Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications."

Ethylene is a simple gaseous plant hormone produced by higher plants, bacteria and fungi. Thanks to new tools that have become available in biochemistry and molecular genetics, parts of the ethylene biosynthesis, perception and signal transduction reactions have been elucidated. This knowledge has been applied to enhance the quality of a number of agronomically important crops. In Biology and Biotechnology of the Plant Hormone Ethylene, leading figures in the field provide surveys of the current state of ethylene biosynthesis and action, perception and signal transduction pathways, senescence, biotechnological control, and the involvement of ethylene in pathogenesis and stress. Audience: Indispensable to all academic, industrial and agricultural researchers as well as undergraduates and graduates in plant biology, biochemistry, genetics, molecular biology and food science.

The inflorescence of the monoecious maize plant is unique among the Gramineae in the sharp separation of the male and female structures. The male tassel at the terminus of the plant most often sheds pollen before the visual appearance of the receptive silks of th the female ear at a lateral bud, normally at the 10 leaf [I]. Earlier studies examined the ontogeny of the growing tissues beginning with the embryo in the kernel through to the obvious protuberances of the growing point as the kernel germinates. The differentiated developing soon-to-become tassel and the lateral bulges that develop into the ears on the lateral buds become apparent very early in the germinating kernel [2, 3, 46]. A certain number of cells are destined for tassel and ear development [8]. As the plant develops, there is a phase transition [\3, 16] from the vegetative lateral buds to the reproductive lateral buds. This change in phase has been ascribed to genotypic control as evidenced in the differences among different genotypes in the initiation of the reproductive [I]. The genetic control of tassel and ear initiation has been gleaned from anatomical observations. Lejeune and Bernier [I2] found that maize plants terminate the initiation of additional axillary meristems at the time of tassel initiation. This would indicate that the top-most ear shoot is initiated on the same day as the initiation of tassel development and this event signals the end of the undifferentiated growing point.

The inflorescence of the monoecious maize plant is unique among the Gramineae in the sharp separation of the male and female structures. The male tassel at the terminus of the plant most often sheds pollen before the visual appearance of the receptive silks of th the female ear at a lateral bud, normally at the 10 leaf [I]. Earlier studies examined the ontogeny of the growing tissues beginning with the embryo in the kernel through to the obvious protuberances of the growing point as the kernel germinates. The differentiated developing soon-to-become tassel and the lateral bulges that develop into the ears on the lateral buds become apparent very early in the germinating kernel [2, 3, 46]. A certain number of cells are destined for tassel and ear development [8]. As the plant develops, there is a phase transition [\3, 16] from the vegetative lateral buds to the reproductive lateral buds. This change in phase has been ascribed to genotypic control as evidenced in the differences among different genotypes in the initiation of the reproductive [I]. The genetic control of tassel and ear initiation has been gleaned from anatomical observations. Lejeune and Bernier [I2] found that maize plants terminate the initiation of additional axillary meristems at the time of tassel initiation. This would indicate that the top-most ear shoot is initiated on the same day as the initiation of tassel development and this event signals the end of the undifferentiated growing point.

Ethylene is a simple gaseous plant hormone produced by higher plants, bacteria and fungi. Thanks to new tools that have become available in biochemistry and molecular genetics, parts of the ethylene biosynthesis, perception and signal transduction reactions have been elucidated. This knowledge has been applied to enhance the quality of a number of agronomically important crops. In Biology and Biotechnology of the Plant Hormone Ethylene, leading figures in the field provide surveys of the current state of ethylene biosynthesis and action, perception and signal transduction pathways, senescence, biotechnological control, and the involvement of ethylene in pathogenesis and stress. Audience: Indispensable to all academic, industrial and agricultural researchers as well as undergraduates and graduates in plant biology, biochemistry, genetics, molecular biology and food science.

Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications."