User:Lincolnp8/sandbox

Original- "Food spoilage agents"
As a result of their metabolic diversity, ability to grow at low temperatures, and ubiquitous nature, many Pseudomonas species can cause food spoilage. Notable examples include dairy spoilage by P. fragi, mustiness in eggs caused by P. taetrolens and P. mudicolens, and P. lundensis, which causes spoilage of milk, cheese, meat, and fish. Lincolnp8 (talk) 06:14, 9 October 2017 (UTC)

Edit- "Food spoilage agents"
Examples of food spoilage include dairy spoilage by P. fragi, mustiness in eggs caused by P. taetrolens and P. mudicolens, and P. lundensis, which causes spoilage of milk, cheese, meat, and fish.

Ribotyping is shown to be a method to isolate bacteria capable of spoilage. Around 51% of Pseudomonas bacteria found in dairy processing plants are P. fluorescens, with 69% of these isolates capable of protease, lipase, and lecithinase activity, contributing to degradation of milk components and subsequent spoilage. Other Pseudomonas species can possess any one of the proteases, lipases, or lecithinases, or none at all. Similar enzymatic activity is performed by Pseudomonas of the same ribotype, with each ribotype showing various degrees of milk spoilage and effects on flavour. The number of bacteria affects the intensity of spoilage, with non-enzymatic Pesudomonas species contributing to spoilage in high number.

P. fluorescens uses a metallo-protease that is at optimal activity at pH 6 or 7 in citrate or phosphate buffer, respectively, and heat stable up to 121°C for 20 minutes, at which activity decreases by one-third.

P. fluorescens also produces lipase from late logarithmic phase to stationary phase, with activity increasing proportionally with nutrient content. Refrigeration temperatures of 10°C show higher lipolytic activity than at 5°C.

Detection of milk spoilage and differentiation of active microorganisms can be achieved by gas-sensing technology. The gas sensor consists of a nose portion made of 14 modifiable polymer sensors that can detect specific milk degradation products produced by microorganisms. Sensor data is produced by changes in electric resistance of the 14 polymers when in contact with its target compound, with four sensor parameters used to further specify the response. The responses can then be pre-processed by a three-layer back propagation neural network which can then differentiate between milk spoilage microorganisms such as P. fluorescens and P. aureofaciens. Lincolnp8 (talk) 06:13, 9 October 2017 (UTC)

Final (Assignment 5)- "Detection of Food Spoilage Agents in Milk"
One way of identifying and categorizing multiple bacterial organisms in a sample is to use ribotyping. In ribotyping, differing lengths of chromosomal DNA are isolated from samples containing bacterial species, and digested into fragments. Similar types of fragments from differing organisms are visualized and their lengths compared to each other by Southern blotting or by the much faster method of PCR. Fragments can then be matched with sequences found on bacterial species. Ribotyping is shown to be a method to isolate bacteria capable of spoilage. Around 51% of Pseudomonas bacteria found in dairy processing plants are P. fluorescens, with 69% of these isolates possessing proteases, lipases, and lecithinases which contribute to degradation of milk components and subsequent spoilage. Other Pseudomonas species can possess any one of the proteases, lipases, or lecithinases, or none at all. Similar enzymatic activity is performed by Pseudomonas of the same ribotype, with each ribotype showing various degrees of milk spoilage and effects on flavour. The number of bacteria affects the intensity of spoilage, with non-enzymatic Pseudomonas species contributing to spoilage in high number.

Food spoilage is detrimental to the food industry due to production of volatile compounds from organisms metabolizing the various nutrients found in the food product. Contamination results in health hazards from toxic compound production as well as unpleasant odours and flavours. Electronic nose technology allows fast and continuous measurement of microbial food spoilage by sensing odours produced by these volatile compounds. Electronic nose technology can thus be applied to detect traces of Pseudomonas milk spoilage and isolate the responsible Pseudomonas species. The gas sensor consists of a nose portion made of 14 modifiable polymer sensors that can detect specific milk degradation products produced by microorganisms. Sensor data is produced by changes in electric resistance of the 14 polymers when in contact with its target compound, while four sensor parameters can be adjusted to further specify the response. The responses can then be pre-processed by a neural network which can then differentiate between milk spoilage microorganisms such as P. fluorescens and P. aureofaciens. Lincolnp8 (talk) 07:45, 20 November 2017 (UTC)