The Diagnosis of Components Information Distribution of Wheat Seedlings Based on the Hyperspectral Imaging

It is adopted mostly of the non-imaging spectrometer in current crop seedling monitoring, this method is greatly interfered by the soil background, makes it difficult to analyze the partial area nutritional status of the seedlings. In this study, we took advantage of merging the image with spectrum of the imaging spectrometer, to analyze the canopy, individuals, different size of leaves, characteristics of different regions of the wheat seedlings under the condition of salt stress, to diagnose the distribution of its chlorophyll composition information. We collected the imaging spectrum of 126 wheat samples in the wavelength range of 400 ~1000 nm, selected the average spectrum, exerted Correlation Analysis on the spectrum of wheat seedlings with the SPAD value, It could be seen that the biggest absolute value of the correlation coefficient was at 693 nm, which was considered as the characteristics wavelength of wheat seedlings. To establish the linear regression model using this wavelength and substituted 1the reflectance data of each point into the model, then we got the SPAD value of each point, to form the relative content distribution map of chlorophyll, whereby to diagnose the distribution of seedlings component. The results showed that: Hyper spectral imaging could reflect the reflectance differences of wheat seedlings under different salt stress treatments, through extracting the spectral reflectance curve leaves of single wheat seedlings in different parts of the different leaves and single leaf base, the midst of leaves and tip in the plant, from the results of filling map we could intuitively see the leaves’ chlorophyll distribution in different parts. It indicated that hyper spectral imaging can characterize the seedlings situation of different plants, also could characterize the characteristics of different district of leaves. The results indicated that hyper spectral imaging were suitable for the non-invasive detection of chlorophyll content of wheat seeding and it has potential for precise diagnosing of the growing status of wheat seeding.