基于红外光谱的苹果叶病害的快速诊断

基于傅里叶变换红外光谱技术,利用光谱检索的方法对苹果叶病害进行病害类型的鉴别研究。测试了正常苹果叶片和4种病害叶片共75份样本的红外光谱,光谱显示,各类样品的红外光谱非常相似,主要由纤维素、木质素、蛋白质和脂类的吸收带组成。利用omnic8.5软件依次建立了由每类样品的平均红外光谱、一阶导数光谱和二阶导数光谱组成的光谱库Lib1、Lib2、Lib3。各样品红外光谱分别与光谱库Lib1进行专家检索和绝对微分差算法检索,专家检索的正确率为80%,绝对微分差检索的正确率为82.7%。各样品红外光谱的一阶导数光谱和二阶导数光谱分别与光谱库Lib2、Lib3在全谱范围进行绝对微分差检索,基于一阶导数光谱的检索正确率为93.3%,二阶导数光谱的检索正确率为82.7%。结果表明:基于一阶导数红外光谱的绝对微分差算法的检索更适合于苹果叶病害的鉴别。基于红外光谱技术的光谱检索的方法能较好地鉴别苹果叶病害,有望成为简便、快捷、低成本的植物病害的鉴别方法。

Diagnosis of Diseases of Apple Based on Fourier Transform Infrared Spectroscopy

Fourier Transform Infrared Spectroscopy was used to identify healthy and four kinds of disease apple leave.The results show the spectra of apple leave are mainly composed of the absorption of cellulose,lignin,protein and aliphatic compound.For the purpose of enhancing the spectral resolution,the first-derivative spectra and second-derivative spectra for all samples were taken by the software omnic8.5,and three spectra libraries were constructed.The library Lib1 includes of the average spectra of each specimen,while Lib2 and Lib3 were constructed from the first-derivative spectra and second-derivative spectra of average spectra,separately.The expert search and absolute differential difference search of the spectra are performed with the library Lib1,and yield correct rate of 80% and 82.7%,respectively.The absolute differential difference search of the first-derivative spectra and second-derivative spectra was carried out with Lib2 and Lib3,and shows correct rate of 93.3% for the former and 82.7% for the later.The results show that the first-derivative spectra retrieval of absolute differential difference algorithm is more suitable for diagnosing disease of apple.