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lessons learnt[J/OL]. Sensors (Basel,Switzerland),2016,16 silience of agriculture production systems[J].Current opinion in
(11):1884[2023-03-01].https://doi.org/10.3390/s1611188.4. biotechnology,2021,70:15-22.
[6] 李道亮 .物联网与智慧农业[J].农业工程,2012,2(1):1-7.LI D [18] 周济,陈佳玮,沈利言,等 . 人工智能——推动植物研究发展的
L.Internet of Things and wisdom agriculture[J].Agricultural engi‐ 新动力[J]. 南京农业大学学报,2022,45(5):1060-1071. ZOU
neering,2012,2(1):1-7 (in Chinese with English abstract). J, CHEN J W, SHEN L Y, et al. Artificial intelligence: ad‐
[7] 赵春江.智慧农业的发展现状与未来展望[J].华南农业大学学报, vancing plant research beyond the state of the art[J]. Journal of
2021,42(6):1-7.ZHAO C J.Development status and future pros‐ Nanjing Agricultural University, 2022,45(5):1060-1071 (in
pect of smart agriculture[J]. Journal of South China Agricultural Chinese with English abstract).
University,2021,42(6):1-7 (in Chinese with English abstract). [19] JANIESCH C,ZSCHECH P,HEINRICH K.Machine learning
[8] 罗锡文,廖娟,胡炼,等 . 我国智能农机的研究进展与无人农场 and deep learning[J].Electronic markets,2021,31(3):685-695.
的实践[J]. 华南农业大学学报,2021,42(6):8-17,5.LUO X [20] LECUN Y,BENGIO Y,HINTON G.Deep learning[J].Nature,
W,LIAO J,HU L,et al.Research progress of intelligent agricul‐ 2015,521(7553):436-444.
tural machinery and practice of unmanned farm in China[J].Jour‐ [21] 李道亮,杨昊 . 农业物联网技术研究进展与发展趋势分析[J].
nal of South China Agricultural University,2021,42(6)8-17,5 农业机械学报,2018,49(1):1-20. LI D L, YANG H. State-of-
(in Chinese with English abstract). the-art review for internet of things in agriculture[J]. Transac‐
[9] 胡静涛,高雷,白晓平,等.农业机械自动导航技术研究进展[J]. tions of the Chinese society for agricultural machinery, 2018,49
农业工程学报,2015,31(10):1-10.HU J T,GAO L,BAI X P, (1):1-20 (in Chinese with English abstract).
et al.Review of research on automatic guidance of agricultural ve‐ [22] 张学工,江瑞,汪小我,等 .从生物大数据到知识大发现:10年进
hicles[J]. Transactions of the CSAE,2015,31(10):1-10 (in 展 与 未 来 展 望[J]. 科 学 通 报 ,2016,61(36):3869-3877.
Chinese with English abstract). ZHANG X G,JIANG R,WANG X W,et al.From big biological
[10] YANG W N,FENG H,ZHANG X H,et al. Crop phenomics data to big discovery:the past decade and the future[J].Chinese
and high-throughput phenotyping:past decades,current challeng‐ science bulletin,2016,61(36):3869-3877 (in Chinese with
es,and future perspectives[J]. Molecular plant,2020,13(2): English abstract).
187-214. [23] LI D L,QUAN C Q,SONG Z Y,et al.High-throughput plant
[11] 邱均平 . 文献计量学的定义及其研究对象[J]. 中国图书馆学 phenotyping platform (HT3P) as a novel tool for estimating ag‐
报,1986,12(2):71.QIU J P.Definition of bibliometrics and its ronomic traits from the lab to the field[J/OL].Frontiers in bioen‐
research object[J].Journal of library science in China,1986,12 gineering and biotechnology,2021,8:623705[2023-03-01].
(2):71(in Chinese). https://doi.org/10.3389/fbioe.2020.623705.
[12] 任妮,郭婷,孙艺伟,等 . 全球智慧农业领域研究态势分析[J]. [24] ZANDER M,LEWSEY M G,CLARK N M,et al. Integrated
农业图书情报学报,2021(9):48-63.REN N,GUO T,SUN Y multi-omics framework of the plant response to jasmonic acid[J].
W,et al.An analysis of global smart agriculture research situation Nature plants,2020,6(3):290-302.
[J].Journal of library and information science in agriculture,2021 [25] GUI S T,YANG L F,LI J B,et al.ZEAMAP,a comprehensive
(9):48-63 (in Chinese with English abstract). database adapted to the maize multi-omics era[J/OL].iScience,
[13] 杨道邦,林婕虹,邓杰,等 .基于 CiteSpace 的国内外智慧农业研 2020,23(6):101241[2022-03-01].https://doi.org/10.1016/j.
究进展[J]. 广东农业科学,2021,48(4):140-150.YANG D B, isci.2020.101241.
LIN J H,DENG J,et al.Research progress of smart agriculture [26] MEUWISSEN T H E,HAYES B J,GODDARD M E.Predic‐
based on CiteSpace at home and abroad[J].Guangdong agricul‐ tion of total genetic value using genome-wide dense marker maps
tural sciences,2021,48(4):140-150(in Chinese with English [J].Genetics,2001,157(4):1819-1829.
abstract). [27] LORENZANA R E,BERNARDO R.Accuracy of genotypic val‐
[14] 洪帅,王天尊,符晓艺 .中国智慧农业研究演进脉络梳理及前沿 ue predictions for marker-based selection in biparental plant pop‐
趋势分析[J]. 江苏农业科学,2023,51(4):28-38.HONG S, ulations[J]. Theoretical and applied genetics,2009,120(1):
WANG T Z,FU X Y.Research evolution and frontier trend anal‐ 151-161.
ysis of smart agriculture in China[J].Jiangsu agricultural scienc‐ [28] MCGOWAN M, WANG J, DONG H, et al. Ideas in genomic
es,2023,51(4):28-38(in Chinese). selection with the potential to transform plant molecula breed‐
[15] WEISS M,JACOB F,DUVEILLER G.Remote sensing for ag‐ ing: a review[J]. Plant breeding reviews, 2021,45: 273-319.
ricultural applications:a meta-review[J/OL].Remote sensing of [29] XU Y B,LIU X G,FU J J,et al.Enhancing genetic gain through
environment,2020,236:111402[2023-03-01].https://doi.org/ genomic selection:from livestock to plants[J /OL]. Plant com‐
10.1016/j.rse.2019.111402. munications,2020,1(1):100005[2023-03-01].https://doi.org/
[16] BOURSIANIS A D,PAPADOPOULOU M S,DIAMAN‐ 10.1016/j.xplc.2019.100005.
TOULAKIS P,et al.Internet of Things (IoT) and agricultural [30] 张颖,廖生进,王璟璐等 .信息技术与智能装备助力智能设计育
unmanned aerial vehicles (UAVs) in smart farming:a compre‐ 种[J]. 吉林农业大学学报,2021,43(2):119-129. ZHANG Y,
hensive review[J/OL]. Internet of Things,2022,18:100187 LIAO S J, WANG J L, et al. Information technology and intelli‐
[2023-03-01].https://doi.org/10.1016/j.iot.2020.100187. gent equipment facilitating smart breeding[J]. Journal of Jilin Ag‐
[17] JUNG J,MAEDA M,CHANG A J,et al.The potential of re‐ ricultural University, 2021,43(2):119-129 (in Chinese with
mote sensing and artificial intelligence as tools to improve the re‐ English abstract).

