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Search Results (24,826)

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14 pages, 1550 KiB  
Article
Non-Invasive Detection of Nitrogen Deficiency in Cannabis sativa Using Hand-Held Raman Spectroscopy
by Graham Antoszewski, James F. Guenther, John K. Roberts, Mickal Adler, Michael Dalle Molle, Nicholas S. Kaczmar, William B. Miller, Neil S. Mattson and Heather Grab
Agronomy 2024, 14(10), 2390; https://doi.org/10.3390/agronomy14102390 (registering DOI) - 16 Oct 2024
Abstract
Proper crop management requires rapid detection methods for abiotic and biotic stresses to ensure plant health and yield. Hemp (Cannabis sativa L.) is an emerging economically and environmentally sustainable crop capable of yielding high biomass. Nitrogen deficiency significantly reduces hemp plant growth, [...] Read more.
Proper crop management requires rapid detection methods for abiotic and biotic stresses to ensure plant health and yield. Hemp (Cannabis sativa L.) is an emerging economically and environmentally sustainable crop capable of yielding high biomass. Nitrogen deficiency significantly reduces hemp plant growth, affecting photosynthetic capacity and ultimately decreasing yield. When symptoms of nitrogen deficiency are visible to humans, there is often already lost yield. A real-time, non-destructive detection method, such as Raman spectroscopy, is therefore critical to identify nitrogen deficiency in living hemp plant tissue for fast, precise crop remediation. A two-part experiment was conducted to investigate portable Raman spectroscopy as a viable hemp nitrogen deficiency detection method and to compare the technique’s predictive ability against a handheld SPAD (chlorophyll index) meter. Raman spectra and SPAD readings were used to train separate nitrogen deficiency discrimination models. Raman scans displayed characteristic spectral markers indicative of nitrogen deficiency corresponding to vibrational modes of carotenoids, essential pigments for photosynthesis. The Raman-based model consistently predicted nitrogen deficiency in hemp prior to the onset of visible stress symptoms across both experiments, while SPAD only differentiated nitrogen deficiency in the second experiment when the stress was more pronounced. Our findings add to the repertoire of plant stresses that hand-held Raman spectroscopy can detect by demonstrating the ability to provide assessments of nitrogen deficiency. This method can be implemented at the point of cultivation, allowing for timely interventions and efficient resource use. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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<p>Agilent Resolve spectrometer scanning the upper node, leaflet 2, of ‘TJ’s CBD’ hemp.</p>
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<p>The mean and standard deviation (shaded region) of Raman spectra of hemp leaf samples after 7 days under N-deficient (n = 36) versus complete nutrition (n = 36) in the two-cultivar trial [<a href="#B39-agronomy-14-02390" class="html-bibr">39</a>].</p>
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<p>Variable importance in projection scores for the three-component PLS-DA model for (<b>a</b>) early and (<b>b</b>) later-stage nitrogen deficiency detection. A VIP score &gt; 1 implies that the wavelength contributes significant information towards the model’s predictions.</p>
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<p>Photos of hemp leaf samples from the first experiment after (<b>a</b>) 7 days of nitrogen-deficient nutrient solution and (<b>b</b>) 7 days of complete solution. (<b>c</b>) Differences in mean SPAD readings between the two trial periods. Error bars represent measured standard deviation.</p>
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20 pages, 5877 KiB  
Article
Black Carbon in Climate Studies: A Bibliometric Analysis of Research Trends and Topics
by Chao Chen, Yinglin Liang, Zhilong Chen, Changwu Zou and Zongbo Shi
Sustainability 2024, 16(20), 8945; https://doi.org/10.3390/su16208945 (registering DOI) - 16 Oct 2024
Abstract
Black carbon is a short-lived climate warming agent and serves as a crucial factor influencing the climate. Numerous models, observations, and laboratory studies have been conducted to quantify black carbon’s direct or indirect impacts on the climate. Here, we applied bibliometric analysis to [...] Read more.
Black carbon is a short-lived climate warming agent and serves as a crucial factor influencing the climate. Numerous models, observations, and laboratory studies have been conducted to quantify black carbon’s direct or indirect impacts on the climate. Here, we applied bibliometric analysis to identify research trends and key topics on black carbon in the climate field. Based on the Web of Science (WOS) Core Collection database, a total of 4903 documents spanning the period from 2000 to 2023 were retrieved and screened, focusing on the topic of black carbon in the climate field, resulting in the Black-Carbon Climate Local (BCL) dataset. Our study examines the influence and trends of major countries, institutions, and authors in this field. The results show that China and the United States hold leading positions in terms of the number of publications. Based on keyword networks, the BCL dataset is segmented into six distinct research directions, and representative keywords of each direction include biomass burning, radiative forcing, air pollution, aerosol optical depth, optical properties, and biochar. This study helps to identify the current research status and trends of black carbon in the climate, highlighting main research directions and emerging topics. Full article
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Figure 1
<p>Conceptual framework of the literature retrieval methods. The asterisk (*) used as a truncation symbol used in search queries, broadening the search to include words starting with “climat”.</p>
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<p>Annual total publications from 2000 to 2023 (the black line) and annual publications of top ten countries (stacked bars).</p>
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<p>(<b>a</b>) International cooperation network, with the node size representing its total link strength, and the color representing the average citations. (<b>b</b>) Development trends in cooperation between major developed and developing countries. The green line with diamond nodes represents the proportionate link strength of USA–China to the total link strength of China, and the green line with triangular nodes represents the proportionate link strength of USA–China to the total link strength of the USA. Orange lines represent the collaboration trends between the USA and Germany, and blue lines represent those between China and India.</p>
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<p>(<b>a</b>) The yearly count of publications for the top ten institutions, (<b>b</b>) the institutional cooperation network, with the color of the links between nodes representing the time when two institutions started collaborating, and (<b>c</b>) the grouped clusters of institutions. <a href="#app1-sustainability-16-08945" class="html-app">Table S5</a> contains the full names corresponding to the institutional abbreviations.</p>
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<p>(<b>a</b>) The top ten authors by cumulative publications over time, with the size of each sphere corresponding to the number of articles, and the color intensity representing the average citation rate. (<b>b</b>) The author cooperation network, with the color of each node representing the standardized average citation of the author’s publications.</p>
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<p>(<b>a</b>) Keyword network with grouped clusters, with the node size correlated positively with the frequency of keyword occurrence, and (<b>b</b>) research trends in topics over time. Each blue sphere represents a topic, corresponding to an author keyword, with its size proportional to the keyword’s frequency of occurrence. The placement of each sphere corresponds to the median frequency distribution of the keyword’s occurrences, and the grey bars represent the first and third quartiles of the frequency distribution.</p>
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<p>Network graph of the top 5 review articles and the top 25 articles in terms of citations [<a href="#B1-sustainability-16-08945" class="html-bibr">1</a>,<a href="#B2-sustainability-16-08945" class="html-bibr">2</a>,<a href="#B6-sustainability-16-08945" class="html-bibr">6</a>,<a href="#B11-sustainability-16-08945" class="html-bibr">11</a>,<a href="#B24-sustainability-16-08945" class="html-bibr">24</a>,<a href="#B40-sustainability-16-08945" class="html-bibr">40</a>,<a href="#B49-sustainability-16-08945" class="html-bibr">49</a>,<a href="#B52-sustainability-16-08945" class="html-bibr">52</a>,<a href="#B53-sustainability-16-08945" class="html-bibr">53</a>,<a href="#B55-sustainability-16-08945" class="html-bibr">55</a>,<a href="#B56-sustainability-16-08945" class="html-bibr">56</a>,<a href="#B81-sustainability-16-08945" class="html-bibr">81</a>,<a href="#B82-sustainability-16-08945" class="html-bibr">82</a>,<a href="#B83-sustainability-16-08945" class="html-bibr">83</a>,<a href="#B84-sustainability-16-08945" class="html-bibr">84</a>,<a href="#B85-sustainability-16-08945" class="html-bibr">85</a>,<a href="#B86-sustainability-16-08945" class="html-bibr">86</a>,<a href="#B87-sustainability-16-08945" class="html-bibr">87</a>,<a href="#B88-sustainability-16-08945" class="html-bibr">88</a>,<a href="#B89-sustainability-16-08945" class="html-bibr">89</a>,<a href="#B90-sustainability-16-08945" class="html-bibr">90</a>,<a href="#B91-sustainability-16-08945" class="html-bibr">91</a>,<a href="#B92-sustainability-16-08945" class="html-bibr">92</a>,<a href="#B93-sustainability-16-08945" class="html-bibr">93</a>,<a href="#B94-sustainability-16-08945" class="html-bibr">94</a>,<a href="#B95-sustainability-16-08945" class="html-bibr">95</a>,<a href="#B96-sustainability-16-08945" class="html-bibr">96</a>,<a href="#B97-sustainability-16-08945" class="html-bibr">97</a>,<a href="#B98-sustainability-16-08945" class="html-bibr">98</a>,<a href="#B99-sustainability-16-08945" class="html-bibr">99</a>]. Each node represents an article, and articles with citation relationships are represented using the same color.</p>
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<p>Network graph of references with the highest local citations within each time slice, with the size of node positively correlated to their local citations and different colored lines represent different time periods [<a href="#B1-sustainability-16-08945" class="html-bibr">1</a>,<a href="#B2-sustainability-16-08945" class="html-bibr">2</a>,<a href="#B6-sustainability-16-08945" class="html-bibr">6</a>,<a href="#B8-sustainability-16-08945" class="html-bibr">8</a>,<a href="#B13-sustainability-16-08945" class="html-bibr">13</a>,<a href="#B21-sustainability-16-08945" class="html-bibr">21</a>,<a href="#B22-sustainability-16-08945" class="html-bibr">22</a>,<a href="#B24-sustainability-16-08945" class="html-bibr">24</a>,<a href="#B40-sustainability-16-08945" class="html-bibr">40</a>,<a href="#B49-sustainability-16-08945" class="html-bibr">49</a>,<a href="#B52-sustainability-16-08945" class="html-bibr">52</a>,<a href="#B53-sustainability-16-08945" class="html-bibr">53</a>,<a href="#B67-sustainability-16-08945" class="html-bibr">67</a>,<a href="#B82-sustainability-16-08945" class="html-bibr">82</a>,<a href="#B83-sustainability-16-08945" class="html-bibr">83</a>,<a href="#B85-sustainability-16-08945" class="html-bibr">85</a>,<a href="#B86-sustainability-16-08945" class="html-bibr">86</a>,<a href="#B89-sustainability-16-08945" class="html-bibr">89</a>,<a href="#B91-sustainability-16-08945" class="html-bibr">91</a>,<a href="#B100-sustainability-16-08945" class="html-bibr">100</a>,<a href="#B101-sustainability-16-08945" class="html-bibr">101</a>,<a href="#B102-sustainability-16-08945" class="html-bibr">102</a>,<a href="#B103-sustainability-16-08945" class="html-bibr">103</a>,<a href="#B104-sustainability-16-08945" class="html-bibr">104</a>,<a href="#B105-sustainability-16-08945" class="html-bibr">105</a>,<a href="#B106-sustainability-16-08945" class="html-bibr">106</a>,<a href="#B107-sustainability-16-08945" class="html-bibr">107</a>,<a href="#B108-sustainability-16-08945" class="html-bibr">108</a>,<a href="#B109-sustainability-16-08945" class="html-bibr">109</a>,<a href="#B110-sustainability-16-08945" class="html-bibr">110</a>,<a href="#B111-sustainability-16-08945" class="html-bibr">111</a>,<a href="#B112-sustainability-16-08945" class="html-bibr">112</a>,<a href="#B113-sustainability-16-08945" class="html-bibr">113</a>,<a href="#B114-sustainability-16-08945" class="html-bibr">114</a>].</p>
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21 pages, 7736 KiB  
Article
Carbonyl Compounds Observed at a Suburban Site during an Unusual Wintertime Ozone Pollution Event in Guangzhou
by Aoqi Ge, Zhenfeng Wu, Shaoxuan Xiao, Xiaoqing Huang, Wei Song, Zhou Zhang, Yanli Zhang and Xinming Wang
Atmosphere 2024, 15(10), 1235; https://doi.org/10.3390/atmos15101235 (registering DOI) - 16 Oct 2024
Abstract
Carbonyl compounds are important oxygenated volatile organic compounds (VOCs) that play significant roles in the formation of ozone (O3) and atmospheric chemistry. This study presents comprehensive field observations of carbonyl compounds during an unusual wintertime ozone pollution event at a suburban [...] Read more.
Carbonyl compounds are important oxygenated volatile organic compounds (VOCs) that play significant roles in the formation of ozone (O3) and atmospheric chemistry. This study presents comprehensive field observations of carbonyl compounds during an unusual wintertime ozone pollution event at a suburban site in Guangzhou, South China, from 19 to 28 December 2020. The aim was to investigate the characteristics and sources of carbonyls, as well as their contributions to O3 formation. Formaldehyde, acetone, and acetaldehyde were the most abundant carbonyls detected, with average concentrations of 7.11 ± 1.80, 5.21 ± 1.13, and 3.00 ± 0.94 ppbv, respectively, on pollution days, significantly higher than those of 2.57 ± 1.12, 2.73 ± 0.88, and 1.10 ± 0.48 ppbv, respectively, on nonpollution days. The Frame for 0-D Atmospheric Modeling (F0AM) box model simulations revealed that local production accounted for 62–88% of observed O3 concentrations during the pollution days. The calculated ozone formation potentials (OFPs) for various precursors (carbonyls and VOCs) indicated that carbonyl compounds contributed 32.87% of the total OFPs on nonpollution days and 36.71% on pollution days, respectively. Formaldehyde, acetaldehyde, and methylglyoxal were identified as the most reactive carbonyls, and formaldehyde ranked top in OFPs, and it alone contributed 15.92% of total OFPs on nonpollution days and 18.10% of total OFPs on pollution days, respectively. The calculation of relative incremental reactivity (RIR) indicates that ozone sensitivity was a VOC-limited regime, and carbonyls showed greater RIRs than other groups of VOCs. The model simulation showed that secondary formation has a significant impact on formaldehyde production, which is primarily controlled by alkenes and biogenic VOCs. The characteristic ratios and backward trajectory analysis also indicated the indispensable impacts of local primary sources (like industrial emissions and vehicle emissions) and regional sources (like biomass burning) through transportation. This study highlights the important roles of carbonyls, particularly formaldehyde, in forming ozone pollution in megacities like the Pearl River Delta region. Full article
(This article belongs to the Section Air Quality)
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<p>Location of the observation site (green star).</p>
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<p>Time series of meteorological parameters and major pollutants during the sampling period, with shaded areas indicating the pollution days.</p>
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<p>Diurnal variations of major carbonyls during pollution days and nonpollution days.</p>
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<p>The contributions of different VOC groups to ozone formation potential (OFP) during the nonpollution and pollution days.</p>
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<p>Carbonyls and NMHC compounds with the top 10 OFP values during nonpollution and pollution days.</p>
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<p>Model simulation of O<sub>3</sub> formation.</p>
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<p>Calculated RIRs for ozone formation from precursors (carbonyls, NMHCs, and NOx).</p>
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<p>Observed and simulated concentrations of formaldehyde during the sampling period.</p>
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<p>Model-simulated production rate (P (HCHO)) and loss rate (L (HCHO)) of formaldehyde through different reaction pathways during nonpollution days (<b>a</b>) and pollution days (<b>b</b>).</p>
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<p>The calculated RIRs of the five major HC groups for the formation of formaldehyde.</p>
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<p>Model-calculated RIRs of the individual top 10 NMHC species for the formation of formaldehyde during pollution days.</p>
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<p>Correlation analysis of formaldehyde to acetaldehyde (<b>a</b>), acetaldehyde to propanal (<b>b</b>), toluene to benzene (<b>c</b>), and m,p-xylene to ethylbenzene (<b>d</b>) during nonpollution days and pollution days.</p>
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<p>Mean 48 h back trajectories of clusters at the Huadu site (black star) during nonpollution days (<b>a</b>) and pollution days (<b>b</b>).</p>
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<p>Backward trajectory and fire hotspot map within 48 h during the sampling period from 19 to 28 December 2020 (24 trajectories per day) at the Huadu site (black star).</p>
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8 pages, 1493 KiB  
Article
Investigating the Potential of River Sediment Bacteria for Trichloroethylene Bioremediation
by Ranjit Gurav, Chang Ji and Sangchul Hwang
Water 2024, 16(20), 2941; https://doi.org/10.3390/w16202941 (registering DOI) - 16 Oct 2024
Viewed by 129
Abstract
Trichloroethylene (TCE) is a prevalent groundwater contaminant detected worldwide, and microbes are sensitive indicators and initial responders to these chemical contaminants causing disturbances to their ecosystem. In this study, microbes isolated from San Marcos River sediment were screened for their TCE degradation potential. [...] Read more.
Trichloroethylene (TCE) is a prevalent groundwater contaminant detected worldwide, and microbes are sensitive indicators and initial responders to these chemical contaminants causing disturbances to their ecosystem. In this study, microbes isolated from San Marcos River sediment were screened for their TCE degradation potential. Among the twelve isolates (SAN1-12), five isolates demonstrated TCE degradation within 5 days at 25 °C and 40 mg/L of TCE concentration in the following order: SAN8 (87.56%), SAN1 (77.31%), SAN2 (76.58%), SAN3 (49.20%), and SAN7 (3.36%). On increasing the TCE concentration to 80 mg/L, the degradation efficiency of these isolates declined, although SAN8 remained the prominent TCE degrader with 75.67% degradation. The prominent TCE-degrading isolates were identified as Aeromonas sp. SAN1, Bacillus sp. SAN2, Gordonia sp. SAN3, and Bacillus proteolyticus SAN8 using 16S rRNA sequencing. The TCE degradation and cell biomass of Bacillus proteolyticus SAN8 were significantly improved when the incubation temperature was increased from 25 °C to 30 °C. However, both slightly acidic and alkaline pH levels, as well as higher TCE concentrations, lowered the efficacy of TCE degradation. Nevertheless, these conditions led to an increase in bacterial cell biomass. Full article
(This article belongs to the Special Issue Biological Treatment of Water Contaminants: A New Insight)
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<p>(<b>a</b>) Screening of the river sediment bacteria for TCE degradation at a TCE concentration of 80 mg/L at 25 °C for 5 days. (<b>b</b>) Phylogenetic position of <span class="html-italic">Bacillus proteolyticus</span> SAN8.</p>
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<p>Time-dependent TCE degradation by <span class="html-italic">Bacillus proteolyticus</span> SAN8 at the TCE concentration of 80 mg/L and temperature of 25 °C.</p>
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<p>Effect of pH (6–8) on TCE degradation and DCE of <span class="html-italic">Bacillus proteolyticus</span> SAN8 at TCE concentration of 80 mg/L, temperature of 25 °C, and incubation time of 5 days.</p>
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<p>Effect of TCE concentration (40–120 mg/L) and temperature on <span class="html-italic">Bacillus proteolyticus</span> SAN8 TCE degradation and dry cell weight (DCW), at temperatures of (<b>a</b>) 25 °C and (<b>b</b>) 30 °C.</p>
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15 pages, 1528 KiB  
Article
Biochar and Deactivated Yeast as Seed Coatings for Restoration: Performance on Alternative Substrates
by Jennifer Cann, Esther Tang and Sean C. Thomas
Seeds 2024, 3(4), 544-558; https://doi.org/10.3390/seeds3040037 (registering DOI) - 16 Oct 2024
Viewed by 126
Abstract
Seedling establishment is often a critical bottleneck in the revegetation of mine tailings and similar substrates. Biochar and deactivated yeast are potential sustainable materials that could be used in this context as seed coatings to aid in seedling establishment. We conducted a greenhouse [...] Read more.
Seedling establishment is often a critical bottleneck in the revegetation of mine tailings and similar substrates. Biochar and deactivated yeast are potential sustainable materials that could be used in this context as seed coatings to aid in seedling establishment. We conducted a greenhouse study on biochar and deactivated yeast use as seed coatings, assessing germination, establishment, and early growth of white clover (Trifolium repens) and purple prairie clover (Dalea purpurea). Coated seeds were applied to a mine tailing, a coarse granitic sand, and potting soil mix substrates; seedling establishment and growth were monitored over 75 days. Biochar coatings enhanced the seedling establishment of Trifolium, with biochar and biochar plus yeast coatings giving the best results. In some cases, these effects persisted throughout the experiment: biochar coatings resulted in a ~fivefold increase in Trifolium biomass at harvest for plants in the potting soil mix but had neutral effects on sand or tailings. Biochar seed coatings also enhanced Dalea germination in some cases, but the benefits did not persist. Our results indicate that biochar-based seed coatings can have lasting effects on plant growth well beyond germination but also emphasize highly species-specific responses that highlight the need for further study. Full article
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<p>The province of Ontario is shown in relation to North America (<b>A</b>). Sites where materials were sourced (Delnite mine and Haliburton Forest) are shown with the greenhouse location relative to Ontario’s provincial borders (<b>B</b>).</p>
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<p>Seedling establishment by species, substrate, and treatment at 7, 14, and 75 days after seeds were sown for (<b>A</b>–<b>C</b>) <span class="html-italic">Trifolium</span> and (<b>D</b>–<b>F</b>) <span class="html-italic">Dalea</span>. Significant effects of substrate (S), (B), yeast (Y), and interactions are indicated: * <span class="html-italic">p</span> &lt; 0.05; full GLM results are in <a href="#seeds-03-00037-t001" class="html-table">Table 1</a>. Lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.1) by post-hoc Dunn tests within each substrate. Means are plotted ±1 SE.</p>
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<p>Final biomass at harvest for (<b>A</b>,<b>B</b>) aboveground, (<b>C</b>,<b>D</b>) belowground, and (<b>E</b>,<b>F</b>) root biomass for <span class="html-italic">Trifolium</span> (<b>A</b>–<b>C</b>) and <span class="html-italic">Dalea</span> (<b>D</b>–<b>F</b>) grown for 75 days. Significant effects of substrate (S), (B), yeast (Y), and interactions are indicated: * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. Full ANOVA results are in <a href="#seeds-03-00037-t002" class="html-table">Table 2</a>. Lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) by post-hoc HSD tests within each substrate. Means are plotted ±1 SE.</p>
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<p>Leaf area (<b>A</b>,<b>D</b>), leaf area ratio (<b>B</b>,<b>E</b>), and root mass fraction (<b>C</b>,<b>F</b>) at harvest for <span class="html-italic">Trifolium</span> (<b>A</b>–<b>C</b>) and <span class="html-italic">Dalea</span> (<b>D</b>–<b>F</b>) grown for 75 days. Significant effects of substrate (S), (B), yeast (Y), and interactions are indicated: * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001. Full ANOVA results are in <a href="#seeds-03-00037-t002" class="html-table">Table 2</a>. Lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) by post-hoc HSD tests within each substrate. Means are plotted ±1 SE.</p>
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17 pages, 2149 KiB  
Article
Exploring the Adsorption Behavior of Organic UV Filter on Carbon-Based Materials as Potential Carriers of Organic Contaminants in the Aquatic Environment
by Jelena Beljin, Marijana Kragulj Isakovski, Tajana Simetić, Nina Đukanović, Jelena Molnar Jazić, Snežana Maletić and Maja Vujić
Appl. Sci. 2024, 14(20), 9424; https://doi.org/10.3390/app14209424 (registering DOI) - 16 Oct 2024
Viewed by 205
Abstract
Environmental pollution poses significant risks to human health and ecosystems, necessitating costly and time-consuming remediation efforts. Consequently, there’s a growing interest among researchers in developing and utilizing next-generation materials. Carbon-based materials have emerged as promising candidates due to their environmentally friendly nature, although [...] Read more.
Environmental pollution poses significant risks to human health and ecosystems, necessitating costly and time-consuming remediation efforts. Consequently, there’s a growing interest among researchers in developing and utilizing next-generation materials. Carbon-based materials have emerged as promising candidates due to their environmentally friendly nature, although their application presents both positive and negative aspects, as evidenced by existing literature. A diverse range of low-cost carbonaceous sorbents, like biochars, have been investigated for their suitability in water treatment. Given the substantial volume of agricultural waste biomass generated globally, the cost-effective production of these materials from residual biomass holds promise for addressing additional environmental challenges, such as biomass waste management. Various biochars derived from corn, hemp, and straw were studied to evaluate the adsorption potential for removing a commonly used organic UV filter 3-(4′-methylbenzylidene)-camphor (4-MBC). The adsorption isotherms obtained were well-described by the Freundlich model, with nonlinearity values below 0.9. Generally, all investigated adsorbents exhibited a higher affinity for 4-MBC, underscoring the importance of such research in identifying safe adsorbents for water remediation purposes. Moreover, this paper also tackles the interactions between 4-MBC and microplastics as polymer carbon-based materials, indicating the highest adsorption capacity of polyethylene terephthalate. Full article
(This article belongs to the Section Environmental Sciences)
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<p>SEM micrographs of biochar from (<b>A</b>) corn, (<b>B</b>) hemp, and (<b>C</b>) straw.</p>
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<p>Kinetics of 4-MBC adsorption on biochar from corn (BC1), hemp (BC2), and straw (BC3) (Ce denotes the equilibrium concentration, Co denotes the initial concentration).</p>
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<p>Adsorption kinetics of 4-MBC on PEg, PET, PP, and PLA.</p>
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<p>Plots illustrating the adsorption kinetics of 4-MBC on PEg, PET, PP, and PLA particles in synthetic water matrix using different models: (<b>a</b>) pseudo-first-order model, (<b>b</b>) pseudo-second-order model, (<b>c</b>) Elovich, and (<b>d</b>) Weber–Morris model.</p>
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<p>Adsorption isotherms of 4-MBC on biochar from (<b>a</b>) corn, (<b>b</b>) hemp, and (<b>c</b>) straw.</p>
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<p>Adsorption isotherms of 4-MBC on (<b>a</b>) PEg, (<b>b</b>) PET, (<b>c</b>) PP, and (<b>d</b>) PLA particles obtained for the synthetic matrix.</p>
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11 pages, 3052 KiB  
Article
Influence of Artemisia dubia Wall and Pig Manual Digestate on Winter Wheat Productivity and Grain Quality
by Ausra Baksinskaite, Modupe Olufemi Doyeni and Vita Tilvikiene
Agriculture 2024, 14(10), 1819; https://doi.org/10.3390/agriculture14101819 (registering DOI) - 15 Oct 2024
Viewed by 222
Abstract
Sustainable agriculture aims to use biological resources to improve crop quality and productivity. This approach promotes alternatives, such as replacing synthetic pesticides with biological ones and substituting mineral fertilizers with organic fertilizers. Field trials were conducted using two different factors: fertilizer treatments (ammonium [...] Read more.
Sustainable agriculture aims to use biological resources to improve crop quality and productivity. This approach promotes alternatives, such as replacing synthetic pesticides with biological ones and substituting mineral fertilizers with organic fertilizers. Field trials were conducted using two different factors: fertilizer treatments (ammonium nitrate and pig manure digestate) and plant protection treatments (pesticides, Artemisia dubia Wall biomass mulch, and strips). After harvesting the winter wheat, the productivity and quality (weight of 1000 grains, protein, gluten, starch, sedimentation of grains) were evaluated. The two-year studies showed that pig manure digestate positively affected winter wheat grain quality. Mugwort biomass outperformed other plant protection options in three key grain quality indicators (protein, gluten, and sedimentation). Furthermore, in 2023, the highest grain yield of 5798 ± 125 kg ha−1 was observed in the pesticides and pig manure digestate treatment. The quick impact and mode of action of vegetation pesticides were more easily felt over the two years of study, leading to the highest yield of wheat grains compared to other plant management measures. This study shows that mugwort biomass can positively influence wheat grain quality, a significant milestone in utilizing nonfood crops as alternatives for agricultural productivity. Full article
(This article belongs to the Section Crop Production)
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<p>The air temperature (2021–2023).</p>
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<p>Precipitation (2021–2023).</p>
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<p>The 2022–2023 winter wheat yield. The same letter indicates no significant difference at <span class="html-italic">p</span> ≤ 0.05 by <span class="html-italic">t</span>-test. Note: *** <span class="html-italic">p</span> &lt; 0.001, * <span class="html-italic">p</span> &lt; 0.05, ns—not significant.</p>
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<p>2022–2023 years of 1000-seed weight of wheat. The same letter indicates no significant difference at <span class="html-italic">p</span> ≤ 0.05 by <span class="html-italic">t</span>-test. Note: *** <span class="html-italic">p</span> &lt; 0.001, ns—not significant.</p>
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<p>Protein and sedimentation of grain. Note: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Gluten and starch of winter wheat grain. Note: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 1.</p>
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18 pages, 1505 KiB  
Article
CFD Simulation of Mixing Forest Biomass to Obtain Cellulose
by Adolfo Angel Casarez-Duran, Juan Carlos Paredes-Rojas, Christopher René Torres-San Miguel, Sergio Rodrigo Méndez-García, Fernando Eli Ortiz-Hernández and Guillermo Manuel Urriolagoitia Calderón
Processes 2024, 12(10), 2250; https://doi.org/10.3390/pr12102250 (registering DOI) - 15 Oct 2024
Viewed by 191
Abstract
Obtaining cellulose from forest residues develops sustainable processes in the biotechnology industry, especially in producing biopolymers, which could replace or add petroleum-derived polymers. This research seeks to optimize the ideal conditions of the mixing process to maximize the efficiency in obtaining cellulose through [...] Read more.
Obtaining cellulose from forest residues develops sustainable processes in the biotechnology industry, especially in producing biopolymers, which could replace or add petroleum-derived polymers. This research seeks to optimize the ideal conditions of the mixing process to maximize the efficiency in obtaining cellulose through a process consisting of two treatment media for pine sawdust, specifically evaluating the impact of three types of impellers (propeller, flat blades, and 45° inclined flat blades) at speeds of (150, 250 and 350 rpm). DIN 28131 was used for the design of stirred tanks. Simulations were carried out with a volume of 50 L. CFD and FSI simulations of the agitation behavior of forest biomass in a stirred tank reactor were performed. The ALE method was applied, and the models were solved using the LS-DYNA computer program. The results indicate that agitation with propellers and flat blades inclined at 150 and 250 rpm was the most efficient, minimizing cell damage and optimizing energy consumption. The impeller with flat blades inclined at 45° proved to be the best option for cellulose extraction. The novelty of this research is that not only the flow fields and the agitation behavior were found, but also the stresses in the impellers were found, and the force, moment, and power required by the motor in each simulation were revealed at a different speed. The power curves shown help to understand how energy consumption varies under different conditions. Full article
17 pages, 1263 KiB  
Article
Differences in Grain Yield and Nitrogen Uptake between Tetraploid and Diploid Rice: The Physiological Mechanisms under Field Conditions
by Jian Xiao, Zhuang Xiong, Jiada Huang, Zuolin Zhang, Detian Cai, Dongliang Xiong, Kehui Cui, Shaobing Peng and Jianliang Huang
Plants 2024, 13(20), 2884; https://doi.org/10.3390/plants13202884 (registering DOI) - 15 Oct 2024
Viewed by 268
Abstract
Research indicates that, owing to the enhanced grain-filling rate of tetraploid rice, its yield has notably improved compared to previous levels. Studies conducted on diploid rice have revealed that optimal planting density and fertilization rates play crucial roles in regulating rice yield. In [...] Read more.
Research indicates that, owing to the enhanced grain-filling rate of tetraploid rice, its yield has notably improved compared to previous levels. Studies conducted on diploid rice have revealed that optimal planting density and fertilization rates play crucial roles in regulating rice yield. In this study, we investigated the effects of different nitrogen application and planting density treatments on the growth, development, yield, and nitrogen utilization in tetraploid (represented by T7, an indica–japonica conventional allotetraploid rice) and diploid rice (Fengliangyou-4, represented by FLY4, a two-line super hybrid rice used as a reference variety for the approval of super rice with a good grain yield performance). The results indicated that the highest grain-filling rate of T7 could reach 77.8% under field experimental conditions due to advancements in tetraploid rice breeding. This is a significant improvement compared with the rate seen in previous research. Under the same conditions, T7 exhibited a significantly lower grain yield than FLY4, which could be attributed to its lower grain-filling rate, spikelets per panicle, panicle number m−2, and harvest index score. Nitrogen application and planting density displayed little effect on the grain yield of both genotypes. A higher planting density significantly enhanced the leaf area index and biomass accumulation, but decreased the harvest index score. Compared with T7, FLY4 exhibited a significantly higher nitrogen use efficiency (NUEg), which was mainly due to the higher nitrogen content in the straw. Increasing nitrogen application significantly decreased NUEg due to its minimal effect on grain yield combined with its significant enhancement of nitrogen uptake. Our results suggest that the yield and grain-filling rate of T7 have been improved compared with those of previously tested polyploid rice, but are still lower than those of FLY4, and the yield of tetraploid rice can be further improved by enhancing the grain-filling rate, panicle number m−2, and spikelets per panicle via genotype improvement. Full article
(This article belongs to the Special Issue Emerging Trends in Alternative and Sustainable Crop Production)
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<p>Effects of different planting density and nitrogen application treatments on grain yield in tetraploid T7 and diploid FLY4 rice in 2018 (<b>a</b>) and 2019 (<b>b</b>). The error bar indicates SE (<span class="html-italic">n</span> = 3). Within a group of the same genotypes, different letters indicate significant differences according to LSD (0.05). T7: tetraploid rice; FLY4: Fengliangyou-4. TD17: lower-density treatment (20.0 cm × 30.0 cm), 16.7 hills per m<sup>−2</sup>; TD25: high-density treatment (13.3 cm × 30.0 cm), 25 hills per m<sup>−2</sup>. N1: N rate 150 kg ha<sup>−1</sup>; N2: N rate 225 kg ha<sup>−1</sup>; N3: N rate 300 kg ha<sup>−1</sup>. N1TD25, N1TD17, N2TD25, N2TD17, N3TD25, and N3TD17 represent different combinations of N application rates and density treatments.</p>
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<p>Changes in tillering dynamics in tetraploid T7 (<b>a</b>,<b>c</b>) and diploid FLY4 (<b>b</b>,<b>d</b>) under different densities and nitrogen application treatments in 2018 (<b>a</b>,<b>b</b>) and 2019 (<b>c</b>,<b>d</b>). The error bar indicates SE (<span class="html-italic">n</span> = 3). The red arrow indicates the time point of the panicle initiation stage. TD17: lower-density treatment (20.0 cm × 30.0 cm), 16.7 hills per m<sup>−2</sup>; TD25: high-density treatment (13.3 cm × 30.0 cm), 25 hills per m<sup>−2</sup>. N1: N rate 150 kg ha<sup>−1</sup>; N2: N rate 225 kg ha<sup>−1</sup>; N3: N rate 300 kg ha<sup>−1</sup>. N1TD25, N1TD17, N2TD25, N2TD17, N3TD25 and N3TD17 represent different combinations of N application rates and density treatments.</p>
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<p>Effects of different planting density and nitrogen application treatments on leaf area index in tetraploid T7 (<b>a</b>,<b>c</b>) and diploid FLY4 (<b>b</b>,<b>d</b>) in 2018 (<b>a</b>,<b>b</b>) and 2019 (<b>c</b>,<b>d</b>). Error bar indicates SE (<span class="html-italic">n</span> = 3). Within a group of the same genotypes, different letters indicate significant differences according to LSD (0.05). TD17: lower-density treatment (20.0 cm × 30.0 cm), 16.7 hills per m<sup>−2</sup>; TD25: high-density treatment (13.3 cm × 30.0 cm), 25 hills per m<sup>−2</sup>. N1: N rate 150 kg ha<sup>−1</sup>; N2: N rate 225 kg ha<sup>−1</sup>; N3: N rate 300 kg ha<sup>−1</sup>. N1TD25, N1TD17, N2TD25, N2TD17, N3TD25 and N3TD17 represent different combinations of N application rates and density treatments. PI: panicle initiation stage approximately 32 days after transplanting; HD: heading stage approximately 63 days after transplanting.</p>
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<p>Effects of different planting density and nitrogen application treatments on biomass in tetraploid T7 (<b>a</b>,<b>c</b>) and diploid FLY4 (<b>b</b>,<b>d</b>) in 2018 (<b>a</b>,<b>b</b>) and 2019 (<b>c</b>,<b>d</b>). The error bar indicates SE (<span class="html-italic">n</span> = 3). Within a group of the same genotypes, different letters indicate significant differences according to LSD (0.05). TD17: lower-density treatments (20.0 cm × 30.0 cm), 16.7 hills per m<sup>−2</sup>; TD25: high-density treatments (13.3 cm × 30.0 cm), 25 hills per m<sup>−2</sup>. N1: N rate 150 kg ha<sup>−1</sup>; N2: N rate 225 kg ha<sup>−1</sup>; N3: N rate 300 kg ha<sup>−1</sup>. N1TD25, N1TD17, N2TD25, N2TD17, N3TD25 and N3TD17 represent different combinations of N application rates and density treatments. PI: panicle initiation stage approximately 32 days after transplanting; HD: heading stage approximately 63 days after transplanting; MA: approximately 104 days after transplanting.</p>
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<p>Effects of different treatments on the SPAD value of the flag leaf in tetraploid T7 (<b>a</b>,<b>c</b>) and diploid FLY4 (<b>b</b>,<b>d</b>) at HD and 21 days after HD stage in 2018 (<b>a</b>,<b>b</b>) and 2019 (<b>c</b>,<b>d</b>). The error bar indicates SE (<span class="html-italic">n</span> = 3). In a set of bar charts of the same color, different letters indicate significant differences according to LSD (0.05). Lower-case letters indicate comparisons among different treatments within each group. The content in the legend represents measurement time at HD (approximately 63 days after transplanting) and 21 days after the HD stage. TD17: lower-density treatment (20.0 cm × 30.0 cm), 16.7 hills per m<sup>−2</sup>; TD25: high-density treatment (13.3 cm × 30.0 cm), 25 hills per m<sup>−2</sup>. N1: N rate 150 kg ha<sup>−1</sup>; N2: N rate 225 kg ha<sup>−1</sup>; N3: N rate 300 kg ha<sup>−1</sup>. N1TD25, N1TD17, N2TD25, N2TD17, N3TD25 and N3TD17 represent different combinations of N application rates and density treatments.</p>
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17 pages, 3688 KiB  
Article
Investigating the Inhibitory Effect of Sargassum natans and Sargassum fluitans Extracts on Iron Corrosion in 1.00 mol L−1 HCl Solution
by Stacy Melyon, Pau Reig Rodrigo, Manon Sénard, Laura Brelle, Muriel Sylvestre, Sarra Gaspard, Drochss Pettry Valencia and Gerardo Cebrian-Torrejon
Coatings 2024, 14(10), 1316; https://doi.org/10.3390/coatings14101316 (registering DOI) - 15 Oct 2024
Viewed by 455
Abstract
This study deals with the efficacy of extracts of Sargassum natans and Sargassum fluitans, an invasive brown algae present in Guadeloupe, as novel and environmentally friendly corrosion inhibitors for iron in 1 mol L−1 hydrochloric acid solutions. Six different Sargassum extracts (SE) were [...] Read more.
This study deals with the efficacy of extracts of Sargassum natans and Sargassum fluitans, an invasive brown algae present in Guadeloupe, as novel and environmentally friendly corrosion inhibitors for iron in 1 mol L−1 hydrochloric acid solutions. Six different Sargassum extracts (SE) were obtained using Soxhlet extraction with ethyl acetate, acetone, and ethanol, respectively, as solvents; cold successive maceration with chloroform and methanol, respectively; and microwave-assisted extraction with water. Subsequent electrochemical analysis showed that extracts from ethanol and ethyl acetate exhibited remarkable inhibition efficiencies of, respectively, 72.6% and 70.2%, but the better one was the extract of the cold maceration from chloroform with an inhibition efficiency of 92.0%. These findings allow us to focus on the chloroform extract (SEd) in order to see the change happening during the corrosion process via SEM and EDX analyses. Also, NMR analysis was conducted to identify the main chemicals responsible for the anticorrosion effect. The successful demonstration of the corrosion inhibitor effectiveness of extracts of Sargassum natans and fluitans suggests a potentially valuable use for this invasive biomass. These encouraging results warrant further investigation to identify and elucidate the active inhibitors in these extracts to deepen our understanding of their mechanisms for corrosion prevention and potentially expand their utility as an environmentally conscious approach to corrosion control. Full article
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<p>E<sub>OCP</sub> vs. time at 25 °C for iron electrode disc (ϕ 2 cm) in 1 M HCl without and with 500 ppm of different SE (<b>a</b>), and for the iron electrode in 1M HCL with and without the SEd deposit in the surface (<b>b</b>).</p>
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<p>Polarization curves of iron in 1 M HCl containing various SE in solution (500 ppm) at 25 °C (<b>a</b>) and with the SEd deposit (<b>b</b>).</p>
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<p>SEM analysis images in low vacuum: (<b>a</b>,<b>b</b>) polished iron electrode; (<b>c</b>,<b>d</b>) iron electrode after 3 h in HCl solution; (<b>e</b>,<b>f</b>) iron electrode with the SEd deposit; (<b>g</b>,<b>h</b>) iron electrode with the SEd deposition after 3 h in HCl solution.</p>
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<p>EDX spectrum of the iron electrode (<b>a</b>); iron electrode after 3 h in HCl solution; (<b>b</b>) iron electrode with the SEd deposit (<b>c</b>); iron electrode with the SEd deposit after 3 h in HCl solution (<b>d</b>).</p>
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16 pages, 8467 KiB  
Article
Quality Enhancement of Torrefied Biopellets Prepared by Unused Forest Biomass and Wood Chip Residues in Pulp Mills
by Tae-Gyeong Lee, Chul-Hwan Kim, Hyeong-Hun Park, Ju-Hyun Park, Min-Sik Park and Jae-Sang Lee
Appl. Sci. 2024, 14(20), 9398; https://doi.org/10.3390/app14209398 (registering DOI) - 15 Oct 2024
Viewed by 348
Abstract
The effects of torrefaction of the biopellets made from hardwood chip residue (HW), camellia oilseed cake (CO), and pruning remnants of the toothache tree (TA) and mulberry tree (MT) were evaluated. Torrefaction of the biopellets reduced the volatile matter content of biopellets by [...] Read more.
The effects of torrefaction of the biopellets made from hardwood chip residue (HW), camellia oilseed cake (CO), and pruning remnants of the toothache tree (TA) and mulberry tree (MT) were evaluated. Torrefaction of the biopellets reduced the volatile matter content of biopellets by 18–58% and increased their heating value by 18–58% without negatively impacting durability or fines content. Torrefaction also reduced the initial ignition time of biopellets by 50–59% and prolonged their combustion duration by 15–24%. Regardless of the type of feedstock, all biopellets exhibited mass yields in the range of 60–80% and energy yields ranging from 80–95%. The novelty of this study lies in the application of torrefaction to already-formed biopellets, which enhances pellet quality without the need for binders, and the use of unused forest biomass and wood chip residue from pulp mills. The use of unused forest biomass and wood chip residue from pulp mills for biopellet production not only provides a sustainable and efficient method for waste utilization but also contributes to environmental conservation by reducing the reliance on fossil fuels. Overall, the torrefaction of biopellets represents a promising technology for producing high-quality solid biofuel from a variety of woody biomass feedstocks without compromising pelletizing efficiency. Full article
(This article belongs to the Section Applied Industrial Technologies)
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<p>Ground woody biomass used to manufacture biopellets.</p>
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<p>Pelletizer with a flat die.</p>
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<p>Images of pellets before and after torrefaction using various raw materials.</p>
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<p>Experimental image of analyzing time for the initial ignition and combustion duration of biopellets: (<b>a</b>) pellet ignition by a potable gas torch; (<b>b</b>) ignited pellet with a flame.</p>
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<p>Proximate analysis of the prepared pellets before and after torrefaction.</p>
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<p>Ultimate analysis of the prepared pellets before and after torrefaction.</p>
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<p>Durability of the prepared pellets before and after torrefaction: (<b>a</b>) durability; (<b>b</b>) fines content.</p>
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<p>Bulk density of the prepared pallets before and after torrefaction.</p>
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<p>Calorific value of the prepared biopellets before and after torrefaction.</p>
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<p>Mass and energy yield of the prepared biopellets by torrefaction.</p>
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<p>Ignition and combustion time of the biopellets before and after torrefaction: (<b>a</b>) ignition time; (<b>b</b>) combustion duration.</p>
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<p>Thermogravimetric analysis of the biopellets before and after torrefaction: (<b>a</b>) HW; (<b>b</b>) CO; (<b>c</b>) TA; (<b>d</b>) MT.</p>
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<p>SEM images of biopellets before and after torrefaction.</p>
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<p>Importance and applications of torrefied biopellets.</p>
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36 pages, 8178 KiB  
Article
Co-Inoculation of Soybean Seeds with Azospirillum and/or Rhizophagus Mitigates the Deleterious Effects of Waterlogging in Plants under Enhanced CO2 Concentrations
by Eduardo Pereira Shimoia, Douglas Antônio Posso, Cristiane Jovelina da-Silva, Adriano Udich Bester, Nathalia Dalla Corte Bernardi, Ivan Ricardo Carvalho, Ana Cláudia Barneche de Oliveira, Luis Antonio de Avila and Luciano do Amarante
Nitrogen 2024, 5(4), 941-976; https://doi.org/10.3390/nitrogen5040061 (registering DOI) - 15 Oct 2024
Viewed by 353
Abstract
Rising CO2 levels, as predicted by global climate models, are altering environmental factors such as the water cycle, leading to soil waterlogging and reduced oxygen availability for plant roots. These conditions result in decreased energy production, increased fermentative metabolism, impaired nutrient uptake, [...] Read more.
Rising CO2 levels, as predicted by global climate models, are altering environmental factors such as the water cycle, leading to soil waterlogging and reduced oxygen availability for plant roots. These conditions result in decreased energy production, increased fermentative metabolism, impaired nutrient uptake, reduced nitrogen fixation, and altered leaf gas exchanges, ultimately reducing crop productivity. Co-inoculation techniques involving multiple plant growth-promoting bacteria or arbuscular mycorrhizal fungi have shown promise in enhancing plant resilience to stress by improving nutrient uptake, biomass production, and nitrogen fixation. This study aimed to investigate carbon and nitrogen metabolism adaptations in soybean plants co-inoculated with Bradyrhizobium elkanii, Azospirillum brasilense, and Rhizophagus intraradices under waterlogged conditions in CO2-enriched environments. Plants were grown in pots in open-top chambers at ambient CO2 concentration (a[CO2]) and elevated CO2 concentration (e[CO2]). After reaching the V5 growth stage, the plants were subjected to waterlogging for seven days, followed by a four-day reoxygenation period. The results showed that plants’ co-inoculation under e[CO2] mitigated the adverse effects of waterlogging. Notably, plants inoculated solely with B. elkanii under e[CO2] displayed results similar to co-inoculated plants under a[CO2], suggesting that co-inoculation effectively mitigates the waterlogging stress, with plant physiological traits comparable to those observed under elevated CO2 conditions. Full article
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<p>Schematic representation of the treatments and experimental design. Soybean plants were cultivated under different CO<sub>2</sub> concentrations (ambient <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) and subsequent reoxygenation (four days). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple co-inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
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<p>Leaf gaseous exchange. Net CO<sub>2</sub> assimilation (<span class="html-italic">A</span>) (<b>A</b>), stomatal conductance (<span class="html-italic">g<sub>s</sub></span>) (<b>B</b>), transpiration (<span class="html-italic">E</span>) (<b>C</b>), and internal CO<sub>2</sub> concentration (<span class="html-italic">C<sub>i</sub></span>) (<b>D</b>) in soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± standard deviation (SD), <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
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<p>Pigment content. Chlorophyll <span class="html-italic">a</span> content (Chlo<span class="html-italic">_a</span>) (<b>A</b>), chlorophyll <span class="html-italic">b</span> (Chlo<span class="html-italic">_b</span>) (<b>B</b>), total chlorophyll (Chlo-total) (<b>C</b>), and carotenoids (Carot) (<b>D</b>) in soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 4
<p>Peroxide content and lipid peroxidation in leaves. Accumulation of hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) (<b>A</b>) and lipid peroxidation (MDA) (<b>B</b>) in leaves of soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 5
<p>Peroxide content and lipid peroxidation in roots. Accumulation of hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) (<b>A</b>) and lipid peroxidation (MDA) (<b>B</b>) in roots of soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 6
<p>Antioxidant enzyme activity in leaves. The activity of the enzymes superoxide dismutase (SOD) (<b>A</b>), catalase (CAT) (<b>B</b>), and ascorbate peroxidase (APX) (<b>C</b>) in leaves of soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 7
<p>Antioxidant enzyme activity in roots. The activity of the enzymes superoxide dismutase (SOD) (<b>A</b>), catalase (CAT) (<b>B</b>), and ascorbate peroxidase (APX) (<b>C</b>) in roots of soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 8
<p>Fermentative enzyme activity. Activity of the enzymes lactate dehydrogenase (LDH) (<b>A</b>), pyruvate decarboxylase (PDC) (<b>B</b>), alcohol dehydrogenase (ADH) (<b>C</b>), and alanine aminotransferase (Ala-At) (<b>D</b>) in roots of soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 9
<p>Shoot biometric parameters. Leaf area (LA) (<b>A</b>), shoot dry mass (SDM) (<b>B</b>), and stem diameter (SD) (<b>C</b>) in soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 10
<p>Root biometric parameters. Accumulation of total soluble sugars (TSS) (<b>A</b>) and root fresh mass (RFM) (<b>B</b>) in roots of soybean plants grown under different CO<sub>2</sub> concentrations (ambient concentration <span class="html-italic">a</span>[CO<sub>2</sub>] or elevated concentration <span class="html-italic">e</span>[CO<sub>2</sub>]) with different symbiotic associations and subjected to waterlogging (seven days) followed by reoxygenation (four days). Values represent the mean ± SD, <span class="html-italic">n</span> = 4. Asterisks indicate a difference between control or waterlogged/reoxygenated plants (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05), uppercase letters indicate differences between treatments under control conditions, lowercase letters indicate differences between treatments under waterlogging/reoxygenated conditions (Tukey, <span class="html-italic">p</span> &lt; 0.05), and Greek letters indicate differences between treatment in <span class="html-italic">a</span>[CO<sub>2</sub>] or <span class="html-italic">e</span>[CO<sub>2</sub>] (<span class="html-italic">t</span>-test; <span class="html-italic">p</span> &lt; 0.05). IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation with <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation with <span class="html-italic">Rhizophagus intraradices</span> + <span class="html-italic">Bradyrhizobium</span>; CAR—triple inoculation with <span class="html-italic">Bradyrhizobium</span> + <span class="html-italic">Azospirillum brasilense</span> + <span class="html-italic">Rhizophagus intraradices</span>.</p>
Full article ">Figure 11
<p>Principal component analysis (PCA) was performed using PC1 and PC2 derived from morphophysiological and biochemical characteristics in the shoots of soybean plants grown under different symbiotic associations and subjected to waterlogging for seven days, followed by four days of reoxygenation, under either elevated CO<sub>2</sub> (<span class="html-italic">e</span>[CO<sub>2</sub>]) or ambient CO<sub>2</sub> (<span class="html-italic">a</span>[CO<sub>2</sub>]) conditions. I—first sampling during waterlogging; II—second sampling during reoxygenation; 400—plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>]; 700—plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>]; Ctrl—plants maintained as hydric controls; Wtlg—plants subjected to waterlogging; Rox—plants undergoing reoxygenation; IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation of <span class="html-italic">Azospirillum brasilense</span> and <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation of <span class="html-italic">Rhizophagus intraradices</span> and <span class="html-italic">Bradyrhizobium</span>; CAR—triple co-inoculation of <span class="html-italic">Bradyrhizobium</span>, <span class="html-italic">Azospirillum brasilense</span>, and <span class="html-italic">Rhizophagus intraradices</span>. Ellipses of different colors delineate the 95% confidence intervals, with colors chosen according to the water treatment in each CO<sub>2</sub> environment. Different symbols represent the microbiological treatments.</p>
Full article ">Figure 12
<p>Principal component analysis (PCA) was performed using PC1 and PC2 derived from morphophysiological and biochemical characteristics in the roots of soybean plants grown under different symbiotic associations and subjected to waterlogging for seven days, followed by four days of reoxygenation, under either elevated CO<sub>2</sub> (<span class="html-italic">e</span>[CO<sub>2</sub>]) or ambient CO<sub>2</sub> (<span class="html-italic">a</span>[CO<sub>2</sub>]) conditions. I—first sampling during waterlogging; II—second sampling during reoxygenation; 400—plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>]; 700—plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>]; Ctrl—plants maintained as hydric controls; Wtlg—plants subjected to waterlogging; Rox—plants undergoing reoxygenation; IB—<span class="html-italic">Bradyrhizobium</span> inoculation; CA—co-inoculation of <span class="html-italic">Azospirillum brasilense</span> and <span class="html-italic">Bradyrhizobium</span>; CR—co-inoculation of <span class="html-italic">Rhizophagus intraradices</span> and <span class="html-italic">Bradyrhizobium</span>; CAR—triple co-inoculation of <span class="html-italic">Bradyrhizobium</span>, <span class="html-italic">Azospirillum brasilense</span>, and <span class="html-italic">Rhizophagus intraradices</span>. Ellipses of different colors delineate the 95% confidence intervals, with colors chosen according to the water treatment in each CO<sub>2</sub> environment. Different symbols represent the microbiological treatments.</p>
Full article ">Figure 13
<p>Hierarchical clustering analysis (HCA) of H<sub>2</sub>O<sub>2</sub>, MDA, Chlo<span class="html-italic">_a</span>, Chlo<span class="html-italic">_b</span>, SOD, CAT, and APX enzyme activities, gas exchange parameters (<span class="html-italic">g<sub>s</sub></span>, <span class="html-italic">E</span>, <span class="html-italic">A</span>, and <span class="html-italic">C<sub>i</sub></span>), and biometric measurements (LA, SD, SDW) in the shoots of waterlogged soybean plants grown under elevated CO<sub>2</sub> (<span class="html-italic">e</span>[CO<sub>2</sub>]) or ambient CO<sub>2</sub> (<span class="html-italic">a</span>[CO<sub>2</sub>]) conditions. Variations in red and blue colors indicate increases and decreases, respectively, for each variable. Light gray shades represent control plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>], while dark gray shades represent waterlogged plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>]. Red shades indicate control plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>], and blue shades represent waterlogged plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>].</p>
Full article ">Figure 14
<p>Hierarchical clustering analysis (HCA) of H<sub>2</sub>O<sub>2</sub>, MDA, Chlo<span class="html-italic">_a</span>, Chlo<span class="html-italic">_b</span>, SOD, CAT, and APX enzyme activities, gas exchange parameters (<span class="html-italic">g<sub>s</sub></span>, <span class="html-italic">E</span>, <span class="html-italic">A</span>, and <span class="html-italic">C<sub>i</sub></span>), and biometric measurements (LA, SD, SDW) in the shoots of reoxygenated soybean plants grown under elevated CO<sub>2</sub> (<span class="html-italic">e</span>[CO<sub>2</sub>]) or ambient CO<sub>2</sub> (<span class="html-italic">a</span>[CO<sub>2</sub>]) conditions. Variations in red and blue colors indicate increases and decreases, respectively, for each variable. Light gray shades represent control plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>], while dark gray shades represent waterlogged plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>]. Red shades indicate control plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>], and blue shades represent waterlogged plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>].</p>
Full article ">Figure 15
<p>Hierarchical clustering analysis (HCA) of H<sub>2</sub>O<sub>2</sub>, MDA, TSS, SOD, CAT, APX, ADH, LDH, PDC, and Ala-AT enzyme activities, as well as RFW in the roots of waterlogged soybean plants grown under elevated CO<sub>2</sub> (<span class="html-italic">e</span>[CO<sub>2</sub>]) or ambient CO<sub>2</sub> (<span class="html-italic">a</span>[CO<sub>2</sub>]) conditions. Variations plotted in red and blue colors on a log10 scale indicate increases and decreases, respectively, for each variable. Light gray shades represent control plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>], while dark gray shades denote waterlogged plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>]. Red shades indicate control plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>], and blue shades represent waterlogged plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>].</p>
Full article ">Figure 16
<p>Hierarchical clustering analysis (HCA) of H<sub>2</sub>O<sub>2</sub>, MDA, TSS, SOD, CAT, APX, ADH, LDH, PDC, and Ala-AT enzyme activities, as well as RFW in the roots of reoxygenated soybean plants grown under elevated CO<sub>2</sub> (<span class="html-italic">e</span>[CO<sub>2</sub>]) or ambient CO<sub>2</sub> (<span class="html-italic">a</span>[CO<sub>2</sub>]) conditions. Variations plotted in red and blue colors on a log10 scale indicate increases and decreases, respectively, for each variable. Light gray shades represent control plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>], while dark gray shades denote waterlogged plants grown under <span class="html-italic">a</span>[CO<sub>2</sub>]. Red shades indicate control plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>], and blue shades represent waterlogged plants grown under <span class="html-italic">e</span>[CO<sub>2</sub>].</p>
Full article ">
17 pages, 3824 KiB  
Review
Cakile maritima: A Halophyte Model to Study Salt Tolerance Mechanisms and Potential Useful Crop for Sustainable Saline Agriculture in the Context of Climate Change
by Ricardo Mir, Diana M. Mircea, Mario X. Ruiz-González, Paco Brocal-Rubio, Monica Boscaiu and Oscar Vicente
Plants 2024, 13(20), 2880; https://doi.org/10.3390/plants13202880 (registering DOI) - 15 Oct 2024
Viewed by 342
Abstract
Salinity is an increasing problem for agriculture. Most plant species tolerate low or, at best, moderate soil salinities. However, a small (<1%) proportion of species, termed halophytes, can survive and complete their life cycle in natural habitats with salinities equivalent to 200 mM [...] Read more.
Salinity is an increasing problem for agriculture. Most plant species tolerate low or, at best, moderate soil salinities. However, a small (<1%) proportion of species, termed halophytes, can survive and complete their life cycle in natural habitats with salinities equivalent to 200 mM NaCl or more. Cakile maritima is a succulent annual halophyte belonging to the Brassicaceae family; it is dispersed worldwide and mainly grows in foreshores. Cakile maritima growth is optimal under slight (i.e., 100 mM NaCl) saline conditions, measured by biomass and seed production. Higher salt concentrations, up to 500 mM NaCl, significantly impact its growth but do not compromise its survival. Cakile maritima alleviates sodium toxicity through different strategies, including anatomical and morphological adaptations, ion transport regulation, biosynthesis of osmolytes, and activation of antioxidative mechanisms. The species is potentially useful as a cash crop for the so-called biosaline agriculture due to its production of secondary metabolites of medical and nutritional interest and the high oil accumulation in its seeds. In this review, we highlight the relevance of this species as a model for studying the basic mechanisms of salt tolerance and for sustainable biosaline agriculture in the context of soil salination and climate change. Full article
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Figure 1

Figure 1
<p>General features of <span class="html-italic">Cakile maritima</span>. (<b>A</b>) Natural worldwide distribution of <span class="html-italic">Cakile maritima</span> (extracted from (eHALOPH; Ref. [<a href="#B25-plants-13-02880" class="html-bibr">25</a>]). Details of (<b>B</b>) leaf morphotypes, (<b>C</b>) flowers, (<b>D</b>) two-segmented dehiscent siliques, and (<b>E</b>) root (indicated with an asterisk) and horizontal stems. (<b>F</b>) Naturally growing <span class="html-italic">Cakile maritima</span> plants on the Mediterranean coast of Xilxes, Castellón (Spain). Scale bars in (<b>B</b>,<b>D</b>,<b>E</b>) represent lengths of 10 cm, 1 cm, and 100 cm, respectively.</p>
Full article ">Figure 2
<p>Plants of <span class="html-italic">Cakile maritima</span> watered with tap water (<b>left</b>) and 400 mM NaCl solution (<b>right</b>) for eight weeks.</p>
Full article ">Figure 3
<p>General aspects of leaves (<b>A</b>,<b>C</b>,<b>E</b>) and flowers (<b>B</b>,<b>D</b>,<b>F</b>) excised from adult <span class="html-italic">Cakile maritima</span> plants growing under natural conditions. (<b>A</b>,<b>B</b>) Leaves and flowers at day 0. (<b>C</b>,<b>D</b>) Leaves and flowers at day 10, stored at 4 °C under dry conditions. (<b>E</b>,<b>F</b>) Leaves and flowers at day 10, stored at 4 °C under humid conditions.</p>
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14 pages, 4146 KiB  
Article
Preparation and Characterization of Glucose-Based Self-Blowing Non-Isocyanate Polyurethane (NIPU) Foams with Different Acid Catalysts
by Tianjiao Yang, Antonio Pizzi, Xuedong Xi, Xiaojian Zhou and Qianyu Zhang
Polymers 2024, 16(20), 2899; https://doi.org/10.3390/polym16202899 (registering DOI) - 15 Oct 2024
Viewed by 212
Abstract
The preparation and application of non-isocyanate polyurethane (NIPU) from biomass raw materials as a substitute for traditional polyurethane (PU) has recently become a research hot topic as it avoids the toxicity and moisture sensitivity of isocyanate-based PU. In the work presented here, self-blowing [...] Read more.
The preparation and application of non-isocyanate polyurethane (NIPU) from biomass raw materials as a substitute for traditional polyurethane (PU) has recently become a research hot topic as it avoids the toxicity and moisture sensitivity of isocyanate-based PU. In the work presented here, self-blowing GNIPU non-isocyanate polyurethane (NIPU) rigid foams were prepared at room temperature, based on glucose, with acids as catalysts and glutaraldehyde as a cross-linker. The effects of different acids and glutaraldehyde addition on foam morphology and properties were investigated. The water absorption, compressive resistance, fire resistance, and limiting oxygen index (LOI) were tested to evaluate the relevant properties of the foams, and scanning electron microscopy (SEM) was used to observe the foams’ cell structure. The results show that all these foams have a similar apparent density, while their 24 h water absorption is different. The foam prepared with phosphoric acid as a catalyst presented a better compressive strength compared to the other types prepared with different catalysts when above 65% compression. It also presents the best fire resistance with an LOI value of 24.3% (great than 22%), indicating that it possesses a good level of flame retardancy. Thermogravimetric analysis also showed that phosphoric acid catalysis slightly improved the GNIPU foams’ thermal stability. This is mainly due to the flame-retardant effect of the phosphate ion. In addition, scanning electron microscopy (SEM) results showed that all the GNIPU foams exhibited similar open-cell morphologies with the cell pore sizes mainly distributed in the 200–250 μm range. Full article
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<p>Photograph of GNIPU foams.</p>
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<p>The main reactions leading to a cross-linked network in the foams.</p>
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<p>Water absorption (24 h) of GNIPU foams (F1, F2, F3, and F4).</p>
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<p>Water absorption (24 h) of GNIPU foams (F3, F5, and F6).</p>
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<p>Effects of different initiators on compression performance of GNIPU foams.</p>
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<p>Effect of different additions of glutaraldehyde on compression properties of GNIPU foams.</p>
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<p>Photographic record of ignition experiments.</p>
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<p>LOI of foams F1, F2, F3, F4, F5, and F6.</p>
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<p>TG (<b>a</b>) and DTG (<b>b</b>) curves of GNIPU foams (F1, F2, F3, and F4).</p>
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<p>FT-IR spectra of GNIPU and foams (F1, F2, F3, and F4).</p>
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<p>SEM pictures of GNIPU foams.</p>
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<p>Cell size distributions of GNIPU foams. Gaussian cell size distribution curve indicated in red.</p>
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13 pages, 3859 KiB  
Article
Effect of Pipe Materials and Interspecific Interactions on Biofilm Formation and Chlorine Resistance: Turn Enemies into Friends
by Lili Shan, Yunyan Pei, Siyang Xu, Yuhong Cui, Zhengqian Liu, Zebing Zhu and Yixing Yuan
Water 2024, 16(20), 2930; https://doi.org/10.3390/w16202930 (registering DOI) - 15 Oct 2024
Viewed by 239
Abstract
Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine [...] Read more.
Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine resistance of 10 dual-species biofilms in polyethylene (PE) and cast iron (CI) pipes were investigated in this paper. The biofilm biomass (heterotrophic bacterial plate count and crystal violet) of dual species in CI pipes is significantly higher than that in PE pipes, but the biofilm activity in CI pipes is significantly lower than that in PE pipes. The interspecific interaction of Sphingomonas-containing group presented synergistic or neutral relationship in PE pipes, whereas the interspecific interaction of the Acidovorax-containing group showed a competitive relationship in CI pipes. Although interspecific relationships may help bacteria resist chlorine, the chlorine resistance was more reliant on dual-species groups and pipe materials. In CI pipes, the Microbacterium containing biofilm groups showed better chlorine resistance, whereas in PE pipes, most biofilm groups with Bacillus exhibited better chlorine resistance. The biofilm groups with more extracellular polymeric substance (EPS) secretion showed stronger chlorine resistance. The biofilm in the PE pipe is mainly protected by EPS, while both EPS and corrosion products shield the biofilms within CI pipe. These results supported that dual-species biofilms are affected by pipe materials and interspecific interactions and provided some ideas for microbial control in two typical pipe materials. Full article
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<p>Dual-species biofilm formation ability and biofilm biomass in two pipe materials. (<b>a</b>) Crystal violet of PE pipe during the biofilm formation, (<b>b</b>) crystal violet of cast iron pipe during the biofilm formation, (<b>c</b>) HPC of the 5-day biofilm. a, b, and c in the figure represent the results of a cluster analysis. a<sub>1</sub>, b<sub>1</sub>, and c<sub>1</sub> are the results of the PE pipe, while a<sub>2</sub>, b<sub>2</sub>, and c<sub>2</sub> are the results of cast iron pipe. I: <span class="html-italic">Sphingomonas</span> sp. + <span class="html-italic">Acidovorax defluvii</span>, II: <span class="html-italic">Sphingomonas</span> sp. + <span class="html-italic">Bacillus cereus</span>, III: <span class="html-italic">Sphingomonas</span> sp. + <span class="html-italic">Acinetobacter</span> sp., IV: <span class="html-italic">Sphingomonas</span> sp. + <span class="html-italic">Microbacterium laevaniformans,</span> V: <span class="html-italic">Acidovorax defluvii</span> + <span class="html-italic">Bacillus cereus</span>, VI: <span class="html-italic">Acidovorax defluvii</span> + <span class="html-italic">Acinetobacter</span> sp., VII: <span class="html-italic">Acidovorax defluvii</span> + <span class="html-italic">Microbacterium laevaniformans</span>, VIII: <span class="html-italic">Bacillus cereus</span> + <span class="html-italic">Acinetobacter</span> sp., IX: <span class="html-italic">Bacillus cereus</span> + <span class="html-italic">Microbacterium laevaniformans</span>, X: <span class="html-italic">Acinetobacter</span> sp. + <span class="html-italic">Microbacterium laevaniformans.</span> The groups corresponding to I~X in the following figure are the same as those in <a href="#water-16-02930-f001" class="html-fig">Figure 1</a>.</p>
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<p>Dual-species biofilm bacteria activity in two pipes. (<b>a</b>) ATP concentration, (<b>b</b>) specific respiratory activity. a, b, and c in the figure represent the results of a cluster analysis. a<sub>1</sub>, b<sub>1</sub>, and c<sub>1</sub> are the results of the PE pipe, while a<sub>2</sub>, b<sub>2</sub>, c<sub>2</sub> are the results of the cast iron pipe.</p>
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<p>Dual-species biofilm biomass reduction in the two pipe materials after chlorination. (<b>a</b>) CV reduction rate, (<b>b</b>) HPC reduction rate. a, b, c, and d in the figure represented the results of a cluster analysis. a<sub>1</sub>, b<sub>1</sub>, c<sub>1</sub>, and d<sub>1</sub> are the results of the PE pipe, while a<sub>2</sub>, b<sub>2</sub>, c<sub>2</sub>, and d<sub>2</sub> are the results of the cast iron pipe.</p>
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<p>Dual-species biofilm bacteria activity reduction in two pipe materials after chlorination. (<b>a</b>) ATP concentration reduction, (<b>b</b>) specific respiratory activity reduction. a, b, and c in the figure represent the results of a cluster analysis. a<sub>1</sub>, b<sub>1</sub>, and c<sub>1</sub> are the results of the PE pipe, while a<sub>2</sub>, b<sub>2</sub>, and c<sub>2</sub> are the results of the cast iron pipe.</p>
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<p>Dual-species biofilm EPS contents before (<b>a</b>) and after (<b>b</b>) chlorination in two pipe materials. PS represents polysaccharides, and PN represents protein. a, b, c, and d in the figure represent the results of a cluster analysis. a<sub>1</sub>, b<sub>1</sub>, and c<sub>1</sub> are the result of the PE pipe, while a<sub>2</sub>, b<sub>2</sub>, c<sub>2</sub>, and d<sub>2</sub> are the results of the cast iron pipe.</p>
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<p>Biofilm morphology before and after chlorination in two pipe materials. (<b>a</b>) PE pipe before chlorination, (<b>b</b>) PE pipe after chlorination, (<b>c</b>) cast iron pipe before chlorination, (<b>d</b>) cast iron pipe after chlorination. IV: <span class="html-italic">Sphingomonas</span> sp. + <span class="html-italic">Microbacterium laevaniforman</span>, V: <span class="html-italic">Acidovorax defluvii</span> + <span class="html-italic">Bacillus cereus</span>, VI: <span class="html-italic">Acidovorax defluvii</span> + <span class="html-italic">Acinetobacter</span> sp., VII: <span class="html-italic">Acidovorax defluvii</span> + <span class="html-italic">Microbacterium laevaniforman</span>, VIII: <span class="html-italic">Bacillus cereus</span> + <span class="html-italic">Acinetobacter</span> sp., X: <span class="html-italic">Acinetobacter</span> sp. + <span class="html-italic">Microbacterium laevaniforman</span>. Triangular tips: amorphous extracellular matrix; arrows swollen, damaged, and deformed cells; tips: spores.</p>
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<p>Schematic of dual-species biofilm formation and chlorine resistance in two pipe materials.</p>
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