Determination of viability of Retinispora (Hinoki cypress) seeds using FT-NIR spectroscopy

Mukasa, Perez,Wakholi, Collins,Mo, Changyeun,Oh, Mirae,Joo, Hye-Joon,Suh, Hyun Kwon,Cho, Byoung-Kwan Elsevier 2019 Infrared physics & technology Vol.98 No.-

<P><B>Abstract</B></P> <P>The use of Hinoki cypress for the formation of healing forest is gradually increased in South Korea, but the germination rate of these seeds is low, and viability determination by conventional methods is destructive and time-consuming. Therefore, the aim of this study was to investigate the potential of Fourier transform infrared (FT-NIR) spectroscopy in determining the viable seeds of Hinoki cypress nondestructively. FT-NIR reflectance spectra for single seeds were collected in the range of 4000–10,000 cm<SUP>−1</SUP> (1000–2500 nm), and a germination test was carried out to determine viability. To differentiate between viable and nonviable seeds, a multivariate classification with partial least square discriminant analysis (PLS-DA) was developed. The best PLS-DA model assigned the seeds to their respective classes, with 97.7–99.2% and 94.4–95.4% accuracy in the calibration and validation sets, respectively. The PLS-DA Beta coefficient revealed the important wavelength to differentiate viable from nonviable seeds, which was attributed to changes in the chemical composition of the seeds, such as lipids and proteins, which might be responsible for the germination ability of the seeds. Variable importance of projection (VIP) was applied on the spectral data which reduced original variables from 1557 to 27. The developed VIP-PLS-DA model resulted into classification accuracy of 97.7% in calibration and 91.7% in the validation set, with maximum normalization data preprocessing method. In conclusion, the results demonstrate the potential of FT-NIR spectroscopy as a powerful nondestructive method for determination of viable Hinoki cypress seeds, which could be applied in the development of an online sorting technique for seed companies and nurseries.</P> <P><B>Highlights</B></P> <P> <UL> <LI> FTNIR and chemometrics to detect natural viability of Hinoki seeds was investigated. </LI> <LI> A model with minimum variables for viability detection was constructed with PLSDA and VIP. </LI> <LI> This work showed over 95% model accuracy achieved for determination of viable Hinoki seeds. </LI> </UL> </P>

A prediction model of Nephrolithiasis Risk: A population-based cohort study in Korea

David Mukasa,성주훈 대한비뇨의학회 2020 Investigative and Clinical Urology Vol.61 No.2

Purpose: Well-validated risk prediction models help to stratify individuals on the basis of their disease risks and to guide health care professionals in decision-making. The incidence of nephrolithiasis has been increasing in Korea. Racial differences in the distribution of and risk for nephrolithiasis have been reported in Asia but no population-specific nephrolithiasis models have been developed. We aimed to develop a simplified nephrolithiasis prediction model for the Korean population by using data from general medical practice. Materials and Methods: This was a prospective, population-based cohort study in Korea. A total of 497,701 participants from the National Health Insurance Service–National Sample Cohort (NHIS-NSC) were enrolled from 2002 to 2010. A Cox proportional hazards model was used. Results: During a median follow-up time of 8.5 years (range, 2.0–8.9 years) and among 497,701 participants, there were 15,783 cases (3.2%) of nephrolithiasis. The parsimonious model included age, sex, income grade, alcohol consumption, body mass index, total cholesterol, fasting blood glucose, and medical history of diseases. The Harrell's C-statistic was 0.806 (95% confidence interval [CI], 0.790–0.821) and 0.805 (95% CI, 0.782–0.827) in the derivation and validation cohorts, respectively. Conclusions: The results of the present study imply that nephrolithiasis risk can be predicted by use of data from general medical practice and based on predictors that clinicians and individuals from the general population are likely to know. This model comprises modifiable risk factors and can be used to identify those at higher risk who can modify their lifestyle to lower their risk for nephrolithiasis. This study also offers an opportunity for external validation or updating of the model through the incorporation of other risk predictors in other settings.

A prediction model of low back pain risk: a population based cohort study in Korea

David Mukasa,Joohon Sung 대한통증학회 2020 The Korean Journal of Pain Vol.33 No.2

Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its re-currence.Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service–National Sample Cohort en-rolled from 2002 to 2010. We used Cox proportional hazards models.Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, in-come grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescrip-tion, and medical history of diseases. The Harrell’s C-statistic was 0.812 (95% con-fidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been de-veloped and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorpo-rating other risk predictors in other settings, especially in this era of precision medi-cine.

Purity Detection for Seedless Watermelon Seeds using Near Infrared Hyperspectral Imaging Spectroscopy

( Perez Mukasa ),( Collins Wakholi ),( Jannat Yasmin ),( Mohammed Raju Ahmed ),( Hee Young Lee ),( Eunsoo Park ),( Byoung-kwan Cho ) 한국농업기계학회 2020 한국농업기계학회 학술발표논문집 Vol.25 No.1

Seedless watermelon seeds (triploid) production is nearly the same as seeded (diploid and tetraploid seeds), although production cost is higher in triploid seeds than seeded one due to the high cost. Many attempts to separate these two kinds of seed before planting have had only slight success with conventional means. In this investigation, we demonstrate the potential of near infrared hyperspectral imaging (NIR-HSI) method to discriminate triploid (3x) seeds from diploid (2x) and tetraploid (4x) seeds, and its application on the online system for real time seed sorting. In order to establish a model for purity discrimination, NIR-hyperspectral images of these three seed groups were collected and analyzed. A multivariate classification model with partial least square discriminant analysis (PLS-DA) was developed, and accuracy analyzed. Over 95% accuracy was obtained in both calibration and validation sets of the PLS-DA model. We further applied the model to the online system for real time discrimination that yielded 80.5% accuracy separation of triploid seeds from its counterparts. The results show good potential of NIR hyperspectral imaging technique for purity separation of watermelon seedless seeds nondestructively, that can be automated for real time sorting for commercial purposes.

Determination of Viability of Japanese Larch Seeds using Hyperspectral Imaging

( Perez Mukasa ),( Byoung-kwan Cho ),( Hye-joon Joo ),( Yong-rak Kwon ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1

Japanese larch (Larix kaempfen) is a deciduous needle-leaf conifer, which is valued for the production of strong, durable and naturally decay-resistant woods that have been used for construction of bridges, ships, buildings. Their ability to grow in a harsh cold environment, coupled with several values and uses, have stimulated interests in larch cultivation throughout. However, poor seed lot quality is the major hurdle for production of sufficient quantity of planting stocks. This study aims at the potential of Hyperspectral SWIR imaging to classify viable and non-viable seeds. In order to establish a model for viability determination, hyperspectral SWIR images for 200 seeds were collected with conventional germination test. A multivariate classification model with partial least square discriminant analysis (PLS-DA) was developed, and the accuracy was analyzed. The results show the good potential of hyperspectral imaging technique for the viability determination of larch seeds.

The Case for a ‘Public Lane’ on the Information Superhighway : Strategies for and Implications the GII on the Third World

Stanford Garikayi Mukasa 한국방송학회 1996 한국방송학회 세미나 및 보고서 Vol.- No.-

Initiation of Franciscan subduction along a large-offset fracture zone: Evidence from mantle peridotites, Stonyford, California

Choi, Sung Hi,Mukasa, Samuel B.,Shervais, John W. Geological Society of America 2008 Geology Vol.36 No.8

Electrical breakdown of microwave plasma in water

Yoshiaki Hattori,Shinobu Mukasa,Hiromichi Toyota,Shinfuku Nomura 한국물리학회 2013 Current Applied Physics Vol.13 No.6

The electrical breakdown of microwave plasma in water was investigated between 1 and 30 kPa. The dependency of the ignition power for generating plasma on the size of coaxial electrode was measured. The ignition power decreases with a decrease of the diameter of the inner electrode. The behavior of microwave plasma in water was observed using a high-speed camera. The plasma ignites in a bubble generated by microwave heating. The model for calculating the electric field was created on the basis of the captured images of the bubble just before plasma ignition. The method presented can be used to visualize the electrical field distribution in the bubble. The electric field breakdown was calculated using the measured ignition power. The electric field breakdown of plasma in water is of the same order as gas phase plasma.

Hyperspectral Imaging System for Online Sorting of Adulterated Almond Nuts

( Mohammad Akbar Faqeerzada ),( Mukasa Parez ),( Santosh Lohumi ),( Hoonsoo Lee ),( Hee Young Lee ),( Collins Wakholi ),( Rahul Joshi ),( Byoung-kwan Cho ) 한국농업기계학회 2020 한국농업기계학회 학술발표논문집 Vol.25 No.1

Almonds are nutrient-rich nuts, their health benefits are potentially linked to the high consumption worldwide. Due to relatively higher price, the producers are targeting it as an illegal practice for earning more profit. The most common adulterants are based on superficially matching, which the apricot nut as an adulterant comparatively are inexpensive, almost identical in color, texture, odor, and other physicochemical characteristics with almonds. In addition, apricots nuts contain amygdalin component which is converted to hazardous toxic cyanide in the digestive system. In the past decades, hyperspectral imaging (HSI) has attracted good attention as a rapid, real-time and non-destructive measurement method for food quality and safety analysis. In this study, near-infrared hyperspectral imaging (NIR-HSI system) with the wavelength of 900-1700 nm synchronized to a conveyor belt was used for online detection of added apricot nuts in almond. A total of 448 samples from different varieties of almond and apricot nuts (112x4) were scanned while the samples are moving on the conveyor belt. The spectral data were extracted from each imaged nuts and used for developing a PLS-DA model coupled with different preprocessing techniques. The PLS-DA model showed over 95% accuracy for the validation set. Additionally, the obtained beta coefficient from the developed model was used for pixel-based classification. An image processing algorithm was developed for chemical visualization mapping of almond and apricot nuts. The online classification system feedback with an overall accuracy of 87% for the classification of nuts. The developed online prototype (NIR-HIS) system combined with multivariate analysis exhibit strong potential for classification of adulterated almond, and the result indicates the system can be used effectively for high-throughput industrial classification of adulterated almond nuts in an industrial environment.

스발바드 맨틀암석에 대한 Lu-Hf 및 Re-Os 동위원소 시스템의 활용 : 맨틀과 지각간의 성인적 연계성에 대한 고찰

최성희,K. Shzuki,S.B. Mukasa,이종익,정해명 한국암석학회 2010 한국암석학회 학술발표회 논문집 Vol.2010 No.5