Qin Zhang

Francis J. Pierce

Agricultural automation is the core technology for computer-aided agricultural production management and implementation. An integration of equipment, infotronics, and precision farming technologies, it creates viable solutions for challenges facing the food, fiber, feed, and fuel needs of the human race now and into the future. Agricultural Automat

Fundamentals and Practices

Agricultural Automation

Oliver Schabenberger

Despite its many origins in agronomic problems, statistics today is often unrecognizable in this context. Numerous recent methodological approaches and advances originated in other subject-matter areas and agronomists frequently find it difficult to see their immediate relation to questions that their disciplines raise. On the other hand, statisticians often fail to recognize the riches of challenging data analytical problems contemporary plant and soil science provides. The first book to integrate modern statistics with crop, plant and soil science, Contemporary Statistical Models for the Plant and Soil Sciences bridges this gap. The breadth and depth of topics covered is unusual. Each of the main chapters could be a textbook in its own right on a particular class of data structures or models. The cogent presentation in one text allows research workers to apply modern statistical methods that otherwise are scattered across several specialized texts. The combination of theory and application orientation conveys ìwhyî a particular method works and ìhowî it is put in to practice. About the downloadable resources The accompanying downloadable resources are a key component of the book. For each of the main chapters additional sections of text are available that cover mathematical derivations, special topics, and supplementary applications. It supplies the data sets and SAS code for all applications and examples in the text, macros that the author developed, and SAS tutorials ranging from basic data manipulation to advanced programming techniques and publication quality graphics. Contemporary statistical models can not be appreciated to their full potential without a good understanding of theory. They also can not be applied to their full potential without the aid of statistical software. Contemporary Statistical Models for the Plant and Soil Science provides the essential mix of theory and applications of statistical methods pertinent to research in life sciences.

Contemporary Statistical Models for the Plant and Soil Sciences

Stephen L. Young

Technology is rapidly advancing in all areas of society, including agriculture. In both conventional and organic systems, there is a need to apply technology beyond our current approach to improve the efficiency and economics of management. Weeds, in particular, have been part of cropping systems for centuries often being ranked as the number one production cost. Now, public demand for a sustainably grown product has created economic incentives for producers to improve their practices, yet the development of advanced weed control tools beyond biotech has lagged behind. An opportunity has been created for engineers and weed scientists to pool their knowledge and work together to ‘fill the gap’ in managing weeds in crops. Never before has there been such pressure to produce more with less in order to sustain our economies and environments. This book is the first to provide a radically new approach to weed management that could change cropping systems both now and in the future.

Francis J. Pierce

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