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Search Results (1,454)

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21 pages, 11139 KiB  
Article
The Transcriptional Landscape of Berry Skin in Red and White PIWI (“Pilzwiderstandsfähig”) Grapevines Possessing QTLs for Partial Resistance to Downy and Powdery Mildews
by Francesco Scariolo, Giovanni Gabelli, Gabriele Magon, Fabio Palumbo, Carlotta Pirrello, Silvia Farinati, Andrea Curioni, Aurélien Devillars, Margherita Lucchin, Gianni Barcaccia and Alessandro Vannozzi
Plants 2024, 13(18), 2574; https://doi.org/10.3390/plants13182574 - 13 Sep 2024
Viewed by 269
Abstract
PIWI, from the German word Pilzwiderstandsfähig, meaning “fungus-resistant”, refers to grapevine cultivars bred for resistance to fungal pathogens such as Erysiphe necator (the causal agent of powdery mildew) and Plasmopara viticola (the causal agent of downy mildew), two major diseases in viticulture. These [...] Read more.
PIWI, from the German word Pilzwiderstandsfähig, meaning “fungus-resistant”, refers to grapevine cultivars bred for resistance to fungal pathogens such as Erysiphe necator (the causal agent of powdery mildew) and Plasmopara viticola (the causal agent of downy mildew), two major diseases in viticulture. These varieties are typically developed through traditional breeding, often crossbreeding European Vitis vinifera with American or Asian species that carry natural disease resistance. This study investigates the transcriptional profiles of exocarp tissues in mature berries from four PIWI grapevine varieties compared to their elite parental counterparts using RNA-seq analysis. We performed RNA-seq on four PIWI varieties (two red and two white) and their noble parents to identify differential gene expression patterns. Comprehensive analyses, including Differential Gene Expression (DEGs), Gene Set Enrichment Analysis (GSEA), Weighted Gene Co-expression Network Analysis (WGCNA), and tau analysis, revealed distinct gene clusters and individual genes characterizing the transcriptional landscape of PIWI varieties. Differentially expressed genes indicated significant changes in pathways related to organic acid metabolism and membrane transport, potentially contributing to enhanced resilience. WGCNA and k-means clustering highlighted co-expression modules linked to PIWI genotypes and their unique tolerance profiles. Tau analysis identified genes uniquely expressed in specific genotypes, with several already known for their defense roles. These findings offer insights into the molecular mechanisms underlying grapevine resistance and suggest promising avenues for breeding strategies to enhance disease resistance and overall grape quality in viticulture. Full article
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<p>(<b>A</b>) Correlation matrix heatmap showing the Euclidean distance between samples based on normalized data obtained from 18 RNA-seq samples constituted of berry skin tissues of the CC, CV, CS, SR, SN, and SB varieties in the ripening (R) phase. A darker color indicates a stronger correlation. (<b>B</b>) PCA on normalized data obtained from 18 RNA-seq samples. Colors indicate different varieties considered. (<b>C</b>) The histogram shows the number of upregulated and downregulated DEGs in white and red PIWI varieties compared to their respective noble parents (SB for white and CS for red). It includes both cumulative comparisons of all PIWI varieties of the same color against their parental variety, as well as individual comparisons (e.g., SR vs. SB). (<b>D</b>) Upset plots visualizing the intersections amongst different groups of DEGs identified in pairwise comparisons. Single points indicate a private DEG identified in each group, whereas 2 to <span class="html-italic">n</span> dot plots indicate DEGs shared by 2 to n groups.</p>
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<p>K-means-corrected WGCNA. (<b>A</b>) Cluster dendrogram of module eigengenes. Branches of the dendrogram group together eigengenes that are positively correlated. The merge threshold was set to 0.25: modules under this value were merged due to their similarity in expression profiles. (<b>B)</b> Bar graph showing the distribution of genes over the twenty-six modules identified. (<b>C</b>) Module-variety/trait association analysis. The heatmap shows the correlation between modules and varieties/traits. Each row corresponds to a module, whereas each column corresponds to a specific trait. The correlation coefficient between a given module and tissue type is indicated by the color of the cell at the row–column intersection and by the text inside the cells (squared boxes indicate significant <span class="html-italic">p</span>-values). Red and blue indicate positive and negative correlations, respectively. CC, Cabernet cortis; SN, Sauvignon nepis; SR, Sauvignon rytos; CV, Cabernet volos; SB, Sauvignon blanc; CS, Cabernet sauvignon; T/S, tolerance/susceptibility; GC, grape color. (<b>D</b>) Scatterplots of gene significance (GS) vs. module membership (MM) in the brown module associated with Cabernet cortis (CC). Genes highly significantly associated with a trait are often also the most important (central) elements of modules associated with the trait. (<b>E</b>) Heatmap visualizing gene expression within the brown module across all biological replicates of the six considered varieties, normalized using Z-scores.</p>
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<p>Modules contemporaneously associated with both tolerance/susceptibility and one or more grapevine varieties analyzed. (<b>A</b>) Table showing the orientation of correlations in all varieties/traits considered (CC, Cabernet cortis; SN, Sauvignon nepis; SR, Sauvignon rytos; CV, Cabernet volos; SB, Sauvignon blanc; CS, Cabernet sauvignon; T/S, tolerance/susceptibility; GC, grape color). Green arrows indicate a positive correlation between the specific module and the trait/genotype. Red arrows indicate a negative association between the specific module and the trait/genotype considered. (<b>B</b>) Gene Set Enrichment Analyses of the tan and blue modules showing the top 10 enriched categories based on fold change. The threshold <span class="html-italic">p</span>-value was set to 0.01 (<b>C</b>) Heatmap visualizing gene expression within the blue and tan modules across all biological replicates of the six considered varieties, normalized using Z-scores.</p>
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<p>Vesicle transport pathways in plants. COP-II vesicles mediate cargo transport from the ER to the cis-Golgi, while COP-I traffics the cargo from the Golgi to the ER and intra-Golgi as well. Clathrin-mediated endocytosis (CME) is the primary mechanism by which eukaryotic cells internalize extracellular or membrane-bound cargoes and it plays crucial roles in plant–microbe interactions Clathrin-coated vesicles (CCVs) are involved in the flow of cargo from the plasma membrane and trans-Golgi network to endosomes and retromers. Grapevine genes found to be enriched in the tan module are indicated in proximity to the related transport pathway.</p>
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<p>Identification of absolutely specific genes in different grapevine varieties. (<b>A</b>) Distribution of the variety-specificity tau parameter over the 23,847 genes considered. (<b>B</b>) Bar graph showing the distribution of absolutely specific genes (ASG; tau = 1) and highly specific genes (HSG; tau &gt; 0.85) over the six varieties considered. (<b>C</b>) Heatmap illustrating the expression of ASG in all biological replicates of the six varieties considered (Z-score normalized). (<b>D</b>) Scatterplot illustrating the relation/negative correlation r = −0.78) between specificity (tau) and expression in Sauvignon nepis. Blue dots represent all genes considered in the analysis, orange dots represent ASG in S. nepis, and red dots indicate the top optimal genes for S. nepis based on the score value. (<b>E</b>) Heatmap showing the expression of the top 10 optimal genes identified over the six varieties considered.</p>
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14 pages, 1236 KiB  
Article
Diversity of Saccharomyces cerevisiae Yeast Strains in Granxa D’Outeiro Winery (DOP Ribeiro, NW Spain): Oenological Potential
by Pilar Blanco, Estefanía García-Luque, Rebeca González, Elvira Soto, José Manuel M. Juste and Rafael Cao
Fermentation 2024, 10(9), 475; https://doi.org/10.3390/fermentation10090475 - 13 Sep 2024
Viewed by 209
Abstract
Yeasts play an essential role in the aroma and sensory profiles of wines. Spontaneous fermentations were carried out at the newly built winery of Granxa D’Outeiro. Yeasts were isolated from must at different stages of fermentation. Colonies belonging to Saccharomyces cerevisiae were characterised [...] Read more.
Yeasts play an essential role in the aroma and sensory profiles of wines. Spontaneous fermentations were carried out at the newly built winery of Granxa D’Outeiro. Yeasts were isolated from must at different stages of fermentation. Colonies belonging to Saccharomyces cerevisiae were characterised at the strain level by mtDNA-RFLPs. General chemical parameters and aroma profiles of the wines were determined using official OIV methodology and GC-MS analysis, respectively. The diversity of S. cerevisiae per fermentation ranged from 5 to 13 different strains depending on the grapevine variety. Out of 24 strains, strain B was the dominant yeast in most fermentations at different proportions, but strains D, E, and H also reached up to 25% of the total population in some fermentations. The yeast diversity was higher in the Lado fermentation than in those containing Treixadura. The chemical compositions of the wines revealed differences among them, with Loureira and Albariño wines showing the highest content of volatile compounds. The evaluation of their technological properties revealed the oenological potential of some strains of S. cerevisiae. The strains showing the best scores were selected to be used in future vintages to enhance the typicality of wines in the Granxa D’Outeiro winery. Full article
(This article belongs to the Special Issue Saccharomyces cerevisiae Strains and Fermentation: 2nd Edition)
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<p>Cumulative percentages of <span class="html-italic">Saccharomyces cerevisiae</span> strains isolated from spontaneous fermentations in the Granxa D’Outeiro winery. Sc-minor: the sum of the strains found at proportions &lt; 5% in each wine.</p>
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<p>Principal component analysis (PCA) of wines from the Granxa D’Outeiro winery based on their main volatile compounds.</p>
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<p>Concentrations (mg/L) of the main families of fermentative volatile compounds in wines obtained with different <span class="html-italic">S. cerevisiae</span> strains isolated from the Granxa D’Outeiro winery.</p>
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10 pages, 1290 KiB  
Article
Characterization of Genetic Diversity in the Capsid Protein Gene of Grapevine Fleck Virus and Development of a New Real-Time RT-PCR Assay
by Juliana Osse de Souza, Vicki Klaassen, Kristian Stevens, Teresa M. Erickson, Claire Heinitz and Maher Al Rwahnih
Viruses 2024, 16(9), 1457; https://doi.org/10.3390/v16091457 - 13 Sep 2024
Viewed by 201
Abstract
The grapevine fleck virus (GFkV) is a ubiquitous grapevine-infecting virus found worldwide, is associated with the grapevine fleck complex, and is often found in mixed infections with viruses of the grapevine leafroll complex and/or vitiviruses. Although GFkV has been studied for a long [...] Read more.
The grapevine fleck virus (GFkV) is a ubiquitous grapevine-infecting virus found worldwide, is associated with the grapevine fleck complex, and is often found in mixed infections with viruses of the grapevine leafroll complex and/or vitiviruses. Although GFkV has been studied for a long time, limited sequence information is available in the public databases. In this study, the GFkV sequence data available in GenBank and data generated at the Foundation Plant Services, University of California, Davis, were used to perform nucleotide sequence comparisons, construct a phylogenetic tree, and develop a new RT-qPCR assay. Sequence comparisons showed high genetic diversity among the GFkV isolates, and the phylogenetic analyses revealed a new group comprised of GFkV isolates identified in the present study. A new assay, referred to as GFkV-CP, was designed and validated using an existing GFkV positive control together with 11 samples known to be infected with combinations of different marafiviruses and maculaviruses but not GFkV. In addition, the newly designed assay was used in a field survey to screen grapevines from diverse geographical locations that are maintained at the United States Department of Agriculture (USDA) National Clonal Germplasm Repository (NCGR) in Winters, CA. Full article
(This article belongs to the Special Issue Diversity and Coinfections of Plant or Fungal Viruses, 3rd Edition)
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<p>Bayesian phylogenetic consensus tree generated from an alignment of the complete open reading frame (ORF) 2, which encodes the capsid protein (CP), of 73 grapevine fleck virus (GFkV) isolates generated in the present study and 53 GFkV isolates from GenBank, for a total of 126 sequences. The phylogenetic analysis was performed with BEAST v.2.5. Branch strengths were evaluated by Bayesian posterior probabilities; posterior probabilities for the two most important clades are shown. The length of horizontal branches corresponds to the rate of nucleotide substitution. GenBank accession numbers are given.</p>
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<p>Alignment of partial capsid protein gene of selected grapevine fleck virus (GFkV) isolates showing the binding sites of the primers and probes developed in this study. The red horizontal bars represent the primers and probes of the GFkV-CP assay designed in this study, the sequences of primers and probes are directly below the bars. Nucleotide divergence is highlighted in different colors for each nucleotide.</p>
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21 pages, 6139 KiB  
Article
Identification of VvAGL Genes Reveals Their Network’s Involvement in the Modulation of Seed Abortion via Responding Multi-Hormone Signals in Grapevines
by Fei Liu, Rana Badar Aziz, Yumiao Wang, Xuxian Xuan, Mucheng Yu, Ziyang Qi, Xinpeng Chen, Qiqi Wu, Ziyang Qu, Tianyu Dong, Shaonan Li, Jinggui Fang and Chen Wang
Int. J. Mol. Sci. 2024, 25(18), 9849; https://doi.org/10.3390/ijms25189849 - 12 Sep 2024
Viewed by 205
Abstract
The formation of seedless traits is regulated by multiple factors. AGLs, which belong to the MADS-box family, were reported to be important regulators in this process; however, the underlying mechanism remains elusive. Here, we identified the VvAGL sub-family genes during the seed abortion [...] Read more.
The formation of seedless traits is regulated by multiple factors. AGLs, which belong to the MADS-box family, were reported to be important regulators in this process; however, the underlying mechanism remains elusive. Here, we identified the VvAGL sub-family genes during the seed abortion process in seedless grapevine cv. ‘JingkeJing’ and found 40 differentially expressed VvAGL members and 1069 interacting proteins in this process. Interestingly, almost all members and their interacting proteins involved in the tryptophan metabolic pathway (K14486) and participated in the phytohormone signalling (KO04075) pathway, including the growth hormone (IAA), salicylic acid (SA), abscisic acid (ABA), cytokinin (CTK), and ethylene signalling pathways. The promoters of AGL sub-family genes contain cis-elements in response to hormones such as IAA, ABA, CTK, SA, and ETH, implying that they might respond to multi-hormone signals and involve in hormone signal transductions. Further expression analysis revealed VvAGL6-2, VvAGL11, VvAGL62-11, and VvAGL15 had the highest expression at the critical period of seed abortion, and there were positive correlations between ETH-VvAGL15-VvAGL6-2, ABA-VvAGL80, and SA-VvAGL62 in promoting seed abortion but negative feedback between IAA-VvAGL15-VvAGL6-2 and CTK-VvAGL11. Furthermore, many genes in the IAA, ABA, SA, CTK, and ETH pathways had a special expressional pattern in the seed, whereby we developed a regulatory network mediated by VvAGLs by responding to multihormonal crosstalk during grape seed abortion. Our findings provide new insights into the regulatory network of VvAGLs in multi-hormone signalling to regulate grape seed abortion, which could be helpful in the molecular breeding of high-quality seedless grapes. Full article
(This article belongs to the Collection Advances in Molecular Plant Sciences)
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<p>Morphological changes in berries’ development during grapevine seed abortion process: (<b>A</b>) Morphological changes of ‘Zhengyan seedless’ during berries and seeds development in seeds abortion process. (<b>B</b>) The length and width of grapefruits in the seed abortion process.</p>
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<p>Physicochemical properties of AGL family genes: (<b>A</b>) Residual base. (<b>B</b>) Molecular mass/KD. (<b>C</b>) Isoelectric point. (<b>D</b>) Fat factor. (<b>E</b>) Hydrophilicity. (<b>F</b>) Maximum distribution of chromosomes. The X-axis indicates the chromosome on which the AGL sub-family genes are located, and the Y-axis indicates the maximum and minimum values of the corresponding physicochemical properties of the genes distributed on this chromosome.</p>
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<p>Sequence analysis and chromosomal location of <span class="html-italic">VvAGLs</span>: (<b>A</b>) The phylogenetic tree generated using the MEGA11.0 program with the Maximum Likelihood method. Yellow, green and blue colours represent different branches; red colour indicates the CDS region of the gene structure and purple colour represents the exons of the gene. (<b>B</b>) The exon–intron composition of <span class="html-italic">AGL</span> genes. The coding sequences (CDS) and up- or down-stream regions of <span class="html-italic">AGL</span> genes are represented by red and purple boxes, respectively. Lines represent the introns. (<b>C</b>) The chromosome localisation of <span class="html-italic">VvAGLs</span>. The red dashed box indicates the distribution of key AGL family members on the chromosome. Different colours represent different chromosomes.</p>
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<p>Phylogenetic analysis of the AGL family across six species: The phylogenetic tree was generated after an alignment of deduced <span class="html-italic">Vitis vinifera</span>, <span class="html-italic">Zea mays</span>, <span class="html-italic">Arabidopsis thaliana</span>, <span class="html-italic">Citrus sinensis</span>, <span class="html-italic">Malus domestic</span>, and <span class="html-italic">Solanum lycopersicum AGL</span> domains at the N-terminus. We constructed the phylogenetic tree using the Maximum Likelihood method against MEGA11.0 to study the evolutionary relationship between species. Based on the results of the clustering analysis of the homologous gene family, a single copy of the homologous gene was selected for multi-sequence alignment [using MUSCLE software (MEGA11.0) for sequence alignment] and a phylogenetic tree was constructed based on the single-copy gene method. Stars represented VvAGLs family members, triangular stars represented the main members of VvAGLs, different colors represented different groupings.</p>
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<p>GO and KEEG enrichment analysis of <span class="html-italic">VvAGLs</span> family: (<b>A</b>) Number of interacting proteins in different periods. (<b>B</b>) The KEGG pathway annotation of the top 42 significant enriched pathways. (<b>C</b>) The GO analysis of 14 biological processes. Numbers on columns: The number of interacted genes involved in the GO pathway. ko00604//Glycosphingolipid biosynthesis—ganglio series.</p>
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<p>Screening and analysis of cis-elements in the promoters of <span class="html-italic">VvAGLs</span>: (<b>A</b>) The number of hormone-responsive cis-elements in promoter regions of <span class="html-italic">VvAGLs</span>; (<b>B</b>) Types of hormone-responsive cis-elements in promoter regions of <span class="html-italic">VvAGLs.</span> ABRE: ABA-responsive cis-elements; AuxRR-core and TGA-element: IAA-responsive cis-elements; CGTCA-motif and TGACG-motif: MeJA-responsive cis-elements; TCA-element and SARE: SA-responsive cis-elements; GARE-motif, P-box and TATC-box: GA-responsive cis-elements. ABA: abscisic acid; CTK: cytokinin; AUX/IAA: auxin–response repressor protein/indole acetic acid; SA: salicylic acid; MeJA: methyl jasmonate. Lighter to darker colous represented an increase in the number of cis-elements.</p>
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<p>Expression analysis of <span class="html-italic">VvAGL</span> and reciprocal proteins: (<b>A</b>) Expression of the <span class="html-italic">VvAGL</span> family at different developmental periods. (<b>B</b>) Expression of <span class="html-italic">VvAGL</span> reciprocal proteins at different developmental periods. (<b>C</b>) Proteins are specifically expressed in different hormone metabolic pathways. JY: Stage of seed development; JS: Stage of seed beginning to abort; JB: Late stage of seed abortion; Asterisks indicate a significant difference between JY, JS, and JB by Student (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Expression analysis of <span class="html-italic">VvAGL</span> and reciprocal proteins: (<b>A</b>) Expression of the <span class="html-italic">VvAGL</span> family at different developmental periods. (<b>B</b>) Expression of <span class="html-italic">VvAGL</span> reciprocal proteins at different developmental periods. (<b>C</b>) Proteins are specifically expressed in different hormone metabolic pathways. JY: Stage of seed development; JS: Stage of seed beginning to abort; JB: Late stage of seed abortion; Asterisks indicate a significant difference between JY, JS, and JB by Student (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Expression of <span class="html-italic">VvAGL</span> family members in grape seed. Asterisks indicate a significant difference between different development periods using Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.01; ** <span class="html-italic">p</span> &lt; 0.05); WK ‘Wink’; HL ‘Blush seedless’; JT ‘Jintian Huangjia seedless’.</p>
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<p>VvAGL-interacting genes and polyhormonal regulatory networks: (<b>A</b>) AGL family genes and interacting proteins are involved in the metabolic processes. (<b>B</b>) Involvement of VvAGL-interacting genes in the polyhormonal interaction network. (<b>C</b>) The levels of VvAGLs expression and the involvement of hormonal biosynthesis and signalling genes in plant growth and development. Asterisks indicate a significant difference between different development periods using Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.01; ** <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Schematic representation of plant hormone metabolism and signalling pathway gene network during grape seed abortion. The genes involved in the CTK signalling pathway are represented by a grey box; the genes involved in the SA signalling pathway are represented by a brown box; the genes involved in the IAA signalling pathway are represented by an orange box; the genes involved in ETH signalling pathway are represented by the yellow box; the genes involved in ABA signalling pathway are represented by the green box. STK, AP2, FUL, SUN, and bHLH were referenced in previous studies but not identified in this study. The bidirectional arrows represented the interaction between the two genes.</p>
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29 pages, 10327 KiB  
Article
Simulation and Testing of Grapevine Branch Crushing and Collection Components
by Lei He, Zhimin Wang, Long Song, Pengyu Bao and Silin Cao
Agriculture 2024, 14(9), 1583; https://doi.org/10.3390/agriculture14091583 - 11 Sep 2024
Viewed by 336
Abstract
Aiming at the problem of the low rate of resource utilization of large amounts of grape branch pruning and the high cost of leaving the garden, we design a kind of grape branch picking and crushing collection machine that integrates the collection of [...] Read more.
Aiming at the problem of the low rate of resource utilization of large amounts of grape branch pruning and the high cost of leaving the garden, we design a kind of grape branch picking and crushing collection machine that integrates the collection of strips, the picking up, crushing, and collecting operations. The crushing and collecting parts of the machine are simulated, analyzed, and tested. Using the method of numerical simulation, combined with the results of the pre-branch material properties measurement, the branch crushing process is simulated based on LS-DYNA software. Our analysis found that in the branch destruction process, not only does knife cutting exist, but the bending fracture of the opposite side of the cutting place also exists. With the increase in the knife roller speed, the cutting resistance of the tool increases, reaching 2690 N at 2500 r/min. In the cutting simulation under different tool edge angles, the cutting resistance of the tool is the smallest when the edge angle is 55°, which is 1860 N, and this edge angle is more suitable for branch crushing and cutting. In the cutting simulation under different cutting edge angles, the cutting resistance of the tool is the smallest when the edge angle is 55°, which is 1860 N, and this edge angle is more suitable for branch crushing and cutting. Using Fluent software to analyze the characteristics of the airflow field of the pulverizing device, it was found that with the increase in the knife roller speed, the inlet flow and negative pressure of the pulverizing chamber increase. When the knife roller speed is 2500 r/min, the inlet flow rate and negative pressure are 1.92 kg/s and 37.16 Pa, respectively, which will be favorable to the feeding of the branches, but the speed is too high and will also lead to the enhancement of the vortex in some areas within the pulverizing device, which will in turn affect the feeding of the branches as well as the throwing out of pulverized materials. Therefore, the speed range of the pulverizing knife roller was finally determined to be 1800~2220 r/min. Based on the ANSYS/Model module modal analysis of the crushing knife roller, the knife roller of the first six orders of the intrinsic frequency and vibration pattern, the crushing knife roller of the lowest order had a modal intrinsic frequency of 137.42 Hz, much larger than the crushing knife roller operating frequency of 37 Hz, above which the machine will not resonate during operation. The research results can provide a theoretical basis and technical support for other similar crops to be crushed and collected. Full article
(This article belongs to the Section Agricultural Technology)
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<p>Establishment of three-dimensional models of branches and knife rollers.</p>
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<p>Mesh division of branches and knife rollers.</p>
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<p>Initial interface of crushing process.</p>
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<p>Three-dimensional model and grid division diagram of crushing device.</p>
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<p>Grid division diagram of crushing knife roller.</p>
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<p>The process of crushing grape branches.</p>
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<p>The process of crushing grape branches.</p>
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<p>Cutting force–time curve under different blade roller speeds.</p>
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<p>Cutting force–time curve under different blade roller speeds.</p>
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<p>Maximum cutting resistance and corresponding time at different blade roller speeds.</p>
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<p>Cutting force–time curve under different cutting tool angles.</p>
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<p>Maximum cutting resistance and corresponding time under different cutting tool angles.</p>
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<p>Cross-section location map of fluid computing domain.</p>
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<p>Speed cloud map of P1~P7 sections at a speed of 2100 r/min.</p>
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<p>Speed cloud map of P1~P7 sections at a speed of 2100 r/min.</p>
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<p>Cloud map of surface pressure on the grinding knife roller at a speed of 2100 r/min.</p>
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<p>Pressure cloud map of inlet and P1~P7 sections at a speed of 2100 r/min.</p>
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<p>Cloud map of inlet pressure at different rotational speeds.</p>
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<p>Inlet mass flow rate and maximum negative pressure at different blade roller speeds.</p>
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<p>P2, P3 cross-sectional streamline diagram at different speeds.</p>
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<p>Modal shape of the grinding knife roller at each stage.</p>
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<p>Modal shape of the grinding knife roller at each stage.</p>
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<p>Crushing effect.</p>
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25 pages, 2229 KiB  
Review
CRISPR/Cas in Grapevine Genome Editing: The Best Is Yet to Come
by Chong Ren, Mohamed Salaheldin Mokhtar Mohamed, Nuremanguli Aini, Yangfu Kuang and Zhenchang Liang
Horticulturae 2024, 10(9), 965; https://doi.org/10.3390/horticulturae10090965 - 11 Sep 2024
Viewed by 447
Abstract
The advent of Clustered Regularly Interspaced Palindromic Repeat (CRISPR)/CRISPR-associated (Cas) proteins as a revolutionary innovation in genome editing has greatly promoted targeted modification and trait improvement in most plant species. For grapevine (Vitis vinifera L.), a perennial woody plant species, CRISPR/Cas genome [...] Read more.
The advent of Clustered Regularly Interspaced Palindromic Repeat (CRISPR)/CRISPR-associated (Cas) proteins as a revolutionary innovation in genome editing has greatly promoted targeted modification and trait improvement in most plant species. For grapevine (Vitis vinifera L.), a perennial woody plant species, CRISPR/Cas genome editing is an extremely promising technique for genetic improvement in a short period. Advances in grapevine genome editing have been achieved by using CRISPR technology in recent years, which promises to accelerate trait improvement in grapevine. In this review, we describe the development and advances in CRISPR/Cas9 and its orthologs and variants. We summarize the applications of genome editing in grapevine and discuss the challenges facing grapevine genome editing as well as the possible strategies that could be used to improve genome editing in grapevine. In addition, we outline future perspectives for grapevine genome editing in a model system, precise genome editing, accelerated trait improvement, and transgene-free genome editing. We believe that CRISPR/Cas will play a more important role in grapevine genome editing, and an exciting and bright future is expected in this economically significant species. Full article
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<p>Illustration of the generic organizations of the class 1 and class 2 CRISPR/Cas loci. Class 1 systems have effector modules composed of multiple Cas proteins that function in protein complex during the editing. Class 2 systems have a single, multidomain effector protein that is functionally analogous to the effector protein complex of class 1. Some of the class 2 systems like Cas9 proteins require trans-acting CRISPR RNA (tracrRNA).</p>
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<p>Genome editing induced by CRISPR/Cas9 and CRISPR/Cas12a. Both CRISPR/Cas9 and CRISPR/Cas12a generate double-stranded break (DSB), which can be repaired via end joining or the homology-directed repair (HDR) pathway, resulting in indel (random insertion or deletion) or knock-in mutations. The inserted nucleotides via end joining and desired mutations carried by donor template are indicated in red and yellow, respectively.</p>
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<p>Current CRISPR editing in grapevine. CRISPR/Cas9 (including optimized Cas9 system) and CRISPR/LbCas12a have been employed for gene knockout. CRISPR activation systems based on nuclease-dead Cas9 (dCas9), namely, dCas9-VP64 and dCas9-TV, have been developed for gene activation. Cytosine base editor (CBE) and prime editor (PE) have been used for base editing. RNA-targeting effectors, FnCas9 and LshCas13a, have also been reported in grapevine.</p>
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<p>Time schedule of Agrobacterium-mediated CRISPR editing in grapevine.</p>
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<p>A strategy for accelerated improvement of grapevine traits. Bioinformatics analysis based on sequencing data and grapevine phenome provides candidate genes, and CRISPR editing, together with grape transformation system, enables a rapid verification of gene functions. The results pave the way for improvement of different grapevine traits.</p>
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15 pages, 1338 KiB  
Article
Varying Tolerance to Diesel Toxicity Revealed by Growth Response Evaluation of Petunia grandiflora Shoot Lines Regenerated after Diesel Fuel Treatment
by Solomon Peter Wante, David W. M. Leung and Hossein Alizadeh
Agriculture 2024, 14(9), 1562; https://doi.org/10.3390/agriculture14091562 - 9 Sep 2024
Viewed by 273
Abstract
Continuous efforts are required to find ways to protect crop production against the toxicity of petroleum hydrocarbons, such as diesel, and contamination of soils. There is a need for identification of candidate plants that are tolerant to diesel toxicity that might also have [...] Read more.
Continuous efforts are required to find ways to protect crop production against the toxicity of petroleum hydrocarbons, such as diesel, and contamination of soils. There is a need for identification of candidate plants that are tolerant to diesel toxicity that might also have the potential for remediation of diesel-contaminated soils. In this study, petunia, a popular ornamental plant and a model experimental plant in research on phytoremediation of environmental pollutants, was used to evaluate a novel method for rapidly assessing diesel toxicity based on the tolerance of shoots generated through in vitro plant cell culture selection. Petunia shoot lines (L1 to L4) regenerated from diesel-treated callus were compared with those from non-diesel-treated callus (control). Significant morphological differences were observed among the tested lines and control, notably with L1 and L4 showing superior growth. In particular, L4 exhibited remarkable adaptability, with increased root development and microbial counts in a diesel-contaminated potting mix, suggesting that the shoots exhibited enhanced tolerance to diesel exposure. Here, this rapid bioassay has been shown to effectively identify plants with varying levels of tolerance to diesel toxicity and could therefore assist accelerated selection of superior plants for phytoremediation. Further research is needed to understand the genetic and physiological mechanisms underlying tolerance traits, with potential applications beyond petunias to other environmentally significant plants. Full article
(This article belongs to the Section Crop Production)
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<p>The stem diameters of <span class="html-italic">Petunia grandiflora</span> shoot cuttings of lines 1, 2, 3, and 4 [subfigures (<b>a</b>–<b>d</b>), respectively], and controls C-G and C-R in the four subfigures, were measured after 5 weeks of growth under glasshouse conditions. The average stem diameters at the beginning of each experiment were 3.3 mm. Values represent means ± SEM of three replicates in each of the experiments (1, 2, 3, and 4). Different letters among the treatments of different plant lines at diesel concentrations in an experiment indicate means that are significantly different from each other (LSD test, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The average number of leaves at the beginning of each experiment was 2. The average number of leaves of <span class="html-italic">Petunia grandiflora</span> shoot cuttings of lines 1, 2, 3, and 4 [subfigures (<b>a</b>–<b>d</b>), respectively], controls C-G and C-R in the four subfigures was determined after 5 weeks of growth under glasshouse conditions. Values represent means ± SEM of three replicates in each of the experiments (1, 2, 3, and 4). Different letters among the treatments of different plant lines at diesel concentrations in an experiment indicate means that are significantly different from each other (LSD test, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Visual chlorosis rating scores of <span class="html-italic">Petunia grandiflora</span> shoot cuttings of lines 1, 2, 3, and 4 [subfigures (<b>a</b>–<b>d</b>), respectively], and controls C-G and C-R in the four subfigures were determined after 5 weeks of growth under glasshouse conditions. Values represent means ± SEM of three replicates in each of the experiments (1, 2, 3, and 4). Different letters among the treatments of different plant lines at diesel concentrations in an experiment indicate means that are significantly different from each other (LSD test, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The shoot height of <span class="html-italic">Petunia grandiflora</span> shoot cuttings from lines 1, 2, 3, and 4 [subfigures (<b>a</b>–<b>d</b>), respectively], as well as controls C-G and C-R in the four subfigures was measured after 5 weeks of growth under glasshouse conditions. The average shoot height at the beginning of each experiment was 7 cm. Values represent means ± SEM of three replicates in each of the experiments (1, 2, 3, and 4). Different letters among the treatments of different plant lines at diesel concentrations in an experiment indicate means that are significantly different from each other (LSD test, <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Root length [subfigure (<b>a</b>)] and the number of roots [subfigure (<b>b</b>)] of <span class="html-italic">Petunia grandiflora</span> shoot cuttings from line 4, C-G, and C-R were measured after 5 weeks of growth under glasshouse conditions. Values represent means ± SEM of three replicates in experiment 4. Different letters among the treatments of different plant lines at diesel concentrations indicate means that are significantly different from each other (LSD test, <span class="html-italic">p</span> &lt; 0.05).</p>
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16 pages, 1281 KiB  
Article
Carbon and Nitrogen Stocks in Vineyard Soils Amended with Grape Pomace Residues
by Allan Augusto Kokkonen, Samuel Schemmer, Rian Brondani, João Francisco Fornari, Daniéle Gonçalves Papalia, Elena Baldi, Moreno Toselli, Jean Michel Moura-Bueno, Arcângelo Loss, Tadeu Luis Tiecher and Gustavo Brunetto
Agronomy 2024, 14(9), 2055; https://doi.org/10.3390/agronomy14092055 - 8 Sep 2024
Viewed by 559
Abstract
Fruit crops under soil conservational management might sequester carbon (C) in soils and mitigate greenhouse gases emissions. Using grape pomace residues as soil amendment holds promise for sustainable viticulture. However, its actual capability to increase soil organic carbon (SOC) and nitrogen (N) is [...] Read more.
Fruit crops under soil conservational management might sequester carbon (C) in soils and mitigate greenhouse gases emissions. Using grape pomace residues as soil amendment holds promise for sustainable viticulture. However, its actual capability to increase soil organic carbon (SOC) and nitrogen (N) is unknown, especially in subtropical climates. This research aims to investigate whether grape pomace compost and vermicompost can increase SOC, total N (TN), and C and N stocks in subtropical vineyards. Two vineyards located in Veranópolis, in South Brazil, one cultivated with ‘Isabella’ and the other with ‘Chardonnay’ varieties, were annually amended with these residues for three years. We quantified SOC and TN in each condition in different soil layers, as well as C and N content in two different granulometric fractions: mineral-associated organic matter (MAOM) and particulate organic matter (POM). C and N stocks were also calculated. Despite potential benefits, neither treatment enhanced SOC, its fractions, or C stocks. In fact, vermicompost was rapidly mineralized and depleted SOC and its fractions in the 0.0 to 0.05 m layers of the ‘Isabella’ vineyard. Our findings indicate that the tested grape pomace residues were unable to promote C sequestration in subtropical vineyards after a three-year period. Full article
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<p>Accumulated monthly rainfall (mm), shown in bars, and monthly mean temperatures (°C), shown in lines, from January 2020 to February 2023, obtained from an automatic meteorological station (National Institute of Meteorology conventional station) located 150 m from the vineyards.</p>
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<p>C stocks on 0.0–0.05 m, 0.05–0.10 m, 0.10–0.20 m, and 0.20–0.40 m soil layers, in Vineyard 1 (‘Isabella’) (<b>a</b>) and Vineyard 2 (‘Chardonnay’) (<b>b</b>), after three years of the following treatment applications: C—control (no organic fertilization), VC—fertilization with grape pomace vermicompost, and CO—fertilization with grape pomace compost. Darker colors indicate the MAOC fraction and the lighter colors indicate the POC fraction. <span class="html-italic">p</span>-values of ANOVA test are shown and different letters indicate different means among treatments (Tukey test, α = 5%).</p>
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<p>N stocks on 0.0–0.05 m, 0.05–0.10 m, 0.10–0.20 m, and 0.20–0.40 m soil layers, in Vineyard 1 (‘Isabella’) (<b>a</b>) and Vineyard 2 (‘Chardonnay’) (<b>b</b>), after three years of the following treatment applications: C—control (no organic fertilization), VC—fertilization with grape pomace vermicompost, and CO—fertilization with grape pomace compost. Darker colors indicate the MAN fraction and the lighter colors indicate the PN fraction. <span class="html-italic">p</span>-values of ANOVA test are shown and different letters indicate different means among treatments (Tukey test, α = 5%).</p>
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32 pages, 6285 KiB  
Article
Unveiling Iso- and Aniso-Hydric Disparities in Grapevine—A Reanalysis by Transcriptome Portrayal Machine Learning
by Tomas Konecny, Armine Asatryan, Maria Nikoghosyan and Hans Binder
Plants 2024, 13(17), 2501; https://doi.org/10.3390/plants13172501 - 6 Sep 2024
Viewed by 364
Abstract
Mechanisms underlying grapevine responses to water(-deficient) stress (WS) are crucial for viticulture amid escalating climate change challenges. Reanalysis of previous transcriptome data uncovered disparities among isohydric and anisohydric grapevine cultivars in managing water scarcity. By using a self-organizing map (SOM) transcriptome portrayal, we [...] Read more.
Mechanisms underlying grapevine responses to water(-deficient) stress (WS) are crucial for viticulture amid escalating climate change challenges. Reanalysis of previous transcriptome data uncovered disparities among isohydric and anisohydric grapevine cultivars in managing water scarcity. By using a self-organizing map (SOM) transcriptome portrayal, we elucidate specific gene expression trajectories, shedding light on the dynamic interplay of transcriptional programs as stress duration progresses. Functional annotation reveals key pathways involved in drought response, pinpointing potential targets for enhancing drought resilience in grapevine cultivation. Our results indicate distinct gene expression responses, with the isohydric cultivar favoring plant growth and possibly stilbenoid synthesis, while the anisohydric cultivar engages more in stress response and water management mechanisms. Notably, prolonged WS leads to converging stress responses in both cultivars, particularly through the activation of chaperones for stress mitigation. These findings underscore the importance of understanding cultivar-specific WS responses to develop sustainable viticultural strategies in the face of changing climate. Full article
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Graphical abstract
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<p>Transcriptome portrayal of the WS experiment reveals distinct trajectories for isohydric (MP) and anisohydric (SG) cultivars. (<b>A</b>) SOM transcriptome portraits of all samples studied. (<b>B</b>) The pairwise correlation map of the SOM portraits indicates two distinct clusters for the two cultivars, correlation squares along the diagonal due to the replicates, and off-diagonal correlations between different time points and stress-induced effects in both cultivars (see arrows). (<b>C</b>) The independent component plot of the portraits shows linear trajectories along the IC2 axis of both cultivars. IC1, IC2, and IC3 denote the first three independent components. (<b>D</b>) Sample SOM represents a two-dimensional presentation of the trajectories: Transcriptome trajectories separate due to isohydric and anisohydric cultivars in the horizontal direction and develop with time vertically with an additional increment due to WS. Dots inside each “Sample SOM” represent samples. The color code of samples is indicated in the bottom right corner.</p>
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<p>Transcriptome dynamics under WS in isohydric (MP) and anisohydric (SG) water management. (<b>A</b>) The regions of characteristic overexpression as red areas labeled A–F (see “Overexpression map”) agree with regions of highest expression variance (see “Variance map”). (<b>B</b>) Spots usually contain a few hundred genes of different functional contexts (left). Expression profiles of the spots across all conditions reveal characteristic courses of transcriptomic co-regulation (right). (<b>C</b>) Transcriptome dynamics under WS is characterized by waterline portraits revealing different stress trajectories for SG and MP (gray arrows), time, as well as by spot activation patterns (spots jointly activated in the portraits are connected by lines at the time points indicated). The number of jointly expressed spots increases under WS, thus indicating a more complex transcriptomic pattern compared to the controls (see text).</p>
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<p>Topology of expression trajectories under WS. (<b>A</b>) The stress trajectories in the three-dimensional expression landscape. (<b>B</b>) Schematic spot activation along the T1-T2-T3 trajectory. (<b>C</b>) Gene ontology enrichment in spots A–F (biological processes in green, molecular functions in pink text).</p>
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<p>Stilbenoid, diarylheptanoid, and gingerol biosynthetic pathway. (<b>A</b>) Genes of the pathway (downstream flow visualized by black arrows) are along the two STRS trajectories (gray arrows), indicating their condition-specific activation. (<b>B</b>) The heatmap shows the expression changes in response to WS. (<b>C</b>) KEGG pathway with gene color code derived from their positions in the SOM portrait indicated by the colored waterline portraits of SG CTRL and STRS and MP CTRL and STRS (see the lower right part).</p>
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<p>Thiamine biosynthetic pathway. (<b>A</b>) Map of the pathway (downstream flow visualized by black arrows). Genes accumulate in areas related to stress response, and the two STRS trajectories are shown by gray arrows. (<b>B</b>) Heatmap depicting the thiamine biosynthetic pathway gene expression in response to WS. (<b>C</b>) KEGG pathway with gene color code derived from their positions in the SOM portrait indicated by the colored waterline portraits of SG CTRL and STRS and MP CTRL and STRS (see the upper right part).</p>
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<p>Covariance and population structure of the SOM expression landscape. (<b>A</b>) The 5947 genes significantly modulated in leaves under our experimental conditions were taken from the SAM analysis in [<a href="#B15-plants-13-02501" class="html-bibr">15</a>] and mapped into our SOM. Occupied metagenes (pixels) are marked in greyish. They refer mostly to metagenes of high and moderate variance of gene expression (see part C). (<b>B</b>) The covariance structure of the SOM was estimated by calculating a weighted topological overlap (WTO) network between the spot modules [<a href="#B65-plants-13-02501" class="html-bibr">65</a>]. It reveals strong anticorrelations (w &lt; 0) between the two cultivars (SG vs. MP) and between the two conditions (STRS vs. CTRL; see the scheme on the right). It thus assigns the “modulated genes” (part A) to up- and downregulation under the different conditions. Note also that the SOM decomposes the “modulated genes” into clusters of co-regulated genes called spot modules. (<b>C</b>) The variance map of the metagenes reveals a variance gradient of gene expression from the center of the SOM (blue) towards its edges (brown). The population map color codes the number of genes per metagene from high (red) to low (blue). The gene density changes across the SOM. Also, the Euclidean distances between neighboring metagenes are variant and “amplify” regions of increased gene density. The K-means map provides a space-filling segmentation of the SOM, enabling it to consider any region for downstream analysis, such as function mining.</p>
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<p>Genes specifically modulated in the accessions were taken from supporting data [<a href="#B15-plants-13-02501" class="html-bibr">15</a>] and compared to the respective waterline portraits. Genes modulated in SG and MP accumulate in the overexpressed areas in SG and MP, respectively.</p>
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<p>Genes modulated specifically under stress conditions. The cutoffs defining upregulated (UP in STRS/CTRL) and downregulated (DOWN in STRS/CTRL) genes were taken from [<a href="#B15-plants-13-02501" class="html-bibr">15</a>] (fold change &gt; 2 and top 20% variant genes) and mapped into the SOM. Clusters of genes accumulate in different areas of the SOM in and near the spots. The respective profiles are shown on the right, together with the respective biological functions. As expected, the profiles confirm the UP/DOWN under STRS conditions, showing the respective changes, especially under lasting stress at T3. The profiles also show that the expression changes are about one order of magnitude smaller compared with that observed in the spots. The bars are color-coded as in the other figures.</p>
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<p>Genes specifically modulated under recovery from WS. Recovery conditions were achieved by re-watering the plants 46 days after the onset of WS, and the post-recovery plant material was collected 70 days after the onset of WS (see Materials and Methods in [<a href="#B15-plants-13-02501" class="html-bibr">15</a>]). Upregulated (UP) and downregulated (DOWN) genes and their respective profiles are shown separately. The profiles refer to the stress experiment. Recovery virtually reverses expression changes observed for lasting stress (STRS at T3).</p>
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21 pages, 19720 KiB  
Article
Structural and Phylogenetic In Silico Characterization of Vitis vinifera PRR Protein as Potential Target for Plasmopara viticola Infection
by Sofía M. Martínez-Navarro, Xavier de Iceta Soler, Mónica Martínez-Martínez, Manuel Olazábal-Morán, Paloma Santos-Moriano and Sara Gómez
Int. J. Mol. Sci. 2024, 25(17), 9553; https://doi.org/10.3390/ijms25179553 - 3 Sep 2024
Viewed by 336
Abstract
Fungi infection, especially derived from Plasmopara viticola, causes severe grapevine economic losses worldwide. Despite the availability of chemical treatments, looking for eco-friendly ways to control Vitis vinifera infection is gaining much more attention. When a plant is infected, multiple disease-control molecular mechanisms [...] Read more.
Fungi infection, especially derived from Plasmopara viticola, causes severe grapevine economic losses worldwide. Despite the availability of chemical treatments, looking for eco-friendly ways to control Vitis vinifera infection is gaining much more attention. When a plant is infected, multiple disease-control molecular mechanisms are activated. PRRs (Pattern Recognition Receptors) and particularly RLKs (receptor-like kinases) take part in the first barrier of the immune system, and, as a consequence, the kinase signaling cascade is activated, resulting in an immune response. In this context, discovering new lectin-RLK (LecRLK) membrane-bounded proteins has emerged as a promising strategy. The genome-wide localization of potential LecRLKs involved in disease defense was reported in two grapevine varieties of great economic impact: Chardonnay and Pinot Noir. A total of 23 potential amino acid sequences were identified, exhibiting high-sequence homology and evolution related to tandem events. Based on the domain architecture, a carbohydrate specificity ligand assay was conducted with docking, revealing two sequences as candidates for specific Vitis vinifera–Plasmopara viticola host–pathogen interaction. This study confers a starting point for designing new effective antifungal treatments directed at LecRLK targets in Vitis vinifera. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>Chromosomal distribution of LecRLK genes in the genome of <span class="html-italic">Vitis vinifera</span> Chardonnay variety. (<b>A</b>) Chromosomal location of proposed LecRLK genes in the <span class="html-italic">Vitis vinifera</span> genome obtained with MG2C [<a href="#B23-ijms-25-09553" class="html-bibr">23</a>]. (<b>B</b>) Phylogenetic tree obtained with ClustalW, and exon–intron distribution of LecRLK genes performed with gene structure display server. Legend: Yellow boxes represent CDS sequence, blue boxes represent UTR sequence, and black lines represent introns [<a href="#B24-ijms-25-09553" class="html-bibr">24</a>,<a href="#B25-ijms-25-09553" class="html-bibr">25</a>]. (<b>C</b>) Amino acid length distribution of LecRLKs in Chardonnay variety.</p>
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<p>Chromosomal distribution of LecRLK genes in the genome of <span class="html-italic">Vitis vinifera</span> Pinot Noir variety. (<b>A</b>) Chromosomal location of proposed LecRLK genes in the <span class="html-italic">Vitis vinifera</span> genome obtained with MG2C [<a href="#B23-ijms-25-09553" class="html-bibr">23</a>]. (<b>B</b>) Phylogenetic tree obtained with ClustalW, and exon–intron distribution of LecRLK genes performed with gene structure display server. Legend: Yellow boxes represent CDS sequence, blue boxes represent UTR sequence, and black lines represent introns [<a href="#B24-ijms-25-09553" class="html-bibr">24</a>,<a href="#B25-ijms-25-09553" class="html-bibr">25</a>]. (<b>C</b>) Amino acid length distribution of LecRLKs in Pinot Noir variety.</p>
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<p>Domain architecture of LecRLKs from <span class="html-italic">Vitis vinifera</span>. (<b>A</b>) Chardonnay proteins and (<b>B</b>) Pinot Noir proteins. SP (light cyan color): signal peptide; TM (red color): transmembrane domain; Lectin (green color): legume lectin domain (Pfam 00139); and kinase (light yellow color): kinase domain (Pfam IPR011009). Created with DOG 2.0 software [<a href="#B26-ijms-25-09553" class="html-bibr">26</a>].</p>
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<p>Multiple sequence alignment of LecRLK legume lectin domain sequences obtained with ClustalW and colored as Clustal codes. Predicted secondary structure of O80939 UniProt code protein was obtained with Jprep for comparison, and consensus logo sequence is shown at the bottom. β-strands (numbered β1–β13) are displayed as green arrows and the α-helix as red regions. Loops A–D are included in secondary structure. Essential amino acids involved in carbohydrate recognition are highlighted with an asterisk. (<b>A</b>) Chardonnay variety; (<b>B</b>) Pinot Noir variety [<a href="#B25-ijms-25-09553" class="html-bibr">25</a>,<a href="#B29-ijms-25-09553" class="html-bibr">29</a>,<a href="#B30-ijms-25-09553" class="html-bibr">30</a>].</p>
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<p>Multiple sequence alignment of LecRLK legume lectin domain sequences obtained with ClustalW and colored as Clustal codes. Predicted secondary structure of O80939 UniProt code protein was obtained with Jprep for comparison, and consensus logo sequence is shown at the bottom. β-strands (numbered β1–β13) are displayed as green arrows and the α-helix as red regions. Loops A–D are included in secondary structure. Essential amino acids involved in carbohydrate recognition are highlighted with an asterisk. (<b>A</b>) Chardonnay variety; (<b>B</b>) Pinot Noir variety [<a href="#B25-ijms-25-09553" class="html-bibr">25</a>,<a href="#B29-ijms-25-09553" class="html-bibr">29</a>,<a href="#B30-ijms-25-09553" class="html-bibr">30</a>].</p>
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<p>Multiple sequence alignment of LecRLK domain sequences obtained with ClustalW and colored as Clustal codes. Predicted secondary structure of Q96285 UniProt code protein was obtained with Jprep for comparison, and consensus logo sequence is shown at the bottom. β-strands are displayed as green arrows and the α-helix as red regions. Essential amino acids involved in catalytic activity are highlighted with an asterisk. (<b>A</b>) Chardonnay variety; (<b>B</b>) Pinot Noir variety [<a href="#B25-ijms-25-09553" class="html-bibr">25</a>,<a href="#B29-ijms-25-09553" class="html-bibr">29</a>,<a href="#B30-ijms-25-09553" class="html-bibr">30</a>].</p>
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<p>Multiple sequence alignment of LecRLK domain sequences obtained with ClustalW and colored as Clustal codes. Predicted secondary structure of Q96285 UniProt code protein was obtained with Jprep for comparison, and consensus logo sequence is shown at the bottom. β-strands are displayed as green arrows and the α-helix as red regions. Essential amino acids involved in catalytic activity are highlighted with an asterisk. (<b>A</b>) Chardonnay variety; (<b>B</b>) Pinot Noir variety [<a href="#B25-ijms-25-09553" class="html-bibr">25</a>,<a href="#B29-ijms-25-09553" class="html-bibr">29</a>,<a href="#B30-ijms-25-09553" class="html-bibr">30</a>].</p>
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<p>Cartoon representation of LecRLKs modeled with Phyre2 and represented by Pymol. Amino acids implicated in carbohydrate stability are shown as sticks, and GalNAc ligands are shown as green sticks. (<b>A</b>) A0A438E3M7; (<b>B</b>) A0A438J290; (<b>C</b>) F6CH85; (<b>D</b>) F6CH87 [<a href="#B47-ijms-25-09553" class="html-bibr">47</a>].</p>
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<p>Surface electrostatic potential calculated by PyMOL. A positive charge is shown in blue, and a negative charge is shown in red. (<b>A</b>) A0A438E3M7; (<b>B</b>) A0A438J290; (<b>C</b>) F6CH85; (<b>D</b>) F6CH87. GalNAc ligands are represented by green sticks [<a href="#B47-ijms-25-09553" class="html-bibr">47</a>].</p>
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22 pages, 2666 KiB  
Review
Future Agricultural Water Availability in Mediterranean Countries under Climate Change: A Systematic Review
by André M. Claro, André Fonseca, Helder Fraga and João A. Santos
Water 2024, 16(17), 2484; https://doi.org/10.3390/w16172484 - 1 Sep 2024
Viewed by 1219
Abstract
Warming and drying trends in the Mediterranean Basin exacerbate regional water scarcity and threaten agricultural production, putting global food security at risk. This study aimed to review the most significant research on future water availability for the Mediterranean agricultural sector under climate change [...] Read more.
Warming and drying trends in the Mediterranean Basin exacerbate regional water scarcity and threaten agricultural production, putting global food security at risk. This study aimed to review the most significant research on future water availability for the Mediterranean agricultural sector under climate change (CC) scenarios published during 2009–2024. Two searches were performed in the Scopus and Web of Science databases, to which previously identified significant studies from different periods were also added. By applying a methodology duly protocoled in the PRISMA2020-based guideline, a final number of 44 particularly relevant studies was selected for review. A bibliometric analysis has shown that most of the published research was focused on Southwestern European countries (i.e., Spain, Italy, Portugal) and grapevine and olive tree crops. Overall, the reviewed studies state that future Mediterranean water reserves may not meet agricultural water demands, due to reduced reservoir inflows and higher irrigation demands under future CC and socioeconomic scenarios. Regarding adaptation measures to improve water-use management in agriculture, the majority of the reviewed studies indicate that the use of integrated modelling platforms and decision–support systems can significantly contribute to the development and implementation of improved water/land-management practices. Full article
(This article belongs to the Section Water, Agriculture and Aquaculture)
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<p>PRISMA 2020 flow diagram of the methodology used to select the most adequate reports for review, retrieved from the Scopus and Web of Science (WoS) web databases.</p>
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<p>Word count of the name of each Mediterranean country, and all its derivatives, appearing in the title/keywords of the records identified in the first search.</p>
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<p>Word count of all the crop-related (C), agricultural practices-related (A), water-related (W), temperature and aridity-related (TA), meteorology and climate-related (MC), methodology and modeling-related (MM) and management-related (M) words appearing in the records’ title/keywords, as well as the percentage share of each of those word categories.</p>
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<p>Main title/keywords identified in the agricultural practices-related (A), water-related (W), temperature and aridity-related (TA), methodology and modelling-related (MM) and management-related (M) words categories.</p>
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<p>Main title/keywords identified in the crop-related (C) words category, and their word count.</p>
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15 pages, 3547 KiB  
Article
Assessing the Potential of Tortistilus (Hemiptera: Membracidae) from Northern California Vineyards as Vector Candidates of Grapevine Red Blotch Virus
by Victoria J. Hoyle, Elliot J. McGinnity Schneider, Heather L. McLane, Anna O. Wunsch, Hannah G. Fendell-Hummel, Monica L. Cooper and Marc F. Fuchs
Insects 2024, 15(9), 664; https://doi.org/10.3390/insects15090664 - 31 Aug 2024
Viewed by 455
Abstract
Ceresini treehoppers are present in northern California vineyard ecosystems, including the closely related Spissistilus and Tortistilus (Hemiptera: Membracidae). These membracids are not direct pests of wine grapes, but S. festinus is a vector of grapevine red blotch virus (GRBV). No information is available [...] Read more.
Ceresini treehoppers are present in northern California vineyard ecosystems, including the closely related Spissistilus and Tortistilus (Hemiptera: Membracidae). These membracids are not direct pests of wine grapes, but S. festinus is a vector of grapevine red blotch virus (GRBV). No information is available on the ability of Tortistilus spp. to transmit GRBV. In this study, Tortistilus were collected on yellow panel cards across 102 vineyard sites and surrounding areas in Napa Valley, California, USA in 2021–2023. Specimens were morphotyped, sexed and tested for GRBV ingestion and acquisition by multiplex PCR or qPCR. Phylogenetic analysis of the partial sequence of mt-COI and ITS gene fragments of a subset of 40 Tortistilus specimens revealed clustering in a monophyletic clade with T. wickhami with the former barcode sequence. Only 6% (48/758) of the T. wickhami tested positive for GRBV, but none of the heads with salivary glands (0%, 0/50) of the dissected specimens tested positive for GRBV, indicating no virus acquisition. In contrast, half of the dissected heads with salivary glands of S. festinus (52%, 12/23), from the same collection vineyard sites, tested positive for GRBV. Together, our findings confirmed the presence of T. wickhami in northern California vineyards and suggested a dubious role of this treehopper as a vector of GRBV. Full article
(This article belongs to the Section Insect Pest and Vector Management)
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<p>Depiction of a <span class="html-italic">Tortistilus wickhami</span> (<b>A</b>) and a <span class="html-italic">Spissistilus festinus</span> (<b>B</b>) with a differential morphological shape. Note the pronotum rising vertically above the head with lateral ridges joining over the thorax for <span class="html-italic">T. wickhami</span>, compared with the pronotum gradually curving backwards for <span class="html-italic">S. festinus.</span></p>
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<p>Location of the 102 vineyard sites selected for this study in Napa Valley, California, USA, depicting the abundance of <span class="html-italic">Tortistilus</span> and the presence of grapevine red blotch virus (GRBV) in specimens collected, as shown by PCR. Positive (+) indicates only GRBV positive specimens; Mix (-/+) indicates a combination of GRBV positive and negative specimens; and Negative (-) indicates only GRBV negative specimens at each of the 102 vineyard sites.</p>
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<p>The cumulative distribution of <span class="html-italic">Tortistilus</span> collected by sex, in northern California vineyards, over three growing seasons (June to November in 2021 and March to November in 2022 and 2023).</p>
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<p>A side angle view of 24 <span class="html-italic">Tortistilus wickhami</span> specimens collected in northern California vineyards obtained under a SZX16 stereoscope (Olympus, Center Valley, PA, USA). Photographs were captured using the cellSense Standard software (version 1.18).</p>
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<p>A dorsal view of the same 24 <span class="html-italic">Tortistilus wickhami</span> specimens shown in <a href="#insects-15-00664-f004" class="html-fig">Figure 4</a> obtained under a SZX16 stereoscope (Olympus, Center Valley, PA, USA). Photographs were captured using the cellSense Standard software (version 1.18).</p>
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<p>A face view of the same 24 <span class="html-italic">Tortistilus wickhami</span> specimens shown in <a href="#insects-15-00664-f004" class="html-fig">Figure 4</a> obtained under a SZX16 stereoscope (Olympus, Center Valley, PA, USA). Photographs were captured using the cellSense Standard software (version 1.18).</p>
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<p>Phylogeny of partial mitochondrial cytochrome C oxidase I (mt-COI) sequences from <span class="html-italic">Tortistilus</span> populations collected from various sites and years in northern California vineyards produced by the Maximum Likelihood analysis with 1000 bootstrap replicates. Sequences derived from specimens collected in this study are listed without accession numbers and correspond to the information in <a href="#insects-15-00664-t001" class="html-table">Table 1</a>, while the remaining sequences were retrieved from GenBank.</p>
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<p>Phylogenetic analysis of partial internal transcribed spacer 2 (ITS2) sequences from <span class="html-italic">Tortistilus</span> populations collected from various sites and years in northern California vineyards produced by Maximum Likelihood analysis with 1000 bootstrap replicates. <span class="html-italic">Tortistilus</span> sequences are derived from specimens listed in <a href="#insects-15-00664-t001" class="html-table">Table 1</a>. Additional sequences are from Ceresini treehoppers sourced from New York or retrieved from GenBank.</p>
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<p>Diagnostic polymerase chain reaction for DNA-sequence-based identification of <span class="html-italic">Spissistilus festinus</span> (lanes 1–3, 496 bp) and <span class="html-italic">Tortistilus wickhami</span> (lanes 4–6, 314 bp) specimens from northern California using <span class="html-italic">S. festinus</span> TCAHcoiWestF and TCAHcoiWestR primers (<b>A</b>) or <span class="html-italic">T. wickhami</span> TWICKcoiF and TWICKcoiR primers (<b>B</b>). Lane 6 is a water control.</p>
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16 pages, 4582 KiB  
Article
Strategies to Increase the Phosphorus Content in the Soil Profile of Vineyards Grown in Subtropical Climates
by Adriele Tassinari, Lincon Stefanello, Jean Michel Moura-Bueno, Gustavo Nogara de Siqueira, Guilherme Zanon Peripolli, Bianca Goularte Dias, Douglas Luiz Grando, William Natale, Carlos Alberto Ceretta and Gustavo Brunetto
Plants 2024, 13(17), 2434; https://doi.org/10.3390/plants13172434 - 31 Aug 2024
Viewed by 403
Abstract
Phosphate fertilizers are applied to the soil surface, especially in vineyards in production in subtropical regions. Nowadays, phosphorus (P) is not incorporated into the soil to avoid mechanical damage to the root system in orchards. However, over the years, successive surface P applications [...] Read more.
Phosphate fertilizers are applied to the soil surface, especially in vineyards in production in subtropical regions. Nowadays, phosphorus (P) is not incorporated into the soil to avoid mechanical damage to the root system in orchards. However, over the years, successive surface P applications can increase the P content only in the topsoil, maintaining low P levels in the subsurface, which can reduce its use by grapevines. For this reason, there is a need to propose strategies to increase the P content in the soil profile of established orchards. The study aimed to evaluate the effect of management strategies to (i) increase the P content in the soil profile; (ii) enhance the grape production; and (iii) maintain the grape must composition. An experiment on the ‘Pinot Noir’ grape in full production was carried out over three crop seasons. The treatments were without P application (C), P on the soil surface without incorporation (SP), P incorporated at 20 cm (IP20), P incorporated at 40 cm (IP40), and twice the P dose incorporated at 40 cm (2IP40). The P concentration in leaves at flowering and veraison, P content in the soil, grape production and its components, and chemical parameters of the grape must (total soluble solids, total polyphenols, total titratable acidity, total anthocyanins, and pH) were evaluated. The P concentration in leaves did not differ among the P application modes. The application of P associated with soil mobilization, especially at 20 cm depth, increased grape production. The P application modes did not affect the values of the chemical parameters of the grape must except for the total anthocyanins, which had the highest values when the vines were subjected to 2IP40. Finally, the P application and incorporation into the soil profile was an efficient strategy for increasing the grape production in full production vineyards. Full article
(This article belongs to the Special Issue Soil Fertility, Plant Nutrition and Nutrient Management)
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Graphical abstract
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<p>Average temperature (°C) and accumulated monthly precipitation (mm) in the years corresponding to the 2018/19 (<b>a</b>), 2019/20 (<b>b</b>), and 2020/21 (<b>c</b>) crop seasons; and average temperature and accumulated monthly precipitation recorded over the previous 17 years in the region where the study was carried out, Santana do Livramento, southern Brazil (<b>d</b>). The dashed lines represent the average temperature and average precipitation recorded for the entire period.</p>
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<p>P concentrations in leaves at flowering (<b>a</b>) and at <span class="html-italic">veraison</span> (<b>b</b>) evaluated over three crop seasons of ‘Pinot Noir’ grapevines subjected to P application modes to a Typic Hapludalf soil in from southern Brazil. ns = non-significant difference by Tukey’s test (<span class="html-italic">p</span> &lt; 0.05). Without P application (C), P on the soil surface without incorporation (SP), P incorporated at 20 cm (IP20), P incorporated at 40 cm (IP40), and twice P dose incorporated at 40 cm (2IP40).</p>
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<p>Grape production per plant (<b>a</b>), number of clusters (<b>b</b>), average weight of clusters (<b>c</b>) and weight of 100 berries (<b>d</b>) evaluated over three crop seasons of ‘Pinot Noir’ grapevines subjected to P application modes in a Typic Hapludalf soil from southern Brazil. Lowercase letters compare the means of the treatments (P application modes) by Tukey’s test (<span class="html-italic">p</span> &lt; 0.05). ns = non-significant difference. Without P application (C), P on the soil surface without incorporation (SP), P incorporated at 20 cm (IP20), P incorporated at 40 cm (IP40), and twice P dose incorporated at 40 cm (2IP40).</p>
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<p>Total soluble solids (<b>a</b>), total anthocyanins (<b>b</b>), total polyphenols (<b>c</b>), pH (<b>d</b>), total titratable acidity (<b>e</b>), and P concentration in the grape must (<b>f</b>) evaluated over three crop seasons of ‘Pinot Noir’ grapevines subjected to P application modes in a Typic Hapludalf soil from southern Brazil. Lowercase letters compare the means of the treatments (modes of P application) using Tukey’s test (<span class="html-italic">p</span> &lt; 0.05). ns = non-significant difference. Without P application (C), P on the soil surface without incorporation (SP), P incorporated at 20 cm (IP20), P incorporated at 40 cm (IP40), and twice P dose incorporated at 40 cm (2IP40).</p>
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<p>P content in the soil extracted by Mehlich-1 in the 0–10, 10–20 and 20–40 cm layers, in a vineyard evaluated over three crop seasons subjected to P application modes to a Typic Hapludalf soil from southern Brazil. Capital letters compare the P content between soil layers using Tukey’s test (<span class="html-italic">p</span> &lt; 0.05). ns = non-significant difference between treatments in the same soil layer. In the 2018/19 crop season, the P content in the 20–40 cm layer was not determined. Without P application (C), P on the soil surface without incorporation (SP), P incorporated at 20 cm (IP20), P incorporated at 40 cm (IP40), and twice P dose incorporated at 40 cm (2IP40).</p>
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<p>Proportion of variance explained by each source of variation for each response variable. The colors represent the source of variation (P application modes, crop seasons, blocks, residuals, and interaction between P application modes and crop seasons).</p>
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<p>Conditional inference tree showing the effect of P application modes and crop seasons on grape production (<b>a</b>): total soluble solids—TSS (<b>b</b>), total anthocyanins—TA (<b>c</b>), total titratable acidity—TTA (<b>d</b>) and pH of the grape must (<b>e</b>).</p>
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<p>Relation between principal component 1 (PC1) and principal component 2 (PC2), for P concentration in the soil and leaves, grape production and its components, grape must parameters and climatic variables evaluated over three crop seasons to P application modes in the soil. Without P application (C), P on the soil surface without incorporation (SP), P incorporated at 20 cm (IP20), P incorporated at 40 cm (IP40), and twice P dose incorporated at 40 cm (2IP40).</p>
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16 pages, 599 KiB  
Article
Effects of Apical, Late-Season Leaf Removal on Vine Performance and Wine Properties in Sangiovese Grapevines (Vitis vinifera L.)
by Alberto Vercesi, Mario Gabrielli, Alessandra Garavani and Stefano Poni
Horticulturae 2024, 10(9), 929; https://doi.org/10.3390/horticulturae10090929 - 30 Aug 2024
Viewed by 288
Abstract
An urgent challenge posed by climate change in warm grapevine-growing areas is accelerated ripening, which leads to rapid sugar accumulation while phenolics and aroma traits lag behind. Techniques that enable selectively delaying the sugar accumulation process without affecting the accumulation of secondary metabolites [...] Read more.
An urgent challenge posed by climate change in warm grapevine-growing areas is accelerated ripening, which leads to rapid sugar accumulation while phenolics and aroma traits lag behind. Techniques that enable selectively delaying the sugar accumulation process without affecting the accumulation of secondary metabolites are essential. This study aimed to evaluate the effects of apical-to-cluster defoliation, manually applied in 2019 at the onset of veraison (D1) or 20 days later (D2), which removed about 30–40% of the pending total leaf area without altering the cluster microclimate compared with a non-defoliated control (C). Ripening trends, vegetative growth, yield components, and the final grape and wine composition, as well as wine sensorial attributes, were assessed. Although both treatments significantly lowered the final leaf area-to-yield ratio (0.80–0.90 m2/kg) compared with the 1.35 m2/kg recorded in the C vines, only D1 reduced the final total soluble solids (TSS) at harvest (2 °Brix less than C). However, the total anthocyanins were similarly limited, and titratable acidity (TA) did not differ from the C vines. The D1 wine was deemed similar to that made from control plants. Conversely, D2 failed to delay ripening, yet the D2 wine was deemed superior in terms of olfactory intensity, body, fruitiness, balance, and overall preference. Although the study was conducted over a single season, the results are robust enough to conclude that the timing of defoliation—i.e., the level of TSS concurrently reached by the C treatment—is crucial to achieving specific effects. Early defoliation appears valid for postponing ripening into a cooler period, making it quite interesting in warm–hot areas with a very long growing season; a much later defoliation, likely due to the interaction between mean canopy age and more light filtering from above the cluster zone, can elevate the quality of and appreciation for the final wine. Full article
(This article belongs to the Topic Effects of Climate Change on Viticulture (Grape))
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<p>Seasonal variation in berry fresh mass (<b>A</b>), total soluble solids (TSS) (<b>B</b>), titratable acidity (<b>C</b>), and total anthocyanin concentration (<b>D</b>) recorded in 2019 from the onset of veraison until harvest in C, D<sub>1,</sub> and D<sub>2</sub> treatments. The two broken arrows indicate dates of leaf removal, whereas the solid arrow indicates the harvest date. Repeated measures analysis resulted in the following: for (<b>A</b>), between-subject (treatment) effects and time × treatment interaction were non-significant; in (<b>B</b>), treatment and time × treatment effects were significant at Pr &gt; F = 0.0001; in (<b>C</b>), treatment effect was significant at Pr &gt; F = 0.015 and time × treatment interaction was significant at Pr &gt; F = 0.0001; in (<b>D</b>), treatment effect was significant at Pr &gt; F = 0.0001 and time × treatment interaction was significant at Pr &gt; F = 0.023. Mean separation within single dates using lowercase letters was performed by SNK test at <span class="html-italic">p</span> = 0.05 level only when a significant time × treatment interaction was found (indicated with an asterisk). Within single dates, lack of separation implies ns.</p>
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<p>Aroma spider graph of the sensory characteristics of Sangiovese wines, obtained using 12 panelists with wines analyzed in triplicate. Black dots indicate significance at ● <span class="html-italic">p</span> &lt; 0.1, ●● <span class="html-italic">p</span> &lt; 0.05.</p>
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20 pages, 6126 KiB  
Article
Combined Metabolome and Transcriptome Analysis Revealed the Accumulation of Anthocyanins in Grape Berry (Vitis vinifera L.) under High-Temperature Stress
by Feifei Dou, Fesobi Olumide Phillip and Huaifeng Liu
Plants 2024, 13(17), 2394; https://doi.org/10.3390/plants13172394 - 27 Aug 2024
Viewed by 377
Abstract
In grape (Vitis vinifera L.) cultivation, high temperatures (HTs) usually reduce the accumulation of anthocyanins. In order to elucidate the regulatory mechanism of anthocyanin biosynthesis under high-temperature environments, we investigated the effects of HT stress at veraison (5% coloring of grape ears) [...] Read more.
In grape (Vitis vinifera L.) cultivation, high temperatures (HTs) usually reduce the accumulation of anthocyanins. In order to elucidate the regulatory mechanism of anthocyanin biosynthesis under high-temperature environments, we investigated the effects of HT stress at veraison (5% coloring of grape ears) on fruit coloration and anthocyanin biosynthesis in ‘Summer Black’ (XH) and ‘Flame seedless’ (FL) grapevines. Compared to the control group (35 °C), the total anthocyanin content of XH and FL grapes subjected to a high-temperature (HT) treatment group (40 °C) decreased significantly as the HT treatment continued, but showed an upward trend with fruit development. However, the concentration of procyanidins increased significantly following HT treatment but decreased with fruit development. Nonetheless, FL grapes showed some resistance to the HT condition, producing anthocyanin content at ripeness comparable to the control group, demonstrating a greater adaptability to HT conditions than XH grapes. Based on the CIRG index, at stage S4, the fruit of FL was classified as dark red, while XH was classified as blue-black in the control group. Anthocyanin-targeted metabonomics identified eight different types of anthocyanins accumulating in the peels of XH and FL grapes during ripening, including cyanidins, delphinidins, malvidins, pelargonidins, peonidins, petunidins, procyanidins, and flavonoids. Malvidins were the most abundant in the two grape varieties, with malvidin-3-O-glucoside being more sensitive to high temperatures. HT treatment also down-regulated the expression of structural genes and regulators involved in the anthocyanin synthesis pathways. We used the WGCNA method to identify two modules that were significantly correlated with total anthocyanin and procyanidin contents. Among them, MYBCS1, bHLH137, WRKY65, WRKY75, MYB113-like, bZIP44, and GST3 were predicted to be involved in grape anthocyanin biosynthesis. In conclusion, this study conducted in-depth research on the HT inhibition of the biosynthesis of anthocyanins in XH and FL grapes, for reference. Full article
(This article belongs to the Section Plant Physiology and Metabolism)
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<p>(<b>A</b>) Temperature changes during fruit development from June to August 2020. (<b>B</b>) Average temperature (°C) of high-temperature (HT) and control treatments (C). DHT: daily average temperature of high-temperature treatment; NHT: night average temperature of high-temperature treatment; DC: daily average temperature of control treatment; NC: night average temperature of control treatment.</p>
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<p>High-temperature treatment affected the color phenotype of XH and FL grape berries. The appearance (<b>A</b>) of grape berries, and CIRG of XH (<b>B</b>) and FL (<b>C</b>) grapes, total anthocyanin contents of XH (<b>D</b>) and FL (<b>E</b>) grape, and procyanidin contents of XH (<b>F</b>) and FL (<b>G</b>) grape. FW: fresh weight. S1, S2, S3, and S4 represent 0, 10, 20, 30, and 40 days after 5% coloration of whole panicle, respectively. Values stand for means ± standard deviation (SD) of three independent biological replicates. The vertical bars indicate the SDs. Statistical significance was measured using Student’s <span class="html-italic">t</span>-test (*: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01). This is the same in the following.</p>
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<p>Targeted metabolomic analysis of XH and FL grape peels after HT treatment. (<b>A</b>) PCA of metabolites from HT treatment of XH and FL. (<b>B</b>) Stacked bar chart of relative changes in metabolite content. Statistical significance was measured using Student’s <span class="html-italic">t</span>-test (*: <span class="html-italic">p</span> &lt; 0.05). The <span class="html-italic">x</span>-axis and <span class="html-italic">y</span>-axis represent different treatments and anthocyanin contents, respectively. (<b>C</b>) KEGG pathway enrichment analysis of different metabolites. (<b>D</b>) The cluster heat map of anthocyanins in XH grape peels under HT treatments. (<b>E</b>) The cluster heat map of anthocyanins in FL grape peels under HT treatments. (<b>F</b>) The variable important in projection of OPLS-DA based on the anthocyanins detected in XH. (<b>G</b>) The variable important in projection of OPLS-DA based on the anthocyanins detected in FL. The blue column represents DAMs with VIP &gt; 1 and <span class="html-italic">p</span>-value &lt; 0.05, the pink column represents DAMs with VIP &lt; 1 and <span class="html-italic">p</span>-value &gt; 0.05.</p>
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<p>DEG analysis in XH and FL grape peels under HT treatment. (<b>A</b>) The quantity statistics of DEGs in different stages of XCK and XT. (<b>B</b>) The quantity statistics of DEGs in different stages of FCK and FT. (<b>C</b>) Venn diagram depicting the shared DEGs between XCK and XT. (<b>D</b>) Venn diagram depicting the shared DEGs between FCK and FT. (<b>E</b>) Venn diagram depicting the shared core and specific DEGs of XH grape among four color-transition periods. (<b>F</b>) Venn diagram depicting the shared core and specific DEGs of the XH grape among four color-transition periods. XCK1, XCK2, XCK3, and XCK4 represent the S1, S2, S3, and S4 of the XH grape in the control group, respectively; XT1, XT2, XT3, and XT4 represent the S1, S2, S3, and S4 of the XH grape in the HT treatment group, respectively; FCK1, FCK2, FCK3, and FCK4 represent the S1, S2, S3, and S4 of the FL grape in the control group, respectively; FT1, FT2, FT3, and FT4 represent the S1, S2, S3, and S4 of the FL grape in the HT treatment group, respectively. This is the same in the following.</p>
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<p>Analysis of transcription families in grape fruit under HT conditions. (<b>A</b>) Main differentially expressed transcription families. (<b>B</b>) Venn diagram shows the number of genes between XH and FL grapes. (<b>C</b>) KEGG analysis of shared genes in the two grapes. (<b>D</b>) The k-means clustering divided the DEGs profiles of XH and FL berries at different developmental stages into six clusters. The <span class="html-italic">x</span>-axis represents the four stages of fruit growth and development in grapes, while the <span class="html-italic">y</span>-axis represents the log2fc value of TF differential expression.</p>
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<p>Expression levels of structural DEGs and DAMs involved in anthocyanin biosynthesis pathways in XH and FL grapes after HT treatment. The white filled box represents DEGs, and the heatmap represents the expression level of DEGs of XH and FL. Red indicates a significant up-regulation of DEGs, while blue indicates a significant down-regulation of DEGs. The white filled ellipse represents the identified DAMs in the metabolome, and the bar graph represents the accumulation level of DAMs of XH and FL. PAL, phenylalanine ammonia lyase gene; C4H, trans-cinnamate 4-monooxygenase gene; 4CL, 4-coumarate–CoA ligase gene; CHS, chalcone synthase gene; F3H, naringenin 3-dioxygenase gene; ANS, anthocyanidin synthase gene; BZ1, anthocyanidin 3-O-glucosyltransferase gene; F3′5′H, flavonoid 3′,5′-hydroxylase gene; F3′H, flavonoid 3′-monooxygenase gene; DFR, bifunctional dihydroflavonol 4-reductase/flavanone 4-reductase gene; CHI, chalcone isomerase gene; FLS, flavonol synthase gene; LAR, leucoanthocyanidin reductase gene; CCR, cinnamoyl-CoA reductase gene; CAD, cinnamyl-alcohol dehydrogenase gene.</p>
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<p>Co-expression network analysis of genes in modules at control temperature and HT treatment in two grape varieties. (<b>A</b>) Modules most associated with anthocyanins and procyanidin. The left panel shows 11 modules and the color scale on the right shows the correlation between −1 and 1. (<b>B</b>) Connectivity network between 26 key anthocyanin-related genes in the “blue” module. (<b>C</b>) Connectivity network between 31 key anthocyanin-related genes in the “turquoise” module. (<b>D</b>) Heatmap of 26 genes expression in the “blue” module. (<b>E</b>) Heatmap of 31 genes’ expression in the “turquoise” module. The values of the blue-to-red gradient bars indicate the log2-fold change relative to the control sample. XS1, XS2, XS3 and XS4 represent S1, S2, S3, and S4 of the XH grape, respectively. FS1, FS2, FS3 and FS4 represent S1, S2, S3, and S4 of the FL grape, respectively.</p>
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