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Switchgrass is a high yielding, low-input intensive, native perennial grass that has been promoted as a major second-generation bioenergy crop. Raw switchgrass is not a readily acceptable feedstock in existing power plants that were built to accommodate coal and peat. The objective of this research was to elucidate some of the characteristics of switchgrass biochar produced via carbonization and to explore its potential use as a solid fuel. Samples were carbonized in a batch reactor under reactor temperatures of 300, 350 and 400 °C for 1, 2 and 3 h residence times. Biochar mass yield and volatile solids decreased from 82.6% to 35.2% and from 72.1% to 43.9%, respectively, by increasing carbonization temperatures from 300 °C to 400 °C and residence times from 1 h to 3 h. Conversely, biochar heating value (HV) and fixed carbon content increased from 17.6 MJ kg and from 22.5% to 44.9%, respectively, under the same conditions. A biomass discoloration index (BDI) was created to quantify changes in biochar colors as affected by the two tested parameters. The maximum BDI of 77% was achieved at a carbonization temperature of 400 °C and a residence time of 3 h. The use of this index could be expanded to quantify biochar characteristics as affected by thermochemical treatments. Carbonized biochar could be considered a high quality solid fuel based on its energy content. OPEN ACCESSEnergies 2014, 7 549

Core Ideas Topographic variation influenced soil nutrient distribution in a silvopasture system. High‐resolution digital maps of soil nutrients were generated. Terrain attributes identified topographic functional units as management zones. Level of soil nutrients in topographic functional units were different. Topography plays a crucial role in spatial distribution of nutrients in soils; however, studies to quantify topographic influence on soil nutrient distribution from a silvopasture system are mostly lacking. To address this question, a 4.3‐ha silvopasture site in northwest Arkansas was selected and a total of 51 topsoil (0–15 cm thickness) samples were collected and analyzed for primary (total N [TN], P, K), secondary (Ca, Mg, S), and micronutrients (Fe, Zn, Cu, Mn, B, Na). Topographic information was acquired from 12 terrain attributes derived from a 1‐m digital elevation model. The prediction model was based on random forest. Results showed TN, S, and P were best predicted, whereas Cu, Ca, and Mn had the lowest prediction performance. Levels of S, Ca, Zn, Fe, and TN increased with SAGA wetness index, valley depth, flow accumulation, and multi‐resolution valley bottom flatness index. Normalized height and slope height were positively related to Na but negatively to B and Cu distribution. Aspect had a positive influence on P and Mg concentrations. Based on terrain attributes, the study site could be divided into four topographic functional units (TFU), namely A, B, C, and D; TFU A had the highest nutrients present, whereas TFU B had the lowest P, K, Zn, Cu, Fe, and Ca but highest Na content. However, Mn, Mg, and B did not vary among TFUs. This study affirmed topographic influences on soil nutrient distribution, and the resulting continuous soil nutrient maps are useful for fine‐tuning production systems through optimum nutrient and pasture management.

Temporal patterns of plant growth, composition, and nutrient removal impact development of models for predicting optimal switchgrass (Panicum virgatum L.) harvest times for bioenergy. Original time-course data are needed to construct useful models. Objectives were to characterize seasonal trends in yield, tissue moisture, ash content, leaf area index (LAI), interception of photosynthetically active radiation (PAR), and macronutrient accumulation and losses. Plots were subjected to 12 single harvests

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