Jongguk Lim

A microfluidic nano-biosensor for the detection of pathogenic Salmonella.

Rapid detection of pathogenic Salmonella in food products is extremely important for protecting the public from salmonellosis. The objective of the present study was to explore the feasibility of using a microfluidic nano-biosensor to rapidly detect pathogenic Salmonella. Quantum dot nanoparticles were used to detect Salmonella cells. For selective detection of Salmonella, anti-Salmonella polyclonal antibodies were covalently immobilized onto the quantum dot surface. To separate and concentrate the cells from the sample, superparamagnetic particles and a microfluidic chip were used. A portable fluorometer was developed to measure the fluorescence signal from the quantum dot nanoparticles attached to Salmonella in the samples. The sensitivity for detection of pathogenic Salmonella was evaluated using serially diluted Salmonella Typhimurium in borate buffer and chicken extract. The fluorescence response of the nano-biosensor increased with increasing cell concentration. The detection limit of the sensor was 10(3) CFU/mL Salmonella in both borate buffer and food extract.

Detection of melamine in milk powders using near-infrared hyperspectral imaging combined with regression coefficient of partial least square regression model

Illegal use of nitrogen-rich melamine (C3H6N6) to boost perceived protein content of food products such as milk, infant formula, frozen yogurt, pet food, biscuits, and coffee drinks has caused serious food safety problems. Conventional methods to detect melamine in foods, such as Enzyme-linked immunosorbent assay (ELISA), High-performance liquid chromatography (HPLC), and Gas chromatography-mass spectrometry (GC-MS), are sensitive but they are time-consuming, expensive, and labor-intensive. In this research, near-infrared (NIR) hyperspectral imaging technique combined with regression coefficient of partial least squares regression (PLSR) model was used to detect melamine particles in milk powders easily and quickly. NIR hyperspectral reflectance imaging data in the spectral range of 990-1700nm were acquired from melamine-milk powder mixture samples prepared at various concentrations ranging from 0.02% to 1%. PLSR models were developed to correlate the spectral data (independent variables) with melamine concentration (dependent variables) in melamine-milk powder mixture samples. PLSR models applying various pretreatment methods were used to reconstruct the two-dimensional PLS images. PLS images were converted to the binary images to detect the suspected melamine pixels in milk powder. As the melamine concentration was increased, the numbers of suspected melamine pixels of binary images were also increased. These results suggested that NIR hyperspectral imaging technique and the PLSR model can be regarded as an effective tool to detect melamine particles in milk powders.

Comparison of Whole-Cell SELEX Methods for the Identification of Staphylococcus Aureus-Specific DNA Aptamers

Whole-cell Systemic Evolution of Ligands by Exponential enrichment (SELEX) is the process by which aptamers specific to target cells are developed. Aptamers selected by whole-cell SELEX have high affinity and specificity for bacterial surface molecules and live bacterial targets. To identify DNA aptamers specific to Staphylococcus aureus, we applied our rapid whole-cell SELEX method to a single-stranded ssDNA library. To improve the specificity and selectivity of the aptamers, we designed, selected, and developed two categories of aptamers that were selected by two kinds of whole-cell SELEX, by mixing and combining FACS analysis and a counter-SELEX process. Using this approach, we have developed a biosensor system that employs a high affinity aptamer for detection of target bacteria. FAM-labeled aptamer sequences with high binding to S. aureus, as determined by fluorescence spectroscopic analysis, were identified, and aptamer A14, selected by the basic whole-cell SELEX using a once-off FACS analysis, and which had a high binding affinity and specificity, was chosen. The binding assay was evaluated using FACS analysis. Our study demonstrated the development of a set of whole-cell SELEX derived aptamers specific to S. aureus; this approach can be used in the identification of other bacteria.

A Simple Multispectral Imaging Algorithm for Detection of Defects on Red Delicious Apples

Purpose: A multispectral algorithm for detection and differentiation of defective (defects on apple skin) and normal Red Delicious apples was developed from analysis of a series of hyperspectral line-scan images. Methods: A fast line-scan hyperspectral imaging system mounted on a conventional apple sorting machine was used to capture hyperspectral images of apples moving approximately 4 apples per second on a conveyor belt. The detection algorithm included an apple segmentation method and a threshold function, and was developed using three wavebands at 676 nm, 714 nm and 779 nm. The algorithm was executed on line-by-line image analysis, simulating online real-time line-scan imaging inspection during fruit processing. Results: The rapid multispectral algorithm detected over 95% of defectiv e apples and 91% of normal apples investigated. Conclusions: The multispectral defect detection algorithm can potentially be used in commercial apple processing lines.

Detecting Drought Stress in Soybean Plants Using Hyperspectral Fluorescence Imaging

Purpose: Soybean growth is adversely affected by environmental stresses such as drought, extreme temperatures, and nutrient deficiency. The objective of this study was to develop a method for rapid measurement of drought stress in soybean plants using a hyperspectral fluorescence imaging technique. Methods: Hyperspectral fluorescence images were obtained using UV-A light with 365 nm excitation. Two soybean cultivars under drought stress were analyzed. A partial least square regression (PLSR) model was used to predict drought stress in soybeans. Results: Partial least square (PLS) images were obtained for the two soybean cultivars using the results of the developed model during the period of drought stress treatment. Analysis of the PLS images showed that the accuracy of drought stress discrimination in the two cultivars was 0.973 for an 8-day treatment group and 0.969 for a 6-day treatment group. Conclusions: These results validate the use of hyperspectral fluorescence images for assessing drought stress in soybeans.

A Review on Lateral Flow Test Strip for Food Safety

Background: Foodborne disease outbreaks from various food sources are a major health concern worldwide. Current methods for detection of foodborne pathogens are both expensive and time-consuming. Purpose: This review aims to present the current information available on the use of lateral flow test strips to detect pathogens in food products to enhance food safety. Results: Frequent foodborne disease outbreaks from various food sources have increased the need for rapid and easy methods for routine analysis of foodborne pathogens. Present detection methods for foodborne pathogens require expensive instruments, experts, and long time for sample analysis. Lateral flow test strips have drawn attention in recent years because of their ability to detect analytes quickly and easily. This review focuses on the principle of the lateral flow test, the various formats of lateral flow test strips, recognition elements, labeling tags, and reading instruments. In addition, this review also discusses the future prospects for the lateral flow test strips.

Non-destructive and Rapid Prediction of Moisture Content in Red Pepper (Capsicum annuum L.) Powder Using Near-infrared Spectroscopy and a Partial Least Squares Regression Model

National Academy of Agricultural Science, Rural Development Administration, 150 Suinro, Gwonseon-gu, Suwon, Gyeonggi-do 441-100, Korea Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Ave, Beltsville, MD 20705 Received: July 23rd 2014; Revised: July 29th 2014; Accepted: August 9th 2014 Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of RV2, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ±0.487% wb, and 10.00, respectively. Conclusions: These results demonstrated that NIR spectroscopy and a PLSR model could be useful techniques for measuring rapidly and non-destructively the moisture content in red pepper powder.

Design and Fabrication of a Real-Time Measurement System for the Capsaicinoid Content of Korean Red Pepper (Capsicum annuum L.) Powder by Visible and Near-Infrared Spectroscopy.

This research aims to design and fabricate a system to measure the capsaicinoid content of red pepper powder in a non-destructive and rapid method using visible and near infrared spectroscopy (VNIR). The developed system scans a well-leveled powder surface continuously to minimize the influence of the placenta distribution, thus acquiring stable and representative reflectance spectra. The system incorporates flat belts driven by a sample input hopper and stepping motor, a powder surface leveler, charge-coupled device (CCD) image sensor-embedded VNIR spectrometer, fiber optic probe, and tungsten halogen lamp, and an automated reference measuring unit with a reference panel to measure the standard spectrum. The operation program includes device interface, standard reflectivity measurement, and a graphical user interface to measure the capsaicinoid content. A partial least square regression (PLSR) model was developed to predict the capsaicinoid content; 44 red pepper powder samples whose measured capsaicinoid content ranged 13.45–159.48 mg/100 g by per high-performance liquid chromatography (HPLC) and 1242 VNIR absorbance spectra acquired by the pungency measurement system were used. The determination coefficient of validation (RV2) and standard error of prediction (SEP) for the model with the first-order derivative pretreatment method for Korean red pepper powder were 0.8484 and ±13.6388 mg/100 g, respectively.

Development of Models for the Prediction of Domestic Red Pepper (Capsicum annuum L.) Powder Capsaicinoid Content using Visible and Near-infrared Spectroscopy

National Academy of Agricultural Science, Rural Development Administration, 310 Nongsaengmyeng-ro, Wansan-gu, Jeonju, Jeollabuk-do, Korea Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Ave, Beltsville, MD 20705 Received: October 19th, 2014; Revised: November 24th, 2014; Accepted: January 13rd, 2015 Purpose: The purpose of this study was to non-destructively and quickly predict the capsaicinoid content of domestic red pepper powders from various areas of Korea using a pungency measurement system in combination with visible and near-infrared (VNIR) spectroscopic techniques. Methods: The reflectance spectra of 149 red pepper powder samples from 14 areas of Korea were obtained in the wavelength range of 450–950 nm and partial least squares regression (PLSR) models for the prediction of capsaicinoid content were developed using area models. Results: The determination coefficient of validation (RV2), standard error of prediction (SEP), and residual prediction deviation (RPD) for the capsaicinoid content prediction model for the Namyoungyang area were 0.985, ±2.17 mg/100g, and 7.94, respectively. Conclusions: These results show the possibility of VNIR spectroscopy combined with PLSR models in the non-destructive and facile prediction of capsaicinoid content of red pepper powders from Korea.

Development of a portable 3CCD camera system for multispectral imaging of biological samples.

Recent studies have suggested the need for imaging devices capable of multispectral imaging beyond the visible region, to allow for quality and safety evaluations of agricultural commodities. Conventional multispectral imaging devices lack flexibility in spectral waveband selectivity for such applications. In this paper, a recently developed portable 3CCD camera with significant improvements over existing imaging devices is presented. A beam-splitter prism assembly for 3CCD was designed to accommodate three interference filters that can be easily changed for application-specific multispectral waveband selection in the 400 to 1000 nm region. We also designed and integrated electronic components on printed circuit boards with firmware programming, enabling parallel processing, synchronization, and independent control of the three CCD sensors, to ensure the transfer of data without significant delay or data loss due to buffering. The system can stream 30 frames (3-waveband images in each frame) per second. The potential utility of the 3CCD camera system was demonstrated in the laboratory for detecting defect spots on apples.