Download or read book Over the row Machine Vision System for Improved Apple Crop load Estimation written by Aleana Gongal and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Towards Unmanned Apple Orchard Production Cycle written by Zhao Zhang and published by Springer Nature. This book was released on 2024-01-12 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides the most recent technology for sensing and automation in apple production cycle in terms of bagging robotics, flower pollination robotics, pruning robotics, and harvest robotics. It does not only summarize the development of technology progress, but also discuss the future trend for unmanned apple production cycle. Though apple production still mainly relies on manual labor, a huge number of innovative technologies emerge during the past years, which pave the road for unmanned apple orchard management. A book summarizing all these new and innovative technologies is needed, to provide an easy approach to understand this field quickly and comprehensively, which drives the publication of this book. This book is a useful reference for students, researchers, and practitioners in the field of apple production.

Download or read book Advances in Fruit Growing Systems as a Key Factor of Successful Production written by Geza Bujdoso and published by Frontiers Media SA. This book was released on 2024-07-08 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fruit production industry has been facing many challenges recently. For example, climate change, the introduction of new fruit-bearing species into production, traits of novel-bred fruit cultivars, innovations in orchard systems, rootstock/scion interactions, effects of fruit-growing technology and growing systems on yield, growing systems on yield, the appearance of new pathogens and pests, as well as birds and mammals in orchards, organic production, fruit quality and compounds, regulatory framework, high labour input, etc. Farmers need to have more up-to-date information and answers regarding these challenges. Modern fruit production is based on an adequate fruit-growing system, supported by many elements that complete this production.

Download or read book Metaheuristics and Optimization in Computer and Electrical Engineering written by Navid Razmjooy and published by Springer Nature. This book was released on 2023-11-08 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses different methods of modifying the original metaheuristics and their application in computer and electrical engineering. As the race to develop advanced technology accelerates, a new era of "metaheuristics" has emerged. Through researched-based techniques and collaborative problem-solving, this book helps engineers to find efficient solutions to their engineering challenges. With the help of an expert guide and the collective knowledge of the engineering community, this comprehensive guide shows readers how to use machine learning and other AI techniques to reinvent smart engineering. From understanding the fundamentals to mastering the latest metaheuristics models, this guide provides with the skills and knowledge that need to stay ahead in the technology race. In the previous volume, authors focused on the application of original metaheuristics on electrical and computer sciences. This volume learns how AI and modified metaheuristics can be used to optimize algorithms and create more efficient electrical engineering designs. It gets insights on how data can be effectively processed and discover new techniques for creating sophisticated automation systems. It maximizes the potential of readers’ computer and electrical engineering projects with powerful metaheuristics and optimization techniques.

Download or read book Advances in Distributed Computing and Machine Learning written by Suchismita Chinara and published by Springer Nature. This book was released on 2023-06-27 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of peer-reviewed best selected research papers presented at the Fourth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2023), organized by Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India, during 15–16 January 2023. This book presents recent innovations in the field of scalable distributed systems in addition to cutting edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.

Download or read book In field Imaging of Apple Orchards Using Stereo Vision for Improved Fruit Size and Yield Estimation written by Omeed Mirbod and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Apple fruit size plays an integral role in management decision-making for orchards throughout the growing season. Early in the season, fruit size is used to choose effective chemical thinning applications. At mid-season, sample measurements can be used to estimate fruit size at harvest. Towards end of the season, fruit size and fruit count can help to better estimate yield, harvest operation costs, and packout. Fruit size measurements are currently done by hand which can be costly and time-consuming. In this study, a machine vision system was developed to automate the process of detection and sizing of apples in an orchard. The objectives of the study were to: (1) develop a stereo vision system capable of sizing fruit at different stages of maturity by capturing high-quality images resistant to lighting variability and motion blur, (2) develop computer vision algorithms to find the metric diameter and surface area of apples, and (3) analyze correlation between estimated fruit size and actual fruit diameter and weight. The developed system used a high-resolution stereo camera pair combined with an active light source to capture images in field conditions. A deep neural network model, Mask R-CNN, was used to segment out apples in images. Depth perception from the stereo camera system was used to convert pixel surface area of each fruit to metric size measurements. The machine vision system took images of apples in a laboratory setting to determine sizing accuracy performance and was also taken to an orchard for field testing. During the growing season, ground truth measurements of fruit diameter were collected from 30 trees as well as their harvest weights. The system demonstrated strong capability for accurately sizing fruit in a controlled environment, achieving an R2 value of 0.98 for two apple varieties when compared against fruit weight. In the field, the result was more varied for different months of the growing season, achieving a high accuracy in August (R2 = 0.75) and a low accuracy (R2 = 0.53) in June when comparing ground truth diameter measurements and the imaging system's measurements.

Download or read book Advanced Automation for Tree Fruit Orchards and Vineyards written by Stavros G. Vougioukas and published by Springer Nature. This book was released on 2023-05-23 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern tree fruit orchards and vineyards constitute complex production systems that are exposed to highly dynamic and stochastic natural, financial and societal forces, and face demands for increased production using fewer resources, with reduced environmental impact. Successful operation of orchards and vineyards under these conditions is practically impossible without careful and extensive use of state-of-the-art automation technologies and careful planning of future operations (e.g., training systems when replanting) that can be enabled by knowledge of emerging technologies and future trends. Also, improvement of existing automation technologies and development of novel future systems cannot be accomplished without a working understanding of the tree and vine biological production systems, their management needs, and the capabilities and limitations of existing automation systems. The book aims to provide the necessary knowledge to achieve the above goals in a way that can engage readers without engineering or horticultural backgrounds.

Download or read book Machine Vision System for Robotic Apple Harvesting in Fruiting Wall Orchards written by Abhisesh Silwal and published by . This book was released on 2016 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation focuses on the study and evaluation of a machine vision and an integrated robotic system for automated harvesting of apples grown in modern fruiting wall orchards. The machine vision algorithm designed to work in orchard environment accurately detected apples growing individually as well as in heavy clusters under variable natural lighting conditions. A pragmatic approach to harvesting (also called hierarchical approach) showed that 98% of the fruit could be detected with iterative imaging and harvesting of most visible fruits. The integrated robotic system with global camera and custom built seven degrees of freedom manipulator successfully picked 84% of attempted fruit with 6 seconds of average harvest time per fruit. This approach of selective apple harvesting with a global camera system and low-cost manipulator show a huge potential for cost-effective robotic solutions for harvesting fresh market apples. However, several limitations still remain to be addressed for commercialization.

Download or read book Advancing Robotic Approaches to Precision Apple Crop Load Management in Blossom Thinning Stage written by Xinyang Mu and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation project focuses on the development of a robotic system aimed at advancing the field of precision apple crop load management during the critical blossom thinning stage. The research encompasses three primary objectives, each addressing crucial aspects of robotic technology integration for more efficient and sustainable apple orchard management. The first objective was to develop a Mask R-CNN-based instance segmentation vision system tailored specifically for the detection and identification of apple flowers and king flowers within the orchard environment. Achieving precision in blossom thinning requires accurate identification of apple flowers, as over-thinning or under-thinning can lead to suboptimal crop yield and quality. The machine vision system employs advanced deep learning techniques to enhance the accuracy and robustness of apple flower cluster detection, providing an essential foundation for subsequent robotic integration. The overall precision and recall of apple flower segmentation achieved 78.1% and 71.3% respectively. The king flower detection accuracy varied from 98.7% to 65.6% with respect to the flower stages ranging from 20% to 80% blooming. This information was used to calculate the percentage of the king flowers and their distribution in the tree canopy, which provides decision-making information for robotic blossom thinning. The second objective focused on the integration of the developed vision system with a cartesian robotic manipulator, enabling precise and targeted apple chemical blossom thinning. Traditional methods of blossom thinning often lack the required precision, leading to chemical waste and potential damage to the apple trees. By combining computer vision with robotics, this objective aims to optimize the thinning process, ensuring that only the targeted blossoms are sprayed with chemicals. In the field test conducted in 2022, the integrated robotic system used 2.3 L of chemical thinner to finish the chemical thinning for 18 apple trees. Followed by the boom sprayer and air-blast sprayer with 4.2 and 6.8 L usage respectively. The cartesian target spraying system also obtained an average fruit set of 2.4 per cluster after thinning, which was comparable to that of the air-blast sprayer. The results showed that the robotic thinning system saved 66.7% and 45.5% of chemicals compared to the air-blast sprayer and boom-typed sprayers respectively, while achieving a similar fruit set per cluster. The outcomes of the study provided guidance for developing a full-scale robotic chemical thinning system for apple orchards. The third objective of this research involved the integration of the vision system with a Husky A200 Unmanned Ground Vehicle (UGV) and the establishment of communication between a Real-Time Kinematic (RTK) GPS system and the vision system. This integration is crucial for enabling efficient autonomous navigation of the UGV within the apple orchard, ensuring that the robot can navigate with centimeter-level accuracy. The fusion of GPS data with the vision system's output allows the UGV to make informed decisions about its path and tasks, further enhancing the precision and efficiency of apple crop load management. The results of the field test showed that the UGV-based spraying system demonstrated a 68.2% reduction in chemical usage compared to the air-blast sprayer and exhibited a 43% faster operation speed than the cartesian target sprayer, while attaining a comparable fruit set per cluster. In summary, this study addressed three objectives to advance robotic approaches for precision apple crop load management during the blossom thinning stage. The development of a real-time vision system for apple flower cluster detection, its integration with a cartesian robotic manipulator for precise chemical thinning, and integration of the vision system with the Husky A200 UGV and RTK GPS represent a further step towards autonomous apple crop load management. This research not only contributes to the advancement of agricultural robotics but also holds promise for increasing crop quality, reducing chemical usage, and promoting automation in precision apple crop load management.

Download or read book Encyclopedia of Digital Agricultural Technologies written by Qin Zhang and published by Springer Nature. This book was released on 2023-10-11 with total page 1636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital agriculture is an emerging concept of modern farming that refers to managing farms using modern Engineering, Information and Communication Technologies (EICT) aiming at increasing the overall efficiency of agricultural production, improving the quantity and quality of products, and optimizing the human labor required and natural resource consumption in operations. This encyclopedia is designed to collect the summaries of knowledge on as many as subjects or aspects relevant to ECIT for digital agriculture, present such knowledge in entries, and arrange them alphabetically by articles titles. Springer Major Reference Works platform offers Live Update capability. Our reference work takes full advantage of this feature, which allows for continuous improvement or revision of published content electronically. The Editorial Board Dr. Irwin R. Donis-Gonzalez, University of California Davis, Dept. Biological and Agricultural Engineering, Davis, USA (Section: Postharvest Technologies) Prof. Paul Heinemann, Pennsylvania State University, Department Head of Agricultural and Biological Engineering, PA, USA (Section: Technologies for Crop Production) Prof. Manoj Karkee, Washington State University, Center for Precision and Automated Agricultural Systems, Washington, USA (Section: Robotics and Automation Technologies) Prof. Minzan Li, China Agricultural University, Beijing, China (Section: Precision Agricultural Technologies) Prof. Dikai Liu, University of Technology Sydney (UTS),Faculty of Engineering & Information Technologies, Broadway NSW, Australia (Section: AI, Information and Communication Technologies) Prof. Tomas Norton, University of Leuven, Dept. of Biosystems, Heverlee Leuven, Belgium (Section: Technologies for Animal and Aquatic Production) Dr. Manuela Zude-Sasse, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Precision Horticulture, Potsdam, Germany (Section: Engineering and Mechanization Technologies)

Download or read book Early Season Crop Load Estimation and Yield Prediction in Apple Orchards written by Thomas Dunn Jarvinen and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In apple production, early season yield predictions have applications in labordemand projections, packing-house inventory management, and sales planning. Tomake these predictions, fruit counts are a useful metric, but it is expensive tomeasure these by hand. To automate this process, a computer vision system usinga Faster R-CNN object detector was developed which detected immature fruit witha precision of 0.85 and a recall of 0.92, and detected mature fruit with a precisionof 0.92 and a recall of 0.82. However, for the purpose of counting fruit even ahighly accurate detector will fail to find many apples due to occlusion. It has beenproposed that analyzing video streams rather than single images could minimizeaccuracy loss due to occlusion. To this end, the CNN based object detector wasintegrated with a video multiple-object tracking algorithm to produce fruit countsfor early-season yield prediction. This system was demonstrated to be an accuratefruit counting system which is robust to variability in fruit maturity, and treestructure. Video based fruit counting was found to be a strong predictor of yield,predicting with R 2 = 0.81 when compared against harvest weight. The resultingyield prediction system was tested on trees with varying canopy depths to finda relationship between canopy density and prediction accuracy. No significantdifference was found in prediction accuracy over the different pruning severites.The resulting system has potential applications as an early season yield predictorin a commercial setting.

Download or read book Vision System for the Detection of Apples in the Green Fruit Stage written by Juan Arguijo and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study explores the development of a vision system for detecting and measuring the size of apples in the green fruit stage, aiming to aid in crop load management. Different camera positions and times of day were evaluated to maximize visible fruit detection. The camera was placed at three different positions relative to the tree: top, middle, and bottom, with the camera placed over 1 m from the tree. The next camera position was placing the camera closer to the tree, less than 1 m, to capture a series of images to be stitched together to create one image of the apple tree. The YOLOv5s model architecture, activation functions, and hyperparameters were changed and evaluated to determine a YOLOv5s model that increases the accuracy of green fruit detection. The results show that the original YOLOv5s model, with no changes made to the architecture, activation function, or hyperparameters, was the optimal model for green fruit detection with a precision score of 0.653, recall of 0.407, mean average precision of 0.454, and a F1 score of 0.501. However, the overall detection rates remained low, with large root mean square error (RMSE) for green fruit detections for all camera positions and time of day. Green fruit detection increased with the images stitched together, showing that the machine learning model could retrieve more information from the stitched images to detect green fruit. Fruit sizing also demonstrated a high mean absolute error (MAE). The outcomes of this study show the necessity for further research, including testing more robust architectures and refining the fruit sizing algorithm for precision in fruit measurement.

Download or read book Development of a Machine Vision based Yield Monitoring System for Vegetable Crops written by Amanda Boatswain Jacques and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Crop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer and machine vision have improved the detection, quality assessment and yield estimation processes for crops including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have yet to be fully developed. A machine vision-based yield monitor was designed to perform identification, size categorization and continuous counting of shallot onions in-situ during the harvesting process. The system is composed of a video logger and a global navigation satellite system (GNSS), coupled with computer software developed in Python. Computer vision analysis is performed within the tractor itself while an RGB camera positioned directly above the harvesting conveyor collects real time video data of the crops under natural sunlight conditions. Vegetables are segmented using Watershed segmentation, detected on the conveyor and then classified by size. Results showed that the system was able to correctly detect 62.6% of onions in a subsample of the dataset and resulted in a linear regression with a coefficient of determination (R2) of 0.49 between true and estimated counts. The software was also evaluated on its ability to classify the onions into 3 size categories (small, medium and large). A total of 55.9% of 271 analyzed onions were correctly categorized, with the highest performance achieved in the large class (73.3%), followed by the small class (58.7%) and medium class (44.4%). Based on the obtained results, occasional occlusion of vegetables and inconsistent lighting conditions were the main factors that inhibited performance. Finally, these geotagged images were used to map the size distribution of the shallot onions on a small section of the onion field. Although further enhancements are envisioned for the prototype system to improve overall detection and size classification, its modular and novel design allows it to be used to map a selection of crops including carrots, shallot onions, Chinese radish and lettuce crops. The system has the potential to benefit many producers of small vegetable crops by providing them with useful harvest information in real time that can significantly improve current harvesting logistics"--

Download or read book Agrindex written by and published by . This book was released on 1995 with total page 1390 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Video and Image Processing written by Thomas B. Moeslund and published by Springer Science & Business Media. This book was released on 2012-01-24 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents the fundamental concepts and methods for understanding and working with images and video in an unique, easy-to-read style which ensures the material is accessible to a wide audience. Exploring more than just the basics of image processing, the text provides a specific focus on the practical design and implementation of real systems for processing video data. Features: includes more than 100 exercises, as well as C-code snippets of the key algorithms; covers topics on image acquisition, color images, point processing, neighborhood processing, morphology, BLOB analysis, segmentation in video, tracking, geometric transformation, and visual effects; requires only a minimal understanding of mathematics; presents two chapters dedicated to applications; provides a guide to defining suitable values for parameters in video and image processing systems, and to conversion between the RGB color representation and the HIS, HSV and YUV/YCbCr color representations.

Download or read book Evaluation of Quality of Fruits and Vegetables written by Harold E. Pattee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acceptance or rejection of any edible commodity, whether it is raw or processed, is usually conditioned by sensory stimuli. The impact of these stimuli on the decision-making proce·ss is broadly termed sensory evaluation. Advances in sensory evaluation research have been slow in the past because of the human factor-the necessity to use highly trained sensory panels to conduct this research. High technology in strumentation and new understandings of sensory evaluations are now combining to make possible quantum jumps forward in sensory eval uation research. It is widely recognized that the sensory aspects of fruits and vegeta bles are affected by many factors, among them environment, variety, cultural practices, and handling practices. However, if one attempts to find a general reference or compilation of findings regarding this sub ject area there seems to be few, if any, available. A survey of the literature does suggest that in the past few years research into specific factors which influence the sensory aspects of fruits and vegetables has increased significantly. This increased interest in sensory research and the renewed national awareness of the value of research into pre and postharvest quality of fruits and vegetables prompted the Flavor Subdivision, Agricultural and Food Chemistry Division, American Chemical Society to sponsor a symposium entitled "Sensory Evalua tion of Fruits and Vegetables: Effect of Environment, Cultural Prac tices and Variety" during the 1982 meeting in Kansas City, Missouri.

Download or read book Plant Biodiversity Science in the Era of Artificial Intelligence written by Pierre Bonnet and published by Frontiers Media SA. This book was released on 2022-11-15 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: