A discrimination model for dead cocoons using near-infrared transmission spectra analyses

Lee, Ahyeong; Kim, Ghiseok; Kim, Seong-Wan; Kim, Gi‐Young

doi:10.1016/j.sna.2022.113857

Cited by 3 publications

(1 citation statement)

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“…In addition to using artificial intelligence models to discriminate live cocoons from dead cocoons, there are also some examples in the literature of work using near-infrared spectroscopy for such discrimination. In fact, in the study by Lee et al [ 14 ], live cocoons were discriminated from dead cocoons by near-infrared spectroscopy. A total of 367 normal cocoons and 152 dead cocoons were considered in order to determine whether they were alive or dead.…”

Section: Introductionmentioning

confidence: 99%

Automated Prototype for Bombyx mori Cocoon Sorting Attempts to Improve Silk Quality and Production Efficiency through Multi-Step Approach and Machine Learning Algorithms

Vasta

Figorilli

Ortenzi

et al. 2023

Sensors

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Cocoon sorting is one of the most labor-demanding activities required both at the end of the agricultural production and before the industrial reeling process to obtain an excellent silk quality. In view of the possible relaunch of European sericulture, the automatization of this production step is mandatory both to reduce silk costs and to standardize fiber quality. The described research starts from this criticality in silk production (the manual labor required to divide cocoons into different quality classes) to identify amelioration solutions. To this aim, the automation of this activity was proposed, and a first prototype was designed and built. This machinery is based on the use of three cameras and imaging algorithms identifying the shape and size of the cocoons and outside stains, a custom-made light sensor and an AI model to discard dead cocoons. The current efficiency of the machine is about 80 cocoons per minute. In general, the amelioration obtained through this research involves both the application of traditional sensors/techniques to an unusual product and the design of a dedicated sensor for the identification of dead/alive pupae inside the silk cocoons. A general picture of the overall efficiency of the new cocoon-sorting prototype is also outlined.

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Section: Introductionmentioning

confidence: 99%