Study on Extraction Method of Melanotic Characteristics of Infected Cooked Shrimp

HONG Chen; LIU Zihao; WANG Xuqian; GAO Le; ZHENG Zhenyu

doi:10.13386/j.issn1002-0306.2021100264

Volume 43 Issue 17

Aug. 2022

Turn off MathJax

Article Contents

Abstract

References

Science and Technology of Food Industry > 2022 > 43(17): 11-18. > DOI: 10.13386/j.issn1002-0306.2021100264

HONG Chen, LIU Zihao, WANG Xuqian, et al. Study on Extraction Method of Melanotic Characteristics of Infected Cooked Shrimp[J]. Science and Technology of Food Industry, 2022, 43(17): 11−18. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021100264.

Citation:

PDF (7666 KB)

Study on Extraction Method of Melanotic Characteristics of Infected Cooked Shrimp

College of Information Science and Engineering, Jiaxing University, Jiaxing 314001, China

More Information

Received Date: October 25, 2021
Available Online: June 29, 2022

Graphical Abstract

Abstract

Abstract

In this paper, a method for extracting browning features from cooked shrimps based on a simplified color model was proposed. A large number of images of normal cooked shrimps and melanotic cooked shrimps in the dynamic production line were obtained by online image acquisition equipment, and the region of interest of cooked shrimps was extracted by using the grey-scale difference method and morphological operations, and the browning features of cooked shrimps were extracted by three color spaces; a color model was constructed for 151 images of normal shrimps and 66 images of melanotic shrimps in the training set, and the percentage of browning areas of cooked shrimps were used as the benchmark condition to determine whether browning occurred in cooked shrimps, and were graded. The results showed that the RGB color model with the B-component range of 0~77 was the most effective, and the recognition rate could reach 91.36 ms/each of the 116 normal and 50 browned shrimp images, which reduced the complexity of the algorithm from O(n²) to O(n) and improved the recognition accuracy by 7.3% to 92.77% compared with the traditional binary linear discriminant analysis method. The method has greater practical advantages and application prospects, providing performance support for the application of machine vision technology to the online non-destructive inspection of the appearance quality of South American white shrimp.
- shrimp (Litopenaeus vannamei),
- melanotic cooked shrimp,
- color feature,
- machine vision,
- image processing

FullText(HTML)

References (35)

References

[1]	LIU Z H, JIA X J, XU X S. Study of shrimp recognition methods using smart networks[J]. Computers and Electronics in Agriculture,2019,165:104926. doi: 10.1016/j.compag.2019.104926
[2]	MATSUMOTO M, YAMANAKA H. Post-mortem biochemical changes in the muscle of Kuruma shrimp during storage and evaluation of the freshness[J]. Bull Jap Soc Sei Fish,1990,56(7):1145−1149. doi: 10.2331/suisan.56.1145
[3]	殷磊. 即食干制对虾加工工艺及货架期预测[D]. 保定: 河北农业大学, 2018 YIN L. Ready-to-eat dried shrimp processing technology and shelf life prediction[D]. Baoding: Hebei Agricultural University, 2018.
[4]	陈飞东, 戴志远, 王宏海. 虾保鲜冰对南美白对虾保鲜效果影响[J]. 食品研究与开发,2009,31(1):120−123. [CHEN F D, DAI Z Y, WANG H H. Study on preparation effect of fresh ice for white leg shrimp[J]. Food Research and Development,2009,31(1):120−123. doi: 10.3969/j.issn.1005-6521.2009.01.036 CHEN F D, DAI Z Y, WANG H H. Study on preparation effect of fresh ice for white leg shrimp[J]. Food Research and Development, 2009, 31(1): 120-123. doi: 10.3969/j.issn.1005-6521.2009.01.036
[5]	农业农村部渔业渔政管理局. 2020中国渔业统计年鉴[M]. 北京: 中国农业出版社, 2021 Fishery Administration of Ministry of Agriculture and Rural Affairs. China fishery statistics yearbook 2020[M]. Beijing: China Agriculture Press, 2021.
[6]	张高静, 韩丽萍, 孙剑锋, 等. 南美白对虾营养成分分析与评价[J]. 中国食品学报,2013,13(8):254−260. [ZHANG G J, HAN L P, SUN J F, et al. Analysis and evaluation of nutritive composition in Penaeus vannamei[J]. J Chin Inst Food Sci Technol,2013,13(8):254−260. ZHANG G J, HAN L P, SUN J F, et al. Analysis and evaluation of nutritive composition in Penaeus vannamei[J]. J Chin Inst Food Sci Technol, 2013, 13(8): 254‒260.
[7]	中华人民共和国农业部. 中华人民共和国水产行业标准. 冻熟对虾[S]. 2012, 1−2 The Ministry of Agriculture of the People's Republic of China. Fishery industry standard of the People's Republic of China. Frozen cooked shrimp[S]. 2012, 1−2.
[8]	徐德峰, 李彩虹, 孙力军, 等. 冷藏南美白对虾丝氨酸蛋白酶活力与黑变相关性研究[J]. 现代食品科技,2014,30(2):100−104. [XU D F, LI C H, SUN L J, et al. The melanosis, serine protease activity and their correlation of Litopenaeus vannamei during cold storage[J]. Modern Food Science and Technology,2014,30(2):100−104. XU D F, LI C H, SUN L J, et al. The melanosis, serine protease activity and their correlation of Litopenaeus vannamei during cold storage[J]. Modern Food Science and Technology, 2014, 30(2): 100-104.
[9]	吕艳芳, 蔡路昀, 李颖畅, 等. 冰温下复合保鲜剂和焦亚硫酸钠对南美白对虾防黑变保鲜效果比较[J]. 中国食品学报,2017,17(7):129−138. [LÜ Y F, CAI L Y, LI Y C, et al. The comparison between compound preservatives and sodium metabisulfitetreatment on the anti-melanosis effect of Penaeus vannamei under ice-temperature[J]. Chinese Journal of Food,2017,17(7):129−138. LÜ Y F, CAI L Y, LI Y C, etal. The comparison between compound preservatives and sodium metabisulfitetreatment on the anti-melanosis effect of Penaeus vannamei under ice-temperature[J]. 2017, 17(7): 129-138.
[10]	LIU Z H, CHENG F, ZHANG W. Recognition-based image segmentation of touching pairs of cooked shrimp (Penaeus orientalis) using improved pruning algorithm for quality measurement[J]. Journal of Food Engineering,2017,195(feb.):166−181.
[11]	黄万有, 吉宏武, 刘书成, 等. 凡纳滨对虾PPO的组织分布和活性与其贮藏过程中黑变的关系[J]. 现代食品科技,2014,30(2):89−94. [HUANG W Y, JI H W, LIU S C, et al. Relation of tissue distribution and activity of polyphenol oxidase from Litopenaeus vannamei and its melanosis during storage[J]. Modern Food Science and Technology,2014,30(2):89−94. HUANG W Y, JI H W, LIU S C, et al. Relation of tissue distribution and activity of polyphenol oxidase from Litopenaeus vannamei and its melanosis during storage[J]. Modern Food Science and Technology, 2014, 30(2): 89-94.
[12]	凌萍华, 谢晶. 冰温技术结合保鲜剂对南美白对虾品质的影响[J]. 食品科学,2010,31(14):280−284. [LING P H, XIE J. Effects of super-chilling combined with preservatives on chemical, biochemical and sensory properties of Pacific white shrimp[J]. Food Science,2010,31(14):280−284. LING P H, XIE J. Effects of super-chilling combined with preservatives on chemical, biochemical and sensory properties of Pacific white shrimp[J]. Food Science, 2010, 31(14): 280-284.
[13]	陈田聪, 谢达祥, 陈晓汉. 南美白对虾淡水养殖常见病害及防治措施[J]. 南方农业,2018,12(20):145−147. [CHEN T C, XIE D X, CHEN X H. Common diseases of freshwater shrimp and control measures[J]. South China Agriculture,2018,12(20):145−147. CHEN T C, XIE D X, CHEN X H. Common diseases of freshwater shrimp and control measures[J]. South China Agriculture, 2018, 12(20): 145-147.
[14]	高学礼, 李月娟. 对虾加工鲜度控制及检验[J]. 中国酿造,2009(6):144−145. [GAO X L, LI Y J. Control and inspection of shrimp freshness during processing[J]. China Brewing,2009(6):144−145. doi: 10.3969/j.issn.0254-5071.2009.06.046 GAO X L, LI Y J. Control and inspection of shrimp freshness during processing[J]. China Brewing, 2009(6): 144-145. doi: 10.3969/j.issn.0254-5071.2009.06.046
[15]	LIU Z H, CHENG F, GONG Z Y, et al. Automatic system for eliminating shrimp impurities using iteration algorithm[J]. International Agricultural Engineering Journal,2016,25(4):210−224.
[16]	LUZURIAGA D A, BALABAN M O, YERALAN S. Analysis of visual quality attributes of white shrimp by machine vision[J]. Journal of Food Science,1997,62(1):113−118. doi: 10.1111/j.1365-2621.1997.tb04379.x
[17]	MOHEBBI M, AKBARZADEH-T M R, SHAHIDI F, et al. Computer vision systems (CVS) for moisture content estimation in dehydrated shrimp[J]. Computers and Electronics in Agriculture,2009,69(2):128−134. doi: 10.1016/j.compag.2009.07.005
[18]	贾磊, 陈俊超. 机器视觉的水产食品外观品质检测系统[J]. 食品工业,2021,42(5):266−268. [JIA L, CHEN J C. Machine vision inspection system for appearance quality of aquatic food[J]. Food Industry,2021,42(5):266−268. JIA L, CHEN J C. Machine vision inspection system for appearance quality of aquatic food[J]. Food Industry, 2021, 42(5): 266‒268.
[19]	章建设, 陈玉玲, 谢主兰. 对虾产品质量安全标准要求[J]. 食品安全导刊,2015(15):154−156. [ZHANG J S, CHEN Y L, XIE Z L. Quality and safety standard requirements for prawn products[J]. China Food Safety Magazine,2015(15):154−156. ZHANG J S, CHEN Y L, XIE Z L. Quality and safety standard requirements for prawn products[J]. China Food Safety Magazine, 2015(15): 154‒156.
[20]	黄卉, 李来好, 杨贤庆, 等. 对虾产品质量分级要素及评价技术[J]. 中国水产科学,2010,17(6):1371−1376. [HUANG H, LI L H, YANG X Q, et al. Quality grading factors and evaluation technology of prawn[J]. Journal of Fishery Sciences of China,2010,17(6):1371−1376. HUANG H, LI L H, YANG X Q, et al. Quality grading factors and evaluation technology of prawn[J]. Journal of Fishery Sciences of China, 2010, 17(6): 1371-1376.
[21]	贾志鑫, 傅玲琳, 杨信廷, 等. 机器视觉技术在水产食品感官检测方面的应用研究进展[J]. 食品科学,2019,40(13):320−325. [JIA Z X, FU Z L, YANG X T, et al. A review of the application of machine vision technique in sensory testing of aquatic foods[J]. Food Science,2019,40(13):320−325. doi: 10.7506/spkx1002-6630-20180730-364 JIA Z X, FU Z L, YANG X T, et al. A review of the application of machine vision technique in sensory testing of aquatic foods[J]. Food Science, 2019, 40(13): 320-325. doi: 10.7506/spkx1002-6630-20180730-364
[22]	余博文. 数字图像阈值分割研究与应用[J]. 科学技术创新,2021(19):91−92. [YU B W. Research and application of digital image threshold segmentation[J]. Scientific and Technological Innovation,2021(19):91−92. doi: 10.3969/j.issn.1673-1328.2021.19.040 YU B W. Research and application of digital image threshold segmentation[J]. Scientific and Technological Innovation, 2021(19): 91‒92. doi: 10.3969/j.issn.1673-1328.2021.19.040
[23]	王羿翔. 激光标刻扫描路径生成算法研究[D]. 武汉: 武汉大学, 2017 WANG Y X. Research on laser marking scan path generation algorithm[D]. Wuhan: Wuhan University, 2017.
[24]	燕红文, 邓雪峰. 中值滤波在数字图像去噪中的应用[J]. 计算机时代,2020(2):47−49. [YAN H W, DENG X F. Application of median filter in digital image denoising[J]. Computer Era,2020(2):47−49. YAN H W, DENG X F. Application of median filter in digital image denoising[J]. Computer Era, 2020(2): 47‒49.
[25]	孙全鑫. 基于颜色特征提取的辣椒自动分类系统的设计与实现[D]. 长春: 吉林大学, 2013 SUN Q X. Design and implementation based on color feature extraction of pepper automatic classification system[D]. Changchun: Jilin University, 2013.
[26]	杨奥博, 盛家川, 李玉芝, 等. 基于HSV空间的颜色特征提取[J]. 电脑知识与技术,2017,13(18):193−195. [YANG A B, SHENG J C, LI Y Z, et al. Color feature extraction based on HSV space[J]. Computer Knowledge and Technology,2017,13(18):193−195. YANG A B, SHENG J C, LI Y Z, et al. Color feature extraction based on HSV space[J]. Computer Knowledge and Technology, 2017, 13(18): 193-195.
[27]	GUPTE V. Color constancy, by Marc Ebner (Wiley; 2007) pp 394 ISBN 978-0-470-05829-9 (HB)[J]. Coloration Technology,2009,125(6):366−367. doi: 10.1111/j.1478-4408.2009.00219.x
[28]	BASIRI S, SHEKARFOROUSH S S, AMINLARI M, et al. The effect of pomegranate peel extract (PPE) on the polyphenol oxidase (PPO) and quality of Pacific white shrimp (Litopenaeus vannamei) during refrigerated storage[J]. LWT-Food Science and Technology,2015,63(1):798−798. doi: 10.1016/j.lwt.2015.04.001
[29]	石美红, 申亮, 龙世忠, 等. 从RGB到HSV色彩空间转换公式的修正[J]. 纺织高校基础科学学报,2008(3):351−356. [SHI M H, SHEN L, LONG S Z, etal. The revision of conversion formula from RGB color space to HSV color space[J]. Basic Sciences Journal of Textile Universitles,2008(3):351−356. doi: 10.3969/j.issn.1006-8341.2008.03.023 SHI M H, SHEN L, LONG S Z, etal. The revision of conversion formula from RGB color space to HSV color space[J]. Basic Sciences Journal of Textile Universitles, 2008(3): 351-356. doi: 10.3969/j.issn.1006-8341.2008.03.023
[30]	洪寒梅. 黑变熟对虾的机器视觉识别方法研究[D]. 杭州: 浙江大学, 2015 HONG H M. Research of melanotic cooked shrimp recognition method using machine vision[D]. Hangzhou: Zhejiang University, 2015.
[31]	刘子豪. 基于机器视觉技术的南美白对虾分类算法研究与在线实现[D]. 杭州: 浙江大学, 2016 LIU Z H. Study and online verification for shrimp classification algorithm based on machine vision technology[D]. Hangzhou: Zhejiang University, 2016.
[32]	浙江省海洋与渔业局. DB4155-2003 海捕虾质量要求[S]. 2003 Zhejiang Ocean and Fishery Bureau. DB14155-2003, Quality requirements for marine shrimp fishing[S]. 2003.
[33]	张伟. 基于机器视觉技术的缺损对虾在线识别与剔除系统研究[D]. 杭州: 浙江大学, 2018 ZHANG W. Study of on-line identification and elimination system for incomplete shrimp based on machine vision technology[D]. Hangzhou: Zhejiang University, 2018.
[34]	LIU Z H, CHENG F, HONG H M. Identification of impurities in fresh shrimp using improved majority scheme-based classifier[J]. Food Analytical Methods,2016,9(11):1−10.
[35]	蔡燕萍, 张建友. 虾体多酚氧化酶特性及其抑制技术研究进展[J]. 食品工业科技,2012,33(13):424−428. [CAI Y P, ZHANG J Y. Research progress in characterizationand inhibition of shrimp polyphenol oxidase[J]. Science and Technology of Food Industry,2012,33(13):424−428. CAI Y P, ZHANG J Y. Research progress in characterizationand inhibition of shrimp polyphenol oxidase[J]. Science and Technology of Food Industry, 2012, 33(13): 424-428.

Supplements (0)

Cited By

Cited by

Periodical cited type(2)

1.	武亚帅，邹优扬，张梦璐，赵逸涵，王宗义，高秀芝. 液相色谱法检测烧烤食品中多环芳烃污染情况. 食品工业. 2022(04): 316-321 .
2.	潘芳，曹璐. 2019、2020年抚顺市蔬菜农药残留及膳食暴露风险评估. 预防医学论坛. 2022(05): 364-367 .