Determination Model of Epidermal Wettability for Apple Rootstock Cutting Based on the Improved U-Net

Xu Wang, Lixing Liu, Jinxuan Zou, Hongjie Liu, Jianping Li, Pengfei Wang and Xin Yang ()
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Xu Wang: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Lixing Liu: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Jinxuan Zou: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Hongjie Liu: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Jianping Li: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Pengfei Wang: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Xin Yang: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China

Agriculture, 2024, vol. 14, issue 12, 1-24

Abstract: Keeping the epidermis of apple rootstock cuttings moist is important for maintaining physiological activities. It is necessary to monitor the epidermis moisture in real time during the growth process of apple rootstock cuttings. A machine vision-based discrimination model for the moisture degree of cuttings’ epidermis was designed. This model optimizes the structure of the semantic segmentation model U-Net. The model takes the Saturation channel and Value channel information of the cutting images in the HSV color space as the characteristics of the cuttings’ moisture, so that the model has good performance in the blue-purple supplementary light environment. The average accuracy of the improved model is 95.07% for dry and wet cuttings without supplementary light, and 84.83% with supplementary light. The humidification system implanted in the model can control the atomizer to complete the task of moisturizing the cuttings’ epidermis. The average moisture retention rate of the humidification system for cuttings was 92.5%. Compared with the original model, the moisturizing effect of the humidification system increased by 26.87%. The experimental results show that the improved U-Net model has good generalization and high accuracy, which provides a method for the design of an accurate humidification system.

Keywords: epidermis moisture; semantic segmentation; U-Net; HSV; humidification system (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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