Abstract
Corn stover, a major crop-based lignocellulosic biomass feedstock, is required to be at an optimum moisture content for efficient bioconversion processes. Environmental conditions surrounding corn stover, as in storage facilities, affect its moisture due to hygroscopic sorption or desorption. The measurement and modeling of sorption characteristics of corn stover and its leaf, husk, and stalk fractions are useful from utilization and storage standpoints, hence investigated in this article. A benchtop low-temperature humidity chamber provided the test environments of 20°C, 30°C, and 40°C at a constant 95% relative humidity. Measured sorption characteristics with three replications for each fraction were obtained from instantaneous sample masses and initial moisture contents. Observed sorption characteristics were fitted using exponential, Page, and Peleg models. Corn stover fractions displayed a rapid initial moisture uptake followed by a slower sorption rates and eventually becoming almost asymptotic after 25 h. Sorption characteristics of all corn stover fractions were significantly different (P < 0.0001) but not the effect of temperature (P > 0.05) on these fractions. The initial 30 min of sorption was found to be critical due to peak rates of sorption from storage, handling, and processing standpoints. The Page and Peleg models had comparable performance fitting the sorption curves (R2 = 0.995), however the exponential model (R2 = 0.91) was not found suitable because of patterned residuals. The Arrhenius type relationship (P < 0.05; R2 = 0.80) explained the temperature variation of the fitted sorption model parameters. The Peleg model fitted constants, among the sorption models studied, had the best fit (R2 = 0.93) with the Arrhenius relationship. A developed method of mass proportion, involving individual corn stover fraction dry matter ratios, predicted the whole corn stover sorption characteristics from that of its individual fractions. Sorption characteristics models of individual corn stover fractions and predicted whole corn stover including a nomogram can be used for direct and quick estimation. Developed sorption characteristics find application in several fields of corn stover biomass processing, handling, and transport