The anticipated world population increase demands growth in sustainable food production. The current trend is to use more efficient agricultural processes in order to increase food production. Precision agriculture (PA) technology provides the means to increase equipment productivity and field and input efficiency. The concept of small modular and scalable intelligent machines tries to address the challenge of more productivity with the goal of reduced cost and power. In addition, power system technologies with potential application to agricultural machines are evolving quickly and issues of renewability and sustainability are becoming common priorities, with demands for standardization and certification. At present, most of the energy used directly in agriculture of developed countries comes from fossil fuels, and agricultural machinery systems are typically powered with diesel engines because of their reliability, efficiency and durability. With the emergence of precision technologies enabling intra-row and plant scale cultural practices, agricultural machines could be smaller in size and powered by electrical energy. This evolution of agricultural machinery systems could move agricultural production to a new level of sustainability. However, there are challenges making this transition from conventional agricultural machines to smaller, electrically powered agricultural machines. Currently, in the area of weed control, there are several strategies for controlling weed infestations in crop production, such as chemical control, mechanical cultivation, and thermal treatment among others. All of these strategies have different power and energy requirements, and sustainability could be improved from each of these strategies. In a case study, a prototype robotic mechanical weed control system powered by electrical power was analyzed using performance metrics such as work rate and energy requirements per area across different operational speeds. Several different weed control technologies were compared on an energy per area basis to determine how agricultural precision information can be used to reduce energy requirements. The comparison showed that the energy of the prototype represents less than 20% of that associated with conventional cultivation and chemical weed control.