Sugarcane-Seed-Cutting System Based on Machine Vision in Pre-Seed Mode.

YOLO V5 computer vision pre-cutting mode precision agriculture sugarcane

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
02 Nov 2022
Historique:
received: 20 09 2022
revised: 26 10 2022
accepted: 30 10 2022
entrez: 11 11 2022
pubmed: 12 11 2022
medline: 15 11 2022
Statut: epublish

Résumé

China is the world's third-largest producer of sugarcane, slightly behind Brazil and India. As an important cash crop in China, sugarcane has always been the main source of sugar, the basic strategic material. The planting method of sugarcane used in China is mainly the pre-cutting planting mode. However, there are many problems with this technology, which has a great impact on the planting quality of sugarcane. Aiming at a series of problems, such as low cutting efficiency and poor quality in the pre-cutting planting mode of sugarcane, a sugarcane-seed-cutting device was proposed, and a sugarcane-seed-cutting system based on automatic identification technology was designed. The system consists of a sugarcane-cutting platform, a seed-cutting device, a visual inspection system, and a control system. Among them, the visual inspection system adopts the YOLO V5 network model to identify and detect the eustipes of sugarcane, and the seed-cutting device is composed of a self-tensioning conveying mechanism, a reciprocating crank slider transmission mechanism, and a high-speed rotary cutting mechanism so that the cutting device can complete the cutting of sugarcane seeds of different diameters. The test shows that the recognition rate of sugarcane seed cutting is no less than 94.3%, the accuracy rate is between 94.3% and 100%, and the average accuracy is 98.2%. The bud injury rate is no higher than 3.8%, while the average cutting time of a single seed is about 0.7 s, which proves that the cutting system has a high cutting rate, recognition rate, and low injury rate. The findings of this paper have important application values for promoting the development of sugarcane pre-cutting planting mode and sugarcane planting technology.

Identifiants

pubmed: 36366128
pii: s22218430
doi: 10.3390/s22218430
pmc: PMC9655777
pii:
doi:

Substances chimiques

pre-seed 0
Poloxamer 106392-12-5

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Weiwei Wang
ID : Grant No. GXXT-2020-011

Références

Sensors (Basel). 2021 Nov 08;21(21):
pubmed: 34770726
Sensors (Basel). 2021 Nov 28;21(23):
pubmed: 34883953
Sensors (Basel). 2022 Aug 11;22(16):
pubmed: 36015768
Sensors (Basel). 2022 Jul 22;22(15):
pubmed: 35897992
Comput Intell Neurosci. 2022 May 17;2022:3248722
pubmed: 35619764
Sensors (Basel). 2021 Jul 14;21(14):
pubmed: 34300543
Sensors (Basel). 2020 Dec 03;20(23):
pubmed: 33287100
Sensors (Basel). 2022 Aug 22;22(16):
pubmed: 36016074

Auteurs

Da Wang (D)

School of Engineering, Anhui Agricultural University, Hefei 230036, China.

Rui Su (R)

School of Engineering, Anhui Agricultural University, Hefei 230036, China.

Yanjie Xiong (Y)

School of Engineering, Anhui Agricultural University, Hefei 230036, China.

Yuwei Wang (Y)

School of Engineering, Anhui Agricultural University, Hefei 230036, China.
Anhui Province Engineering Laboratory of Intelligent Agricultural Machinery and Equipment, Hefei 230036, China.

Weiwei Wang (W)

School of Engineering, Anhui Agricultural University, Hefei 230036, China.
Anhui Province Engineering Laboratory of Intelligent Agricultural Machinery and Equipment, Hefei 230036, China.

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Classifications MeSH