Shaojun Xiong

Carbon-allocation dynamics in reed canary grass as affected by soil type and fertilization rates in northern Sweden

Abstract A field experiment was conducted in northern Sweden between 1995 and 1997, with the objectives (1) to quantify the dynamics of carbon accumulation in above- and belowground crop components of reed canary grass (RCG) during the second and third year after sowing and (2) to examine the effect of fertilization and soil type (mineral vs. organic) on C allocation. Across all treatments, carbon accumulation in belowground organs in the top 20 cm was on average 3 and 3.4 Mg C by the end of the second and third year, respectively, with roots and rhizomes accounting for up to 80%. Roots contributed most to belowground C mass during the second growing season but during the preceding winter, root biomass C decreased by 44–67%, and, thereafter, during the third growing season, the proportion of rhizome C increased. The dynamics of root biomass was considerably high, suggesting high root turnover rates. Rhizomes support re-growth during spring and rhizome biomass seems to increase with crop age. Thus, early harvesting before October may impact on the productivity during the following season. Among the factors studied, harvest date was the most influential and affected C allocation in all crop components considerably. Fertilization stimulated growth of shoots, rhizomes, and BSBs (belowground shoot bases) but not that of roots. However, root biomass was higher in the organic than in the mineral soil. In this study, we considered only plant components above 20 cm depth. More detailed studies are needed to calculate more complete soil C balances. However, high belowground biomass production and root turnover indicate a high C input to the soil, which may result in positive soil C balances. Therefore, RCG cropping could have considerable carbon-sequestration potential.

Delayed harvest of reed canary grass translocates more nutrients in rhizomes.

Abstract Two field experiments, one in large plots and the other in small framed plots, were conducted in Umeå, northern Sweden. The objectives were (1) to examine the seasonal patterns of rhizome growth and nutrient dynamics of the energy crop reed canary grass (Phalaris arundinacea L.) in ley I and II, and (2) to evaluate the roles of soil type (mineral vs. organic), fertilisation level (0, 50, and 100 kg N ha−1s), and season/harvest time (Oct-96, May-97, and Aug-97) on the rhizome growth and nutrient dynamics by means of a factorially designed experiment. The general pattern of rhizome growth was that biomass was low in June during initiation of shoot growth, but increased steadily during the growing season, reached a peak in late autumn, and remained high until next spring. The N and P accumulation in rhizomes followed a similar pattern. During ley years I and II, reed canary grass rhizome growth was less dependent on soil type, and more dependent on fertilisation and season, with fertilisation being the most important predictor of growth. The season/harvest time, followed by soil type, was the most important factor for both concentrations and therefore total uptake of N, P, and K in rhizomes. Soil type affected N content in rhizomes significantly, and also interacted with season and enhanced the effect on N, P, and K content in rhizomes. The seasonal dynamics of the nutrient content in rhizomes indicate a remobilisation of the nutrients from rhizomes to the regrowth of shoots and roots in spring and relocation/storage from aboveground shoots to rhizomes during late summer and autumn. The results of this study suggest that delaying the harvest to later than October would result in considerably more energy and nutrient resources being translocated from aboveground shoots to rhizomes for growth in the next season.

Cassava stems: a new resource to increase food and fuel production

Given the growing global population, mankind must find new ways to lower competition for land between food and fuel production. Our findings for cassava suggest that this important crop can substantially increase the combined production of both food and fuel. Cassava stems have previously been overlooked in starch and energy production. These food‐crop residues contain about 30% starch (dry mass) mostly in the xylem rather than phloem tissue. Up to 15% starch of the stem dry mass can be extracted using simple water‐based techniques, potentially leading to an 87% increase in global cassava starch production. The integration of biofuel production, using residues and wastewater from starch extraction, may bring added value. The cassava roots on which biofuels and other products are based can be replaced by cassava stems without land use expansion, making root starch available as food for additional 30 million people today.

Multivariate modelling on biomass properties of cassava stems based on an experimental design

Based on a factorial experimental design (three locations × three cultivars × five harvest times × four replicates) conducted with the objective of investigating variations in fuel characteristics of cassava stem, a multivariate data matrix was formed which was composed of 180 samples and 10 biomass properties for each sample. The properties included as responses were two different calorific values and ash, N, S, Cl, P, K, Ca, and Mg content. Overall principal component analysis (PCA) revealed a strong clustering for the growing locations, but overlapping clusters for the cultivar types and almost no useful information about harvest times. PCA using a partitioned data set (60 × 10) for each location revealed a clustering of cultivars. This was confirmed by soft independent modelling of class analogy (SIMCA) and partial-least-squares discriminant analysis (PLS-DA), and indicated that the locations gave meaningful information about the differences in cultivar, whereas harvest time was not found to be a differentiating factor. Using the PLS technique, it was revealed that ash, K, and Cl content were the most important responses for PLS-DA models. Furthermore, using PLS regression of fuel and soil variables it was also revealed that fuel K and ash content were correlated with the soil P, Si, Ca, and K content, whereas fuel Cl content was correlated with soil pH and content of organic carbon, N, S, and Mg in the soil. Thus, the multivariate modelling used in this study reveals the possibility of performing rigorous analysis of a complex data set when an analysis of variance may not be successful.

Effects of salt stress on biomass and ash composition of switchgrass (Panicum virgatum)

This study was to evaluate the effects of salt stress on the biomass production and fuel characteristics of energy crop switchgrass in Northern China. A greenhouse-pot experiment was conducted to investigate the salt tolerance of the Blackwell, Cave-in-rock and Sunburst cultivars, using the dominant native grass Leymus chinensis as a reference. All three switchgrasses yielded a greater aboveground biomass per plant than Leymus under low-salt conditions (≤2 g NaCl kg−1). However, their biomass production declined significantly at higher salt concentrations. The most salt-tolerant cultivar with respect to biomass production was Cave-in-rock, followed by Blackwell and Sunburst. Among the biomass fuel characteristic studied, ash composition was more significantly affected by salt stress than calorific values. High salt concentrations in the soil increased the content of Ca, Cl and Na in the biomass ash but reduced that of K. The impact of salt stress on ash transformation during combustion was estimated by considering three molar ratios of mineral elements. Growth in high-salt soils reduced the slagging tendency of the fuel, as indicated by the K/(Ca + Mg) ratio. The added Na is unlikely to cause eutectic formation during switchgrass combustion because the Na/(K + Na) ratio was generally below 0.2. However, the addition of NaCl increased the risk of forming chlorine-rich deposits (probably from the fly ash), as indicated by the Cl/(K + Na) ratio.

NIR hyperspectral imaging and multivariate image analysis to characterize spent mushroom substrate: a preliminary study

Commercial mushroom growth on substrate material produces a heterogeneous waste that can be used for bioenergy purposes. Hyperspectral imaging in the near-infrared (NHI) was used to experimentally study a number of spent mushroom substrate (SMS) packed samples under different conditions (wet vs. dry, open vs. plastic covering, and round or cuboid) and to explore the possibilities of direct characterization of the fresh substrate within a plastic bag. Principal components analysis (PCA) was used to remove the background of images, explore the important studied factors, and identify SMS and mycelia (Myc) based on the pixel clusters within the score plot. Overview PCA modeling indicated high moisture content caused the most significant effects on spectra followed by the uneven distribution of Myc and the plastic cover. There were well-separated pixel clusters for SMS and Myc under different conditions: dry, wet, or wet and plastic covering. The loading peaks of the related component and the second derivative of the mean spectra of pixel clusters of SMS and Myc indicated that there are chemical differences between SMS and Myc. Partial least squares discriminant analysis (PLS-DA) models were calculated and classification of SMS and Myc was successful, whether the materials were dry or wet. Peak shifts because of high moisture content and unexpected peaks from the plastic covering were found. Although the best results were obtained for dried cylinders, it was shown that almost equally good results could be obtained for the wet material and for the wet material covered by plastic. Furthermore, PLS-DA prediction showed that a side face hyperspectral image could represent the information for the entire SMS cylinder when Myc was removed. Thus, the combination of NHI and multivariate image analysis has great potential to develop calibration models to directly predict the contents of water, carbohydrates, lignin, and protein in wet and plastic-covered SMS cylinders.