• 농업과학연구
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• 제50권3호
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• pp.527-538
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• 2023

In this study, we aimed to apply multispectral imaging (713 - 920 nm, 10 bands) for maturity classification and recognition of oriental melons grown in hydroponic greenhouses. A total of 20 oriental melons were selected, and time series multispectral imaging of oriental melons was 7 - 9 times for each sample from April 21, 2023, to May 12, 2023. We used several approaches, such as Savitzky-Golay (SG), standard normal variate (SNV), and Combination of SG and SNV (SG + SNV), for pre-processing the multispectral data. As a result, 713 - 759 nm bands were preprocessed with SG for the maturity classification of oriental melons. Additionally, a Light Gradient Boosting Machine (LightGBM) was used to train the recognition model for oriental melon. R² of recognition model were 0.92, 0.91 for the training and validation sets, respectively, and the F-scores were 96.6 and 79.4% for the training and testing sets, respectively. Therefore, multispectral imaging in the range of 713 - 920 nm can be used to classify oriental melons maturity and recognize their fruits.

• 농업과학연구
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• 제46권2호
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• pp.381-393
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• 2019

A smart farm is a system that combines information and communication technology (ICT), internet of things (IoT), and agricultural technology that enable a farm to operate with minimal labor and to automatically control of a greenhouse environment. Machine learning based on recently data-driven techniques has emerged with big data technologies and high-performance computing to create opportunities to quantify data intensive processes in agricultural operational environments. This paper presents research on the application of machine learning technology to diagnose the growth status of crops and predicting the harvest time of strawberries in a greenhouse according to image processing techniques. To classify the growth stages of the strawberries, we used object inference and detection with machine learning model based on deep learning neural networks and TensorFlow. The classification accuracy was compared based on the training data volume and training epoch. As a result, it was able to classify with an accuracy of over 90% with 200 training images and 8,000 training steps. The detection and classification of the strawberry maturities could be identified with an accuracy of over 90% at the mature and over mature stages of the strawberries. Concurrently, the experimental results are promising, and they show that this approach can be applied to develop a machine learning model for predicting the strawberry harvesting time and can be used to provide key decision support information to both farmers and policy makers about optimal harvest times and harvest planning.

• 농촌지도와개발
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• 제16권4호
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• pp.939-965
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• 2009

The Machine Learning has been identified as a promising approach to knowledge-based system development. This study aims to examine the ability of machine learning techniques for farmer's decision making and to develop the reference model for using pig farm data. We compared five machine learning techniques: logistic regression, decision tree, artificial neural network, k-nearest neighbor, and ensemble. All models are well performed to predict the sow's productivity in all parity, showing over 87.6% predictability. The model predictability of total litter size are highest at 91.3% in third parity and decreasing as parity increases. The ensemble is well performed to predict the sow's productivity. The neural network and logistic regression is excellent classifier for all parity. The decision tree and the k-nearest neighbor was not good classifier for all parity. Performance of models varies over models used, showing up to 104% difference in lift values. Artificial Neural network and ensemble models have resulted in highest lift values implying best performance among models.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.648-655
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• 1993

The hydraulic coconut dehusking machine consists of three main parts ie. The frame , the power unit including the hydraulic accessories, the lifting and dehusking mechanisms. Two sets of the hydraulic coconut dehusking machine were developed . their hydraulic and electrical control circuits were connected in series to enable them operating contemporaneously. Two operators are required to operate the machine. Each of them put a coconut on the lifting mechanism in order to start the working cycle automatically. As a result, the nut are immediately pushed up and seized by the holding teeth under the supplement of the hydraulic reducing circuit. After that the dehusking mechanism started operating via the sequence circuit. At the end of the cycle, both mechanisms return to their original positions. Some remaining fibrous is taken out manually from the nut subsequently . The continuous dehusking speed was found to be 22.2 seconds per 2 coconuts.

• Journal of Biosystems Engineering
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• 제22권2호
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• pp.163-176
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• 1997

Sesame was one of the economical crops in Korea. However, cultivation area of sesame has been decreasing rapidly due to the lack of mechanization for this crop and the opening of agricultural product market. Sesame seed is so small that ordinary seeder can not seed properly. In rural practice, farmers seed sesame with hand and do thinning after shoot emerges. Seeding and thinning in sesame cultivation take more than 40% of total labor To reduce labor in seeding and thinning, a pellet seed machine for sesame has been developed. The pellet seed machine is very simple in structure. It utilizes the chemical reaction between alginate solution and $CaCl_2$. Two material forms a membrane when they meet The uniqueness of the pellet seed machine for sesame were 1) a counter rotating roller for metering the mixture of activated carbon and alginate and 2) swinging plate for submerging seed into the mixture. The prototype machine can produce 30, 000 pellets per hour and costs ￦6, 891 per 1 km sesame.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.1041-1044
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• 1996

The plastic-film-covered hill planter is a new-type seeding machine, including tow types which are mounted by 11kw and 40 kw tractors. It is made up of fertilizing , plastic-film covering perforating film and hole seeding, soil sealing apparatus, and can work at 5-7kw/h. The plastic-film covering and seeding of cotton, corn and soybean can all use this machine. The plastic-film-covered hill planter is mainly composed of plastic film covering unit, drum-type hill-drop unit and furrow coverer, some other types are also equipped with fertilizer drill unit. It can do combined work of covering plastic film , sowing , plastic film perforating , soil covering at one time, and it is suitable to the covering plastic film as well as planting of the grandulated crops, such as cotton , corn, soybean and so on.

• 한국농림기상학회지
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• 제19권3호
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• pp.86-92
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• 2017

본 연구에서는 기상청 예보자료를 이용할 것을 전제로 서리가 발생하는 날과 서리가 발생하지 않는 날을 구분하는 모형을 구축하였다. 서리가 발생한 날과 서리가 발생하지 않은 날을 구분할 수 있는 기상인자로서 최저기온, 평균풍속, 평균상대습도, 평균이슬점온도로 나타났다. 기상인자별로 두 날을 비교한 결과 서리가 발생한 날이 서리가 발생하지 않은 날에 비해 최저기온, 이슬점온도, 평균풍속은 낮게 나타났고 상대습도는 높게 나타났다. 이러한 기상인자로 인공신경망, 랜덤포레스트, 서포트벡터 머신의 기계학습법을 이용한 모형을 연구한 결과 70%이상의 정확도를 나타내어 활용 가능성이 있을 것으로 판단된다.

• Journal of Biosystems Engineering
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• 제26권6호
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• pp.571-578
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• 2001

Production of green pepper has increased for ten years in Korea, as customer's preference of a pepper tuned to fiesta one. This study was conducted to develop an on-line fading algorithm of green pepper using machine vision and aimed to develop the automatic on-line grading and sorting system. The machine vision system was composed of a professive scan R7B CCD camera, a frame grabber and sets of 3-wave fluorescent lamps. The length and curvature, which were main quality factors of a green pepper were measured while removing the stem region. The first derivative of the thickness profile was used to remove the stem area of the segmented image of the pepper. A new boundary was generated after the stem was removed and a baseline of a pepper which was used for the curvature determination was also generated. The developed algorithm showed that the accuracy of the size measurement was 86.6% and the accuracy of the bent was 91.9%. Processing time spent far grading was around 0.17 sec per pepper.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.464-469
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• 2023

The government has set the mechanization of paddy agriculture as a national task, aiming to achieve over 70% by 2025. The main objective is to stabilize the farming costs of rural households due to the aging and feminization of rural areas, as well as the shortage of agricultural labor. In response to this, the Korea Rural Economic Institute operates a farm machinery rental business. However, there are challenges in selecting and managing rental machinery, including issues related to labor, costs, verification, and time. Additionally, there is a limit to upgrades, and overseas models are being imported and used for transplanters and rice planters, which do not conform to domestic standards and face maintenance difficulties. In order to solve the difficulties of the agricultural machine rental business, we intend to develop an application that shares domestic and foreign machines purchased and used by individuals at a low cost and use them in gun-level administrative districts.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2001년도 하계 학술대회 논문집
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• pp.123-128
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• 2001