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A computational tool is developed for the estimation of the energy requirements of Miscanthus x giganteus on individual fields that includes a detailed analysis and account of the involved in-field and transport operations. The tool takes into account all the individual involved in-field and transport operations and provides a detailed analysis on the energy requirements of the components that contribute to the energy input. A basic scenario was implemented to demonstrate the capabilities of the tool. Specifically, the variability of the energy requirements as a function of field area and field-storage distance changes was shown. The field-storage distance highly affects the energy requirements resulting in a variation in the efficiency if energy (output/input ratio) from 15.8 up to 23.7 for the targeted cases. Not only the field-distance highly affects the energy requirements but also the biomass transportation system. Based on the presented example, different transportation systems adhering to the same configuration of the production system creates variation in the efficiency of energy (EoE) between 12.9 and 17.5. The presented tool provides individualized results that can be used for the processes of designing or evaluating a specific production system since the outcomes are not based on average norms.

Biomass production systems include multiple-crops rotations, various machinery systems, diversified operational practices and several dispersed fields located in a range of distances between the various facilities (e.g., storage and processing facilities). These factors diversify the energy and cost requirements of the system. To that effect, assessment tools dedicated a single-crop production based on average standards cannot provide an insight evaluation of a specific production system, e.g., for a whole farm in terms of energy and cost requirements. This paper is the continuation of previous work, which presents a web-based tool for cost estimation of biomass production and transportation of multiple-crop production. In the present work, the tool is extended to additionally provide the energy balance of the examined systems. The energy input includes the whole supply chain of the biomass, namely crop cultivation, harvesting, handling of biomass and transportation to the processing facilities. A case study involving a real crop production system that feeds a biogas plant of 200 kW was selected for the demonstration of the tool's applicability. The output of the tool provides a series of indexes dedicated to the energy input and balance. The presented tool can be used for the comparison of the performance, in terms of energy requirements, between various crops, fields, operations practices, and operations systems providing support for decisions on the biomass production system design (e.g., allocation of crops to fields) and operations management (e.g., machinery system selection).

Various crops can be considered as potential bioenergy and biofuel production feedstocks. The selection of the crops to be cultivated for that purpose is based on several factors. For an objective comparison between different crops, a common framework is required to assess their economic or energetic performance. In this paper, a computational tool for the energy cost evaluation of multiple-crop production systems is presented. All the in-field and transport operations are considered, providing a detailed analysis of the energy requirements of the components that contribute to the overall energy consumption. A demonstration scenario is also described. The scenario is based on three selected energy crops, namely Miscanthus, Arundo donax and Switchgrass. The tool can be used as a decision support system for the evaluation of different agronomical practices (such as fertilization and agrochemicals application), machinery systems, and management practices that can be applied in each one of the individual crops within the production system.

Various sources of biomass contribute significantly in energy production globally given a series of constraints in its primary production. Green biomass sources (such as perennial grasses), yellow biomass sources (such as crop residues), and woody biomass sources (such as willow) represent the three pillars in biomass production by crops. In this paper, we conducted a comprehensive review on research studies targeted to advancements at biomass supply-chain management in connection to these three types of biomass sources. A framework that classifies the works in problem-based and methodology-based approaches was followed. Results show the use of modern technological means and tools in current management-related problems. From the review, it is evident that the presented up-to-date trends on biomass supply-chain management and the potential for future advanced approach applications play a crucial role on business and sustainability efficiency of biomass supply chain.

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Capacity planning in agricultural field operations needs to give consideration to the operational system design which involves the selection and dimensioning of production components, such as machinery and equipment. Capacity planning models currently onstream are generally based on average norm data and not on specific farm data which may vary from year to year. In this paper a model is presented for predicting the cost of in-field and transport operations for multiple-field and multiple-crop production systems. A case study from a real production system is presented in order to demonstrate the model's functionalities and its sensitivity to parameters known to be somewhat imprecise. It was shown that the proposed model can provide operation cost predictions for complex cropping systems where labor and machinery are shared between the various operations which can be individually formulated for each individual crop. By so doing, the model can be used as a decision support system at the strategic level of management of agricultural production systems and specifically for the mid-term design process of systems in terms of labor/machinery and crop selection conforming to the criterion of profitability.

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