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Title:   Author  item
                                            Kiniry, Jamesitem
                                            Johnson, Mari-Vaughnitem
                                            Mitchell, Robert

                                                         - *Rob*item
                                            Vogel, Kennethitem
                                            KAISER, JERRY - Natural Resources Conservation Service (NRCS, USDA)item
                                            BRUCKERHOFF, STEVE - Natural Resources Conservation Service (NRCS, USDA)item
                                            CORDSIEMON, RON - Natural Resources Conservation Service (NRCS, USDA)
  Submitted to: Agronomy Journal
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 10/5/2010
                                    Publication  Date: 1/10/2011
                                    Citation: Kiniry, J.R., Johnson, M., Mitchell, R., Vogel, K.P., Kaiser, J., Bruckerhoff, S.B., Cordsiemon, R.L. 2011. Switchgrass leaf area index and light extinction coefficients. Agronomy Journal. 103(1):119-122.Interpretive Summary: Computer models that predict plant production simulation often depend on accurate simulation or measurement of leaf light interception.  With the recent interest in converting large tracts of land to biofuel species cropping, modeling vegetative yield with greater accuracy has become more imperative. We investigated the stability of the light extinction coefficient (k) in Beer’s Law to identify sources of error that might affect simulations of biomass yields for the important biofuel species switchgrass (Panicum virgatum L.).  Data used included measurements on Alamo switchgrass for 56 dates over multiple years at Temple, TX and single date measurements on various switchgrass cultivars and Miscanthus (Miscanthus X giganteus) at Lincoln, NE and Elsberry, MO.  Variability in k values was not related to fraction of light intercepted , time of day, or incident light level.  Only the magnitude of leaf area index (LAI) showed a significant impact on the k value.  The mean k value for the pooled Alamo switchgrass data at Temple (k=-0.37) was similar to the previously published k value for Alamo switchgrass (k=-0.33) and similar to Alamo k values in Nebraska (k=-0.31) and Missouri (k=-0.38).  Other switchgrass cultivars showed k values similar to Alamo’s in Nebraska (mean k=-0.29), but were higher than Alamo’s in Missouri (mean k=-0.89). However, the LAI values for non-Alamo cultivars at Missouri were lower (mean LAI = 3.9) than they were at Nebraska (mean LAI = 14.3).  We conclude that, of the potential sources of variability explored, only LAI affected k, with higher LAI values associated with lower k values.  Beer’s Law promises to continue to be a valuable system of simulating fraction of light interception of Alamo switchgrass and other important biofuel grasses.
                                Technical Abstract: Biomass production simulation modeling for plant species is often dependent upon accurate simulation or measurement of canopy light interception and radiation use efficiency.  With the recent interest in converting large tracts of land to biofuel species cropping, modeling vegetative yield with greater accuracy has become more imperative. We investigated the stability of the light extinction coefficient (k) in Beer’s Law to identify sources of error that might affect simulations of biomass yields for the important biofuel species switchgrass (Panicum virgatum L.)   Data used included measurements on Alamo switchgrass for 56 dates over multiple years at Temple, TX and single date measurements on various switchgrass cultivars and Miscanthus (Miscanthus X giganteus) at Lincoln, NE and Elsberry, MO.  Variability in k values was not related to fraction of light intercepted (P=0.86), time of day (P=0.48), or incident solar radiation (P=0.09).  Only the magnitude of leaf area index (LAI) showed a significant impact on the k value (P=0.0001).  The mean k value for the pooled Alamo switchgrass data at Temple (k=-0.37) was similar to the previously published k value for Alamo switchgrass (k=-0.33) and similar to Alamo k values in Nebraska (k=-0.31) and Missouri (k=-0.38).  Other switchgrass cultivars showed k values similar to Alamo’s in Nebraska (mean k=-0.29), but were higher than Alamo’s in Missouri (mean k=-0.89). However, the LAI values for non-Alamo cultivars at Missouri were lower (mean LAI = 3.9) than they were at Nebraska (mean LAI = 14.3).  We conclude that, of the potential sources of variability explored, only LAI affected k, with higher LAI values associated with lower k values.  Beer’s Law promises to continue to be a valuable system of simulating fraction of light interception of Alamo switchgrass and other important biofuel grasses.


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