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浙江大学学报（农业与生命科学版）
浙江大学学报（农业与生命科学版）  2023, Vol. 49 Issue (3): 293-304    DOI: 10.3785/j.issn.1008-9209.2022.04.062
综述     
农业传感器技术在我国的应用和市场：现状与未来展望
刘羽飞1,2(),何勇1,2(),刘飞1,2,许丽佳3,冯旭萍1,2,唐宇4,王正肖1
1.浙江大学华南工业技术研究院, 广东 广州 510535
2.浙江大学生物系统工程与食品科学学院, 浙江 杭州 310058
3.四川农业大学机电学院, 四川 雅安 625014
4.广东技术师范大学交叉学科研究院, 广东 广州 510665
Application and market of agricultural sensor technology in China: current status and future perspectives
Yufei LIU1,2(),Yong HE1,2(),Fei LIU1,2,Lijia XU3,Xuping FENG1,2,Yu TANG4,Zhengxiao WANG1
1.Huanan Industrial Technology Research Institute of Zhejiang University, Guangzhou 510535, Guangdong, China
2.College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China
3.College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625014, Sichuan, China
4.Academy of Interdisciplinary Studies, Guangdong Polytechnic Normal University, Guangzhou 510665, Guangdong, China
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摘要：

农业传感器技术是农业信息化的基础，是实现农业现代化的核心要素和关键支撑之一。首先，本文在总结农业传感器技术在智能农机装备、农用无人机遥感及农业物联网三方面的研究及应用现状的基础上，对我国农业传感器技术需求和市场发展进行了深入分析。其次，通过技术产业调研分析，对农业传感器产业化、市场化及未来的发展趋势进行了总结与展望。最后，凝练了农业传感器产业领域的16项关键技术，并在此基础上开展了德尔菲法专家问卷调查，阐明了农业传感器最重要的属性是通用性，明确了相关技术发展最大的制约因素是基础理论和研发投入，提出了农业传感器技术将朝着低成本化、高稳定性、高智能化、可移植性、可操作性方向发展。本文可为我国农业传感器技术研发和产业发展提供参考。
关键词： 农业传感器;  技术分析;  市场现状;  发展趋势    
Abstract:

Sensor technology is the foundation of agricultural informatization, and it is one of the core elements and key support to realize agricultural modernization. First, this paper summarizes the current technical status and application of agricultural sensor technology in three areas of intelligent agricultural machinery equipment, agricultural unmanned aerial vehicle (UAV) based remote sensing, and agricultural internet of things, and conducts an in-depth analysis on the technical demands and market development of agricultural sensor in China. Second, the industrialization, marketization, and future development trends of agricultural sensors were summarized and pointed out through the technical industry analysis. Finally, 16 key technologies in the field of agricultural sensor industry were condensed, and on this basis, a Delphi-based expert questionnaire survey was carried out. The results showed that universality was the most important attribute of agricultural sensors; basic theory and research and development input were the two biggest constraints to the development of agricultural sensor technology. It was proposed that the agricultural sensor technology would develop towards low cost, high stability, high intelligence, portability, and operability in the future. This paper provides a reference for the technical and industrial development of agricultural sensors in China.
Key words: agricultural sensor    technical analysis    market status    development trend
收稿日期: 2022-04-06 出版日期: 2023-06-25
CLC:  S24  
基金资助: 广东省重点领域研发计划项目(2019B020216001);浙江省重点研发计划项目(2021C02023);中国工程院咨询项目“智慧农业发展战略研究”(2019-ZD-5);浙江省属高校基本科研业务费专项(2021XZZX024)
通讯作者: 何勇     E-mail: yufeiliu@zju.edu.cn;yhe@zju.edu.cn
作者简介: 刘羽飞（https://orcid.org/0000-0001-7027-8911），Tel：+86-571-88982631，E-mail：yufeiliu@zju.edu.cn
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引用本文:

刘羽飞,何勇,刘飞,许丽佳,冯旭萍,唐宇,王正肖. 农业传感器技术在我国的应用和市场：现状与未来展望[J]. 浙江大学学报（农业与生命科学版）, 2023, 49(3): 293-304.

Yufei LIU,Yong HE,Fei LIU,Lijia XU,Xuping FENG,Yu TANG,Zhengxiao WANG. Application and market of agricultural sensor technology in China: current status and future perspectives. Journal of Zhejiang University (Agriculture and Life Sciences), 2023, 49(3): 293-304.

链接本文:

https://www.zjujournals.com/agr/CN/10.3785/j.issn.1008-9209.2022.04.062    或    https://www.zjujournals.com/agr/CN/Y2023/V49/I3/293

图1  未来5—10年最具市场发展潜力的农业传感器或测控终端产品调查结果
图2  农产品/食品质量安全检测仪器发展重点调查结果
图3  农业机器人发展重点调查结果
图4  作物长势检测传感仪器发展重点调查结果
55 LI J Q, WU H, TAO Y P, et al. Advances in smart agriculture research: application of nanobiotechnology to obtain crop information[J]. Journal of Smart Agriculture, 2021, 1(11): 1-6. (in Chinese with English abstract)
56 仇焕广,黄季焜,杨军中.关于消费者对转基因技术和食品态度研究的讨论[J].中国科技论坛,2007(3):105-108. DOI:10.3969/j.issn.1002-6711.2007.03.023
QIU H G, HUANG J K, YANG J Z. Discussion on consumer attitudes to GMO technology and food research[J]. Forum on Science and Technology in China, 2007(3): 105-108. (in Chinese)
doi: 10.3969/j.issn.1002-6711.2007.03.023
57 刘李,呼英俊.机器人:农业的新时代[J].天津农业科学,2014,20(7):47-50. DOI:10.3969/j.issn.1006-6500.2014.07.011
doi: 10.3969/j.issn.1006-6500.2014.07.011
1 夏显力,陈哲,张慧利,等.农业高质量发展:数字赋能与实现路径[J].中国农村经济,2019(12):2-15.
XIA X L, CHEN Z, ZHANG H L, et al. Agricultural high-quality development: digital empowerment and implementation path[J]. Chinese Rural Economy, 2019(12): 2-15. (in Chinese with English abstract)
2 刘成良,林洪振,李彦明,等.农业装备智能控制技术研究现状与发展趋势分析[J].农业机械学报,2020,51(1):1-18. DOI:10.6041/j.issn.1000-1298.2020.01.001
LIU C L, LIN H Z, LI Y M, et al. Analysis on status and development trend of intelligent control technology for agricultural equipment[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(1): 1-18. (in Chinese with English abstract)
doi: 10.6041/j.issn.1000-1298.2020.01.001
3 李琼,韩雪.温湿度传感器在智慧农业中的应用[J].电脑与电信,2018(10):6-11. DOI:10.15966/j.cnki.dnydx.2018.10.003
LI Q, HAN X. Application of temperature and humidity sensor in smart agriculture[J]. Computer & Telecommunication, 2018(10): 6-11. (in Chinese with English abstract)
doi: 10.15966/j.cnki.dnydx.2018.10.003
4 吕国策.传感器技术在智慧农业中的应用研究[J].南方农机,2020,51(14):56-57. DOI:10.3969/j.issn.1672-3872.2020.14.039
LÜ G C. Application research of sensor technology in smart agriculture[J]. China Southern Agricultural Machinery, 2020, 51(14): 56-57. (in Chinese)
doi: 10.3969/j.issn.1672-3872.2020.14.039
5 李道亮,杨昊.农业物联网技术研究进展与发展趋势分析[J].农业机械学报,2018,49(1):1-20. DOI:10.6041/j.issn.1000-1298.2018.01.001
LI D L, YANG H. State-of-the-art review for internet of things in agriculture[J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(1): 1-20. (in Chinese with English abstract)
doi: 10.6041/j.issn.1000-1298.2018.01.001
6 赵春江,李瑾,冯献,等.“互联网+”现代农业国内外应用现状与发展趋势[J].中国工程科学,2018,20(2):50-56. DOI:10.15302/J-SSCAE-2018.02.008
ZHAO C J, LI J, FENG X, al el. Application status and trend of “internet plus” modern agriculture in China and abroad[J]. Strategic Study of CAE, 2018, 20(2): 50-56. (in Chinese with English abstract)
doi: 10.15302/J-SSCAE-2018.02.008
7 张酉军.农田土壤信息无线传感器网络与数据融合算法研究[D].江苏,无锡:江南大学,2009.
ZHANG Y J. Research of wireless sensor networks and data fusion algorithm based on farmland soil information[D]. Wuxi, Jiangsu: Jiangnan University, 2009. (in Chinese with English abstract)
8 郑丽萍.基于ARM的农田土壤信息获取系统研究与开发[D].陕西,杨凌:西北农林科技大学,2008.
ZHENG L P. Research and development of farmland soil information acquisition system based on ARM[D]. Yangling, Shaanxi: Northwest A&F University, 2008. (in Chinese with English abstract)
9 李惠玲,张晓东,李苇,等.作物生长和环境信息多传感检测系统设计[J].现代农业装备,2021,42(2):38-43. DOI:10.3969/j.issn.1673-2154.2021.02.008
LI H L, ZHANG X D, LI W, et al. Design of multi-sensor detection system for crop growth and environmental information[J]. Modern Agricultural Equipment, 2021, 42(2): 38-43. (in Chinese with English abstract)
doi: 10.3969/j.issn.1673-2154.2021.02.008
10 林维潘,李怀民,倪军,等.基于便携式三波段作物生长监测仪的水稻长势监测[J].农业工程学报,2020,36(20):203-208. DOI:10.11975/j.issn.1002-6819.2020.20.024
LIN W P, LI H M, NI J, et al. Monitoring rice growth based on a portable three-band instrument for crop growth monitoring and diagnosis[J]. Transactions of the CSAE, 2020, 36(20): 203-208. (in Chinese with English abstract)
doi: 10.11975/j.issn.1002-6819.2020.20.024
57 LIU L, HU Y J. Robot: the new age of agriculture[J]. Tianjin Agricultural Sciences, 2014, 20(7): 47-50. (in Chinese with English abstract)
doi: 10.3969/j.issn.1006-6500.2014.07.011
11 唐颖.基于无线传感器网络的作物病虫害监测研究[D].湖南,长沙:湖南农业大学,2008.
TANG Y. Research on crop diseases and pest monitoring based on wireless sensor networks[D]. Changsha, Hunan: Hunan Agricultural University, 2008. (in Chinese with English abstract)
12 唐佳明.基于多传感器融合的小麦病虫害监测系统研究[D].河北,唐山:华北理工大学,2015.
TANG J M. Research on monitoring system of wheat diseases and insect pests based on multi-sensor fusion[D]. Tangshan, Hebei: North China University of Science and Technology, 2015. (in Chinese with English abstract)
13 蔡道清.非结构农田环境下的自主作业感知技术研究[D].上海:上海交通大学,2020.
CAI D Q. Research on autonomous operation perception technology in unstructural farmland environment[D]. Shanghai: Shanghai Jiao Tong University, 2020. (in Chinese with English abstract)
14 郭慧泉.智能农机控制系统的方案设计与验证平台开发[D].安徽,合肥:中国科学技术大学,2019.
GUO H Q. Scheme design and verification platform develop-ment for the control system of intelligent agricultural machinery[D]. Hefei, Anhui: University of Science and Technology of China, 2019. (in Chinese with English abstract)
15 解春季,杨丽,张东兴,等.基于激光传感器的播种参数监测方法[J].农业工程学报,2021,37(3):140-146. DOI:10.11975/j.issn.1002-6819.2021.03.017
XIE C J, YANG L, ZHANG D X, et al. Seeding parameter monitoring method based on laser sensors[J]. Transactions of the CSAE, 2021, 37(3): 140-146. (in Chinese with English abstract)
doi: 10.11975/j.issn.1002-6819.2021.03.017
16 张俊杰,徐双杰,张秀平,等.联合整地小麦智能施肥播种机研制与试验[J].农机化研究,2021,43(11):51-56. DOI:10.13427/j.cnki.njyi.2021.11.010
ZHANG J J, XU S J, ZHANG X P, et al. Development and test of intelligent fertilizing seeder for wheat combining with soil preparation[J]. Journal of Agricultural Mechanization Research, 2021, 43(11): 51-56. (in Chinese with English abstract)
doi: 10.13427/j.cnki.njyi.2021.11.010
17 马瑞峻, MICHAEL S, CRAIG L,等.多土壤信息测量传感器的硬件系统集成设计[J].农业工程学报,2010,26(4):156-161. DOI:10.3969/j.issn.1002-6819.2010.04.026
MA R J, MICHAEL S, CRAIG L, et al. Integrated multi-sensor hardware system for soil information measurement[J]. Transactions of the CSAE, 2010, 26(4): 156-161. (in English)
doi: 10.3969/j.issn.1002-6819.2010.04.026
18 张东兴,刘江,杨丽,等.基于VIS-NIR的播种沟内土壤水分测量传感器研究[J].农业机械学报,2021,52(2):218-226. DOI:10.6041/j.issn.1000-1298.2021.02.020
ZHANG D X, LIU J, YANG L, et al. Soil moisture measure-ment sensor research in seeding ditch based on VIS-NIR[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(2): 218-226. (in Chinese with English abstract)
doi: 10.6041/j.issn.1000-1298.2021.02.020
19 岑海燕,朱月明,孙大伟,等.深度学习在植物表型研究中的应用现状与展望[J].农业工程学报,2020,36(9):1-16. DOI:10.11975/j.issn.1002-6819.2020.09.001
CEN H Y, ZHU Y M, SUN D W, et al. Current status and future perspective of the application of deep learning in plant phenotype research[J]. Transactions of the CSAE, 2020, 36(9): 1-16. (in Chinese with English abstract)
doi: 10.11975/j.issn.1002-6819.2020.09.001
20 张漫,季宇寒,李世超,等.农业机械导航技术研究进展[J].农业机械学报,2020,51(4):1-18. DOI:10.6041/j.issn.1000-1298.2020.04.001
ZHANG M, JI Y H, LI S C, al el. Research progress of agricultural machinery navigation technology[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(4): 1-18. (in Chinese with English abstract)
doi: 10.6041/j.issn.1000-1298.2020.04.001
21 李少朋,张涛.深度学习在视觉SLAM中应用综述[J].空间控制技术与应用,2019,45(2):1-10. DOI:10.3969/j.issn.1674-1579.2019.02.001
LI S P, ZHANG T. A survey of deep learning application in visual SLAM[J]. Aerospace Control and Application, 2019, 45(2): 1-10. (in Chinese with English abstract)
doi: 10.3969/j.issn.1674-1579.2019.02.001
22 蒋啸虎,佟金,马云海,等.基于卡尔曼滤波融合算法的深松耕深检测装置研究[J].农业机械学报,2020,51(9):53-60. DOI:10.6041/j.issn.1000-1298.2020.09.007
JIANG X H, TONG J, MA Y H, et al. Study of tillage depth detecting device based on Kalman filter and fusion algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(9): 53-60. (in Chinese with English abstract)
doi: 10.6041/j.issn.1000-1298.2020.09.007
23 尉庆国,孟继祖.汽车发动机传感器的检测[J].机械管理开发,2005(2):28-29. DOI:10.3969/j.issn.1003-773X.2005.02.015
WEI Q G, MENG J Z. Measurement of automobile engine sensor[J]. Mechanical Management and Development, 2005(2): 28-29. (in Chinese with English abstract)
doi: 10.3969/j.issn.1003-773X.2005.02.015
24 陈学庚,温浩军,张伟荣,等.农业机械与信息技术融合发展现状与方向[J].智慧农业(中英文),2020,2(4):1-16. DOI:10.12133/j.smartag.2020.2.4.202002-SA003
CHEN X G, WEN H J, ZHANG W R, et al. Advances and progress of agricultural machinery and sensing technology fusion[J]. Smart Agriculture, 2020, 2(4): 1-16. (in Chinese with English abstract)
doi: 10.12133/j.smartag.2020.2.4.202002-SA003
25 陈鹏飞.无人机在农业中的应用现状与展望[J].浙江大学学报(农业与生命科学版),2018,44(4):399-406. DOI:10.3785/j.issn.1008-9209.2017.12.150
CHEN P F. Applications and trends of unmanned aerial vehicle in agriculture[J]. Journal of Zhejiang University (Agriculture & Life Sciences), 2018, 44(4): 399-406. (in Chinese with English abstract)
doi: 10.3785/j.issn.1008-9209.2017.12.150
26 王庆,车荧璞,柴宏红,等.基于无人机可见光与激光雷达的甜菜株高定量评估[J].农业机械学报,2021,52(3):178-184. DOI:10.6041/j.issn.1000-1298.2021.03.019
WANG Q, CHE Y P, CHAI H H, et al. Quantitative evaluation of sugar beet plant height based on UAV-RGB and UAV-LiDAR[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(3): 178-184. (in Chinese with English abstract)
doi: 10.6041/j.issn.1000-1298.2021.03.019
27 杨帅,陈俊英,周永财,等.无人机热红外遥感反演玉米根域土壤含水率方法研究[J].节水灌溉,2021(3):12-18. DOI:10.3969/j.issn.1007-4929.2021.03.003
YANG S, CHEN J Y, ZHOU Y C, et al. A study on the method of UAV thermal infrared remote sensing to retrieve soil moisture content in corn root zone[J]. Water Saving Irrigation, 2021(3): 12-18. (in Chinese with English abstract)
doi: 10.3969/j.issn.1007-4929.2021.03.003
28 田明璐,班松涛,袁涛,等.基于无人机平台的稻纵卷叶螟为害程度遥感监测[J].上海农业学报,2020,36(6):132-137. DOI:10.15955/j.issn1000-3924.2020.06.24
TIAN M L, BAN S T, YUAN T, et al. Monitoring of rice damage by rice leaf roller using UAV-based remote sensing[J]. Acta Agriculturae Shanghai, 2020, 36(6): 132-137. (in Chinese with English abstract)
doi: 10.15955/j.issn1000-3924.2020.06.24
29 李强.基于无人机影像技术的小麦长势遥感监测[J].农机化研究,2022,44(5):193-197. DOI:10.13427/j.cnki.njyi.2022.05.035
LI Q. Remote sensing monitoring of wheat growth based on UAV image technology[J]. Journal of Agricultural Mechaniza-tion Research, 2022, 44(5): 193-197. (in Chinese with English abstract)
doi: 10.13427/j.cnki.njyi.2022.05.035
30 段小斌.基于无人机遥感技术的水稻倒伏区域识别研究[J].农机化研究,2021,43(12):225-228. DOI:10.13427/j.cnki.njyi.2021.12.039
DUAN X B. Study of rice lodging areas identification based on UAV remote sensing technology[J]. Journal of Agricultural Mechanization Research, 2021, 43(12): 225-228. (in Chinese with English abstract)
doi: 10.13427/j.cnki.njyi.2021.12.039
31 吴刚,彭要奇,周广奇,等.基于多光谱成像和卷积神经网络的玉米作物营养状况识别方法研究[J].智慧农业(中英文),2020,2(1):111-120. DOI:10.12133/j.smartag.2020.2.1.202001-SA001
WU G, PENG Y Q, ZHOU G Q, et al. Recognition method for corn nutrient based on multispectral image and convolu-tional neural network[J]. Smart Agriculture, 2020, 2(1): 111-120. (in Chinese with English abstract)
doi: 10.12133/j.smartag.2020.2.1.202001-SA001
32 曹峰.基于多源数据的油菜病害快速诊断方法与物联网监测系统[D].浙江,杭州:浙江大学,2019.
CAO F. Rapid diagnostic method of oilseed rape of diseases and IoT monitoring system based on multi-source data[D]. Hangzhou, Zhejiang: Zhejiang University, 2019. (in Chinese with English abstract)
33 高铭阳,张锦水,潘耀忠,等.结合植被指数与作物高度反演冬小麦叶面积指数[J].中国农业资源与区划,2020,41(8):49-57. DOI:10.7621/cjarrp.1005-9121.20200806
GAO M Y, ZHANG J S, PAN Y Z, et al. Retrieval of winter wheat leaf area index based on vegetation index and crop height[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2020, 41(8): 49-57. (in Chinese with English abstract)
doi: 10.7621/cjarrp.1005-9121.20200806
34 黄愉淇.基于无人机遥感技术的作物面积提取研究[D].湖南,长沙:湖南农业大学,2018.
HUANG Y Q. Study on crop area extraction using remote sensing technology based on unmanned aerial vehicle[D]. Changsha, Hunan: Hunan Agricultural University, 2018. (in Chinese with English abstract)
35 吴晗.基于时序可见光无人机遥感影像的水稻估产研究[D].湖北,武汉:武汉大学,2019.
WU H. Rice yield estimation based on time-series visible unmanned aerial vehicle remote sensing images[D]. Wuhan, Hubei: Wuhan University, 2019. (in Chinese with English abstract)
36 陆国政,李长春,杨贵军,等.基于无人机搭载数码相机的小麦育种表型信息解析[J].中国种业,2016(8):60-63. DOI:10.19462/j.cnki.1671-895x.2016.08.029
LU G Z, LI C C, YANG G J, et al. Analysis of wheat breeding phenotypic information based on UAV-mounted digital camera[J]. China Seed Industry, 2016(8): 60-63. (in Chinese)
doi: 10.19462/j.cnki.1671-895x.2016.08.029
37 WATANBE K, GUO W, ARAI K, et al. High-throughput phenotyping of sorghum plant height using an unmanned aerial vehicle and its application to genomic prediction modeling[J]. Frontiers in Plant Science, 2017, 8: 421. DOI:10.3389/fpls.2017.00421
doi: 10.3389/fpls.2017.00421
38 秦占飞,常庆瑞,谢宝妮,等.基于无人机高光谱影像的引黄灌区水稻叶片全氮含量估测[J].农业工程学报,2016,32(23):77-85. DOI:10.11975/j.issn.1002-6819.2016.23.011
QIN Z F, CHANG Q R, XIE B N, et al. Rice leaf nitrogen content estimation based on hyperspectral imagery of UAV in Yellow River diversion irrigation district[J]. Transactions of the CSAE, 2016, 32(23): 77-85. (in Chinese with English abstract)
doi: 10.11975/j.issn.1002-6819.2016.23.011
39 朱婉雪,李仕冀,张旭博,等.基于无人机遥感植被指数优选的田块尺度冬小麦估产[J].农业工程学报,2018,34(11):78-86. DOI:10.11975/j.issn.1002-6819.2018.11.010
ZHU W X, LI S J, ZHANG X B, et al. Estimation of winter wheat yield using optimal vegetation indices from unmanned aerial vehicle remote sensing[J]. Transactions of the CSAE, 2018, 34(11): 78-86. (in Chinese with English abstract)
doi: 10.11975/j.issn.1002-6819.2018.11.010
40 王俊丽,任世奇,张忠华,等.基于文献计量评价的无人机生态遥感监测研究进展[J].热带地理,2019,39(4):616-624. DOI:10.13284/j.cnki.rddl.003157
WANG J L, REN S Q, ZHANG Z H, et al. Research progress on unmanned aerial vehicle for ecological remote sensing monitoring based on bibliometric assessment[J]. Tropical Geography, 2019, 39(4): 616-624. (in Chinese with English abstract)
doi: 10.13284/j.cnki.rddl.003157
41 FAROOQ M S, RIAZ S, ABID A, et al. A survey on the role of IoT in agriculture for the implementation of smart farming[J]. IEEE Access, 2019, 7: 156237-156271. DOI: 10.1109/ACCESS.2019.2949703
doi: 10.1109/ACCESS.2019.2949703
42 李瑾,郭美荣,高亮亮.农业物联网技术应用及创新发展策略[J].农业工程学报,2015,31():200-209. DOI:10.11975/j.issn.1002-6819.2015.z2.031
LI J, GUO M R, GAO L L. Application and innovation strategy of agricultural internet of things[J]. Transactions of the CSAE, 2015, 31(): 200-209. (in Chinese with English abstract)
doi: 10.11975/j.issn.1002-6819.2015.z2.031
43 朱超.基于物联网的温室大棚远程环境监测系统[D].江苏,南京:南京信息工程大学,2019.
ZHU C. Greenhouse remote environment monitoring system based on IoT[D]. Nanjing, Jiangsu: Nanjing University of Information Science and Technology, 2019. (in Chinese with English abstract)
44 刘义飞.基于LabVIEW的温室番茄雾培控制系统研究[D].北京:中国农业科学院,2014.
LIU Y F. Aeroponics control system for tomato cultivation in greenhouse based on LabVIEW[D]. Beijing: Chinese Academy of Agricultural Sciences, 2014. (in Chinese with English abstract)
45 隋学艳,李少昆,张晓冬,等.棉花叶片厚度的高光谱测试方法[J].农业工程学报,2010,26(1):262-266. DOI:10.3969/j.issn.1002-6819.2010.01.046
SUI X Y, LI S K, ZHANG X D, et al. Measurement of cotton leaf thickness with hyper spectrum[J]. Transactions of the CSAE, 2010, 26(1): 262-266. (in Chinese with English abstract)
doi: 10.3969/j.issn.1002-6819.2010.01.046
46 王震.基于图像识别和GPRS网络技术的植物生长速率检测系统的研究[D].山东,泰安:山东农业大学,2011.
WANG Z. Research on growing rate detecting system for plant based on image recognition and GPRS network technology[D]. Tai’an, Shandong: Shandong Agricultural University, 2011. (in Chinese with English abstract)
47 柳月强.基于多传感器数据融合的奶山羊行为分类研究[D].陕西,杨凌:西北农林科技大学,2020.
LIU Y Q. Research of dairy goat behavior classification based on multi-sensor data[D].Yangling, Shaanxi: Northwest A&F University, 2020. (in Chinese with English abstract)
48 姜美曦.基于姿态传感器的肉牛行为特征识别研究[D].辽宁,沈阳:沈阳农业大学,2017.
JIANG M X. Recognition of behavioral characteristics of beef cattle based on posture sensor[D]. Shenyang, Liaoning: Shenyang Agricultural University, 2017. (in Chinese with English abstract)
49 SRBINOVSKA M, GAVROVSKI C, DIMCEV V, et al. Environmental parameters monitoring in precision agriculture using wireless sensor networks[J]. Journal of Cleaner Produc-tion, 2015, 88: 297-307. DOI: 10.1016/j.jclepro.2014.04.036
doi: 10.1016/j.jclepro.2014.04.036
50 葛文杰,赵春江.农业物联网研究与应用现状及发展对策研究[J].农业机械学报,2014,45(7):222-230, 277. DOI:10.6041/j.issn.1000-1298.2014.07.035
GE W J, ZHAO C J. State-of-the-art and developing stra-tegies of agricultural internet of things[J]. Transactions of the Chinese Society for Agricultural Machinery, 2014, 45(7): 222-230, 277. (in Chinese with English abstract)
doi: 10.6041/j.issn.1000-1298.2014.07.035
51 蓝玲怡.植物水分信息原位无损感知方法及其自供电柔性可穿戴器件研究[D].浙江,杭州:浙江大学,2021.
LAN L Y. In-situ and non-destructive sensing of plant water information based on self-powered flexible and wearable devices[D]. Hangzhou, Zhejiang: Zhejiang University, 2021. (in Chinese with English abstract)
52 肖文敏,唐小燕,任志红,等.基于电子鼻技术的茶鲜叶农残快速诊断[J].茶叶通讯,2021,48(3):484-493. DOI:10.3969/j.issn.1009-525X.2021.03.016
XIAO W M, TANG X Y, REN Z H, et al. Rapid diagnosis of pesticide residues in fresh tea leaves based on electronic nose technology[J]. Journal of Tea Communication, 2021, 48(3): 484-493. (in Chinese with English abstract)
doi: 10.3969/j.issn.1009-525X.2021.03.016
53 何莲,易宇文,彭毅秦,等.基于电子鼻和气质联用分析不同生长期茂县花椒叶挥发性风味物质[J].南方农业学报,2019,50(3):641-648. DOI:10.3969/j.issn.20951191.2019.03.28
HE L, YI Y W, PENG Y Q, et al. Analysis of the volatile flavor substances of Chinese prickly ash leaf in different growth stages based on E-nose and gas chromatography-mass spectrometry[J]. Journal of Southern Agriculture, 2019, 50(3): 641-648. (in Chinese with English abstract)
doi: 10.3969/j.issn.20951191.2019.03.28
54 邹秋菊.微型生物传感器及其在转基因植物生理实时监测中的应用研究[D].湖北,武汉:华中科技大学,2007.
ZOU Q J. Microbiosensor and its application on the transgenic plant physiological process in real time[D]. Wuhan, Hubei: Huazhong University of Science and Technology, 2007. (in Chinese with English abstract)
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