Modeling Differential Growth in Switchgrass Cultivars Across the Central and Southern Great Plains

Autor: Timothy H. Keitt, Kathrine D. Behrman, James R. Kiniry
Rok vydání: 2014
Předmět:
Zdroj: BioEnergy Research. 7:1165-1173
ISSN: 1939-1242
1939-1234
DOI: 10.1007/s12155-014-9450-8
Popis: Switchgrass (Panicum virgatum L.) has been recognized as a potential biofuel crop, because it is adapted to a wide range of environmental and climatic conditions. Zones of adaptation for many switchgrass cultivars are well documented and attributed to local adaptation to the temperature and photoperiod at the location of origin. The objective of this study is to develop cultivar-specific growth parameters for the Agricultural Land Management and Numerical Assessment Criteria (ALMANAC) model based on location of origin and use these parameters to predict the biomass production of two lowland cultivars (Alamo and Kanlow) and two upland cultivars (Blackwell and Cave-in-Rock) in the central and southern Great Plains (TX, AR, LA, OK, KS, and MO). The plant parameters adjusted for each cultivar’s origin include average growing season temperature (22–27 °C), photoperiod at growth onset (11.46–13.12 h), maximum number of heat units (1,500–2,300), maximum leaf area index (6–12), and light extinction coefficient (0.33–0.50). The absolute difference between the average simulated and measured yields across all seven field locations for each cultivar is less than 0.5 Mg ha−1. Performance of the cultivar-specific parameters varies by location, but the parameters do a reasonable job of estimating the average yield (less than 15 % difference) of each cultivar for a majority of field locations. In addition, regional simulations of the four cultivars each show realistic spatial variation in yield across the central and southern Great Plains. The parameters derived in this project for the ALMANAC model provide a tool for optimizing choice of switchgrass cultivar on different soils, in different climates, and with different management across large geographic regions.
Databáze: OpenAIRE
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