基于可见-近红外光谱的植物叶绿素含量无损检测方法研究

Abstract

叶绿素含最足植物营养胁迫、光合作用能力和生长状况的良好指示剂.实时、可靠的作物营养诊断是进行科学施肥管理的基础,也是实施精细农业的关键技术之一.文章提出了一种应用可见-近红外光谱技术检测植物叶绿素含量的方法.采用透反射测样方式获取了植物叶片的可见-近红外光谱,并对获得的500～900 nm光谱数据进行平滑、一阶微分以及小波变换等预处理,然后采用偏最小二乘法(PLS)建立了植物叶片叶绿素含量与叶片吸收光谱的定量分析模型,最后利用该模型对预测集样本进行预测.预测集中样本的预测值与标准值之间的相关系数为0.93,预测均方根误差为1.1 SPAD.实验结果表明,利用可见-近红外光谱检测叶片叶绿素含量是可行的,这对今后实现快速无损榆测植物叶绿素含量具有重要的指导意义.

In the present paper a method based on Vis/NIR spectral analysis technology was applied to the nondestructive meas-urement of plant chlorophyll content. Firstly, the Vis/NIR spectra in the wavelength range from 500 to 900 nm of the plant leav-es were acquired from 35 samples by transmittance and reflectance method, and then three different mathematical treatments were used in original spectra data pretreatment to decrease the noise: moving average smoothing with the segment size 5, first Savitzky-Golay derivative, and wavelet transform (WT) way. Secondly, a total of 35 samples were examined in the test, in which 23 samples were selected randomly for model building and the other 12 for model prediction, then partial least squares (PLS) method was used to develop the quantitative analysis model for chlorophyll content with absorbance spectroscopy, and 7 principal components (PCs) were selected. Finally, this model was used to predict the chlorophyll content of 12 unknown leaf samples in prediction collection. The experiment result indicated that the better prediction performance was achieved with the correlation coefficient between the prediction values and the truth values being 0. 93, and the root mean squared error of predic-tion is about 1.1 SPAD. It could be concluded that it is feasible to measure plant chlorophyll content based on visible/near infra-red (Vis/NIR) spectroscopy. And it is also significant in realizing rapid and nondestructive measurement of chlorophyll contentin the future.