Monday, 6 October 2008
George R. Brown Convention Center, Exhibit Hall E
Developing functional algorithms for various crop growth processes as affected by multiple environmental factors is pivotal for modeling. The objective of this study is to describe the concept of Environmental Productivity Index (EPI), and its effectiveness in quantifying stress effects on crop growth and in modeling using cotton as a model crop. Several experiments were conducted in a sunlit Soil-Plant-Atmosphere-Research facility. Temperature, atmospheric CO2, water, ultraviolet-B radiation and nutrients were varied systematically and cotton organ growth and abiotic variables were measured and quantified. Potential growth, defined as the rate of crop growth processes occurring under range of temperatures under optimum water, nutrient and zero UV-B radiation levels were measured and estimated. Then, algorithms were developed for simulating various stress factor effects, known as EPIs to decrease the potential crop growth rates. The EPI indices for each environmental factor range from 0, when a given environmental stress is totally limiting a process, to 1, when it does not limit that process. These indices represent the fractional limitation due to the environmental stress effects on crop growth processes. The utility of this concept in the real-world situation was further tested by incorporating these concepts into a processes-level cotton model and comparing predictions with field measurements across several environments and management scenarios.