Wang-Hee Lee

Detection of starch adulteration in onion powder by FT-NIR and FT-IR spectroscopy.

Adulteration of onion powder with cornstarch was identified by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra of 180 pure and adulterated samples (1-35 wt % starch) were collected and preprocessed to generate calibration and prediction sets. A multivariate calibration model of partial least-squares regression (PLSR) was executed on the pretreated spectra to predict the presence of starch. The PLSR model predicted adulteration with an R(p)2 of 0.98 and a standard error of prediction (SEP) of 1.18% for the FT-NIR data and an R(p)2 of 0.90 and SEP of 3.12% for the FT-IR data. Thus, the FT-NIR data were of greater predictive value than the FT-IR data. Principal component analysis on the preprocessed data identified the onion powder in terms of added starch. The first three principal component loadings and β coefficients of the PLSR model revealed starch-related absorption. These methods can be applied to rapidly detect adulteration in other spices.

Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging.

BACKGROUND There is a need to minimize economic damage by sorting infected seeds from healthy seeds before seeding. However, current methods of detecting infected seeds, such as seedling grow-out, enzyme-linked immunosorbent assays, the polymerase chain reaction (PCR) and the real-time PCR have a critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to evaluate the potential of visible/near-infrared (Vis/NIR) hyperspectral imaging system for detecting bacteria-infected watermelon seeds. RESULTS A hyperspectral Vis/NIR reflectance imaging system (spectral region of 400-1000 nm) was constructed to obtain hyperspectral reflectance images for 336 bacteria-infected watermelon seeds, which were then subjected to partial least square discriminant analysis (PLS-DA) and a least-squares support vector machine (LS-SVM) to classify bacteria-infected watermelon seeds from healthy watermelon seeds. The developed system detected bacteria-infected watermelon seeds with an accuracy > 90% (PLS-DA: 91.7%, LS-SVM: 90.5%), suggesting that the Vis/NIR hyperspectral imaging system is effective for quarantining bacteria-infected watermelon seeds. CONCLUSION The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds.

Non‐destructive evaluation of bacteria‐infected watermelon seeds using Vis/NIR hyperspectral imaging

BACKGROUND There is a need to minimize economic damage by sorting infected seeds from healthy seeds before seeding. However, current methods of detecting infected seeds, such as seedling grow-out, enzyme-linked immunosorbent assays, the polymerase chain reaction (PCR) and the real-time PCR have a critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to evaluate the potential of visible/near-infrared (Vis/NIR) hyperspectral imaging system for detecting bacteria-infected watermelon seeds. RESULTS A hyperspectral Vis/NIR reflectance imaging system (spectral region of 400-1000 nm) was constructed to obtain hyperspectral reflectance images for 336 bacteria-infected watermelon seeds, which were then subjected to partial least square discriminant analysis (PLS-DA) and a least-squares support vector machine (LS-SVM) to classify bacteria-infected watermelon seeds from healthy watermelon seeds. The developed system detected bacteria-infected watermelon seeds with an accuracy > 90% (PLS-DA: 91.7%, LS-SVM: 90.5%), suggesting that the Vis/NIR hyperspectral imaging system is effective for quarantining bacteria-infected watermelon seeds. CONCLUSION The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds.

Optimal Optical Filters of Fluorescence Excitation and Emission for Poultry Fecal Detection

th , 2012; Revised: August 3 rd , 2012; Accepted: August 20 th , 2012 Purpose: An analytic method to design excitation and emission filters of a multispectral fluorescence imaging system is proposed and was demonstrated in an application to poultry fecal inspection Methods: A mathematical model of a multispectral imaging system is proposed and its system parameters, such as excitation and emission filters, were optimally determined by linear discriminant analysis (LDA). An alternating scheme was proposed for numerical implementation. Fluorescence characteristics of organic materials and feces of poultry carcasses are analyzed by LDA to design the optimal excitation and emission filters for poultry fecal inspection. Results: The most appropriate excitation filter was UV-A (about 360 nm) and blue light source (about 460 nm) and band-pass filter was 660-670 nm. The classification accuracy and false positive are 98.4% and 2.5%, respectively. Conclusions: The proposed method is applicable to other agricultural products which are distinguishable by their spectral properties.

Physicochemical Quality Changes in Chinese Cabbage with Storage Period and Temperature: A Review

and Temperature: A Review Joon-Yong Shim, Do-Gyun Kim, Jong-Tae Park, Lalit Mohan Kandpal, Soon-jung Hong, Byoung-Kwan Cho, Wang-Hee Lee* Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon, 34134, Korea Department of Food Science and Technology, Chungnam National University, Daejeon, 34134, Korea Rural Human Resource Development Center, Rural Development Administration, Jeonju, Jeollabuk-do, 54874, Korea Received: November 10th, 2016; Revised: November 21st, 2016; Accepted: November 25th, 2016 Background: Recent inquiries into high-quality foods have discussed the importance of the functional aspects of foods, in addition to traditional quality indicators such as color, firmness, weight, trimming loss, respiration rate, texture, and soluble solid content. Recently, functional Chinese cabbage, which makes up a large portion of the vegetables consumed in Korea, has been identified as an anticancer treatment. However, the investigation of practical issues, such as the effects of storage conditions on quality indicators (including functional compounds), is still limited. Purpose: We reviewed various studies on variations in the quality indicators and functional compounds of Chinese cabbage in response to different storage environments, focusing on storage temperature and storage period. In particular, we emphasized the effect of storage temperature and storage period on glucosinolate (GSL) levels, in order to provide guidelines for optimizing storage environments to maximize GSLs. Additionally, we used response surface methodology to propose experimental designs for future studies exploring the optimal storage conditions for enhancing GSL contents. Review: Large variations in quality indicators were observed depending on the cultivar, the type of storage, the storage conditions, and the harvest time. In particular, GSL content varied with storage conditions, indicating that either low temperatures or adequate air composition by controlled atmospheric storage may preserve GSL levels, as well as prolonging shelf life. Even though genetic and biochemical approaches are preferred for developing functional Chinese cabbage, it is important to establish a practical method for preserving quality for marketability; a prospective study into optimal storage conditions for preserving functional compounds (which can be applied in farms), is required. This may be achievable with the comprehensive meta-analysis of currently published data introduced in this review, or by conducting newly designed experiments investigating the relationship between storage conditions and the levels of functional compounds.

Review of Rice Quality under Various Growth and Storage Conditions and its Evaluation using Spectroscopic Technology

and its Evaluation using Spectroscopic Technology Ritu Joshi, Changyeun Mo, Wang-Hee Lee, Seung Hyun Lee, Byoung-Kwan Cho* Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea National Academy of Agricultural Science, Rural Development Administration, 166 Nonsaengmyeong-ro, Iseo-myeon, Wanju-gun, Jeollabuk-do 565-851, South Korea Received: April 2nd, 2015; Revised: May 9th, 2015; Accepted: May 22nd, 2015 Purpose: Grain quality is a general concept that covers many characteristics, ranging from physical to biochemical and physiochemical properties. Rice aging during storage is currently a challenge in the rice industry, and is a complicated process involving changes in all of the above properties. Spectroscopic techniques can be used to obtain information on the quality of rice samples in a non-destructive manner. Methods: The objective of this review was to highlight the factors that contribute to rice quality and aging, and to describe various spectroscopic modalities, particularly vibrational and hyperspectral imaging, for the assessment of rice quality. Results: Starch and protein are the main components of the rice endosperm, and are therefore key factors contributing to eating and cooking quality. While the overall starch, protein, and lipid content in the rice grain remains essentially unchanged during storage, structural changes do occur. These changes affect pasting and gel properties, and ultimately the flavor of cooked rice. In addition, grain quality is significantly affected by growing and environmental conditions, such as water availability, temperature, fertilizer application, and salinity stress. These properties can be evaluated using spectroscopic techniques, and rice samples can be discriminated by using multivariate statistical analysis methods. Conclusion: Hyperspectral imaging and vibrational spectroscopy techniques have good potential for determining rice quality properties in a non-invasive manner, i.e., not requiring the introduction of instruments into the rice grain.

Effect of Microwave Heat Treatment on Inhibition of Corn Seed Germination

Purpose: Corn is a major commercial crop targeted for genetic modification owing to its high consumer demand as a foodstuff for humans and livestock, as well as its other industrial applications. However, the safety of genetically modified (GM) crops is controversial. Indeed, several countries have banned the importation of GM seeds that can germinate. Therefore, development of effective, convenient, and nondestructive methods to inhibit seed germination is required. Methods: This study aimed to examine the efficacy of microwave heat treatment for inhibition of germination of corn kernels and for optimization of power and exposure time required for effective aging treatment. Artificial inhibition was induced in corn kernels using microwave heat treatment. Seven power levels were examined (400, 500, 600, 700, 800, 900, and 1000 W) at each of the four exposure times (0.5, 1.0, 1.5, and 2.0 min). Results: Corn kernels could be aged effectively after heating for 0.5~1.0 min at powers greater than 800 W, with increasing efficacy observed at higher powers. Further analysis showed that the most effective inhibition of germination was observed at 1000 W for 40 s. This setting did not cause any physical damage to the corn kernels. Conclusions: Optimal inhibition of corn kernel germination was achieved using higher power for shorter times, which may be useful for industrial corn seed treatment.

A Theoretical Modeling for Suggesting Unique Mechanism of Adolescent Calcium Metabolism

Purpose: Modeling has been used for elucidating the mechanism of complex biosystems. In spite of importance and uniqueness of adolescent calcium (Ca) metabolism characterized by a threshold Ca intake, its regulatory mechanism has not been covered and even not proposed. Hence, this study aims at model-based proposing potential mechanisms regulating adolescent Ca metabolism. Methods: Two different hypothetic mechanisms were proposed. The main mechanism is conceived based on Ca-protein binding which induces renal Ca filtration, while additional mechanism assumed that active renal Ca re-absorption regulated Ca metabolism in adolescents. Mathematical models were developed to represent the proposed mechanism and simulated them whether they could produce adolescent Ca profiles in serum and urine. Results: Simulation showed that both mechanisms resulted in the unique behavior of Ca metabolism in adolescents. Based on the simulation insulin-like growth factor-1 (IGF-1) is suggested as a potential regulator because it is related to both growth, a remarkable characteristic of adolescence, and Ca metabolism including absorption and bone accretion. Then, descriptive modeling is employed to conceptualize the hypothesized mechanisms governing adolescent Ca metabolism. Conclusions: This study demonstrated that modeling is a powerful tool for elucidating an unknown mechanism by simulating potential regulatory mechanisms in adolescent Ca metabolism. It is expected that various analytic applications would be plausible in the study of biosystems, particularly with combination of experimental and modeling approaches.

Statistical modeling for estimating glucosinolate content in Chinese cabbage by growth conditions: Statistical estimation of glucosinolate by growth conditions

BACKGROUND Glucosinolate in Chinese cabbage (Brassica campestris L. ssp. pekinensis (Lour.) Rupr) has potential benefits for human health, and its content is affected by growth conditions. In this study, we used a statistical model to identify the relationship between glucosinolate content and growth conditions, and to predict glucosinolate content in Chinese cabbage. RESULT Multiple regression analysis was employed to develop the models growth condition parameters of growing period, temperature, humidity and glucosinolate content measured in Chinese cabbage grown in a plant factory. The developed model was represented by a second-order multi-polynomial equation with two independent parameters: growth duration and temperature (adjusted R2  = 0.81), and accurately predicted glucosinolate content after 14 days of seeding. CONCLUSION To our knowledge, this study presents the first statistical model for evaluating glucosinolate content, suggesting a useful methodology for designing glucosinolate-related experiments, and optimizing glucosinolate content in Chinese cabbage cultivation.

MODEL-BASED ANALYSIS OF IGF-1 EFFECT ON OSTEOBLAST AND OSTEOCLAST REGULATION IN BONE TURNOVER

The main determinant of bone Ca accretion is a bimolecular regulatory network on osteoblast (OB) and osteoclast (OC). Even though IGF-1 is known as an important regulator in bone cell cycle, little has been done to model IGF-1 action in bone cell regulation. Thus, the objective is to develop a mathematical model that depicts the regulatory action of IGF-1 onto the OB and OC interaction, and to evaluate adolescent and adult bone Ca accretion in response to differences in IGF-1 levels. As a result, a dynamic model of OB and OC with two main regulatory systems, i.e., Receptor Activator for Nuclear Factor κB (RANK)-RANK Ligand (RANKL)-osteoprogerin (OPG) system, and TGF-β, was augmented with the IGF-1, and incorporated into Ca kinetic data to predict exchangeable bone Ca. The developed model could predict a change in OB and OC levels in response to perturbations in regulators, producing results consistent with bone physiology and published experimental data. The model also estimated parametric difference in regulators between adults and adolescents, suggesting that RANKL/OPG in adolescents was about 4 times higher than in adults, while adolescent serum PTH and IGF-1 concentrations were 60% and 220% of those of adults, respectively. This study highlighted the influence of IGF-1 on the regulation of bone cells in positively modulating bone Ca, suggesting that IGF-1 may be an effective target for reducing bone loss by promoting mature OB.