363-7A Web-Based Tool for Evaluating the Potential of Sugarcane As a Biofuel Crop Through the Use of a Semi-Mechanistic Model of Plant Growth.
See more from this Division:
C03 Crop Ecology, Management & Quality
See more from this Session:
Crop Ecology, Management and Quality
Wednesday, October 24, 2012: 9:30 AM
Duke Energy Convention Center, Junior Ballroom A, Level 3
Deepak Jaiswal, Energy Biosciences Institute, University of Illinois, Urbana, IL, Stephen Long, Energy Biosciences Institute, UIUC, Urbana, IL, German A. Bollero, University of Illinois-Urbana-Champaign, Urbana, IL and Fernando Miguez, Department of Agronomy, Iowa State University, Ames, IA
Sugarcane is an important bioenergy crop in Brazil, and could potentially be grown commercially in the southeastern USA to meet the demand of feedstock for biofuel production in the US. Total acreage under sugarcane cultivation is expected to increase in order to meet the rising demand of biofuel. Expansion of sugarcane cultivation area critically depends on many factors, including yield potential of a site. In the absence of field trial data, usage of process-based plant growth models becomes essential in evaluating yield potential of newly developed sugarcane varieties (e.g., Energycane, Miscane, etc., for ligno-cellulosic ethanol production) under a wide range of soil and climatic conditions. Parallel evaluation of model-predicted yields and regional field trials of these second-generation feedstocks would be doubly beneficial to not only identify suitable land areas, but also to provide guidelines for the development of new varieties.
A generic plant productivity model was adapted to model growth of sugarcane. The model was parameterized and calibrated for sugarcane (RB72454) in Brazil. Multiple sites (9) in Brazil were used for the validation of model-predicted yields. Thereafter, the model was used to predict regional maps of sugarcane yields in Brazil and southeastern USA.
A web interface was developed to visualize annual yields for an area of interest as predicted by the model. In addition, the web- interface is linked to a soil and climate database that allows non-expert users to run the model. This web interface can potentially be used for: (1) implementing corrective measures to reduce the risk of crop failure due to adverse weather conditions (2) analyzing phenotypic variations in traits and model-predicted yields over a wide range of soil and climatic conditions.
See more from this Division:
C03 Crop Ecology, Management & Quality
See more from this Session:
Crop Ecology, Management and Quality