural Plant Genomics)
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Figure 1
<p>Coloration and pigment contents in ‘Danruo No.1’ pomegranate peel during fruit development. (<b>A</b>) Representative images of fruits at developmental stage 1 (S1), stage 2 (S2), and stage 3 (S3). (<b>B</b>) Fruit peel lightness (<span class="html-italic">L*</span> value). (<b>C</b>) Fruit peel <span class="html-italic">a*</span> value (higher value means redness and lower value means greenness). (<b>D</b>) Fruit peel <span class="html-italic">b*</span> value (higher value means yellowness and lower value means blueness). (<b>E</b>) Chlorophyll a content. (<b>F</b>) Chlorophyll b content. (<b>G</b>) Total chlorophyll content. (<b>H</b>) Anthocyanin content. (<b>I</b>) Carotenoid content. Each value represents the mean ± standard deviation of three biological replicates. Different letters above the bars indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) according to one-way analysis of variance (ANOVA) followed by Tukey test.</p>
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<p>Differentially expressed genes (DEGs) identification and KEGG analysis. Volcano plots of DEGs from S2 vs. S1 (<b>A</b>), S3 vs. S1 (<b>B</b>), and S3 vs. S2 (<b>C</b>). Horizontal coordinates indicate the fold change of gene expression between different groups, and vertical coordinates indicate the significance level of gene expression difference in the two groups. Red dots indicate upregulated genes, green dots indicate downregulated genes, and grey dots indicate insignificant genes. Top 20 metabolic pathways analyzed by KEGG enrichment for DEGs from S2 vs. S1 (<b>D</b>), S3 vs. S1 (<b>E</b>), and S3 vs. S2 (<b>F</b>). The pathways associated with pigments metabolism are highlighted in red color.</p>
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<p>Expression patterns of the DEGs involved in anthocyanins synthesis in pomegranate peel at developmental stage 1 (S1), stage 2 (S2), and stage 3 (S3). The color scale from green to red represents the fragments per kilobase of transcript per million of fragments mapped (FPKM) values, from low to high.</p>
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<p>Expression pattern of the DEGs involved in carotenoids synthesis in pomegranate peel at developmental stage 1 (S1), stage 2 (S2), and stage 3 (S3). The color scale from blue to red represents the fragments per kilobase of transcript per million of fragments mapped (FPKM) values from low to high.</p>
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<p>Expression pattern of the DEGs involved in chlorophyll biosynthesis and degradation in pomegranate peel at developmental stage 1 (S1), stage 2 (S2), and stage 3 (S3). The color scale from green to red represents the fragments per kilobase of transcript per million of fragments mapped (FPKM) values from low to high.</p>
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<p>Identification of transcription factors (TFs) regulating pigments metabolism in pomegranate peel during fruit development. (<b>A</b>) K-means analysis of DEGs identified from transcriptome sequencing. The expression profiles of genes in each cluster are represented in different colors, and the average expression levels of all genes in developmental stage 1 (S1), S2, and S3 are represented in black. (<b>B</b>) Weighted gene co-expression network analysis (WGCNA) of DEGs identified from transcriptome sequencing. Module-trait correlations and corresponding <span class="html-italic">p</span>-values in parentheses. The left panel shows the six modules with gene numbers. The color scale on the right shows the module-trait correlations from −1 (blue) to 1 (red). ‘Anthocyanin’, ‘Chlorophyll a’, ‘Chlorophyll b’, ‘Total chlorophyll’ and ‘Carotenoid’ represent the changes in corresponding substances’ concentrations. (<b>C</b>) Heatmap presenting the expression patterns of regulatory genes regulating pomegranate peel pigments metabolism during fruit development. (<b>D</b>) Correlation network between TFs’ expression and pigments’ contents; pink and blue circles represent positive and negative correlations, respectively. Purple, orange, and green lines representing the relation between TFs and anthocyanin, carotenoid, and chlorophyll, respectively.</p>
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<p>The expressions of seven genes in pomegranate peel at developmental stage 1 (S1), S2, and S3 from transcriptome data were examined by quantitative polymerase chain reaction (q-PCR). The expression levels obtained by RNA-seq and q-PCR are shown with a line chart and histogram, respectively. Data are presented as the mean ± standard deviation of three biological replicates. Different letters above the bars indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) according to one-way analysis of variance (ANOVA) followed by Tukey test. Data analyzed by qPCR (marked with gray letters) or RNA-seq (marked with red letters) were tested separately.</p>
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13 pages, 9828 KiB  
Article
Examining Carotenoid Metabolism Regulation and Its Role in Flower Color Variation in Brassica rapa L.
by Guomei Liu, Liuyan Luo, Lin Yao, Chen Wang, Xuan Sun and Chunfang Du
Int. J. Mol. Sci. 2024, 25(20), 11164; https://doi.org/10.3390/ijms252011164 - 17 Oct 2024
Abstract
Carotenoids are vital organic pigments that determine the color of flowers, roots, and fruits in plants, imparting them yellow, orange, and red hues. This study comprehensively analyzes carotenoid accumulation in different tissues of the Brassica rapa mutant “YB1”, which exhibits altered flower and [...] Read more.
Carotenoids are vital organic pigments that determine the color of flowers, roots, and fruits in plants, imparting them yellow, orange, and red hues. This study comprehensively analyzes carotenoid accumulation in different tissues of the Brassica rapa mutant “YB1”, which exhibits altered flower and root colors. Integrating physiological and biochemical assessments, transcriptome profiling, and quantitative metabolomics, we examined carotenoid accumulation in the flowers, roots, stems, and seeds of YB1 throughout its growth and development. The results indicated that carotenoids continued to accumulate in the roots and stems of YBI, especially in its cortex, throughout plant growth and development; however, the carotenoid levels in the petals decreased with progression of the flowering stage. In total, 54 carotenoid compounds were identified across tissues, with 30 being unique metabolites. Their levels correlated with the expression pattern of 22 differentially expressed genes related to carotenoid biosynthesis and degradation. Tissue-specific genes, including CCD8 and NCED in flowers and ZEP in the roots and stems, were identified as key regulators of color variations in different plant parts. Additionally, we identified genes in the seeds that regulated the conversion of carotenoids to abscisic acid. In conclusion, this study offers valuable insights into the regulation of carotenoid metabolism in B. rapa, which can guide the selection and breeding of carotenoid-rich varieties. Full article
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<p>Dynamics of the phenotype and total carotenoid content in the mutants. (<b>A</b>): YB1 flowers; (<b>B</b>): TY7 flowers; (<b>C</b>): comparison of total carotenoid content at different flowering stages; CB, CO and CA represent the bud stage, semi-open stage, and full bloom stage of TY7 petals, respectively; YB, YO, and YA represent the bud stage, semi-open stage, and full bloom stage of YB1 petals, respectively; (<b>D</b>): YB1 rhizomes; (<b>E</b>): TY7 rhizomes; (<b>F</b>): comparison of total carotenoids at different stages of rhizome fertility; CP and YP denote the TY7 and YB1 cortices, respectively, and CW and YW denote the TY7 and YB1 vascular bundles, respectively; November 2022 is referred to as the 11th, December 2022 as the 12th, January 2023 as the 1st, February 2023 as the 2nd, March 2023 as the 3rd, April 2023 as the 4th, and May 2023 as the 5th. Data are expressed as the mean of three biological replicates. Differences between the two varieties were considered statistically significant at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Identification and clustering analysis of carotenoid differential metabolites. (<b>A</b>): OPLS-DA supervised analysis; CK1, CK2, and CK3 denote the petal, rhizome, and seed samples of the TY7 variety, respectively; YB1, YB2, and YB3 denote the petal, rhizome, and seed samples of the YB1 variety, respectively; (<b>B</b>): metabolite Wayne plots; comparisons between CSM (TY7 seed) and YSM (YB1 seed); CRM (TY7 root) and YRM (YB1 root); and CFM (TY7 petal) and YFM (YB1 petal); (<b>C</b>): heatmap of carotenoid metabolite clustering in different tissues; CF1−1, CF1−2, and CF1−3 represent the three biological replicates of TY7 petal samples; CR2−1, CR2−2, and CR2−3 represent the three biological replicates of TY7 root samples; CS3−1, CS3−2, and CS3−3 represent the three biological replicates of TY7 seed samples; YF1−1, YF1−2, YF1−3 represent the three biological replicates of YB1 petal samples; YR2−1, YR2−2, and YR2−3 represent the three biological replicates of YB1 root samples; and YS3−1, YS3−2, and YS3−3 represent the three biological replicates of YB1 seed samples; (<b>D</b>): KEGG analysis of differential metabolites. Note: CF stands for TY7 flower, YF stands for YB1 flower, CR stands for TY7 rhizome, YR stands for YB1 rhizome, CS stands for TY7 seed, and YS denotes YB1 seed.</p>
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<p>Transcriptome analysis of different samples. (<b>A</b>): Wayne plots of differentially expressed genes (DEGs) in different tissues of the control and mutant plants; (<b>B</b>): transcriptome DEGs; CF_vs._YF denotes the comparison between petals of TY7 and YB1; CR_vs._YR denotes the comparison between the roots of TY7 and YB1; and CS_vs._YS denotes the comparison between the seeds of TY7 and YB1. (<b>C</b>): GO classification of DEGs. (<b>D</b>): KEGG pathway enrichment of the DEGs.</p>
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<p>Weighted gene co-expression network analysis of the genes associated with carotenoid metabolism. (<b>A</b>): Hierarchical clustering tree diagram of co-expressed genes in WGCNA, with each leaf corresponding to one gene, and the main branches from seven modules labeled in different colors; (<b>B</b>): relationship between modules and carotenoid metabolism-related DEGs, with each row representing one module. Each column represents the carotenoid biosynthesis-related DEGs; the value of each cell at the intersection of rows and columns represents the coefficient of correlation between the modules and carotenoid metabolism DEGs (shown on the right side of the color scale), whereas the value in parentheses in each cell represents the <span class="html-italic">p</span> value; (<b>C</b>): KEGG enrichment analysis of turquoise module DEGs; (<b>D</b>): KEGG enrichment analysis of green module DEGs; (<b>E</b>): KEGG enrichment analysis of yellow module DEGs.</p>
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<p>Pearson correlation analysis of DEGs with carotenoid differential metabolites (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Carotenoid regulatory networks in different tissues. Note: CF: TY7 petals; YF: YB1 petals; CR: TY7 rhizomes; YR: YB1 rhizomes; CS: TY7 seeds; YS: YB1 seeds; PDS: 15-cis-octahydroxylycopene desaturase; crtL2: lycopene e-cyclase; CYP97A3: β-cyclohydroxylase; crtZ: β-carotenoids 3-lightening enzyme; CCD8: carotenoid cleavage dioxygenase; NCED: 9-cis-epoxycarotenoid dioxygenase; ABA2: xanthoxin dehydrogenase; CYP707A: (+)−abscisic acid 8′-hydroxylase; ZEP, ABA1: zeaxanthin epoxidase. Orange color indicates upregulation and light blue color indicates downregulation.</p>
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<p>qRT-PCR assay for the differential expression profiles of genes in the seeds, petals, and roots of the control and mutant plants and transcriptome heat map. *** Significantly Note: CF: TY7 petals; YF: YB1 petals; CR: TY7 rhizomes; YR: YB1 rhizomes; CS: TY7 seeds; YS: YB1 seeds.</p>
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27 pages, 2390 KiB  
Article
Visualizing Plant Responses: Novel Insights Possible Through Affordable Imaging Techniques in the Greenhouse
by Matthew M. Conley, Reagan W. Hejl, Desalegn D. Serba and Clinton F. Williams
Sensors 2024, 24(20), 6676; https://doi.org/10.3390/s24206676 - 17 Oct 2024
Abstract
Efficient and affordable plant phenotyping methods are an essential response to global climatic pressures. This study demonstrates the continued potential of consumer-grade photography to capture plant phenotypic traits in turfgrass and derive new calculations. Yet the effects of image corrections on individual calculations [...] Read more.
Efficient and affordable plant phenotyping methods are an essential response to global climatic pressures. This study demonstrates the continued potential of consumer-grade photography to capture plant phenotypic traits in turfgrass and derive new calculations. Yet the effects of image corrections on individual calculations are often unreported. Turfgrass lysimeters were photographed over 8 weeks using a custom lightbox and consumer-grade camera. Subsequent imagery was analyzed for area of cover, color metrics, and sensitivity to image corrections. Findings were compared to active spectral reflectance data and previously reported measurements of visual quality, productivity, and water use. Results confirm that Red–Green–Blue imagery effectively measures plant treatment effects. Notable correlations were observed for corrected imagery, including between yellow fractional area with human visual quality ratings (r = −0.89), dark green color index with clipping productivity (r = 0.61), and an index combination term with water use (r = −0.60). The calculation of green fractional area correlated with Normalized Difference Vegetation Index (r = 0.91), and its RED reflectance spectra (r = −0.87). A new chromatic ratio correlated with Normalized Difference Red-Edge index (r = 0.90) and its Red-Edge reflectance spectra (r = −0.74), while a new calculation correlated strongest to Near-Infrared (r = 0.90). Additionally, the combined index term significantly differentiated between the treatment effects of date, mowing height, deficit irrigation, and their interactions (p < 0.001). Sensitivity and statistical analyses of typical image file formats and corrections that included JPEG, TIFF, geometric lens distortion correction, and color correction were conducted. Findings highlight the need for more standardization in image corrections and to determine the biological relevance of the new image data calculations. Full article
(This article belongs to the Special Issue Feature Papers in Sensing and Imaging 2024)
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<p>The lightbox is shown in greenhouse #1 (panel (<b>a</b>), left side) with the camera installed on top. The remote trigger with switch and the 12-volt power supply with 7.5 Ah SLA battery and wires are visible on the left and bottom left side. The lightbox diagram (panel (<b>b</b>), right side) illustrates the placement of LED lights and demonstrates how a lysimeter would be inserted into the box and photographed against the white background.</p>
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<p>An example lysimeter uncorrected image and three masked views. Experiment treatment 30% water and 5.0 cm mow height is shown in an image taken on 10/26/2023 (Week 2) with associated 0.61 NDVI and 7.0 VQ (panel (<b>a</b>), upper left), 97.8% of the lysimeter area covered in live green material (%C) segment (panel (<b>b</b>), upper right), resulting in 0.280 DGCI, 0.400 HSVi, and 7.010 COMB2 calculation values, with 31.1% yellow (%Y) plant cover (panel (<b>c</b>), lower left), and 59.0% green (%G) cover fractions (panel (<b>d</b>), lower right).</p>
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<p>NDVI time series chart with NDVI plotted on the Y-axis and date on the X-axis. The experimental treatments are labeled by their percentage of consumptive demand-based irrigation supplied (i = 100, 65, and 30) and their mowing heights (h = 10, 7.5, 5.0, and 2.5 cm). Each treatment is grouped by irrigation level and is uniquely colored, and the line pattern is based on mowing height. NDVI shows changes in time and differences with experimental treatment.</p>
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<p>A %Y time series chart is presented, where the image-based yellow color classification segment is plotted on the inverted Y-axis and the date is on the X-axis. The experimental treatments are labeled by their percentage of consumptive demand-based irrigation supplied (i = 100, 65, and 30) and their mowing heights (h = 10, 7.5, 5.0, and 2.5 cm). Each treatment is grouped by irrigation level and uniquely colored, the line pattern is based on mowing height. Results show change over time and increased treatment separation with the greatly reduced water treatment.</p>
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<p>A COMB2 time series chart is presented where the combination term is plotted on the Y-axis and date is on the X-axis. The experimental treatments are labeled by their percentage of consumptive demand-based irrigation supplied (i = 100, 65, and 30 actual evapotranspiration replacement) and their mowing heights (h = 10, 7.5, 5.0, and 2.5 cm). Each treatment is grouped by irrigation level and uniquely colored, the line pattern is based on mowing height. Results show reduced change over time, but increased treatment separation when compared to NDVI and %Y (<a href="#sensors-24-06676-f003" class="html-fig">Figure 3</a> and <a href="#sensors-24-06676-f004" class="html-fig">Figure 4</a>).</p>
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21 pages, 4478 KiB  
Article
Visual Cues, Liking, and Emotional Responses: What Combination of Factors Result in the Willingness to Eat Vegetables Among Children with Food Neophobia?
by Xiaoqin Tan, Shureen Faris Abdul Shukor and Kim Geok Soh
Foods 2024, 13(20), 3294; https://doi.org/10.3390/foods13203294 - 17 Oct 2024
Abstract
Childhood nutrition is a cornerstone of long-term health, yet many children exhibit reluctance to consume healthy foods such as vegetables. This aversion can be influenced by various factors, including food neophobia and the sensory and visual appeal of the foods that are being [...] Read more.
Childhood nutrition is a cornerstone of long-term health, yet many children exhibit reluctance to consume healthy foods such as vegetables. This aversion can be influenced by various factors, including food neophobia and the sensory and visual appeal of the foods that are being presented. Hence, understanding how visual cues affect children’s willingness to eat can provide insights into effective strategies to enhance their dietary habits. This research explores the influence of visual cues on the dietary behaviors of children aged 9 to 12, their willingness to consume and request healthy foods such as vegetables, within the context of challenges such as food neophobia. This study examines how intrinsic cues (e.g., vegetable characteristics) and extrinsic cues (e.g., the plate’s color and shape) affect children’s liking and emotional responses, impacting their willingness to eat and request purchases from parents. Conducted using a sample of 420 children, this cross-sectional study reveals that attributes such as a plate’s color and shape significantly affect food-related behaviors and emotions. A validated and reliable self-administered questionnaire was employed. Independent t-tests and ANOVA were used to test the differences between gender and food neophobia, while Spearman correlations were used for correlation analysis. Visual cues served as the independent variables, liking and emotional responses as the mediating variables, and willingness behaviors as the dependent variable. Hierarchical regression analyses were conducted to explore the relationships among intrinsic cues, extrinsic cues, and the mediating effect of liking and emotional responses. Findings show that boys prefer blue and triangular plates, while girls prefer pink plates, generating more positive emotions. Children with food neophobia initially experience aversion, but this can be reduced by enhancing sensory appeal and emotional engagement. The findings underscore the importance of leveraging visual cues and fostering positive emotional experiences to encourage healthier eating habits and increase children’s acceptance and purchase of nutritious foods. Full article
(This article belongs to the Section Sensory and Consumer Sciences)
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<p>The valence× arousal circumplex-inspired emotion word questionnaire (CEQ) used in this research.</p>
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<p>The stimuli of vegetables and plates.</p>
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<p>Visual cues inducing liking of the participants with gender.</p>
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<p>Mean score of willingness behaviors of the participants with gender.</p>
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<p>Visual cues induce Liking of the participants with Food Neophobia.</p>
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<p>Spider plots showing comparison of the “low” FN group, “medium” FN group and “high” FN group for the 12 CEQ emotion word pairs (frequency of use, %) (RQ1). Significant differences are shown with * when <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** when <span class="html-italic">p</span> &lt; 0.001. The nine visual cues are shown in order.</p>
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<p>Mean score of willingness behaviors of the participants with food neophobia.</p>
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21 pages, 7722 KiB  
Article
Transcriptomic Analysis During Olive Fruit Development and Expression Profiling of Fatty Acid Desaturase Genes
by Alicia Serrano, Judith García-Martín, Martín Moret, José Manuel Martínez-Rivas and Francisco Luque
Int. J. Mol. Sci. 2024, 25(20), 11150; https://doi.org/10.3390/ijms252011150 - 17 Oct 2024
Abstract
The olive fruit is a drupe whose development and ripening takes several months from flowering to full maturation. During this period, several biochemical and physiological changes occur that affect the skin color, texture, composition, and size of the mesocarp. The final result is [...] Read more.
The olive fruit is a drupe whose development and ripening takes several months from flowering to full maturation. During this period, several biochemical and physiological changes occur that affect the skin color, texture, composition, and size of the mesocarp. The final result is a fruit rich in fatty acids, phenolic compounds, tocopherols, pigments, sterols, terpenoids, and other compounds of nutritional interest. In this work, a transcriptomic analysis was performed using flowers (T0) and mesocarp tissue at seven different stages during olive fruit development and ripening (T1–T7) of the ‘Picual’ cultivar. A total of 1755 genes overexpressed at any time with respect to the flowering stage were further analyzed. These genes were grouped into eight clusters based on their expression profile. The gene enrichment analysis revealed the most relevant biological process of every cluster. Highlighting the important role of hormones at very early stages of fruit development (T1, Cluster 1), whereas genes involved in fatty acid biosynthesis were relevant throughout the fruit developmental process. Hence, genes coding for different fatty acid desaturase (SAD, FAD2, FAD3, FAD4, FAD5, FAD6, and FAD7) enzymes received special attention. In particular, 26 genes coding for different fatty acid desaturase enzymes were identified in the ‘Picual’ genome, contributing to the improvement of the genome annotation. The expression pattern of these genes during fruit development corroborated their role in determining fatty acid composition. Full article
(This article belongs to the Special Issue Genomic and Transcriptomic Analysis of Olive (Olea europaea L.))
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<p>(<b>A</b>) Developmental stages collected for RNAseq analysis. (<b>B</b>) PCA plot showing the expression differences among olive fruit developing samples. Samples collected in triplicate: T0: flowers at full bloom, T1: fruits at 15 days after full blooming (AFB), T2: fruits at 1 month AFB, T3: fruits at 2 months AFB, T4: fruits at 3 months AFB, T5: fruits at 4 months AFB, T6: fruits at 5 months AFB, and T7: fruits at 6 months AFB.</p>
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<p>Differentially expressed genes throughout fruit development owing to the flowering stage. T0: flowers at full bloom, T1: 15 days after full blooming (AFB), T2: 1 month AFB, T3: 2 months AFB, T4: 3 months AFB, T5: 4 months AFB, T6: 5 months AFB, and T7: 6 months AFB.</p>
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<p>Cluster A. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Cluster B. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Cluster C. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Cluster D. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Cluster E. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Cluster F. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Cluster G. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Cluster H. (<b>A</b>) Gene expression profile. Blue line represents the mean value of expression for the total genes in the group. Blue shadow represents the standard error of gene expression. Gray lines represent the expression of individual genes. The red horizontal line represents the threshold separating positive from negative expression levels. (<b>B</b>) The 20 most representative biological processes according to the FDR and fold enrichment values obtained in ShinyGO 0.80.</p>
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<p>Expression of coding genes for isoforms of SAD enzyme during olive fruit development.</p>
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<p>Expression of coding genes for microsomal FAD enzymes during olive fruit development.</p>
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<p>Expression of coding genes for plastidial membrane-bound FAD enzymes during olive fruit development.</p>
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16 pages, 1844 KiB  
Article
Innovative Pathogen Reduction in Exported Sea Bass Through Atmospheric Cold Plasma Technology
by Şehnaz Yasemin Tosun, Sehban Kartal, Tamer Akan, Sühendan Mol, Serap Coşansu, Didem Üçok, Şafak Ulusoy, Hande Doğruyol and Kamil Bostan
Foods 2024, 13(20), 3290; https://doi.org/10.3390/foods13203290 - 17 Oct 2024
Viewed by 136
Abstract
The safety of sea bass is critical for the global food trade. This study evaluated the effectiveness of atmospheric cold plasma in reducing food safety risks posed by Salmonella Enteritidis and Listeria monocytogenes, which can contaminate sea bass post harvest. Cold plasma [...] Read more.
The safety of sea bass is critical for the global food trade. This study evaluated the effectiveness of atmospheric cold plasma in reducing food safety risks posed by Salmonella Enteritidis and Listeria monocytogenes, which can contaminate sea bass post harvest. Cold plasma was applied to inoculated sea bass for 2 to 18 min, achieving a maximum reduction of 1.43 log CFU/g for S. Enteritidis and 0.80 log CFU/g for L. monocytogenes at 18 min. Longer treatments resulted in greater reductions; however, odor and taste quality declined to a below average quality in samples treated for 12 min or longer. Plasma treatment did not significantly alter the color, texture, or water activity (aw) of the fish. Higher levels of thiobarbituric acid reactive substances (TBARSs) were observed with increased exposure times. Cold plasma was also tested in vitro on S. Enteritidis and L. monocytogenes on agar surfaces. A 4 min treatment eliminated the initial loads of S. Enteritidis (2.71 log CFU) and L. monocytogenes (2.98 log CFU). The findings highlight the potential of cold plasma in enhancing the safety of naturally contaminated fish. Cold plasma represents a promising technology for improving food safety in the global fish trade and continues to be a significant area of research in food science. Full article
(This article belongs to the Section Food Quality and Safety)
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<p>Original atmospheric cold plasma equipment ((A) power supply; (B) plasma generation cite; (C) glass Petri dish lid; (D) copper plate; (E) copper wire; (F) sample site; (G) cold plasma).</p>
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<p>In vitro reduction in <span class="html-italic">S.</span> Enteritidis and <span class="html-italic">L. monocytogenes</span> by atmospheric cold plasma (a, b: different letters show significant differences between reduction rates, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Reduction in <span class="html-italic">S.</span> Enteritidis and <span class="html-italic">L. monocytogenes</span> on sea bass by atmospheric cold plasma (a–d: different letters show significant differences in reduction rates, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Sensory analysis of sea bass treated with atmospheric cold plasma for various durations (* decreases in odor and taste after 8 min and in overall acceptability after 10 min are significant, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Color change in plasma-treated sea bass compared to untreated samples (a; no significant differences between ΔE vales, <span class="html-italic">p</span> &gt; 0.05).</p>
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<p>TBARS values of sea bass treated with atmospheric cold plasma (a–i: letters indicate the significant difference between treatments, <span class="html-italic">p</span> &lt; 0.05).</p>
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12 pages, 22317 KiB  
Article
Biomimetic Cooling: Functionalizing Biodegradable Chitosan Films with Saharan Silver Ant Microstructures
by Markus Zimmerl, Richard W. van Nieuwenhoven, Karin Whitmore, Wilfried Vetter and Ille C. Gebeshuber
Biomimetics 2024, 9(10), 630; https://doi.org/10.3390/biomimetics9100630 - 17 Oct 2024
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Abstract
The increasing occurrence of hot summer days causes stress to both humans and animals, particularly in urban areas where temperatures can remain high, even at night. Living nature offers potential solutions that require minimal energy and material costs. For instance, the Saharan silver [...] Read more.
The increasing occurrence of hot summer days causes stress to both humans and animals, particularly in urban areas where temperatures can remain high, even at night. Living nature offers potential solutions that require minimal energy and material costs. For instance, the Saharan silver ant (Cataglyphis bombycina) can endure the desert heat by means of passive radiative cooling induced by its triangular hairs. The objective of this study is to transfer the passive radiative cooling properties of the micro- and nanostructured chitin hairs of the silver ant body to technically usable, biodegradable and bio-based materials. The potential large-scale transfer of radiative cooling properties, for example, onto building exteriors such as house facades, could decrease the need for conventional cooling and, therefore, lower the energy demand. Chitosan, a chemically altered form of chitin, has a range of medical uses but can also be processed into a paper-like film. The procedure consists of dissolving chitosan in diluted acetic acid and uniformly distributing it on a flat surface. A functional structure can then be imprinted onto this film while it is drying. This study reports the successful transfer of the microstructure-based structural colors of a compact disc (CD) onto the film. Similarly, a polyvinyl siloxane imprint of the silver ant body shall make it possible to transfer cooling functionality to technically relevant surfaces. FTIR spectroscopy measurements of the reflectance of flat and structured chitosan films allow for a qualitative assessment of the infrared emissivity. A minor decrease in reflectance in a relevant wavelength range gives an indication that it is feasible to increase the emissivity and, therefore, decrease the surface temperature purely through surface-induced functionalities. Full article
(This article belongs to the Special Issue The Latest Progress in Bionics Research)
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Graphical abstract

Graphical abstract
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<p>Incoming and outgoing radiation energy intensity and the absorption spectrum of the atmosphere. The bulk of the outgoing energy lies within the atmospheric window from 8 to 13 µm [<a href="#B17-biomimetics-09-00630" class="html-bibr">17</a>].</p>
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<p>(<b>a</b>) SEM micrograph of cross-sections cut with a focused ion beam (FIB) through triangular chitin hairs of a Sahara silver ant gaster (hind part). Scale bar—2 µm. (<b>b</b>) Illustration of the triangular cross-section of a silver ant hair. Incoming solar radiation undergoes Mie scattering at the small indentations of the top sides. The light that enters the silver ant hair can be reflected on the bottom side when the conditions for total reflection are met (incidence angle and difference in refractive index between silver ant hair and air gap) [<a href="#B14-biomimetics-09-00630" class="html-bibr">14</a>]. Scale bar—1 µm.</p>
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<p>(<b>a</b>) SEM sample holder with exposed and unexposed shrimp shell sample, as well as silver ant gaster (rear segment of the silver ant). Scale bar—1 cm. (<b>b</b>) Climate chamber cycles (programmed).</p>
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<p>Process of creating a copy of the silver ant surface structure in chitosan with the help of a PVS stamp.</p>
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<p>(<b>a</b>) Confocal image of scratched shrimp shell before and after exposure in the climate chamber. Scale bar—200 µm. (<b>b</b>) Chitosan film with iridescent microstructures transferred from a CD. Scale bar—0.5 cm.</p>
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<p>Confocal images of (<b>a</b>) an ’unstructured’ area of the PVS stamp, which shows the structure of the cardboard that surrounded the silver ant gaster. (<b>b</b>) The PVS–cardboard structure transferred onto chitosan. (<b>c</b>) A structured area of the PVS stamp structured with an ant gaster. (<b>d</b>) The PVS–ant structure transferred onto chitosan. Scale bars—200 µm.</p>
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<p>(<b>a</b>) Average reflectance (* in relation to a reference gold mirror) of structured and unstructured chitosan films. The structured areas in both samples exhibit a slightly higher reflectance for wavelengths greater than 6 µm. However, this difference is less than the calculated standard deviation. Below 6 µm, the two samples feature inconsistent differences in reflectance. (<b>b</b>) Zoom into the respective region of the atmospheric window in (<b>a</b>).</p>
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