In order to reduce the human efforts during manual harvesting and increase the operational capacity and quality, the mechanization of the harvesting operation has been significantly increasing in the last few years for coffee crops. Therefore, for the design of coffee harvesting machines, the physical and mechanical properties of coffee branches are of utmost importance for harvesting machines projects. In this way, using an experimental approach, the present paper analyzes the variability of physical and mechanical properties in the coffee branches, of the Coffea arabica L., cultivar Catuaí-Vermelho (IAC 144). The branches were collected in different positions, along the orthotropic branch: upper, middle and lower parts of the plant. The mass, volume, specific mass, and modulus of elasticity of the collected specimens were determined considering their position in the plant and position along the branches. According to the position in the plant, no significant differences were found between the specific mass averages for the upper, middle, and lower parts of the plant. The research obtained an average of 1.24 GPa with a standard deviation of 0.13 GPa for the elasticity modulus. A significant increase in the elasticity modulus could be noted in the branches from the top to the bottom of the plant in the present research.
This work proposes evaluating statistically the metrological performance of three-dimensional reconstructions built with fused long-wavelength infrared (LWIR) and visible-light (VL) images. The image fusion procedure was essentially based on two-dimensional wavelet transform and two pixel-level fusion rules: the maximum intensity level, presented in a previous work of the authors, and a new fusion rule, which replaces the VL information with the LWIR information in the region of the measured object on the images. The reconstructions of a translucent cube were performed with a point triangulation-based procedure and its dimension measurements were employed as evaluation criteria. The results show that the fused images have more contrast but also more artifacts. The fusion procedures generated denser reconstructions with at least 34.83% more points. Considering the metrological result, reconstructions with only visible-light images resulted in maximal 89.31% less measurement bias but at least 47.25% more uncertainty than the fusion ones. The new fusion rule provided the best results, with more points in the dense cloud and lower uncertainty. The work is important to provide a metrologically viable alternative for three-dimensional reconstruction of objects in situations of low contrast or poor texture information in the visible spectrum, and in which no target can be applied to the inspected part.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.