• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.45-49
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• 2003

According to the rising of national economic level, domestic consumption of vegetables having high additive values is increased continuously due to increased consumption of meat in last decade. These vegetables are produced almost in this country and are limited to import from neighbor countries in due of high transportation expenses for storing in refrigerated container. It is very important to mechanize the harvest work, forming more than 30% for their production cost, in order to cultivate variable vegetables at the same time according to their harvesting seasons. In this state its former harvest methods, with using of human power or semi-automatic harvest, caused to increase their production cost due to high labor cost and low working efficiency.

• Korean Journal of Agricultural Science
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• v.49 no.2
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• pp.341-355
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• 2022

This research was to examine the differences in post-harvest quality of melons depending on the harvest time after fruit setting. Musk melon cultivar 'K3' plants were grown in glass house conditions with a hydroponic system, and the fruits were harvested at 50, 60, and 70 days after fruit setting. The post-harvest characteristics of melons stored at 7℃ were measured over 32 days. The harvested fruits at 50, 60, 70 days after fruit setting did not differ significantly in weight, height, or size. Solid sugar content was highest in the fruits harvested at 70 days after fruit setting, but firmness, L* value, and respiration rate were highest in the fruits harvested at 50 days after fruit setting. When the harvested melons were stored at 7℃, 'K3' melons responded differently according to the harvest days after fruit setting. The major changes during storage of 'K3' melons can be summarized as follows: Firmness, respiration, moisture content, and general appearance index during storage were highest in the melons harvested at 50 days after fruit setting, but soluble solid content, fresh weight loss, and sensory evaluation were high in the melons harvested at 60 and 70 days after one. During storage at 7℃, there were no significant differences in the appearance of 'K3' melons harvested at different periods after fruit setting, but difference in soluble solid content and taste were noted. It is recommended that the fruit of 'K3' melon plants be harvested about 60 days after fruiting to provide consumers with the highest quality for taste and for storage.

• Journal of the Korean Society of Tobacco Science
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• v.7 no.1
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• pp.39-47
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• 1985

Normally cultured aromatic tobaccos, KA 101 and KA 103, were primed progressively in three-leaf segments, either 7 days before bud, bud, or early flower stage with 7 days interval, respectively, The cured leaves were weighed for yield, graded, analyzed for quality-related constituents including volatile aroma components. Also the cured leaves were manufactured and smoked by panelists. Yield and quality by price decreased with advancing ripeness. Reducing sugar, total nitrogen, protein nitrogen decreased with successive ripeness, but reverse in this trends with nicotine, petroleum ether extracts and volatile acids components. Among volatile neutral components, furfural, furfuryl alcohol, benzyl alcohol, penethyl alcohol and p-cresol decreased, but solanone increased with delayed harvest. Neophytadiene, oxysolanone, furfuryl aceton was highest at mid harvest, which was judged to be best by panelists. Mid harvest, first primed at bud stage when leaf color comes to pale green to yellow green, seems to be highly recommendable.

• Korean Journal of Medicinal Crop Science
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• v.5 no.4
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• pp.284-288
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• 1997

In order to study on suitable harvest time of adlay utilizing self-feeding combine harvester with four rows, which is originally designed for rice harvest, harvesting were carried out at four different times (40, 50, 60 and 70 days after anthesis) . For efficient operation, appropriate working rows were 2 rows at 50 days after anthesis and working speed was 0.26m/sec at 60 days after anthesis. Theoretical working capability was 11.23a/hr at 60 days after anthesis. As the harvesting was delayed, water content of adlay decreased. Water content of culm+leaf was $69.7{\sim}55.3%$ and water content of grain was 34.2% at 60 days after anthesis. The later adlay was harvested. the higher the percent of ripened grain was. But the immature grain was decreased. Remnants was less than 1.8% at 60 days after anthesis. The later adlay was harvested, the heavier volume weight was. Yield was the highest at 60 days after anthesis. When utilizing self-feeding combine harvester with four rows, which was originally designed for rice harvest, suitable harvesting time was 60 days after anthesis. Therefore, theoretically suitable harvest time was 68 days after anthesis.

• Smart Media Journal
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• v.6 no.4
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• pp.58-64
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• 2017

Modern society is characterized by rapid increase in world population, aging of the rural population, decrease of cultivation area due to industrialization. The food problem is becoming an important issue with the farmers and becomes rural. Recently, the researches about the field of the smart farm are actively carried out to increase the profit of the rural area. The existing smart farm researches mainly monitor the cultivation environment of the crops in the greenhouse, another way like in the case of poor quality t is being studied that the system to control cultivation environmental factors is automatically activated to keep the cultivation environment of crops in optimum conditions. The researches focus on the crops cultivated indoors, and there are not many studies applied to the cultivation environment of crops grown outside. In this paper, we propose a method to improve the harvestability of poor areas by monitoring the areas with bad harvests by using big data analysis, by precisely predicting the harvest timing of fruit trees growing in orchards. Factors besides for harvesting include fruit color information and fruit weight information We suggest that a harvest correlation factor data collected in real time. It is analyzed using the Apache Spark engine. The Apache Spark engine has excellent performance in real-time data analysis as well as high capacity batch data analysis. User device receiving service supports PC user and smartphone users. A sensing data receiving device purpose Arduino, because it requires only simple processing to receive a sensed data and transmit it to the server. It regulates a harvest time of fruit which produces a good quality fruit, it is needful to determine a poor harvest area or concentrate a bad area. In this paper, we also present an architectural model to determine the bad areas of fruit harvest using strong data analysis.

• Horticultural Science & Technology
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• v.31 no.4
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• pp.437-446
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• 2013

This study was conducted for three years (2007, 2009, and 2010) to investigate the changes in fruit quality during maturation, and the quality and storage ability of fruits harvested at different times of 'Fuji' apple in Daegu region with a high air temperature during the fall season. Changes in apple fruit quality during the maturation period were investigated from 120-135 days to 183-198 days after full bloom. In comparing quality and storage ability of fruits harvested at different times, fruits harvested more than 180 days after full bloom were used. During the maturation period, poor coloring was the problem for 'Fuji' apple in Daegu region by the high air temperature about $20^{\circ}C$. In comparing quality of fruits harvested at different times, the soluble solid contents and hunter a value were increased by the extended harvest time. Fruit weight during harvest was not affected by different harvest time, while the fruit firmness and titratable acidity during harvest were decreased critically when the freezing damage happened. Ethylene production, fruit firmness, and titratable acidity during cold storage for twenty weeks did not differ according to the different harvest time. Soluble solid contents of fruits harvested at 216 days after full bloom in 2009 were similar at the time of harvest and cold storage. For fruits harvested at 201 days after full bloom, soluble solid content during cold storage was higher than during harvest time. However fruit firmness, soluble solid content, and titratable acidity after cold storage of fruit harvested after freezing damage was lower than those of the fruit harvested before freezing damage. The results show that the extended harvest time of 'Fuji' apples about 2-4 weeks from 180-200 days after full bloom in area with above-air temperature during fall season was seemed to be beneficial to enhancing soluble solid contents and fruit red color, but harvesting after the middle of November was dangerous because minimum air temperature began to fall under $-3.0^{\circ}C$.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.5
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• pp.373-380
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• 2004

The production of sweet (su) and super sweet corns (sh2) has been economically feasible in Korea in recent years. Major factors limiting super sweet corn production are low germination and low seedling vigor. Since seed quality is closely related to seed maturity, the optimum harvest time for the seed production of sweet and super sweet corns was studied and the quality of seeds with varying maturities was investigated in 2001 and 2002 cropping seasons. The parents of the sweet corn seeds were Hybrid Early Sunglow and 'Golden Cross Bantam 70' and those of super sweet corn were Xtrasweet 82 and 'For­tune'. Seeds were harvested at 21, 28, 35, 42, 49, and 56 days after silking (DAS). As the seeds developed, seed weight of sweet corn increased and the seed moisture content decreased faster than that of super sweet corn. Germination rates of sweet corn seeds harvested 21 and 28 DAS at $25^{\circ}C$ and emergence rates in the cold soil test were significantly lower than those of seeds harvested after 42 DAS in both years. Although the germination rates of super sweet corn seeds with varying maturities showed similar patterns as sweet corn seeds at $25^{\circ}C$, the emergence rate of super sweet corn seeds in cold soil test continuously increased with seed maturity. This suggests that seed quality of super sweet corn should be tested in a cold soil test to estimate field emergence. As the seeds developed, leakage of total sugars and electrolytes from the both sweet and super sweet corn seeds decreased up to 42 or 49 DAS. The $\alpha-amylase$ activities of both sweet and super sweet corn seeds increased with seed maturity from 21 to 35 or 49 DAS depending on genotype and year. The optimum harvest time for the seed production of sweet corn was 42 DAS and 49 DAS for super sweet corn considering emergence rate and plumule dry weight in the cold soil test, leakage of sugars and electrolytes from the seeds, and $\alpha-amylase$ activity.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47 no.3
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• pp.254-258
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• 2002

The characteristics of yield and quality in 3 rice varieties according to harvest time of 40, 50, 60 and 70days after heading(DAH) was investigated to obtain basic information for the production of high quality rice. The protein content of milled rice increased significantly as increase the ripening period from 40 to 70DAH. The palatability value measured by rice taster was the highest in ripening period of 40DAH and decreased with increase of ripening period. The optimum time for harvest in terms of both rice yield and quality was 4050DAH in Daejinbyeo, and 4060DAH in Seojinbyeo and Chucheongbyeo, however, it was considered to be 4050DAH only for rice quality. The palatability value measured by rice taster showed a highly negative correlation with protein content of milled rice(1=-0.94$^{**}$) and cumulative ripening temperature(r=-0.79$^{**}$).

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Journal of Nutrition and Health
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• v.16 no.1
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• pp.1-9
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• 1983

An investigation was made of the effect of carrot variety and harvest time (DAP) on the composition of carotenoids and the Retinol Equivalent value by column chromatography, and of the relation of the total carotenoid content to the Retinol Equivalent by regression analysis. The results are summarized as follows : 1. There were very significant differences of total carotenoid, ${\alpha}-carotene,\;and\;{\beta}-carotene$ contents among carrot varieties and between two harvest times(90 DAP, 99 DAP). Especially, each component of carotenoids in carrots harvested at 99 DAP attained higher concentrations than 90 DAP. 2. Retinol Equivalent value showed the tendency to increase as the numbers of DAP incr The Shindaehyung-Ochon and Hongshim-Ochon varieties had the highest RE. value. 3. In the composition of carotenoids and Retinol Equivalent value, the Shamgae-Ochon variety had the nearest value to the mean of all variety. Therefore, it is most reasonable to use the Shamgae-Ochon variety for the analysis of vitamin A value in carrots. 4. The regression of the totel carotenoid (x) to the Retinol Equivalent (y) was y = 0.074 + 0.12x $(r^2$ = 0.91). So, if total carotenoid content is determined, R.E. value can be predicted by this regression equations, saving time and labor.