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19 pages, 6017 KiB  
Article
The Effect of CaO in the Immobilization of Cd2+ and Pb2+ in Fly Ash-Based Geopolymer
by Xupicheng Ren, Fan Wang, Xiang He and Xiaomin Hu
Clean Technol. 2024, 6(3), 1057-1075; https://doi.org/10.3390/cleantechnol6030053 (registering DOI) - 14 Aug 2024
Abstract
The use of geopolymers for the solidification/stabilization (S/S) of municipal solid waste incineration fly ash (MSWI FA) is promising because the Cao in MSWI FA can provide an alkaline environment to facilitate geopolymer reactions and help to form the gel phase in the [...] Read more.
The use of geopolymers for the solidification/stabilization (S/S) of municipal solid waste incineration fly ash (MSWI FA) is promising because the Cao in MSWI FA can provide an alkaline environment to facilitate geopolymer reactions and help to form the gel phase in the solidified body. This study investigated the role of CaO in MSWI FA in immobilizing common heavy metals, especially Cd2+ and Pb2+. Tests were performed to evaluate the effect of CaO on the unconfined compressive strength (UCS) of the polymer and the leaching of heavy metals. The findings revealed that as the CaO content increased, the UCS of the geopolymer samples also rose, reaching a maximum 28-day UCS of 24.8 MPa at a CaO content of 31.5%. Additionally, higher CaO levels resulted in lower leaching concentrations of heavy metals in the stabilized material. When the CaO level is 32%, the levels of heavy metals that leach out are very low, with Pb2+ at 0. 02 mg/L and Cd2+ at 0. 01 mg/L, achieving a stabilization rate of over 93.6% for these ions. Moreover, the geopolymer’s characteristics were analyzed by XRD, FTIR, and SEM, and the immobilization mechanisms of Cd2+ and Pb2+ were identified as gelation, physical encapsulation, and chemical substitution. Full article
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Figure 1
<p>Effect of different fly ash content on UCS of geopolymer.</p>
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<p>The UCS of MSWI fly ash-based geopolymer: (<b>a</b>) low-CaO condition, (<b>b</b>) medium-CaO condition, (<b>c</b>) high-CaO condition, (<b>d</b>) ternary system of SiO<sub>2</sub>-Al<sub>2</sub>O<sub>3</sub>-CaO under the conditions of low, medium, and high CaO.</p>
Full article ">Figure 2 Cont.
<p>The UCS of MSWI fly ash-based geopolymer: (<b>a</b>) low-CaO condition, (<b>b</b>) medium-CaO condition, (<b>c</b>) high-CaO condition, (<b>d</b>) ternary system of SiO<sub>2</sub>-Al<sub>2</sub>O<sub>3</sub>-CaO under the conditions of low, medium, and high CaO.</p>
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<p>The results of the leaching test. (<b>a</b>) Determining the concentration of heavy metal ions released during leaching in the geopolymer. (<b>b</b>) The immobilization percentage of heavy metal ions in the geopolymer.</p>
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<p>Characteristics of geopolymers. (<b>a</b>) XRD (a: geopolymer, b: MSWI FA, c: geopolymer based on MSWI FA). (<b>b</b>) FTIR (a: geopolymer, b: MSWI FA, c: geopolymer based on MSWI FA).</p>
Full article ">Figure 4 Cont.
<p>Characteristics of geopolymers. (<b>a</b>) XRD (a: geopolymer, b: MSWI FA, c: geopolymer based on MSWI FA). (<b>b</b>) FTIR (a: geopolymer, b: MSWI FA, c: geopolymer based on MSWI FA).</p>
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<p>SEM images of MSWI fly ash-based geopolymer: (<b>a</b>) low-CaO condition, (<b>b</b>) medium-CaO condition, (<b>c</b>) high-CaO condition.</p>
Full article ">Figure 5 Cont.
<p>SEM images of MSWI fly ash-based geopolymer: (<b>a</b>) low-CaO condition, (<b>b</b>) medium-CaO condition, (<b>c</b>) high-CaO condition.</p>
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12 pages, 2664 KiB  
Article
Research on the Structural–Phase and Physical–Mechanical Characteristics of the Cr3C2-NiCr Composite Coating Deposited by the HVOF Method on E110 Zirconium Alloy
by Sherzod Kurbanbekov, Bauyrzhan Rakhadilov, Dauir Kakimzhanov, Bekbolat Seitov, Karakoz Katpaeva, Abil Kurmantayev, Merkhat Dautbekov and Aidar Kengesbekov
Coatings 2024, 14(8), 1030; https://doi.org/10.3390/coatings14081030 (registering DOI) - 14 Aug 2024
Abstract
Composite coatings based on chromium carbide (Cr3C2) and nickel–chromium alloys (NiCr) are widely used due to their unique properties, including high heat resistance, wear resistance and corrosion resistance. This article studies the structural–phase and physical–mechanical characteristics of Cr3 [...] Read more.
Composite coatings based on chromium carbide (Cr3C2) and nickel–chromium alloys (NiCr) are widely used due to their unique properties, including high heat resistance, wear resistance and corrosion resistance. This article studies the structural–phase and physical–mechanical characteristics of Cr3C2-NiCr composite coatings applied by high-velocity oxygen fuel to E110 zirconium alloy. The HVOF method was chosen to create coatings with high adhesion to the substrate and excellent performance properties. Analysis of the microstructure of the cross-section showed the thickness of the modified surface layer from 75 to 110 μm, depending on the processing modes. Energy dispersive X-ray spectral analysis revealed the presence of elements Cr, Ni, C and O in the coating composition. Structural–phase analysis confirmed the formation of coatings with a high concentration of Cr3C2 carbide particles and NiCr (nickel–chromium) phases. The resulting composite coatings based on Cr3C2-NiCr had a significantly high microhardness, ranging from HV 1190 to HV 1280, and the friction coefficient varied in a significant range from 0.679 to 0.502 depending on the processing conditions. The maximum adhesion strength was 9.19 MPa per square centimeter. Full article
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<p>Appearance (<b>a</b>) and block diagram (<b>b</b>) of installation for high-velocity HVOF spraying: 1—burner, 2—powder dispenser, 3—chiller, 4—gas control panel, 5—compressor, 6—gas in cylinder (C<sub>3</sub>H<sub>8</sub>) and 7—gas in cylinder (O<sub>2</sub>).</p>
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<p>SEM image and EDX analysis of cross-sectional morphology of Cr<sub>3</sub>C<sub>2</sub>-NiCr coatings. (<b>a</b>–<b>d</b>) see <a href="#coatings-14-01030-t001" class="html-table">Table 1</a>.</p>
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<p>Results of X-ray phase analysis of Cr<sub>3</sub>C<sub>2</sub>-NiCr coatings obtained by HVOF method. (<b>a</b>–<b>d</b>) see <a href="#coatings-14-01030-t001" class="html-table">Table 1</a>.</p>
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<p>Microhardness distribution from the surface layer to the core of the samples. (<b>a</b>–<b>d</b>) see <a href="#coatings-14-01030-t001" class="html-table">Table 1</a>.</p>
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<p>The dependence of the friction coefficient of the coatings on the length of the friction path. (<b>a</b>–<b>d</b>) see <a href="#coatings-14-01030-t001" class="html-table">Table 1</a>.</p>
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<p>Adhesion testing using the peel-off method for the Cr<sub>3</sub>C<sub>2</sub>-NiCr coatings obtained through the HVOF method. (<b>a</b>–<b>d</b>) see <a href="#coatings-14-01030-t001" class="html-table">Table 1</a>.</p>
Full article ">Figure 7
<p>Potentiodynamic polarization curves of Cr<sub>3</sub>C<sub>2</sub>-NiCr coatings. (<b>a</b>–<b>d</b>) see <a href="#coatings-14-01030-t001" class="html-table">Table 1</a>.</p>
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12 pages, 5955 KiB  
Article
A Novel Synthesis Method of Dumbbell-like (Gd1−xTbx)2O(CO3)2·H2O Phosphor for Latent Fingerprint
by Lei Huang, Jian Qian, Shijian Sun, Zheng Li and Dechuan Li
Molecules 2024, 29(16), 3846; https://doi.org/10.3390/molecules29163846 (registering DOI) - 14 Aug 2024
Abstract
A novel method for synthesizing dumbbell-shaped (Gd1−xTbx)2O(CO3)2·H2O (GOC:xTb3+) phosphors using sodium carbonate was investigated. An amount of 1 mmol of stable fluorescent powder can be widely [...] Read more.
A novel method for synthesizing dumbbell-shaped (Gd1−xTbx)2O(CO3)2·H2O (GOC:xTb3+) phosphors using sodium carbonate was investigated. An amount of 1 mmol of stable fluorescent powder can be widely prepared using 3–11 mmol of Na2CO3 at a pH value of 8.5–10.5 in the reaction solution. The optimal reaction conditions for the phosphors were determined to be 7 mmol for the amount of sodium carbonate and a pH of 9.5 in the solution. Mapping analysis of the elements confirmed uniform distribution of Gd3+ and Tb3+ elements in GOC:xTb3+. The analysis of fluorescence intensity shows that an optimal excitation wavelength of 273 nm is observed when the concentration of Tb3+ is between 0.005 and 0.3. The highest emission intensity was observed for GOC:0.05Tb3+ with a 57.5% maximum quantum efficiency. The chromaticity coordinates show that the color of GOC:Tb3+ is stable and suitable for fluorescence recognition. Latent fingerprint visualization reveals distinctive features like whorls, hooks, and bifurcations. Therefore, the sodium carbonate method offers an effective alternative to traditional urea chemical reaction conditions for preparing GOC:Tb3+. Full article
(This article belongs to the Special Issue Synthesis and Crystal Structure of Rare-Earth Metal Compounds)
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Figure 1
<p>XRD patterns of GOC:0.05Tb<sup>3+</sup> prepared at different (<b>a</b>) contents of Na<sub>2</sub>CO<sub>3</sub> at a constant pH value of 9.5; (<b>b</b>) pH values at a constant Na<sub>2</sub>CO<sub>3</sub> dosage of 7 mmol.</p>
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<p>Excitation spectra of GOC:0.05Tb<sup>3+</sup> prepared at different (<b>a</b>) contents of Na<sub>2</sub>CO<sub>3</sub> (pH:9.5); (<b>b</b>) pH values of the reaction solution (Na<sub>2</sub>CO<sub>3</sub>:7 mmol).</p>
Full article ">Figure 3
<p>XRD patterns of (Gd<sub>1−<span class="html-italic">x</span></sub>Tb<span class="html-italic"><sub>x</sub></span>)<sub>2</sub>O(CO<sub>3</sub>)<sub>2</sub>·H<sub>2</sub>O.</p>
Full article ">Figure 4
<p>(<b>a</b>–<b>g</b>) Morphologies of GOC:<span class="html-italic">x</span>Tb<sup>3+</sup> (<span class="html-italic">x</span> = 0, 0.05, 0.1, 0.3, 0.5, 0.7, 1); (<b>h</b>) enlarged image of GOC:1Tb<sup>3+</sup> sample; (<b>i</b>) energy dispersive spectrum of GOC:0.05Tb<sup>3+</sup> sample.</p>
Full article ">Figure 5
<p>Schematic illustration for the formation process of the dumbbell-like GOC:<span class="html-italic">x</span>Tb<sup>3+</sup> (<b>a</b>) aggregate; (<b>b</b>) grow; (<b>c</b>) form.</p>
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<p>Excitation spectra of GOC:<span class="html-italic">x</span>Tb<sup>3+</sup> (<span class="html-italic">x</span> = 0–1).</p>
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<p>Emission spectra of GOC:<span class="html-italic">x</span>Tb<sup>3+</sup> excitation at (<b>a</b>) 365 nm; (<b>b</b>) 273 nm.</p>
Full article ">Figure 8
<p>Plot of log (<span class="html-italic">I</span>/<span class="html-italic">x</span>) as function of log(<span class="html-italic">x</span>) in GOC:<span class="html-italic">x</span>Tb<sup>3+</sup> (<span class="html-italic">x</span> = 0.05–1).</p>
Full article ">Figure 9
<p>Typical decay curve of GOC:0.05Tb<sup>3+</sup>.</p>
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<p>Chromaticity coordinates of GOC:<span class="html-italic">x</span>Tb<sup>3+</sup> excitation at 273 nm.</p>
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<p>The latent fingerprint details and gray value of forefinger.</p>
Full article ">
21 pages, 2214 KiB  
Review
A Review of Green, Low-Carbon, and Energy-Efficient Research in Sports Buildings
by Feng Qian, Zedao Shi and Li Yang
Energies 2024, 17(16), 4020; https://doi.org/10.3390/en17164020 (registering DOI) - 14 Aug 2024
Abstract
The demand for low-carbon and energy-efficient building designs is urgent, especially considering that building energy consumption constitutes a significant part of global energy usage. Unlike small to medium-sized buildings such as residential and office spaces, large public buildings, like sports facilities, have unique [...] Read more.
The demand for low-carbon and energy-efficient building designs is urgent, especially considering that building energy consumption constitutes a significant part of global energy usage. Unlike small to medium-sized buildings such as residential and office spaces, large public buildings, like sports facilities, have unique usage patterns and architectural forms, offering more significant potential for energy-saving strategies. This review focuses on sports buildings, selecting 62 high-quality papers published in building science over the past 30 years that investigate low-carbon and energy-efficient research. Summarizing and synthesizing these papers reveals that current studies predominantly concentrate on four main areas: indoor air quality, ventilation, thermal environment, and energy consumption. Notably, many studies emphasize improving indoor thermal comfort and reducing energy consumption in sports buildings through measurements and evaluations of indoor thermal environments, temperature distributions, heat transfer phenomena, and energy consumption analyses. Key outcomes indicate that green technology innovations, such as energy substitution technologies, significantly enhance energy efficiency and reduce CO2 emissions. However, present research emphasizes singular energy-saving approaches, suggesting future directions could integrate comprehensive green technologies, life-cycle assessments, and applications of intelligent technologies and the Internet of Things (IoT). These enhancements aim to provide more effective and sustainable solutions for implementing green, low-carbon energy practices in sports buildings. The review emphasizes that in order to accomplish sustainable urban growth and achieve global carbon neutrality targets, a comprehensive approach involving technical innovation, legislative assistance, and extensive preparation is crucial. Full article
(This article belongs to the Section G: Energy and Buildings)
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<p>The article screening flowchart.</p>
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<p>Trend of the number of papers over the years.</p>
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<p>Categories and proportions of papers after screening.</p>
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<p>Sustainable considerations in sports architecture.</p>
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<p>Air quality enhancement framework.</p>
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<p>Three ventilation strategies in sports architecture: (<b>a</b>) wind-driven ventilation; (<b>b</b>) buoyancy-driven ventilation; and (<b>c</b>) mixed-mode ventilation.</p>
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<p>Key influencing factors of thermal environment in sports architecture.</p>
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12 pages, 1029 KiB  
Article
Inorganic Characterization of Feeds Based on Processed Animal Protein Feeds
by Paolo Inaudi, Luca Maria Mercurio, Daniela Marchis, Andrea Bosusco, Mery Malandrino, Ornella Abollino, Laura Favilli, Stefano Bertinetti and Agnese Giacomino
Molecules 2024, 29(16), 3845; https://doi.org/10.3390/molecules29163845 (registering DOI) - 14 Aug 2024
Abstract
The potential of utilizing inorganic constituents in processed animal proteins (PAPs) for species identification in animal feeds was investigated, with the aim of using these constituents to ensure the quality and authenticity of the products. This study aimed to quantify the inorganic content [...] Read more.
The potential of utilizing inorganic constituents in processed animal proteins (PAPs) for species identification in animal feeds was investigated, with the aim of using these constituents to ensure the quality and authenticity of the products. This study aimed to quantify the inorganic content across various PAP species and assess whether inorganic analysis could effectively differentiate between PAP species, ultimately aiding in the identification of PAP fractions in animal feeds. Four types of PAPs, namely bovine, swine, poultry, and fish-based, were analyzed and compared to others made up of feathers of vegetal-based feed. Also, three insect-based PAPs (Cricket, Silkworm, Flour Moth) were considered in this study to evaluate the differences in terms of the nutrients present in this type of feed. Ionic chromatography (IC) was used to reveal the concentrations of NO3, NO2, Cl, and SO42−, and inductively coupled plasma optical emission spectroscopy (ICP-OES) to detect Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P, Si, Sr, Ti, and Zn. The application of multivariate chemometric techniques to the experimental results allowed us to determine the identification capability of the inorganic composition to identify correlations among the variables and to reveal similarities and differences among the different species. The results show the possibility of using this component for discriminating between different PAPS; in particular, fish PAPs are high in Cd, Sr, Na, and Mg content; swine PAPs have lower metal content due to high fat; feathers and vegetal feed have similar Al, Si, and Ni, but feathers are higher in Fe and Zn; and insect PATs have nutrient levels comparable to PAPs of other origins but are very high in Zn, Cu, and K. Full article
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<p>Graph for ICP-OES analysis results.</p>
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<p>PCA on mean ICP-OES and IC results.</p>
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14 pages, 466 KiB  
Article
Study of the Effects of Condensed Tannin Additives on the Health and Growth Performance of Early-Weaned Piglets
by Min Ma, Yuriko Enomoto, Tomotsugu Takahashi, Kazuyuki Uchida, James K. Chambers, Yuki Goda, Daisuke Yamanaka, Shin-Ichiro Takahashi, Masayoshi Kuwahara and Junyou Li
Animals 2024, 14(16), 2337; https://doi.org/10.3390/ani14162337 (registering DOI) - 14 Aug 2024
Abstract
Using 0.5% and 1.0% MGM-P, the objective of the present study was to determine a more appropriate additive level for early-weaned piglets as an alternative to the use of antibiotics. Thirty-six weaned piglets were allotted to one of four groups and given a [...] Read more.
Using 0.5% and 1.0% MGM-P, the objective of the present study was to determine a more appropriate additive level for early-weaned piglets as an alternative to the use of antibiotics. Thirty-six weaned piglets were allotted to one of four groups and given a basal diet (NC), with the basal diet containing either 0.5% (LT) or 1.0% (HT) MGM-P or antibiotics (PC). Diarrhea incidence, growth performance, hematology, blood biochemistry, and blood amino acid concentrations were monitored during the experimental period. Three piglets per group with a body weight nearest to the average level were slaughtered after the experiment to assess their organ index. The results showed that no diarrhea was observed either in the treatment groups or in the control group. The 0.5% group showed an upward trend in body weight and average daily gain at all stages. The WBC counts at 21 days of age were higher (p > 0.05) both in the MGM-P addition groups and the LT and HT groups. For some of the plasma amino acids, such as arginine, phenylalanine concentrations were significantly lower (p < 0.05) in the HT group at the end of the trial. The pathological examination of all organs confirmed no differences. Consequently, the 0.5% MGM-P addition level may be suggested as a potential alternative to the use of antibiotic additives. Even with additives as high as 1%, there is no negative effect on ADG and FCR. Full article
(This article belongs to the Special Issue Feed Additives in Pig Feeding: 2nd Edition)
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<p>Effects of MGM-P supplementation on the body weight of the weaned piglets. Values are expressed as the mean ± SEM; <span class="html-italic">n</span> = 9. There were no statistically significant differences among the four groups based on the results of the one-way analysis of variance.</p>
Full article ">
10 pages, 229 KiB  
Article
Effects of Dietary Energy Levels on Growth Performance, Serum Metabolites, and Meat Quality of Jersey Cattle–Yaks
by Dongqiang Zhang, Min Chu, Qianyun Ge, Ping Yan, Pengjia Bao, Xiaoming Ma, Xian Guo, Chunnian Liang and Xiaoyun Wu
Foods 2024, 13(16), 2527; https://doi.org/10.3390/foods13162527 (registering DOI) - 14 Aug 2024
Abstract
Energy feed can provide animals with balanced nutrition, thereby enhancing their growth performance. This study aimed to evaluate the effects of dietary energy levels on the growth performance, serum metabolites, and meat quality of Jersey cattle–yaks. A total of 24 male Jersey cattle–yaks [...] Read more.
Energy feed can provide animals with balanced nutrition, thereby enhancing their growth performance. This study aimed to evaluate the effects of dietary energy levels on the growth performance, serum metabolites, and meat quality of Jersey cattle–yaks. A total of 24 male Jersey cattle–yaks were randomly divided into three groups. Each group was fed diets with metabolizable energy levels of 8.21 MJ/kg (LE), 9.50 MJ/kg (ME), and 10.65 MJ/kg (HE), respectively. The HE and ME groups showed significantly higher final body weight, average daily gain (ADG), and feed efficiency compared to the LE group (p < 0.05). The glucose (GLU) and total cholesterol (TC) concentrations were significantly increased in the serum of the ME and HE groups (p < 0.05). The low-density lipoprotein cholesterol (LDL-C) and alanine aminotransferase (ALT) levels were significantly higher in the serum of the HE group than in the ME group (p < 0.05). Blood urea nitrogen (BUN) levels exhibited a significant decrease with increasing metabolizable energy levels in the diet (p < 0.05). Increasing dietary energy levels enhances the eye muscle area and intramuscular fat content of Jersey cattle–yaks (p < 0.05), with no effect on pH45 min, pH24 h, and shear force. In the HE group, the levels of heneicosanoic acid (C21:0), palmitoleic acid (C16:1), elaidic acid (C18:1n9t), and eicosadienoic acid (C20:2n6) were notably elevated (p < 0.05) when compared to the LE group. We concluded that a higher dietary energy level enhanced the growth performance and meat quality traits of male Jersey cattle–yaks. Full article
(This article belongs to the Topic Carcass Characteristics and Meat Quality in Farm Animals)
16 pages, 3382 KiB  
Article
Infestation of Rice Striped Stem Borer (Chilo suppressalis) Larvae Induces Emission of Volatile Organic Compounds in Rice and Repels Female Adult Oviposition
by Chen Shen, Shan Yu, Xinyang Tan, Guanghua Luo, Zhengping Yu, Jiafei Ju, Lei Yang, Yuxuan Huang, Shuai Li, Rui Ji, Chunqing Zhao and Jichao Fang
Int. J. Mol. Sci. 2024, 25(16), 8827; https://doi.org/10.3390/ijms25168827 (registering DOI) - 13 Aug 2024
Abstract
Plants regulate the biosynthesis and emission of metabolic compounds to manage herbivorous stresses. In this study, as a destructive pest, the pre-infestation of rice striped stem borer (SSB, Chilo suppressalis) larvae on rice (Oryza sativa) reduced the subsequent SSB female [...] Read more.
Plants regulate the biosynthesis and emission of metabolic compounds to manage herbivorous stresses. In this study, as a destructive pest, the pre-infestation of rice striped stem borer (SSB, Chilo suppressalis) larvae on rice (Oryza sativa) reduced the subsequent SSB female adult oviposition preference. Widely targeted volatilomics and transcriptome sequencing were used to identify released volatile metabolic profiles and differentially expressed genes in SSB-infested and uninfested rice plants. SSB infestation significantly altered the accumulation of 71 volatile organic compounds (VOCs), including 13 terpenoids. A total of 7897 significantly differentially expressed genes were identified, and genes involved in the terpenoid and phenylpropanoid metabolic pathways were highly enriched. Correlation analysis revealed that DEGs in terpenoid metabolism-related pathways were likely involved in the regulation of VOC biosynthesis in SSB-infested rice plants. Furthermore, two terpenoids, (−)-carvone and cedrol, were selected to analyse the behaviour of SSB and predators. Y-tube olfactometer tests demonstrated that both (−)-carvone and cedrol could repel SSB adults at higher concentrations; (−)-carvone could simultaneously attract the natural enemies of SSB, Cotesia chilonis and Trichogramma japonicum, and cedrol could only attract T. japonicum at lower concentrations. These findings provide a better understanding of the response of rice plants to SSB and contribute to the development of new strategies to control herbivorous pests. Full article
(This article belongs to the Special Issue Physiology and Molecular Biology of Plant Stress Tolerance)
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<p>Oviposition preference of SSB in different treated rice plants. (<b>A</b>) A scheme of the oviposition experiments; (<b>B</b>) Number of eggs laid by SSB female adults in uninfested and SSB pre-infested rice plants; (<b>C</b>) Numbers of egg masses by SSB female adults in uninfested and SSB pre-infested rice plants. The experiment was continued for 72 h and repeated 15 times. Statistical significance was calculated using SPSS. Each bar represents the mean ± SE. Data analysed using GLMs with Wald χ2 statistics indicate the overall difference between uninfested rice and SSB pre-infested rice plants. *** <span class="html-italic">p</span> &lt; 0.001 indicate significant differences between comparison groups.</p>
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<p>Volatile organic compounds analysis in rice plants. (<b>A</b>) Classification and proportion of 650 VOCs detected in rice plants. (<b>B</b>) Principal component analysis (PCA) among samples of rice plants by HS-SPME-GC-MS in different groups; the X-axis and Y-axis represent the first and second principal components, respectively.</p>
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<p>Overall analysis of VOC changes in rice plants’ response to SSB infestation. (<b>A</b>) Hierarchical cluster analysis of differentially accumulated VOCs in three treatment groups (SSB_24 h, SSB_48 h, Control); each group contained three biological replicates. (<b>B</b>) A histogram with VOCs in SSB-infested rice plants compared with the control group. (<b>C</b>) Venn of VOCs in two comparison groups.</p>
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<p>K-means plot and KEGG pathways enrichment of VOCs metabolome in SSB-infested rice compared with the control group. (<b>A</b>) VOCs from different samples collected from control, 24 h and 48 h after treatment were used for the K-means plot. KEGG pathways enrichment of VOCs metabolome in SSB_24 h vs. Control (<b>B</b>) and SSB_48 h vs. Control comparison groups (<b>C</b>).</p>
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<p>Overall analysis of differentially expressed genes changes in rice plant response to SSB infestation. (<b>A</b>) Principal component analysis of each transcriptome sample; X-axis, Y-axis and Z-axis represent the first, second and third principal components, respectively. (<b>B</b>) A histogram with DEGs in plants infested by SSB compared with control group. (<b>C</b>) Venn of DEGs in two comparison groups. (<b>D</b>) Hierarchical cluster analysis of DEGs in the three groups of SSB-infested; each group contained three biological replicates. (<b>E</b>,<b>F</b>) Bubble plots with KEGG pathways enriched for DEGs in rice infested by SSB at the 24 h and 48 h time-point compared with the control group.</p>
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<p>Analysis of terpenoid biosynthesis and differences between the three treatment groups in rice and GC-MS validation. Note: (<b>A</b>) Key structural genes and their expression level involved in terpenoid backbone biosynthesis pathway in rice in treatment groups. (<b>B</b>) Expression levels of differential metabolites in monoterpenoid biosynthesis pathway. DEV represents differentially expressed volatiles; DEG represents differentially expressed genes; red represents high expression levels; green and blue represent low expression levels in volatiles and transcript, respectively. (<b>C</b>) Relative abundance of (−)-carvone compared with SSB_induced to Control group in GC-MS. (The values represent the mean percentages ± SE of the peak area relative to the peak area of the internal standard). (<b>D</b>) Relative abundance of cedrol compared with SSB_induced to Control group in GC-MS. (The values represent the mean percentages ± SE of the peak area relative to the peak area of the internal standard).</p>
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<p>Analysis of terpenoid biosynthesis and differences between the three treatment groups in rice and GC-MS validation. Note: (<b>A</b>) Key structural genes and their expression level involved in terpenoid backbone biosynthesis pathway in rice in treatment groups. (<b>B</b>) Expression levels of differential metabolites in monoterpenoid biosynthesis pathway. DEV represents differentially expressed volatiles; DEG represents differentially expressed genes; red represents high expression levels; green and blue represent low expression levels in volatiles and transcript, respectively. (<b>C</b>) Relative abundance of (−)-carvone compared with SSB_induced to Control group in GC-MS. (The values represent the mean percentages ± SE of the peak area relative to the peak area of the internal standard). (<b>D</b>) Relative abundance of cedrol compared with SSB_induced to Control group in GC-MS. (The values represent the mean percentages ± SE of the peak area relative to the peak area of the internal standard).</p>
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<p>Behaviour response to significant chemical compounds in monoterpenoid biosynthesis pathway to SSB; natural enemy <span class="html-italic">Cotesia chilonis</span>, <span class="html-italic">Trichogramma japonicum</span>. (<b>A</b>–<b>C</b>) show preference for SSB, <span class="html-italic">C. chilonis</span>, and <span class="html-italic">T. japonicum</span> behaviour response to chemical compounds (−)-carvone, respectively. (<b>D</b>–<b>F</b>) show the preference of SSB, <span class="html-italic">C. chilonis</span>, and <span class="html-italic">T. japonicum</span> behaviour response to chemical compounds cedrol, respectively.</p>
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25 pages, 3521 KiB  
Article
Emission Rate Estimation of Industrial Air Pollutant Emissions Based on Mobile Observation
by Xinlei Cui, Qi Yu, Weichun Ma and Yan Zhang
Atmosphere 2024, 15(8), 969; https://doi.org/10.3390/atmos15080969 (registering DOI) - 13 Aug 2024
Abstract
Mobile observation has been widely used in the monitoring of air pollution. However, studies on pollution sources and emission characteristics based on mobile navigational observation are rarely reported in the literature. A method for quantitative source analysis for industrial air pollutant emissions based [...] Read more.
Mobile observation has been widely used in the monitoring of air pollution. However, studies on pollution sources and emission characteristics based on mobile navigational observation are rarely reported in the literature. A method for quantitative source analysis for industrial air pollutant emissions based on mobile observations is introduced in this paper. NOx pollution identified in mobile observations is used as an example of the development of the method. A dispersion modeling scheme that fine-tuned the meteorological parameters according to the actual meteorological conditions was adopted to minimize the impact of uncertainties in meteorological conditions on the accuracy of small-scale dispersion modeling. The matching degree between simulated and observed concentrations was effectively improved through this optimization search. In response to the efficiency requirements of source resolution for multiple sources, a random search algorithm was first used to generate candidate solution samples, and then the solution samples were evaluated and optimized. Meanwhile, the new index was established to evaluate the quality of candidate samples, considering both numerical error and spatial distribution error of concentration, in order to address the non-uniqueness of the solution in the multi-source problem. Then, the necessity of considering the spatial distribution error of concentration is analyzed with the case study. The average values of NOx emission rates for the two study cases were calculated as 69.8 g/s and 70.8 g/s. The scores were 0.92–0.97 and 0.92–0.99. The results were close to the online monitoring data, and this kind of pollutant emission monitoring based on the mobile observation experiment was initially considered feasible. Additional analysis and clarifications were provided in the discussion section on the impact of uncertainties in meteorological conditions, the establishment of a priori emission inventories, and the interpretation of inverse calculation results. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
16 pages, 2045 KiB  
Article
Plant-Based Substrates for the Production of Iron Bionanoparticles (Fe-BNPs) and Application in PCB Degradation with Bacterial Strains
by Marcela Tlčíková, Hana Horváthová, Katarína Dercová, Michaela Majčinová, Mariana Hurbanová, Katarína Turanská and Ľubomír Jurkovič
Processes 2024, 12(8), 1695; https://doi.org/10.3390/pr12081695 - 13 Aug 2024
Abstract
Removing polychlorinated biphenyls (PCBs) from the environment is an important process for the protection of biota. This work examines three different approaches to the degradation of such contaminants. The first involves the use of iron bionanoparticles (Fe-BNPs) prepared through green synthesis from selected [...] Read more.
Removing polychlorinated biphenyls (PCBs) from the environment is an important process for the protection of biota. This work examines three different approaches to the degradation of such contaminants. The first involves the use of iron bionanoparticles (Fe-BNPs) prepared through green synthesis from selected plant matrices. The second approach entails the use of the bacteria Stenotrophomonas maltophilia (SM) and Ochrobactrum anthropi (OA) isolated from a PCB-contaminated area, Strážsky canal, located in the Slovak republic, which receives efflux of canal from Chemko Strážske plant, a former producer of PCB mixtures. The third approach combines these two methods, employing a sequential hybrid two-step application of Fe-BNPs from the plant matrix followed by the application of bacterial strains. Fe-BNPs are intended to be an eco-friendly alternative to synthetic nanoscale zero-valent iron (nZVI), which is commonly used in many environmental applications. This work also addresses the optimization parameters for using nZVI in PCB degradation, including the pH of the reaction, oxygen requirements, and dosage of nZVI. Pure standards of polyphenols (gallic acid, GA) and flavonoids (quercetin, Q) were tested to produce Fe-BNPs using green synthesis at different concentrations (0.1, 0.3, 0.5, 0.8, and 1 g.L−1) and were subsequently applied to the PCB degradation experiments. This step monitored the minimum content of bioactive substances needed for the synthesis of Fe-BNPs and their degradation effects. Experimental analysis indicated that among the selected approaches, sequential nanobiodegradation appears to be the most effective for PCB degradation, specifically the combination of Fe-BNPs from sage and bacteria SM (75% degradation of PCBs) and Fe-BNPs from GA (0.3 g.L−1) with bacteria OA (92% degradation of PCBs). Full article
(This article belongs to the Special Issue Advances in Wastewater and Solid Waste Treatment Processes)
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<p>Degradation of PCBs using Fe-BNPs synthesized from six different substrates. Experimental conditions: 7 days, 20 °C, and 100 rpm.</p>
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<p>Degradation of the sum of seven PCB congeners using iron bionanoparticles from Q (Q-derived Fe-BNPs) and iron bionanoparticles from GA (GA-derived Fe-BNPs) at five different concentrations (0.1; 0.3; 0.5; 0.8; and 1 g.L<sup>−1</sup>). Experimental conditions: 7 days, 20 °C, and 100 rpm.</p>
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<p>Degradation of PCBs by individual bacterial strains <span class="html-italic">Ochrobactrum anthropi</span> and <span class="html-italic">Stenotrophomonas maltophilia</span>. Experimental conditions: 14 days, 20 °C, and 180 rpm.</p>
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<p>Sequential degradation of PCBs using plant-based Fe-BNPs and the bacteria <span class="html-italic">S. maltophilia</span>. Experimental conditions: 7-day cultivation with limited oxygen access to the reagent flask (3 mL of Fe-BNPs) at 25 °C and 100 rpm, and then 14-day cultivation under aerobic conditions (1 g.L<sup>−1</sup> of bacterial inoculum at 25 °C and 180 rpm.</p>
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<p>Sequential degradation of PCBs using plant-based Fe-BNPs and the bacteria <span class="html-italic">O. anthropi</span>. Experimental conditions: 7-day cultivation with limited oxygen access to the reagent flask (3 mL of Fe-BNPs) at 25 °C and 100 rpm, and then 14-day cultivation under aerobic conditions (1 g.L<sup>−1</sup> of bacterial inoculum) at 25 °C and 180 rpm.</p>
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<p>Sequential degradation of the sum of PCB congeners using Fe-BNPs from GA and Fe-BNPs from Q with the addition of bacterial strain <span class="html-italic">O. anthropi</span> (OA). Experimental conditions: 7-day anaerobic cultivation at 25 °C and 100 rpm, and then 14-day aerobic cultivation and 25 °C and 180 rpm.</p>
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<p>Graphical comparison of nanodegradation (Fe-BNPs applied individually) and nanobiodegradation of PCBs (Fe-BNPs with subsequent application of bacterial strain OA or SM) approaches with four different Fe-BNPs prepared from selected plants.</p>
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19 pages, 1701 KiB  
Review
Upholding or Breaking the Law of Superposition in Pharmacokinetics
by Malaz Yousef, Jaime A. Yáñez, Raimar Löbenberg and Neal M. Davies
Biomedicines 2024, 12(8), 1843; https://doi.org/10.3390/biomedicines12081843 - 13 Aug 2024
Abstract
The law of superposition underpins first-order linear pharmacokinetic relationships. Most drugs, therefore, after a single dose can be described by first-order or linear processes, which can be superposed to understand multiple-dose regimen behavior. However, there are a number of situations where drugs could [...] Read more.
The law of superposition underpins first-order linear pharmacokinetic relationships. Most drugs, therefore, after a single dose can be described by first-order or linear processes, which can be superposed to understand multiple-dose regimen behavior. However, there are a number of situations where drugs could display behaviors after multiple dosing that leads to capacity-limited or saturation non-linear kinetics and the law of superposition is overruled. This review presents a practical guide to understand the equations and calculations for single and multiple-dosing regimens after intravenous and oral administration. It also provides the pharmaceutical basis for saturation in ADME processes and the consequent changes in the area under the concentration–time curve, which represents drug exposure that can lead to the modulation of efficacy and/or toxic effects. The pharmacokineticist must implicitly understand the principles of superposition, which are a central tenet of drug behavior and disposition during drug development. Full article
(This article belongs to the Special Issue Pharmacokinetics and Pharmacodynamics of Therapeutic Biologics)
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<p>Concentration time profile after a single dose and multiple dosing when reaching the steady state.</p>
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<p>Concentration–time profile of an ideal scenario after multiple-dose regimen 132, administered at the same time interval and reaching a steady state. Modified from Wang et al. [<a href="#B19-biomedicines-12-01843" class="html-bibr">19</a>].</p>
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<p>Representation of a concentration–time profile after six sequential doses administered at the same time interval until the steady state. Modified from Wang et al. [<a href="#B19-biomedicines-12-01843" class="html-bibr">19</a>].</p>
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<p>The law of superposition used to generate the concentration profile of multiple dosing from the profile of a single dose. The area of the first dose during the interval of the second dose adds to the area of the second dose, and so on. Modified from Van Rossum and de Bie [<a href="#B34-biomedicines-12-01843" class="html-bibr">34</a>].</p>
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<p>(<b>a</b>) Linearity of pharmacokinetics and the validity of the superposition principle, along with (<b>b</b>) scenarios where non-linearity in pharmacokinetics leads to the breakdown of this principle.</p>
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19 pages, 8318 KiB  
Article
Study on the Effect of Size on the Surface Wind Pressure and Shape Factor of Wind Load of Solar Greenhouses
by Zongmin Liang, Zixuan Gao, Yanfeng Li, Shumei Zhao, Rui Wang and Jing Xu
Appl. Sci. 2024, 14(16), 7114; https://doi.org/10.3390/app14167114 - 13 Aug 2024
Abstract
In this paper, the effect of size on the wind pressure coefficient on the surface of solar greenhouses is investigated using numerical simulations. The models were designed with consistent ratios of ridge height to span and north wall height to ridge height across [...] Read more.
In this paper, the effect of size on the wind pressure coefficient on the surface of solar greenhouses is investigated using numerical simulations. The models were designed with consistent ratios of ridge height to span and north wall height to ridge height across different spans. To effectively understand the impact of dimensions on wind pressure distribution, two wind directions—0° (north wind) and 180° (south wind)—which have previously been shown to impose significant overall wind loads on solar greenhouses, are focused on. It was found that the wind load per unit area increases continuously with greenhouse size. Wind-induced suction is particularly concentrated along the ridge, with greater suction on the leeward side compared to the windward side. The wind suction near the ridge is more significantly affected by greenhouse size. This study provides valuable insights for the practical engineering design of solar greenhouses. Full article
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<p>Surface profile of solar greenhouse.</p>
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<p>Size of calculation domain under 0° wind angle. Note: X-axis is parallel to the direction of incoming wind, Y-axis is height direction, Z-axis is perpendicular to the direction of incoming wind; 10 <span class="html-italic">L</span>, 9 <span class="html-italic">W</span>, 5 <span class="html-italic">H</span> are the length, width, and height of the calculation domain, respectively; <span class="html-italic">L</span> is the length of the greenhouse profile perpendicular to the incoming flow, m; <span class="html-italic">W</span> is the length of the greenhouse profile parallel to the incoming flow, m; and <span class="html-italic">H</span> is the height of the greenhouse, m.</p>
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<p>Cloud chart of wind pressure coefficients on the north wall of solar greenhouse with five different sizes under 0° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the north wall of solar greenhouse with five different sizes under 0° wind angle.</p>
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<p>Wind pressure coefficient curve at h/2 height of north wall with different sizes.</p>
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<p>Cloud chart of wind pressure coefficients on the rear roof of solar greenhouses with five different sizes under 0° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the rear roof of solar greenhouses with five different sizes under 0° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the front roof of solar greenhouses with five different sizes under 0° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the front roof of solar greenhouses with five different sizes under 0° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the north wall of solar greenhouses with five different sizes under 180° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the rear roof of solar greenhouses with five different sizes under 180° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the front roof of solar greenhouses with five different sizes under 180° wind angle.</p>
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<p>Cloud chart of wind pressure coefficients on the front roof of solar greenhouses with five different sizes under 180° wind angle.</p>
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<p>Extreme wind pressure at the ridge with 0° wind angle.</p>
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<p>Extreme wind pressure at the ridge with 180° wind angle.</p>
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<p>Surface zoning plan of solar greenhouse.</p>
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<p>Comparison of the arc length of the lower part of the front roof with different zoning methods under 180° wind angle.</p>
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14 pages, 5473 KiB  
Article
In-Situ Sulfuration of CoAl Metal–Organic Framework for Enhanced Supercapacitor Properties
by Mengchen Liao, Kai Zhang, Chaowei Luo, Guozhong Wu and Hongyan Zeng
Materials 2024, 17(16), 4030; https://doi.org/10.3390/ma17164030 - 13 Aug 2024
Abstract
Designing efficient electrode materials is necessary for supercapacitors but remains highly challenging. Herein, cobalt sulfide with crystalline/amorphous heterophase (denoted as Co(Al)S) derived from an Al metal–organic framework was constructed by ion exchange/acid etching and subsequent sulfidation strategy. It was found that rational sulfidation [...] Read more.
Designing efficient electrode materials is necessary for supercapacitors but remains highly challenging. Herein, cobalt sulfide with crystalline/amorphous heterophase (denoted as Co(Al)S) derived from an Al metal–organic framework was constructed by ion exchange/acid etching and subsequent sulfidation strategy. It was found that rational sulfidation by adjusting the sulfur source concentration to a suitable level was favorable to form a 3D nanosheet-interconnected network architecture with a large specific surface area, which promoted ion/electron transport and charge separation. Benefiting from the features of the unique network structure and heterophase accompanied by aluminum, nitrogen and carbon coordinated in amorphous phase, the optimal Co(Al)S(10) exhibited a high specific capacity (1791.8 C g−1 at 1 A g−1), an outstanding rate capability and an excellent cycling stability. Furthermore, the as-assembled Co(Al)S//AC device afforded an energy density of 72.3 Wh kg−1 at a power density of 750 W kg−1, verifying that the Co(Al)S was a promising material for energy storage devices. The developed scheme is expected to promote the application of MOF-derived electrode materials in electrochemical energy storage and conversion fields. Full article
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<p>SEM images of the CAU-1, Co(Al)O, and Co(Al)S samples.</p>
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<p>TEM (<b>A</b>), HRTEM (<b>B</b>–<b>D</b>) and HAADF-STEM (<b>E</b>) images of the Co(Al)S<sub>(10)</sub>.</p>
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<p>(<b>A</b>) XRD patterns of the Co(Al)O and the Co(Al)S; (<b>B</b>) Raman spectra of the Co(Al)O and the Co(Al)S<sub>(10)</sub>; (<b>C</b>) N<sub>2</sub> adsorption–desorption isotherms; (<b>D</b>) pore size distributions of the Co(Al)O and the Co(Al)S.</p>
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<p>XPS spectrum of the Co(Al)S<sub>(10)</sub> (survey (<b>A</b>), Co 2p (<b>B</b>), N 1s (<b>C</b>), C 1s (<b>D</b>), S 2p (<b>E</b>) and Al 2p (<b>F</b>)).</p>
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<p>(<b>A</b>) CV curves of the Co(Al)O and the Co(Al)S at 30 mV s<sup>–1</sup>; (<b>B</b>) CV curves of the Co(Al)S<sub>(10)</sub> at different scan rates; (<b>C</b>) plots of log<span class="html-italic">i</span> vs. log<span class="html-italic">υ</span> for the CoAl<sub>2</sub>O<sub>4</sub> and the Co(Al)S; (<b>D</b>) capacitive contribution of the Co(Al)S<sub>(10)</sub> and the Co(Al)O (<b>E</b>) at 5 mV s<sup>–1</sup>; (<b>F</b>) histograms of the capacitance contributions for the Co(Al)S<sub>(10)</sub> (red area) and the Co(Al)O (blue-gray area) at different scan rates.</p>
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<p>Nyquist plots (<b>A</b>) and GCD profiles at 1 A g<sup>−1</sup> (<b>B</b>) of the Co(Al)O and the Co(Al)S; GCD profiles of the Co(Al)S<sub>(10)</sub> at different current densities (<b>C</b>); specific charges of the Co(Al)O and the Co(Al)S at different current densities (<b>D</b>); cycling stability of the Co(Al)O and the Co(Al)S<sub>(10)</sub> (<b>E</b>); schematic illustration of the energy storage mechanism of the Co(Al)S (<b>F</b>).</p>
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<p>SEM(<b>A</b>) and XRD images (<b>B</b>) of the spent Co(Al)S<sub>(10)</sub>; CV curves at 30 mV s<sup>–1</sup> (<b>C</b>); GCD profiles at 1 A g<sup>–1</sup> (<b>D</b>); and Nyquist plots (<b>E</b>) of the Co(Al)S<sub>(10)</sub> before and after 5000 cycles. Capacitance contribution (<b>F</b>) of the spent Co(Al)S<sub>(10)</sub> at 5 mV s<sup>−1</sup>.</p>
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<p>Supercapacitor performances of the Co(Al)S//AC device. (<b>A</b>) CV curves of the AC and the Co(Al)S<sub>(10)</sub> at 10 mV s<sup>−1</sup> in a three-electrode system; (<b>B</b>) CV curves at 10 mV s<sup>−1</sup> in different working potentials; (<b>C</b>) CV curves at 1.5 V in different scan rates; (<b>D</b>) GCD curves at different current densities; (<b>E</b>) cycling stability at 1.0 A g<sup>−1</sup>; (<b>F</b>) Ragone plots [<a href="#B14-materials-17-04030" class="html-bibr">14</a>,<a href="#B24-materials-17-04030" class="html-bibr">24</a>,<a href="#B27-materials-17-04030" class="html-bibr">27</a>,<a href="#B39-materials-17-04030" class="html-bibr">39</a>,<a href="#B46-materials-17-04030" class="html-bibr">46</a>,<a href="#B48-materials-17-04030" class="html-bibr">48</a>,<a href="#B49-materials-17-04030" class="html-bibr">49</a>].</p>
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<p>Synthesis procedure and phase transformation of the Co(Al)S.</p>
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18 pages, 1031 KiB  
Article
Chemical Characterization of Cider Produced in Hardanger—From Juice to Finished Cider
by Ingunn Øvsthus, Mitja Martelanc, Alen Albreht, Tatjana Radovanović Vukajlović, Urban Česnik and Branka Mozetič Vodopivec
Beverages 2024, 10(3), 73; https://doi.org/10.3390/beverages10030073 - 13 Aug 2024
Abstract
Our investigation delves into the previously uncharted territory of cider composition from Norway. This study aimed to obtain an overview of the qualitative and quantitative compositions of general chemical parameters, polyphenols (individual and total expressed as gallic acids equivalents), selected esters, and selected [...] Read more.
Our investigation delves into the previously uncharted territory of cider composition from Norway. This study aimed to obtain an overview of the qualitative and quantitative compositions of general chemical parameters, polyphenols (individual and total expressed as gallic acids equivalents), selected esters, and selected C6-alcohols in ciders with the PDO label Cider from Hardanger. In total, 45 juice and cider samples from the fermentation process were collected from 10 cider producers in Hardanger in 2019, 2020, and 2021. Individual sugars, acids, ethanol, and 13 individual phenols were quantified using HPLC-UV/RI. Seven ethyl esters of fatty acids, four ethyl esters of branched fatty acids, ten acetate esters, two ethyl esters of hydroxycinnamic acids, and four C6-alcohols were quantified using HS-SPME-GC-MS. For samples of single cultivars (‘Aroma’, ‘Discovery’, ‘Gravenstein’, and ‘Summerred’), the sum of the measured individual polyphenols in the samples ranges, on average, from 79 to 289 mg L−1 (the lowest for ‘Summerred’ and highest for ‘Discovery’ and ‘Gravenstein’). Chlorogenic acid was the most abundant polyphenol in all samples. Ethyl butyrate, ethyl hexanoate, ethyl octanoate, ethyl decanoate, ethyl isobutyrate, ethyl 2-methylbutyrate, isoamyl acetate, and hexanol were present at concentrations above the odour threshold and contributed to the fruity flavour of the Cider from Hardanger. Full article
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<p>Principal component analysis loading plot (<b>A</b>) and score plot for cultivars (<b>B</b>) for measured esters and C6-alcohols in the collected samples in 2019, 2020, and 2021 for ciders. Aroma compounds in bold letters are in concentrations over the threshold limit.</p>
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15 pages, 2700 KiB  
Article
Conservation Practices Boost Soil-Protected Organic Carbon Stocks in Olive Orchards
by Evangelina Pareja-Sánchez, Pablo Domouso, Beatriz Gómez-Muñoz, María T. Heras-Linares and Roberto García-Ruíz
Agriculture 2024, 14(8), 1354; https://doi.org/10.3390/agriculture14081354 - 13 Aug 2024
Abstract
Carbon farming practices are pivotal for enhancing soil organic carbon (SOC) storage in agricultural systems. This study focuses on evaluating the effects of spontaneous cover crops as a conservation strategy compared to conventional management practices on total, non-protected, and protected SOC fractions, as [...] Read more.
Carbon farming practices are pivotal for enhancing soil organic carbon (SOC) storage in agricultural systems. This study focuses on evaluating the effects of spontaneous cover crops as a conservation strategy compared to conventional management practices on total, non-protected, and protected SOC fractions, as well as carbon saturation, in olive groves across 13 paired sites (26 sites in total) in Andalucía, Spain. The research evaluates organic carbon concentrations in different soil fractions: non-protected (250–2000 µm), physically protected (53–250 µm), and chemically protected (<53 µm). The results reveal that olive groves managed with temporary spontaneous cover crops (CC) over the last 8–12 years generally exhibit higher SOC concentrations compared to those managed conventionally (BS), with significant differences observed across multiple sites. CC sites exhibited higher carbon stocks, with protected carbon averaging 42.6 Mg C ha−1 compared to 29.7 Mg C ha−1 in BS, and non-protected carbon at 10.3 Mg C ha−1 versus 4.8 Mg C ha−1. A direct relationship was identified between total SOC and both protected and non-protected carbon fractions, indicating that the soil of the studies olive orchards is far from being saturated in protected SOC. Moreover, the soil of the CC olive farms had a lower carbon saturation deficit (45.3%) compared to BS (67.2%). The findings show that maintaining the cover crops in olive orchards significantly contributed to carbon sequestration and reduced carbon saturation deficits by increasing the stocks of protected SOC. Full article
(This article belongs to the Special Issue Soil Conservation in Olive Orchard)
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<p>Placement of the olive orchards selected in Andalucía (Spain).</p>
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<p>Soil organic carbon concentration per gram of fraction (mg C g<sup>−1</sup> fraction) (<b>a</b>–<b>c</b>) and per gram of soil (mg C g<sup>−1</sup> soil) (<b>d</b>–<b>f</b>) of different fractions (non-protected C 250–2000 µm (<b>a</b>,<b>d</b>); physically protected 53–250 µm (<b>b</b>,<b>e</b>) and chemically protected &lt;53 µm (<b>c</b>,<b>f</b>)) as affected by management (CC; spontaneous cover crops and BS; bare soil) at different sites. Vertical bars indicate standard errors. The asterisk denotes significant differences between the CC and BS olive groves in each pair (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Average of soil organic carbon concentration per gram of fraction (mg C g<sup>−1</sup> fraction) (<b>a</b>–<b>c</b>) and per gram of soil (mg C g<sup>−1</sup> soil) (<b>d</b>–<b>f</b>) of different fractions (non-protected C 250–2000 µm (<b>a</b>,<b>d</b>); physically protected 53–250 µm (<b>b</b>,<b>e</b>) and chemically protected &lt;53 µm) (<b>c</b>,<b>f</b>) as affected by management (CC; spontaneous cover crops and BS; bare soil). Vertical bars indicate standard errors. Distinct lowercase letters signify significant differences between management treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Stock of soil organic carbon (stock SOC) (Mg C ha<sup>−1</sup> top 30 cm of soil) as affected by management (CC; spontaneous cover crops and BS; bare soil) of different fractions (protected and non-protected soil carbon) at the site of field experiments and average (Average) of the groups of CC and BS olive groves. Vertical bars indicate standard errors. The asterisk denotes significant differences between the CC and BS olive groves in each pair (<span class="html-italic">p</span> &lt; 0.05) for both non-protected (upper asterisk) and protected SOC (lower asterisk).</p>
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<p>Linear regression between total soil organic carbon (total SOC) (mg g<sup>−1</sup> soil) and (<b>a</b>) protected soil carbon (mg g<sup>−1</sup> soil) and (<b>b</b>) non-protected soil carbon (mg g<sup>−1</sup> soil). Each point represents the values of each replicate for each site.</p>
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<p>Box-plot representation of carbon saturation deficit (% of the current SOC content (mg C g<sup>−1</sup>) relative to the SOC content (mg C g<sup>−1</sup>) at carbon saturation) in each soil management (CC; spontaneous cover crops and BS; bare soil). Dots are the values of each group. The edges of the boxes nearest to and farthest from zero represent the 25th and 75th percentiles, respectively. The thin lines inside the boxes denote the median, while the ‘X’ symbol indicates the mean. The bars extending above and below the box correspond to the 90th and 10th percentiles. Outliers are shown as black dots. Distinct lowercase letters denote statistically significant differences between soil management practices (CC and BS) at <span class="html-italic">p</span> &lt; 0.05.</p>
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