Neuropeptides, InvertebrateMention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture.

Masler, Edward P.

doi:10.1002/3527600906.mcb.200400031

Cited by 2 publications

(2 citation statements)

References 81 publications

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“…spring) with increasing soil carbon benefits. Harvest yields are known to decrease because of prolonged senescence and crop damage caused by wind and snow for both crops (Lewandowski et al, 2003;Adler et al, 2006;Fike et al, 2006;Christian et al, 2008;Miguez et al, 2008;Wang et al, 2010;Maughan et al, 2012). Consequently, more of the aboveground plant biomass is allowed to enter the litter pool which decays and a portion of this pool becomes part of soil carbon.…”

Section: Discussionmentioning

confidence: 99%

Bioenergy crop greenhouse gas mitigation potential under a range of management practices

et al. 2014

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Perennial grasses have been proposed as viable bioenergy crops because of their potential to yield harvestable biomass on marginal lands annually without displacing food and to contribute to greenhouse gas (GHG) reduction by storing carbon in soil. Switchgrass, miscanthus, and restored native prairie are among the crops being considered in the corn and agricultural regions of the Midwest and eastern United States. In this study, we used an extensive dataset of site observations for each of these crops to evaluate and improve the DayCent biogeochemical model and make predictions about how both yield and GHG fluxes would respond to different management practices compared to a traditional corn-soy rotation. Using this model-data integration approach, we found 30-75% improvement in our predictions over previous studies and a subsequent evaluation with a synthesis of sites across the region revealed good model-data agreement of harvested yields (r 2 > 0.62 for all crops). We found that replacement of corn-soy rotations would result in a net GHG reduction of 0.5, 1.0, and 2.0 Mg C ha À1 yr À1 with average annual yields of 3.6, 9.2, and 17.2 Mg of dry biomass per year for native prairie, switchgrass, and miscanthus respectively. Both the yield and GHG balance of switchgrass and miscanthus were affected by harvest date with highest yields occurring near onset of senescence and highest GHG reductions occurring in early spring before the new crops emergence. Addition of a moderate length rotation (10-15 years) caused less than a 15% change to yield and GHG balance. For policy incentives aimed at GHG reduction through onsite management practices and improvement of soil quality, post-senescence harvests are a more effective means than maximizing yield potential.

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Section: Discussionmentioning

confidence: 99%

Bioenergy crop greenhouse gas mitigation potential under a range of management practices

et al. 2014

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“…This variability comes from both temporal and spatial variations in biomass composition. For example, switchgrass harvested from different geographical locations and in different seasons may have a distinct composition. , Storage conditions (e.g., dry, wet, field side, bales, loose pile, etc. ), also can cause significant variations in chemical composition and physical properties of biomass, even over relatively short time periods, and subsequently affect the total cost of the biomass over the course of a year.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective

Luo

Ray

et al. 2018

ACS Sustainable Chem. Eng.

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Feedstock price and availability are key challenges for biorefinery development. Biomass blending has been suggested as a route to overcome these limitations. However, the impacts of feedstock blending on the uncertainty in hydrolyzed sugar yields remain unclear. This study quantifies the uncertainties in the sugar yields from hydrolysis of the blends of corn stover, switchgrass, and grass clippings by considering both feedstock compositional variation and model uncertainty.The results indicate that feedstock blending reduces the uncertainties in sugar yields and delivers feedstock of more uniform quality. A 60/35/5 blend of corn stover, switchgrass, and grass clippings on average achieves a glucose yield of 32.6 g/100 g of biomass, which is comparable to those of corn stover (33.3 g/100 g) and switchgrass (32.9 g/100 g), but drastically higher than that of grass clippings (21.7 g/100 g). This same blend also achieves the lowest variance in glucose yield (2.9 g/100 g) compared to corn stover (3.1 g/100 g), switchgrass (3.3 g/100 g), and grass clippings (5.6 g/100 g). A further investigation on the breakdown of the variability of the hydrolyzed sugar yields reveals that the reduction in the variability of sugar yields for blended feedstocks is achieved by reduced feedstock compositional variation. Based on these results, the optimization of blending ratios is performed with respect to three objectives: (1) to maximize the probability of meeting the sugar yields target, (2) to maximize the expected sugar yields, and (3) to maximize sugar yields per unit feedstock expense, while satisfying constraints of feedstock availability and price. The maximized probability of meeting the sugar yield target, expected sugar yield, and glucose yield per unit feedstock expense are 91.33%, 32.66 g of sugar/100 g of biomass, and 40.83 g/$, respectively. The optimization method developed in this study is readily applied to other combinations of feedstocks, biofuel production processes, and constraints.

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Neuropeptides, InvertebrateMention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture.

Cited by 2 publications

References 81 publications

Bioenergy crop greenhouse gas mitigation potential under a range of management practices

Bioenergy crop greenhouse gas mitigation potential under a range of management practices

Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective

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