An Efficient Computer Vision-Based Dual-Face Target Precision Variable Spraying Robotic System for Foliar Fertilisers Article Swipe
Chengtian Zhu
,
Shuaihua Hao
,
Cailing Liu
,
Yuewei Wang
,
Xuan Jia
,
Jitong Xu
,
Shuxiang Guo
,
Jie Huo
,
Weiming Wang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/agronomy14122770
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/agronomy14122770
The application of foliar fertiliser can rapidly replenish the essential nutrients required by crops. In order to enhance the precision of foliar fertiliser spraying, fertiliser utilisation, and leaf absorption efficiency, this study proposes the implementation of an efficient foliar fertiliser dual-face target precision variable spraying robot system based on computer vision. In this study, we propose the SN-YOLOX Nano-ECA as a real-time classification model for potted plants. The model has parameters and FLOPs of only 0.48 M and 0.16 G, respectively. Following deployment, the classification precision and recall reached 97.86% and 98.52%, respectively, with an FPS of 37.6. A dual-face target precision variable spraying method of foliar fertiliser based on the determination of leaf area and plant height information of potted plants was proposed. A robot platform for the application of foliar fertilisers was developed, and a positioning and navigation system based on the RSSI principle was constructed. The results of the foliar fertiliser spraying experiments demonstrate that the precision of the extracted leaf area and height information is above 97% and 96%, respectively. The navigation system demonstrated distance and angle errors of only 5.598 cm and 0.2245°. The mean discrepancy between the actual and set spraying volumes was 0.46 mL. This robotic system is capable of precise spraying of foliar fertiliser, which provides a new idea and reference for the development of efficient and precise variable spraying technology for foliar fertiliser.
Related Topics
Concepts
Precision agriculture
Computer vision
Dual (grammatical number)
Artificial intelligence
Face (sociological concept)
Variable (mathematics)
Machine vision
Computer science
Agricultural engineering
Environmental science
Mathematics
Agriculture
Engineering
Geography
Mathematical analysis
Archaeology
Art
Sociology
Social science
Literature
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/agronomy14122770
- OA Status
- gold
- Cited By
- 17
- References
- 56
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404615570
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4404615570Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/agronomy14122770Digital Object Identifier
- Title
-
An Efficient Computer Vision-Based Dual-Face Target Precision Variable Spraying Robotic System for Foliar FertilisersWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-22Full publication date if available
- Authors
-
Chengtian Zhu, Shuaihua Hao, Cailing Liu, Yuewei Wang, Xuan Jia, Jitong Xu, Shuxiang Guo, Jie Huo, Weiming WangList of authors in order
- Landing page
-
https://doi.org/10.3390/agronomy14122770Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.3390/agronomy14122770Direct OA link when available
- Concepts
-
Precision agriculture, Computer vision, Dual (grammatical number), Artificial intelligence, Face (sociological concept), Variable (mathematics), Machine vision, Computer science, Agricultural engineering, Environmental science, Mathematics, Agriculture, Engineering, Geography, Mathematical analysis, Archaeology, Art, Sociology, Social science, LiteratureTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
17Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 17Per-year citation counts (last 5 years)
- References (count)
-
56Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4404615570 |
|---|---|
| doi | https://doi.org/10.3390/agronomy14122770 |
| ids.doi | https://doi.org/10.3390/agronomy14122770 |
| ids.openalex | https://openalex.org/W4404615570 |
| fwci | 13.29483431 |
| type | article |
| title | An Efficient Computer Vision-Based Dual-Face Target Precision Variable Spraying Robotic System for Foliar Fertilisers |
| awards[0].id | https://openalex.org/G3297890246 |
| awards[0].funder_id | https://openalex.org/F4320321001 |
| awards[0].display_name | |
| awards[0].funder_award_id | 52175261 |
| awards[0].funder_display_name | National Natural Science Foundation of China |
| biblio.issue | 12 |
| biblio.volume | 14 |
| biblio.last_page | 2770 |
| biblio.first_page | 2770 |
| topics[0].id | https://openalex.org/T10616 |
| topics[0].field.id | https://openalex.org/fields/11 |
| topics[0].field.display_name | Agricultural and Biological Sciences |
| topics[0].score | 0.9983000159263611 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1110 |
| topics[0].subfield.display_name | Plant Science |
| topics[0].display_name | Smart Agriculture and AI |
| topics[1].id | https://openalex.org/T11164 |
| topics[1].field.id | https://openalex.org/fields/23 |
| topics[1].field.display_name | Environmental Science |
| topics[1].score | 0.9840999841690063 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2305 |
| topics[1].subfield.display_name | Environmental Engineering |
| topics[1].display_name | Remote Sensing and LiDAR Applications |
| topics[2].id | https://openalex.org/T12707 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9664000272750854 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2214 |
| topics[2].subfield.display_name | Media Technology |
| topics[2].display_name | Vehicle License Plate Recognition |
| funders[0].id | https://openalex.org/F4320321001 |
| funders[0].ror | https://ror.org/01h0zpd94 |
| funders[0].display_name | National Natural Science Foundation of China |
| is_xpac | False |
| apc_list.value | 2000 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2165 |
| apc_paid.value | 2000 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2165 |
| concepts[0].id | https://openalex.org/C120217122 |
| concepts[0].level | 3 |
| concepts[0].score | 0.6182137727737427 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q740083 |
| concepts[0].display_name | Precision agriculture |
| concepts[1].id | https://openalex.org/C31972630 |
| concepts[1].level | 1 |
| concepts[1].score | 0.5871721506118774 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[1].display_name | Computer vision |
| concepts[2].id | https://openalex.org/C2780980858 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5808513164520264 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q110022 |
| concepts[2].display_name | Dual (grammatical number) |
| concepts[3].id | https://openalex.org/C154945302 |
| concepts[3].level | 1 |
| concepts[3].score | 0.5611206293106079 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[3].display_name | Artificial intelligence |
| concepts[4].id | https://openalex.org/C2779304628 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4970076382160187 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q3503480 |
| concepts[4].display_name | Face (sociological concept) |
| concepts[5].id | https://openalex.org/C182365436 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4794794023036957 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q50701 |
| concepts[5].display_name | Variable (mathematics) |
| concepts[6].id | https://openalex.org/C5339829 |
| concepts[6].level | 2 |
| concepts[6].score | 0.449089914560318 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1425977 |
| concepts[6].display_name | Machine vision |
| concepts[7].id | https://openalex.org/C41008148 |
| concepts[7].level | 0 |
| concepts[7].score | 0.4482041001319885 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[7].display_name | Computer science |
| concepts[8].id | https://openalex.org/C88463610 |
| concepts[8].level | 1 |
| concepts[8].score | 0.4307126998901367 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q194118 |
| concepts[8].display_name | Agricultural engineering |
| concepts[9].id | https://openalex.org/C39432304 |
| concepts[9].level | 0 |
| concepts[9].score | 0.38669854402542114 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q188847 |
| concepts[9].display_name | Environmental science |
| concepts[10].id | https://openalex.org/C33923547 |
| concepts[10].level | 0 |
| concepts[10].score | 0.25301581621170044 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[10].display_name | Mathematics |
| concepts[11].id | https://openalex.org/C118518473 |
| concepts[11].level | 2 |
| concepts[11].score | 0.2054138481616974 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11451 |
| concepts[11].display_name | Agriculture |
| concepts[12].id | https://openalex.org/C127413603 |
| concepts[12].level | 0 |
| concepts[12].score | 0.1987071931362152 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[12].display_name | Engineering |
| concepts[13].id | https://openalex.org/C205649164 |
| concepts[13].level | 0 |
| concepts[13].score | 0.17256107926368713 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q1071 |
| concepts[13].display_name | Geography |
| concepts[14].id | https://openalex.org/C134306372 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7754 |
| concepts[14].display_name | Mathematical analysis |
| concepts[15].id | https://openalex.org/C166957645 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q23498 |
| concepts[15].display_name | Archaeology |
| concepts[16].id | https://openalex.org/C142362112 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q735 |
| concepts[16].display_name | Art |
| concepts[17].id | https://openalex.org/C144024400 |
| concepts[17].level | 0 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q21201 |
| concepts[17].display_name | Sociology |
| concepts[18].id | https://openalex.org/C36289849 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q34749 |
| concepts[18].display_name | Social science |
| concepts[19].id | https://openalex.org/C124952713 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q8242 |
| concepts[19].display_name | Literature |
| keywords[0].id | https://openalex.org/keywords/precision-agriculture |
| keywords[0].score | 0.6182137727737427 |
| keywords[0].display_name | Precision agriculture |
| keywords[1].id | https://openalex.org/keywords/computer-vision |
| keywords[1].score | 0.5871721506118774 |
| keywords[1].display_name | Computer vision |
| keywords[2].id | https://openalex.org/keywords/dual |
| keywords[2].score | 0.5808513164520264 |
| keywords[2].display_name | Dual (grammatical number) |
| keywords[3].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[3].score | 0.5611206293106079 |
| keywords[3].display_name | Artificial intelligence |
| keywords[4].id | https://openalex.org/keywords/face |
| keywords[4].score | 0.4970076382160187 |
| keywords[4].display_name | Face (sociological concept) |
| keywords[5].id | https://openalex.org/keywords/variable |
| keywords[5].score | 0.4794794023036957 |
| keywords[5].display_name | Variable (mathematics) |
| keywords[6].id | https://openalex.org/keywords/machine-vision |
| keywords[6].score | 0.449089914560318 |
| keywords[6].display_name | Machine vision |
| keywords[7].id | https://openalex.org/keywords/computer-science |
| keywords[7].score | 0.4482041001319885 |
| keywords[7].display_name | Computer science |
| keywords[8].id | https://openalex.org/keywords/agricultural-engineering |
| keywords[8].score | 0.4307126998901367 |
| keywords[8].display_name | Agricultural engineering |
| keywords[9].id | https://openalex.org/keywords/environmental-science |
| keywords[9].score | 0.38669854402542114 |
| keywords[9].display_name | Environmental science |
| keywords[10].id | https://openalex.org/keywords/mathematics |
| keywords[10].score | 0.25301581621170044 |
| keywords[10].display_name | Mathematics |
| keywords[11].id | https://openalex.org/keywords/agriculture |
| keywords[11].score | 0.2054138481616974 |
| keywords[11].display_name | Agriculture |
| keywords[12].id | https://openalex.org/keywords/engineering |
| keywords[12].score | 0.1987071931362152 |
| keywords[12].display_name | Engineering |
| keywords[13].id | https://openalex.org/keywords/geography |
| keywords[13].score | 0.17256107926368713 |
| keywords[13].display_name | Geography |
| language | en |
| locations[0].id | doi:10.3390/agronomy14122770 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2738977497 |
| locations[0].source.issn | 2073-4395 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2073-4395 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Agronomy |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Agronomy |
| locations[0].landing_page_url | https://doi.org/10.3390/agronomy14122770 |
| locations[1].id | pmh:oai:doaj.org/article:cf90937618534638b3ff9ad505f6eb30 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Agronomy, Vol 14, Iss 12, p 2770 (2024) |
| locations[1].landing_page_url | https://doaj.org/article/cf90937618534638b3ff9ad505f6eb30 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5091092781 |
| authorships[0].author.orcid | https://orcid.org/0009-0006-2801-3657 |
| authorships[0].author.display_name | Chengtian Zhu |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[0].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[0].institutions[0].id | https://openalex.org/I52158045 |
| authorships[0].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | China Agricultural University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Chengtian Zhu |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[1].author.id | https://openalex.org/A5086491467 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-2872-6770 |
| authorships[1].author.display_name | Shuaihua Hao |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[1].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[1].institutions[0].id | https://openalex.org/I52158045 |
| authorships[1].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | China Agricultural University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Shuaihua Hao |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[2].author.id | https://openalex.org/A5073474619 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-9190-4117 |
| authorships[2].author.display_name | Cailing Liu |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[2].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[2].institutions[0].id | https://openalex.org/I52158045 |
| authorships[2].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | China Agricultural University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Cailing Liu |
| authorships[2].is_corresponding | True |
| authorships[2].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[3].author.id | https://openalex.org/A5067219624 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-6740-8954 |
| authorships[3].author.display_name | Yuewei Wang |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[3].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[3].institutions[0].id | https://openalex.org/I52158045 |
| authorships[3].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | China Agricultural University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Yuewei Wang |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[4].author.id | https://openalex.org/A5072948004 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Xuan Jia |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[4].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[4].institutions[0].id | https://openalex.org/I52158045 |
| authorships[4].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | China Agricultural University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Xuan Jia |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[5].author.id | https://openalex.org/A5038009323 |
| authorships[5].author.orcid | https://orcid.org/0009-0001-0451-1129 |
| authorships[5].author.display_name | Jitong Xu |
| authorships[5].countries | CN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[5].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[5].institutions[0].id | https://openalex.org/I52158045 |
| authorships[5].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[5].institutions[0].country_code | CN |
| authorships[5].institutions[0].display_name | China Agricultural University |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Jitong Xu |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[6].author.id | https://openalex.org/A5100611041 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-0607-9798 |
| authorships[6].author.display_name | Shuxiang Guo |
| authorships[6].countries | CN |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[6].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[6].institutions[0].id | https://openalex.org/I52158045 |
| authorships[6].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[6].institutions[0].country_code | CN |
| authorships[6].institutions[0].display_name | China Agricultural University |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Songbao Guo |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[7].author.id | https://openalex.org/A5079280268 |
| authorships[7].author.orcid | https://orcid.org/0000-0001-6171-4654 |
| authorships[7].author.display_name | Jie Huo |
| authorships[7].countries | CN |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I52158045 |
| authorships[7].affiliations[0].raw_affiliation_string | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[7].institutions[0].id | https://openalex.org/I52158045 |
| authorships[7].institutions[0].ror | https://ror.org/04v3ywz14 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I52158045 |
| authorships[7].institutions[0].country_code | CN |
| authorships[7].institutions[0].display_name | China Agricultural University |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Juxin Huo |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | College of Engineering, China Agricultural University, Beijing 100083, China |
| authorships[8].author.id | https://openalex.org/A5113291172 |
| authorships[8].author.orcid | |
| authorships[8].author.display_name | Weiming Wang |
| authorships[8].countries | CN |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I115592961 |
| authorships[8].affiliations[0].raw_affiliation_string | School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China |
| authorships[8].institutions[0].id | https://openalex.org/I115592961 |
| authorships[8].institutions[0].ror | https://ror.org/03jc41j30 |
| authorships[8].institutions[0].type | education |
| authorships[8].institutions[0].lineage | https://openalex.org/I115592961 |
| authorships[8].institutions[0].country_code | CN |
| authorships[8].institutions[0].display_name | Jiangsu University |
| authorships[8].author_position | last |
| authorships[8].raw_author_name | Weiming Wang |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.3390/agronomy14122770 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | An Efficient Computer Vision-Based Dual-Face Target Precision Variable Spraying Robotic System for Foliar Fertilisers |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10616 |
| primary_topic.field.id | https://openalex.org/fields/11 |
| primary_topic.field.display_name | Agricultural and Biological Sciences |
| primary_topic.score | 0.9983000159263611 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1110 |
| primary_topic.subfield.display_name | Plant Science |
| primary_topic.display_name | Smart Agriculture and AI |
| related_works | https://openalex.org/W2382920002, https://openalex.org/W2390141787, https://openalex.org/W2384046104, https://openalex.org/W1551473783, https://openalex.org/W2912977869, https://openalex.org/W2170509036, https://openalex.org/W3195856620, https://openalex.org/W2622264455, https://openalex.org/W3209610942, https://openalex.org/W2995581643 |
| cited_by_count | 17 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 17 |
| locations_count | 2 |
| best_oa_location.id | doi:10.3390/agronomy14122770 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2738977497 |
| best_oa_location.source.issn | 2073-4395 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2073-4395 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Agronomy |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Agronomy |
| best_oa_location.landing_page_url | https://doi.org/10.3390/agronomy14122770 |
| primary_location.id | doi:10.3390/agronomy14122770 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2738977497 |
| primary_location.source.issn | 2073-4395 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2073-4395 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Agronomy |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Agronomy |
| primary_location.landing_page_url | https://doi.org/10.3390/agronomy14122770 |
| publication_date | 2024-11-22 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W4400247939, https://openalex.org/W4294983343, https://openalex.org/W4402847860, https://openalex.org/W4310043920, https://openalex.org/W4210871632, https://openalex.org/W4400470392, https://openalex.org/W4321372004, https://openalex.org/W4378909144, https://openalex.org/W2002400888, https://openalex.org/W1982934546, https://openalex.org/W4285043374, https://openalex.org/W4317609244, https://openalex.org/W4389079931, https://openalex.org/W4282963788, https://openalex.org/W4317740367, https://openalex.org/W3014054611, https://openalex.org/W4377139754, https://openalex.org/W6851967781, https://openalex.org/W4394994789, https://openalex.org/W2934198733, https://openalex.org/W3180134609, https://openalex.org/W3042011474, https://openalex.org/W2531409750, https://openalex.org/W2109255472, https://openalex.org/W2883780447, https://openalex.org/W2982083293, https://openalex.org/W3035414587, https://openalex.org/W2752782242, https://openalex.org/W3034552520, https://openalex.org/W4320176361, https://openalex.org/W3021743810, https://openalex.org/W4319978454, https://openalex.org/W2090401855, https://openalex.org/W6692326907, https://openalex.org/W2964029185, https://openalex.org/W2194775991, https://openalex.org/W4402159185, https://openalex.org/W4392637973, https://openalex.org/W4402413015, https://openalex.org/W4387840039, https://openalex.org/W4402213857, https://openalex.org/W4402486584, https://openalex.org/W2989646980, https://openalex.org/W4389479194, https://openalex.org/W4390576998, https://openalex.org/W4400246995, https://openalex.org/W4380767730, https://openalex.org/W3206738484, https://openalex.org/W4402026277, https://openalex.org/W4312110972, https://openalex.org/W3030285646, https://openalex.org/W4392010565, https://openalex.org/W4393276637, https://openalex.org/W3106505022, https://openalex.org/W2259806077, https://openalex.org/W4367839311 |
| referenced_works_count | 56 |
| abstract_inverted_index.A | 98, 124 |
| abstract_inverted_index.M | 76 |
| abstract_inverted_index.a | 60, 136, 214 |
| abstract_inverted_index.G, | 79 |
| abstract_inverted_index.In | 14, 51 |
| abstract_inverted_index.an | 36, 94 |
| abstract_inverted_index.as | 59 |
| abstract_inverted_index.by | 12 |
| abstract_inverted_index.cm | 185 |
| abstract_inverted_index.is | 168, 204 |
| abstract_inverted_index.of | 2, 20, 35, 73, 96, 105, 112, 119, 130, 150, 160, 182, 206, 209, 222 |
| abstract_inverted_index.on | 48, 109, 142 |
| abstract_inverted_index.to | 16 |
| abstract_inverted_index.we | 54 |
| abstract_inverted_index.97% | 170 |
| abstract_inverted_index.FPS | 95 |
| abstract_inverted_index.The | 0, 67, 148, 174, 188 |
| abstract_inverted_index.and | 26, 71, 77, 86, 90, 115, 135, 138, 165, 171, 179, 186, 194, 217, 224 |
| abstract_inverted_index.can | 5 |
| abstract_inverted_index.for | 64, 127, 219, 229 |
| abstract_inverted_index.has | 69 |
| abstract_inverted_index.mL. | 200 |
| abstract_inverted_index.new | 215 |
| abstract_inverted_index.set | 195 |
| abstract_inverted_index.the | 8, 18, 33, 56, 83, 110, 128, 143, 151, 158, 161, 192, 220 |
| abstract_inverted_index.was | 122, 133, 146, 198 |
| abstract_inverted_index.0.16 | 78 |
| abstract_inverted_index.0.46 | 199 |
| abstract_inverted_index.0.48 | 75 |
| abstract_inverted_index.96%, | 172 |
| abstract_inverted_index.RSSI | 144 |
| abstract_inverted_index.This | 201 |
| abstract_inverted_index.area | 114, 164 |
| abstract_inverted_index.idea | 216 |
| abstract_inverted_index.leaf | 27, 113, 163 |
| abstract_inverted_index.mean | 189 |
| abstract_inverted_index.only | 74, 183 |
| abstract_inverted_index.that | 157 |
| abstract_inverted_index.this | 30, 52 |
| abstract_inverted_index.with | 93 |
| abstract_inverted_index.37.6. | 97 |
| abstract_inverted_index.5.598 | 184 |
| abstract_inverted_index.FLOPs | 72 |
| abstract_inverted_index.above | 169 |
| abstract_inverted_index.angle | 180 |
| abstract_inverted_index.based | 47, 108, 141 |
| abstract_inverted_index.model | 63, 68 |
| abstract_inverted_index.order | 15 |
| abstract_inverted_index.plant | 116 |
| abstract_inverted_index.robot | 45, 125 |
| abstract_inverted_index.study | 31 |
| abstract_inverted_index.which | 212 |
| abstract_inverted_index.97.86% | 89 |
| abstract_inverted_index.actual | 193 |
| abstract_inverted_index.crops. | 13 |
| abstract_inverted_index.errors | 181 |
| abstract_inverted_index.foliar | 3, 21, 38, 106, 131, 152, 210, 230 |
| abstract_inverted_index.height | 117, 166 |
| abstract_inverted_index.method | 104 |
| abstract_inverted_index.plants | 121 |
| abstract_inverted_index.potted | 65, 120 |
| abstract_inverted_index.recall | 87 |
| abstract_inverted_index.study, | 53 |
| abstract_inverted_index.system | 46, 140, 176, 203 |
| abstract_inverted_index.target | 41, 100 |
| abstract_inverted_index.98.52%, | 91 |
| abstract_inverted_index.between | 191 |
| abstract_inverted_index.capable | 205 |
| abstract_inverted_index.enhance | 17 |
| abstract_inverted_index.plants. | 66 |
| abstract_inverted_index.precise | 207, 225 |
| abstract_inverted_index.propose | 55 |
| abstract_inverted_index.rapidly | 6 |
| abstract_inverted_index.reached | 88 |
| abstract_inverted_index.results | 149 |
| abstract_inverted_index.robotic | 202 |
| abstract_inverted_index.vision. | 50 |
| abstract_inverted_index.volumes | 197 |
| abstract_inverted_index.Nano-ECA | 58 |
| abstract_inverted_index.SN-YOLOX | 57 |
| abstract_inverted_index.computer | 49 |
| abstract_inverted_index.distance | 178 |
| abstract_inverted_index.platform | 126 |
| abstract_inverted_index.proposes | 32 |
| abstract_inverted_index.provides | 213 |
| abstract_inverted_index.required | 11 |
| abstract_inverted_index.spraying | 44, 103, 154, 196, 208, 227 |
| abstract_inverted_index.variable | 43, 102, 226 |
| abstract_inverted_index.0.2245°. | 187 |
| abstract_inverted_index.Following | 81 |
| abstract_inverted_index.dual-face | 40, 99 |
| abstract_inverted_index.efficient | 37, 223 |
| abstract_inverted_index.essential | 9 |
| abstract_inverted_index.extracted | 162 |
| abstract_inverted_index.nutrients | 10 |
| abstract_inverted_index.precision | 19, 42, 85, 101, 159 |
| abstract_inverted_index.principle | 145 |
| abstract_inverted_index.proposed. | 123 |
| abstract_inverted_index.real-time | 61 |
| abstract_inverted_index.reference | 218 |
| abstract_inverted_index.replenish | 7 |
| abstract_inverted_index.spraying, | 23 |
| abstract_inverted_index.absorption | 28 |
| abstract_inverted_index.developed, | 134 |
| abstract_inverted_index.fertiliser | 4, 22, 24, 39, 107, 153 |
| abstract_inverted_index.navigation | 139, 175 |
| abstract_inverted_index.parameters | 70 |
| abstract_inverted_index.technology | 228 |
| abstract_inverted_index.application | 1, 129 |
| abstract_inverted_index.demonstrate | 156 |
| abstract_inverted_index.deployment, | 82 |
| abstract_inverted_index.development | 221 |
| abstract_inverted_index.discrepancy | 190 |
| abstract_inverted_index.efficiency, | 29 |
| abstract_inverted_index.experiments | 155 |
| abstract_inverted_index.fertiliser, | 211 |
| abstract_inverted_index.fertiliser. | 231 |
| abstract_inverted_index.fertilisers | 132 |
| abstract_inverted_index.information | 118, 167 |
| abstract_inverted_index.positioning | 137 |
| abstract_inverted_index.constructed. | 147 |
| abstract_inverted_index.demonstrated | 177 |
| abstract_inverted_index.utilisation, | 25 |
| abstract_inverted_index.determination | 111 |
| abstract_inverted_index.respectively, | 92 |
| abstract_inverted_index.respectively. | 80, 173 |
| abstract_inverted_index.classification | 62, 84 |
| abstract_inverted_index.implementation | 34 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| corresponding_author_ids | https://openalex.org/A5073474619 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I52158045 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.98886927 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |