Keru Wang

Estimation of wheat agronomic parameters using new spectral indices.

Crop agronomic parameters (leaf area index (LAI), nitrogen (N) uptake, total chlorophyll (Chl) content ) are very important for the prediction of crop growth. The objective of this experiment was to investigate whether the wheat LAI, N uptake, and total Chl content could be accurately predicted using spectral indices collected at different stages of wheat growth. Firstly, the product of the optimized soil-adjusted vegetation index and wheat biomass dry weight (OSAVI×BDW) were used to estimate LAI, N uptake, and total Chl content; secondly, BDW was replaced by spectral indices to establish new spectral indices (OSAVI×OSAVI, OSAVI×SIPI, OSAVI×CIred edge, OSAVI×CIgreen mode and OSAVI×EVI2); finally, we used the new spectral indices for estimating LAI, N uptake, and total Chl content. The results showed that the new spectral indices could be used to accurately estimate LAI, N uptake, and total Chl content. The highest R2 and the lowest RMSEs were 0.711 and 0.78 (OSAVI×EVI2), 0.785 and 3.98 g/m2 (OSAVI×CIred edge) and 0.846 and 0.65 g/m2 (OSAVI×CIred edge) for LAI, nitrogen uptake and total Chl content, respectively. The new spectral indices performed better than the OSAVI alone, and the problems of a lack of sensitivity at earlier growth stages and saturation at later growth stages, which are typically associated with the OSAVI, were improved. The overall results indicated that this new spectral indices provided the best approximation for the estimation of agronomic indices for all growth stages of wheat.

Spectrum Characteristics of Cotton Canopy Infected with Verticillium Wilt and Inversion of Severity Level

Verticillium wilt of cotton is one of the diseases of cotton with extensive occurrence and maximal harming in our country even in the world .Hyper spectrum remote sensing with the fine spectrum information has becoming the efficient method to monitor the Verticillium wilt of cotton. The research was conducted in Xinjiang, the largest cotton plant region of China. The paper used data which was collected both canopy spectrum infected with verticillium wilt and SL (severity level) in the year 2005 2006, the quantitative correlation were analyzed between SL and canopy reflectance spectrum derivative spectrum. The tested results indicated that spectrum characteristics of cotton canopy infected with verticillium wilt had better regularity with the increase of SL in different periods and varieties. Spectrum reflectance increased in visible light region (620 700nm) with the increase of the SL, which inverted in nearinfrared region, and extreme signification in 78

Evaluating the severity level of cotton Verticillium using spectral signature analysis

High spatial or spectral resolution remote sensing might be an efficient method for estimating Verticillium wilt incidence in cotton. The objectives of this study were to characterize leaf spectra and the physiological and biochemical parameters of cotton (Gossypium hirsutum) damaged by Verticillium dahliae Kleb. (simply, Verticillium) to determine the wavelengths of those leaves that were most responsive to cotton with Verticillium and to develop a spectral model to predict the severity levels (SLs) of Verticillium through evaluation of the SLs of cotton leaves with Verticillium at different growth stages using reflectance and the first derivative (FD) spectrum. The study revealed that the values of the physiological and biochemical parameters all gradually decreased with increasing SLs in cotton leaves infected with Verticillium. The spectral characteristics of cotton leaves infected with Verticillium were significant compared to healthy ones. The reflectance of cotton leaves increased with increasing SLs of SLs disease in the range of 400–2500 nm (excluding 700–900 nm). The values of FD spectrum changed significantly at the red edge of the chlorophyll absorption feature (680–740 nm). The wavelength position of the red edge shifted towards shorter wavelengths and the red-edge swing decreased with respect to increasing SLs. From this study, the raw spectral bands of 437–724 and 909–2500 nm and the FD spectra bands of 535–603 and 699–750 nm can be selected as sensitive bands for estimating the SLs of disease in cotton leaves. Inversion models have been established to estimate the SLs of cotton leaves infected with Verticillium. Of all models, the model of R 700nm/R 825nm was superior for quantitatively estimating the disease SLs of cotton leaves infected with Verticillium in practice: its root mean square error (RMSE) was 0.866 and relative error (RE) was only 0.012. Thus, both the selected wavelength ranges and the chosen reflectance models were good indicators of damage caused by Verticillium to cotton leaves. The results provide theoretical support for large-scale monitoring of cotton infected with Verticillium by air- and spaceborne remote sensing.

Monitoring Chlorophyll and Nitrogen Contents in Cotton Leaf Infected by Verticillium wilt with Spectra Red Edge Parameters

The relationship between chlorophyll (Chl) content, leaf nitrogen content (LNC) and red edge parameters were analyzed, and diagnose models of spectra red edge parameters were established for cotton leaf infected by Verticillium wilt. Results showed that: (1) Chl a, Chl b, Chl a+b content, and LNC decreased with increasing in severity level (SL) of Verticillium wilt in cotton leaves, in which Chl a showed the highest and Chl b showed the lowest decrement rate, respectively. (2) Spectrum reflectance increased with increasing severity of Verticillium wilt in the visible region (400–700 nm), near-infrared region (700–1300 nm) and short infrared region (1300–2500 nm), and significantly higher increment was detected in 525–680 nm region (P0.01). Spectrum absorption decreased significantly with increasing SL of Verticillium wilt in the visible region and short infrared region (P0.01), and which increased first and then decreased in near-infrared region. (3) Decrease of REP, Dr, Lo, Depth672, Area672 and increase of Lwidth was detected among red edge parameters, in which Area672 showed the highest and Dr showed the Lowest decrement rate, respectively. (4) There was significantly positive correlation between Chl a, Chl b, Chl a+b, LNC of cotton leaves and REP, Lo, Depth672, Area672 of red edge parameters, significantly negative correlation was found for Lwidth of red edge parameter, while no significant correlation was found for Dr of red edge parameter. (5) Diagnose models of Chl a, Chl a+b,edge parameter, while no significant correlation was found for Dr of red edge parameter. (5) Diagnose models of Chl a, Chl a+b, and LNC for Verticillium wilt in cotton leaves with the independent variables Area672, and Chl b with the independent variables Lo reached the best estimated precision (P0.01). This could diagnose severity level of Verticillium wilt in cotton leaves effectively.

A Leaf Layer Spectral Model for Estimating Protein Content of Wheat Grains

The spectral signatures of crop canopies in the field provide much information relating morphological or quality characteristics of crops to their optical properties. This experiment was conducted using two winter-wheat (Triticum aestivum) cultivars, Jingdong8 (with erect leaves) and Zhongyou9507 (with horizontal leaves). We analysiced the relation between the direction spectral characteristics and the laeves nitrogen content(LNC). The result showed that the spectral information observed at the 0° angle mainly provided information on the upper canopy and the lower layer had little impact on their spectra. However, the spectral information observed at 30° and 60° angles reflected the whole canopy information and the status of the lower layer of the canopy had great effects on their spectra. Variance analysis indicated that the ear layer of canopy and the topmost leaf blade made greater contributions to CDS. The predicted grain protein content (GPC) model by leaf layers spectra using 0° view angle was the best with root mean squares (RMSE) of 0.7500 for Jingdong8 and 0.6461 for Zhongyou9507. The coefficients of determination, R2 between measured and estimated grain protein contents were 0.7467 and 0.7599. Thus, grain protein may be reliably predicted from the leaf layer spectral model.

Spectral Characteristics of Cotton Infected with Verticillium Wilt and Severity Level of Disease Estimated Models

In order to elucidated characteristics of spectrum of cotton leaf infected with Verticillium wilt and estimated its severity level (SL) to provide theoretic foundation for further monitoring cotton Verticillium wilt at large scale using airborne and airspace remote sensing. The spectrum reflectance of cotton single leaf infected with Verticillium wilt was measured in cotton disease nursery and field at different growth phases, meanwhile, SL of single leaf infected with Verticillium wilt was investigated. The methods of first derivative spectraum were used to estimate accurately disease of cotton with Verticillium wilt when compared with the reflectance spectrum of different single leaf infected of Verticillium wilt. The results indicated that Spectral characteristic of cotton leaf of Verticillium wilt had better regularity with the increase of SL in different periods and varieties. Spectral reflectance increased significantly at visible light region (400–700nm) and near -infrared region (700–1300nm) with the increase of the SL, and specially signification at blue — violet to red regions(525–680nm). when SL got 25%, cotton leaf of Verticillium wilt could be used as a watershed and diagnosed index in early time. There were evident different characteristics of first derivative spectra in these disease leave, it changed significantly in red edge ranges(680–780nm) with different disease level, derivative spectra of red edge swing decreased, and red edge position equal moved to the blue. The thesis indicated that 434–724nm and 909–1600nm were selected out as sensitive bands region to SL of single leaf. Some inversion models for estimating cotton leaf diseased level of Verticillium wilt all reached the best significantly level. The model in which the first derivative spectra at 723nm could invert accurately the cotton leaf SL, and it may be used to forecasting the position of cotton leaf infected with Verticillium wilt in quantitatively.