Radiation use efficiency and leaf CO2 exchange for diverse C4 grasses

Kiniry, James R.; Tischler, C. R.; Esbroeck, G. A. Van

doi:10.1016/s0961-9534(99)00036-7

Cited by 125 publications

(119 citation statements)

References 29 publications

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“…Biomass yields greater than 28 Mg ha -1 were uncommon, but were reported for lowland ecotypes (e.g., Kanlow and Alamo) planted at fi eld sites in Alabama, Texas, and Oklahoma (Sladden et al, 1991;Kiniry et al, 2005;Th omason et al, 2004). Th e highest annual yield reported in this compilation was 39.1 Mg ha -1 for the cultivar Alamo under high fertilization (200 kg N ha -1 ) and in a year with high precipitation and temperatures (Kiniry et al, 1999). Frequency distributions for upland (Fig.…”

Section: Resultsmentioning

confidence: 70%

Biomass Production in Switchgrass across the United States: Database Description and Determinants of Yield

et al. 2010

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Fundamental to deriving a sustainable supply of cellulosic feedstock for an emerging biofuels industry is understanding how biomass yield varies as a function of crop management, climate, and soils. Here we focus on the perennial switchgrass (Panicum virgatum L.) and compile a database that contains 1190 observations of yield from 39 fi eld trials conducted across the United States. Data include site location, stand age, plot size, cultivar, crop management, biomass yield, temperature, precipitation, and information on land quality. Statistical analysis revealed the major sources of variation in yield. Frequency distributions of yield for upland and lowland ecotypes were unimodal, with mean (±SD) biomass yields of 8.7 ± 4.2 and 12.9 ± 5.9 Mg ha -1 for the two ecotypes, respectively. We looked for, but did not fi nd, bias toward higher yields associated with small plots or preferential establishment of stands on high quality lands. A parametric yield model was fi t to the data and accounted for one-third of the total observed variation in biomass yields, with an equal contribution of growing season precipitation, annual temperature, N fertilization, and ecotype. Th e model was used to predict yield across the continental United States. Mapped output was consistent with the natural range of switchgrass and, as expected, yields were shown to be limited by precipitation west of the Great Plains. Future studies should extend the geographic distribution of fi eld trials and thus improve our understanding of biomass production as a function of soil, climate, and crop management for promising biofuels such as switchgrass.

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Section: Resultsmentioning

confidence: 70%

Biomass Production in Switchgrass across the United States: Database Description and Determinants of Yield

et al. 2010

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“…15 Irrigati on application data were acquired from the 2002 and 2007 Census of Agriculture, 16,17 and the Farm and Ranch Irrigation Survey 18,19 published by the USDA and USGS. 20 Th e crop coeffi cient K c , used in estimating evapotranspiration (ET, the loss of water from the soil by evaporation and by transpiration from the crops), was compiled from the High Plains Regional Climate Center, 21 the Texas High Plains Evapotranspiration network, 22 and the previous studies of Kiniry et al 23,24 Climate in 2017 was assumed to remain the same as the historical average from 1970 to 2000. However, the irrigation demand was further adjusted from historical values to refl ect the increase of corn acreage and yield 25 (Table 6).…”

Section: Climate Irrigation Crop and Nutrient Loading Datamentioning

confidence: 99%

Investigation of biochemical biorefinery sizing and environmental sustainability impacts for conventional bale system and advanced uniform biomass logistics designs

Argo

Tan

Inman

et al. 2013

Biofuels Bioprod Bioref

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The 2011 US Billion-Ton Update 1 estimates that there are enough agricultural and forest resources to sustainably provide enough biomass to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefi nery capacity, which, in turn, depend on economics, feedstock logistics, and sustainability. A cross-functional team has examined optimal combinations of advances in feedstock supply systems and biorefi nery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. Biochemical-conversion-to-ethanol is analyzed for conventional bale-based system and advanced uniform-format feedstock supply system designs. The latter involves 'pre-processing' biomass into a higher-density, aerobically stable, easily transportable format that can supply large-scale biorefi neries. Feedstock supply costs, logistics and processing costs are analyzed and compared, taking into account environmental sustainability metrics.

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“…Subsequently, the model was extended to range simulation with multiple grass species at diverse sites (Kiniry et al, 2002). Parameters for common warm season grasses (Kiniry et al, 1999), improved grasses (Kiniry et al, 2007), and for mesquite and juniper (Kiniry & Bockholt, 1998) were developed to allow their simulation. The model has also been demonstrated as a valuable tool to assess switchgrass production for biofuels at diverse sites in the USA (Kiniry et al, 1996.…”

Section: Almanacmentioning

confidence: 99%

History of model development at Temple, Texas

Williams

Arnold

Kiniry

et al. 2008

Hydrological Sciences Journal

171

109

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Model development at Temple, Texas, USA has a long history. Prior to the actual model development research, a hydrological data collection programme was established at Riesel, Texas (about 60 km northeast of Temple) in 1937. Data collected from the Riesel watersheds during 1937-2006 have been valuable in developing and testing models at Temple, as well as at other locations. Actual modelling research began in the mid-1960s with the development of single event models that served as building blocks for the comprehensive models of today. The focus of the early models was on surface water hydrology (rainfall excess, unit hydrographs and flood routing) and sediment yield. The models currently supported at Temple (ALMANAC, EPIC, APEX and SWAT) are continuous and operate on spatial scales ranging from individual fields to river basins. These models have been used worldwide in many projects dealing with soil and water resources and environmental management.

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Radiation use efficiency and leaf CO2 exchange for diverse C4 grasses

Cited by 125 publications

References 29 publications

Biomass Production in Switchgrass across the United States: Database Description and Determinants of Yield

Biomass Production in Switchgrass across the United States: Database Description and Determinants of Yield

Investigation of biochemical biorefinery sizing and environmental sustainability impacts for conventional bale system and advanced uniform biomass logistics designs

History of model development at Temple, Texas

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