STUDIES ON THE PROPERTIES OF SCHIFF BASE TYPE ARYLMERCURY COMPOUNDS.II ^(199)Hg NMR SPECTRA OF MERCURATED DERIVATIVES OF SUBSTITUTED BENZYLIDENEANILINES

^(199)Hg NHR spectra of 18 Schiff base type arylmercury compounds have been studied.It was further confirmed that in the molecule of XC_6H_4CH=NC_6H_3-2-HgC1-4-CH_3 there exists an intramolecular N→Hg coordination via a four-membered ring.For the series of XC_6H_4CH=NC_6H_3-2-HgCl-4-CH_3(X is a para-or mera-substituent),there is a good linear correlation between δ^(199)Hg and Hammett's o constants.The influence of substituents of C-pheny1 ring on the δ ^(199)Hg can be explained in terms of the intramolecular N→Hg coordination.

Detection of Broad Bean Diseases by Fourier Transform Infrared Spectroscopy Combined with Curve Fitting

Fourier transform infrared （FTIR） spectroscopy was used to study diseased leaves in broad bean. Results showed that the infrared spectra of different broad bean diseased leaves were similar, which were mainly made up of the vibrational absorption bands of protein,lipid and polysaccharide.There were minor differences in-cluding the spectral peak position, peak shape and the absorption intensity in the range of 1 800-1 300 cm-1. There were obvious differences among their second derivative spectra in the range of 1 800-1 300 cm-1. After the procedure of the Fourier self-deconvolution and curve fitting of health bean leaves and broad bean diseased leaves in the range of 1 700-1 500 cm-1, three sub-peaks were obtained at 1 550 cm-1 （protein amide Ⅱ band）, 1 605 cm-1 （lignin） and 1 650 cm-1 （protein amide I band）.The ratios of relative areas of the bands of amide Ⅱ, lignin, and amide I were 38.86%, 28.68% and 32.47% in the spectra of healthy leaves, respec-tively. It was distinguished from the diseased leaves （chocolate spot leaf： 15.42%, 42.98% and 41.61%, ring spot leaf：32.39%, 35.63% and 31.98%, rust leaf： 13.97%, 46.40% and 39.65%, yel owing leaf curl disease leaf： 24.01%,36.55% and 39.44%）. For sub-peak area ratios （A1 563/A1 605, A1 650/A1 605 and A1 563/A1 654）, those of four kinds of diseased leaves were smal er than that of healthy leaves, and there were also differences among four kinds of diseased leaves. The results proved that FTIR combining with curve fitting might be a potential y useful tool for detecting different kinds of broad bean diseases.

Studies on nitramide and its methyl derivatives with ab initio calculations——Ⅳ.The harmonic force field and vibrational spectra of dimethylnitramine and its isotopic derivatives

The complete harmonic vibrational force field of dimethylnitramine has been calculated at the Hartree-Fock level using 4-21G basis set.The harmonic force field was then scaled with scale factors previously derived from N-methylnitramine,and the vibrational spectrum of dimethylnitramine was computed.This apriori prediction,made with no reference to observations on dimethylnitramine, agrees with the experimental IR spectrum in gas phase with a mean deviation of 8.4 cm^(-1).Some of the scale factors were reoptimized by fitting of the computed force field to experimental data.The new set of scale factors reduced the mean deviation to 4.5 cm^(-1),and was used to predict the vibrational spectrum of deuterated form of dimethylnitramine(-6D).Dipole moment derivatives were also cal- culated and used to predict infrared intensities which are comparable with experimental values.

Discrimination of rice panicles by hyperspectral reflectance data based on principal component analysis and support vector classification

Detection of crop health conditions plays an important role in making control strategies of crop disease and insect damage and gaining high-quality production at late growth stages. In this study, hyperspectral reflectance of rice panicles was measured at the visible and near-infrared regions. The panicles were divided into three groups according to health conditions： healthy panicles, empty panicles caused by Nilaparvata lugens St^l, and panicles infected with Ustilaginoidea virens. Low order derivative spectra, namely, the first and second orders, were obtained using different techniques. Principal component analysis （PCA） was performed to obtain the principal component spectra （PCS） of the foregoing derivative and raw spectra to reduce the reflectance spectral dimension. Support vector classification （SVC） was employed to discriminate the healthy, empty, and infected panicles, with the front three PCS as the in- dependent variables. The overall accuracy and kappa coefficient were used to assess the classification accuracy of SVC. The overall accuracies of SVC with PCS derived from the raw, first, and second reflectance spectra for the testing dataset were 96.55%, 99.14%, and 96.55%, and the kappa coefficients were 94.81%, 98.71%, and 94.82%, respectively. Our results demonstrated that it is feasible to use visible and near-infrared spectroscopy to discriminate health conditions of rice panicles.

Characterization of the Rice Canopy Infested with Brown Spot Disease Using Field Hyperspectral Data

Based on the field hyperspectral data from the analytical spectral devices （ASD） spectrometer, we characterized the spectral properties of rice canopies infested with brown spot disease and selected spectral regions and bands sensitive to four severity degrees （severe, moderate, light, and healthy）. The results show that the curves＇ variation on the original and the first- and second-order de- rivative curves are greatly different, but the spectral difference in the near-infrared region is the most obvious for each level. Specifically, the peaks are located at 822, 738, and 793 nm, while the valleys are located at 402, 570, and 753 run, respectively. The sensitive regions are between 430-520, 530-550, and 650-710 nm, and the bands are 498, 539, and 673 nm in the sensitivity analysis, while they are in the ranges of 401-530, 550-730 as well as at 498 nm and 678 nm in the continuum removal.