• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.96-108
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• 2011

Several methods of in-field measurements of Nitrogen and other soil properties using cores extracted by a hydraulic soil sampler were evaluated. A prototype core scanner was built to accommodate Veris Technologies commercial Vis-NIRS equipment. The testing result for pH, P and Mg were close to RPD (Ratio of Prediction to Deviation = Standard deviation/RMSE) of 2, however the scanner could not achieve the goal of RPD of 2 on some other properties, especially on nitrate nitrogen ($NO_3$) and potassium (K). In situ NIRS/EC probe showed similar results to the core scanner; pH, P and Mg were close to RPD of 2, while $NO_3$ and K were RPD of 1.5 and 1.2, respectively. Correlations between estimations using the probe and the core scanner were strong, with $r^2$ > 0.7 for P, Mg, Total N, Total C and CEC. Preliminary results for mid-IR spectroscopy showed an $r^2$ of 0.068 and an RMSE for nitrate (N) of 18 ppm, even after the removal of calcareous samples and possible N outlier. After removal of calcareous samples on a larger sample set, results improved considerably with an $r^2$ of 0.64 and RMSE of 6 ppm. However, this was only possible after carbonate samples were detected and eliminated, which would not be feasible under in-field measurements. Testing of $NO_3$ and K ion-selective electrodes (ISEs) revealed promising results, with acceptable errors measuring soil solutions containing nitrate and potassium levels that are typical of production agriculture fields.

• Food Science of Animal Resources
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• v.33 no.2
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• pp.198-204
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• 2013

This study aimed to apply the Parallux system to detect (fluoro)quinone antibiotics residues in raw bovine milk. The immunogen enabled the generation of a specific antiserum with a titer of 1/40,000. The $Parallax^{TM}$ kit using the antibody displayed $IC_{50}$ value of 10 to 150 ppb for (fluoro)quinolone antibiotics. $Parallax^{TM}$ kit was also sensitive for the detection of incurred (fluoro)quinolone at Korean Maximum Residual Levels in raw bovine milk as the result of dose response test. Cross reactivities of the antibody with the common (fluoro)quinolones were determined to be norfloxacin, 100%; enrofloxacin, 100%; ciprofloxacin, 100%; danofloxacin, 100%; nalidixic acid, 40%. Lower detection limit (LOD) values of the $Parallax^{TM}$ kit in raw bovine milk were determined to be norfloxacin, 4 ppb; enrofloxacin, 5 ppb; danofloxacin, 5 ppb; ciprofloxacin, 5 ppb and nalidixic acid, 10 ppb. The $Parallax^{TM}$ kit was run 8 times with five different concentrations of norfloxacin to determine the coefficient of variation (CV, %) of intra-assay, which was between 2.7% and 11.8%. To confirm the precision among kit batches for the inter-assay, five different batch kits were tested with 2 different concentration of norfloxacin. The CVs of the inter assay were 4.2% at 50 ppb, and 7.2% at 10 ppb norfloxacin, respectively.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.165-173
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• 2020

The emergence of unmanned agricultural machinery has brought new research content to the development of precision agriculture. In order to speed up the research on key technologies of unmanned agricultural machinery, classification of intelligence level of unmanned agricultural machinery has become a primary task. In this study, the researchers take the complex interactive system consisting of unmanned grain harvester, task and driving environment as the research object, and carry out a research on the grading and classification of intelligent level of unmanned grain harvester. The researchers of this study also establish an evaluation model of unmanned grain harvester vehicle, which consists of human intervention degree, environmental complexity, and task complexity. Besides, the grading and classification of intelligence level of the unmanned grain harvester is carried out according to the human intervention degree, environmental complexity and the task complexity of the unmanned grain harvester. It provides a direction for the future development of unmanned agricultural machinery.

• Korean Journal of Environmental Agriculture
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• v.40 no.2
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• pp.142-147
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• 2021

BACKGROUND: Agricultural use and pest control purposes of pesticides may lead to livestock products contamination. Thiodicarb and its degraded product, methomyl, are carbamate insecticides that protect soya bean, maize, fruit, and vegetables and control flies in animal and poultry farms. For maximum residue limit enforcement and monitoring, the JMPR residue definition of thiodicarb in animal products is the sum of thiodicarb and methomyl, expressed as methomyl. This residue definition was set to consider the fact that thiodicarb was readily degraded to methomyl in animal commodities. And therefore the simultaneous analytical method of thiodicarb and methomyl is required for monitoring in livestock products. METHODS AND RESULTS: The study was conducted using a quick, easy, cheap, effective, rugged, and safe (QuEChERS) method and HPLC-MS/MS to determine the thiodicarb and methomyl in livestock products. The limit of quantitation (LOQ) was 0.01 mg/kg for livestock products, including beef, pork, chicken, milk, and egg. The coefficient of determinations (r²) for the calibration curve were > 0.99, which was acceptable values for linearity. Average recoveries at spiked levels (LOQ, 10LOQ, and 50LOQ, n=5) in triplicate ranged from 73.2% to 102.1% and relative standard deviations (RSDs) were less than 10% in all matrices. CONCLUSION: The analytical method was validated for the performance parameters (specificity, linearity, accuracy, and precision) in livestock products to be acceptable by the CODEX guidelines.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.273-284
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• 2018

Purpose: Conventional headland turning typically requires repeated forward and backward movements to move the farming equipment to the next row. This research focuses on developing an upland agricultural robot with an optimized headland turning mechanism that enables a $180^{\circ}$ turning positioning to the next row in one steering motion designed for a two-wheel steering, four-wheel drive agricultural robot named the HADA-bot. The proposed steering mechanism allows for faster turnings at each headland compared to those of the conventional steering system. Methods: The HADA-bot was designed with 1.7-m wide wheel tracks to travel along the furrows of a garlic bed, and a look-ahead path following algorithm was applied using a real-time kinematic global positioning system signal. Pivot turning tests focused primarily on accuracy regarding the turning radius for the next path matching, saving headland turning time, area, and effort. Results: Several test cases were performed by evaluating right and left turns on two different surfaces: concrete and soil, at three speeds: 1, 2, and 3 km/h. From the left and right side pivot turning results, the percentage of lateral deviation is within the acceptable range of 10% even on the soil surface. This U-turn scheme reduces 67% and 54% of the headland turning time, and 36% and 32% of the required headland area compared to a 50 hp tractor (ISEKI, TA5240, Ehime, Japan) and a riding-type cultivator (CFM-1200, Asia Technology, Deagu, Rep. Korea), respectively. Conclusion: The pivot turning trajectory on both soil and concrete surfaces achieved similar results within the typical operating speed range. Overall, these results prove that the pivot turning mechanism is suitable for improving conventional headland turning by reducing both turning radius and turning time.

• Korean Journal of Environmental Agriculture
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• v.38 no.1
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• pp.1-9
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• 2019

BACKGROUND: Accurate and simple analytical method determining Fluxametamid residue was necessary in various food matrices. Additionally, fulfilment of the international guideline of Codex (Codex Alimentarius Commission CAC/GL 40) was required for the analytical method. In this study, we developed Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) method to determine the Fluxametamid residue in foods. METHODS AND RESULTS: Fluxametamid was extracted with acetonitrile, partitioned and concentrated with dichloromethane. To remove the interferences, silica SPE cartridge was used before LC-MS/MS (Liquid Chromatography-Tandem Mass Spectrometry) analysis with $C_{18}$ column. Five agricultural commodities (mandarin, potato, soybean, hulled rice, and red pepper) were used as a group representative to verify the method. The liner matrix-matched calibration curves were confirmed with coefficient of determination ($r^2$) greater than 0.99 at calibration range of 0.001-0.25 mg/kg. The limits of detection and quantification were 0.001 and 0.005 mg/kg, respectively. Mean average accuracies were shown to be 82.24-115.27%. The precision was also shown to be less than 10% for all five samples. CONCLUSION: The method investigated in this study was suitable to the Codex guideline for the residue analysis. Thus, this method can be useful for determining the residue in various food matrices as routine analysis.

• Korean Journal of Environmental Agriculture
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• v.40 no.3
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• pp.186-193
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• 2021

BACKGROUND: Before generating transgenic plant using the CRISPR-Cas9 system, the efficiency test of sgRNAs is recommended to reduce the time and effort for plant transformation and regeneration process. The efficiency of the sgRNA can be measured through the transient expression of sgRNA and Cas9 gene in tomato cotyledon; however, we found that the calculated efficiency showed a large variation. It is necessary to increase the precision of the experiment to obtain reliable sgRNA efficiency data from transient expression. METHODS AND RESULTS: The cotyledon of 11^th, 15^th, 19^th, and 23^rd-day-old tomato (Solanum lycopersicum cv. Micro-Tom) were used for expressing CRISPR-Cas9 transiently. The agrobacterium harboring sgRNA for targeting ALS2 gene of tomato was injected through the stomata of leaf adaxial side and the genomic DNA was extracted in 5 days after injection. The target gene edition was identified by amplifying DNA fragment of target region and analyzing with Illumina sequencing method. The target gene editing efficiency was calculated by counting base deletion and insertion events from total target sequence read. CONCLUSION: The CRISPR-Cas9 editing efficiency varied with tomato cotyledon age. The highest efficiency was observed at the 19-day-old cotyledons. Both the median and mean were the highest at this stage and the sample variability was also minimized. We found that the transgene of CRISPR-Cas9 system was strongly correlated with plant leaf development and suggested the optimum cotyledon leaf age for Agrobacterium-mediated transfection in tomato.

• Korean Journal of Environmental Agriculture
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• v.39 no.4
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• pp.368-374
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• 2020

BACKGROUND: The residual analysis of polar pesticides has remained a challenge. It is even more difficult to simultaneously analyze multiple polar pesticides. Diquat, paraquat, and chlormequat are typical examples of highly polar pesticides. The existing methods for the analysis of diquat, paraquat and chlormequat are complex and time consuming. Therefore, a simple, quick and effective method was developed in the represent study for simultaneous analysis of diquat, paraquat and chlormequat in animal products, meat and fat using UPLC-MS/MS. METHODS AND RESULTS: Sample extraction was carried out using acidified acetonitrile and water and re- extracted with acidified acetonitrile and combine the extracts followed by centrifugation. The extract was then cleaned up with a HLB cartridge after reconstitution with acidic acetonitrile and water. The method was validated in quintuplicate at three different concentrations. The limits of detection (LOD) and quantification (LOQ) were 0.0015 and 0.005 mg/L, respectively. Matrix suppression effect was observed for all of the analytes. A seven point matrix matched calibration curve was constructed for each of the compound resulted excellent linearity with determination coefficients (R2) ≥ 0.991. Accuracy and precision of the method was calculated from the recovery and repeatability and ranged from 62.4 to 119.7% with relative standard deviation less than 18.8%. CONCLUSION: The recovery and repeatability of the developed method were in the acceptable range according to the Codex Alimentarius guideline. The developed method can be applied for the routine monitoring of diquat, paraquat, and chlormequat in animal products, meat and fat.

• Journal of Practical Agriculture & Fisheries Research
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• v.10 no.1
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• pp.29-41
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• 2008

This research was conducted to develop a technology transfer and farmer's extension of newly released technology of Bokto seeding method for crop and vegetable production based on the theory of Asian and Pacific Center for Transfer of Technology(APCTT). This technology has recently transferred to not only Korea but also other countries like North Korea, China, Japan, Taiwan, Russia and Africa(Cameroon, Sudan and South Africa) since 2005. It has known as a highly reduction of production cost in terms of labors, chemical fertilizer and pesticides as well as environmental friendly due to a deep and side banded placement of chemical fertilizer at basal application. In addition this technology was proven to a precision farming on sowing depth and mechanism of chemical application method and also highly resistant against disasters like typhoon, flooding, low temperature, drought and lodging due to silicate application. It has improved a constraints such as a poor seedling establishment, weed occurrence, lodging, low yield and poor grain and eating quality in the previous direct seeding methods but still have a problem in occurrence of weedy rice and ununiformed operation of wet or flooded soil condition. Also this technology has a limit in marketing and A/S system. Based on a theory of APCTT evaluation and analysis this technology may be more concentrated on establishment of a special cooperation team among researcher and scientists, extension workers, industry sections and governmental sectors in order to rapidly transfer this technology to farmer's field. Also there will be needed to operate a web site for this newly released technology to inform and exchange an idea, experiences and newly improved information. A feed back system might be operated in this technology as well to improve a technology under way on users' operation. Also user's manual will be internationally released and provided for farmer's instruction and training at field site.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.