铅气溶胶胁迫下茶树叶片生理生化指标变化及光谱快速检测

Changes of physiological and biochemical indexes of tea plant leaves under lead aerosol stress and their rapid spectral detection

茶树作为多年生叶用植物,在铅气溶胶胁迫下的生理生化指标变化和铅累积效应亟待研究。本文以铅气溶胶方式模拟大气污染环境,研究‘乌牛早’与‘迎霜’2个品种茶树在铅气溶胶胁迫下根、茎、叶各器官的铅累积情况以及叶片中光合色素和抗氧化物的变化规律,并结合傅里叶变换红外(Fourier transform infrared, FTIR)光谱技术建立各指标的快速检测模型。结果表明:在正常环境条件下茶树叶片的铅含量极少,符合食品安全国家标准,根的铅含量远高于叶,证明在正常环境条件下土壤-根途径是茶树积累铅的主要途径。随着胁迫时间的延长,高质量浓度铅胁迫组叶片的铅含量显著高于茎和根,证明存在大气-叶面吸收途径,高质量浓度铅胁迫组叶片中铅含量最高可达无铅处理组的14倍;在胁迫试验的42 d中,叶片的光合色素含量与抗坏血酸含量在胁迫的前中期不断增加,而在胁迫的中后期不断减少,谷胱甘肽含量整体处于上升趋势。分别采用支持向量机(support vector machine, SVM)与人工神经网络(artificial neural network, ANN)建立了基于中红外光谱特征波段的生理生化指标定量预测模型,两者均可实现铅气溶胶胁迫下茶树生理生化指标的快速检测,并且ANN模型的效果普遍优于SVM模型。其中,叶绿素a的ANN定量模型得到了最佳预测效果,在预测集中的相关系数可达0.810,均方根误差可达0.032 mg/g。综上所述,铅气溶胶胁迫会导致茶树体内铅的累积以及生理生化指标的显著变化,基于FTIR光谱技术可实现茶树生理生化指标的快速检测,有望构建茶树受铅气溶胶胁迫的快速诊断方法。

As a perennial foliage plant, the changes of physiological and biochemical indexes of tea plant under lead aerosol stress and the lead accumulation effect need to be studied urgently. In the present study, the lead aerosol was used to simulate atmospheric pollution, and the lead accumulation in roots, stems, and leaves as well as the changes of photosynthetic pigments and antioxidants in leaves of ’Wuniuzao’ and ’Yingshuang’ tea plants were evaluated. Then the model for the rapid detection of each index was established based on Fourier transform infrared(FTIR) spectroscopy. The results showed that the lead content of tea plant leaves in the normal environment was very low, which met the national food safety standards. The lead content of roots was much higher than that of leaves, which proved that the soil-root pathway was the main way for tea plants to accumulate lead in the normal environment. With the increase of stress time, the lead content in the leaves of high concentration lead stress group was significantly higher than that in the stems and roots, which proved that there was an air-leaf absorption pathway, and high concentration lead stress group was up to 14 times that of no lead treatment group. In addition,the photosynthetic pigment and ascorbic acid contents increased initially and then decreased, whereas glutathione content basically increased during the entire 42 days. Support vector machine(SVM) and artificial neural network(ANN) were used to establish quantitative prediction models for monitoring the physiological and biochemical indexes based on the characteristic wave-band of the mid-infrared spectrum, proving that the mid-infrared spectrum could be a potential approach for the rapid detection of physiological and biochemical indexes in tea plants under the lead aerosol stress, and the ANN model showed better effects than the SVM model. The ANN quantitative model of chlorophyll a obtained the best prediction effect, of which the best correlation coefficient of prediction set(rp) could reach 0.810, and the root-mean-square error of prediction set(RMSEp) was 0.032 mg/g. The above results indicate that lead aerosol stress could cause the accumulation of lead and result in the significant changes of physiological and biochemical indexes in tea plants, and the FTIR spectroscopy is a reliable method for the rapid detection of physiological and biochemical indexes in tea plants under the lead aerosol stress.