Dynamic behavior of coffee tree branches during mechanical harvest

https://doi.org/10.1016/j.compag.2020.105415Get rights and content

Highlights

  • A real time data acquisition system was proposed for coffee mechanical harvesting.

  • It is a low cost system consisting of an open source electronic prototyping platform.

  • The displacement of the coffee tree branches during mechanical harvest was estimated.

  • The results have evidenced the dynamic interaction between machine and coffee tree.

  • It may be useful for improving the harvesting efficiency and for selectivity of fruits.

Abstract

The coffee industry stands out worldwide due to its socioeconomic importance, acting directly or indirectly in the most diverse sectors. With this, new technologies and several harvester models have emerged. These harvesters have regulations that can influence the efficiency of harvesting, the selectivity of fruits and the preservation of the crop. In this way, the understanding of the behavior of harvester components and their dynamic relationship with coffee are essential for mechanical harvesting management and for developing new products. The objective of this work was to obtain the coffee tree branch displacement (in terms of frequency and amplitude of vibration) through instrumentation and signal processing techniques. For this, a low cost system was developed, consisting of an Arduino open source electronic prototyping platform and an accelerometer. The acceleration signals were collected and processed via MatLab. The results showed the complete two-dimensional displacement performed by the coffee tree branches for different harvester settings during the mechanical coffee harvesting. From the vibration displacements of the branches it is possible to unveil the dynamic interaction between machine and coffee tree, contributing to the management of mechanical coffee harvesting and to the development of new vibration harvesting systems.

Introduction

Coffee mechanization has led to the emergence of new Technologies and various harvester models, favoring cost reductions during the harvesting process and, consequently, making the coffee grower more competitive in the agricultural Market.

The mechanization of cultivation and harvesting operations assumes a role that has been giving breath to coffee farmers in times of crisis by reducing operating costs (Oliveira et al., 2007a, Oliveira et al., 2007b).

According to Ferraz (2012) coffee harvesting is more difficult to study than crops such as cereals due to characteristics such as plant shape, uneven fruit ripeness and high moisture content. They also states that besides being a perennial shrub, each coffee plant can have different shape, with differences in height, length and width.

Coffee fruit has been harvested by mechanical vibration. From the association of factors such as frequency and amplitude of vibration, sufficient vibrational energy can be transferred to detach the fruits. Thus, from the knowledge of the model properties of the fruit-peduncle system, appropriate frequency and amplitude levels can be employed to perform selective or total fruit harvesting (Santos et al., 2010).

According to Guedes (2011), the improvement of coffee harvesting machines requires prior knowledge of details concerning the mechanical, geometric and dynamics properties of the fruits and the plant. Guedes (2011) states that experimental tests conducted in laboratory with appropriate machines to analyze the behavior of the fruit-peduncle-branch system can assist in the parametrization and design of harvesting machines.

For Roque and Schievelbein (2016), the development of computational technologies in the agricultural area is not new. On the other hand, it is a daily challenge, since every year new technologies are applied in this area aiming at improving the agricultural production process and reducing it operating costs.

Coffee harvesters have been around for over four decades, but there is still a lack of information on their dynamics relationship with coffee.

Seeking to understand the mechanical behavior of the coffee plant through finite element analysis, Carvalho et al. (2016) simulated the coffee tree in a three-dimensional system and compared it with the behavior of a real plant under static load, validating the methodology for studies to prevent structural problems during mechanical coffee harvesting. Tinoco et al. (2014) observed that with the progression of fruit maturation, they lose their elastic capacity.

Determining natural frequencies and vibration modes, Coelho et al. (2016) found that these frequencies decrease as the total mass of the system increases, given the greater number of fruits in solidarity with the stalk. Villibor et al. (2016) used image processing techniques, finding natural frequencies of 11.62 and 13.29 Hz for the red and green maturation stages, respectively.

Besides the importance of studying the frequency, amplitude, brake regulation of oscillation cylinders, fruit detachment forces, mechanical, geometric and dynamics properties of fruits, in mechanical coffee harvesting by vibration, further study and knowledge of the dynamics behavior of the mechanical components responsible for vibration transmission to the coffee tree branches and fruits is also required.

In order to know the dynamics behavior of a coffee harvester’s vibrating rods in terms of frequency and amplitude of vibration for different settings, Ferreira Júnior et al., 2016a, Ferreira Júnior et al., 2016b used instrumentation and signal processing techniques to identify and map the tip movement of the rods during operation. The achieved results made it possible to infer on the recommendation of regulation for mechanical harvesting, selective harvesting and less damage to plants.

In coffee growing, especially for the harvesting process, the pursuit of cost reduction, better harvesting performance, greater selectivity and crop preservation is very important, being of interest to both the coffee grower and the harvester manufacturing industries.

Thus, seeking to understand the vibration dynamics of coffee tree branches during harvesting, this work was aimed to determine the vibration behavior of coffee plagiotropic branches, in terms of frequency and amplitude of vibration, in order to raise the displacement profile, that is, the trajectory of these branches in different settings recommended for mechanical coffee harvesting, with the aid of signal processing and instrumentation techniques.

Section snippets

Materials and methods

The tests were carried out in the experimental area of Fazenda Bela Vista, in Nepomuceno, Minas Gerais State, Brazil. It was used a self-propelled coffee harvester, model K-3 Challenger, manufactured by the Brazilian company Máquinas Agrícolas Jacto S/A.

The harvester was configured with 13 × 570 mm (diameter × length respectively) shanks on the 22 lower flanges of the oscillating cylinders and 13 × 600 mm shanks on the 14 upper flanges. It is noteworthy that original rods recommended by the

Results and discussions

The steps shown in Fig. 4 were applied to all tested settings. For simplicity, the sequential results of each step for only one of the tested settings are presented in this section.

The vibration signals captured by the accelerometer were passed by a high-pass filter (cut-off frequency of 1 Hz) to eliminate non-expected low frequency components (below 1 Hz) with high energy. Fig. 6 shows the vibration signals captured by the accelerometer in the horizontal and vertical directions and their

Conclusions

The signal acquisition and processing methodology provided agility, clarity and quality in the interpretation of the results, supporting the understanding of the behavior of the coffee tree vibration signals. It is possible to obtain the displacement profile performed by the plagiotropic coffee branches in the different settings tested, obtaining the horizontal and vertical amplitudes (“peak to peak”) performed by them. Note that the instrumentation system proposed takes advantages of being

Author contributions

Luiz de Gonzaga Ferreira Júnior: Collected the data, Contributed data or analysis tools, Performed the analysis, Wrote the paper. Fábio Moreira da Silva: Conceived and designed the analysis, Performed the analysis. Danton Diego Ferreira: Conceived and designed the analysis, Performed the analysis, Wrote the paper. Carlos Eduardo Pereira de Souza: Collected the data, Contributed data or analysis tools. Andrey Willian Marques Pinto: Contributed data or analysis tools, Performed the analysis.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), the Fundação de Amparo à Pesquisa de MG (FAPEMIG), ao Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and the company L D Gonzaga Treinamentos e Consultoria Agrícola Ltda-ME, by the support. A special thanks to Dr. Carlos Augusto Duque for providing valuable comments about specific points of the paper.

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