• Journal of Bio-Environment Control
• /
• v.29 no.4
• /
• pp.414-420
• /
• 2020

This study was carried out to investigate the growth characteristics of standard chrysanthemum 'Baekma', such as fresh weight, dry weight, and leaf area and to develop prediction models for the production greenhouse based on the growth parameters and climatic elements. Sigmoid regressions models for the prediction of growth parameters in terms of dry weight and leaf area were analyzed according to the number of the day after transplanting and the accumulate temperature during this experimental period. The relative growth rate (RGR) of the chrysanthemum was 0.084 g·g^-1·d^-1 on average during the period.The dry weight and leaf area of 'Beakma' increased exponentially according to the number of day after transplanting and the accumulated temperature, in the case of dry weight increased by an average of 39.1% until 63 days (accumulated temperature of 1601℃), after that dry weight increased by an average of 7.4% before harvest. The leaf area increased by an average of 63.3% until the 28th day after transplanting, and by an average of 6.5% until the 84th day before flower bud differentiation occurred, and increased by an average of 10.6% before harvest. This experiment can be used as a useful data for establishing a cultivation management system and a planned year-round production system for standard chrysanthemum "Baekma". To make a more precise growth prediction model, it will need to be corrected and verified based on various weather data including accumulated irradiation.

• Food Science of Animal Resources
• /
• v.30 no.3
• /
• pp.487-494
• /
• 2010

Cooked pork can be easily contaminated with Staphylococcus aureus during carriage and serving after cooking. This study was performed to develop growth prediction models of S. aureus to assure the safety of cooked pork. The Baranyi and Gompertz primary predictive models were compared. These growth models for S. aureus in cooked pork were developed at storage temperatures of 5, 15, and $25^{\circ}C$. The specific growth rate (SGR) and lag time (LT) values were calculated. The Baranyi model, which displayed a $R^2$ of 0.98 and root mean square error (RMSE) of 0.27, was more compatible than the Gompertz model, which displayed 0.84 in both $R^2$ and RMSE. The Baranyi model was used to develop a response surface secondary model to indicate changes of LT and SGR values according to storage temperature. The compatibility of the developed model was confirmed by calculating $R^2$, $B_f$, $A_f$, and RMSE values as statistic parameters. At 5, 15 and $25^{\circ}C$, $R^2$ was 0.88, 0.99 and 0.99; RMSE was 0.11, 0.24 and 0.10; $B_f$ was 1.12, 1.02 and 1.03; and $A_f$ was 1.17, 1.03 and 1.03, respectively. The developed predictive growth model is suitable to predict the growth of S. aureus in cooked pork, and so has potential in the microbial risk assessment as an input value or model.

• Journal of Food Hygiene and Safety
• /
• v.34 no.4
• /
• pp.374-379
• /
• 2019

This study developed predictive growth models of Salmonella enterica Serovar Typhimurium on lettuce washed with chlorine (100~300 ppm) and ultrasound (US, 37 kHz, 380 W) treatment and stored at different temperatures ($10{\sim}25^{\circ}C$) using a polynomial equation. The primary model of specific growth rate (SGR) and lag time (LT) showed a good fit ($R^2{\geq}0.92$) with a Gompertz equation. A secondary model was obtained using a quadratic polynomial equation. The appropriateness of the secondary SGR and LT model was verified by coefficient of determination ($R^2=0.98{\sim}0.99$ for internal validation, 0.97~0.98 for external validation), mean square error (MSE=-0.0071~0.0057 for internal validation, -0.0118~0.0176 for external validation), bias factor ($B_f=0.9918{\sim}1.0066$ for internal validation, 0.9865~1.0205 for external validation), and accuracy factor ($A_f=0.9935{\sim}1.0082$ for internal validation, 0.9799~1.0137 for external validation). The newly developed models for S. Typhimurium could be incorporated into a tertiary modeling program to predict the growth of S. Typhimurium as a function of combined chlorine and US during the storage. These new models may also be useful to predict potential S. Typhimurium growth on lettuce, which is important for food safety purposes during the overall supply chain of lettuce from farm to table. Finally, the models may offer reliable and useful information of growth kinetics for the quantification microbial risk assessment of S. Typhimurium on washed lettuce.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.401-401
• /
• 2020

최근 전 세계적으로 기후변화로 인한 자연재해가 빈번하게 발생하고 있으며, 우리나라 역시 해마다 가뭄과 홍수 등의 피해가 큰 실정이다. 특히 가뭄으로 인한 피해는 농업분야와 직결되어 있으며, 미래식량과 물안보에 영향을 미친다. 최근에는 국내 물관리일원화 정책에 따른 통합물관리 시행으로 수요관리에 의한 물이용 효율성이 물관리 기본원칙으로 포함되어 있어, 농업용수 분야의 물절약 필요성과 중요성은 더욱 증대되고 있는 실정이다. 농업농촌부문 가뭄대응 종합대책의 일환으로 2016년부터 농업용수 이용자 측면에서 물절약 실천을 유도하기 위한 물절약 교육 모델의 개발과 농업인 대상 시범교육이 실시되고 있으나 일부 지역에만 단발성 사업으로 제한적으로 추진되고 있는 실정이다. 따라서 물절약 교육 및 홍보사업을 보다 체계적이고 광법위하게 적용하여 농업 현장에서의 가시적인 물절약 성과를 도출하기 위한 노력이 요구된다. 이에 대한 일환으로 본 연구에서는 물절약 교육 콘텐트 개발 및 현장 교육에 반영하기 위하여 농업인 대상 물절약 의식과 행동실천 여부에 대해 조사를 실시해 보았다. 포항 및 영덕지역의 한국농어촌공사 관할지구 내 농업용수 이용자 중 수리시설감시원(이하 '수감원') 100여명을 대상으로 설문조사로 파악해 보았다. 설문에 참여한 수감원들은 대부분 65세 이상의 고령으로 농업에 오랜 기간 종사한 경험의 소유자로서 소규모 농업경영이 주를 이루었다. 대부분 농사기간동안 물부족 경험이 있었으며, 모내기 및 벼생육기 강우조건에 따라 물부족을 경험한 것으로 파악되었다. 이로 인해 설문 참여자들의 물절약 필요성에 대해서는 높은 공감대를 나타내었으며, 특히 농업인 대상 물절약 교육의 필요성에 대해서 매우 높은 공감대를 나타내었다. 농업인의 물과다 사용 및 물꼬관리 부실 등 필지단위 물관리 부실에 대해서도 상당히 인정하는 편이었으며, 이러한 농업인의 관행적인 물관리 행태에 대해서 변화를 유도할 수 있는 수리계조직 부활을 통한 농업인 물관리 직접 참여 등의 대안이 필요하다는 의견에 대해서도 긍정적이었다. 또한 농업인 용수이용에 대한 비용 부담에 대해서도 다소 긍정적인 의견도 제시되었다. 본 연구 결과로 농업인의 적극적인 물관리 및 물절약 참여를 이끌어 낼 수 있는 실현가능한 관련 제도 마련의 필요성과 체계적이고 지속적인 물절약 교육 및 홍보 정책 추진의 필요성이 제기된다.

• Journal of Mushroom
• /
• v.16 no.3
• /
• pp.155-161
• /
• 2018

In this study, we analyze the growth environment using smart farm technology in order to develop the optimal growth model for the precision cultivation of the bottle-grown oyster mushroom 'Suhan'. Experimental farmers used $88m^2$ of bed area, 2 rows and 5 columns of shelf shape, 5 hp refrigerator, 100T of sandwich panel for insulation, 2 ultrasonic humidifiers, 12 kW of heating, and 5,000 bottles for cultivation. Data on parameters such as temperature, humidity, carbon dioxide concentration, and illumination, which directly affect mushroom growth, were collected from the environmental sensor part installed at the oyster mushroom cultivator and analyzed. It was found that the initial temperature at the time of granulation was $22^{\circ}C$ after the scraping, and the mushroom was produced and maintained at about $25^{\circ}C$ until the bottle was flipped. On fruiting body formation, mushrooms were harvested while maintaining the temperature between $13^{\circ}C$ and $15^{\circ}C$. Humidity was approximately 100% throughout the growth stage. Carbon dioxide concentration gradually increased until 3 days after the beginning of cultivation, and then increased rapidly to approximately 2,600 ppm. From the 6th day, $CO_2$ concentration was gradually decreased through ventilation and maintained at 1,000 ppm during the harvest. Light was not provided at the initial stage of oyster mushroom cultivation. On the $3^{rd}$ and $4^{th}$ day, mushrooms were irradiated by 17 lux light. Subsequently, the light intensity was increased to 115-120 lux as the growth progressed. Fruiting body characteristics of 'Suhan' cultivated in a farmhouse were as follows: Pileus diameter was 30.9 mm and thickness was 4.5 mm; stipe thickness was 11.0 mm and length was 76.0 mm; stipe and pileus hardness was 0.8 g/mm and 2.8 g/mm, respectively; L values of the stipe and pileus were 79.9 and 52.3, respectively. The fruiting body yield was 160.2 g/850 ml, and the individual weight was 12.8 g/10 unit.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.374-390
• /
• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.51 no.2
• /
• pp.1-11
• /
• 2023

This study intended to develop a technique for quantitatively and 3-dimensionally predicting the potential failure zone and impulse that may occur when trees are fall down. The main outcomes of this study are as follows. First, this study established the potential failure zone and impulse calculation formula in order to quantitatively calculate the risks generated when trees are fallen down. When estimating the potential failure zone, the calculation was performed by magnifying the height of trees by 1.5 times, reflecting the likelihood of trees falling down and slipping. With regard to the slope of a tree, the range of 360° centered on the root collar was set in the case of trees that grow upright and the range of 180° from the inclined direction was set in the case of trees that grow inclined. The angular momentum was calculated by reflecting the rotational motion from the root collar when the trees fell down, and the impulse was calculated by converting it into the linear momentum. Second, the program to calculate a potential failure zone and impulse was developed using Rhino3D and Grasshopper. This study created the 3-dimensional models of the shapes for topography, buildings, and trees using the Rhino3D, thereby connecting them to Grasshopper to construct the spatial information. The algorithm was programmed using the calculation formula in the stage of risk calculation. This calculation considered the information on the trees' growth such as the height, inclination, and weight of trees and the surrounding environment including adjacent trees, damage targets, and analysis ranges. In the stage of risk inquiry, the calculation results were visualized into a three-dimensional model by summarizing them. For instance, the risk degrees were classified into various colors to efficiently determine the dangerous trees and dangerous areas.

• Korean Journal of Weed Science
• /
• v.30 no.4
• /
• pp.390-395
• /
• 2010

This study was conducted to predict reduction of soybean yield as affected by different densities of Cuscuta pentagona. All data were fitted to Cousens' rectangular hyperbola model to estimate parameters for predicting soybean yield loss. The yield of soybean in the various densities (1 to 48 plants $m^{-2}$) of C. pentagona reduced by 80.3 to 99.7%, respectively. Among yield components, number of pods was the most significantly influenced by weed interferences. The prediction model for soybean yield as affected by weed competition was as follows: Y= 274.6783/(1+4.3522X), $r^2$=0.999 in C. pentagona. Economic threshold levels calculated using cousens' equation was 0.004 plants $m^{-2}$ in C. pentagona.

• Journal of Food Hygiene and Safety
• /
• v.33 no.4
• /
• pp.248-254
• /
• 2018

To assess the risk of V. parahaemolyticus infection caused by consumption of raw oysters in Korea, contamination levels during the retail-to-table route of oysters was modeled to predict V. parahaemolyticus growth based on temperature and time. The consumed amount data of the KNHANES and the standard recipe of RDA were applied. A consumption scenario for exposure assessment was developed and combined with a Beta-Poisson dose-response model. The estimated probability of illness from consumption of pathogenic V. parahaemolyticus in raw oysters during three separate months (April, October, and November) was $5.71{\times}10^{-5}$ (within the 5th and 95th percentile ranges of $2.71{\times}10^{-8}$ to $1.03{\times}10^{-4}$). The results of the quantitative microbial-risk assessment indicated that the major factors affecting the probability of illness were the initial contamination level at the retailer, the consumed amount, the prevalence of pathogenic strains [tdh or trh genes], and exposure temperature and time.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.274-274
• /
• 2015

전 세계적으로 식량과 물 안보에 대한 중요도가 높아지고 있으며 이에 따라 물발자국은 식량과 물을 연계하는 요소로서 거론되고 있다. 물발자국은 제품이 생산되는 과정동안에 사용되는 물의 양을 의미하며 $m^3/ton$으로 표현한다. 이러한 물발자국은 작물 필요수량 및 생산량을 기반으로 산정되기 때문에 기후변화와 밀접한 관계가 있다. 따라서 농업 및 수자원 계획 분야에서 물발자국의 활용성을 높이기 위해서는 기후변화에 따른 우리나라 농산물의 물발자국 변화를 살펴보는 것이 필요하다. 이에 따라 본 연구에서는 기후변화에 따른 논벼의 농업용수량 및 생산량 산정을 통하여 미래의 녹색 및 청색 물발자국을 산정하고, 시기 및 시나리오별 불확실성 및 민감도를 평가하고자 하였다. 기후변화 시나리오는 RCP 기반의 신 기후변화 시나리오를 이용하였으며, 물발자국 산정 작물은 우리나라의 주곡인 논벼를 대상으로 하였다. 물발자국은 작물의 단위생산량당 소비되는 물의 양으로 정의되며, 최근 연구에서 물발자국은 용수 공급원에 따라 녹색(green), 청색(blue), 회색(grey) 물발자국으로 구분하여 산정되고 있다. 본 연구에서는 작물의 증발산으로 소비되는 수량만을 물발자국 산정에 적용하여 증발산량 중 강우에 의해 공급되는 수량인 녹색 물발자국과 관개에 의해 인위적으로 공급되는 수량인 청색물발자국을 산정하였다. 기후변화에 따른 미래의 작물의 생산량을 산정하기 위해 작물모델로 기상, 재배관리, 작물의 유전정보, 토양수분 및 질소의 효과까지 고려하여 작물의 생육뿐만 아니라 생산량까지도 모의할 수 있는 CERES-Rice모델을 적용하였다. 미래 기후 전망을 위한 전지구모형은 종류가 다양하고 모형의 특성과 모형 입력 자료에 따라 모의 결과가 상이하게 나타남에 따라 불확실성을 내포하고 있다. 따라서 기후변화에 능동적으로 대처할 수 있는 논벼의 물발자국을 산정하기 위하여 각 시나리오 및 시기별 물발자국의 불확실성 및 민감도를 분석하였다. 본 연구의 결과는 기후변화에 따른 미래 농업수자원의 변화를 분석하는데 이용될 수 있을 뿐 만아니라 우리나라 미래 국가수자원 정책의 수립을 위한 기초자료로 활용될 것으로 기대된다.