Evidence map›Paper›PMID 42799148›Full record

ReviewFrontiers in plant science2026

Low-damage mechanised harvesting of shallots: from biomechanical interaction mechanisms to bionic and flexible design strategies.

Honglei Zhang, Xiaoying He, Zhong Tang

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Honglei ZhangSchool of Agricultural Engineering, Jiangsu University, Zhenjiang, China.
Xiaoying HeSchool of Agricultural Engineering, Jiangsu University, Zhenjiang, China.
Zhong TangSchool of Agricultural Engineering, Jiangsu University, Zhenjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid expansion of the shallot industrial scale, the high costs and low efficiency associated with traditional manual harvesting have emerged as core bottlenecks restricting the sustainable development of the industry. When deployed in shallot fields, existing general-purpose root-crop harvesting equipment encounters a typical engineering mechanics contradiction: the "high pull-out resistance of deep root systems" versus the "high vulnerability of tender pseudostems". Consequently, achieving efficient, intact, and non-destructive harvesting remains challenging. To address the technical difficulties of the low-damage mechanised harvesting of shallots, this review systematically summarises the research progression of core engineering strategies based on the microscopic "machine-soil-plant" interaction mechanism. First, the viscoelastic rheological characteristics of shallot pseudostems and the pull-out mechanical responses of root-soil complexes are analysed to establish the physical damage boundaries for mechanical operations. Secondly, the bionic drag reduction technologies for soil-engaging components are highlighted, evaluating the efficacy of macroscopic geometric bionics and microscopic non-smooth surface features in optimising cutting stress fields and severing interfacial adhesion networks. Furthermore, the evolution of compliant mechanisms in the non-destructive clamping and conveying of pseudostems is explored. This includes an in-depth analysis of adaptive clamping mechanisms, which are transitioning from passive rigid-flexible coupling towards morphological enveloping driven by soft actuators. Finally, addressing the current wear-resistance bottlenecks of bionic materials in complex adhesive environments and the dynamic adaptation limitations of rigid-flexible coupled systems, this paper proposes cutting-edge developmental trends. These encompass the integration of multi-body dynamics and discrete element method (MBD-DEM) coupled simulations, alongside machine vision-based intelligent closed-loop control. This review aims to provide rigorous theoretical support and system integration references for the research and development of a new generation of intelligent, low-damage shallot harvesting equipment.

Indexed as

biomechanicsbionic drag reductionflexible clampinglow-damage harvestingshallot

Identifiers

PMID42799148
PMCPMC13614099

What OpenQuestion holds

Textmetadata
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.