Back

A novel anti-climbing barrier prevents black soldier fly larval escape from rearing containers

Jang, S.; Shimoda, M.

2026-04-30 bioengineering
10.64898/2026.04.28.721252 bioRxiv
Show abstract

The mass-rearing of black soldier fly (Hermetia illucens) larvae (BSFL) is a promising solution for converting organic waste into high-quality insect protein, but preventing larval escape from open-top rearing containers remains a major management challenge. Conventional escape-control methods are often unreliable or impractical. To address this, we developed and evaluated a novel physical barrier, the anti-climbing tape, featuring regularly arranged macroscale protrusions designed to disrupt larval locomotion on vertical surfaces. We conducted a series of experiments to examine the design parameters of the anti-climbing tapes, including the gap size between protrusions and the number of protrusion rows. Our results demonstrate that the anti-climbing tape prevents escape via a dual mechanism: (1) physical obstruction, in which gaps narrower than the larval body width block larvae from passing through, and (2) adhesion reduction, in which the elevated protrusion array decreases the effective contact area for wet adhesion while increasing gravitational torque acting on the larval body. The effectiveness of these mechanisms was dependent on larval size. A design featuring 0.5-mm gaps and a 15-row protrusion array completely prevented the escape of later-instar larvae (>10 mm) in a 20-day large-scale trial, whereas the method was less effective for smaller larvae. In conclusion, the anti-climbing tape provides a robust and chemical-free approach to BSFL escape in mass rearing. To ensure reliable performance, its design parameters, both gap size and array width must be optimised to suppress the mechanical and adhesive components of larval climbing according to the target larval size. Conflict of interestS. Jang and M. Shimoda are inventors on a Japanese patent application (No. 2022-172252, filed November 27, 2022) related to the method described in this manuscript. FundingThis study was supported by Korea-Japan Joint Government Scholarship Program for the Students in Science and Engineering Departments, the Korean Scholarship Foundation, and the University of Tokyo Foundations Support Fund for International Students.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
PLOS ONE
4510 papers in training set
Top 8%
19.2%
2
Chemical Engineering Journal
10 papers in training set
Top 0.1%
7.0%
3
Scientific Reports
3102 papers in training set
Top 16%
6.5%
4
Science of The Total Environment
179 papers in training set
Top 2%
4.4%
5
Insects
36 papers in training set
Top 0.3%
4.1%
6
Applied and Environmental Microbiology
301 papers in training set
Top 0.7%
3.8%
7
PeerJ
261 papers in training set
Top 3%
3.2%
8
Advanced Science
249 papers in training set
Top 7%
2.8%
50% of probability mass above
9
Cell Reports Physical Science
18 papers in training set
Top 0.1%
2.1%
10
Science China Life Sciences
26 papers in training set
Top 0.7%
1.9%
11
ACS Biomaterials Science & Engineering
37 papers in training set
Top 0.5%
1.7%
12
Nature Communications
4913 papers in training set
Top 51%
1.7%
13
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 1%
1.7%
14
ACS Nano
99 papers in training set
Top 2%
1.7%
15
Journal of Colloid and Interface Science
12 papers in training set
Top 0.2%
1.7%
16
Environmental Science & Technology
64 papers in training set
Top 2%
1.4%
17
Biofabrication
32 papers in training set
Top 0.6%
1.3%
18
Water Research
74 papers in training set
Top 1%
1.3%
19
Bioactive Materials
18 papers in training set
Top 0.5%
1.3%
20
Frontiers in Microbiology
375 papers in training set
Top 7%
1.0%
21
Biotechnology and Bioengineering
49 papers in training set
Top 0.7%
0.9%
22
Insect Biochemistry and Molecular Biology
27 papers in training set
Top 0.2%
0.9%
23
International Journal of Biological Macromolecules
65 papers in training set
Top 3%
0.8%
24
Frontiers in Plant Science
240 papers in training set
Top 5%
0.8%
25
Computational and Structural Biotechnology Journal
216 papers in training set
Top 8%
0.8%
26
Insect Science
11 papers in training set
Top 0.2%
0.8%
27
Advanced Materials Technologies
27 papers in training set
Top 0.6%
0.7%
28
Chemosphere
15 papers in training set
Top 0.6%
0.7%
29
ACS Applied Bio Materials
21 papers in training set
Top 0.9%
0.7%
30
Environmental Science & Technology Letters
22 papers in training set
Top 0.4%
0.7%