Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Monterotondo, 00015 Rome, Italy.
Department of Agricultural and Forestry Sciences (DAFNE), Tuscia University of Viterbo, 01100 Viterbo, Italy.
Sensors (Basel). 2023 Jan 12;23(2):868. doi: 10.3390/s23020868.
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.
茧的分拣是农业生产结束和工业缫丝前最耗费人力的活动之一，这是为了获得优良的丝绸质量。鉴于欧洲丝绸业可能会重新启动，这个生产环节的自动化是必要的，既可以降低丝绸成本，又可以使纤维质量标准化。本研究从丝绸生产中的这一关键问题（将蚕茧分为不同质量等级所需的人工劳动）出发，确定了改进方案。为此，提出了这项活动的自动化，并设计和制造了第一个原型。该机器基于使用三个摄像头和图像处理算法来识别蚕茧的形状和大小以及外部污渍、一个定制的光传感器和一个人工智能模型来剔除死蚕茧。目前机器的效率约为每分钟 80 个蚕茧。总的来说，这项研究的改进涉及到将传统传感器/技术应用于不寻常的产品，并设计专门的传感器来识别丝绸蚕茧内的死活蛹。新的茧分拣原型的整体效率也有一个大致的概述。
