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EN
Oxidative stress and senescence have been shown to participate in the toxicity mechanism of auxin herbicides in the leaves and roots of sensitive plants. However, their role in stem toxicity has not been studied yet. In this work, we report the effect of foliar or root applications of the auxin herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) on the parameters of oxidative stress and senescence of stems of pea (Pisum sativum L.) plants. Contrary to their effect on the pea leaves, in the stems 2,4-D applications did not cause oxidative stress, as shown by the parameters of lipid peroxidation, protein carbonyls, and total and protein thiols. Moreover, they inhibited the superoxide radical (O₂⁻)-producing xanthine oxidase (XOD) activity and stimulated the antioxidant activities of catalase (CAT), guaiacol peroxidase (GPOX), ascorbate peroxidase (APX), glutathione reductase (GR), glutathione S-transferase (GST) and Krebs cycle NAD⁺-isocitrate dehydrogenase (IDH). Applications of 2,4-D also did not induce senescence in the pea stems, as shown by the increase of proteins, the lack of stimulation of proteolytic activity, and the inhibition of senescence-related isocitrate lyase (ICL) activity. However, they stimulated the H₂O₂-producing acyl-CoA oxidase (ACOX) activity of fatty acid beta oxidation. Results suggest that oxidative stress and senescence are not involved in the mechanism of toxicity of 2,4-D in the stems of pea plants, and that these phenomena are not whole-plant toxicity mechanisms for auxin herbicides in susceptible plants. Results also suggest that the effect of 2,4-D on the oxidative metabolism of pea plants might be organ-specific.
2
Content available remote A quasi-LPV model for gain-scheduling canal control
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EN
In this paper, a quasi-linear parameter-varying (quasi-LPV) model for canal control is proposed. This model relates the downstream level with the gate opening and takes into account the non-linearity, the variation of the model parameters and the dependence with the operating point. Thus, this kind of a model represents in a more accurate way the canal behavior than a linear time invariant (LTI) model. Moreover, it is suitable as for the conventional gain-scheduling as for a rigorous and formal (LPV or fuzzy) gain-scheduling control design using linear matrix inequality (LMI) tools. Finally, the proposed LPV model has been used to design a conventional gain-scheduling (GS) PI controller and tested on a single pool canal.
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