• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.153-160
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• 2020

This study was conducted out to investigate the effect of harvest time of the day, precooling or not, and temperature of precooling and storage on the marketability in strawberries 'Maehyang' for export in May. Strawberry colored with 60±5% of the skin was harvested at 07:00 am or 15:00 pm, respectively. After harvesting, some strawberries were precooled to 0, 2, 4℃ for 3 hours in the cold store, respectively, and the others were kept at room temperature. And then, strawberries were stored at low temperature in the cold store set at 4, 8 or 10℃ storage temperatures. The weight loss rate, firmness, soluble solids content, color, incidence of gray mold of strawberries were measured at two days intervals during storage for 14 days. Both 07:00 am and 15:00 pm harvest, fruits as the storage periods lapses increased weight loss rate compared to the weight at harvest time of the day, and the difference in the weight loss rate of fruits depending on the treatment was greater at 15:00 pm harvest than at 07:00 am. Firmness tended to increase again after 8th day at 07:00 am or 15:00 pm harvest, respectively. In the afternoon harvest, 10℃ storage without precooling showed the lowest fruit firmness on the 2nd day after storage. The soluble solids content at 07:00 am or 15:00 pm harvest tended to be maintained at high value with precooled and stored at low temperature as storage days elapse. The color values were significantly higher at 'L' indicating brightness and lower at 'a', indicating redness at low storage temperature regardless of harvesting time of the day and whether it was precooling or not. The incidence of gray mold was higher at 15:00 pm harvest than at 07:00 am harvest, and it was significantly higher in the treatments stored at 10℃ after precooling similarly. In this study, strawberry 'Maehyang' for export harvested at 07:00 am and stored at 4℃ after precooling at 0℃ maintained the best shelf life, therefore, it is judged that desirable to harvest in the morning with low temperature and to precool and store at low temperature.

• 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$^{**}$).

• Journal of Practical Agriculture & Fisheries Research
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• v.6 no.1
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• pp.81-89
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• 2004

The effects of developed grape bags on the micro-climate changes of bag, physiological disorder, pathogenic decay, quality and harvest time evaluation in 'Campbell Early' grapevines were studied. The temperature and light transmittance of developed grape bags showed no differences compared with the onces of conventional bag and non-bagging, but relative humidity and the amount of water evaporation were changed in all treatments. The occurrence of unfertilized fruit, poorly colored fruit, russet and gray mold rot showed no significant difference in all treatment at harvest time. Developed grape bags decreased effectively the occurrence of cracking fruit and bitter rot in 'Campbell Early' fruit. There was no difference in growth of cluster and berry, soluble solids and total acidity in fruits, degree of skin color and bloom appearance at harvest time. The skin color and fruit boom and harvest time evaluation in developed grape bags were resulted excellent compared with the once of conventional bag and non bagging.

• 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.

• Korean Journal of Medicinal Crop Science
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• v.24 no.2
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• pp.110-114
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• 2016

Background: This study aimed to investigate the effect of harvest time on the growth, yield characteristics and loganin content in Dipsacus asperoides Wall. Methods and Results: Dipsacus asperoides seedlings were planted within a nursery environment in early May 2015 and harvested in early, middle and late October 2015, and early November 2015. Harvest time did not result significant differences in the plant height, stem diameter, branch length, leaf width and aboveground dry weight moreover, no significant differences were observed in root length, number of roots and root diameter. However, the diameter of lateral roots was greater in the harvests from the late October and period thereafter. The highest values of root dry weight and yield were recorded in early November. Specifically, the yield significantly increased from 205 kg/10 a (index: 100) in early October to 358 kg/10 a (index: 175) in early November, in terms of root part weight. Loganin contents of D. asperoides differed significantly among harvest times raging from 0.0766% in early October to 0.1704% in late November, thereby showing an increasing trend in later harvest times. Conclusions: These results suggest that the optimum harvest time for D. asperoides is early November, when the yield is the highest. Harvest time significantly affected loganin contents, which constantly increased from early October until early November.

• Food Science and Preservation
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• v.21 no.6
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• pp.917-924
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• 2014

Normal- and late-harvested Fuji apples were fermented using the rapid-fermenting yeast strain Saccharomyces cerevisiae SS89. The late-harvest apples showed a slightly higher soluble-solid content with a lower level of total-acid and moisture (p<0.05) contents as well as hardness (p<0.05) than the normal-harvest apples. During the fermentation, the apples had similar changes in the pH and total-acid content regardless of the harvest time, but the increases in the alcohol content and yeast viable count with the decrease of the soluble-solid content were more rapid in the late-harvest apples than in the normal-harvest apples. After the completion of the fermentation, the soluble-solid and alcohol contents became very similar. The late-harvest cider showed a high total phenolic-compound content and a high DPPH radical scavenging effect, although these were slightly lower than those of the normal-harvest cider. It also showed a higher malic-acid content and higher hue color (p<0.05), Hunter's L, and b (p<0.05) values than the normal-harvest cider. In the sensory evaluation, the late-harvest cider obtained a higher score in taste and a lower score in color compared to the normal-harvest cider.

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.353-358
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• 2014

In order to obtain the basic data that could be used to evaluate the harvest time of new hardy kiwifruit cultivars (Actinidia arguta 'Saehan', 'Daesung' and 'Chilbo'), the seasonal fruit quality and ripening characteristics of hardy kiwifruit were investigated. Fruit sizes of 'Saehan', 'Daesung' and 'Chilbo' were increased from full bloom to 66 days, 85 days and 78 days, respectively. The growth curve of developing fruit of three cultivars showed double sigmoid. As a result of correlation analysis, the seed number per fruit showed a significant positive correlation with fruit weight (r = 0.94~0.97, p<0.01). Fruit length, width, thickness, weight, soluble solid content and titratable acidity were significantly different among the cultivars. Titratable acidity was increased from full bloom to harvest time and the titratable acidity of 'Saehan', 'Daesung' and 'Chilbo' were 1.77%, 1.22% and 1.37% on havest time, respectively. Optimal harvest time of 'Saehan' was 108 days (23 Sep.) after full bloom, those of 'Daesung' and 'Chilbo' were 92 (9 Sep.) days after full bloom.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.1
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• pp.70-74
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• 2008

To determine an optimum harvest time for chinese milk vetch (CMV) seed production, the seeds were harvested at 4 times, according to 25, 30, 35, and 40 day after flowering (DAF), in Miryang, southern part of Korea. CMV plants were manually harvested at each time and seed threshing was done by rice threshing machine. Seed yield, 1,000-seed weight, germinability, and hard coat ratio were investigated. Seed yield was the highest, 53.9 kg/300 kg by dry weight (DW) of CMV plant, at 35 DAF. 1,000-seed weight increased according to seed harvest time from 25 DAF to 40 DAF when it was 3.10 g. The germination ratios of seeds harvested at 4 times were not significantly different when the seeds stored until August 1. In case of long period of CMV seeds stored, the seeds harvested later showed higher germination rate. On the other hand, because the hard coat ratio causing germination inhibition was declined with an increase of storage period, it was higher in the seeds harvested later. There was no difference among the seeds harvested at 4 times at October 1. In conclusion, it was presumed that an optimum harvest time for CMV seed production should be at 35 DAF considering seed yield, weight and germinability.

• 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.