BIOMASS STORAGE, DECISION SUPPORT SYSTEMS AND EXPERT SYSTEMS IN CROP PRODUCTION AND PROCESSING (INFORMATION SYSTEMS, COMPUTER)

ROBERT D SMITH, Purdue University

Abstract

Agricultural production depends on obtaining and efficiently using the necessary resources. Producers must have access to information which will allow them to select among alternative resource inputs and farming practices. This dissertation covers research into the storage of alternative biomass energy crops and the progression into developing integrated, interactive computer based information systems which can be used to support agricultural decisions. Biomass could be a significant source of energy and industrial feedstocks. Storing moist biomass between harvest and conversion can lead to degradation and loss of the material. Data on the storage characteristics of corncobs and corn silage was obtained over two seasons. The results of studies on corncob storage in outside piles indicated that up to 33% of the available energy and 43% of the available pentosans were lost during 18 months storage. Studies of corn silage preservation showed that 0.5% sulfur dioxide effectively reduced losses of water soluble sugars. The storage research indicated that integrated biomass energy systems with the conversion of silages to ethanol and utilizing crop residues for heat are feasible. The development of decision support systems (DSS) and expert systems (ES) offers great potential for effective transfer of technology from researchers to farmers. A crop planning DSS was constructed on an integrated spreadsheet framework with interactive screen inputs and numerical and graphical outputs. Machinery resource and crop growth models were combined with economic analyses of the expected outcomes. The two main uses of the DSS are in comparative analyses of alternative cropping systems and sequential updating of a particular season. A crop planting ES was built with existing development tools to provide recommendations for selecting from corn and soybean planting and replanting alternatives. User inputs were combined with the rule base to infer conclusions which were based on accumulated evidence or matching the inputs with a set of combination rules. Both the DSS and ES contain data which is only valid in central Indiana. The construction of these computer systems indicated that DSS and ES can be effectively used to present information to farmers.

Degree

Ph.D.

Subject Area

Agricultural engineering

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