• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1529-1529
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• 2001

The watercore in apple is very important factor in storage and sorting of fruit. Most consumers tend to prefer the apple included watercore in immediately after harvest, however the watercore causes fruit flesh to brown during storage and lose the worth after all. But it is practically impossible to judge to the naked eye whether an apple has watercore or not. Therefore, the rapid, accurate and non-destructive analysis method for discrimination of watercore should be settled without delay. In this study we attempted the discrimination and quantitative analysis of watercore in apple fruit using near-infrared transmittance spectroscopy ‘Fuji’ apple fruits produced in Kyungpook of Korea was used in this experiment. The watercore content in apple was evaluated by graphic treatment of culled slice sections(10 mm). NIR transmittance spectra were collected over the 500 to 1000 nm spectral region with a spectrometer (Sentronic Co., Germany). The calibration models were carried out by partial least squares (PLS) analysis between NIR spectra data of apples and chemical data of watercore content. The spectra were different in absorbance between apple included watercore and not included one. Apple included watercore had higher absorption band than sample not included one at 732 and 820 nm. The calibration model seems to be accurate to predict the watercore content in apple fruit, the correlation coefficient (R) and root mean square error of prediction (RMSEP) were 0.99 and 0.93%, respectively. This result indicates that the PLSR calibration model by using NIR transmittance spectroscopy could be used for discrimination of watercore in apple fruit.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.153-159
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• 1998

A possibility of evaluation of the major internal quality factors-Brix, moisture contents, firmness and acid content in the Korean domestic 'Fuji'apple fruits by near-infrared reflectance spectroscopic (NIRS) methods were investigated. A multiple linear regression(MLR) analysis between the data obtained by physico- chemical analysis method using refractometer, freeze drier, texture analyzer and titrater and NIR spectral data was carried out to make a calibration. The standard error of prediction(SEP) of Brix, moisture, firmness and acid content were $0.50^{\circ}Brix,\;0.64%,\;0.14kg/cm^2$ and 0.07%. It is concluded that NIRS methods can be used to evaluate Brix and moisture contents of in a apple non-destructive and rapid way but the accuracy for determination of firmness and acid content was slightly low.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.531-538
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• 2011

This study was carried out to investigate the influence of defoliation by Marssonina blotch (Diplocarpon mali Harada et Sawamura) on vegetative growth and fruit quality in 'Fuji'/M.9 apple tree. Soluble solid contents decreased when the defoliation percentage by Marssonina blotch was over 10% before the end of September, and fruit weight decreased when percentage of defoliation was over 30%. Fruit red color and starch contents tend to decrease as percentage of defoliation near the fruit increased. Return bloom, fruit weight, and shoot growth the following year tend to decrease as percentage of defoliation increased. Photosynthetic rate of healthy leaves in bourse shoot during the end of September was maintained about $10{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, effects in increasing fruit growth and soluble solid contents after the end of September. Photosynthetic rates for the damaged leaf, damaged area was over 50% on the leaf surface, while 30% of the photosynthetic rates of healthy leaf are without damage applied with Marssonina blotch at the end of September. The results show that the decrease of fruit quality in defoliation treatments may be caused by the decrease of starch contents in fruit, and that was caused by the photosynthetic rates of leaves near fruit was decreased by Marssonina blotch in the wake of August.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1131-1131
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• 2001

To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.4
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• pp.36-42
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• 2018

Although continuous passenger injuries and physical damages are repeated due to the unexpected aviation turbulence encountered during operations, there is still exist the limitation for preventing recurrence of similar events because the lack of real-time information and delay in technological developments regarding various operating conditions and variable weather phenomena. The purpose of this study is to compare and analyze the meteorological data of the aviation turbulence occurred and actual flight data extracted from the Quick Access Recorder(QAR) to provide some precursors that the pilot can identify aviation turbulence early by referring thru the flight instrumentation indications. The case applied for this study was recent event, a scheduled flight from Incheon Airport, Korea to Narita Airport, Japan that suddenly encountered turbulence at an altitude of approximately 14,000 feet during approach. According to the Korea Meteorological Administration(KMA)'s Regional Data Assessment and Prediction System(RDAPS) data, it was observed that the strong amount of vorticity in the rear area of jet stream, which existed near Mount Fuji at that time. The QAR data analysis shows significant changes in the aircraft's parameters such as Pitch and Roll angle, Static Air Temperature(SAT), and wind speed and direction in tens of seconds to minutes before encounter the turbulence. If the accumulate reliability of the data in addition and verification of various parameters with continuous analysis of additional cases, it can be the precursors for the pilot's effective and pre-emptive action and conservative prevention measures against aviation turbulence to reduce subsequent passenger injuries in the aviation operations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.208-213
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• 2021

There is a lack of studies comparing the internal quality of fruit with its external quality. However, issues of internal quality of fruit such as internal browning are important. We propose a method of classifying normal apples and internally browned apples using a near-infrared (NIR) non-destructive system. Specifically, we found the optimal wavelength and characteristics of the spectra for determining the internal browning of Fuji apples. The NIR spectra of apples were obtained in the wavelength range of 470-1150 nm. A group of normal apples and a group of internally browned apples were identified using principal component analysis (PCA), and a partial least squares regression (PLSR) analysis was performed to develop and evaluate the discriminant model. The PCA analysis revealed a clear difference between the normal and internally browned apples. From the PLSR, the correlation coefficient of the predictive model without pretreatment was determined to be 0.902 with an RMSE value of 0.157. The correlation coefficient of the predictive model with pretreatment was 0.906 with an RMSE value of 0.154. The results show that this model is suitable for classifying normal and internally browned apples and that it can be applied for the sorting and evaluation of agricultural products for internal and external defects.

• Journal of the Speleological Society of Korea
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• no.74
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• pp.23-31
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• 2006

(1) Kaeusetgul Cave in Kimnyong-Ri, Jeju-Do, Korea. Kaeuset-gul Cave (KC) is situated in NNE area of the Manjang-gul cave (125m a.s.l.). Kaeuset-gul Cave lies at $126^{\circ}45'22"$ E in longitude and $33^{\circ}33'09"$ N in latitude. The coast belong Kimnyeong-Ri, Kujwa-eup, Jeju-Do. Altitude of the cave-entrance is 10m and length of the cave is 90m. Lava hand-specimens of KC are studied by X-ray fluorescence analysis (XRF). Average major chemical components of specimens from KC is as follows (wt.%); $SiO_2=47.03$, $TiO_2=3.16$, $Al_2O_3=18.41$, FeO*=13.53, MnO=0.14, MgO=5.05, CaO=8.66, $Na_2O=2.81$, $K_2O=0.67$, $P_2O_5=0.55$ in KC. Polarizing microscopic studyindicates that these specimens are described of alkali-basalt. (2) Tachibori Fuketsu (Cave) in Shizuoka Prefecture, Fuji Volcano, Japan Tachibori Fuketsu lies attoward the south in skirt of the Fuji volcano, $138^{\circ}42'04"$ east longitude and $35^{\circ}18'00"$ north latitude. The location of cave entrance is 2745, Awakura, Fujinomiya-shi, Shizuoka Prefecture. The above sea level and length of Tachibori Fuketsu are 1,170m and 82m. Average major chemical components of specimens from cave areas follows (Total 100 wt.%) ; ($SiO_2$=50.52, $TiO_2$=1.69, $Al_2O_3$=15.47, FeO*=13.13, MnO=0.20, MgO=5.97, CaO=9.17, $Na_2O$=2.52, $K_2O$=0.94 and $P_2O_5=0.40).$ Polarizing microscopic study indicates that these specimens may belong to tholeiite-basalt series. According to polarizing microscopic study, Au (Augite), P1 (Plagioclase), and O1 (Olivine) are contained as phenocryst minerals. (3) Gorely Cave in Kamchatka Peninsula, Russia Gorely caldera is located at the southeastern part of Kamchatka Peninsula, about 75km southwest of Petropavlovsk-Kamchatskiy.. Gorely lava caves are situated in NHE area of Mt. Gorely volcano (1829m a.s.1.). One of lava cave (Go-9612=K-1) lies at $158^{\circ}00'22"$ east longitude and $52^{\circ}36'18"$ north latitude. The elevation of cave entrance is about 990m a.s.1. and the main cave extends in the NNW direction for about 50m by 15m wide and 5m in depth. The cave of K-3is near the K-1 cave. "@Lava hand-specimens K-1 and K-3 caves are studied by X-ray fluorescence analysis and polarizing microscopic observation. Average major chemical components of specimens from these caves are as follows (wt.%) ;($SiO_2$=55.12, $TiO_2$=1.25, $Al_2O_3$=16.07, T-FeO* =9.41, MnO=0.16, MgO=5.01, CaO=7.21, $Na_2O$=3.39, $K_2O$=1.92, $P_2O_5$=0.45) and these values indicate that the Gorely basaltic andesite belong to high alumina basalt. Polarizing microscopic study indicates that these specimens are described of Augite andesite.

• Horticultural Science & Technology
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• v.17 no.4
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• pp.476-480
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• 1999

This study was carried out to determine the optimum storage temperatures of six fruit nurseries ('Fuji' apple, 'Niitaka' pear, 'Sheridan' grape, 'Yumyoung' peach, 'Fuyu' persimmon, and 'Hayward' kiwifruit) from 1995 to 1997. Nursery plants were planted in field after storage at -5, 0, and $5^{\circ}C$ for one year. Nurseries stored at $0^{\circ}C$ showed highest survival rate and growth after planting. The survival rate of 'Sheridan' grape and 'Hayward' kiwifruit nursery plants stored at $-5^{\circ}C$ was 0%. Cold resistance of the two fruit nursery plants appeared weaker than others. Also, 'Niitaka' pear nursery plants stored at $5^{\circ}C$ showed significantly high survival rate and growth after planting. The higher storage temperature, the lower mineral and carbohydrate contents of nursery plants. Therefore, $0{\sim}5^{\circ}C$ in 'Niitaka' pear and near $0^{\circ}C$ in other five fruit nursery stocks were found to be the optimum storage temperatures.