Research Article
Post-harvest technologies
V. Kahrizi; E. Ahmadi; A. R. Shoshtari
Abstract
IntroductionThe growing consumer demand for high-quality products has led to the development of new technologies for assessing the quality of agricultural products. Iran is the 9th largest orange producer in the world. Every year, large quantities of agricultural products lose their optimal quality due ...
Read More
IntroductionThe growing consumer demand for high-quality products has led to the development of new technologies for assessing the quality of agricultural products. Iran is the 9th largest orange producer in the world. Every year, large quantities of agricultural products lose their optimal quality due to mechanical and physical damage during various operations such as harvesting, packaging, transportation, sorting, processing, and storage. This study is performed to identify the natural frequencies and vibration modes of the Thomson orange fruit using finite element modal analysis by ANSYS software. In addition, physical properties including mass, volume, density, and principal dimensions were measured, and mechanical properties were determined using Instron Texture Profile Analysis. The dynamic behavior of the orange fruit was simulated using the pendulum impact test. Afterward, the obtained impact was applied to the orange fruit by force gauge and three-axis accelerometer sensors in both polar and equatorial directions. The three-dimensional geometric model of the orange fruit was drawn in the ANSYS software. After meshing and applying the boundary conditions, the first 20 modes and corresponding natural frequencies were obtained. Since the objective of this study was to identify the natural frequencies of the orange fruit, it was considered to have free movement and rotation in space. The results showed that the natural frequencies of orange fruit are in the range of 0 to 248.41 Hz. Knowledge of the texture characteristics and dynamic behavior of horticultural products is essential for the design and development of agricultural machinery. Furthermore, the design and development of agricultural machinery are directly related to the biological properties of agricultural products.Materials and MethodsThe Thomson orange variety was used in the present study. The oranges used for the experiments were harvested from the Citrus and Subtropical Fruits Research Institute in Ramsar, Iran, located at coordinates 50° 40′ E and 36° 52′ N. The oranges were subsequently divided into two groups: large (average diameter 82 mm) and small (average diameter 66 mm). Conducting the finite element analysis requires knowledge of the physical and mechanical properties of the flesh and skin of the orange fruit. The physical and mechanical properties of the tested samples include geometric dimensions, modulus of elasticity, Poisson’s ratio, and density. In the present study, the dynamic behavior of the orange fruit under dynamic loads was investigated by performing an impact test using a pendulum. The orange fruit was hung from the ceiling using a thin thread to perform experimental tests and extract the modal parameters. The orange samples were subjected to impact at three angles: 7° (below the yield point), 10° (at the dynamic yield point), and 20° (above the dynamic yield point).Results and DiscussionThe comparison of the experimental (laboratory) natural frequencies and simulation validates the simulation results. The experimental natural frequencies of the first, second, and third modes in the large-group oranges are 125.4, 146.9, and 180.4 Hz, respectively. Additionally, the simulation (modal) frequencies are 133.80, 146.16, and 196.66 Hz for the first three modes, respectively. The lowest and the highest differences were observed in the second (0.5%) and third (9.01%) modes, respectively. In the small-group oranges, the first, second, and third modes have experimental natural frequencies of 152.2, 188.8, and 242.2 Hz, respectively, and simulation frequencies are 167.79, 187.50, and 248.30 Hz. The second and first modes exhibited the smallest and largest disparities between experimental and simulated natural frequencies, respectively, at 0.68% and 10.24%.ConclusionWhile there are certain limitations, it is undeniable that Computer Aided Engineering (CAE) applications are advantageous for predicting the natural frequencies and vibration modes of spherical fruits such as oranges. Utilizing the obtained frequencies, especially the resonance frequency and the vibrational mode shape, enables us to avoid the resonance frequency in the actual transportation of oranges. This is possible through the implementation of suitable packaging and transportation methods, thereby mitigating the deterioration of fruit quality and ensuring an accurate prediction of its shelf life.
Research Article
Modeling
A. Taheri hajivand; K. Shirini; S. Samadi Gharehveran
Abstract
IntroductionAgricultural production involves a series of tasks including tillage, planting, and harvesting, which must be done at the right time for each region and type of product. Failing to complete these tasks on time can lead to a decrease in yield. Farmers may wrongly attribute this to factors ...
Read More
IntroductionAgricultural production involves a series of tasks including tillage, planting, and harvesting, which must be done at the right time for each region and type of product. Failing to complete these tasks on time can lead to a decrease in yield. Farmers may wrongly attribute this to factors such as infertile land, pests, diseases, and uneven rainfall distribution. However, this decrease in yield may not always be evident or tangible. To avoid such losses and unforeseen expenses, it is crucial to plan agricultural mechanization projects using the principles of project control. Agricultural projects, like industrial projects, must be carried out in the correct order and at the right time to achieve optimal results. Given the limited availability of resources for mechanization projects, it is imperative to meticulously plan activities to ensure that they are carried out on time and with maximum utilization of resources. To address these challenges, researchers have used meta-heuristic methods in project control, such as the colonial competition algorithm, which has been proven effective in solving the issue of scheduling projects with limited resources. The algorithm has been tested across various industrial activities and projects, and its performance in scheduling the Resource-Constrained Project Scheduling Problem (RCPSP) has been validated by researchers globally.Materials and MethodsThere is a scheduling issue regarding limited resources in agriculture, and this study presents a novel approach using the imperialist competitive algorithm (ICA). The algorithm not only explores a wider solution space but also strives to minimize deviation from the optimal solution, thereby improving the success rate of the proposed method. This research focuses on two dominant products, wheat and rapeseed, produced in Moghan Agriculture and Industry located in Northwest Iran. To evaluate the effectiveness of ICA, we compared it with other well-known meta-heuristic algorithms. We successfully resolved the problem of project scheduling problem with limited resources by implementing the imperialist competitive algorithm. Our findings have shown that this approach not only significantly increased efficiency but also outperformed other algorithms.Results and DiscussionIn this study, we assessed the efficiency of meta-heuristic methods in solving the RCPSP, which can be useful in optimizing the timeliness of project execution, especially for large-scale projects. Some meta-heuristic methods are only useful for smaller problems, while others can provide near-optimal solutions for larger problems, making them suitable for RCPSP. The algorithm explores a wide range of solutions and avoids premature convergence and getting stuck in local optima, unlike other algorithms such as the genetic algorithm. Optimization reduced the required budget and shortened the duration by 42 days for wheat and 25 days for rapeseed.ConclusionWe utilized the colonial competition algorithm to address the RCPSP problem in agricultural mechanization projects for two agricultural products in Moghan. Our results show that the proposed algorithm converged and reached the optimal solution. The proposed algorithm was compared with other algorithms and it outperformed them.
