• Journal of The Korean Society of Grassland and Forage Science
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• v.34 no.1
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• pp.15-20
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• 2014

To investigate lignification process and its physiological significance under water-deficit condition, the responses of peroxidases, polyphenol oxidase (PPO) and phenylalanine ammonia-lyase (PAL) in relation to leaf water status to the short term of water deficit treatment in the leaves with different maturities in forage rape were measured. The significant decrease in relative water content (RWC) and leaf osmotic potential (${\Psi}{\pi}$) were apparent after 5 d of water-deficit treatment. The activity of guaiacol peroxidase (GPOD), ascorbate peroxidase (APOD), coniferyl alcohol peroxidase (CPOD), and syringaldazine peroxidase (SPOD) was depressed especially in middle and old leaves when compared with that of control leaves. On the other hand, in young leaves, a significant increase in CPOD (+34%) and SPOD (+24%) activity as affected by water-deficit treatment was apparent. The activation of PAL and PPO was observed in middle and old leaves for PAL and in young and middle leaves for PPO. These results suggest that peroxidases in middle and old leaves did not involve in lignification under mild water-deficit stress, whereas CPOD and SPOD in young leaves participate in lignification by a coordination with PAL and PPO to incorporate phenol and lignin into the cell walls.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.237-247
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• 2001

In this paper, we will introduce multivariate versions of bivariate conditionally positive dependence and the partial ordering is developed among conditionally positive lower orthant dependent(CPLOD) random vectors. This permits us to measure the degree of CPLOD-ness and to compare pairs of CPLOD random vectors. Some proper ties and closure under certain statistical operations are derived.

• Wind and Structures
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• v.29 no.6
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• pp.389-403
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• 2019

In this study, two original spectral representations of stationary stochastic fields, say the continuous proper orthogonal decomposition (CPOD) and the frequency-wavenumber spectral representation (FWSR), are derived from the Fourier-Stieltjes integral at first. Meanwhile, the relations between the above two representations are discussed detailedly. However, the most widely used conventional Monte Carlo schemes associated with the two representations still leave two difficulties unsolved, say the high dimension of random variables and the incompleteness of probability with respect to the generated sample functions of the stochastic fields. In view of this, a dimension-reduction model involving merely one elementary random variable with the representative points set owing assigned probabilities is proposed, realizing the refined description of probability characteristics for the stochastic fields by generating just several hundred representative samples with assigned probabilities. In addition, for the purpose of overcoming the defects of simulation efficiency and accuracy in the FWSR, an improved scheme of non-uniform wavenumber intervals is suggested. Finally, the Fast Fourier Transform (FFT) algorithm is adopted to further enhance the simulation efficiency of the horizontal stochastic wind velocity fields. Numerical examplesfully reveal the validity and superiorityof the proposed methods.