Improving the energy balance of grass-based anaerobic digestion through combined harvesting and pretreatment.

An important challenge that has to be addressed to achieve sustainable anaerobic digestion of lignocellulosic substrates is the development of energy and cost efficient pretreatment methods. Technologies orientated to simultaneously harvest and mechanically pretreat the biomass at the field could meet these criteria as they can potentially reduce the energy losses. The objective of this study was to elucidate the effect of two full-scale harvesting machines to enhance the biogas production and subsequently, improve energy balance. The performances of Disc-mower and Excoriator were assessed on meadow and cultivated grass silages. The results showed that relatively high methane production can be achieved from meadow and cultivated grass harvested in different seasons. The findings indicated that the bioenergy production can be improved based on the selection of the appropriate harvesting technology. More specifically, Excoriator, which cuts and subsequently applies shearing forces on harvested biomass, enhanced the methane production up to 10% and the overall energy budget was improved proportionally to the driving speed increase.

Technical note: Quantifying and characterizing behavior in dairy calves using the IceTag automatic recording device.

The objectives of the current study were 1) to validate the IceTag (http://www.icerobotics.com) automatic recording device for measuring lying, standing, and moving behavior in dairy calves, and 2) to improve the information yield from this device by applying a filtering procedure allowing for the detection of lying versus upright. The IceTag device provides measures of intensity (I) of lying, standing, and activity measured as percent lying, percent standing, and percent active, but does not directly measure lying, standing, and moving behavior because body movements occurring while lying (e.g., shifts in lying position) and while upright (e.g., grooming) are recorded as activity. Therefore, the following 3-step procedure was applied. First, thresholds for I were determined by choosing the cutoff that maximized the sum of sensitivity (Se) and specificity (Sp). Second, a lying period criterion (LPC) was established empirically, and IceTag data were filtered according to the LPC, providing information on the posture of the animal as lying versus being upright. Third, a new threshold of I was estimated for moving activity conditional on the animal being upright. IceTag recordings from 9 calves were compared with video recordings during a 12-h period and analyzed using 2 x 2 contingency tables. Data from the first 4 calves were used to determine an LPC, whereas the remaining 5 calves served for validation of the procedure. An optimal LPC was found by modeling the deviance between IceTag and video recordings as a function of the LPC and choosing the LPC threshold that minimized the deviance. The IceTag device was found to accurately measure the high-prevalence behaviors (lying and standing; Se+Sp >1.90) and less accurately measure the low-prevalence behavior (moving; Se+Sp = 1.39). Application of the 3-step procedure using an optimal LPC estimate of 24.8 s resulted in an improved description of calf behavior, yielding a valid representation of the number and duration of lying and upright periods (Se+Sp = 2.00) within a precision of 0 to 49 s (95% confidence interval). In group-housed dairy calves, valid measures of the number and duration of lying and upright periods may be obtained from the IceTag device when applying the presented filtering procedure to the data. Measures regarding locomotion, on the other hand, should be used with caution.