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Postharvest residues for southern pine species have not previously been quantified to compare volumes produced from both thinnings and clearcut volumes. A John Deere 1490 Slash Bundler bundled postharvest residues following a first thinning of a 14-year-old stand, a second thinning of a 25-year-old stand, and a clearcut of a naturally regenerated mature stand of 54 years of age. Regardless of stand type, nearly one-fifth of merchantable volume harvested was collected as postharvest residue. Initial bundle moisture contents were 127.3, 81.1, and 49.4% dry basis (db) for the first and second thinnings and mature stands, respectively. Bundle needles content was found to significantly influence the relative moisture contents of the bundles by stand type due to the high moisture content of needles compared to other bundle components. Bundles were stored outside and exposed to very hot and dry conditions and dried very rapidly to lowest moisture contents of 22.8, 14.5, and 13.5% (db) for first and second thinnings and mature stands, respectively. Response to moderating temperatures and higher precipitation resulted in rapid moisture content increase to 69.9, 46.2, and 38.1% (db) for the first and second thinnings and mature stand bundles by the end of the study. Temperature and precipitation and bundle percentage needles content all significantly influenced the rapid moisture content variations observed over the study periods.

This article presents a Decision Support System (DSS) to aid managers with supply chain (SC) design and logistics management of biomass-for-biofuel production. These tools play a very important role in efficiently managing biomass-for-biofuel SCs and have the potential to reduce the cost of biofuels. The proposed model coordinates the long-term decisions of designing a SC with the medium term decisions of logistics management. This system has the ability to (a) identify locations and capacities for biorefineries, given the availability of biomass and costs; (b) estimate the minimum cost of delivering biofuels, which include transportation, investment, and processing costs; and (c) perform sensitivity analyses with respect to a number of parameters. Visual Basic for Applications (VBA) is used to create the interface of the DSS, and Excel's CPLEX Add-In is used to solve the mathematical models.

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