Evidence map›Paper›PMID 37765962›Full record

ReviewSensors (Basel, Switzerland)2023

Perceptual Soft End-Effectors for Future Unmanned Agriculture.

Weikang Ye, Lin Zhao, Xuan Luo, Junxian Guo, Xiangjiang Liu

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Smart agriculture in Asia.Plant communications · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Weikang YeCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Lin ZhaoCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Xuan LuoCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Junxian GuoCollege of Mechanical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
Xiangjiang LiuCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-5419-669X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As consumers demand ever-higher quality standards for agricultural products, the inspection of such goods has become an integral component of the agricultural production process. Unfortunately, traditional testing methods necessitate the deployment of numerous bulky machines and cannot accurately determine the quality of produce prior to harvest. In recent years, with the advancement of soft robot technology, stretchable electronic technology, and material science, integrating flexible plant wearable sensors on soft end-effectors has been considered an attractive solution to these problems. This paper critically reviews soft end-effectors, selecting the appropriate drive mode according to the challenges and application scenarios in agriculture: electrically driven, fluid power, and smart material actuators. In addition, a presentation of various sensors installed on soft end-effectors specifically designed for agricultural applications is provided. These sensors include strain, temperature, humidity, and chemical sensors. Lastly, an in-depth analysis is conducted on the significance of implementing soft end-effectors in agriculture as well as the potential opportunities and challenges that will arise in the future.

Indexed as

end-effectorperceptualsensorsoft

Identifiers

PMID37765962
PMCPMC10537409

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.