This publication presents a GIS-based approach for revising the definitions of global maize production environments, called “mega-environments” (MEs), used by CIMMYT and its partners. A cluster analysis was performed on climate data, representing a four-month growing season, for key maize producing locations. Assuming rainfed production, the onset of the growing season was determined based on the month when the ratio of precipitation over potential evapotranspiration exceeds 0.5. Diagnostic criteria for mapping MEs were based on cluster analysis results and expert knowledge. The resulting maps can be used to select appropriate target environments for maize germplasm and trials, as well as in priority setting and site selection for global maize breeding programs.

Research data is expensive and precious, yet it is seldom fully utilized due to our ability of comprehension. Graphical display is desirable, if not absolutely necessary, for fully understanding large data sets with complex interconnectedness and interactions. The newly developed GGE biplot methodology is a superior approach to the graphical analys

Your all-in-one guide to corn. This book provides practical advice on planting techniques and rates, seed production, treating plant diseases, insect infestation and weeds, harvesting, processing, and worldwide utilization. This is the fourth, and final, volume in the series of comprehensive references on the major crops of the world. Covers new biotechnology techniques for plant breeding and pest management Provides practical advice on planting techniques and rates, seed production, treating plant diseases, insect infestation and weeds, harvesting, processing and worldwide utilization.

The purpose of this book is to examine the nature of and relationship between the knowledge of farmers and of scientists, and how these can be best integrated in plant breeding.

Trends in population growth suggest that global food production is unlikely to satisfy future demand under predicted climate change scenarios unless rates of crop improvement are accelerated. This book provides an overview of the essential disciplines required for sustainable crop production in unpredictable environments.

Mathematical models are being used more and more widely to study complex dynamic systems (global weather, ecological systems, hydrological systems, nuclear reactors etc. including the specific subject of this book, crop-soil systems). The models are important aids in understanding, predicting and managing these systems. Such models are complex and imperfect. One fundamental research direction is to seek a better understanding of how these systems function, and to propose mathematical expressions embodying that understanding. However, this is not sufficient. It is also essential to have tools (often mathematical and statistical methods) to aid in developing, improving and using the models built from those equations. The book is specifically concerned with the application of methods to crop models, but much of the material is also applicable to dynamic system models in other fields. The goal of this book is to fill that gap.* State-of-the-art methods explained simply and illustrated specifically for crop models* Parameter estimation – applying statistical methods to the complex case of crop models, including Bayesian methods * Includes model evaluation, understanding and estimating prediction error* Offers a unique data assimilation by using the Kalman filter and beyond