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Keywords = acetolactate synthase

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15 pages, 1055 KiB  
Article
The Influence of Plant Growth-Stimulating Bacteria on the Glutathione-S-Transferase Activity and the Toxic Effect of the Herbicide Metsulfuron-Methyl in Wheat and Canola Plants
by Darya Chetverikova, Margarita Bakaeva, Sergey Starikov, Aliya Kendjieva and Sergey Chetverikov
Toxics 2024, 12(12), 886; https://doi.org/10.3390/toxics12120886 - 5 Dec 2024
Viewed by 673
Abstract
The ability of some rhizosphere bacteria to mitigate herbicidal stress in cultivated plants may be useful in agriculture and bioremediation. There is poor understanding of how bacteria directly or through herbicide degradation affect the biochemical processes in plants exposed to sulfonylurea herbicides. In [...] Read more.
The ability of some rhizosphere bacteria to mitigate herbicidal stress in cultivated plants may be useful in agriculture and bioremediation. There is poor understanding of how bacteria directly or through herbicide degradation affect the biochemical processes in plants exposed to sulfonylurea herbicides. In this study, treatment with a combination of herbicide metsulfuron-methyl (MSM) and bacteria (Pseudomonas protegens DA1.2 or P. chlororaphis 4CH) of wheat (Triticum aestivum L.) and canola (Brassica napus L.) plants was carried out. Activity of glutathione-S-transferase (GST), an important enzyme for the herbicide detoxification, and acetolactate synthase (ALS), a target for MSM in plants, was measured by spectrophotometric assays. MSM residues were analyzed using the HPLC-MS. Then, 24 h after bacterial treatment, GST activity increased by 75–91% in wheat and by 38–94% in canola. On the 30th day, a decrease in MSM in the soil associated with bacterial treatment was 54.6–79.7%. An increase in GST activity and acceleration of MSM degradation were accompanied by a decrease in inhibition of the ALS enzyme in plants, which indicated a mitigation of the toxic effect. The results obtained are evidence that rhizospheric bacteria can have beneficial effects on plants exposed to MSM due to the combination of abilities to directly affect detoxification enzymes in plants and degrade MSM in the soil. Full article
(This article belongs to the Special Issue Insights into the Biology of Plants Affected by Toxic Chemicals)
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<p>The effect of treatment with bacteria, a low-molecular-weight fraction (LMF) of their culture fluid, and metsulfuron-methyl (MSM) on glutathione-S-transferases (GST) activity in leaf extracts of wheat (<b>a</b>) and canola (<b>b</b>); enzyme activities are presented as average and standard errors (n = 5, Duncan’s test); significantly different means are indicated by different letters (<span class="html-italic">p</span> ≤ 0.05); control—herbicide and bacteria were not used, DA1.2–strain Pseudomonas protegens DA1.2, CH4—strain <span class="html-italic">P. chlororaphis</span> CH4.</p>
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<p>The effect of treatment with bacteria, a low-molecular-weight fraction (LMF) of their culture fluid, and metsulfuron-methyl (MSM) on glutathione-S-transferases (GST) activity in leaf extracts of wheat (<b>a</b>) and canola (<b>b</b>); enzyme activities are presented as average and standard errors (n = 5, Duncan’s test); significantly different means are indicated by different letters (<span class="html-italic">p</span> ≤ 0.05); control—herbicide and bacteria were not used, DA1.2–strain Pseudomonas protegens DA1.2, CH4—strain <span class="html-italic">P. chlororaphis</span> CH4.</p>
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<p>The effect of treatment with bacteria, a low-molecular-weight fraction (LMF) of their culture fluid, and metsulfuron-methyl (MSM) on acetolactate synthase (ALS) activity in leaves of wheat and canola; n = 5, U-test, significantly different (<span class="html-italic">p</span> ≤ 0.05) means within the “wheat” dataset and the “canola” dataset are indicated by different letters (lowercase and uppercase, respectively); control—herbicide and bacteria were not used, DA1.2 –strain <span class="html-italic">Pseudomonas protegens</span> DA1.2, CH4—strain <span class="html-italic">P. chlororaphis</span> CH4.</p>
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<p>Degradation of MSM after introduction of strains <span class="html-italic">Pseudomonas protegens</span> DA1.2rif and <span class="html-italic">P. chlororaphis</span> 4CHrif in: (<b>a</b>) plant-free soils; (<b>b</b>) wheat-sown soils. NB—soil not treated with bacteria, DA1.2rif—soil treated with the rifampicin-resistant strain <span class="html-italic">Pseudomonas protegens</span> DA1.2rif, CH4—soil treated with the rifampicin-resistant strain <span class="html-italic">P. chlororaphis</span> CH4rif; data are presented as mean ± SE (n = 5, Duncan’s test, <span class="html-italic">p</span> ≤ 0.05).</p>
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12 pages, 2218 KiB  
Article
Effects of a Novel Tripyrasulfone Herbicide on Key Soil Enzyme Activities in Paddy Rice Soil
by Penglei Sun, He Sun, Shuo Yu, Lei Lian, Tao Jin, Xuegang Peng, Xiangju Li, Weitang Liu and Hengzhi Wang
Plants 2024, 13(22), 3138; https://doi.org/10.3390/plants13223138 - 7 Nov 2024
Viewed by 697
Abstract
Weeds significantly impact paddy yields, and herbicides offer a cost-effective, rapid, and efficient solution compared to manual weeding, ensuring agricultural productivity. Tripyrasulfone, a novel 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitor developed by Qingdao Kingagroot Chemicals Co., Ltd., has demonstrated high efficacy when applied post-emergence, causing [...] Read more.
Weeds significantly impact paddy yields, and herbicides offer a cost-effective, rapid, and efficient solution compared to manual weeding, ensuring agricultural productivity. Tripyrasulfone, a novel 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitor developed by Qingdao Kingagroot Chemicals Co., Ltd., has demonstrated high efficacy when applied post-emergence, causing characteristic foliar bleaching in susceptible weed species, distinct from conventional acetolactate synthase, acetyl-CoA carboxylase, and synthetic auxin herbicides. This study investigates the impact of tripyrasulfone on the activity of key soil enzymes (urease (UE), acid phosphatase (ACP), sucrase (SC), catalase (CAT), and dehydrogenase (DHA)) in paddy soils from Jilin Province and Shandong Province. Different doses of tripyrasulfone (0.1, 1.0, and 2.5 mg kg−1) were applied, and the enzymatic activities were measured. Results indicated that tripyrasulfone initially inhibited UE and ACP activities before activating them. On the 20th day after treatment, UE activity had returned to control levels, whereas ACP activity remained significantly higher, showing long-lasting activation. SC and CAT activities were inhibited but gradually recovered to control levels. Furthermore, DHA activity was activated with a sustained effect, remaining significantly higher than the control group even 20 days after treatment. Overall, the impact of tripyrasulfone on soil enzyme activities diminished over time, suggesting that tripyrasulfone posed minimal long-term ecological risk to soil health. Full article
(This article belongs to the Section Plant Protection and Biotic Interactions)
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<p>The structural formula of tripyrasulfone.</p>
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<p>Effect of tripyrasulfone on urease (UE) activity in different soils. Data represent the mean plus or minus standard deviation (<span class="html-italic">n</span> = 3). Different letters indicate significant differences at the <span class="html-italic">p</span> &lt; 0.05 level according to Fisher’s protected LSD test. (<b>A</b>): JL-SY soil; (<b>B</b>): SD-LY soil.</p>
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<p>Effect of tripyrasulfone on sucrase (SC) activity in different soils. Data represent the mean plus or minus standard deviation (<span class="html-italic">n</span> = 3). Different letters indicate significant differences at the <span class="html-italic">p</span> &lt; 0.05 level according to Fisher’s protected LSD test. (<b>A</b>): JL-SY soil; (<b>B</b>): SD-LY soil.</p>
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<p>Effect of tripyrasulfone on catalase (CAT) activity in different soils. Data represent the mean plus or minus standard deviation (<span class="html-italic">n</span> = 3). Different letters indicate significant differences at the <span class="html-italic">p</span> &lt; 0.05 level according to Fisher’s protected LSD test. (<b>A</b>): JL-SY soil; (<b>B</b>): SD-LY soil.</p>
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<p>Effect of tripyrasulfone on dehydrogenases (DHA) activity in different soils. Data represent the mean plus or minus standard deviation (<span class="html-italic">n</span> = 3). Different letters indicate significant differences at the <span class="html-italic">p</span> &lt; 0.05 level according to Fisher’s protected LSD test. (<b>A</b>): JL-SY soil; (<b>B</b>): SD-LY soil.</p>
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<p>Effect of tripyrasulfone on acid phosphatase (ACP) activity in different soils. Data represent the mean plus or minus standard deviation (<span class="html-italic">n</span> = 3). Different letters indicate significant differences at the <span class="html-italic">p</span> &lt; 0.05 level according to Fisher’s protected LSD test. (<b>A</b>): JL-SY soil; (<b>B</b>): SD-LY soil.</p>
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13 pages, 1042 KiB  
Article
Comparison of Molecularly Identified Resistant and Susceptible Johnsongrass (Sorghum halepense L.) Populations at ALS Gene, in the Absence and Presence of Field Crops
by Aristeidis P. Papapanagiotou, Eleni A. Anthimidou, Ilias G. Eleftherohorinos and Ioannis A. Giantsis
Genes 2024, 15(11), 1415; https://doi.org/10.3390/genes15111415 - 31 Oct 2024
Viewed by 600
Abstract
Background/Objectives: Johnsongrass (Sorghum halepense) is an erect tetraploid, perennial, C4 grass weed species categorized among the world’s most noxious weeds due to its high competitive ability against crops and the increased number of field-evolved herbicide-resistant populations. The aim of the present [...] Read more.
Background/Objectives: Johnsongrass (Sorghum halepense) is an erect tetraploid, perennial, C4 grass weed species categorized among the world’s most noxious weeds due to its high competitive ability against crops and the increased number of field-evolved herbicide-resistant populations. The aim of the present study was to assess the growth rate and performance of resistant (R) johnsongrass genotypes hosting Trp574Leu target-site cross-resistance at ALS gene, inhibiting various herbicides, compared to susceptible (S) conspecific weeds, in the absence and presence of corn or sunflower antagonism. Methods: The aboveground biomass, tiller, and rhizome production ability of one S and one R johnsongrass population with a Trp574-Leu substitution conferring cross-resistance to ALS-inhibiting herbicides were compared under non-competitive conditions. Furthermore, the competitive ability of these two johnsongrass populations against corn or sunflower was determined in a target-neighborhood design. Results: The S and R johnsongrass populations displayed similar growth rates concerning aboveground biomass and tiller number, whereas the R population displayed a slightly greater growth rate for rhizome production compared to the S population. Both populations grown with corn produced more aboveground biomass than the ones grown with sunflowers. The aboveground biomass of corn was reduced to a greater extent than sunflower by the presence of both johnsongrass populations, while both crops were affected more by the S than by the R population. Conclusions: Although the inheritance and the genetic background of plant materls were not addressed, the findings of this study indicate clearly that the growth rate and competitive ability of the ALS-resistant johnsongrass population are not associated with the resistance mechanism involved. Full article
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<p>Schematic presentation of the crop/weed density pattern (2:0, 2:1, 2:2, 2:3, 2:4) to assess plant responses of corn or sunflower grown in pure stands and in competition with the R (ALS-herbicide resistant) or S (sensitive) johnsongrass populations [corn or sunflower plants = open circles vs. R or S johnsongrass plants = black circles].</p>
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<p>Linear equation and coefficient of determination of aboveground biomass, number of tillers and rhizomes produced by the R and S Johnsongrass populations grown in the absence of crop competition and monitored throughout the life cycle by seven destructive samplings.</p>
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<p>Linear equation and coefficient of determination of aboveground biomass and number of tillers produced by the R and S Johnsongrass populations grown in competition with corn, as well as of the aboveground corn biomass against weed density.</p>
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<p>Linear equation and coefficient of determination of aboveground biomass and number of tillers produced by the R and S Johnsongrass populations grown in competition with sunflower, as well as the aboveground sunflower biomass against weed density.</p>
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16 pages, 17600 KiB  
Article
Using RNA-Seq Analysis to Select Key Genes Related to Seed Dormancy in ALS-Inhibiting Resistant Descurainia sophia with Pro-197-Thr Mutation
by Xian Xu, Bochui Zhao, Beibei Shen, Zhizun Qi, Jianping Wang, Haiyan Cui, Binghua Li, Silong Chen, Guiqi Wang and Xiaomin Liu
Plants 2024, 13(16), 2305; https://doi.org/10.3390/plants13162305 - 19 Aug 2024
Viewed by 830
Abstract
Flixweed (Descurainia sophia) is a weed that seriously affects wheat fields in China. Over the past 20 years, it has evolved resistance to the herbicide tribenuron-methyl. In the present study, a resistant D. sophia population with a Pro-197-Thr mutation of acetolactate [...] Read more.
Flixweed (Descurainia sophia) is a weed that seriously affects wheat fields in China. Over the past 20 years, it has evolved resistance to the herbicide tribenuron-methyl. In the present study, a resistant D. sophia population with a Pro-197-Thr mutation of acetolactate synthetase (ALS) was found to have a resistance index of 457.37 for tribenuron-methyl. Under the same growth conditions, the seeds of resistant (R) and susceptible (S) populations exhibited similar vitality but the germination rates of R seeds were higher than those of S seeds. This result demonstrated that seed dormancy periods were shorter in the R seeds. RNA-Seq transcriptome analysis was then used to choose candidate genes that could regulate seed dormancy pathways in the R population. A total of 504,976,046 clean reads were selected from nine RNA-Seq libraries and assembled into 79,729 unigenes. Among these, 33,476 unigenes were assigned to 51 GO subgroups, and 26,117 unigenes were assigned to 20 KEGG secondary metabolic pathways. Next, 2473 differentially expressed genes (DEGs) were divided into three groups, as follows: G-24 h (germinating seeds) vs. D (dormant seeds); G-48 h (germinated seeds) vs. D; and G-48 h vs. G-24 h. From these 2473 DEGs, 8 were selected as candidate dormancy unigenes for the R population if their expression levels continuously decreased during the seed germination progress and their functional annotations were related to plant seed dormancy. One candidate unigene was annotated as CYP707A2; two unigenes were annotated as the transcription factors TGA4 and TGA2; one unigene was annotated as the cystathionine beta-synthase gene; and four unigenes could not be annotated as any gene listed in the six public databases. However, qRT-PCR-validated results showed that, during the germination of R seeds, the expression of the three candidate unigenes first decreased and then increased, indicating that they may have other growth-regulating functions in R populations. In brief, the dormancy function of the eight candidate dormancy unigenes needs to be further studied. Full article
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
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<p>Whole-plant dose–response curves for flixweed (<span class="html-italic">Descurainia sophia</span>) populations that were either S (susceptible) or R (resistant) to tribenuron-methyl. Each value represents a mean of fresh weight (%control) ± standard error.</p>
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<p>Homologous alignment of ALS DNA and amino acid sequences of R, S, and <span class="html-italic">Arabidopsis thaliana</span>. The codon of the 197-Pro was CCT in <span class="html-italic">A. thaliana.</span></p>
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<p>Species distribution of BLASTX matches for the R flixweed (<span class="html-italic">Descurainia sophia</span>) transcriptome unigenes.</p>
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<p>GO function classification of the annotated unigenes in R flixweed (<span class="html-italic">Descurainia Sophia</span>). The unigenes were allocated to three categories: biological process, cellular component, and molecular function.</p>
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<p>KEGG function classification of the annotated unigenes in the R population. The <span class="html-italic">y</span>-axis lists the various KEGG pathways; the <span class="html-italic">x</span>-axis indicates the number of unigenes.</p>
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<p>Number of differentially expressed unigenes in the D, G-24 h, and G-48 h treatments in comparison with the R population. D was a dormant-seed treatment; G_24 h and G_48 h were germinated-seed treatments.</p>
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<p>Venn diagram showing numbers of differentially expressed unigenes in the D, G-24 h, and G-48 h treatments in comparison with the R population.</p>
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18 pages, 3617 KiB  
Article
RNA-Seq Unveils Cross-Talk among Stress Response Mechanisms during Leaf Color Transformation in ALS Resistant Sorghums
by Dilooshi K. Weerasooriya, Ananda Y. Bandara, Sanzhen Liu and Tesfaye T. Tesso
Crops 2024, 4(3), 348-365; https://doi.org/10.3390/crops4030025 - 1 Aug 2024
Viewed by 873
Abstract
Acetolactate synthase (ALS) inhibitor herbicides are among widely marketed herbicide chemistries that act both against grass and broad-leaved weeds. Sorghum (Sorghum bicolor (L.) Moench) variants carrying resistance to ALS inhibitor herbicides were developed as a post-emergence weed control solution in sorghum. However, [...] Read more.
Acetolactate synthase (ALS) inhibitor herbicides are among widely marketed herbicide chemistries that act both against grass and broad-leaved weeds. Sorghum (Sorghum bicolor (L.) Moench) variants carrying resistance to ALS inhibitor herbicides were developed as a post-emergence weed control solution in sorghum. However, some ALS-resistant lines exhibit noticeable interveinal chlorosis at seedling stage, leading to reduced vigor. Although the plants eventually recover at an advanced growth stage, this may be a source of concern for growers and can undermine adoption of the technology. This study was initiated to identify mechanisms related to the manifestation of this phenotype. Two ALS-resistant genotypes, one displaying a yellow phenotype and the other a normal green phenotype, were cultivated, and tissue samples were collected at four time intervals, with the final sampling occurring after the genotypes had fully re-greened. RNA was extracted from the tissue samples and subjected to RNA-Seq analysis. Differential gene expression analysis was carried out using DESeq2, and a selected set of genes were confirmed via qRT-PCR. Gene Ontology enrichment and SorghumCyc pathway analysis uncovered notable regulatory changes in genes associated with chloroplasts, plant defense responses, and hormonal networks in the yellow genotypes. The pattern of gene expression strongly mimicked responses under abiotic stresses. In addition, the findings offer new insights into the potential for sorghum genotypes resistant to environmental stresses to also exhibit tolerance to a range of additional stresses. Full article
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<p>(<b>A</b>) RNA-Seq experimental design with replicates. The stages S0 through S3 represent the stages of tissue sampling with the color code of each sample referring to the leaf color at each stage. (<b>B</b>) Phenotype of yellow and green genotypes as observed in the field.</p>
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<p>(<b>A</b>) RNA-Seq experimental design with replicates. The stages S0 through S3 represent the stages of tissue sampling with the color code of each sample referring to the leaf color at each stage. (<b>B</b>) Phenotype of yellow and green genotypes as observed in the field.</p>
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<p>The variability in seedling chlorophyll content observed for the yellow genotypes and green genotypes from S0 through S3 sampling stages. Y = yellow; G = green.</p>
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<p>The Spearman correlation between (<b>A</b>) raw read counts of normal (green) biological replicate 1 and 3 at stage S0 and (<b>B</b>) quantile normalized counts of normal (green) biological replicate 1 and 3 at stage S0. (<b>C</b>) P-value histogram of the read counts after normalization for yellow and green genotypes for comparison at S0 stage.</p>
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<p>The Spearman correlation between (<b>A</b>) raw read counts of normal (green) biological replicate 1 and 3 at stage S0 and (<b>B</b>) quantile normalized counts of normal (green) biological replicate 1 and 3 at stage S0. (<b>C</b>) P-value histogram of the read counts after normalization for yellow and green genotypes for comparison at S0 stage.</p>
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<p>The qRT-PCR validation using normalized gene expression values for seven sorghum genes using Actin as the reference gene. The expression results for all genes were consistent between the RNA-Seq and qRT-PCR analyses. Genes marked with an asterisk (*) above the bars were significantly up-regulated in the yellow genotype, while the remaining four genes showed non-significant differences in expression (<a href="#app1-crops-04-00025" class="html-app">Supplementary Table S3</a>).</p>
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<p>Up- and down-regulated gene bins in photosynthesis light reaction (<b>A</b>) at S0 and (<b>B</b>) at S3. Excessive chlorophyll degradation at S0 has been reflected by a higher number of gene bins involved in photosynthesis being down-regulated. However, at S3, almost all of the gene bins that were down-regulated have turned out to be not differentially expressed, showing recovery of the yellow color symptom by the last sampling stage (red = up-regulated; green = down-regulated; black = not differentially expressed). (<b>C</b>) Venn diagram showing the number of significantly differentially expressed genes involved in chlorophyll metabolism between yellow and green genotypes at each sampling stage.</p>
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<p>Up- and down-regulated gene bins in photosynthesis light reaction (<b>A</b>) at S0 and (<b>B</b>) at S3. Excessive chlorophyll degradation at S0 has been reflected by a higher number of gene bins involved in photosynthesis being down-regulated. However, at S3, almost all of the gene bins that were down-regulated have turned out to be not differentially expressed, showing recovery of the yellow color symptom by the last sampling stage (red = up-regulated; green = down-regulated; black = not differentially expressed). (<b>C</b>) Venn diagram showing the number of significantly differentially expressed genes involved in chlorophyll metabolism between yellow and green genotypes at each sampling stage.</p>
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<p>Heatmap showing clustering pattern of the genes related to chloroplast and stress response mechanisms (red = up-regulated; green = down-regulated; black = not differentially expressed) at four sampling stages from S0 through S3.</p>
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<p>Abiotic stress response mechanisms that showed significantly altered gene regulation. Defense response gene bins that were significantly up- or down-regulated during the S0 stage including glutathione-S-transferase, peroxidases, heat shock proteins, and defense-related hormonal pathways; auxins, brassinosteroids, jasmonic acid, salicylic acid, ethylene, and abscisic acid showed recovery of altered gene regulation by the S3 stage.</p>
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<p>Clustering pattern of significant DE genes based on the Log<sub>2</sub> fold expression ratio between yellow and green genotypes. The total number of significant genes that had significant interactions with the sampling stage were grouped into 11 basic clusters. Clusters 9, 10, and 11, which contained 327, 46, and 28 genes, which comprised stable, increasing, and decreasing gene expression ratios, were excluded from further considerations.</p>
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13 pages, 302 KiB  
Article
Emergence and Phenological Development of Herbicide-Sensitive and Herbicide-Resistant Biotypes of Apera Spica-Venti and Winter Wheat under Competition
by Beata Jop, Tomasz Wójtowicz, Katarzyna Marczewska-Kolasa, Mariusz Kucharski and Agnieszka Synowiec
Agriculture 2024, 14(6), 945; https://doi.org/10.3390/agriculture14060945 - 17 Jun 2024
Viewed by 973
Abstract
As a result of intensive herbicide protection of crops against silky bentgrass (Apera spica-venti (L.) P. Beauv), numerous herbicide-resistant biotypes have been selected, mainly from the group of acetolactate synthase (ALS) inhibitors. We analyzed the development of herbicide-sensitive and herbicide-resistant biotypes of [...] Read more.
As a result of intensive herbicide protection of crops against silky bentgrass (Apera spica-venti (L.) P. Beauv), numerous herbicide-resistant biotypes have been selected, mainly from the group of acetolactate synthase (ALS) inhibitors. We analyzed the development of herbicide-sensitive and herbicide-resistant biotypes of bentgrass and winter wheat under competition, taking into account selected physical and chemical properties of the soil, including nitrogen fertilization. The pot experiment (additive model) was conducted in the 2018/19 and 2019/20 seasons. The experimental factors included: (1) bentgrass with different sensitivity levels to herbicides from the groups HRAC/WSSA 1 and HRAC/WSSA 2, specifically two sensitive and three resistant biotypes; (2) two types of soil, sandy and clay; and (3) nitrogen fertilization, both with and without fertilization. Winter wheat and bentgrass development was assessed during each growing season, every 5 or 3 days from September until May, using the BBCH scale. The emergence date of the tested species/biotypes was recorded. The development of competing species was compared based on a new, proposed index: the duration of the developmental phases. As a result, the soil type and fertilization level differentiated wheat and bentgrass emergence dates and development. The autumn development of the competing species was slower and more uniform than the spring one. At the same time, the dynamics of the bentgrass and wheat development in the spring were greater. Bentgrass and winter wheat emerged earlier and grew more intensively on clay and fertilized soil. To sum up, no clear relationship was found between the resistance/sensitivity of bentgrass to herbicides and changes in the phenological development of plants in competition with winter wheat. Full article
(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)
17 pages, 511 KiB  
Article
Toxicity Assessment of 36 Herbicides to Green Algae: Effects of Mode of Action and Chemical Family
by Simeng Li and Hailey Mcintyre
Agrochemicals 2024, 3(2), 164-180; https://doi.org/10.3390/agrochemicals3020012 - 22 May 2024
Viewed by 2003
Abstract
Aquatic ecosystems can suffer inadvertent contamination from widely used herbicides. This study delves into the relative toxicity of 36 herbicides on green algae, exploring 11 distinct modes of action and 25 chemical structure classes. Through a 72-h algal growth inhibition test, it was [...] Read more.
Aquatic ecosystems can suffer inadvertent contamination from widely used herbicides. This study delves into the relative toxicity of 36 herbicides on green algae, exploring 11 distinct modes of action and 25 chemical structure classes. Through a 72-h algal growth inhibition test, it was found that herbicides targeting acetolactate synthase (ALS), photosystem II (PSII inhibitors), microtubule assembly, very-long-chain fatty acid (VLCFA) synthesis, and lipid synthesis exhibited high toxicity, with 72-h EC50 (half-maximal effective concentration) values ranging from 0.003 mg/L to 24.6 mg/L. Other pesticide types showed moderate to low toxicity, with EC50 values ranging from 0.59 mg/L to 143 mg/L. Interestingly, herbicides sharing the same mode of action but differing in chemical composition displayed significantly varied toxicity. For instance, penoxsulam and pyribenzoxim, both ALS inhibitors, demonstrated distinct toxicity levels. Similarly, terbuthylazine and bentazone, both PSII inhibitors, also exhibited differing toxicities. Notably, herbicides approved for rice cultivation showed lower toxicity to green algae compared to those intended for terrestrial plants. These data offer valuable insights for assessing the potential risks posed by these chemicals to aquatic organisms. Additionally, to prevent or minimize herbicide residual effects, modern management practices were reviewed to offer practical guidance. Full article
(This article belongs to the Section Herbicides)
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<p>Toxicity of 11 herbicide groups to green algae: EC50 values (n = 36). The mode of action of the herbicide groups is identified by corresponding numbers detailed in <a href="#agrochemicals-03-00012-t001" class="html-table">Table 1</a>.</p>
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14 pages, 9632 KiB  
Article
First Clarification of the Involvement of Glycosyltransferase MdUGT73CG22 in the Detoxification Metabolism of Nicosulfuron in Apple
by Yuefeng Zhang, Aijuan Zhao, Lijun Mu, Xiao Teng, Yingxin Ma, Ru Li, Kang Lei, Lusha Ji, Xuekun Wang and Pan Li
Plants 2024, 13(9), 1171; https://doi.org/10.3390/plants13091171 - 23 Apr 2024
Cited by 1 | Viewed by 1075
Abstract
Nicosulfuron, an acetolactate synthase (ALS) inhibitor herbicide, is a broad-spectrum and highly effective post-emergence herbicide. Glycosyltransferases (GTs) are widely found in organisms and transfer sugar molecules from donors to acceptors to form glycosides or sugar esters, thereby altering the physicochemical properties of the [...] Read more.
Nicosulfuron, an acetolactate synthase (ALS) inhibitor herbicide, is a broad-spectrum and highly effective post-emergence herbicide. Glycosyltransferases (GTs) are widely found in organisms and transfer sugar molecules from donors to acceptors to form glycosides or sugar esters, thereby altering the physicochemical properties of the acceptor molecule, such as participating in detoxification. In this study, nine glycosyltransferases in group D of the apple glycosyltransferase family I were predicted to possibly be involved in the detoxification metabolism of ALS-inhibiting herbicides based on gene chip data published online. In order to confirm this, we analysed whether the expression of the nine glycosyltransferase genes in group D was induced by the previously reported ALS-inhibiting herbicides by real-time PCR (polymerase chain reaction). It was found that the ALS-inhibiting herbicide nicosulfuron significantly increased the expression of the MdUGT73CG22 gene in group D. Further investigation of the mechanism of action revealed that the apple glycosyltransferase MdUGT73CG22 glycosylated and modified nicosulfuron both in vivo and ex vivo to form nicosulfuron glycosides, which were involved in detoxification metabolism. In conclusion, a new glycosyltransferase, MdUGT73CG22, was identified for the first time in this study, which can glycosylate modifications of the ALS-inhibiting herbicide nicosulfuron and may be involved in the detoxification process in plants, which can help to further improve the knowledge of the non-targeted mechanism of herbicides. Full article
(This article belongs to the Special Issue Plant Chemical Ecology)
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<p>Relative expression of nine glycosyltransferase genes induced by 12 types of acetolactate synthase (ALS) inhibitor herbicides: (<b>a</b>) real-time PCR detection of glycosyltransferase gene <span class="html-italic">MdUGT73B40</span> (<span class="html-italic">MD05G1085700</span>), <span class="html-italic">MdUGT73CG21</span> (<span class="html-italic">MD12G1104300</span>), <span class="html-italic">MdUGT73CG22</span> (<span class="html-italic">MD12G1104800</span>), <span class="html-italic">MdUGT73CP3</span> (<span class="html-italic">MD05G1085400</span>), and <span class="html-italic">MdUGT73AC7</span> (<span class="html-italic">MD05G1085600</span>) are affected by acetolactate synthase (ALS) inhibitor herbicides: bensulfuron methyl, nicosulfuron, thifensulfuron, chlorsulfuron, metsulfuron, triasulfuron, cinosulfuron, chlorimuron-ethyl, sulfometuron, pyrazosulfuron, rimsulfuron, and ethametsulfuron induced expression at 0, 3, 6, 12, and 24 h; (<b>b</b>) real-time PCR detection of glycosyltransferase gene <span class="html-italic">MdUGT73CG22</span> (<span class="html-italic">MD12G1104800</span>) subjected to expression induced by the acetolactate synthase (ALS) inhibitor-like herbicide nicosulfuron at 0, 3, 6, 12, and 24 h. Note: <span class="html-italic">* p</span> &lt; 0.05, <span class="html-italic">** p</span> &lt; 0.01, <span class="html-italic">n</span> = 3.</p>
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<p>Relative expression of nine glycosyltransferase genes induced by 12 types of acetolactate synthase (ALS) inhibitor herbicides: (<b>a</b>) real-time PCR detection of glycosyltransferase gene <span class="html-italic">MdUGT73B40</span> (<span class="html-italic">MD05G1085700</span>), <span class="html-italic">MdUGT73CG21</span> (<span class="html-italic">MD12G1104300</span>), <span class="html-italic">MdUGT73CG22</span> (<span class="html-italic">MD12G1104800</span>), <span class="html-italic">MdUGT73CP3</span> (<span class="html-italic">MD05G1085400</span>), and <span class="html-italic">MdUGT73AC7</span> (<span class="html-italic">MD05G1085600</span>) are affected by acetolactate synthase (ALS) inhibitor herbicides: bensulfuron methyl, nicosulfuron, thifensulfuron, chlorsulfuron, metsulfuron, triasulfuron, cinosulfuron, chlorimuron-ethyl, sulfometuron, pyrazosulfuron, rimsulfuron, and ethametsulfuron induced expression at 0, 3, 6, 12, and 24 h; (<b>b</b>) real-time PCR detection of glycosyltransferase gene <span class="html-italic">MdUGT73CG22</span> (<span class="html-italic">MD12G1104800</span>) subjected to expression induced by the acetolactate synthase (ALS) inhibitor-like herbicide nicosulfuron at 0, 3, 6, 12, and 24 h. Note: <span class="html-italic">* p</span> &lt; 0.05, <span class="html-italic">** p</span> &lt; 0.01, <span class="html-italic">n</span> = 3.</p>
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<p>Real-time PCR detection of apple glycosyltransferase MdUGT73CG22 tissue expression pattern, including root, stem, young leaves, mature leaves, flower, young peel, mature peel, young seeds, and mature seeds. Note: * <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 3.</p>
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<p>HPLC identification of glycosylation substrates for the apple glycosyltransferase MdUGT73CG22: (<b>a</b>) lane M is Mark; lane S1 is GST tag protein extracted from bacterial solution; lane S2 is MdUGT73CG22-GST fusion protein extracted from bacterial solution; lane S3 is purified GST tag protein; lane S4 is purified MdUGT73CG22 protein. Induced expression of apple glycosyltransferase MdUGT73CG22 protein GST tag: 26.0 KDa; MdUGT73CG22-GST: 81.0 KDa; (<b>b</b>) HPLC assay revealed that apple glycosyltransferase MdUGT73CG22 could modify nicosulfuron by glycosylation in vitro, with a peak time of 2.9 min for nicosulfuron and 2.3 min for nicosulfuron glycosides; (<b>c</b>) determination of nicosulfuron glycosides, the product of apple glycosyltransferase MdUGT73CG22, by molecular weight by HPLC-MS.</p>
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<p>HPLC identification of glycosylation substrates for the apple glycosyltransferase MdUGT73CG22: (<b>a</b>) lane M is Mark; lane S1 is GST tag protein extracted from bacterial solution; lane S2 is MdUGT73CG22-GST fusion protein extracted from bacterial solution; lane S3 is purified GST tag protein; lane S4 is purified MdUGT73CG22 protein. Induced expression of apple glycosyltransferase MdUGT73CG22 protein GST tag: 26.0 KDa; MdUGT73CG22-GST: 81.0 KDa; (<b>b</b>) HPLC assay revealed that apple glycosyltransferase MdUGT73CG22 could modify nicosulfuron by glycosylation in vitro, with a peak time of 2.9 min for nicosulfuron and 2.3 min for nicosulfuron glycosides; (<b>c</b>) determination of nicosulfuron glycosides, the product of apple glycosyltransferase MdUGT73CG22, by molecular weight by HPLC-MS.</p>
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<p>HPLC detection of nicosulfuron glycosides in apple glycosyltransferase gene <span class="html-italic">MdUGT73CG22</span> overexpression lines <span class="html-italic">OE14</span> and <span class="html-italic">OE26</span>: (<b>a</b>) expression level of gene <span class="html-italic">MdUGT73CG22</span> in overexpression lines detected by real-time PCR; (<b>b</b>) HPLC detection of nicosulfuron glycosides in <span class="html-italic">MdUGT73CG22</span> overexpression lines <span class="html-italic">OE14</span> and <span class="html-italic">OE26</span>. Note: 1, nicosulfuron glycosides, 2.3 min; 2, nicosulfuron, 2.9 min; 3, internal reference, 3.8 min. Note: ** <span class="html-italic">p</span> &lt; 0.01, <span class="html-italic">n</span> = 3.</p>
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12 pages, 2094 KiB  
Article
Distribution and Mechanism of Japanese Brome (Bromus japonicus) Resistance to ALS-Inhibiting Herbicides in China
by Linzhi Bai, Xiangju Li, Xiaotong Guo, Jingchao Chen, Haiyan Yu and Hailan Cui
Plants 2024, 13(8), 1139; https://doi.org/10.3390/plants13081139 - 19 Apr 2024
Viewed by 1161
Abstract
Bromus japonicus is a common monocot weed that occurs in major winter wheat fields in the Huang–Huai–Hai region of China. Pyroxsulam is a highly efficient and safe acetolactate synthase (ALS)-inhibiting herbicide that is widely used to control common weeds in wheat fields. However, [...] Read more.
Bromus japonicus is a common monocot weed that occurs in major winter wheat fields in the Huang–Huai–Hai region of China. Pyroxsulam is a highly efficient and safe acetolactate synthase (ALS)-inhibiting herbicide that is widely used to control common weeds in wheat fields. However, B. japonicus populations in China have evolved resistance to pyroxsulam by different mutations in the ALS gene. To understand the resistance distribution, target-site resistance mechanisms, and cross-resistance patterns, 208 B. japonicus populations were collected from eight provinces. In the resistant population screening experiment, 59 populations from six provinces showed different resistance levels to pyroxsulam compared with the susceptible population, of which 17 B. japonicus populations with moderate or high levels of resistance to pyroxsulam were mainly from the Hebei (4), Shandong (4) and Shanxi (9) Provinces. Some resistant populations were selected to investigate the target site-resistance mechanism to the ALS-inhibiting herbicide pyroxsulam. Three pairs of primers were designed to amplify the ALS sequence, which was assembled into the complete ALS sequence with a length of 1932 bp. DNA sequencing of ALS revealed that four different ALS mutations (Pro-197-Ser, Pro-197-Thr, Pro-197-Phe and Asp-376-Glu) were found in 17 moderately or highly resistant populations. Subsequently, five resistant populations, QM21-41 with Pro-197-Ser, QM20-8 with Pro-197-Thr and Pro-197-Phe, and QM21-72, QM21-76 and QM21-79 with Asp-376-Glu mutations in ALS genes, were selected to characterize their cross-resistance patterns to ALS inhibitors. The QM21-41, QM20-8, QM21-72, QM21-76 and QM21-79 populations showed broad-spectrum cross-resistance to pyroxsulam, mesosulfuron–methyl and flucarbazone–sodium. This study is the first to report evolving cross-resistance to ALS-inhibiting herbicides due to Pro-197-Phe mutations in B. japonicus. Full article
(This article belongs to the Section Plant Protection and Biotic Interactions)
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<p>Levels and geographical distribution of pyroxsulam resistance in <span class="html-italic">Bromus japonicus</span> populations in China.</p>
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<p>Pyroxsulam GR<sub>50</sub> values of <span class="html-italic">Bromus japonicus</span> populations from different provinces.</p>
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<p>Dose-response curve of one susceptible and five resistant <span class="html-italic">B. japonicus</span> populations to different ALS inhibitors: pyroxsulam (<b>A</b>), mesosulfuron-methyl (<b>B</b>) and flucarbazone-sodium (<b>C</b>).</p>
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17 pages, 3554 KiB  
Article
Effect of Plant Growth-Promoting Bacteria on Antioxidant Status, Acetolactate Synthase Activity, and Growth of Common Wheat and Canola Exposed to Metsulfuron-Methyl
by Margarita Bakaeva, Sergey Chetverikov, Sergey Starikov, Aliya Kendjieva, Gaisar Khudaygulov and Darya Chetverikova
J. Xenobiot. 2024, 14(1), 79-95; https://doi.org/10.3390/jox14010005 - 2 Jan 2024
Cited by 1 | Viewed by 6451
Abstract
Metsulfuron-methyl, a widely used herbicide, could cause damage to the sensitive plants in crop-rotation systems at extremely low levels in the soil. The potential of plant growth-promoting bacteria (PGPB) for enhancing the resistance of plants against herbicide stress has been discovered recently. Therefore, [...] Read more.
Metsulfuron-methyl, a widely used herbicide, could cause damage to the sensitive plants in crop-rotation systems at extremely low levels in the soil. The potential of plant growth-promoting bacteria (PGPB) for enhancing the resistance of plants against herbicide stress has been discovered recently. Therefore, it is poorly understood how physiological processes occur in plants, while PGPB reduce the phytotoxicity of herbicides for agricultural crops. In greenhouse studies, the effect of strains Pseudomonas protegens DA1.2 and Pseudomonas chlororaphis 4CH on oxidative damage, acetolactate synthase (ALS), enzymatic and non-enzymatic antioxidants in canola (Brassica napus L.), and wheat (Triticum aestivum L.) were investigated under two levels (0.05 and 0.25 mg∙kg−1) of metsulfuron-methyl using spectrophotometric assays. The inoculation of herbicide-exposed wheat with bacteria significantly increased the shoots fresh weight (24–28%), amount of glutathione GSH (60–73%), and flavonoids (5–14%), as well as activity of ascorbate peroxidase (129–140%), superoxide dismutase SOD (35–49%), and ALS (50–57%). Bacterial treatment stimulated the activity of SOD (37–94%), ALS (65–73%), glutathione reductase (19–20%), and the accumulation of GSH (61–261%), flavonoids (17–22%), and shoots weight (27–33%) in herbicide-exposed canola. Simultaneous inoculation prevented lipid peroxidation induced by metsulfuron-methyl in sensitive plants. Based on the findings, it is possible that the protective role of bacterial strains against metsulfuron-metil is linked to antioxidant system activation. Full article
(This article belongs to the Special Issue Plant Biostimulants - a Promising Tool in Organic Farming)
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<p>The scheme of wheat (<b>A</b>) and rapeseed (<b>B</b>) treatments. The figure does not indicate the location of the pots in the greenhouse.</p>
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<p>Effect of strains <span class="html-italic">Pseudomonas protegens</span> DA1.2, <span class="html-italic">P. chlororaphis</span> 4CH, and metsulfuron-methyl treatment on the fresh weight (FW) of one wheat (<b>A</b>) or rapeseed (<b>B</b>) shoot; significantly different means are indicated by different letters (<span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 30).</p>
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<p>Effect of <span class="html-italic">Pseudomonas protegens</span> DA1.2, <span class="html-italic">P. chlororaphis</span> 4CH, and metsulfuron-methyl treatment on the MDA level in wheat (<b>A</b>) and rapeseed (<b>B</b>) shoots; significantly different means are indicated by different letters (<span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 5).</p>
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<p>Effect of <span class="html-italic">Pseudomonas protegens</span> DA1.2, <span class="html-italic">P. chlororaphis</span> 4CH, and metsulfuron-methyl treatment on the activity of GR (<b>A</b>), APX (<b>B</b>), SOD (<b>C</b>), and CAT (<b>D</b>) from wheat shoots; significantly different means are indicated by different letters (<span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6).</p>
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<p>Effect of <span class="html-italic">Pseudomonas protegens</span> DA1.2, <span class="html-italic">P. chlororaphis</span> 4CH, and metsulfuron-methyl treatment on the activity of GR (<b>A</b>), APX (<b>B</b>), SOD (<b>C</b>), and CAT (<b>D</b>) from canola shoots; significantly different means are indicated by different letters (<span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6).</p>
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<p>Effect of strains <span class="html-italic">Pseudomonas protegens</span> DA1.2, <span class="html-italic">P. chlororaphis</span> 4CH, and metsulfuron-methyl treatment on the ALS activity in wheat (<b>A</b>) and rapeseed (<b>B</b>) shoots; significantly different means are indicated by different letters (<span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6).</p>
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16 pages, 2318 KiB  
Article
Post-Emergence Water-Dispersal Application Provides Equal Herbicidal Activity against Echinochloa crus-galli and Rice Safety as Foliar Spraying of Penoxsulam
by Jinqiu Sun, Xiaoyue Yu, Hongxing Xu, Yongjie Yang, Mengjie Liu, Yanchao Zhang, Yongliang Lu and Wei Tang
Plants 2023, 12(23), 4061; https://doi.org/10.3390/plants12234061 - 3 Dec 2023
Cited by 2 | Viewed by 1537
Abstract
Penoxsulam is an acetolactate synthase (ALS)-inhibiting herbicide usually applied by post-emergence foliar spraying (PFS) for the control of Echinochloa crus-galli and numerous annual weeds in paddy fields. Herbicides applied by foliar spraying can have negative impacts on the environment, ecosystems, and human health. [...] Read more.
Penoxsulam is an acetolactate synthase (ALS)-inhibiting herbicide usually applied by post-emergence foliar spraying (PFS) for the control of Echinochloa crus-galli and numerous annual weeds in paddy fields. Herbicides applied by foliar spraying can have negative impacts on the environment, ecosystems, and human health. In this study, the response of E. crus-galli and rice to the PFS and post-emergence water-dispersal (PWD) applications of penoxsulam, and the differences in the detoxification displayed by them between the two treatment methods were compared. The results showed that the PWD application of penoxsulam provides a similar control efficacy against E. crus-galli as PFS at the 1-, 3-, and 5-leaf stages. Meanwhile, the PWD application had a higher safety for the rice. After being treated with 30 g a.i. ha−1 penoxsulam, residues were not detected in the rice treated by the PWD application method, whereas, with the PFS treatment, there was 59.0 µg/kg penoxsulam remaining. With the PFS application, there were many more residues of penoxsulam in the E. crus-galli than with the PWD method; the amount of residues was 32-fold higher 12 h after treatment. The in vitro enzyme activity assays revealed that the activities of ALS, glutathione-S-transferase (GST), and cytochrome P450 monooxygenases (P450) were increased in the PWD treatments, and were 1.5-, 1.3-, and 2.3-fold higher than with PFS 72 h after treatment. The real-time quantitative PCR (qRT-PCR) revealed that the GST1 and P450 genes, CYP81A14, CYP81A12, CYP81A18, and CYP81A21 were upregulated with the PWD application versus PFS in the E. crus-galli. In summary, these results demonstrate that the herbicidal activity was not affected by the upregulation of target and metabolic enzyme activities with the PWD application of penoxsulam. This research could contribute to application strategies reducing the risk of rice injury and environmental impacts by using water-dispersal formulations of penoxsulam. Full article
(This article belongs to the Special Issue Sustainable Weed Management II)
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<p>Photographs of barnyard grass after 21 days of treatment with different doses of penoxsulam by post-emergence foliar spraying (PFS) and water-dispersal application (PWD). The first, second, and third rows represent <span class="html-italic">E. crus-galli</span> at 1- (first row), 3- (second row), and 5-leaf stages (third row), respectively.</p>
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<p>Dose–response curve of <span class="html-italic">E. crus-galli</span> at 1-leaf stage (<b>a</b>), 3-leaf stage (<b>b</b>) and 5-leaf stage (<b>c</b>) at different doses of penoxsulam by post-emergence foliar spraying (PFS) and water-dispersal application (PWD). Each point represents the mean ± SE of twice-repeated experiments, each including three replicates.</p>
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<p>Activity of ALS (<b>a</b>), P450 (<b>b</b>), and GST (<b>c</b>) at 0, 12, 24, 72, and 120 h after treatment with penoxsulam by post-emergence foliar spraying (PFS) and water-dispersal application (PWD). Each point refers to mean ± SE of twice-repeated experiments, each including three replicates. The significance between the two methods was detected by <span class="html-italic">t</span>-tests (** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>The gene expression levels of <span class="html-italic">ALS</span> (<b>a</b>), <span class="html-italic">GST1</span> (<b>b</b>), and <span class="html-italic">CYP81A14</span> (<b>c</b>) at different time intervals, and the relative gene expression levels of <span class="html-italic">CYP81A12</span>, <span class="html-italic">CYP81A18,</span> and <span class="html-italic">CYP81A21</span> after 24 h treatment by post-emergence foliar spraying (PFS) and water-dispersal application (PWD) of penoxsulam treatment (<b>d</b>). Data are presented as mean ± SE; significant differences between the two methods were detected by <span class="html-italic">t</span>-tests (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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17 pages, 2910 KiB  
Article
Snapshot of the Probiotic Potential of Kluveromyces marxianus DMKU-1042 Using a Comparative Probiogenomics Approach
by Mati Ullah, Muhammad Rizwan, Ali Raza, Yutong Xia, Jianda Han, Yi Ma and Huayou Chen
Foods 2023, 12(23), 4329; https://doi.org/10.3390/foods12234329 - 30 Nov 2023
Cited by 2 | Viewed by 2172
Abstract
Kluyveromyces marxianus is a rapidly growing thermotolerant yeast that secretes a variety of lytic enzymes, utilizes different sugars, and produces ethanol. The probiotic potential of this yeast has not been well explored. To evaluate its probiotic potential, the yeast strain Kluyveromyces marxianus DMKU3-1042 [...] Read more.
Kluyveromyces marxianus is a rapidly growing thermotolerant yeast that secretes a variety of lytic enzymes, utilizes different sugars, and produces ethanol. The probiotic potential of this yeast has not been well explored. To evaluate its probiotic potential, the yeast strain Kluyveromyces marxianus DMKU3-1042 was analyzed using next-generation sequencing technology. Analysis of the genomes showed that the yeast isolates had a GC content of 40.10–40.59%. The isolates had many genes related to glycerol and mannose metabolism, as well as genes for acetoin and butanediol metabolism, acetolactate synthase subunits, and lactic acid fermentation. The strain isolates were also found to possess genes for the synthesis of different vitamins and Coenzyme A. Genes related to heat and hyperosmotic shock tolerance, as well as protection against reactive oxygen species were also found. Additionally, the isolates contained genes for the synthesis of lysine, threonine, methionine, and cysteine, as well as genes with anticoagulation and anti-inflammatory properties. Based on our analysis, we concluded that the strain DMKU3-1042 possesses probiotic properties that make it suitable for use in food and feed supplementation. Full article
(This article belongs to the Special Issue Milk and Dairy Products: Quality, Microorganisms and Health Benefits)
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<p>Whole-genome-based phylogenetic tree of 5 isolates of <span class="html-italic">Kluyveromyces marxianus</span> DMKU3-1042 genomes compared to the genomes of other strains. To generate the support values of the tree, 100 rounds of RAxML Fast Bootstrapping option were used.</p>
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<p>Whole-genome comparison of <span class="html-italic">Kluyveromyces marxianus</span> DMKU3-1042 genomes with other yeast strains.</p>
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<p>Functional categorization of all predicted coding sequences (CDS) in <span class="html-italic">Kluyveromyces marxianus</span> strains.</p>
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<p>Relative abundance of sugars between <span class="html-italic">K. marxianus</span> strain DMKU3-1042 isolates (S1, S2, S3, S4, S5) and other investigated strains in this study.</p>
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<p>Relative abundance of vitamins, coenzymes, and prosthetic groups across <span class="html-italic">K. marxianus</span> strains in this study.</p>
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<p>The percentage frequency of the three forms of glutathione across <span class="html-italic">K. marxianus</span> strains.</p>
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17 pages, 10377 KiB  
Article
Do Traits Travel? Multiple-Herbicide-Resistant A. tuberculatus, an Alien Weed Species in Israel
by Idan S. Roth, Aviv Singer, Inon Yadid, Moshe Sibony, Zvi Peleg and Baruch Rubin
Plants 2023, 12(23), 4002; https://doi.org/10.3390/plants12234002 - 28 Nov 2023
Viewed by 1109
Abstract
Amaranthus tuberculatus is the most common weed in soybean and corn in the USA and Canada. In Israel, it has been a minor riverbank weed. However, in recent years, growing densities of this plant have been observed in field crops, orchards, and roadsides. [...] Read more.
Amaranthus tuberculatus is the most common weed in soybean and corn in the USA and Canada. In Israel, it has been a minor riverbank weed. However, in recent years, growing densities of this plant have been observed in field crops, orchards, and roadsides. Between 2017 and 2022, we surveyed the distribution of A. tuberculatus and collected seeds for further study. We identified three main distribution zones in Israel: the Jezreel Valley, Hula Valley, and Coastal Plain. Most of the populations were found near water sources, fishponds, barns, dairies, or bird-feeding sites, suggesting the involvement of imported grain in introducing A. tuberculatus to Israel. Populations were screened for their responses to various post-emergence herbicides (i.e., ALS, EPSPS, PPO, HPPD, and PSII inhibitors). Several populations from the Jezreel Valley were found to be putatively resistant to ALS, EPSPS, and PPO inhibitors. The responses of those populations to trifloxysulfuron, glyphosate, and carfentrazone-ethyl were also studied. A single ALS-, EPSPS- and PPO-resistant plant was vegetatively propagated to create a clonal population, which was treated with foramsulfuron, glyphosate, and carfentrazone-ethyl. No resistance to PSII or HPPD inhibitors was observed, but resistance to herbicides that inhibit ALS, EPSPS, and PPO was observed. A clonal propagation assay revealed the existence of a population that was resistant to ALS, EPSPS, and PPO inhibitors. Since the local A. tuberculatus populations have not been exposed to herbicide selection pressure, these traits probably reached Israel through seed-mediated gene flow via imported grain. Full article
(This article belongs to the Collection Feature Papers in Plant Protection)
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<p>Map of the distribution of <span class="html-italic">A. tuberculatus</span> in Israel. This species has been found in three main areas: the Jezreel Valley, the Hula Valley, and the Coastal Plain. Detected = populations from which seeds were not collected or populations identified as susceptible.</p>
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<p>Dose-response curves of two <span class="html-italic">A. tuberculatus</span> populations, Newe Ya’ar (NY, R) and Nahal Timnah (NT, S), to glyphosate (0, 90, 180, 360, 720, 1080, 1440, 2160, 2880 g acid equivalent (ae) ha<sup>−1</sup>) applied post-emergence at the four-to-six-leaf stage. The data represent the mean shoot dry weights (% of untreated control) of three different experiments. Plants were harvested 21 days after application (DAA). UTC-untreated control.</p>
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<p>Glyphosate dose responses (21 DAA) of two populations of <span class="html-italic">A. tuberculatus</span> at 21 DAA, Newe Ya’ar (back row, resistant) and Nahal Timnah (front row, susceptible). The numbers on the pots indicate glyphosate doses of 0, 90, 180, 360, 720, 1080, 1440, 2160, and 2880 g ae ha<sup>−1</sup>. The recommended dose is 720 g ae ha<sup>−1</sup>.</p>
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<p>Dose–response curves of four <span class="html-italic">A. tuberculatus</span> populations: (<span class="html-fig-inline" id="plants-12-04002-i001"><img alt="Plants 12 04002 i001" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i001.png"/></span>) AT-Tel Nof, (<span class="html-fig-inline" id="plants-12-04002-i004"><img alt="Plants 12 04002 i004" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i004.png"/></span>) ZM-Tzora, (ALS-intermediate), (<span class="html-fig-inline" id="plants-12-04002-i003"><img alt="Plants 12 04002 i003" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i003.png"/></span>) NY-Newe Ya’ar and (<span class="html-fig-inline" id="plants-12-04002-i002"><img alt="Plants 12 04002 i002" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i002.png"/></span>) GA-Ginegar (ALS-resistant). Trifloxysulfuron (0, 0.35, 0.7, 2.8, 5.6, 11.3, 45 and 90 g ai ha<sup>−1</sup>) was applied at the four-to-six-leaf stage. The data represent the mean shoot dry weights (% of control) of plants harvested at 21 DAA. Plants were grown in a net-house under ambient summer conditions. UTC-untreated control.</p>
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<p>Trifloxysulfuron dose responses (21 DAA) of three <span class="html-italic">A. tuberculatus</span> populations: (<b>A</b>)-Newe Ya’ar (resistant), (<b>B</b>)-Ginegar (resistant) and, (<b>C</b>)-Tel Nof (susceptible). The pots are labeled with the applied trifloxysulfuron doses: 0, 0.35, 0.7, 2.8, 5.6, 11.3, 45 or 90 (g ai ha<sup>−1</sup>). 11.3 g ai ha<sup>−1</sup> is the recommended dose.</p>
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<p>Dose–response curves of four <span class="html-italic">A. tuberculatus</span> populations from the Jezreel Valley: carfentrazone-ethyl-susceptible-(<span class="html-fig-inline" id="plants-12-04002-i001"><img alt="Plants 12 04002 i001" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i001.png"/></span>) ZM-Tzora; (<span class="html-fig-inline" id="plants-12-04002-i002"><img alt="Plants 12 04002 i002" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i002.png"/></span>) GA-Ginegar; carfentrazone-ethyl-resistant (<span class="html-fig-inline" id="plants-12-04002-i004"><img alt="Plants 12 04002 i004" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i004.png"/></span>) KY-Kfar Yehoshua and (<span class="html-fig-inline" id="plants-12-04002-i003"><img alt="Plants 12 04002 i003" src="/plants/plants-12-04002/article_deploy/html/images/plants-12-04002-i003.png"/></span>) HG-Havat Gadash. Carfentrazone-ethyl (0, 5, 10, 20, 40, 60, 80, and 120 g ai ha<sup>−1</sup>) was applied post-emergence to seedlings at the four-to-six-leaf stage, which were grown in a net-house under ambient summer conditions. The experiment was repeated twice, and the data represent the mean shoot dry weights (% of control) of plants harvested at 21 DAA. UTC-untreated control.</p>
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<p>Carfentrazone-ethyl dose responses (21 DAA) of two populations of <span class="html-italic">A. tuberculatus</span>: Tzora (susceptible) and Kfar Yehoshua (resistant). Numbers indicate doses of 0, 5, 10, 20, 40, 60, 80, and 120 g ai ha<sup>−1</sup> applied post-emergence to seedlings at the four-to-six-leaf stage, which were grown in a net-house under ambient summer conditions. The recommended dose is 20 g ai ha<sup>−1</sup>.</p>
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<p>Results of a multiple-resistance assay using clonal propagated plants. Plants were propagated from a single mother plant from each population (Megiddo-resistant and Tzora-susceptible). The plants were treated post-emergence with carfentrazone-ethyl (20 g ai ha<sup>−1</sup>), foramsulfuron (45 g ai ha<sup>−1</sup>), and glyphosate (360 g ae ha<sup>−1</sup>). The data represent the mean shoot dry weights (% of control) of plants harvested at 21 DAA. The responses of the different populations were tested twice, and the means were compared using a student’s <span class="html-italic">t</span>-test for each herbicide treatment. Means followed by the same letter are not significantly different (<span class="html-italic">p</span> ≤ 0.05). UTC-untreated control.</p>
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<p><span class="html-italic">Amaranthus tuberculatus</span> infestation following local dairy cow manure application in olive grove-Jezreel Valley (2018).</p>
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<p>Schematic description of the clonal cutting experiment. Five stock plants from two <span class="html-italic">A. tuberculatus</span> were examined. Four cuttings were rooted in water from each stock plant, transferred to a growth mix in pots, and treated with the different herbicides in five biological replicates.</p>
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14 pages, 3366 KiB  
Article
Cytochrome P450s-Involved Enhanced Metabolism Contributes to the High Level of Nicosulfuron Resistance in Digitaria sanguinalis from China
by Xumiao Wang, Wei Hu, Yuxi Li, Minghao Jiang, Ning Zhao, Haiqun Cao and Min Liao
Biology 2023, 12(9), 1192; https://doi.org/10.3390/biology12091192 - 31 Aug 2023
Cited by 4 | Viewed by 1393
Abstract
Large crabgrass (Digitaria sanguinalis (L.) Scop.) is one of the major malignant grass weeds in Chinese maize (Zea mays L.) fields, and it has recently developed resistance to the acetolactate synthase (ALS)-inhibiting herbicide nicosulfuron. This study focused on a suspected nicosulfuron-resistant [...] Read more.
Large crabgrass (Digitaria sanguinalis (L.) Scop.) is one of the major malignant grass weeds in Chinese maize (Zea mays L.) fields, and it has recently developed resistance to the acetolactate synthase (ALS)-inhibiting herbicide nicosulfuron. This study focused on a suspected nicosulfuron-resistant (R) population (LJ-01) of D. sanguinalis, collected from Lujiang County in Anhui Province, China, to explore the resistance level and potential resistance mechanism. Whole-plant dose–response testing confirmed that the LJ-01 population evolved a high level of resistance to nicosulfuron (11.5-fold) compared to the susceptible (S) population, DY-02. The ALS gene sequencing and relative expression assay of the R plants indicated that target gene mutation and overexpression were not responsible for the resistance phenotype. However, pretreatment with malathion, a known cytochrome P450 monooxygenase (P450) inhibitor, alleviated the resistance of the R population to nicosulfuron by approximately 36%. High-performance liquid chromatography (HPLC) analysis revealed that the R plants metabolized nicosulfuron faster than the S plants. Moreover, cross-resistance testing suggested that the R population exhibited low levels of resistance to thifensulfuron-methyl and pyrazosulfuron-ethyl, but it remained susceptible to rimsulfuron. Multiple resistance patterns showed that the R population evolved low resistance to the photosystem inhibitors bromoxynil octanoate and atrazine and sensitivity to the acetyl-CoA carboxylase (ACCase) inhibitor cyhalofop-butyl and the 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitors tembotrione, mesotrione, and topramezone. This study reports, for the first time, the simultaneous resistance to ALS and different photosystem inhibitors in D. sanguinalis. The nicosulfuron resistance observed in the R population could primarily be attributed to an enhanced metabolism involving P450 enzymes. Full article
(This article belongs to the Special Issue Current Advances in Weed Biology, Ecology and Management)
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Figure 1
<p>Sequence alignment of <span class="html-italic">ALS</span> genes amplified from the ALS-resistant (LJ-01) and ALS-susceptible (DY-02) populations of <span class="html-italic">D. sanguinalis</span>. The bold text indicates the known nine codon positions in <span class="html-italic">ALS</span> that can mutate to confer ALS resistance.</p>
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<p>Relative expression level of the <span class="html-italic">ALS</span> gene in the R and S plants of <span class="html-italic">D. sanguinalis</span> at 0 (control), 12, and 24 h after nicosulfuron treatment. No significant difference in <span class="html-italic">ALS</span> expression between R and S populations was detected. Vertical bars represent the standard errors of the means.</p>
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<p>(<b>A</b>) Nicosulfuron susceptibility of the S (bottom) and R (top) populations without or with P450 inhibition. Weed seedlings were grown to the three- to four-leaf stages and treated with water (CK), malathion alone (M), nicosulfuron alone (T), and malathion plus nicosulfuron (M + T). Photographs were taken 21 d after treatment. (<b>B</b>) Whole-plant dose–response curves for the aboveground fresh weights of the S (▼) and R (●) populations treated with nicosulfuron alone or nicosulfuron plus 1000 g a.i. ha<sup>−1</sup> malathion (△, ○). Vertical bars represent the standard errors of the means.</p>
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<p>Typical chromatograms of the nicosulfuron detected in the (<b>A</b>) standard, (<b>B</b>) green means S plants, and (<b>C</b>) red means R plants at 48 h after treatment.</p>
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<p>Susceptibilities of the R and S populations of <span class="html-italic">D. sanguinalis</span> to nine herbicides with four modes of action, including ALS inhibitors: (<b>A</b>) thifensulfuron-methyl; (<b>B</b>) rimsulfuron; (<b>C</b>) pyrazosulfuron-ethyl; HPPD inhibitors—(<b>D</b>) tembotrione, (<b>E</b>) mesotrione, and (<b>F</b>) topramezone; PS II inhibitors—(<b>G</b>) bromoxynil octanoate and (<b>H</b>) atrazine; ACCase inhibitor—(<b>I</b>) cyhalofop-butyl. Vertical bars represent the standard errors of the means.</p>
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15 pages, 2749 KiB  
Article
Unveiling the Impact of Different Nitrogen Fertilizer Levels on Rice’s Eating Quality through Metabolite Evaluation
by Nianbing Zhou, Yanhong Zhang, Tong Sun, Jinyan Zhu, Jinlong Hu and Qiangqiang Xiong
Agronomy 2023, 13(8), 2123; https://doi.org/10.3390/agronomy13082123 - 13 Aug 2023
Viewed by 1485
Abstract
We investigated the variations in metabolites associated with the quality of rice consumption when exposed to varying nitrogen fertilizer levels, as well as the regulatory role of pivotal metabolites within metabolic pathways. This research employed Hongyang 5 as the subject of experimentation, examining [...] Read more.
We investigated the variations in metabolites associated with the quality of rice consumption when exposed to varying nitrogen fertilizer levels, as well as the regulatory role of pivotal metabolites within metabolic pathways. This research employed Hongyang 5 as the subject of experimentation, examining the metabolites of Hongyang 5 at three different nitrogen levels using non-targeted metabonomic analysis. The findings indicated that the overall assessment of the eating quality/palatability (CEQ) and amylose contents (AC) of Low nitrogen (D1: 180 kg·ha−1) was notably greater than that of Medium nitrogen (D2: 270 kg·ha−1) and High nitrogen (D3: 315 kg·ha−1). Conversely, the amylopectin (APC), total starch (SC), and protein contents (AP) of D1 were remarkably lower than those observed in D2 and D3. The starch debranching enzyme (DBE) and granule-bound starch synthetase (GBSS) of D1 were remarkably higher than those of D2 and D3. The soluble starch synthase (SSS) of D1 was the lowest. The ADP-glucose pyro-phosphorylase (AGP) and starch branching enzyme (SBE) of D3 were remarkably higher than that of D1 and D2. We identified 76 differential metabolites (DMs) between D1 and D2 (20 up-regulated and 56 down-regulated). A total of 88 DMs were identified between D3 and D1 (42 up-regulated and 46 down-regulated). A total of 57 DMs were identified between D3 and D2. Most of the DMs related to rice-eating quality were involved in the lipid metabolic pathway and amino acid metabolic pathway. The essential metabolites within the metabolic pathway are classified as lipid metabolites and are (13(S)-hydroperoxylinolenic acid, PGB2, 3-phosphocholine, 7-epijasmonic acid, 20-carboxyleukotriene B4 and 11-dehydro-thromboxane B2), amino acid metabolites (4-guanidinobutanoic acid, (3R, 5S)-1-pyrroline-3-hydroxy-5-carboxylic acid, citric acid, (S)-2-Acetolactate, L-glutamine, L-2, 4-aminobutyric acid and putrescine). These key metabolites may be affected by nitrogen fertilizer conditions and play critical regulatory roles in the metabolic pathway, resulting in differences in rice eating quality. Full article
(This article belongs to the Section Farming Sustainability)
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<p>The PCA of rice quality and enzyme activities. (<b>A</b>) PCA of enzyme activities under nitrogen treatments; (<b>B</b>) PCA of rice eating quality under nitrogen treatments; (<b>C</b>) PCA of rice component content under nitrogen treatments. The ellipses of different colors indicate that the "real" samples of this group are distributed in this region with 95% confidence; Exceeding this area indicates that the sample may be abnormal.</p>
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<p>Exploration of multivariate statistical analysis and differential metabolites under three nitrogen fertilizer treatments. (<b>A</b>) PCA score plot illustrating the distribution of samples as per their metabolic profiles. The ellipses of different colors indicate that the "real" samples of this group are distributed in this region with 95% confidence; Exceeding this area indicates that the sample may be abnormal. (<b>B</b>) PLS-DA score plot demonstrating the discrimination between different treatments. In the figure, the greater the degree of separation between the two groups of samples, the smaller the overlap of ellipses of different colors, indicating that the classification effect is more significant. (<b>C</b>) DMs up-regulated and down-regulated in different comparison groups. (<b>D</b>) Venn distribution map depicting the overlapping and unique metabolites among the treatments. Different colors represent different groups, overlapping numbers represent the number of metabolites common to multiple groups, and non-overlapping numbers represent the number of metabolites unique to the corresponding group.</p>
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<p>Statistical map of compounds based on HMDB hierarchy (Class). (<b>A</b>) Comparison between D1 and D2 treatments showing the metabolites organized by class, listed in descending sequence of abundance. (<b>B</b>) Comparison between D3 and D1 treatments displaying the metabolites categorized by class, listed in descending sequence of abundance. (<b>C</b>) Comparison between D3 and D2 treatments indicating the metabolites grouped by class, listed in descending sequence of abundance.</p>
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<p>Volcano plot of DMs. Each dot depicts a specific metabolite, with the dot size corresponding to the VIP value. <span class="html-italic">p</span> values were estimated with paired Student’s <span class="html-italic">t</span>-test on Single dimensional statistical analysis. VIP &gt; 1, fold-change = 1, <span class="html-italic">p</span> &lt; 0.05 is a significant difference metabolite. The down-regulated metabolites are on the left side, while the up-regulated metabolites are on the right side. The further to the right or left a point is, the higher significant the differential expression. (<b>A</b>) D1 and D2 treatment comparison (<b>B</b>) D3 and D1 treatments comparison. (<b>C</b>) D3 and D2 treatments comparison.</p>
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<p>Correlation analysis between rice enzyme activities and DMs, unraveling potential links between enzymatic processes and metabolic regulation in rice. Each cell represents the correlation between two attributes (metabolites and associated features), with different colors representing the magnitude of the correlation coefficient between attributes. * indicates statistical significant at the <span class="html-italic">p</span> = 0.05 level, whereas ** significance at the <span class="html-italic">p</span> = 0.01 level, *** indicates statistical signifificantat the <span class="html-italic">p</span> = 0.001 level.</p>
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<p>A snapshot of the potential regulation of essential metabolites in metabolic pathways during pairwise comparisons of three nitrogen levels. Key metabolites are highlighted within orange rectangles. Small red rectangles denote significant metabolite content upregulation, while small blue rectangles denote significant downregulation. Small grey rectangles denote no significant difference in metabolite content. This visualization provides insights into the regulatory patterns of essential metabolites under different nitrogen levels.</p>
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