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Bioenergy has been globally recognized as one of the sustainable alternatives to fossil fuels. An assured supply of biomass feedstocks is a crucial bottleneck for the bioenergy industry emanating from uncertainties in land-use changes and future prices. Analytical approaches deriving from geographical information systems (GIS)-based analysis, mathematical modeling, optimization analyses, and empirical techniques have been widely used to evaluate the potential for bioenergy feedstock. In this study, we propose a three-phase methodology integrating fuzzy logic, network optimization, and ecosystem services assessment to estimate potential bioenergy supply. The fuzzy logic analysis uses multiple spatial criteria to identify suitable biomass cultivating regions. We extract spatial information based on favorable conditions and potential constraints, such as developed urban areas and croplands. Further, the network analysis uses the road network and existing biorefineries to evaluate feedstock production locations. Our analysis extends previous studies by incorporating biodiversity and ecologically sensitive areas into the analysis, as well as incorporating ecosystem service benefits as an additional driver for adoption, ensuring that biomass cultivation will minimize the negative consequences of large-scale land-use change. We apply the concept of assessing the potential for switchgrass-based bioenergy in Missouri to the proposed methodology.

Mobile Drip Irrigation (MDI) involves attaching driplines to center pivot drops. MDI has potential to eliminate water losses due to spray droplet evaporation, water evaporation from the canopy, and wind drift. MDI also may reduce soil water evaporation due to limited surface wetting. A study was conducted with the following objectives: 1) compare soil water evaporation under MDI and in-canopy spray nozzles; 2) evaluate soil water redistribution under MDI at 60 inch dripline lateral spacing; 3) compare corn grain yield, water productivity, and irrigation water use efficiency; and 4) compare end-of-season profile soil water under MDI and in-canopy spray at two well capacities 300 and 600 gpm. The experiment was conducted at the Kansas State University Southwest Research-Extension Center near Garden City, Kansas. The experimental design was randomized complete block with four replications, and two treatments MDI and in-canopy spray nozzles. Soil water evaporation was measured using four-inch minilysimeters placed between corn rows. The effect of a 60-inch lateral spacing on soil water redistribution was evaluated using soil water measurements made using neutron attenuation to a depth of 8 feet.Preliminary results indicate soil water evaporation was lower under MDI compared to in-canopy spray nozzles, by 35% on average. Soil water redistribution was adequate for dripline spacing of 60 inches in silt loam soils of southwest Kansas. At 600 gpm well capacity, corn yields were 247 and 255 bu/a for MDI and in-canopy spray nozzles, respectively. At 300 gpm well capacity, yields were 243 and 220 bu/a for MDI and in-canopy spray nozzles, respectively. However, the differences were not significant (p > 0.05) between the irrigation application technologies in 2015. The effect of application method on water productivity and irrigation water use efficiency was also not significant. The lack of significant differences could be attributed to the above normal rainfall received during the 2015 growing season (18.3 inches from May to October). Normal mean annual rainfall for the study area is 18 inches. The effect of application method on end-of-season soil water was statistically significant under low well capacity (300 gpm) with Mobile Drip Irrigation having more soil water compared to in-canopy spray nozzles in the 8 foot profile at harvest. It is worth noting that plots under MDI did not have deep wheel tracks associated with sprinkler nozzles.

This study analyzed the perceptions of four stakeholder groups (forest landowners, private forest consultants, forest management researchers or educators, and federal or state agency foresters), regarding their management practices and preferred geographic growing conditions of loblolly pine in Virginia by combining AHP (analytical hierarchy process) and regression modeling. By ranking the importance of different geographical conditions for managing loblolly pine, we aimed to identify ways to support loblolly growth as a potential feedstock for biofuel generation. We achieved this through collecting survey responses from 43 stakeholders during the 2019 Virginia Forestry Summit. The results showed that the landowner, researcher/educator, and federal/state agency stakeholder groups all indicated that proximity to a mill was the most important criteria, whereas the consultant stakeholder group indicated that proximity to a road was the most important criteria. All the stakeholder groups indicated that distance from protected land was the least important criteria, followed by proximity to a water body and flat land. The regression model revealed that acres of land managed and loblolly rotation age were correlated to the weight given to the distance to a mill criterion, where increased acreage and increased rotation age were associated with an increased prioritization of proximity to a mill. Distance from protected land, the lowest-ranking criteria, was shown to have an association with the level of experience with loblolly, where more experience was associated with a lower prioritization of proximity from protected land. A contingency analysis of the self-identified level of experience with loblolly in each stakeholder group revealed that federal/state agency foresters had the most experience, followed by consultants, landowners, and researchers/educators. The research supports the importance of understanding the variation of perceptions between and within stakeholder groups in order to develop the necessary infrastructural and policy support for the sustainable development of bioenergy.