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Keywords = Polygonum aviculare L.

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14 pages, 1605 KiB  
Article
Hydroethanolic Extract of Polygonum aviculare L. Mediates the Anti-Inflammatory Activity in RAW 264.7 Murine Macrophages Through Induction of Heme Oxygenase-1 and Inhibition of Inducible Nitric Oxide Synthase
by Chan Ho Jang, You Chul Chung, Ami Lee and Youn-Hwan Hwang
Plants 2024, 13(23), 3314; https://doi.org/10.3390/plants13233314 - 26 Nov 2024
Viewed by 828
Abstract
Polygonum aviculare L. (PAL), commonly known as knotgrass, has been utilized as a traditional folk medicine across Asian, African, Latin American and Middle Eastern countries to treat various inflammatory diseases, including arthritis and airway inflammation. Numerous medicinal herbs exert anti-inflammatory and antioxidative effects [...] Read more.
Polygonum aviculare L. (PAL), commonly known as knotgrass, has been utilized as a traditional folk medicine across Asian, African, Latin American and Middle Eastern countries to treat various inflammatory diseases, including arthritis and airway inflammation. Numerous medicinal herbs exert anti-inflammatory and antioxidative effects that are mediated through the activation of nuclear factor-erythroid 2-related factor 2 (Nrf2) and the inhibition of nuclear factor kappa B (NF-κB). However, the underlying molecular mechanisms linking the antioxidative and anti-inflammatory effects remain poorly understood. Heme oxygenase-1 (HO-1) is an antioxidant enzyme that catalyzes heme degradation, ultimately leading to the production of carbon monoxide (CO). Elevated levels of CO have been correlated with the decreased level of inducible nitric oxide synthase (iNOS). In this study, we examined whether HO-1 plays a key role in the relationship between the antioxidative and anti-inflammatory properties of PAL. The anti-inflammatory and antioxidative activities of PAL in an in vitro system were evaluated by determining NF-κB activity, antioxidant response element (ARE) activity, pro-inflammatory cytokine and protein levels, as well as antioxidant protein levels. To examine whether HO-1 inhibition interfered with the anti-inflammatory effect of PAL, we measured nitrite, reactive oxygen species, iNOS, and HO-1 levels in RAW 264.7 murine macrophages pre-treated with Tin protoporphyrin (SnPP, an HO-1 inhibitor). Our results demonstrated that PAL increased ARE activity and the Nrf2-regulated HO-1 level, exerting antioxidative activities in RAW 264.7 macrophages. Additionally, PAL reduced cyclooxygenase-2 (COX-2) and iNOS protein levels by inactivating NF-κB in lipopolysaccharide (LPS)-activated RAW 264.7 macrophages. Further investigation using the HO-1 inhibitor revealed that HO-1 inhibition promoted iNOS expression, subsequently elevating nitric oxide (NO) generation in LPS-activated RAW 264.7 macrophages treated with PAL compared to those in the macrophages without the HO-1 inhibitor. Overall, our findings suggest that HO-1 induction by PAL may exert anti-inflammatory effects through the reduction of the iNOS protein level. Hence, this study paves the way for further investigation to understand molecular mechanisms underlying the antioxidative and anti-inflammatory activities of medicinal herbs. Full article
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Graphical abstract

Graphical abstract
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<p>Inhibition of NF-κB activation by PAL hydroethanolic extract. Cell viability of PAL hydroethanolic extract in (<b>A</b>) NF-κB Luciferase Reporter-RAW 264.7 cells, and (<b>B</b>) RAW 264.7 macrophages was quantified using a CCK-8 assay. (<b>C</b>) Concentration-dependent inhibition of NF-κB luciferase activity by PAL hydroethanolic extract in LPS-activated NF-κB Luciferase Reporter-RAW 264.7 cells. (<b>D</b>) Expression level of nuclear NF-κB in LPS-activated RAW 264.7 macrophages were quantitatively analyzed. Data are presented as mean  ±  standard error of the mean (SEM) from three independent experiments (<span class="html-italic">N</span>  =  3). A statistical significance compared with LPS alone treatment at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 was marked by an asterisk (*) and double asterisk (**), respectively. LPS, lipopolysaccharide; DEX, dexamethasone; PAL, <span class="html-italic">Polygonum aviculare</span> L.; NS, not significant.</p>
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<p>Anti-inflammatory effects of PAL hydroethanolic extract in LPS-activated RAW 264.7 macrophages. Expression levels of (<b>A</b>) COX-2 and (<b>B</b>) iNOS in LPS-activated RAW 264.7 macrophages were quantitatively analyzed. The levels of extracellular (<b>C</b>) PGE<sub>2</sub> and (<b>D</b>) NO were analyzed in LPS-activated RAW 264.7 macrophages. Data are presented as the mean  ±  SEM (<span class="html-italic">N</span>  =  3). A statistical significance compared with LPS alone treatment at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 was marked by an asterisk (*) and double asterisk (**), respectively.</p>
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<p>Effects of PAL hydroethanolic extract on the production of pro-inflammatory cytokines in LPS-activated RAW 264.7 macrophages. Cellular inflammatory response was provoked by LPS in RAW 264.7 macrophages. Pro-inflammatory cytokines, including (<b>A</b>) IL-1β, (<b>B</b>) IL-6, and (<b>C</b>) TNF-α were analyzed in LPS-activated RAW 264.7 cells. Data are presented as the mean  ±  SEM (<span class="html-italic">N</span>  =  3). A statistical significance compared with LPS alone treatment at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 was marked by an asterisk (*) and double asterisk (**), respectively.</p>
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<p>Antioxidant effects of PAL hydroethanolic extract by activation of Nrf2 signaling pathway in RAW 264.7 macrophages. Protein levels of (<b>A</b>) nuclear Nrf2 and (<b>B</b>) cytoplasmic HO-1 in RAW 264.7 macrophages were quantitatively analyzed. (<b>C</b>) ARE activity by PAL hydroethanolic extract in HepG2-ARE cells. (<b>D</b>) Intracellular ROS level by PAL hydroethanolic extract in RAW 264.7 macrophages. Data are presented as the mean  ±  SEM (<span class="html-italic">N</span>  =  3). A statistical significance compared with control group at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 was marked by an asterisk (*) and double asterisk (**), respectively. SFN, sulforaphane; tBHP, tert-butyl hydroperoxide; tBHQ, tertiary-butylhydroquinone.</p>
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<p>HO-1 inhibition nullified anti-inflammatory effects by PAL hydroethanolic extract. (<b>A</b>) Cytoplasmic iNOS protein level was quantitatively analyzed in RAW 264.7 cells pre-treated with or without SnPP. (<b>B</b>) Extracellular NO level by PAL hydroethanolic extract in RAW 264.7 cells pre-treated with or without SnPP. (<b>C</b>) Cytoplasmic HO-1 protein level was quantitatively analyzed in RAW 264.7 cells pre-treated with or without SnPP. (<b>D</b>) Intracellular ROS level was analyzed in LPS-activated RAW 264.7 cells pre-treated with and without SnPP. Values are mean  ±  SEM (<span class="html-italic">N</span>  =  3). A significance difference compared with LPS alone or control group at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 was indicated by an asterisk (*) and double asterisk (**), respectively. A hash (# <span class="html-italic">p</span> &lt; 0.05) and double hash (## <span class="html-italic">p</span> &lt; 0.01) indicate a significant difference between groups. SnPP, Tin Protoporphyrin IX dichloride.</p>
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<p>HO-1 inhibition abrogates anti-inflammatory effects by KAE and QUE abundant in PAL hydroethanolic extract. NF-κB luciferase activity by (<b>A</b>) KAE and (<b>B</b>) QUE in LPS-activated NF-κB Luciferase Reporter-RAW 264.7 cells pre-treated with or without SnPP. Extracellular NO level by (<b>C</b>) KAE and (<b>D</b>) QUE in LPS-activated RAW 264.7 macrophages pre-treated with and without SnPP. Data are presented as the mean  ±  SEM (<span class="html-italic">N</span>  =  3). A statistical significance compared with LPS alone group at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 was marked by an asterisk (*) and double asterisk (**), respectively. A hash (# <span class="html-italic">p</span> &lt; 0.05) and double hash (## <span class="html-italic">p</span> &lt; 0.01) indicate a statistical significance between groups. NS, not significant.</p>
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15 pages, 2474 KiB  
Article
Analysis of the Effects of Organic and Synthetic Mulching Films on the Weed, Root Yield, Essential Oil Yield, and Chemical Composition of Angelica archangelica L.
by Jovan Lazarević, Sava Vrbničanin, Ana Dragumilo, Tatjana Marković, Rada Đurović Pejčev, Svetlana Roljević Nikolić and Dragana Božić
Horticulturae 2024, 10(11), 1199; https://doi.org/10.3390/horticulturae10111199 - 14 Nov 2024
Viewed by 845
Abstract
Angelica archangelica L. (Garden angelica) is a medicinal and aromatic plant from the Apiaceae family, originating from North Europe (Iceland, Greenland, and Scandinavian countries). A. archangelica is commonly used in traditional medicine to treat anxiety, insomnia, stomach and intestinal disorders, skin conditions, respiratory [...] Read more.
Angelica archangelica L. (Garden angelica) is a medicinal and aromatic plant from the Apiaceae family, originating from North Europe (Iceland, Greenland, and Scandinavian countries). A. archangelica is commonly used in traditional medicine to treat anxiety, insomnia, stomach and intestinal disorders, skin conditions, respiratory problems, and arthritis. This plant is generally cultivated for its root and seed where the essential oil (EO) is concentrated the most. Angelica archangelica cultivation has a lot of challenges but the main one is weed control; so, the aim of this study was to investigate the influence of four different mulch types as non-chemical weed control measures on weediness, fresh root yield, and EO chemical composition and yield from A. archangelica roots. A field trial was conducted with the following six treatments: two organic mulches, two synthetic mulches, and two controls (regular hand-weeded and weeded). The results show that the most present weeds were Ambrosia artemisiifolia, Chenopodium album, Polygonum aviculare, and Polygonum lapathyfolium, but synthetic mulch foils achieved the best weed suppression (100%). These fields also achieved the highest fresh root yield in both of the experimental seasons. The highest EO yield was detected with agrotextile mulch foil at season I (0.41%, v/w) and with the weeded control (0.51%, v/w) at season II, but dominant components at both seasons were α-pinene and β-phellandrene. The results suggest that the agrotextile black and silver–brown mulch foils achieved complete weed suppression, but the agrotextile black mulch foil had a better effect on fresh root yield, EO yield, and its chemical composition. Full article
(This article belongs to the Section Medicinals, Herbs, and Specialty Crops)
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Figure 1

Figure 1
<p>Total dry weed biomass (TDWB; g m<sup>−2</sup>) in the first experimental season. Letters on bars (a–c) refer to the statistical evaluation of the sum of the dry weed biomass illustrated by stacked bars in the diagram (<span class="html-italic">p</span> &lt; 0.05 Duncan’s test). Synthetic mulches: ATF—agrotextile foil; SBF—silver–brown foil. Organic mulches: S—straw; SW—sawdust. Controls: WCT—weeded control; WFC—weed-free control.</p>
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<p>Total dry weed biomass (TDWB; g m<sup>−2</sup>) in the second experimental season. Letters on bars (a–d) refer to the statistical evaluation of the sum of the dry weed biomass illustrated by stacked bars in the diagram (<span class="html-italic">p</span> &lt; 0.05 Duncan’s test). Synthetic mulches: ATF—agrotextile foil; SBF—silver–brown foil. Organic mulches: S—straw; SW—sawdust. Controls: WCT—weeded control; WFC—weed-free control.</p>
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<p><span class="html-italic">A. archangelica</span> fresh root yield (t ha<sup>−1</sup>) in the first experimental season. Letters on bars (a–e) refer to the statistical evaluation of the sum of the fresh root yield illustrated by stacked bars in the diagram (<span class="html-italic">p</span> &lt; 0.05. Duncan’s test). Synthetic mulches: ATF—agrotextile foil; SBF—silver–brown foil. Organic mulches: S—straw; SW—sawdust. Controls: WCT—weeded control; WFC—weed-free control.</p>
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<p><span class="html-italic">A. archangelica</span> fresh root yield (t ha<sup>−1</sup>) in the second experimental season. Letters on bars (a–d) refer to the statistical evaluation of the sum of the fresh root yield illustrated by stacked bars in the diagram (<span class="html-italic">p</span> &lt; 0.05. Duncan’s test). Synthetic mulches: ATF—agrotextile foil; SBF—silver–brown foil. Organic mulches: S—straw; SW—sawdust. Controls: WCT—weeded control; WFC—weed-free control.</p>
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<p>Experimental field assay.</p>
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<p>Weediness of <span class="html-italic">A. archangelica</span> experimental field.</p>
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<p><span class="html-italic">A. archangelica</span> roots.</p>
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41 pages, 3391 KiB  
Review
A Comprehensive Review of Molecular Mechanisms, Pharmacokinetics, Toxicology and Plant Sources of Juglanin: Current Landscape and Future Perspectives
by Magdalena Rutkowska, Martyna Witek and Monika A. Olszewska
Int. J. Mol. Sci. 2024, 25(19), 10323; https://doi.org/10.3390/ijms251910323 - 25 Sep 2024
Cited by 1 | Viewed by 1652
Abstract
Juglanin (kaempferol 3-O-α-L-arabinofuranoside) is a flavonol glycoside occurring in many plants, including its commercial sources Juglans regia, Polygonum aviculare and Selliguea hastata. Recent extensive studies have explored the potential of using juglanin in various pathological conditions, including cardiovascular disorders, [...] Read more.
Juglanin (kaempferol 3-O-α-L-arabinofuranoside) is a flavonol glycoside occurring in many plants, including its commercial sources Juglans regia, Polygonum aviculare and Selliguea hastata. Recent extensive studies have explored the potential of using juglanin in various pathological conditions, including cardiovascular disorders, central nervous and skeletal system disorders, metabolic syndrome, hepatic injury, and cancers. The results indicated a wide range of effects, like anti-inflammatory, anti-oxidant, anti-fibrotic, anti-thrombotic, anti-angiogenic, hepatoprotective, hypolipidemic, hypoglycemic, anti-apoptotic (normal cells), and pro-apoptotic (cancer cells). The health-promoting properties of juglanin can be attributed to its influence on many signaling pathways, associated with SIRT1, AMPK, Nrf2, STING, TLR4, MAPKs, NF-κB, AKT, JAK, and their downstream genes. This review primarily summarizes the current knowledge of molecular mechanisms, pharmacokinetics, biocompatibility, and human use safety of juglanin. In addition, the most promising new plant sources and other existing challenges and prospects have also been reviewed and discussed, aiming to provide direction and rationale for the further development and broader pharmaceutical application of juglanin. Full article
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Graphical abstract
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<p>The chemical structure of juglanin.</p>
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<p>The mechanism of fibrosis with potential grip points for juglanin activity. Abbreviations: collagen type I alpha 1 (COL1A1); collagen type I alpha 2 (COL1A2); connective tissue growth factor (CTGF); chemokine C-X-C motif ligand 1 (CXCL1); extracellular matrix (ECM); fibronectin 1 (FN1); interleukin 17 (IL-17); interleukin 18 (IL-18); interleukin 1β (IL-1β); interleukin 6 (IL-6); mitogen activated protein kinase (MAPK); matrix metalloproteinase 9 (MMP-9); nuclear factor-κB (NF-κB); stimulator of interferon genes (STING); transforming growth factor β1 (TGF-β1); tissue inhibitor of metalloproteinase 1 (TIMP-1); toll-like receptor 4 (TLR4); tumor necrosis factor-α (TNF-α); α-smooth muscle actin (α-SMA).</p>
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<p>The effects of juglanin on metabolic syndrome. Abbreviations: acetyl-CoA carboxylase α (ACCα); AMP-activated protein kinase (AMPK); carnitine-palmitoyl transferase 1α (CPT-1); CCAAT-enhancer-binding protein α/β (C/EBP α/β); fatty acid synthase (FAS); fatty acid-binding protein 4 (FABP4); glucose transporter 4 (GLUT4); high-density lipoprotein (HDL); nuclear factor-κB (NF-κB); peroxisome proliferator-activated receptor α (PPAR-α); peroxisome proliferator-activated receptor γ (PPAR-γ); sirtuin 1 (SIRT1); stearoyl-CoA desaturase 1 (SCD1); sterol regulatory-element binding proteins 1c (SREBP-1c); triglycerides (TG); tumor necrosis factor-α (TNF-α); uncoupling protein 2 (UCP-2). ↑ increase; ↓ decrease; − not changed.</p>
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<p>The potential mechanisms of juglanin hepatoprotective activity. Abbreviations: B-cell lymphoma-extra large (Bcl-xL); bcl-2-like protein 4 (Bax); catalase (CAT); glutamate-cysteine ligase subunits (GCLC, GCLM); glutathione peroxides (GPx); interferon β (IFN-β); interleukin 1β (IL-1β); interleukin 6 (IL-6); mitogen-activated protein kinase (MAPK); NAD(P)H quinone dehydrogenase 1 (NQO-1); nuclear factor erythroid 2-related factor 2 (Nrf2); oxygenase 1 (HO-1); phosphorylated signal transducer and activator of transcription (p-STAT); phosphorylated c-Jun N-terminal kinase (p-JNK); phosphorylated extracellular signal-regulated kinase (p-ERK); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated IκB kinase α (p-IKKα); phosphorylated Janus Kinase 2 gene (p-JAK2); phosphorylated nuclear factor-κB (p-NF-κB); phosphorylated TANK-binding kinase 1 (p-TBK1); toll-like receptor 4 (TLR4); reactive oxygen species (ROS); superoxide dismutase (SOD); suppressor of IKKepsilon (SIKE); tumor necrosis factor-α (TNF-α).</p>
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<p>The potential mechanisms of juglanin activity in the cardiovascular system. Abbreviations: AMP-activated protein kinase (AMPK); endothelial nitric oxide synthase (eNOS); high mobility group box 1 (HMGB1); interleukin 1β (IL-1β); interleukin 6 (IL-6); kruppel-like factor 2 (KLF-2); mitogen-activated protein kinase (MAPK); monocyte chemoattractant protein 1 (MCP-1); NADPH oxidase 2 (NOX-2); nitrogen oxide (NO); nuclear factor erythroid 2-related factor 2 (Nrf2); nuclear factor-κB (NF-κB); oxygenase 1 (HO-1); phosphorylated c-Jun N-terminal kinase (p-JNK); phosphorylated extracellular signal-regulated kinase (p-ERK); reactive oxygen species (ROS); receptor for advanced glycation end products (RAGE); superoxide dismutase (SOD); toll-like receptor 4 (TLR4); tryptophan hydroxylase-1 (TPH-1); tumor necrosis factor-α (TNF-α); vascular cellular adhesion molecule-1 (VCAM-1); vascular endothelial growth factor (VEGF); vascular endothelial growth factor receptor 2 (VEGFR2); zonula occludens-1 (ZO-1).</p>
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<p>The potential pathways of juglanin activity in the central nervous system. Abbreviations: AMP-activated protein kinase (AMPK); B-cell lymphoma 2 (Bcl-2); Bcl-2-like protein 4 (Bax); beta-amyloid (Aβ); cluster of differentiation 11b (CD11b); cluster of differentiation 14 (CD14); cyclooxygenase 2 (COX-2); enhanced neurotrophic factor (BDNF); glial fibrillary acidic protein (GFAP); inducible nitric oxide synthase (iNOS); interleukin 18 (IL-18); interleukin 1β (IL-1β); interleukin 6 (IL-6); ionized calcium-binding adaptor molecule 1 (Iba1); monocyte chemoattractant protein 1 (MCP-1); myeloid differentiation primary response 88 (MyD88); nuclear factor-κB (NF-κB); phosphoinositide 3-kinase (PI3K); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated IκB kinase α (p-IKKα); phosphorylated microtubule-associated protein (p-Tau); poly-ADP-ribose polymerase (PARP); protein kinase B (AKT); toll-like receptor 4 (TLR4); tumor necrosis factor-α (TNF-α).</p>
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<p>The potential pathways of juglanin activity in the skeletal system. Abbreviations: apoptosis-associated Speck-like protein containing a caspase activation and recruitment domain (ASC); cysteine cathepsin K (CTSK); disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS); factor matrix metalloproteinase (MMP); factor matrix metalloproteinase 9 (MMP-9); glutathione (GSH); interleukin 1 (IL-1); interleukin 1β (IL-1β); interleukin 6 (IL-6); malondialdehyde (MDA); NADPH oxidase 4 (NOX-4); nitrogen oxide (NO); nucleotide-binding domain, leucine-rich–containing family, pyrin domain–containing-3 (NLRP3); nuclear factor-κB (NF-κB); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated IκB kinase (p-IKK); prostaglandin E2 (PGE2); reactive oxygen species (ROS); receptor activator for nuclear factor κ B (RANK); receptor activator for nuclear factor κ B ligand (RANKL); sirtuin 1 (SIRT1); superoxide dismutase (SOD); thioredoxin-interacting protein (TxNIP); transcription factor nuclear factor of activated T cells c1 (NFATc1); Fos proto-oncogene (c-Fos); transforming growth factor β (TGF-β); translating ribosome affinity purification (TRAP); tumor necrosis factor receptor-associated factor 6 (TRAF6); tumor necrosis factor-α (TNF-α).</p>
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<p>The potential metabolic pathways of juglanin anti-cancer activity. Abbreviations: ataxia telangiectasia mutated (ATM); autophagy protein 7, 3 (ATG-7, ATG-3); B-cell lymphoma 2 (Bcl-2); B-cell lymphoma-extra large (Bcl-xL); bcl-2-like protein 4 (Bax); BH3 domain-containing protein (Bad); cyclin-dependent kinase 1 (CDK1); death receptor 4 (DR4); death receptor 5 (DR5); FAS-associated death domain protein (FADD); gap 2 phase/mitosis phase in the cell cycle (G2/M); interleukin 18 (IL-18); interleukin 1β (IL-1β); microtubule-associated protein light chain 3 (LC3); nuclear factor-κB (NF-κB); phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3); phosphoinositide 3-kinase (PI3K); phosphorylated cell division cycle 2 (p-Cdc2); phosphorylated cell division cycle 25C (p-Cdc25C); phosphorylated checkpoint kinase 2 (p-Chk2); phosphorylated c-Jun N-terminal kinase (p-JNK); phosphorylated extracellular signal-regulated kinase 1/2 (p-ERK 1/2); phosphorylated inhibitor κB-α (p-IκBα); phosphorylated mammalian target of rapamycin (p-mTOR); poly-ADP-ribose polymerase (PARP); protein kinase B (AKT); reactive oxygen species (ROS); TNF-related apoptosis-inducing ligand (TRAIL); tumor necrosis factor-α (TNF-α).</p>
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<p>Summary of the potential pathways of juglanin’s biological activity. Abbreviations: AMP-activated protein kinase (AMPK); high mobility group box 1 (HMGB1); Janus kinase gene/signal transducer and activator of transcription (JAK/STAT); Kruppel-like factor 2 (KLF-2); mitogen-activated protein kinase (MAPK); nuclear factor erythroid 2-related factor 2 (Nrf2); nuclear factor-κB (NF-κB); nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3 (NLRP3); phosphoinositide 3-kinase/protein kinase B (PI3K/AKT); sirtuin 1 (SIRT1); stimulator of interferon genes (STING); toll-like receptor 4 (TLR4); transforming growth factor β1 (TGF- β1).</p>
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18 pages, 4902 KiB  
Article
The Electric Spatula: Killing Weeds with Pulsed Microshocks from a Flat-Plate Electrode
by Daniel J. Bloomer, Kerry C. Harrington, Hossein Ghanizadeh and Trevor K. James
Agronomy 2023, 13(11), 2694; https://doi.org/10.3390/agronomy13112694 - 26 Oct 2023
Cited by 1 | Viewed by 1965
Abstract
Seeking an easy-to-deploy, energy-efficient, non-herbicide weed control method, we tested a flat-plate electrode to apply pulsed electric microshocks (PMS) to a grass and four broadleaf weed species. The method can be deployed via a hand-held unit or as part of a fully automated [...] Read more.
Seeking an easy-to-deploy, energy-efficient, non-herbicide weed control method, we tested a flat-plate electrode to apply pulsed electric microshocks (PMS) to a grass and four broadleaf weed species. The method can be deployed via a hand-held unit or as part of a fully automated system to control escape weeds in field crops. The effectiveness of the treatments and the relative energy discharges when applying similar electric doses to the plant leaves or to the plant when pressed to the soil with a flat-plate electrode were compared. The method killed only half of the treated Lolium multiflorum “Winter Star” plants, well below our target rate, but significantly reduced growth rates and indicated that effective treatment of <1.0 MJ ha−1 for treating five plants m−2 is possible. Polygonum aviculare L., Amaranthus powellii S. Wats., Amaranthus deflexus, and Solanum nitidibaccatum Bitter plants were successfully controlled, with the energy required to kill 100% of seedlings varying from 0.1 to 0.9 MJ ha−1, indicating that broadleaf weeds are more susceptible. This easily met our target effectiveness and efficiency goals. The discharged energy increased when the electrode pressed the plant to a dry soil surface rather than to the leaves only and increased further when the electrode pressed the plant to a wet soil surface. Full article
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Figure 1

Figure 1
<p>Application method showing the earth electrode inserted horizontally into the base of the bag and the flat plate electrode ready to be pressed against the weed (<span class="html-italic">Polygonum aviculare</span>).</p>
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<p>Simple box plot of mean <span class="html-italic">L. multiflorum</span> plant dry mass per bag 10 days after treatment by treatment applied, with treatments varying by placement of the electrode (electrode contact), the electric pulse length, and the number of pulses applied in the treatment. Asterisks indicate extreme outliers, and the circle indicates a mild outlier. Plots sharing the same letters are not significantly different.</p>
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<p>Simple boxplot of calculated discharged energy (J) by treatment when multiple DC electric pulses of varying pulse lengths were applied to sets of three <span class="html-italic">L. multiflorum</span> seedlings in bags with a flat-plate electrode pressed to the leaves only or plants pressed to the soil with either a dry or wet soil surface. Mild outliers are indicated by small circles. Plots sharing the same letters are not significantly different.</p>
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<p>Simple box plot of <span class="html-italic">L. multiflorum</span> final death rate per bag when treated with pulsed microshocks at a range of voltages, pulse lengths, and number of pulses, which were applied to leaves only or to leaves pressed to the soil. Plots sharing the same letters are not significantly different.</p>
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<p>Simple box plot of <span class="html-italic">L. multiflorum</span> plant dry mass by bag (mg) measured 14 days after treatments were applied to leaves only or to leaves pressed to the soil with pulsed microshocks at 3.5 or 4.5 kV with different pulse lengths and a different number of pulses applied to plants. Plots sharing the same letters are not significantly different.</p>
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<p>Scatter plot of <span class="html-italic">L. multiflorum</span> plant dry mass (mg) by discharged energy (J) by electrode placement with overall linear fit line bounded by 90% individual confidence levels.</p>
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<p>Simple box plot of discharged energy (J) applied to <span class="html-italic">L. multiflorum</span> by treatments at 3.5 kV and 4.5 kV with different electric pulse lengths and a different number of pulses applied to plants. Plots sharing the same letters are not significantly different.</p>
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<p>Stacked histogram count of treatment by final status of <span class="html-italic">P. aviculare</span> plants that were subjected to treatments at 3.0 kV and 4.5 kV with different electric pulse lengths and a different number of pulses applied with the electrode pressed to the leaves only or to the leaves pressed against the soil.</p>
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<p>Simple box plot of discharged energy (J) applied to <span class="html-italic">P. aviculare</span> by treatments at 3.0 kV and 4.5 kV at different electric pulse lengths and a different number of pulses applied with the electrode pressed to the leaves only or to the leaves pressed against the soil. Extreme outliers are indicated by stars. A mild outlier is indicated by a small circle. Plots sharing the same letters are not significantly different.</p>
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<p>Simple boxplot of <span class="html-italic">P. aviculare</span> final dry mass following application of treatments at 3.0 kV and 4.5 kV with different electric pulse lengths and a different number of pulses applied with the electrode pressed to the leaves only or to the leaves pressed against the soil. An extreme outlier is indicated by the star. Plots sharing the same letters are not significantly different.</p>
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<p>Stacked histogram count of treatment by survival of <span class="html-italic">A. powellii</span> following application of treatments at 4.5 kV with different electric pulse lengths and a different number of pulses applied with the electrode pressed to the leaves only or to the leaves pressed against the soil.</p>
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<p>Clustered boxplot of measured energy (J) discharged when <span class="html-italic">A. powellii</span> were subjected to treatments at 3.0 kV and 4.5 kV with different electric pulse lengths and a different number of pulses applied to plants with the electrode pressed to the leaves only or to the leaves pressed against the soil. A mild outlier is indicated by the small circle. Plots sharing the same letters are not significantly different.</p>
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<p>Simple boxplot of plant longevity when <span class="html-italic">A. powellii</span> were subjected to treatments at 3.0 kV and 4.5 kV with different electric pulse lengths and a different number of pulses applied to plants with the electrode pressed to the leaves only or to the leaves pressed against the soil. Plant assessment stopped 28 days after treatment. A mild outlier is indicated by the small circle. Plots sharing the same letters are not significantly different.</p>
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<p>Simple boxplot of <span class="html-italic">A. powellii</span> final plant dry mass when plants were subjected to treatments at 3.0 kV and 4.5 kV with different electric pulse lengths and a different number of pulses applied to plants with the electrode pressed to the leaves only or to the leaves pressed against the soil. An extreme outlier is indicated by the star. Mild outliers are indicated by the small circles. Plots sharing the same letters are not significantly different.</p>
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<p>Clustered boxplot of discharged energy (J) by dose applied by electrode placement when PMS was applied to <span class="html-italic">S. nitidibaccatum</span>. A mild outlier is indicated by the small circle. Plots sharing the same letters are not significantly different.</p>
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12 pages, 976 KiB  
Article
Chemical Composition of Essential Oils of Seven Polygonum Species from Turkey: A Chemotaxonomic Approach
by Azize Demirpolat
Molecules 2022, 27(24), 9053; https://doi.org/10.3390/molecules27249053 - 19 Dec 2022
Cited by 12 | Viewed by 2882
Abstract
Medicinal plants and herbal preparations are gaining attention in the scientific community today, as they are often used intermittently in the treatment of various diseases. The genus of Polygonum (Polygonaceae), known locally as “madimak”, is an aromatic plant widely used in world flavors. [...] Read more.
Medicinal plants and herbal preparations are gaining attention in the scientific community today, as they are often used intermittently in the treatment of various diseases. The genus of Polygonum (Polygonaceae), known locally as “madimak”, is an aromatic plant widely used in world flavors. The chemical composition of the essential oils of dried aerial parts of seven of Polygonum was analyzed by GC-MS. These species are Polygonum lapathifolium L., Polygonum persicaria L., Polygonum arenastrum Bor., Polygonum bellardii All., Polygonum arenarium Waldst. Et Kit., Polygonum aviculare L., and Polygonum cognatum Meissn. Qualitative and quantitative differences were found in the essential oil analysis of the seven Polygonum species. The major compounds were determined as (E)-β-farnesene (19. 46%), dodecanal (15.92%), β-caryophyllene (12.95%), in P. aviculare; (E)-β-farnesene (25.00%), dodecanal (20.45%), β-caryophyllene (9.38%), and caryophyllene oxide (8. 26%) in P. persicaria; dodecanal (25.65%), caryophyllene oxide (13.35%), β-caryophyllene (7.95%), and (E)-β-farnesene (6.20%) in P. lapathifolium, and dodecanal (19.65%), (E)-β-farnesene (13.86%), β-caryophyllene (8.06%), and α-terpineol (7.2%) in P. arenarium, dodecanal (16.23%), β-caryophyllene (16.09%), (E)-β-farnesene (12.26%), caryophyllene oxide (7.94%) in P. bellardii, (E)-β-farnesene (20.75%), dodecanal (17.96%), β-caryophyllene (13.01%), α-terpineol (4.97%) in P. arenastrum, (E)-β-farnesene (9.49%), dodecanal (14.01%), β-caryophyllene (11.92%), geranyl acetate (9.49%), and undecanal (7.35%) in P. cognatum. This study is the most comprehensive study conducted to determine the essential oil components of Polygonum species. In addition, a literature review on the composition of the essential oils of these Polygonum taxa was performed. The essential oil components of the species in our study were revealed for the first time with this study. Full article
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<p>Clustering analysis of seven <span class="html-italic">Polygonum</span> species to essential oil components.</p>
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<p>Principal component analysis (PCA) of the essential-oil composition of <span class="html-italic">Polygonum</span> species.</p>
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<p>Biplot (PCA) from the analysis of the essential oil composition of the <span class="html-italic">Polygonum</span> species.</p>
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24 pages, 3046 KiB  
Article
Comparative Study of the Pharmacological Properties and Biological Effects of Polygonum aviculare L. herba Extract-Entrapped Liposomes versus Quercetin-Entrapped Liposomes on Doxorubicin-Induced Toxicity on HUVECs
by Mariana Mureşan, Diana Olteanu, Gabriela Adriana Filip, Simona Clichici, Ioana Baldea, Tunde Jurca, Annamaria Pallag, Eleonora Marian, Adina Frum, Felicia Gabriela Gligor, Paula Svera, Bogdan Stancu and Laura Vicaș
Pharmaceutics 2021, 13(9), 1418; https://doi.org/10.3390/pharmaceutics13091418 - 7 Sep 2021
Cited by 15 | Viewed by 3969
Abstract
This study aimed to evaluate the comparative biological effects of Polygonum aviculare L. herba (PAH) extract and quercetin-entrapped liposomes on doxorubicin (Doxo)-induced toxicity in HUVECs. HUVECs were treated with two formulations of liposomes loaded with PAH extract (L5 and L6) and two formulations [...] Read more.
This study aimed to evaluate the comparative biological effects of Polygonum aviculare L. herba (PAH) extract and quercetin-entrapped liposomes on doxorubicin (Doxo)-induced toxicity in HUVECs. HUVECs were treated with two formulations of liposomes loaded with PAH extract (L5 and L6) and two formulations of liposomes loaded with quercetin (L3 prepared with phosphatidylcholine and L4 prepared with phosphatidylserine). The results obtained with atomic force microscopy, zeta potential and entrapment liposome efficiency confirmed the interactions of the liposomes with PAH or free quercetin and a controlled release of flavonoids entrapped in all the liposomes. Doxo decreased the cell viability and induced oxidative stress, inflammation, DNA lesions and apoptosis in parallel with the activation of Nrf2 and NF-kB. Free quercetin, L3 and L4 inhibited the oxidative stress and inflammation and reduced apoptosis, particularly L3. Additionally, these compounds diminished the Nrf2 and NF-kB expressions and DNA lesions, principally L4. PAH extract, L5 and L6 exerted antioxidant and anti-inflammatory activities, reduced γH2AX formation and inhibited extrinsic apoptosis and transcription factors activation but to a lesser extent. The loading of quercetin in liposomes increased the cell viability and exerted better endothelial protection compared to free quercetin, especially L3. The liposomes with PAH extract had moderate efficiency, mainly due to the antioxidant and anti-inflammatory effects and the inhibition of extrinsic apoptosis. Full article
(This article belongs to the Special Issue Nanotechnology-Enabled Strategies to Enhance Topical Bioavailability)
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<p>DLS analysis of the liposomal systems. Particle size distribution of the L1 (<b>a</b>), L2 (<b>b</b>), L3 (<b>c</b>), L4 (<b>d</b>), L5 (<b>e</b>) and L6 (<b>f</b>) formulations.</p>
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<p>AFM images for the studied liposomes. The letters correspond to (<b>A</b>) L1, (<b>B</b>) L2, (<b>C</b>) L3, (<b>D</b>) L4, (<b>E</b>) L5 and (<b>F</b>) L6. The numbers correspond to (<b>1</b>) AFM image, (<b>2</b>) 3D image, (<b>3</b>) profile of the sample and (<b>4</b>) area selected for profiling.</p>
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<p>The release of flavonoids from liposomes loaded with the PAH extract (L5 and L6) vs. liposomes loaded with quercetin (L3 and L4).</p>
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<p>Cell viability of HUVECs treated with quercetin, PAH extract and different liposome formulations with quercetin and the PAH extract. HUVECs were exposed to quercetin and L3 and L4 formulations in concentrations ranging between 0.001-µg GAE/mL and 100-µg GAE/mL and to the PAH extract and L5 and L6 formulations in concentrations between 0.006-µg GAE/mL and 0.678-µg GAE/mL (data are presented as the mean of OD540 ± SD; <span class="html-italic">n</span> = 3 for each sample). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 vs. control, untreated cells.</p>
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<p>Malondialdehyde levels in the cell lysates, and IL-6 secretion in the supernates of the HUVECs exposed to Doxo and quercetin, the PAH extract and different formulations of liposomes. (<b>A</b>) MDA increased significantly after Doxo administration and diminished in the cells treated with quercetin (<span class="html-italic">p</span> &lt; 0.001), the PAH extract (<span class="html-italic">p</span> &lt; 0.001), L3 and L4 with quercetin (<span class="html-italic">p</span> &lt; 0.001) and L5 and L6 with the PAH extract (<span class="html-italic">p</span> &lt; 0.001). (<b>B</b>) IL-6 secretion increased after Doxo exposure (<span class="html-italic">p</span> &lt; 0.001) and diminished in the supernates of the cells treated with L3, L4 (<span class="html-italic">p</span> &lt; 0.001), L5 and L6 (<span class="html-italic">p</span> &lt; 0.05). The statistical significance of the differences between the treated and control groups was evaluated with one-way ANOVA, followed by Dunnett’s multiple range test. Data are presented as the mean and SD of triplicate samples. <sup>###</sup> vs. control and * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001 vs. Doxo-treated cells.</p>
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<p>Caspases-3, -8 and -9 in the supernates of HUVECs exposed to Doxo and quercetin, the PAH extract and different liposomes formulations. Caspases-3 (<b>A</b>), -8 (<b>B</b>) and -9 (<b>C</b>) increased significantly after Doxo exposure and diminished both in cells treated with quercetin (<span class="html-italic">p</span> &lt; 0.001) and L3 (<span class="html-italic">p</span> &lt; 0.001). The PAH extract significantly reduced caspase-8 and caspase-9 (<span class="html-italic">p</span> &lt; 0.001), while L5 and L6 decreased the caspase-3 and caspase-8 levels (<span class="html-italic">p</span> &lt; 0.001). The statistical significance of the difference between the treated and control groups was evaluated with one-way ANOVA, followed by Dunnett’s multiple range test. Data are presented as the mean and SD of triplicate samples. <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01; <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. control and *** <span class="html-italic">p</span> &lt; 0.001 vs. Doxo-treated cells.</p>
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<p>NF-kB, pNF-kB, Nrf2 and γH2AX expressions in HUVEC lysates after exposure to Doxo and the treatments with quercetin; the PAH extract and the L3, L4, L5 and L6 formulations. Representative images of immunoblotting for NF-kB, pNF-kB, Nrf2, γH2AX and GAPDH in the HUVECs treated with quercetin, the PAH extract and liposomes loaded with quercetin and the PAH extract are shown in the upper panel (<b>A</b>), and the results of the statistical analysis for the ratio of Nrf2, γH2AX and GAPDH expressions are in the lower panels (<b>C</b>,<b>D</b>). For NF-kB and pNF-kB, the results were expressed as pNF-kB divided by the total NF-kB (<b>B</b>). The statistical significance of the differences between treated and control groups was evaluated with one-way ANOVA, followed by Dunnett’s multiple range test; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05; <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 vs. control cells and * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001 vs. Doxo-treated cells.</p>
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17 pages, 3817 KiB  
Article
Production of Antioxidant Molecules in Polygonum aviculare (L.) and Senecio vulgaris (L.) under Metal Stress: A Possible Tool in the Evaluation of Plant Metal Tolerance
by Mirko Salinitro, Sara Hoogerwerf, Sonia Casolari, Alessandro Zappi, Dora Melucci and Annalisa Tassoni
Int. J. Mol. Sci. 2020, 21(19), 7317; https://doi.org/10.3390/ijms21197317 - 3 Oct 2020
Cited by 16 | Viewed by 2724
Abstract
Plants growing on heavy metal (HM)-polluted soils show toxicity symptoms, such as chlorosis and growth reduction, and undergo oxidative stress due to the formation of reactive oxygen species (ROS). Plants overcome oxidative stress by producing a wide range of antioxidant molecules, such as [...] Read more.
Plants growing on heavy metal (HM)-polluted soils show toxicity symptoms, such as chlorosis and growth reduction, and undergo oxidative stress due to the formation of reactive oxygen species (ROS). Plants overcome oxidative stress by producing a wide range of antioxidant molecules, such as polyphenols and flavonoids. The aim of the present work was to study the accumulation of these molecules in response to increasing concentrations of Cd, Cr, Cu, Ni, Pb and Zn and to assess whether they can be used as a tool in assessing metal-related stress in Polygonum aviculare and Senecio vulgaris. On average, P. aviculare shoots accumulated lower amounts of metals than S. vulgaris shoots. The uptake of all six elements was correlated and proportional to their concentration in the nutrient solution (ρ > 0.9), with the bioaccumulation factor (BAF) being >1 for most of them. The present research demonstrated that 82% of the samples showed a good correlation (|ρ| > 0.5) between the level of polyphenols, flavonoids and antioxidant activity and the metal concentration in plant shoots, confirming that the metal stress level and production of phenolic compounds having antioxidant activity were strictly connected. Nonetheless, the mere quantification of these molecules cannot identify the type of metal that caused the oxidative stress, neither determine the concentration of the stressors. The five tested populations of each species did not show any specific adaptation to the environment of origin. Full article
(This article belongs to the Special Issue Environmental Stress and Plants)
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<p>Metal contents in shoots of <span class="html-italic">P. aviculare</span> grown in hydroponics at increasing metal concentrations (from control to D, see Methods section). (<b>A</b>) Cd; (<b>B</b>) Cr; (<b>C</b>) Cu; (<b>D</b>) Ni; (<b>E</b>) Pb; (<b>F</b>) Zn. Bars represent the average of data coming from five populations analyzed in three biological replicates (<span class="html-italic">n</span> = 15). Different small letters (from v to z) above the bars indicate a statistically significant difference among the treatments (<span class="html-italic">p</span> &lt; 0.05) calculated with <span class="html-italic">Dunn.test</span> using R software.</p>
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<p>Metal contents in shoots of <span class="html-italic">S. vulgaris</span> grown in hydroponics at increasing metal concentrations (from control to D, see Methods section). (<b>A</b>) Cd; (<b>B</b>) Cr; (<b>C</b>) Cu; (<b>D</b>) Ni; (<b>E</b>) Pb; (<b>F</b>) Zn. Bars represent the average of data coming from five populations analyzed in three biological replicates (<span class="html-italic">n</span> = 15). Different small letters (from v to z) above the bars indicate a statistically significant difference among the treatments (<span class="html-italic">p</span> &lt; 0.05) calculated with <span class="html-italic">Dunn.test</span> using R software.</p>
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<p>PCA analysis showing the grouping for <span class="html-italic">P. aviculare</span> data according to different metal treatments. The complete dataset reported in <a href="#app1-ijms-21-07317" class="html-app">Supplementary Table S1</a> was used to perform the analysis by means of the <span class="html-italic">prcomp</span> function of the R package. Treatments: control, no metal; A, urban metal concentration; B, medium metal concentration, C, high metal concentration, D, maximum metal concentration allowing plant survival.</p>
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<p>PCA analysis showing the grouping for <span class="html-italic">P. aviculare</span> data according to different metal treatments. The complete dataset reported in <a href="#app1-ijms-21-07317" class="html-app">Supplementary Table S1</a> was used to perform the analysis by means of the <span class="html-italic">prcomp</span> function of the R package. Treatments: control, no metal; A, urban metal concentration; B, medium metal concentration, C, high metal concentration, D, maximum metal concentration allowing plant survival.</p>
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<p>Shoot metal concentration in different <span class="html-italic">P. aviculare</span> populations. (<b>A</b>) Cd; (<b>B</b>) Cr; (<b>C</b>) Cu; (<b>D</b>) Ni; (<b>E</b>) Pb; (<b>F</b>) Zn. Populations: B, Bologna urban; M, Milan urban; N, Bologna woodland; T, Milan woodland; P, serpentine. Data represent the mean value of three biological replicates (<span class="html-italic">n</span> = 3). Different small letters (from x to z) above the bars indicate a statistically significant difference among the treatments (<span class="html-italic">p</span> &lt; 0.05) calculated with <span class="html-italic">Dunn.test</span> using R software.</p>
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<p>Shoot metal concentration in different <span class="html-italic">S. vulgaris</span> populations. (<b>A</b>) Cd; (<b>B</b>) Cr; (<b>C</b>) Cu; (<b>D</b>) Ni; (<b>E</b>) Pb; (<b>F</b>) Zn. Populations: B, Bologna urban; M, Milan urban; N, Bologna woodland; T, Milan woodland; P, Mt. Prinzera serpentine. Data represent the mean value of three biological replicates (<span class="html-italic">n</span> = 3). Different small letters (from x to z) above the bars indicate a statistically significant difference among the treatments (<span class="html-italic">p</span> &lt; 0.05) calculated with <span class="html-italic">Dunn.test</span> using R software.</p>
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<p>(<b>A</b>) <span class="html-italic">Polygonum aviculare</span> (L.), and (<b>B</b>) <span class="html-italic">Senecio vulgaris</span> (L.). Photo by Mirko Salinitro.</p>
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31 pages, 4889 KiB  
Article
The Effect of Botanical Extracts Obtained through Ultrasound-Assisted Extraction on White Head Cabbage (Brassica Oleracea L. Var. Capitata L.) Seedlings Grown under Controlled Conditions
by Katarzyna Godlewska, Anita Biesiada, Izabela Michalak and Paweł Pacyga
Sustainability 2020, 12(5), 1871; https://doi.org/10.3390/su12051871 - 2 Mar 2020
Cited by 33 | Viewed by 5149
Abstract
This research presents the possibility of using innovative botanical extracts as biostimulants of plant growth to improve plant nutritional value, growth, and development. It is important to increase agricultural production but this process should be carried out in a sustainable way, without causing [...] Read more.
This research presents the possibility of using innovative botanical extracts as biostimulants of plant growth to improve plant nutritional value, growth, and development. It is important to increase agricultural production but this process should be carried out in a sustainable way, without causing risks for both the environment and consumers. For this reason, we have focused on the use of 14 natural raw materials and ultrasound assisted extraction for the production of biostimulants. Results proved that higher plants can be used to obtain valuable products for the application in modern horticulture and agriculture. For instance, extract based on Urtica dioica L. showed the highest biostimulatory properties: in the group sprayed with 0.1% extract cabbage seedlings were longer by 31%, while with 1.0% extract of Polygonum aviculare L. roots were longer by 72% than in the control group treated with water. Extracts based on Equisetum arvense L. (0.5%) and Urtica dioica L. (leaf) (0.1%) increased the fresh weight of sprouts by 113% and 112%, respectively. The highest root weight was observed in groups treated with Equisetum arvense L. (0.5%), Polygonum aviculare L. (0.5%), and Urtica dioica L. (leaf) (2.5%)—heavier by 207%, 206%, and 205%, respectively. Most of biostimulants increased the content of pigments involved in photosynthesis (e.g. 156% more chlorophyll for 0.1% Hypericum perforatum L. extract), decreased the content of polyphenols (e.g. 47% less for 2.5% Trifolium pretense extract), and showed a varied impact on antioxidant activity. There is an increasing interest in botanical extracts due to their high content of biologically active compounds and wide variety of application possibilities. Full article
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<p>The schematic methodology of the experiment.</p>
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<p>The shoot length of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations: Al L, <span class="html-italic">Aloë vera</span> L. Burm. f. (leaf); Ar Fr, <span class="html-italic">Aronia melanocarpa</span> (Michx) Elliott (fruit); Bv R, <span class="html-italic">Beta vulgaris</span> L. (root); Eq H, <span class="html-italic">Equisetum arvense</span> L. (herb); Hr Fr, <span class="html-italic">Hippophae rhamnoides</span> L. (fruit); Hp H, <span class="html-italic">Hypericum perforatum</span> L. (herb); Lc S, <span class="html-italic">Lens culinaris</span> Medik.(seeds); Paq L, <span class="html-italic">Pteridium aquilinum</span> L.) (leaf); Pav L, <span class="html-italic">Polygonum aviculare</span> L. (herb); Pi S, <span class="html-italic">Pisum sativum</span> L. (seeds); Pm H, <span class="html-italic">Plantago major</span> L. (herb); Tp F, <span class="html-italic">Trifolium pratense</span> L. (flower); Ur L, <span class="html-italic">Urtica dioica</span> L. (leaf); Ur R, <span class="html-italic">Urtica dioica</span> L. (root).</p>
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<p>The root length of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The shoot fresh weight of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The root fresh weight of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The shoot dry weight of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The root dry weight of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The of chlorophyll <span class="html-italic">a + b</span> of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The SPAD index of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The content of carotenoids of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The content of polyphenols of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The antioxidant activity (DPPH) of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The antioxidant activity (ABTS) of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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<p>The antioxidant activity (FRAP) of white head cabbage seedlings after application of plant extracts. (a) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between the control group (C) and extracts. (b) Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between commercial biostimulant (CB) and extracts. Abbreviations as in <a href="#sustainability-12-01871-f002" class="html-fig">Figure 2</a>.</p>
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17 pages, 996 KiB  
Article
Mulch-Based No-Tillage Effects on Weed Community and Management in an Organic Vegetable System
by Elena Testani, Corrado Ciaccia, Gabriele Campanelli, Fabrizio Leteo, Luca Salvati and Stefano Canali
Agronomy 2019, 9(10), 594; https://doi.org/10.3390/agronomy9100594 - 28 Sep 2019
Cited by 19 | Viewed by 3571
Abstract
Weeds can cooperate with the agroecosystem’s functioning by providing ecosystem services. Effective weed management should mitigate negative weed–crop interference, while maintaining a functional and balanced weed community. In a two-year trial, the in-line/roller crimper (RC) was used to terminate an agroecological service crop [...] Read more.
Weeds can cooperate with the agroecosystem’s functioning by providing ecosystem services. Effective weed management should mitigate negative weed–crop interference, while maintaining a functional and balanced weed community. In a two-year trial, the in-line/roller crimper (RC) was used to terminate an agroecological service crop (ASC; here barley, Hordeum vulgare L.) before organic zucchini (Cucurbita pepo, L.) and compared with green manure (GM) ASC and tilled no-ASC with Mater-Bi mulch on the rows (No_ASC). Zucchini yield, soil N availability, weed density/cover, biomass, and community composition were assessed. Analysis of variance, exploratory statistical analysis, and non-parametric inferential approaches were run, respectively, on agronomic data, species-specific weed frequencies, and Shannon diversity. Zucchini yield was the highest in No_ASC, due to soil N immobilization under high C:N barley residues in GM and RC. Multivariate analysis discriminated RC from tilled systems, outlining a specific ensemble of weed species correlated to Shannon diversity. From zucchini fruit set, RC selectively favored Polygonum aviculare L. and Helminthotheca echioides (L.), reasonably because of their oligotrophy and creeping habit. Their dominance finally caused low RC weed control. Results highlight strong weed selective pressure by the mulch-based no-tillage. Understanding the mechanisms underpinning the impact of soil management practices on weed community can drive towards a tailor-made and more effective weed management. Full article
(This article belongs to the Special Issue Weed Management & New Approaches)
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<p>Mean monthly temperature and rainfall of the experimental trial during the barley and zucchini cycles compared with the mean long-term values (30 years).</p>
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<p>PCA biplot ordering the experimental trials relative to weed frequency and Shannon diversity index (H’). FA, fallow; GM, green manure; RC, in-line/roller crimper.</p>
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<p>Hierarchical clustering run on (<b>a</b>) different treatment types (tillage systems) and (<b>b</b>) weed species. FA, fallow; GM, green manure; RC, in-line/roller crimper.</p>
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<p>Two-dimensional non-metric multi-dimensional scaling ordination of weed frequencies/biodiversity (Shannon H’ diversity index) and tillage systems. FA, fallow; GM, green manure; RC, in-line/roller crimper.</p>
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18 pages, 3289 KiB  
Article
Heavy Metals Bioindication Potential of the Common Weeds Senecio vulgaris L., Polygonum aviculare L. and Poa annua L.
by Mirko Salinitro, Annalisa Tassoni, Sonia Casolari, Francesco de Laurentiis, Alessandro Zappi and Dora Melucci
Molecules 2019, 24(15), 2813; https://doi.org/10.3390/molecules24152813 - 1 Aug 2019
Cited by 17 | Viewed by 3655
Abstract
In recent years, heavy metals (HMs) levels in soil and vegetation have increased considerably due to traffic pollution. These pollutants can be taken up from the soil through the root system. The ability of plants to accumulate HMs into their tissues can therefore [...] Read more.
In recent years, heavy metals (HMs) levels in soil and vegetation have increased considerably due to traffic pollution. These pollutants can be taken up from the soil through the root system. The ability of plants to accumulate HMs into their tissues can therefore be used to monitor soil pollution. The aim of this study was to test the ruderal species Senecio vulgaris L., Polygonum aviculare L., and Poa annua L., as possible candidates for biomonitoring Cu, Zn, Cd, Cr, Ni and Pb in multiple environments. The soils analyzed in this work came from three different environments (urban, woodland, and ultramafic), and therefore deeply differed for their metal content, texture, pH, and organic matter (OM) content. All urban soils were characterized by high OM content and presence of anthropogenic metals like Pb, Zn, Cd, and Cu. Woodland soils were sandy and characterized by low metal content and low OM content, and ultramafic soils had high Ni and Cr content. This soil variability affected the bioindication properties of the three studied species, leading to the exclusion of most metals (Zn, Cu, Cr, Cd, and Pb) and one species (P. aviculare) due to the lack of linear relations between metal in soil and metal in plants. Senecio vulgaris and Poa annua, conversely, appeared to be good indicators of Ni in all the soils tested. A high linear correlation between total Ni in soil and Ni concentration in P. annua shoots (R2 = 0.78) was found and similar results were achieved for S. vulgaris (R2 = 0.88). Full article
(This article belongs to the Special Issue Analytical Methods for Toxics Determination)
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<p>Sampling locations of soils and plants used in the study. In each station one soil sample and three plant species have been collected.</p>
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<p>Soil clustering after principal component analysis (PCA). The input data were the soil variables of granulometry, OM, IM, and total heavy metals concentration.</p>
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<p>(<b>A</b>) Table: Linear regression between total Ni concentration in soil and Ni in <span class="html-italic">P. annua</span> shoots. Plot: recalculated total soil Ni by the model, input data derived from the linear relation between total Ni in soil, and Ni in plant. Blue dots: forecasted soil Ni concentrations in calibration mode (all soil data were used as input). Red dots: forecasted soil Ni concentrations in cross-validation mode, excluding one soil data at a time (leave-one-out mode). (<b>B</b>) <a href="#molecules-24-02813-t002" class="html-table">Table 2</a>: Linear regression between bioavailable Ni concentration in soil and Ni in <span class="html-italic">P. annua</span> shoots. Plot: Recalculated total soil Ni by the model; input data are derived from the linear relation between total Ni in soil and Ni in plant. Blue dots: forecasted soil Ni concentrations in calibration mode (all soil data were used as input). Red dots: forecasted soil Ni concentrations in cross-validation mode, excluding one soil data at a time (leave-one-out mode).</p>
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<p>(<b>A</b>) Table: Linear regression between total Ni concentration in soil and Ni in <span class="html-italic">S. vulgaris</span> shoots. Plot: recalculated total soil Ni by the model, input data derived from the linear relation between total Ni in soil and Ni in plant. Blue dots: forecasted soil Ni concentrations in calibration mode (all soil data were used as input). Red dots: forecasted soil Ni concentrations in cross-validation mode, excluding one soil data at a time (leave-one-out mode). (<b>B</b>) Table: Linear regression between bioavailable Ni concentration in soil and Ni in <span class="html-italic">S. vulgaris</span> shoots. Plot: Recalculated total soil Ni by the model; input data are derived from the linear relation between total Ni in soil and Ni in plant. Blue dots: forecasted soil Ni concentrations in calibration mode (all soil data were used as input). Red dots: forecasted soil Ni concentrations in cross-validation mode, excluding one soil data at a time (leave-one-out mode).</p>
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<p>(<b>A</b>) <span class="html-italic">Senecio vulgaris</span> growing at a busy street crossing in Bologna. (<b>B</b>) <span class="html-italic">Poa annua</span> growing on the sidewalk in Milan.</p>
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22 pages, 2745 KiB  
Article
May the Inclusion of a Legume Crop Change Weed Composition in Cereal Fields? Example of Sainfoin in Aragon (Spain)
by Alicia Cirujeda, Ana Isabel Marí, Sonia Murillo, Joaquín Aibar, Gabriel Pardo and Xavier-Oriol Solé-Senan
Agronomy 2019, 9(3), 134; https://doi.org/10.3390/agronomy9030134 - 14 Mar 2019
Cited by 5 | Viewed by 4182
Abstract
Onobrychis viciifolia (Scop.) (sainfoin) is promoted in the Spanish Aragón region through the Agro-Environmental Schemes (AES) since 2007 with the aim of enhancing biodiversity. Also, in other countries, the interest in this legume crop is growing due to its rusticity and beneficial effects [...] Read more.
Onobrychis viciifolia (Scop.) (sainfoin) is promoted in the Spanish Aragón region through the Agro-Environmental Schemes (AES) since 2007 with the aim of enhancing biodiversity. Also, in other countries, the interest in this legume crop is growing due to its rusticity and beneficial effects on the soil and livestock. However, the effect of the crop on weed flora in the subsequent cereal crops has hardly been investigated yet. With this aim, weed flora has been characterised in 2011–2014 in sainfoin fields in the second and third year of establishment (S2 and S3), in cereal monocrop (CM), in cereal after sainfoin (CS) and in organic cereal fields (OC). Additionally, the soil seedbank was determined in two years in CM and S3 fields. Weed species richness of emerged flora and of the soil seedbank was highest for sainfoin and lowest for CM, being intermediate for OC and CS regardless of the sampling year. The most feared weed species in winter cereal did not increase by growing sainfoin or in CS compared to CM. Curiously, summer annuals dominated in the soil seedbank. Sainfoin fields cause thus a shift in the weed flora, which does not seem to damage subsequent cereal crops provided fields are mouldboard ploughed after sainfoin. Full article
(This article belongs to the Special Issue Weed Management in Annual and Perennial Cropping Systems)
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<p>Map showing the surveyed fields. S2: sainfoin in the second year, S3: sainfoin in the third year, CS: sainfoin after cereal, OC: organic cereal, CM: cereal monocrop. The rest of OC fields were located in Fuentes Calientes, approximately 20 km south and are not included in the Figure to facilitate visualisation.</p>
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<p>Mean, maximum and minimum monthly temperatures (°C) and monthly rainfall (mm) of the data collected in the four survey years in Calamocha (Spain) [<a href="#B44-agronomy-09-00134" class="html-bibr">44</a>].</p>
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<p>Species relative frequency and mean abundance when present in cereal monocrop fields (CM). Data of years 2011–2014 pooled together. Named species are the most abundant and most frequent ones.</p>
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<p>Species relative frequency and mean abundance when present in organic cereal fields (OC). Data of years 2013–2014 pooled together. Named species are the most abundant and most frequent ones.</p>
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<p>Species relative frequency and mean abundance when present in cereal fields after cropping sainfoin (CS). Data of years 2011–2014 pooled together. Named species are the most abundant and most frequent ones.</p>
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<p>Species relative frequency and mean abundance when present in sainfoin fields in their second year of establishment (S2). Data of years 2011–2014 pooled together. Named species are the most abundant and most frequent ones.</p>
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<p>Species relative frequency and mean abundance when present in sainfoin fields in their third year of establishment (S3). Data of years 2011–2014 pooled together.</p>
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<p>CCA analysis graph. CM: cereal monocrop, CS: cereal after sainfoin, OC: organic cereal, S2: sainfoin second year, S3: sainfoin third year.</p>
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<p>Nonmetric multidimensional scaling ordination based on the floristic similarities depending on the crop type of 108 fields.</p>
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