• Agribusiness and Information Management
• /
• v.12 no.1
• /
• pp.36-49
• /
• 2020

This study pertains to direction of exports direction of major agricultural commodities viz., rice, maize, bengal gram, chillies and cotton from India. In the ensuing next decade during 21st century, India is likely to witness changes in the export pattern of these commodities due to both internal and external constraints. One of the major internal constraints is mounting cost of production. Similarly, one of the most important external constraints include excessive subsidization by importing countries that makes Indian commodities less competitive in the international market. So, the important research question is to analyse the direction of exports of major agricultural commodities from India during post-WTO regime. The dynamic nature of trade pattern of the selected commodities was analyzed by employing the first order Markov process by examining gains and losses in respect of export shares of major Indian agricultural commodities to different countries. During the post-WTO regime, it was found that Saudi Arabia for rice, Bangladesh for maize, Pakistan for bengal gram, Malaysia for (dry) chillies, China, mainland for cotton are the loyal destinations for the commodities. The increasing demand for the selected commodities in countries like Saudi Arabia, Côte d'Ivoire for rice; Malaysia for maize; Pakistan and Algeria for Bengal gram; USA and Sri Lanka for (dry) chillies and Vietnam, Pakistan and Indonesia for cotton need to be explored for augmenting the exports. In order to achieve this goal, it is essential that consumer preferences in newer markets, market intelligence and impediments for augmenting exports need to be researched. It is also high time to analyze the export competitiveness of selected commodities across these importing countries.

• Toxicological Research
• /
• v.30 no.4
• /
• pp.251-260
• /
• 2014

The number of farmers who have suffered from non-fatal acute pesticide poisoning has been reported to vary from 5.7% to 86.7% in South Korea since 1975. Absorption through the skin is the main route of exposure to pesticides for farmers who operate with them. Several in vitro tests using the skins of humans or animal and in vivo tests using laboratory animals are introduced for the assessment of human dermal absorption level of pesticides. The objective of this study is to evaluate and compare international guidelines and strategies of dermal absorption assessments and to propose unique approaches for applications into pesticide registration process in our situation. Until present in our situation, pesticide exposure level to operator is determined just using default value of 10 as for skin absorption ratio because of data shortage. Dermal absorption tests are requested to get exposure level of pesticides and to ultimately know the safety of pesticides for operators through the comparison with the value of AOEL. When the exposure level is higher than AOEL, the pesticide cannot be approved. We reviewed the skin absorption test guidelines recommended by OECD, EFSA and EPA. The EPA recommends assessment of skin absorption of pesticides for humans through the TPA which includes all the results of in vitro human and animal and animal in vivo skin absorption studies. OECD and EFSA, employ a tiered approach, which the requirement of further study depends on the results of the former stage study. OECD guidelines accept the analysis of pesticide level absorbed through skin without radioisotope when the recovery using the non-labeled method is within 80~120%. Various factors are reviewed in this study, including the origin of skin (gender, animal species and sites of skin), thickness, temperature and, etc., which can influence the integrity of results.

• Journal of Microbiology and Biotechnology
• /
• v.20 no.5
• /
• pp.893-903
• /
• 2010

A cellulolytic and xylanolytic enzyme complex-producing alkalothermoanaerobacterium strain, Tepidimicrobium xylanilyticum BT14, is described. The cell was Grampositive, rod-shaped, and endospore-forming. Based on 16S rRNA gene analysis and various lines of biochemical and physiological properties, the strain BT14 is a new member of the genus Tepidimicrobium. The strain BT14 cells had the ability to bind to Avicel, xylan, and corn hull. The pH and temperature optima for growth were 9.0 and $60^{\circ}C$, respectively. The strain BT14 was able to use a variety of carbon sources. When the bacterium was grown on corn hulls under an anaerobic condition, a cellulolytic and xylanolytic enzyme complex was produced. Crude enzyme containing cellulase and xylanase of the strain BT14 was active in broad ranges of pH and temperature. The optimum conditions for cellulase and xylanase activities were pH 8.0 and 9.0 at $60^{\circ}C$, respectively. The crude enzyme had the ability to bind to Avicel and xylan. The analysis of native-PAGE and native-zymograms indicated the cellulosebinding protein showing both cellulase and xylanase activities, whereas SDS-PAGE zymograms showed 4 bands of cellulases and 5 bands of xylanases. Evidence of a cohesinlike amino acid sequence seemed to indicate that the protein complex shared a direct relationship with the cellulosome of Clostridium thermocellum. The crude enzyme from the strain BT14 showed effective degradation of plant biomass. When grown on corn hulls at pH 9.0 and $60^{\circ}C$ under anaerobic conditions, the strain BT14 produced ethanol and acetate as the main fermentation products.

• International journal of advanced smart convergence
• /
• v.12 no.3
• /
• pp.104-108
• /
• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Journal of Environmental Science International
• /
• v.17 no.9
• /
• pp.1039-1052
• /
• 2008

The SWAT model developed by the USDA-Agricultural Research service for the prediction of rainfall run-off, sediment, and chemical yields in a basin was applied to Jeju Island watershed to estimate the amount of runoff. The research outcomes revealed that the estimated amount of runoff for the long term on 2 water-sheds showed fairly good performance by the long-term daily runoff simulation. The watershed of Chunmi river located the eastern region in Jeju Island, after calibrations of direct runoff data of 2 surveys, showed the similar values to the existing watershed average runoff rate as 22% of average direct runoff rate for the applied period. The watershed of Oaedo river located the northern region showed $R^2$ of 0.93, RMSE of 14.92 and ME of 0.70 as the result of calibrations by runoff data in the occurrence of 7 rainfalls.

• Korean Journal of Environmental Agriculture
• /
• v.31 no.1
• /
• pp.9-15
• /
• 2012

BACKGROUND: A preliminary investigation of the radon ($^{222}Rn$) concentration has been conducted, employing solid-state nuclear-track detectors (SSNTD) and a continuous radon monitor (CRM), for fourteen randomly selected agricultural greenhouses in Jeju Island, where the underground-air was used for air conditioning and $CO_2$ supplement. METHODS AND RESULTS: The SSNTD was used to measure the average radon concentration for three months and the CRM was used for an instantaneous measurement. In order to obtain the radon concentration of a greenhouse, the SSNTDs were placed at a number of evenly distributed points inside the greenhouse and the mean of the measured values was taken. In addition, in order to assess the radon concentration of the underground-air itself, measurement was also made at the borehole of the underground-air in each agricultural facility, employing both the SSNTD and CRM. It is found that the radon concentration of the greenhouses ranges higher than those not using the underground-air and the average of Korean dwellings. While the radon concentration of most agricultural facilities is still lower than the reference level (1,000 Bq/$m^3$) recommended by the International Radiation Protection Committee (ICRP), three facilities at one site show higher concentrations than the reference level. The three-month-averaged radon concentration and the instantaneous radon concentration of the underground-air itself ranges 1,228- 5,259 and 3,322-17,900 Bq/$m^3$, respectively, and regional variation is more significant. CONCLUSION: From this results, radon concentration of the underground-air is assumed that it is associated with the geological characteristics and the boring depth of the region located of their.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.59 no.4
• /
• pp.65-74
• /
• 2017

North Korea is one of the high vulnerable countries facing the threat of natural disaster and has experienced more frequent disasters in recent years. These disasters have significantly led to food shortages and large reductions in crop yields. In 2015, both North Korean officials and international agencies had identified the extreme drought event, the worst in one hundred years according to the North Korean government. The objective of this study was an assessment of the extreme drought events in 2014~2015, and to apply climatic drought indices for drought monitoring in North Korea. Characteristics of the extreme drought in North Korea are examined by using the weekly-based Standardized Precipitation Evapotranspiration Index (SPEI). The drought characteristics illustrated by the SPEI results are compared with a Standardized Precipitation Index (SPI) results and drought impact information to understand how these indices can explain the drought conditions within the country. These results demonstrated that the SPEI could be an effective tool to provide improved spatial and temporal drought conditions to inform management decisions for drought policy.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.63 no.1
• /
• pp.11-25
• /
• 2021

The objective of this study was to analyze the impact of activation functions on flood forecasting model based on Artificial neural networks (ANNs). The traditional activation functions, the sigmoid and tanh functions, were compared with the functions which have been recently recommended for deep neural networks; the ReLU, leaky ReLU, and ELU functions. The flood forecasting model based on ANNs was designed to predict real-time runoff for 1 to 6-h lead time using the rainfall and runoff data of the past nine hours. The statistical measures such as R2, Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE), the error of peak time (ETp), and the error of peak discharge (EQp) were used to evaluate the model accuracy. The tanh and ELU functions were most accurate with R2=0.97 and RMSE=30.1 (㎥/s) for 1-h lead time and R2=0.56 and RMSE=124.6~124.8 (㎥/s) for 6-h lead time. We also evaluated the learning speed by using the number of epochs that minimizes errors. The sigmoid function had the slowest learning speed due to the 'vanishing gradient problem' and the limited direction of weight update. The learning speed of the ELU function was 1.2 times faster than the tanh function. As a result, the ELU function most effectively improved the accuracy and speed of the ANNs model, so it was determined to be the best activation function for ANNs-based flood forecasting.

• Korean Journal of Soil Science and Fertilizer
• /
• v.47 no.6
• /
• pp.510-517
• /
• 2014

The purpose of this study was to analyze microbial hazards for cultivation environments and personal hygiene of strawberry and tomato farms at the growth and harvesting stage. Samples were collected from thirty strawberry farms and forty tomato farms located in Korea and tested for Staphylococcus aureus and Bacillus cereus. To investigate the change in the distribution of the S. aureus and B. cereus, a total of 4,284 samples including air born, soil or medium, mulching film, harvest basket, groves and irrigation water etc. were collected from eight strawberry farms and nine tomato farms for one year. As a result, total S. aureus and B. cereus in all samples were detected. Among the total bacteria of strawberry farms, S. aureus (glove: $0{\sim}2.1Log\;CFU/100cm^2$, harvest basket: $0{\sim}3.0Log\;CFU/100cm^2$, soil or culture media: 0~4.1 Log CFU/g, mulching film: $0{\sim}3.8Log\;CFU/100cm^2$), B. cereus (glove: $0{\sim}2.8Log\;CFU/100cm^2$, harvest basket: $0{\sim}4.8Log\;CFU/100cm^2$, soil or culture media: 0~5.3 Log CFU/g, mulching film: $0{\sim}4.5Log\;CFU/100cm^2$) were detected in all samples. The total bacteria of tomato farms, S. aureus (glove: $0{\sim}4.0Log\;CFU/100cm^2$, harvest basket: $0{\sim}5.0Log\;CFU/100cm^2$, soil or culture media: 0~6.1 Log CFU/g, mulching film: $0{\sim}4.0Log\;CFU/100cm^2$), B. cereus (glove: $0{\sim}4.0Log\;CFU/100cm^2$, harvest basket: $0{\sim}4.3Log\;CFU/100cm^2$, soil or culture media: 0~5.9 Log CFU/g, mulching film: $0{\sim}4.7Log\;CFU/100cm^2$) were detected in all samples. The contamination of S. aureus and B. cereus were detected in soil, mulching film and harvest basket from planting until harvest to processing, with the highest count recorded from the soil. But S. aureus and B. cereus were not detected in irrigation water samples. The incidence of S. aureus and B. cereus in hydroponics culture farm were less than those in soil culture. The amount of S. aureus and B. cereus detected in strawberry and tomato farms were less than the minimum amount required to produce a toxin that induces food poisoning. In this way, the degree of contamination of food poisoning bacteria was lower in the production environment of the Korea strawberry and tomato, but problems can be caused by post-harvest management method. These results will be used as fundamental data to create a manual for sanitary agricultural environment management, and post-harvest management should be performed to reduce the contamination of hazardous microorganisms.

• Asian-Australasian Journal of Animal Sciences
• /
• v.33 no.5
• /
• pp.732-741
• /
• 2020

Objective: The study was conducted to investigate the effects of Broussonetia papyrifera L. (B. papyrifera) silage on growth performance, serum biochemical parameters, meat quality, and meat amino acids and fatty acids compositions in beef cattle. Methods: Sixty-four male Angus beef cattle were assigned to 4 groups with 4 pens in each group and 4 beef cattle in each pen, and fed with the total mixed ration supplemented with 0%, 5%, 10%, or 15% B. papyrifera silage for 100 days (control group, 5% group, 10% group and 15% group) separately. Results: Beef cattle had significantly higher final body weight (BW) in 15% group, higher average daily gain (ADG) and dry matter intake (DMI) in 5% group, 10% group and 15% group, and higher feed conversion ratio (FCR) in 10% group and 15% group. Significantly higher blood superoxide dismutase (SOD) concentration was noted in 15% group, higher blood total antioxidant capacity (TAC) in 10% group and 15% group, lower 8-hydroxydeoxyguanosine (8-OHdG) and malondialdehyde (MDA) in 15% group. Meat had lower pH in 15% group, higher Commission International DeI'Eclairage (CIE) L^⋆ in 5% group, 10% group, and 15% group, and lower drip loss in 15% group. Greater concentration of meat polyunsaturated fatty acids (PUFA) was observed in 10% group and 15% group, and docosahexaenoic acid (DHA) in 15% group. Conclusion: Diet with 15% B. papyrifera silage could improve performance and increase final BW, ADG, DMI, and FCR, enhance the antioxidant functions by decreasing blood 8-OHdG and MDA and increasing blood SOD and TAC, improve the meat quality by lowing pH and drip loss and increasing CIE L^⋆, increase the meat PUFA and DHA concentration. Polyphenols and flavonoids might be the main components responsible for the antioxidant activity and anti-biohydrogenation in the B. papyrifera silage. And B. papyrifera silage could be used as a new feedstuff in beef cattle nutrition.