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首页> 外文期刊>International Journal of Phytoremediation >POTENTIAL OF THE AQUATIC FERN AZOLLA FILICULOIDES IN BIODEGRADATION OF AN AZO DYE: MODELING OF EXPERIMENTAL RESULTS BY ARTIFICIAL NEURAL NETWORKS
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POTENTIAL OF THE AQUATIC FERN AZOLLA FILICULOIDES IN BIODEGRADATION OF AN AZO DYE: MODELING OF EXPERIMENTAL RESULTS BY ARTIFICIAL NEURAL NETWORKS

机译：Azo染料生物降解的水生蕨类植物丝素的潜力：人工神经网络模拟实验结果

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摘要

The potential of an aquatic fern, Azolla filiculoides, in phytoremediation of a mono azo dye solution, C.I. Acid Blue 92 (AB92), was studied. The effects of operational parameters such as reaction time, initial dye concentration, fern fresh weight, pH, temperature and reusability of the fern on biodegradation efficiency were investigated. The intermediate compounds produced by biodegradation process were analyzed using GCMS analysis. An artificial neural network (ANN) model was developed to predict the biodegradation efficiency. The findings indicated that ANN provides reasonable predictive performance (R2 = 0.961). The effects of AB92 solutions (10 and 20mg L1) on growth, chlorophylls and carotenoids content, activity of antioxidant enzymes such as superoxide dismutase, peroxidase and catalase and formation of malondialdehyde were analyzed. AB92 generally showed inhibitory effects on the growth. Moreover, photosynthetic pigments in the fronds significantly decreased in the treatments. An increase was detected for lipid peroxidation and antioxidant enzymes activity, suggesting that AB92 caused reactive oxygen species production in Azolla fronds, which were scavenged by induced activities of antioxidant enzymes.
机译：水生蕨，azolla丝状素，在单氮杂染料溶液的植物修复中的潜力，C.I.研究了酸蓝92（AB92）。研究了诸如反应时间，初始染料浓度，蕨类植物新鲜重量，pH，温度和可重复用来对生物降解效率的效果的影响。通过GCMS分析分析通过生物降解过程产生的中间化合物。开发了一种人工神经网络（ANN）模型来预测生物降解效率。调查结果表明，ANN提供合理的预测性能（R2 = 0.961）。分析了AB92溶液（10和20mg L1）对生长，叶绿素和类胡萝卜素含量的影响，抗氧化酶如超氧化物歧化酶，过氧化物酶和过氧化氢酶以及形成丙二醛的活性。 AB92通常表现出对生长的抑制作用。此外，在治疗中，叶片中的光合色素显着降低。针对脂质过氧化和抗氧化酶活性检测到增加，表明AB92引起了ZOLORA叶片中的反应性氧物种，通过诱导抗氧化酶的活性清除。

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