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alcohol dehydrogenase/soijapapu
Linkki tallennetaan leikepöydälle
Sivu 1 alkaen 17 tuloksia
Alcohol Dehydrogenase and Pyruvate Decarboxylase Activity in Leaves and Roots of Eastern Cottonwood (Populus deltoides Bartr.) and Soybean (Glycine max L.).
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Pyruvate decarboxylase (PDC, EC 4.1.1.1) and alcohol dehydrogenase (ADH, EC 1.1.1.1) are responsible for the anaerobic production of acetaldehyde and ethanol in higher plants. In developing soybean embryos, ADH activity increased upon imbibition and then declined exponentially with development, and
Low Temperature Effects on Soybean (Glycine max [L.] Merr. cv. Wells) Mitochondrial Respiration and Several Dehydrogenases during Imbibition and Germination.
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The influence of low temperature on soybean (Glycine max [L.] Merr. cv. Wells) energy transduction via mitochondrial respiration and dehydrogenases was investigated in this study during imbibition and germination. Mitochondria were isolated from embryonic axes of seeds treated at 10 and 23 C
Molecular characterization of the soybean alcohol dehydrogenase gene family amplified in vitro by the polymerase chain reaction.
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Soybean (Glycine max) alcohol dehydrogenase (ADH) cDNAs were amplified in vitro from total RNA by the polymerase chain reaction (PCR). The amplification strategy involved first strand cDNA synthesis from anaerobic cotyledon total RNA using an 18-thymidine primer. The second strand cDNA primer was a
High performance liquid chromatography method for the determination of cinnamyl alcohol dehydrogenase activity in soybean roots.
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This study proposes a simple, quick and reliable method for determining the cinnamyl alcohol dehydrogenase (CAD; EC 1.1.1.195) activity in soybean (Glycine max L. Merr.) roots using reversed-phase high performance liquid chromatography (RP-HPLC). The method includes a single extraction of the tissue
A mechanistic study on the toxic effect of copper oxide nanoparticles in soybean (Glycine max L.) root development and lignification of root cells.
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Copper oxide nanoparticles (CuONPs) are widely used in several products and their release into the environment can cause toxicity to major food crops. In this study, toxic responses as a result of CuONPs exposure were studied in soybean (Glycine max L.) seedlings. The plants were grown in 1/2
Biotransformation of 6:2 fluorotelomer alcohol by the whole soybean (Glycine max L. Merrill) seedlings.
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Fluorotelomer alcohols (FTOHs) are important precursors of perfluorocarboxylic acids (PFCAs) in the environment and biota. With the growing application of 6:2 FTOH [F(CF2)6CH2CH2OH] in product formulation, it is becoming increasingly urgent to investigate
Uptake, Translocation, and Metabolism of 8:2 Fluorotelomer Alcohol in Soybean (Glycine max L. Merrill).
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Biotransformation of fluorotelomer alcohols (FTOHs) is widely considered as an additional source of perfluorocarboxylic acids (PFCAs) in environmental biota. Compared with the extensive studies conducted in animals and microbes, biotransformation pathways of FTOHs in plants are still unclear. In
Soybean (Glycine max) root lignification induced by ferulic acid. The possible mode of action.
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Ferulic acid, in the form of feruloyl CoA, occupies a central position as an intermediate in the phenylpropanoid pathway. Due to the allelopathic function, its effects were tested on root growth, H(2)O(2) and lignin contents, and activities of cinnamyl alcohol dehydrogenase (CAD, EC 1.1.1.195) and
Characterization of a novel flooding stress-responsive alcohol dehydrogenase expressed in soybean roots.
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Alcohol dehydrogenase (Adh) is the key enzyme in alcohol fermentation. We analyzed Adh expression in order to clarify the role of Adh of soybeans (Glycine max) to flooding stress. Proteome analysis confirmed that expression of Adh is significantly upregulated in 4-day-old soybean seedlings subjected
Purification and properties of isoenzymes of cinnamyl-alcohol dehydrogenase from soybean-cell-suspension cultures.
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Two isoenzymes of an NADP+ -dependent cinnamyl alcohol dehydrogenase and an NAD+ - dependent aliphatic alcohol dehydrogenase were extracted from cell suspension cultures of soybean (Glycine max L., var. Mandarin) which form lignin during growth. These enzymes could be separated from each other by
Foliar application of silicon improves stem strength under low light stress by regulating lignin biosynthesis genes in soybean (Glycine max (L.) Merr.)
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In order to improve soybean's resistance to lodging, silicon (Si) solutions at concentrations of 0,100, 200,300 mg kg-1 were applied during the seedling stage. The Si accumulation in different parts of the plants, the photosynthetic parameters of leaves and chlorophyll content, the stem
Comparative effects of L-DOPA and velvet bean seed extract on soybean lignification.
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Velvet bean (Mucuna pruriens) is an efficient cover forage that controls weeds, pathogens and nematodes, and the non-protein amino acid L-3,4-dihydroxyphenylalanine (L-DOPA) is its main allelochemical. The effects of 3 g L-1 of an aqueous extract of velvet bean seeds, along with 0.5 mM L-DOPA for
Enzymes for acetaldehyde and ethanol formation in legume nodules.
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Soybean (Glycine max L. var. Wilkin) nodules contain acetaldehyde and ethanol. The cytosol of soybean and other legume nodules contains pyruvic decarboxylase (EC 4.1.1.1) and alcohol dehydrogenase (EC 1.1.1.1). Some of the properties of these enzymes from soybean nodules are described. Their
Developmental regulation of enzymes of sucrose and hexose metabolism in effective and ineffective soybean nodules.
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Soybean (Glycine max) nodules formed by inoculation with either an effective strain or an ineffective (noninvasive, nodule-forming) strain of Bradyrhizobium japonicum were assayed for changes in developmental patterns of carbon metabolic enzymes of the plant nodule cells. Of the enzyme activities
High-throughput peptide mass fingerprinting of soybean seed proteins: automated workflow and utility of UniGene expressed sequence tag databases for protein identification.
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Identification of anonymous proteins from two-dimensional (2-D) gels by peptide mass fingerprinting is one area of proteomics that can greatly benefit from a simple, automated workflow to minimize sample contamination and facilitate high-throughput sample processing. In this investigation we outline
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