Team:UC Davis/Project Overview
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+ | Successful Proof of Concept! | ||
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+ | <p>We were able to demonstrate proof of concept at every step of our electrochemical device. Our completed device is able to differentiate between rancid and fresh olive oil. See our final result <a href="https://2014.igem.org/Team:UC_Davis/Signal_Oil" class="brightlink">here!</a></p> | ||
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- | As students of an agricultural university, the purity and quality of agricultural products is a theme that strikes close to home. Our connection with the UC Davis Olive Oil center inspired us to | + | As students of an agricultural university, the purity and quality of agricultural products is a theme that strikes close to home. Our connection with the UC Davis Olive Oil center inspired us to evaluate quality control and purity standards in the olive oil industry. We were shocked to find that the Olive Oil industry is rife with fraud, and that consumers countrywide are not getting the products they’re paying for. Over seventy percent of imported oils and many US oils are already rancid and do not contain the health benefits advertised. Additionally, there are currently no cheap, effective, and accessible methods for assessing Olive Oil quality. Applying our diverse skill sets, the team set out to provide producers, distributors, and consumers with a way of ensuring oil quality. |
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- | Olive Oil quality turns out to be remarkably difficult to assess from a chemical standpoint. Olive oil is an incredibly complex mixture of tens of thousands of different chemical compounds. Additionally, there is no one molecule that signals that an oil is rancid. However, combinations, or profiles, of certain chemicals in an oil can be linked to rancidity. Based on our collaborations with both researchers at the UC Davis Olive Oil Center, and quality control experts at olive oil mills, we came to the understanding that a single group of chemicals, aldehydes, may serve as an excellent proxy for rancidity. Our challenge was then to develop a method to detect these compounds in oil | + | Olive Oil quality turns out to be remarkably difficult to assess from a chemical standpoint. Olive oil is an incredibly complex mixture of tens of thousands of different chemical compounds. Additionally, there is no one molecule that signals that an oil is rancid. However, combinations, or profiles, of certain chemicals in an oil can be linked to rancidity. Based on our collaborations with both researchers at the UC Davis Olive Oil Center, and quality control experts at olive oil mills, we came to the understanding that a single group of chemicals, aldehydes, may serve as an excellent proxy for rancidity. Our challenge was then to develop a method to detect these compounds in oil. |
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- | <p>How Did We | + | <p>How Did We Do It?</p> |
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- | We developed an enzyme based electrochemical biosensor. We first obtained and engineered several <a href="https://2014.igem.org/Team:UC_Davis/Protein_Engineering" class="brightlink>NAD+ dependent Aldehyde Dehydrogenases</a> to have specificity for Aldehydes commonly found in rancid oils. We then optimized an <a href="https://2014.igem.org/Team:UC_Davis/Electrochemistry" class=brightlink">electrochemical system</a> to detect | + | We developed an enzyme based electrochemical biosensor. We first obtained and engineered several <a href="https://2014.igem.org/Team:UC_Davis/Protein_Engineering" class="brightlink">NAD+ dependent Aldehyde Dehydrogenases</a> to have specificity for Aldehydes commonly found in rancid oils. We then optimized an <a href="https://2014.igem.org/Team:UC_Davis/Electrochemistry" class="brightlink">electrochemical system</a> to detect the enzymes' activity. After validating that our system could detect enzyme activity, we developed a <a href="https://2014.igem.org/Team:UC_Davis/Signal_Processing" class="brightlink">mathematics and software suite</a> that allowed us to connect measured aldehyde profiles to the degree of rancidity in an Olive Oil. |
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+ | <area shape="rect" coords="515,0,600,450" href="https://2014.igem.org/Team:UC_Davis/Potentiostat_Design" alt="Potentiostat"> | ||
+ | <area shape="rect" coords="650,0,900,450" href="https://2014.igem.org/Team:UC_Davis/Signal_Processing" alt="SignalProcessing"> | ||
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Latest revision as of 03:08, 18 October 2014
Successful Proof of Concept!
We were able to demonstrate proof of concept at every step of our electrochemical device. Our completed device is able to differentiate between rancid and fresh olive oil. See our final result here!
Project Motivation
As students of an agricultural university, the purity and quality of agricultural products is a theme that strikes close to home. Our connection with the UC Davis Olive Oil center inspired us to evaluate quality control and purity standards in the olive oil industry. We were shocked to find that the Olive Oil industry is rife with fraud, and that consumers countrywide are not getting the products they’re paying for. Over seventy percent of imported oils and many US oils are already rancid and do not contain the health benefits advertised. Additionally, there are currently no cheap, effective, and accessible methods for assessing Olive Oil quality. Applying our diverse skill sets, the team set out to provide producers, distributors, and consumers with a way of ensuring oil quality.
Defining The Problem
Olive Oil quality turns out to be remarkably difficult to assess from a chemical standpoint. Olive oil is an incredibly complex mixture of tens of thousands of different chemical compounds. Additionally, there is no one molecule that signals that an oil is rancid. However, combinations, or profiles, of certain chemicals in an oil can be linked to rancidity. Based on our collaborations with both researchers at the UC Davis Olive Oil Center, and quality control experts at olive oil mills, we came to the understanding that a single group of chemicals, aldehydes, may serve as an excellent proxy for rancidity. Our challenge was then to develop a method to detect these compounds in oil.
How Did We Do It?
We developed an enzyme based electrochemical biosensor. We first obtained and engineered several NAD+ dependent Aldehyde Dehydrogenases to have specificity for Aldehydes commonly found in rancid oils. We then optimized an electrochemical system to detect the enzymes' activity. After validating that our system could detect enzyme activity, we developed a mathematics and software suite that allowed us to connect measured aldehyde profiles to the degree of rancidity in an Olive Oil.