“Is this blueberry ripe?”: a blueberry ripeness detection algorithm for use on picking robots Article Swipe
Yan Liu
,
Hongtao Zheng
,
Yonghua Zhang
,
Qiujie Zhang
,
Hongli Chen
,
Xueyong Xu
,
Gaoyang Wang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fpls.2023.1198650
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fpls.2023.1198650
Blueberries are grown worldwide because of their high nutritional value; however, manual picking is difficult, and expert pickers are scarce. To meet the real needs of the market, picking robots that can identify the ripeness of blueberries are increasingly being used to replace manual operators. However, they struggle to accurately identify the ripeness of blueberries because of the heavy shading between the fruits and the small size of the fruit. This makes it difficult to obtain sufficient information on characteristics; and the disturbances caused by environmental changes remain unsolved. Additionally, the picking robot has limited computational power for running complex algorithms. To address these issues, we propose a new YOLO-based algorithm to detect the ripeness of blueberry fruits. The algorithm improves the structure of YOLOv5x. We replaced the fully connected layer with a one-dimensional convolution and also replaced the high-latitude convolution with a null convolution based on the structure of CBAM, and finally obtained a lightweight CBAM structure with efficient attention-guiding capability (Little-CBAM), which we embedded into MobileNetv3 while replacing the original backbone structure with the improved MobileNetv3. We expanded the original three-layer neck path by one to create a larger-scale detection layer leading from the backbone network. We added a multi-scale fusion module to the channel attention mechanism to build a multi-method feature extractor (MSSENet) and then embedded the designed channel attention module into the head network, which can significantly enhance the feature representation capability of the small target detection network and the anti-interference capability of the algorithm. Considering that these improvements will significantly extend the training time of the algorithm, we used EIOU_Loss instead of CIOU_Loss, whereas the k-means++ algorithm was used to cluster the detection frames such that the generated predefined anchor frames are better adapted to the scale of the blueberries. The algorithm in this study achieved a final mAP of 78.3% on the PC terminal, which was 9% higher than that of YOLOv5x, and the FPS was 2.1 times higher than that of YOLOv5x. By translating the algorithm into a picking robot, the algorithm in this study ran at 47 FPS and achieved real-time detection well beyond that achieved manually.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fpls.2023.1198650
- https://www.frontiersin.org/articles/10.3389/fpls.2023.1198650/pdf
- OA Status
- gold
- Cited By
- 31
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380082644
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4380082644Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fpls.2023.1198650Digital Object Identifier
- Title
-
“Is this blueberry ripe?”: a blueberry ripeness detection algorithm for use on picking robotsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-09Full publication date if available
- Authors
-
Yan Liu, Hongtao Zheng, Yonghua Zhang, Qiujie Zhang, Hongli Chen, Xueyong Xu, Gaoyang WangList of authors in order
- Landing page
-
https://doi.org/10.3389/fpls.2023.1198650Publisher landing page
- PDF URL
-
https://www.frontiersin.org/articles/10.3389/fpls.2023.1198650/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.frontiersin.org/articles/10.3389/fpls.2023.1198650/pdfDirect OA link when available
- Concepts
-
Ripeness, Computer science, Feature (linguistics), Robot, Convolution (computer science), Algorithm, Artificial intelligence, Artificial neural network, Ripening, Philosophy, Chemistry, Food science, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
31Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 20, 2024: 11Per-year citation counts (last 5 years)
- References (count)
-
47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4380082644 |
|---|---|
| doi | https://doi.org/10.3389/fpls.2023.1198650 |
| ids.doi | https://doi.org/10.3389/fpls.2023.1198650 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/37360727 |
| ids.openalex | https://openalex.org/W4380082644 |
| fwci | 8.18958721 |
| type | article |
| title | “Is this blueberry ripe?”: a blueberry ripeness detection algorithm for use on picking robots |
| biblio.issue | |
| biblio.volume | 14 |
| biblio.last_page | 1198650 |
| biblio.first_page | 1198650 |
| 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 | 0.9987999796867371 |
| 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/T10640 |
| topics[1].field.id | https://openalex.org/fields/16 |
| topics[1].field.display_name | Chemistry |
| topics[1].score | 0.9567999839782715 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1602 |
| topics[1].subfield.display_name | Analytical Chemistry |
| topics[1].display_name | Spectroscopy and Chemometric Analyses |
| topics[2].id | https://openalex.org/T12111 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9556999802589417 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2209 |
| topics[2].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[2].display_name | Industrial Vision Systems and Defect Detection |
| is_xpac | False |
| apc_list.value | 2950 |
| apc_list.currency | USD |
| apc_list.value_usd | 2950 |
| apc_paid.value | 2950 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 2950 |
| concepts[0].id | https://openalex.org/C2780393073 |
| concepts[0].level | 3 |
| concepts[0].score | 0.9126393795013428 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q7335586 |
| concepts[0].display_name | Ripeness |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.6145561933517456 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C2776401178 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5802688598632812 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q12050496 |
| concepts[2].display_name | Feature (linguistics) |
| concepts[3].id | https://openalex.org/C90509273 |
| concepts[3].level | 2 |
| concepts[3].score | 0.48505276441574097 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q11012 |
| concepts[3].display_name | Robot |
| concepts[4].id | https://openalex.org/C45347329 |
| concepts[4].level | 3 |
| concepts[4].score | 0.4749608039855957 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q5166604 |
| concepts[4].display_name | Convolution (computer science) |
| concepts[5].id | https://openalex.org/C11413529 |
| concepts[5].level | 1 |
| concepts[5].score | 0.42269033193588257 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[5].display_name | Algorithm |
| concepts[6].id | https://openalex.org/C154945302 |
| concepts[6].level | 1 |
| concepts[6].score | 0.32065549492836 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[6].display_name | Artificial intelligence |
| concepts[7].id | https://openalex.org/C50644808 |
| concepts[7].level | 2 |
| concepts[7].score | 0.15213626623153687 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[7].display_name | Artificial neural network |
| concepts[8].id | https://openalex.org/C172353545 |
| concepts[8].level | 2 |
| concepts[8].score | 0.11221110820770264 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q2121926 |
| concepts[8].display_name | Ripening |
| concepts[9].id | https://openalex.org/C138885662 |
| concepts[9].level | 0 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[9].display_name | Philosophy |
| concepts[10].id | https://openalex.org/C185592680 |
| concepts[10].level | 0 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[10].display_name | Chemistry |
| concepts[11].id | https://openalex.org/C31903555 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1637030 |
| concepts[11].display_name | Food science |
| concepts[12].id | https://openalex.org/C41895202 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[12].display_name | Linguistics |
| keywords[0].id | https://openalex.org/keywords/ripeness |
| keywords[0].score | 0.9126393795013428 |
| keywords[0].display_name | Ripeness |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.6145561933517456 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/feature |
| keywords[2].score | 0.5802688598632812 |
| keywords[2].display_name | Feature (linguistics) |
| keywords[3].id | https://openalex.org/keywords/robot |
| keywords[3].score | 0.48505276441574097 |
| keywords[3].display_name | Robot |
| keywords[4].id | https://openalex.org/keywords/convolution |
| keywords[4].score | 0.4749608039855957 |
| keywords[4].display_name | Convolution (computer science) |
| keywords[5].id | https://openalex.org/keywords/algorithm |
| keywords[5].score | 0.42269033193588257 |
| keywords[5].display_name | Algorithm |
| keywords[6].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[6].score | 0.32065549492836 |
| keywords[6].display_name | Artificial intelligence |
| keywords[7].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[7].score | 0.15213626623153687 |
| keywords[7].display_name | Artificial neural network |
| keywords[8].id | https://openalex.org/keywords/ripening |
| keywords[8].score | 0.11221110820770264 |
| keywords[8].display_name | Ripening |
| language | en |
| locations[0].id | doi:10.3389/fpls.2023.1198650 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2493613807 |
| locations[0].source.issn | 1664-462X |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1664-462X |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Frontiers in Plant Science |
| locations[0].source.host_organization | https://openalex.org/P4310320527 |
| locations[0].source.host_organization_name | Frontiers Media |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320527 |
| locations[0].source.host_organization_lineage_names | Frontiers Media |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1198650/pdf |
| 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 | Frontiers in Plant Science |
| locations[0].landing_page_url | https://doi.org/10.3389/fpls.2023.1198650 |
| locations[1].id | pmid:37360727 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| 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 | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Frontiers in plant science |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/37360727 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:10289036 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | cc-by |
| locations[2].pdf_url | https://pmc.ncbi.nlm.nih.gov/articles/PMC10289036/pdf/fpls-14-1198650.pdf |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/cc-by |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Front Plant Sci |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/10289036 |
| locations[3].id | pmh:oai:doaj.org/article:69b00b77d9714db984dd7f284a77ce2a |
| locations[3].is_oa | False |
| locations[3].source.id | https://openalex.org/S4306401280 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[3].source.host_organization | |
| locations[3].source.host_organization_name | |
| locations[3].license | |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | article |
| locations[3].license_id | |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Frontiers in Plant Science, Vol 14 (2023) |
| locations[3].landing_page_url | https://doaj.org/article/69b00b77d9714db984dd7f284a77ce2a |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5100351175 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-4242-4840 |
| authorships[0].author.display_name | Yan Liu |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4400573310 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[0].institutions[0].id | https://openalex.org/I4400573310 |
| authorships[0].institutions[0].ror | https://ror.org/01wck0s05 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I4400573310 |
| authorships[0].institutions[0].country_code | |
| authorships[0].institutions[0].display_name | Hangzhou City University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Yan Liu |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[1].author.id | https://openalex.org/A5100785440 |
| authorships[1].author.orcid | https://orcid.org/0009-0004-0810-2519 |
| authorships[1].author.display_name | Hongtao Zheng |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4400573310 |
| authorships[1].affiliations[0].raw_affiliation_string | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[1].institutions[0].id | https://openalex.org/I4400573310 |
| authorships[1].institutions[0].ror | https://ror.org/01wck0s05 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I4400573310 |
| authorships[1].institutions[0].country_code | |
| authorships[1].institutions[0].display_name | Hangzhou City University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Hongtao Zheng |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[2].author.id | https://openalex.org/A5100615106 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-2676-9059 |
| authorships[2].author.display_name | Yonghua Zhang |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4400573310 |
| authorships[2].affiliations[0].raw_affiliation_string | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[2].institutions[0].id | https://openalex.org/I4400573310 |
| authorships[2].institutions[0].ror | https://ror.org/01wck0s05 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I4400573310 |
| authorships[2].institutions[0].country_code | |
| authorships[2].institutions[0].display_name | Hangzhou City University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Yonghua Zhang |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[3].author.id | https://openalex.org/A5088343758 |
| authorships[3].author.orcid | https://orcid.org/0009-0008-5660-7983 |
| authorships[3].author.display_name | Qiujie Zhang |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4400573310 |
| authorships[3].affiliations[0].raw_affiliation_string | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[3].institutions[0].id | https://openalex.org/I4400573310 |
| authorships[3].institutions[0].ror | https://ror.org/01wck0s05 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I4400573310 |
| authorships[3].institutions[0].country_code | |
| authorships[3].institutions[0].display_name | Hangzhou City University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Qiujie Zhang |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[4].author.id | https://openalex.org/A5100605062 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-4530-8474 |
| authorships[4].author.display_name | Hongli Chen |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I76130692 |
| authorships[4].affiliations[0].raw_affiliation_string | School of Information and Electronic Engineering, Zhejiang University, Hangzhou, China |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I4400573310 |
| authorships[4].affiliations[1].raw_affiliation_string | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China |
| authorships[4].institutions[0].id | https://openalex.org/I4400573310 |
| authorships[4].institutions[0].ror | https://ror.org/01wck0s05 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I4400573310 |
| authorships[4].institutions[0].country_code | |
| authorships[4].institutions[0].display_name | Hangzhou City University |
| authorships[4].institutions[1].id | https://openalex.org/I76130692 |
| authorships[4].institutions[1].ror | https://ror.org/00a2xv884 |
| authorships[4].institutions[1].type | education |
| authorships[4].institutions[1].lineage | https://openalex.org/I76130692 |
| authorships[4].institutions[1].country_code | CN |
| authorships[4].institutions[1].display_name | Zhejiang University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Hongli Chen |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China, School of Information and Electronic Engineering, Zhejiang University, Hangzhou, China |
| authorships[5].author.id | https://openalex.org/A5004060021 |
| authorships[5].author.orcid | https://orcid.org/0009-0004-6429-659X |
| authorships[5].author.display_name | Xueyong Xu |
| authorships[5].countries | CN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I1328775524 |
| authorships[5].affiliations[0].raw_affiliation_string | School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China |
| authorships[5].institutions[0].id | https://openalex.org/I1328775524 |
| authorships[5].institutions[0].ror | https://ror.org/03893we55 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I1328775524 |
| authorships[5].institutions[0].country_code | CN |
| authorships[5].institutions[0].display_name | Zhejiang Sci-Tech University |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Xueyong Xu |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China |
| authorships[6].author.id | https://openalex.org/A5016930423 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-6941-7363 |
| authorships[6].author.display_name | Gaoyang Wang |
| authorships[6].countries | CN |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I76130692 |
| authorships[6].affiliations[0].raw_affiliation_string | School of Control Science and Engineering, Zhejiang University, Hangzhou, China |
| authorships[6].institutions[0].id | https://openalex.org/I76130692 |
| authorships[6].institutions[0].ror | https://ror.org/00a2xv884 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I76130692 |
| authorships[6].institutions[0].country_code | CN |
| authorships[6].institutions[0].display_name | Zhejiang University |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Gaoyang Wang |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | School of Control Science and Engineering, Zhejiang University, Hangzhou, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1198650/pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | “Is this blueberry ripe?”: a blueberry ripeness detection algorithm for use on picking robots |
| has_fulltext | True |
| 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 | 0.9987999796867371 |
| 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/W4390619974, https://openalex.org/W2395543297, https://openalex.org/W2163911526, https://openalex.org/W2012057384, https://openalex.org/W2189509717, https://openalex.org/W4385413143, https://openalex.org/W3162834845, https://openalex.org/W2729298216, https://openalex.org/W4210897843, https://openalex.org/W3088721469 |
| cited_by_count | 31 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 20 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 11 |
| locations_count | 4 |
| best_oa_location.id | doi:10.3389/fpls.2023.1198650 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2493613807 |
| best_oa_location.source.issn | 1664-462X |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1664-462X |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Frontiers in Plant Science |
| best_oa_location.source.host_organization | https://openalex.org/P4310320527 |
| best_oa_location.source.host_organization_name | Frontiers Media |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320527 |
| best_oa_location.source.host_organization_lineage_names | Frontiers Media |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1198650/pdf |
| 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 | Frontiers in Plant Science |
| best_oa_location.landing_page_url | https://doi.org/10.3389/fpls.2023.1198650 |
| primary_location.id | doi:10.3389/fpls.2023.1198650 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2493613807 |
| primary_location.source.issn | 1664-462X |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1664-462X |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Frontiers in Plant Science |
| primary_location.source.host_organization | https://openalex.org/P4310320527 |
| primary_location.source.host_organization_name | Frontiers Media |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320527 |
| primary_location.source.host_organization_lineage_names | Frontiers Media |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1198650/pdf |
| 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 | Frontiers in Plant Science |
| primary_location.landing_page_url | https://doi.org/10.3389/fpls.2023.1198650 |
| publication_date | 2023-06-09 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W3200771760, https://openalex.org/W2588938825, https://openalex.org/W6668990524, https://openalex.org/W3018757597, https://openalex.org/W3028857369, https://openalex.org/W6764873646, https://openalex.org/W4284881130, https://openalex.org/W4292223491, https://openalex.org/W4288687070, https://openalex.org/W6791472037, https://openalex.org/W6762585180, https://openalex.org/W6743731764, https://openalex.org/W3042556338, https://openalex.org/W3217381689, https://openalex.org/W7024613528, https://openalex.org/W4296533268, https://openalex.org/W6785652829, https://openalex.org/W2808944785, https://openalex.org/W2945386048, https://openalex.org/W3158394058, https://openalex.org/W4288460555, https://openalex.org/W4288257146, https://openalex.org/W6731892127, https://openalex.org/W4293584584, https://openalex.org/W6620707391, https://openalex.org/W2898512534, https://openalex.org/W2909494862, https://openalex.org/W6768952390, https://openalex.org/W6753412334, https://openalex.org/W3134754127, https://openalex.org/W4297988655, https://openalex.org/W6738846887, https://openalex.org/W3110383822, https://openalex.org/W4298005708, https://openalex.org/W3198305091, https://openalex.org/W4285132074, https://openalex.org/W6990330594, https://openalex.org/W2954930822, https://openalex.org/W3034552520, https://openalex.org/W2962850830, https://openalex.org/W2570343428, https://openalex.org/W2073459066, https://openalex.org/W639708223, https://openalex.org/W3177052299, https://openalex.org/W3152157423, https://openalex.org/W2884585870, https://openalex.org/W2963420686 |
| referenced_works_count | 47 |
| abstract_inverted_index.a | 107, 132, 142, 154, 189, 200, 211, 301, 334 |
| abstract_inverted_index.47 | 344 |
| abstract_inverted_index.9% | 312 |
| abstract_inverted_index.By | 329 |
| abstract_inverted_index.PC | 308 |
| abstract_inverted_index.To | 20, 101 |
| abstract_inverted_index.We | 125, 178, 198 |
| abstract_inverted_index.at | 343 |
| abstract_inverted_index.by | 84, 185 |
| abstract_inverted_index.in | 297, 339 |
| abstract_inverted_index.is | 13 |
| abstract_inverted_index.it | 72 |
| abstract_inverted_index.of | 5, 25, 35, 53, 56, 67, 115, 123, 149, 236, 246, 259, 266, 292, 304, 316, 327 |
| abstract_inverted_index.on | 78, 146, 306 |
| abstract_inverted_index.to | 41, 48, 74, 111, 187, 204, 209, 274, 289 |
| abstract_inverted_index.we | 105, 164, 262 |
| abstract_inverted_index.2.1 | 322 |
| abstract_inverted_index.FPS | 320, 345 |
| abstract_inverted_index.The | 118, 295 |
| abstract_inverted_index.and | 15, 63, 80, 135, 151, 216, 242, 318, 346 |
| abstract_inverted_index.are | 1, 18, 37, 286 |
| abstract_inverted_index.can | 31, 229 |
| abstract_inverted_index.for | 97 |
| abstract_inverted_index.has | 93 |
| abstract_inverted_index.mAP | 303 |
| abstract_inverted_index.new | 108 |
| abstract_inverted_index.one | 186 |
| abstract_inverted_index.ran | 342 |
| abstract_inverted_index.the | 22, 26, 33, 51, 57, 61, 64, 68, 81, 90, 113, 121, 127, 138, 147, 170, 175, 180, 195, 205, 219, 225, 232, 237, 243, 247, 256, 260, 269, 276, 281, 290, 293, 307, 319, 331, 337 |
| abstract_inverted_index.was | 272, 311, 321 |
| abstract_inverted_index.CBAM | 156 |
| abstract_inverted_index.This | 70 |
| abstract_inverted_index.also | 136 |
| abstract_inverted_index.from | 194 |
| abstract_inverted_index.head | 226 |
| abstract_inverted_index.high | 7 |
| abstract_inverted_index.into | 166, 224, 333 |
| abstract_inverted_index.meet | 21 |
| abstract_inverted_index.neck | 183 |
| abstract_inverted_index.null | 143 |
| abstract_inverted_index.path | 184 |
| abstract_inverted_index.real | 23 |
| abstract_inverted_index.size | 66 |
| abstract_inverted_index.such | 279 |
| abstract_inverted_index.than | 314, 325 |
| abstract_inverted_index.that | 30, 250, 280, 315, 326, 352 |
| abstract_inverted_index.then | 217 |
| abstract_inverted_index.they | 46 |
| abstract_inverted_index.this | 298, 340 |
| abstract_inverted_index.time | 258 |
| abstract_inverted_index.used | 40, 263, 273 |
| abstract_inverted_index.well | 350 |
| abstract_inverted_index.will | 253 |
| abstract_inverted_index.with | 131, 141, 158, 174 |
| abstract_inverted_index.78.3% | 305 |
| abstract_inverted_index.CBAM, | 150 |
| abstract_inverted_index.added | 199 |
| abstract_inverted_index.based | 145 |
| abstract_inverted_index.being | 39 |
| abstract_inverted_index.build | 210 |
| abstract_inverted_index.final | 302 |
| abstract_inverted_index.fully | 128 |
| abstract_inverted_index.grown | 2 |
| abstract_inverted_index.heavy | 58 |
| abstract_inverted_index.layer | 130, 192 |
| abstract_inverted_index.makes | 71 |
| abstract_inverted_index.needs | 24 |
| abstract_inverted_index.power | 96 |
| abstract_inverted_index.robot | 92 |
| abstract_inverted_index.scale | 291 |
| abstract_inverted_index.small | 65, 238 |
| abstract_inverted_index.study | 299, 341 |
| abstract_inverted_index.their | 6 |
| abstract_inverted_index.these | 103, 251 |
| abstract_inverted_index.times | 323 |
| abstract_inverted_index.which | 163, 228, 310 |
| abstract_inverted_index.while | 168 |
| abstract_inverted_index.anchor | 284 |
| abstract_inverted_index.better | 287 |
| abstract_inverted_index.beyond | 351 |
| abstract_inverted_index.caused | 83 |
| abstract_inverted_index.create | 188 |
| abstract_inverted_index.detect | 112 |
| abstract_inverted_index.expert | 16 |
| abstract_inverted_index.extend | 255 |
| abstract_inverted_index.frames | 278, 285 |
| abstract_inverted_index.fruit. | 69 |
| abstract_inverted_index.fruits | 62 |
| abstract_inverted_index.fusion | 202 |
| abstract_inverted_index.higher | 313, 324 |
| abstract_inverted_index.manual | 11, 43 |
| abstract_inverted_index.module | 203, 223 |
| abstract_inverted_index.obtain | 75 |
| abstract_inverted_index.remain | 87 |
| abstract_inverted_index.robot, | 336 |
| abstract_inverted_index.robots | 29 |
| abstract_inverted_index.target | 239 |
| abstract_inverted_index.value; | 9 |
| abstract_inverted_index.adapted | 288 |
| abstract_inverted_index.address | 102 |
| abstract_inverted_index.because | 4, 55 |
| abstract_inverted_index.between | 60 |
| abstract_inverted_index.changes | 86 |
| abstract_inverted_index.channel | 206, 221 |
| abstract_inverted_index.cluster | 275 |
| abstract_inverted_index.complex | 99 |
| abstract_inverted_index.enhance | 231 |
| abstract_inverted_index.feature | 213, 233 |
| abstract_inverted_index.finally | 152 |
| abstract_inverted_index.fruits. | 117 |
| abstract_inverted_index.instead | 265 |
| abstract_inverted_index.issues, | 104 |
| abstract_inverted_index.leading | 193 |
| abstract_inverted_index.limited | 94 |
| abstract_inverted_index.market, | 27 |
| abstract_inverted_index.network | 241 |
| abstract_inverted_index.pickers | 17 |
| abstract_inverted_index.picking | 12, 28, 91, 335 |
| abstract_inverted_index.propose | 106 |
| abstract_inverted_index.replace | 42 |
| abstract_inverted_index.running | 98 |
| abstract_inverted_index.scarce. | 19 |
| abstract_inverted_index.shading | 59 |
| abstract_inverted_index.whereas | 268 |
| abstract_inverted_index.However, | 45 |
| abstract_inverted_index.YOLOv5x, | 317 |
| abstract_inverted_index.YOLOv5x. | 124, 328 |
| abstract_inverted_index.achieved | 300, 347, 353 |
| abstract_inverted_index.backbone | 172, 196 |
| abstract_inverted_index.designed | 220 |
| abstract_inverted_index.embedded | 165, 218 |
| abstract_inverted_index.expanded | 179 |
| abstract_inverted_index.however, | 10 |
| abstract_inverted_index.identify | 32, 50 |
| abstract_inverted_index.improved | 176 |
| abstract_inverted_index.improves | 120 |
| abstract_inverted_index.network, | 227 |
| abstract_inverted_index.network. | 197 |
| abstract_inverted_index.obtained | 153 |
| abstract_inverted_index.original | 171, 181 |
| abstract_inverted_index.replaced | 126, 137 |
| abstract_inverted_index.ripeness | 34, 52, 114 |
| abstract_inverted_index.struggle | 47 |
| abstract_inverted_index.training | 257 |
| abstract_inverted_index.(MSSENet) | 215 |
| abstract_inverted_index.EIOU_Loss | 264 |
| abstract_inverted_index.algorithm | 110, 119, 271, 296, 332, 338 |
| abstract_inverted_index.attention | 207, 222 |
| abstract_inverted_index.blueberry | 116 |
| abstract_inverted_index.connected | 129 |
| abstract_inverted_index.detection | 191, 240, 277, 349 |
| abstract_inverted_index.difficult | 73 |
| abstract_inverted_index.efficient | 159 |
| abstract_inverted_index.extractor | 214 |
| abstract_inverted_index.generated | 282 |
| abstract_inverted_index.k-means++ | 270 |
| abstract_inverted_index.manually. | 354 |
| abstract_inverted_index.mechanism | 208 |
| abstract_inverted_index.real-time | 348 |
| abstract_inverted_index.replacing | 169 |
| abstract_inverted_index.structure | 122, 148, 157, 173 |
| abstract_inverted_index.terminal, | 309 |
| abstract_inverted_index.unsolved. | 88 |
| abstract_inverted_index.worldwide | 3 |
| abstract_inverted_index.CIOU_Loss, | 267 |
| abstract_inverted_index.YOLO-based | 109 |
| abstract_inverted_index.accurately | 49 |
| abstract_inverted_index.algorithm, | 261 |
| abstract_inverted_index.algorithm. | 248 |
| abstract_inverted_index.capability | 161, 235, 245 |
| abstract_inverted_index.difficult, | 14 |
| abstract_inverted_index.operators. | 44 |
| abstract_inverted_index.predefined | 283 |
| abstract_inverted_index.sufficient | 76 |
| abstract_inverted_index.Blueberries | 0 |
| abstract_inverted_index.Considering | 249 |
| abstract_inverted_index.MobileNetv3 | 167 |
| abstract_inverted_index.algorithms. | 100 |
| abstract_inverted_index.blueberries | 36, 54 |
| abstract_inverted_index.convolution | 134, 140, 144 |
| abstract_inverted_index.information | 77 |
| abstract_inverted_index.lightweight | 155 |
| abstract_inverted_index.multi-scale | 201 |
| abstract_inverted_index.nutritional | 8 |
| abstract_inverted_index.three-layer | 182 |
| abstract_inverted_index.translating | 330 |
| abstract_inverted_index.MobileNetv3. | 177 |
| abstract_inverted_index.blueberries. | 294 |
| abstract_inverted_index.disturbances | 82 |
| abstract_inverted_index.improvements | 252 |
| abstract_inverted_index.increasingly | 38 |
| abstract_inverted_index.larger-scale | 190 |
| abstract_inverted_index.multi-method | 212 |
| abstract_inverted_index.Additionally, | 89 |
| abstract_inverted_index.computational | 95 |
| abstract_inverted_index.environmental | 85 |
| abstract_inverted_index.high-latitude | 139 |
| abstract_inverted_index.significantly | 230, 254 |
| abstract_inverted_index.(Little-CBAM), | 162 |
| abstract_inverted_index.representation | 234 |
| abstract_inverted_index.one-dimensional | 133 |
| abstract_inverted_index.characteristics; | 79 |
| abstract_inverted_index.anti-interference | 244 |
| abstract_inverted_index.attention-guiding | 160 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| corresponding_author_ids | https://openalex.org/A5100785440 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I4400573310 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.6899999976158142 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.98801195 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |