• Title/Summary/Keyword: Dried Oak Mushroom

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Quality Characteristics of Oak Mushroom Salad Dressing (표고버섯을 이용한 샐러드 드레싱 제조의 품질 특성)

  • Jung, Hyeon-A;Kim, An-Na
    • Journal of the East Asian Society of Dietary Life
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    • v.21 no.5
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    • pp.669-676
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    • 2011
  • This study was conducted to develop a novel salad dressing composite recipe composed of natural seasoning containing dried oak mushroom (Lentirus edodes). Dried oak mushroom (Lentirus edodes) has a better flavor and more nutrients than fresh oak mushroom since vitamins are activated during the drying process. To manufacture salad dressing with Lentirus edodes, dressing with 0%, 3%, 6%, 9%, and 12% added L. edodes were prepared and tested for quality. The pH of the dressing decreased with added L. edodes content, whereas acidity increased but decreased again in the 9% dressing. The L value decreased with added L. edodes content, whereas the a and b values increased but decreased again in the 9% dressing. Sugar content increased with added L. edodes. Rradish strength increased with added oak mushroom. Brittleness and chewiness decreased in the lower percentage dressing, increased in the 9% dressing, but decreased again in the 12% dressing. According to the sensory evaluation results, the highest overall acceptability was 3.3, in the 6% dressing compared to the control group.

RECOGNITION ALGORITHM OF DRIED OAK MUSHROOM GRADINGS USING GRAY LEVEL IMAGES

  • Lee, C.H.;Hwang, H.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1996.06c
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    • pp.773-779
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    • 1996
  • Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

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Development of Automatic Grading and Sorting System for Dry Oak Mushrooms -2nd Prototype- (건표고 자동 등급선별 시스템 개발 -시작 2호기-)

  • Hwang, H.;Kim, S. C.;Im, D. H.;Song, K. S.;Choi, T. H.
    • Journal of Biosystems Engineering
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    • v.26 no.2
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    • pp.147-154
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    • 2001
  • In Korea and Japan, dried oak mushrooms are classified into 12 to 16 different categories based on its external visual quality. And grading used to be done manually by the human expert and is limited to the randomly sampled oak mushrooms. Visual features of dried oak mushrooms dominate its quality and are distributed over both sides of the gill and the cap. The 2nd prototype computer vision based automatic grading and sorting system for dried oak mushrooms was developed based on the 1st prototype. Sorting function was improved and overall system for grading was simplified to one stage grading instead of two stage grading by inspecting both front and back sides of mushrooms. Neuro-net based side(gill or cap) recognition algorithm of the fed mushroom was adopted. Grading was performed with both images of gill and cap using neural network. A real time simultaneous discharge algorithm, which is good for objects randomly fed individually and for multi-objects located along a series of discharge buckets, was developed and implemented to the controller and the performance was verified. Two hundreds samples chosen from 10 samples per 20 grade categories were used to verify the performance of each unit such as feeding, reversing, grading, and discharging unites. Test results showed that success rates of one-line feeding, reversing, grading, and discharging functions were 93%, 95%, 94%, and 99% respectively. The developed prototype revealed successful performance such as the approximate sorting capability of 3,600 mushrooms/hr per each line i.e. average 1sec/mushroom. Considering processing time of approximate 0.2 sec for grading, it was desired to reduce time to reverse a mushroom to acquire the reversed surface image.

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Development of Grading and Sorting System of Dried Oak Mushrooms via Color Computer Vision System (컬러 컴퓨터시각에 의거한 건표고 등급 선별시스템 개발)

  • Kim, S.C.;Choi, D.Y.;Choi, S.;Hwang, H.
    • Journal of Biosystems Engineering
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    • v.32 no.2 s.121
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    • pp.130-135
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    • 2007
  • An on-line real time grading and sorting system for dried oak mushrooms was developed for on-site application. Quality grades of the mushrooms were determined according to an industrial specification. Three dimensional visual quality features were used for the grading. A progressive color computer vision system with white LED illumination was implemented to develop an algorithm to extract external quality patterns of the dried oak mushrooms. Cap (top) and gil (stem) surface images were acquired sequentially and side image was obtained using mirror. Algorithms for extracting size, roundness, pattern and color of the cap, thickness, color of the gil and amount of rolled edge of the dried mushroom were developed. Utilizing those quality factors normal and abnormal ones were classified and normal mushrooms were further classified into 30 different grades. The sorting device was developed using microprocessor controlled electro-pneumatic system with stainless buckets. Grading accuracy was around 97% and processing time was 0.4 s in average.

Development of On-line Grading System Using Two Surface Images of Dried Oak Mushrooms (양면영상을 이용한 온라인 검표고 등급판정 시스템 개발)

  • Hwang, H.;Lee, C. H.;Kim, S. C.
    • Journal of Biosystems Engineering
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    • v.24 no.2
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    • pp.153-158
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    • 1999
  • As a basic research for the development of the automatic grading and sorting system for dried oak mushrooms, the device to acquire both cap and gill side images of mushroom has been developed and neural network based side recognition and quality grading has been proposed via inputting both side images. 20 quality grades have been selected considering the requirement of grade classifications imposed by the mushroom company. Developed DC motor driven‘V’type reversing device for the image acquisition of both side images of mushroom showed more than 95% success. Most error was caused by very small size mushrooms with a radius of around 1cm. However, it required a further research to reduce the reversing time. Grading and side recognition were performed via inputting normalized size factors and average gray levels of $8{\times}8$ grids converted from the raw images of both surfaces to the multi-layer back propagation(BP) network. Accuracy of the grading showed about 88.5% and the total grading time including reversing operation was around 2 seconds.

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Optimization of Iced Cookie Prepared with Dried Oak Mushroom (Lentinus edodes) Powder using Response Surface Methodology (표고버섯 분말 첨가 냉동쿠키 제조의 최적화)

  • Jung, Eun-Kyun;Joo, Na-Mi
    • Korean journal of food and cookery science
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    • v.26 no.2
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    • pp.121-128
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    • 2010
  • This study was conducted to develop an optimal composite recipe of nutritional cookies containing oak mushroom (Lentinus edodes) powder that has a high preference score. Oak mushroom(Lentinus edodes) is considered a significantly wholesome food. In addition, the dried oak mushroom(Lentinus edodes) has a better flavor and more nutrients than the fresh oak mushroom since vitamins are activated during the drying process. Wheat flour was partially substituted with Lentinus edodes powder to reduce its content. The optimal sensory composite recipe was determined by making iced cookies which have the advantage of long storage, at 3 concentrations of Lentinus edodes powder, yellow sugar and butter, using the central composite design. In addition, the mixing condition of Lentinus edodes powder cookies was optimized by subjecting the cookies to a sensory evaluation and instrumental analysis using the response surface methodology(RSM). The effects of the addition of the three variables on the quality of Lentinus edodes cookies were assessed in terms of texture, color, spread ratio and sensory evaluation. The results of the sensory evaluation produced very significant values for color, appearance, texture, overall quality(p<0.05), flavor(p<0.01) and the results of instrumental analysis showed significant values in lightness(p<0.05), spread ratio, hardness(p<0.01). As a result, the optimal sensory ratio of Lentinus edodes cookies was determined to be Lentinus edodes powder 10.83g, yellow sugar 61.89 g, and butter 120.0 g.

Storeability and Cooking Property of Dried Oak Mushroom Treated with Ethylene Oxide and Gamma Radiation (감마선 조사와 훈증 처리된 건조 표고버섯의 저장성 및 조리 적성)

  • 김영재;김종군;조한옥;변명우;권중호
    • Journal of Food Hygiene and Safety
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    • v.2 no.1
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    • pp.29-34
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    • 1987
  • ABSTRACT$.$ Ethylene oxide (E.O) fumigation and gamma irradiation were applied to compar$.$ ative researches on the microbiological, physical and cooking quality of dried oak mushroom stored at $25^{\circ}C$ and different relative humidities. The equivalent moisture contents of dried oak mushroom for the limiting growth of general molds and xerophilic mold at $25^{\circ}C$ were shown to be 17% and 27% respectively. Total aerobic bacteria, molds and coliforms were sterilized at 5 kGy irradiation but E.O. fumigation was proved insufficient to eliminate the molds. The hydration rate of dried oak mushroom increased according to the increase of irradiation dose and soaking temperatures. and an irradiation by 5 kGy could shorten the hydration time of the sample as compared to E.O. treatment and control group. Sensory evaluation for the irradiated cooked sample was not significantly different in flavour but the texture of the gamma irradiated sample was significantly better(p < 0.01) than that of E. O. fumigated sample.sample.

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Development of On-line Quality Sorting System for Dried Oak Mushroom - 3rd Prototype-

  • 김철수;김기동;조기현;이정택;김진현
    • Agricultural and Biosystems Engineering
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    • v.4 no.1
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    • pp.8-15
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    • 2003
  • In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.

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Cultural characteristics according to different rates of substrate composition in bottle cultivation of Grifola frondosa (잎새버섯 병재배 시 배지조성비율에 따른 재배 특성)

  • Jeon, Dae-Hoon;Kim, Jeong-Han;Lee, Yun-Hae;Choi, Jong-In;Chi, Jeong-Hyun;Hong, Hye-Jeong
    • Journal of Mushroom
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    • v.13 no.4
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    • pp.301-304
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    • 2015
  • This study was carried out to investigate the optimum rate of substrate composition in bottle cultivation of Grifola frondosa and had three rates of substrate composition of 67:11:22(T1), 68:15:17(T2) and 74:14:12(T3) as mixing rate of weight of dried oak sawdust, dried corn husk and dried bean-curd refuse. The rate of primordia formation of T3 was 65.8% which was lowest among all treatments. Contraction rate of disease of T1 was 9.8% which was highest among all treatments. Harvesting rate of T2 was 70.5% which was highest among all treatments. Fruit body weights per bottle of T1 and T2 were 85.5 g, 83.3 g respectively and there was not significant difference between those. Yield per 10,000 bottles of T2 was 587 kg and was 7%, 28% higher than those of T1 and T3, respectively. As a result, the rate of substrate composition of 68:15:17(T2) as mixing rate of weight of dried oak sawdust, dried corn husk and dried bean-curd refuse was appeared as optimum rate of substrate composition in bottle cultivation of Grifola frondosa..

Intelligent Automatic Sorting System For Dried Oak Mushrooms

  • Lee, C.H.;Hwang, H.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1996.06c
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    • pp.607-614
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    • 1996
  • A computer vision based automatic intelligent sorting system for dried oak mushrooms has been developed. The developed system was composed of automatic devices for mushroom feeding and handling, two sets of computer vision system for grading , and computer with digital I/O board for PLC interface, and pneumatic actuators for the system control. Considering the efficiency of grading process and the real time on-line system implementation, grading was done sequentially at two consecutive independent stages using the captured image of either side. At the first stage, four grades of high quality categories were determined from the cap surface images and at the second stage 8 grades of medium and low quality categories were determined from the gill side images. The previously developed neuro-net based mushroom grading algorithm which allowed real time on-line processing was implemented and tested. Developed system revealed successful performance of sorting capability of approximate y 5, 000 mushrooms/hr per each line i.e. average 0.75 sec/mushroom with the grading accuracy of more than 88%.

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