Research on Rape Image Automatic Segmentation Method Based on RGB Color Space

Tan, Lixin; Yu-tian, LI

doi:10.1109/cisce50729.2020.00092

Cited by 2 publications

(1 citation statement)

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“…In this study, we compared several image processing methods to extract feature effects on the images and selected the most suitable approach to obtain lettuce parameters. The acquired images were first greyed out, and then data was extracted using the super green feature (2G-R-B) method when dealing with green plant diseases or distinguishing green plants from other objects [16][17][18][19][20][21]. The images of lettuce were greyed out using these methods to compare the greying effect.…”

Section: Image Preprocessing Analysismentioning

confidence: 99%

Development and Performance of a Fuzzy Logic Control System for the Root-to-Shoot Ratio in an Aeroponics System for Lettuce

Gao¹,

Guo²,

Tunio³

et al. 2023

Preprint

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At present, aeroponic control is mainly regulated according to the environmental factors of aeroponics, such as the temperature, humidity, light intensity, carbon dioxide concentration, pH, and electrical conductivity (EC) of the nutrient solution. There is a lack of knowledge available in the literature for an aeroponic control system for plant growth information as the primary feedback signal. Therefore, a fuzzy logic-controlled aeroponics system was developed for the growth of lettuce as a feedback signal. After designing, the effectiveness test of system was performed with experiment having three treatments T1 (180C), T2 (220C) and without control (CK). The results show an increasing trend in shoot length, root length, and shoot area over time in all treatments. In terms of shoot area, the maximum of 345 cm² was observed in the T1 treatment, while the CK treatment had a minimum of 241.8 cm². Statistical analysis indicated that the T1 and T2 treatments were not significantly different, but both were significantly different from the CK treatment. The study demonstrates the effectiveness of the fuzzy logic control system and an 18°C nutrient solution temperature, resulting in improved lettuce growth and reduced root-to-shoot ratio. The findings suggest the potential of using fuzzy logic control in aeroponics for optimized cultivation outcomes.

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