Melon Harvesting Research Articles

Livestock impacts on an iconic Namib Desert plant are mediated by abiotic conditions

Resolving the relative contributions of top-down versus bottom-up drivers of vegetation dynamics is a major challenge in drylands. In the coming decades, growing livestock populations and shifts in water availability will simultaneously impact many arid systems, but a lack of empirical data on plant responses to these pressures limits understanding of how plants will respond. Here, we combine ground and drone observations from an herbivore exclosure experiment to identify ungulate visitation patterns and their impacts on the cover and melon production of !nara (Acanthosicyos horridus), a large, long-lived desert plant in the hyper-arid Namib Desert. !Nara are of key ecological, social, and economic importance to Namib ecosystems and to the local Topnaar people. At our study site, we find that among native and domestic herbivores, free-ranging donkeys have the largest impact on !nara cover and melon production. !Nara cover was negatively affected by herbivores close to the desert-ephemeral river ecotone during a dry period, whereas !nara cover increased on all plants across the landscape during a wetter period, regardless of herbivore access. !Nara near the river channel and those protected from herbivores had more mature melons, particularly during the wetter period. At this site, the potential for conflict between Topnaar !nara melon harvesting and pastoral practices varies with a plant’s distance from the river and prevailing abiotic conditions. This work advances monitoring approaches and adds empirical support to the understanding that top-down and bottom-up regulation of plant dynamics varies with spatiotemporal context, even within landscapes.

Internet of Things: A Monitoring and Control System for Rockmelon Farming

This paper describes the internet of things application in agriculture production especially for rock melon farming. In order to boost agricultural production on a commercial basis, a more systematic approach should be developed and organized to be adopted by operators to increase production and income. This work combines fertilization and irrigation in one system under protective structures to ensure that high-quality plant production and an alternative to conventional cropping systems. In addition, the use of technology for online monitoring and control is an improvement to the system in parallel with the rapid development of information technology today. The proposed system is focusing on automation, wireless, data analytics and simplified design with minimal and scalable skid size for rock melon in the Klang valley. Other than that, a monitoring and control system were developed besides, applied Internet of Thing (IoT) platform with additional user-friendly programmable farming routine Human-machine interfacing (HMI). HMI is a software interface that is capable to conduct the systems directly via autonomous cloud control. It provides time management and contributes to a more efficient workforce. The aim to develop a monitoring and controlling system using IoT for rock melon in this study was achieved. The rock melon harvesting succeeds according to the scheduled routine and the quality of yields also satisfied.

Evaluasi Deskriptif Umur Panen Melon (Cucumis melo, L) Di Pekanbaru

The objective of the study was to examine the factors that caused melon harvesting age in Pekanbaru faster than in the melon-producing regions. The research method used is descriptive qualitative. The results of the discussion found that the factors that influence the harvesting age of melon in Pekanbaru City are the water stress condition, the unfulfilled essential ingredients, the insufficient planting medium of organic matter, the importance of growth regulators that can enlarge the fruit and maintain the age of the plant, environmental modification.

Determination of robotic melon harvesting efficiency: a probabilistic approach

To automate the harvesting of melons, a mobile Cartesian robot is developed that traverses at a constant velocity over a row of precut melons whose global coordinates are known. The motion planner is programmed to have the robot harvest as many melons as possible. Numerous simulations of the robot over a field with different sets of randomly distributed melons resulted in nearly identical percentages of melons harvested. This result holds true over a wide range of robot dimensions, motor capabilities, velocities and melon distributions. Using probabilistic methods, we derive these results by modelling the robotic harvesting procedure as a stochastic process. In this simplified model, a harvest ratio is predicted analytically using Poisson and geometric distributions. Further analysis demonstrates that this model of robotic harvesting is an example of an infinite length Markov chain. Applying the mathematical tools of Markov processes to our model yields a formula for the harvest percentage that is in strong agreement with the results of the simulation. The significance of the approach is demonstrated in two of its applications: to select the most efficient actuators for maximal melon harvesting and determine the set of optimal velocities along a row of melons of varying densities.

The Orienteering Problem with Time Windows Applied to Robotic Melon Harvesting

The goal of a melon harvesting robot is to maximize the number of melons it harvests given a progressive speed. Selecting the sequence of melons that yields this maximum is an example of the orienteering problem with time windows. We present a dynamic programming-based algorithm that yields a strictly optimal solution to this problem. In contrast to similar methods, this algorithm utilizes the unique properties of the robotic harvesting task, such as uniform gain per vertex and time windows, to expand domination criteria and quicken the optimal path selection process. We prove that the complexity of this algorithm is linearithmic in the number of melons and can be implemented online if there is a bound on the density. The results of this algorithm are demonstrated to be significantly better than the standard heuristic solution for a wide range of harvesting robot scenarios.

Motion Planning of a Mobile Cartesian Manipulator for Optimal Harvesting of 2-D Crops

<abstract><title><italic>Abstract.</italic></title> A 3DOF mobile Cartesian robotic harvester for two-dimensionally distributed crops such as melons is being developed. A two-step procedure to calculate the trajectory of its manipulator that will result in the maximum number of melons harvested is described in this article. The goal of the first step is to calculate the minimum-time trajectory required to traverse between any two melons while adhering to velocity, acceleration, location, and endpoint constraints. This step is accomplished in a hierarchal manner by solving several subproblems involving optimal control and nonconvex optimization, enabling optimal (maximum) melon harvesting to be formulated as an orienteering problem with time windows. In the second step, the orienteering problem is solved using the moving branch and prune method, based on dynamic programming. This enables suboptimal sequences of melons (out of all options) to be eliminated on the fly without the need to solve the entire problem at once. An example is shown to demonstrate the efficacy of the algorithm.

참외 수확로봇을 위한 타원 정합기반의 인식 기법 개발

In this paper, vision-based positioning algorithm for melon harvesting robot is presented. RGB value of the input image was converted into HSI value then, melon area was extracted after performing the binarization using HUE value. After morphological filtering was applied to remove noise, outermost boundary points were obtained using border following and convex hull method. Elliptical fitting for melons was perform by the RANSAC algorithm, the center point of ellipse, the length of the short and long axis, and rotation angle were obtained. We verified the effectiveness of the proposed method by various simulation experiments and confirmed actual feasibility of the proposed method by applying to the real melon.

Systems engineering of agricultural robot design

This paper presents a systems engineering method to evaluate the performance of an agricultural robot by simulating and comparing different types of robots, number of arms, multiple arm configurations, workspace design and dynamic characteristics. Numerical simulation tools were developed to quantify measures of machine performance such as cycle time and percentage of successful cycles based on an extensive statistical analysis using measured fruit locations and simulated crop parameters. The methodology developed was applied to determine design parameters for a robotic melon harvester. Simulation results indicated that the Cartesian robot was faster than the cylindrical robot for the melon harvesting task. Activating two arms in tandem was the fastest configuration evaluated. >

Intelligent control system simulation of an agricultural robot

An intelligent control system for an agricultural robot which performs in an uncertain and unstructured environment was modelled as distributed, autonomous computing modules that communicate through globally accessible blackboard structures. The control architecture was implemented for a robotic harvester of melons. A CAD workstation was used to plan, model, simulate and evaluate the robot and gripper motions using 3-D, real-time animation. The intelligent control structure was verified by simulating the dynamic data flow scenarios of melon harvesting. Control algorithms were evaluated on measured melon locations.

Design of an Agricultural Robot for Harvesting Melons

The performance of an agricultural robot has been evaluated through simulation to determine design parameters for a robotic melon harvester. Animated, visual simulation provided a powerful tool to initiate the evaluation of alternative designs. To quantify the many, closely-related design parameters, numerical simulation tools were developed and applied. Simulations using measured cantaloupe locations revealed the effect of design parameters (configuration, number of arms, and actuator speeds) on the average cycle time. Simulation results predicted that a Cartesian robot would perform faster than a cylindrical robot for the melon harvesting task. Activating two arms in tandem was the fastest configuration evaluated. Additional sets of melon locations were stochastically generated from distributions of the field data to determine performance for planting distances between 25 and 125 cm. The fastest cycle time was achieved for an experimental cultural practice that consisted of one plant on each half row in an alternating sequence with 125 cm planting distance. The performance of the robotic melon harvester was found to be highly dependent on the picking time, actuator speeds and planting distance.