Journal of Intelligent Agricultural Mechanization ›› 2024, Vol. 5 ›› Issue (3): 63-74.DOI: 10.12398/j.issn.2096-7217.2024.03.007
ZHANG Ruizhi1(), LIU Qianyuan1(), HUANG Yuying1, LIU Bing1, CHANG Zhiguang1, WANG Jiaoling2,3
Received:
2024-06-01
Revised:
2024-07-28
Online:
2024-08-15
Published:
2024-08-15
Corresponding author:
LIU Qianyuan
About author:
ZHANG Ruizhi, engineer; research interests: agricultural engineering consulting and planning design. E-mail: 312296315@qq.com
Supported by:
CLC Number:
ZHANG Ruizhi, LIU Qianyuan, HUANG Yuying, LIU Bing, CHANG Zhiguang, WANG Jiaoling. Development status and prospect of cold chain logistics of fruits, vegetables, and agricultural products based on intelligent technology[J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(3): 63-74.
Add to citation manager EndNote|Ris|BibTeX
URL: http://znhnyzbxb.niam.com.cn/EN/10.12398/j.issn.2096-7217.2024.03.007
Application scenario | Intelligent technology | Key function | Dominance | Inferior |
---|---|---|---|---|
Intelligent warehousing | 1)Intelligent temperature control: temperature and humidity sensors, Internet of Things, big data and other technologies 2) AGV intelligent handling: electromagnetic navigation technology, two-dimensional code navigation technology, laser navigation technology, vision navigation technology | 1) Intelligent temperature control: real-time monitoring and precise control of temperature and humidity to ensure that fruits and vegetables are stored and transported in a suitable environment 2) Intelligent handling: realise autonomous navigation and obstacle avoidance, improve handling efficiency and reduce manpower cost | 1) Improving freshness and reducing energy costs 2)Improve handling efficiency and accuracy, reduce manual errors 3) Reduce labour intensity and improve working environment | 1) Large initial investment 2) High technical threshold 3) The existence of data security risks |
Intelligent sorting | Sensor and electro-optical technology, computer vision technology, Internet of Things, PLC automatic control technology, etc. | Fast and accurate sorting and grading of fruits and vegetables | Improve sorting speed and accuracy and reduce manual intervention | 1) Highly technically demanding 2) Requires regular maintenance and calibration to ensure accuracy |
Intelligent detection | Computer vision technology, near-infrared spectroscopy technology, acoustic properties application technology, electronic nose (tongue) technology, electric and magnetic properties application technology, X-ray and laser application technology, and so on | 1) Non-contact, non-destructive testing of fruits and vegetables 2) Determine quality indicators such as sugar content and acidity as well as freshness and ripeness | Enables rapid, non-destructive testing to protect the integrity of fruit and vegetables | Equipment is costly and requires specialised personnel to operate and maintain; some detection techniques may be affected by environmental factors |
Intelligent transport | GPS, Internet of Things and big data technology, perspective imaging technology, radioactive on-line detection technology, electromagnetic wave application technology, and so on | 1) Real-time monitoring of the position, speed, temperature, humidity and other parameters of transport vehicles, and can automatically adjust and optimise transport routes and speed 2) Intelligent application of highway green channel to reduce clearance time | 1) Improve transport efficiency 2) Reduce wastage and waste during transport | 1) High investment 2) High dependence on network and data transmission |
Table 1 The main functions and advantages and disadvantages of intelligent technology in the field of fruit and vegetable cold chain
Application scenario | Intelligent technology | Key function | Dominance | Inferior |
---|---|---|---|---|
Intelligent warehousing | 1)Intelligent temperature control: temperature and humidity sensors, Internet of Things, big data and other technologies 2) AGV intelligent handling: electromagnetic navigation technology, two-dimensional code navigation technology, laser navigation technology, vision navigation technology | 1) Intelligent temperature control: real-time monitoring and precise control of temperature and humidity to ensure that fruits and vegetables are stored and transported in a suitable environment 2) Intelligent handling: realise autonomous navigation and obstacle avoidance, improve handling efficiency and reduce manpower cost | 1) Improving freshness and reducing energy costs 2)Improve handling efficiency and accuracy, reduce manual errors 3) Reduce labour intensity and improve working environment | 1) Large initial investment 2) High technical threshold 3) The existence of data security risks |
Intelligent sorting | Sensor and electro-optical technology, computer vision technology, Internet of Things, PLC automatic control technology, etc. | Fast and accurate sorting and grading of fruits and vegetables | Improve sorting speed and accuracy and reduce manual intervention | 1) Highly technically demanding 2) Requires regular maintenance and calibration to ensure accuracy |
Intelligent detection | Computer vision technology, near-infrared spectroscopy technology, acoustic properties application technology, electronic nose (tongue) technology, electric and magnetic properties application technology, X-ray and laser application technology, and so on | 1) Non-contact, non-destructive testing of fruits and vegetables 2) Determine quality indicators such as sugar content and acidity as well as freshness and ripeness | Enables rapid, non-destructive testing to protect the integrity of fruit and vegetables | Equipment is costly and requires specialised personnel to operate and maintain; some detection techniques may be affected by environmental factors |
Intelligent transport | GPS, Internet of Things and big data technology, perspective imaging technology, radioactive on-line detection technology, electromagnetic wave application technology, and so on | 1) Real-time monitoring of the position, speed, temperature, humidity and other parameters of transport vehicles, and can automatically adjust and optimise transport routes and speed 2) Intelligent application of highway green channel to reduce clearance time | 1) Improve transport efficiency 2) Reduce wastage and waste during transport | 1) High investment 2) High dependence on network and data transmission |
1 | Ministry of Transport of the People's Republic of China. Circular of the General Office of the Ministry of Transport on the Issuance of Technical Guidelines for Intelligent Refrigerated Container Terminal Equipment [EB/OL]. , 2022-09-22. |
2 | General Office of the State Council of the People's Republic of China. Circular of the General Office of the State Council on the Issuance of the ‘14th Five-Year Plan’ for the Development of Modern Logistics [EB/OL]. , 2022-12-15. |
3 | State Council of the People's Republic of China. Circular of the State Council on the issuance of the ‘14th Five-Year Plan’ for promoting modernisation of agriculture and rural areas [EB/OL]. , 2021-11-12. |
4 | Central Committee of the Communist Party of China, State Council of the People's Republic of China. CPC Central Committee State Council on the complete and accurate comprehensive implementation of the new development concept to do a good job of carbon peak carbon neutral work [EB/OL]. , 2021-09-22. |
5 | CPC Central Committee,State Council of the People's Republic of China. CPC Central Committee State Council Issues Outline of Strategic Planning for Expanding Domestic Demand (2022-2035) [EB/OL]. , 2022-12-14. |
6 | China Federation of Logistics and Purchasing Cold Chain Logistics Professional Committee and other editors. China cold chain logistics development report(2023) [M]. Beijing: China Fortune Publishing House Ltd, 2023. |
7 | XU Hangyu. Design and implementation of control system for warehouse handling robot [D]. Nanjing: Nanjing University of Science and Technology, 2017. |
8 | WANG Zhendong, GUO Xiaojun, WANG Haifeng, et al. AGV positioning and magnetic navigation based on RFID [J]. Equipment Manufacturing Technology, 2021(7): 106-110. |
9 | ZHENG Jinsong. Design and application of control system for warehouse logistics handling robot [J]. Packaging and Food Machinery, 2023, 41(3): 59-64. |
10 | LI Dunmai. Research on AGV SLAM algorithm based on lidar and vision fusion and path planning [D]. Changchun: Jilin University, 2023. |
11 | GAO Xudong, HAN Xichun, ZHANG Zhengsu, et al. Design of a fruit and vegetable sorting robot intelligent system [J]. Technology & Economy in Areas of Communications, 2016, 18(6): 61-64, 74. |
12 | CAI Xinyao, HE Kaiji, ZHANG Chenyang, et al. Implementation of target extraction algorithm in fruit and vegetable intelligent sorting system [J]. Journal of Southwest Minzu University (Natural Science Edition), 2019, 45(2): 178-184. |
13 | ZHANG Ying, CHENG Ruqi, CHEN Shaohui. Research on fruit and vegetable intelligent sorting technology of high speed remote control based on PLC [J]. Storage and Process, 2021, 21(12): 111-117. |
14 | WANG Lei. Exploratory research on spherical agricultural product sorter based on machine vision [J]. Southern Agricultural Machinery, 2022, 53(10): 9-12, 23. |
15 | BAI Zhenwei, YAN Fuwei, YUAN Peihai, et al. Design and experiment of fruit sorting robot based on embedded machine vision [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(3): 61-70. |
16 | LAKSHMI S, PANDEY A K, RAVI N, et al. Non-destructive quality monitoring of fresh fruits and vegetables [J]. Defence Life Science Journal, 2017, 2: 103-110. |
17 | SHEN Haijun. Research on intelligent detection of apple freshness based on low-field nuclear magnetic resonance technology [D]. Yangzhou: Yangzhou University, 2023. |
18 | WANG Tiesheng. Development and application of computer vision technology [J]. Information System Engineering, 2022(4): 63-66. |
19 | YANG Tao, LI Xiaoxiao. Research progress of machine vision technology in modern agricultural production [J]. Journal of Chinese Agricultural Mechanization, 2021, 42(3): 171-181. |
20 | XU Yingying. Study on melon external quality inspection based on computer vision [D]. Lanzhou: Gansu Agricultural University, 2011. |
21 | WU Guangxu. Research on non-destructive detection and grading technology of blood orange based on computer vision [D]. Chongqing: Southwest University, 2016. |
22 | Jiayu LÜ, ZHU Danshi, FENG Xuqiao,et al. Intelligent sensing technology and its application in quality inspection of fresh fruits and vegetables [J]. Food and Fermentation Industry, 2014, 40(11): 215-221. |
23 | GUO Zhiming, GUO Gang, WANG Mingming, et al. Progress in non-destructive testing of fruit and vegetable quality and safety by near-infrared spectroscopy [J]. Journal of Food Safety and Quality Inspection, 2019, 10(24): 8280-8288. |
24 | LIU Yan, ZHOU Xinqi, YU Xiaofeng, et al. Research progress on the application of non-destructive testing technology in fruit and vegetable quality testing [J]. Journal of Zhejiang University (Agriculture and Life Science Edition), 2020, 46(1): 27-37. |
25 | ZHANG Shuai, SHI Lei, ZHANG Benhua. Ripeness detection method of melon based on acoustic characteristics [J]. Journal of Agricultural Mechanization Research, 2011, 33(10): 126-129. |
26 | GAO Guandong, TENG Guifa, XIAO Ke, et al. Non-destructive detection of watermelon ripeness based on BMV features [J]. Journal of Agricultural Engineering, 2010, 26(8): 326-330. |
27 | ZHANG Yuxin, ZHAO Yang, TAO Jia. Research on non-destructive detection technology of watermelon ripeness based on audio characteristics [J]. Journal of Hebei Agricultural University, 2011, 34(2): 114-118. |
28 | YANG Fan, LU Lixin. Design of non-destructive fruit ripening detection system based on spectral imaging and acoustic technology [J]. Journal of Lanzhou College of Arts and Sciences (Natural Science Edition), 2023, 37(1): 60-65. |
29 | FENG Lei. Research on intelligent detection of cucumber and cherry tomato freshness based on electronic nose and low-field nuclear magnetic resonance [D]. Wuxi: Jiangnan University, 2019. |
30 | CUI Di, ZHANG Wen, YING Yibin. Application of laser Doppler vibrometry in agricultural product quality detection [J]. Journal of Agricultural Machinery, 2013, 44(7): 160-164. |
31 | YU Huafen, QIN Li. Research progress of laser technology in agricultural product quality inspection [J]. Agriculture and Technology, 2019, 39(21): 49-50. |
32 | LIU Peng. Design and realization of highway green channel information management system [D]. Xi'an: Chang'an University, 2017. |
33 | LI Jianli, YUAN Huabing, JIN Bo, et al. Research and application of green channel verification system for highway intelligent logistics [J]. China Logistics and Purchasing, 2022(13): 45-47. |
34 | XUE Chunfeng. Research and application of intelligent detection system for highway green channel vehicles [C]// Highway Operation and Management Branch of China Highway Society. Proceedings of the 2011 Annual Meeting of Highway Operation and Management Branch of China Highway Society and the 18th National Seminar on Highway Operation and Management. Toll Management Branch of North China Expressway Company Limited, 2011: 5. |
35 | NIU Jianqiang, MENG Hongfei, YANG Ruirui, et al. Research on rapid detection program for green channel vehicles [J]. China Traffic Information Technology, 2010(11): 116-117, 119. |
[1] | GAO Zhen, LU Caiyun, LI Hongwen, HE Jin, WANG Qingjie, GUO Zhaoyang. Research progress and the prospect of crucial technology of seed spacing information detection based on computer vision [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(3): 50-60. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||