• Korean Journal of Organic Agriculture
• /
• v.23 no.1
• /
• pp.31-42
• /
• 2015

This thesis has analyzed the determination factor for the crop insurance of rice focused on paddy rice. The analysis on each farmer has been used with integrated probit model & random effects probit model. It has shown in the analysis result of determination factor for buying the crop insurance of paddy rice farmer through integrated probit model & random effects probit model that the higher age, degree of education, cultivated area, and amount of received insurance money and the lower in a number of family member have revealed the higher possibility to buy the crop insurance in the integrated probit model. While the random effects probit model has shown a higher possibility to buy the crop insurance as the higher age, cultivated area, and amount of received insurance money.

• Asian-Australasian Journal of Animal Sciences
• /
• v.20 no.1
• /
• pp.12-18
• /
• 2007

The objective of the study was to compare ranking of Sahiwal bulls selected on the basis of highest lactation milk yield of their dams with their estimated breeding values (EBVs) using an animal model. Data on 23,761 lactation milk yield records of 5,936 cows from five main Livestock Experiment Stations in Punjab province of Pakistan (1964-2004) were used for the study. At present the young A.I bulls are required to be from A-category bull-dams. Dams were categorized as A, B, C and D if they had highest lactation milk yield of ${\geq}$2,700, 2,250-2,699, 1,800-2,249 and <1,800 litres, respectively. The EBVs for lactation milk yield were estimated for all the animals using an individual animal model having fixed effect of herd-year and season of calving and random effect of animal. Fixed effect of parity and random effect of permanent environment were incorporated when multiple lactation were used. There were 396 young bulls used for semen collection and A.I during 1973-2004. However, progeny with lactation yields recorded, were available only for 91 bulls and dams could be traced for only 63 bulls. Overall lactation milk yield averaged 1,440.8 kg. Milk yield was 10% heritable with repeatability of 39%. Ranking bulls on highest lactation milk yield of their dams, the in-vogue criteria of selecting bulls, had a rank correlation of 0.167 (p<0.190) with ranking based on EBVs from animal model analysis. Bulls' EBVs for all lactations had rank correlation of 0.716 (p<0.001) with EBVs based on first lactation milk yield and 0.766 (p<0.001) with average EBVs of dam and sire (pedigree index). Ranking of bulls on highest lactation yield of their dams has no association with their ranking based on animal model evaluation. Young Sahiwal bulls should be selected on the basis of pedigree index instead of highest lactation yield of dams. This can help improve the genetic potential of the breed accruing to conservation and development efforts.

• Journal of Applied Biological Chemistry
• /
• v.43 no.1
• /
• pp.25-30
• /
• 2000

The main form of nitrogen fertilizer applied to lowland rice is urea, but little is known about its transport in waterlogged soil. This study was conducted to investigate the transport of urea in waterlogged soil column using WAVE (simulation of the substances Water and Agrochemicals in the soil, crop and Vadose Environment) model which includes the parameters for urea adsorption and hydrolysis, The adsorption distribution coefficient and hydrolysis rate of urea were measured by batch experiments. A transport experiment was carried out with the soil column which was pre-incubated for 45 days under flooded condition. The urea hydrolysis rate (k) was $0.073h^{-1}$. Only 5% of the applied urea remained in soil column at 4 days after urea application. The distribution coefficient ($K_d$) of urea calculated from adsorption isotherm was $0.21Lkg^{-1}$, so it was assumed that urea that urea was a weak-adsorbing material. The maximum concentration of urea was appeared at the convective water front because transport of mobile and weak-adsorbing chemicals, such as urea, is dependent on water convective flow. The urea moved down to 11 cm depth only for 2 days after application, so there is a possibility that unhydrolyzed urea could move out of the root zone and not be available for crops. A simulated urea concentration distribution in waterlogged soil column using WAVE model was slightly different from the measured concentration distribution. This difference resulted from the same hydrolysis rate applied to all soil depths and overestimated hydrodynamic dispersion coefficient. In spite of these limitations, the transport of urea in waterlogged soil column could be predict with WAVE model using urea hydrolysis rate (k) and distribution coefficient ($K_d$) which could be measured easily from a batch experiment.

• Korean Journal of Agricultural Science
• /
• v.49 no.1
• /
• pp.31-43
• /
• 2022

The global trade environment is rapidly changing. The spread of COVID-19 promotes digitalization, and online transactions are becoming the new normal. Currently, Korea is actively introducing information and communication technology (ICT) that uses the internet of things (IoT) in relation to agriculture. However, few studies have analyzed the impact of digitalization on trade in the agricultural sector. Thus, the purpose of this study is to examine how the introduction of digital technology can affect the economy and trade of Korea. In this study, we estimate the impact of introducing digital technologies using the computable general equilibrium (CGE) model. The results of this analysis indicate that the GDP could increase by 3.82% to 10.53%. Also, agricultural production and trade according to the model will significantly increase to 8.67% and 5.72%, respectively, through a productivity increase from Blockchain, IoT, and artificial intelligence (AI) technologies, despite logistics inefficiencies. Although the effects of digitalization could be significant, farmers are still struggling to introduce digital technologies, stemming from the fact that government support systems are concentrated in only a few sub-sectors. In this regard, support in this area must be expanded and diversified according to the current environment of agriculture in Korea.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.208-221
• /
• 2019

The inference for this research was concentrated on client's data protection in cloud computing i.e. data storages protection problems and how to limit unauthenticated access to info by developing access control model then accessible preparations were introduce after that an access control model was recommend. Cloud computing might refer as technology base on internet, having share, adaptable authority that might be utilized as organization by clients. Compositely cloud computing is software's and hardware's are conveying by internet as a service. It is a remarkable technology get well known because of minimal efforts, adaptability and versatility according to client's necessity. Regardless its prevalence large administration, propositions are reluctant to proceed onward cloud computing because of protection problems, particularly client's info protection. Management have communicated worries overs info protection as their classified and delicate info should be put away by specialist management at any areas all around. Several access models were accessible, yet those models do not satisfy the protection obligations as per services producers and cloud is always under assaults of hackers and data integrity, accessibility and protection were traded off. This research presented a model keep in aspect the requirement of services producers that upgrading the info protection in items of integrity, accessibility and security. The developed model helped the reluctant clients to effectively choosing to move on cloud while considerate the uncertainty related with cloud computing.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.64 no.1
• /
• pp.15-26
• /
• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• Asian-Australasian Journal of Animal Sciences
• /
• v.14 no.1
• /
• pp.1-6
• /
• 2001

Additive and dominance genetic variances were estimated for purebred Landrace selected with line breeding from 1989 to 1995 at Miyazaki Livestock Experiment Station, Kawaminami Branch. Ten body measurements, two reproductive traits and fifteen carcass traits were analyzed with single-trait mixed model analysis. The estimates of narrow-sense heritabilities by additive model were in the range of 0.07 to 0.46 for body measurements, 0.05 to 0.14 for reproductive traits, and 0.05 to 0.68 for carcass traits. The additive model tended to slightly overestimate the narrow-sense heritabilities as compared to the additive and dominance model. The proportion of the dominance variance to total genetic variance ranged from 0.11 to 0.91 for body measurements, 0.00 to 0.65 for reproductive traits, and 0.00 to 0.86 for carcass traits. Large differences among traits were found in the ratio of dominance to total genetic variance. These results suggested that dominance effect would affect the expression of all ten body measurements, one reproductive trait, and nine carcass traits. It is justified to consider the dominance effects in genetic evaluation of the selected lines for those traits.

• The Plant Pathology Journal
• /
• v.32 no.6
• /
• pp.537-544
• /
• 2016

We developed a model, termed D-PSA-K, to estimate the accumulated potential damage on kiwifruit canes caused by bacterial canker during the growing and overwintering seasons. The model consisted of three parts including estimation of the amount of necrotic lesion in a non-frozen environment, the rate of necrosis increase in a freezing environment during the overwintering season, and the amount of necrotic lesion on kiwifruit canes caused by bacterial canker during the overwintering and growing seasons. We evaluated the model's accuracy by comparing the observed maximum disease incidence on kiwifruit canes against the damage estimated using weather and disease data collected at Wando during 1994-1997 and at Seogwipo during 2014-2015. For the Hayward cultivar, D-PSA-K estimated the accumulated damage as approximately nine times the observed maximum disease incidence. For the Hort16A cultivar, the accumulated damage estimated by D-PSA-K was high when the observed disease incidence was high. D-PSA-K could assist kiwifruit growers in selecting optimal sites for kiwifruit cultivation and establishing improved production plans by predicting the loss in kiwifruit production due to bacterial canker, using past weather or future climate change data.

• Bulletin of the Korean Chemical Society
• /
• v.30 no.11
• /
• pp.2749-2753
• /
• 2009

Structural characteristics that influence on the insecticidal activity ($pI_{50}$) of 2-(n-octyl)isothiourea analogues (1-45) against the diamondback moth (Plutella xylostella, L.) based on three dimensional quantitative structure activity relationships (3D-QSARs) were discussed quantitatively using a comparative molecular field analysis (CoMFA) and a comparative molecular similarity indeces analysis (CoMSIA) methods. The statistical values of the CoMFA 2 model were better than those of the CoMSIA 1 model. The CoMFA 2 model was the optimized model with the correlativity (the training set: Ave. = 0.104 & PRESS = 0.613) and the predictability (the test set: Ave. = 0.086 & PRESS = 0.096). Insecticidal activities with the optimized CoMFA 2 model were dependent upon steric factors (79.4%) of $R_1-R_3$ substituents. From the analytical results of CoMFA contour maps, it is predicted that the R1 substituent of 1-45 which has a steric favor in a broad space, $R_2\;and\;R_3$ groups with a steric favor in a narrow space and a H-bond donor favor would have better the insecticidal activity.

• Journal of Biosystems Engineering
• /
• v.43 no.4
• /
• pp.352-361
• /
• 2018

Purpose: The objective of this study was to develop a multilayer perceptron (MLP) model to estimate solar radiation using a solar module. Methods: Data for the short-circuit current of a solar module and other environmental parameters were collected for a year. For MLP learning, 14,400 combinations of input variables, learning rates, activation functions, numbers of layers, and numbers of neurons were trained. The best MLP model employed the batch backpropagation algorithm with all input variables and two hidden layers. Results: The root-mean-squared error (RMSE) of each learning cycle and its average over three repetitions were calculated. The average RMSE of the best artificial neural network model was $48.13W{\cdot}m^{-2}$. This result was better than that obtained for the regression model, for which the RMSE was $66.67W{\cdot}m^{-2}$. Conclusions: It is possible to utilize a solar module as a power source and a sensor to measure solar radiation for an agricultural sensor node.