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

Lim, Jongguk,Mo, Changyeun,Kim, Giyoung,Kim, Moon S.,Lee, Hoyoung Korean Society for Agricultural Machinery 2015 바이오시스템공학 Vol.40 No.1

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, ${\pm}2.17mg/100g$, 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.

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

Lim, Jongguk,Mo, Changyeun,Kim, Giyoung,Kang, Sukwon,Lee, Kangjin,Kim, Moon S.,Moon, Jihea Korean Society for Agricultural Machinery 2014 바이오시스템공학 Vol.39 No.3

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 $R{_V}{^2}$, 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, ${\pm}0.487%$ 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.

Optimized Mass Spectrometry-Based Metabolite Extraction and Analysis for the Geographical Discrimination of White Rice (Oryza sativa L.): A Method Comparison Study

Lim, Dong Kyu,Long, Nguyen Phuoc,Mo, Changyeun,Dong, Ziyuan,Lim, Jongguk,Kwon, Sung Won Oxford University Press 2018 Journal of AOAC International Vol.101 No.2

<B>Abstract</B><P>In this study, we examined the effects of different extraction methods for the GC-MS- and LC-MS-based metabolite profiling of white rice (Oryza sativa L.). In addition, the metabolite divergence of white rice cultivated in either Korea or China was also evaluated. The discrimination analysis of each extraction method for white rice from Korea and China and the corresponding discriminatory markers were estimated by unpaired t-test, principal component analysis, k-means cluster analysis, partial least-squares discriminant analysis (PLS-DA), and random forest (RF). According to the prediction parameters obtained from PLS-DA and RF classifiers as well as features that could be identified, the extraction method using 75% isopropanol heated at 100°C coupled with LC-MS analysis was confirmed to be superior to the other extraction methods. Noticeably, lysophospholipid concentrations were significantly different in white rice between Korea and China, and they are novel markers for geographical discrimination. In conclusion, our study suggests an optimized extraction and analysis method as well as novel markers for the geographical discrimination of white rice.</P>

Non-destructive profiling of volatile organic compounds using HS-SPME/GC-MS and its application for the geographical discrimination of white rice

Lim, Dong Kyu,Mo, Changyeun,Lee, Dong-Kyu,Long, Nguyen Phuoc,Lim, Jongguk,Kwon, Sung Won The Journal of Food and Drug Analysis (JFDA), Food 2018 JOURNAL OF FOOD AND DRUG ANALYSIS Vol.26 No.1

<P>The authenticity determination of white rice is crucial to prevent deceptive origin labeling and dishonest trading. However, a non-destructive and comprehensive method for rapidly discriminating the geographical origins of white rice between countries is still lacking. In the current study, we developed a volatile organic compound based geographical discrimination method using headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS) to discriminate rice samples from Korea and China. A partial least squares discriminant analysis (PLS-DA) model exhibited a good classification of white rice between Korea and China (accuracy = 0.958, goodness of fit = 0.937, goodness of prediction = 0.831, and permutation test p-value = 0.043). Combining the PLS-DA based feature selection with the differentially expressed features from the unpaired t-test and significance analysis of microarrays, 12 discriminatory biomarkers were found. Among them, hexanal and 1-hexanol have been previously known to be associated with the cultivation environment and storage conditions. Other hydrocarbon biomarkers are novel, and their impact on rice production and storage remains to be elucidated. In conclusion, our findings highlight the ability to rapidly discriminate white rice from Korea and China. The developed method maybe useful for the authenticity and quality control of white rice. Copyright (C) 2017, Food and Drug Administration, Taiwan. Published by Elsevier Taiwan LLC.</P>

A rapid and reliable method for discriminating rice products from different regions using MCX-based solid-phase extraction and DI-MS/MS-based metabolomics approach

Lim, Dong Kyu,Mo, Changyeun,Long, Nguyen Phuoc,Lim, Jongguk,Kwon, Sung Won Elsevier 2017 Journal of chromatography. B, Analytical technolog Vol.1061 No.-

<P><B>Abstract</B></P> <P>The expansion of the global rice marketplace ultimately raises concerns about authenticity control. Several analytical methods for differentiating the geographical origin of rice have been developed, yet a high-throughput method is still in demand. In this study, we developed a rapid approach using direct infusion-mass spectrometry (DI-MS) to distinguish rice products from different countries. Specifically, the elimination of the matrix effect by a polytetrafluoroethylene (PTFE) filter, a mixed-mode cation exchange (MCX) solid-phase extraction (SPE) with 20% methanol, and an MCX SPE with 100% methanol were measured. Afterward, partial least squares discriminant analysis and random forests were applied to seek the optimal discrimination method. The results revealed that the combination of MCX SPE with 100% methanol and DI-MS in positive ion mode (accuracy=1.000, R<SUP>2</SUP> =0.916, Q<SUP>2</SUP> =0.720, B/W-based <I>p</I>-value=0.015) or the combination of MCX SPE with 20% methanol and targeted DI-MS/MS in positive ion mode (accuracy=1.000, R<SUP>2</SUP> =0.931, Q<SUP>2</SUP> =0.849, B/W-based <I>p</I>-value=0.002) showed the excellent discriminatory ability. Furthermore, differentially expressed metabolites including sodiated lysophosphatidylcholine, lysophosphatidylcholine, lysophosphatidylethanolamines and lysophosphatidylglycerol classes were found. In conclusion, our study provides a rapid and reliable platform for geographical discrimination of white rice and will contribute to the authenticity control of rice products.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

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

Lim, Jongguk,Kim, Giyoung,Mo, Changyeun,Kim, Moon S.,Chao, Kuanglin,Qin, Jianwei,Fu, Xiaping,Baek, Insuck,Cho, Byoung-Kwan Elsevier 2016 Talanta Vol.151 No.-

<P><B>Abstract</B></P> <P>Illegal use of nitrogen-rich melamine (C<SUB>3</SUB>H<SUB>6</SUB>N<SUB>6</SUB>) 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.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Melamine particles contained in milk powder were detected by NIR hyperspectral imaging. </LI> <LI> Regression coefficient values were used to reconstruct the PLS images. </LI> <LI> PLS images were used to discriminate the melamine pixels from milk powder pixels. </LI> <LI> Melamine particles at 200ppm in milk powder were confirmed without pretreatment. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

The integration of multi-platform MS-based metabolomics and multivariate analysis for the geographical origin discrimination of Oryza sativa L.

Lim, Dong Kyu,Mo, Changyeun,Lee, Jeong Hee,Long, Nguyen Phuoc,Dong, Ziyuan,Li, Jing,Lim, Jongguk,Kwon, Sung Won Elsevier Science B.V., Amsterdam 2018 JOURNAL OF FOOD AND DRUG ANALYSIS Vol.26 No.2

Original Article Journal of Biosystems Engineering : Development and Performance Evaluation of Falling-type Dried-Persimmon Weight Sorting System Utilizing Load Cell

( Jongguk Lim ),( Giyoung Kim ),( Changyeun Mo ),( Inchul Choi ) 한국농업기계학회 2015 바이오시스템공학 Vol.40 No.4

Purpose: A falling-type weight sorter equipped with a load cell was developed to sort lightweight dried persimmons. The performance of the sorter was also evaluated. Methods: The electronic weight sorter for dried persimmon comprises a feeder part, a weight-measurement part, an indicator part, a carrier cup, a discharging part, and a driving part. The weight setting and zero-point adjustment are performed digitally for the convenience of users. For the experimental trials, 228 rubber-clay specimens (representative of dried persimmons) in the weight range of 24.73~99.56 g were manufactured for use in experiments to evaluate the performance of the sorter. Results: The average error of the weight measurements from three experimental trials was 1.655%, with a bias of -0.492 g, a root-mean-square error (RMSE) of ±0.808 g, and a coefficient of determination (R(2)) of 0.997. Conclusions: The load-cell-based electronic dried-persimmon weight sorter developed in this study facilitates effective, precise, and convenient sorting of dried persimmons.

Development and Performance Evaluation of Falling-type Dried-Persimmon Weight Sorting System Utilizing Load Cell

Lim, Jongguk,Kim, Giyoung,Mo, Changyeun,Choi, Inchul Korean Society for Agricultural Machinery 2015 바이오시스템공학 Vol.40 No.4

Purpose: A falling-type weight sorter equipped with a load cell was developed to sort lightweight dried persimmons. The performance of the sorter was also evaluated. Methods: The electronic weight sorter for dried persimmon comprises a feeder part, a weight-measurement part, an indicator part, a carrier cup, a discharging part, and a driving part. The weight setting and zero-point adjustment are performed digitally for the convenience of users. For the experimental trials, 228 rubber-clay specimens (representative of dried persimmons) in the weight range of 24.73~99.56 g were manufactured for use in experiments to evaluate the performance of the sorter. Results: The average error of the weight measurements from three experimental trials was 1.655%, with a bias of -0.492 g, a root-mean-square error (RMSE) of ${\pm}0.808g$, and a coefficient of determination ($R^2$ ) of 0.997. Conclusions: The load-cell-based electronic dried-persimmon weight sorter developed in this study facilitates effective, precise, and convenient sorting of dried persimmons.

CCD 칼라 카메라와 영상처리기술을 이용한 딸기의 중량 예측 모델 개발

임종국 ( Jongguk Lim ),김기영 ( Giyoung Kim ),모창연 ( Changyeun Mo ),유현채 ( Hyeonchae Yoo ),오경민 ( Kyoungmin Oh ),김건섭 ( Geonseob Kim ) 한국농업기계학회 2017 한국농업기계학회 학술발표논문집 Vol.22 No.2

겨울철 대표적인 과채류인 딸기는 9월말부터 이듬해 5월 말까지 약 8개월간 재배되고 있으며 3월과 4월에 연간 반입량의 50% 이상이 집중되어 대부분 생식용으로 소비되고 있다. 딸기는 고유의 맛과 향기를 지니고 있으며 비타민 C, 페놀성 화합물 함량도 풍부한 것으로 알려져 있다. 딸기의 재배면적은 지속적으로 증가되고 있으며 딸기 총 생산액은 원예 산물 중에서 가장 높으아 2015년을 기준으로 1조 2천억원 이상이다. 관행딸기 선별은 대부분 육안에 의한 인력 선별에 의존하고 있으며 기형이거나 짓무름이 심한 딸기는 불량과로 구분하고 있다. 딸기는 개별 중량 측정보다는 포장 용기에 담기는 전체 중량에 맞춰 출하하고 있으며 일부 국내 선별장이나 해외에서는 프리트레이에 딸기를 안착시켜 개별 중량을 측정하여 선별하고 있다. 이러한 딸기 중량 측정은 트레이에 안착된 딸기가 로드 셀이 장착된 벨트식 저울을 통과할 때 측정하는 방식을 이용하고 있다. 본 연구에서는 CCD 칼라 카메라로 획득한 딸기 영상 정보를 이용하여 딸기의 착색도 및 기형과를 선별하기 위한 연구를 수행하였으며 추가적으로 기존 벨트식 저울을 대체하여 딸기의 중량을 측정할 수 있는 영상 처리 기술을 개발하기 위해 수행되었다. 중량 예측식 개발을 위해 사용된 딸기 시료는 매향 77개, 설향 395개, 싼타 101개, 장희 91개의 4개 품종 664개를 사용하였다. 664개 딸기로부터 상·하면에서 획득한 1,328개 영상은 초록색 꼭지 부분을 제거한 과육부분에 대한 픽셀수를 카운트하여 실제 측정한 중량과 일차 함수식을 개발하였다. 전체 664개의 딸기를 대상으로 개발된 일차함수 예측식은 Y=0.0011X-5.8153이었으며 이때 R²=0.9143으로 우수한 중량 예측 결과를 보여주었다. CCD 칼라 카메라의 딸기 영상정보를 이용하여 딸기의 중량 측정이 가능하다면 딸기 선별 시설 구축을 위한 벨트식 저울을 제외할 수 있어 시스템이 간소화되고 비용이 감소될 수 있을 것으로 기대된다.