Chapters authored
Metabolic Engineering of the Model Photoautotrophic Cyanobacterium Synechocystis for Ethanol Production: Optimization Strategies and Challenges
Photoautotrophic ethanol production using model cyanobacteria is an attractive technology that offers potential for sustainable ethanol production as a biofuel. Model strains of Synechocystis PCC6803 have been metabolically engineered to convert central metabolic intermediates such as pyruvate to acetaldehyde via cloned heterologous pyruvate decarboxylase and from acetaldehyde to ethanol via cloned homologous or heterologous alcohol dehydrogenase. While the technology is now proven, strategies are required to increase the ethanol levels through metabolic and genetic engineering and in addition, production and process strategies are required to make the process sustainable. Here we discuss both genetic and molecular strategies in combination with do wnstream strategies that are being applied while also discussing challenges to future application.
Part of the book: Fuel Ethanol Production from Sugarcane
The Dairy Industry: Process, Monitoring, Standards, and Quality
Sampling and analysis occur along the milk processing train: from collection at farm level, to intake at the diary plant, the processing steps, and the end products. Milk has a short shelf life; however, products such as milk powders have allowed a global industry to be developed. Quality control tests are vital to support activities for hygiene and food standards to meet regulatory and customer demands. Multiples of chemical and microbiological contamination tests are undertaken. Hazard analysis testing strategies are necessary, but some tests may be redundant; it is therefore vital to identify product optimization quality control strategies. The time taken to undergo testing and turnaround time are rarely measured. The dairy industry is a traditional industry with a low margin commodity. Industry 4.0 vision for dairy manufacturing is to introduce the aspects of operational excellence and implementation of information and communications technologies. The dairy industries’ reply to Industry 4.0 is represented predominantly by proactive maintenance and optimization of production and logistical chains, such as robotic milking machines and processing and packaging line automation reinforced by sensors for rapid chemical and microbial analysis with improved and real-time data management. This chapter reviews the processing trains with suggestions for improved optimization.
Part of the book: Descriptive Food Science