Potentiometric sensor array for the determination of lysine in feed samples using multivariate calibration methods.

Area of Science:

• Analytical Chemistry
• Biosensors
• Electrochemistry

Background:

• Accurate determination of lysine is crucial for animal feed quality assessment.
• Existing methods for lysine quantification can be complex and time-consuming.
• Potentiometric sensors offer a potential alternative for rapid analysis.

Purpose of the Study:

• To develop and validate a potentiometric sensor array for the determination of lysine in feed samples.
• To address the challenge of poor selectivity in lysine biosensors through multi-sensor data analysis.
• To enable accurate lysine quantification in complex feed matrices.

Main Methods:

• Development of an all-solid-state potentiometric sensor array including a lysine biosensor and seven ion-selective electrodes (NH4+, K+, Na+, Ca2+, Mg2+, Li+, H+).
• Construction of the lysine biosensor using a lysine oxidase membrane on an NH4+ electrode.
• Application of multivariate calibration methods, specifically partial least-squares regression, to analyze multi-sensor data and circumvent interference.
• Validation of the sensor array against a standard amino acid analysis method.

Main Results:

• The developed sensor array successfully determined lysine in feed samples.
• Multivariate analysis effectively compensated for the limited selectivity of the individual biosensor.
• The sensor array demonstrated cross-selectivity with each electrode, providing rich data for quantification.
• Results from the sensor array showed reasonable agreement with the standard amino acid analysis method.

Conclusions:

• A potentiometric sensor array based on all-solid-state technology is effective for lysine determination in feed.
• Mathematical analysis of multi-sensor data is a viable strategy to overcome biosensor selectivity limitations.
• This approach offers a promising method for accurate and efficient lysine quantification in complex samples.