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Author : Valerio Giuffrida,Hanno Scharr,Ian Stavness
Publisher : Frontiers Media SA
Page : 265 pages
File Size : 41,6 Mb
Release : 2023-06-06
Category : Science
ISBN : 9782832510650
Author : Huajian Liu,Zhanyou Xu
Publisher : Frontiers Media SA
Page : 423 pages
File Size : 44,6 Mb
Release : 2024-01-18
Category : Science
ISBN : 9782832542934
Plant phenotyping (PP) describes the physiological and biochemical properties of plants affected by both genotypes and environments. It is an emerging research field that is assisting the breeding and cultivation of new crop varieties to be more productive and resilient to challenging environments. Precision agriculture (PA) uses sensing technologies to observe crops and then manage them optimally to ensure that they grow in healthy conditions, have maximum productivity, and have minimal negative effects on the environment. Traditionally, the observation of plant traits heavily relies on human experts which is labor intensive, time-consuming, and subjective. Automatic crop traits measurement in PP and PA are two different fields, but they share the same sensing and data processing technologies in many respects. Recently, driven by computer and sensor technologies, machine vision (MV) and machine learning (ML) have contributed to accurate, high-throughput, and nondestructive plant phenotyping and precision agriculture. However, these technologies are still in their infant stage and there are many challenges and questions related to them that still need to be addressed. The goal of this Research Topic is to provide a platform to share the latest research results on the application of MV and ML for PP and PA. It aims to highlight cutting-edge technologies, bottle-necks, and future research directions for MV and ML in crop breeding, crop cultivation, disease management, weed control, and pest control.
Author : Ashok Samal,Sruti Das Choudhury
Publisher : CRC Press
Page : 347 pages
File Size : 49,5 Mb
Release : 2020-10-21
Category : Computers
ISBN : 9781351709996
Domesticated crops are the result of artificial selection for particular phenotypes or, in some cases, natural selection for an adaptive trait. Plant traits can be identified through image-based plant phenotyping, a process that was, until recently, strenous and time-consuming. Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques, using computer vision and imaging technologies. These methodologies provide an automated, non-invasive, and scalable mechanism by which to define and collect plant phenotypes. Beautifully illustrated, with numerous color images, the book focuses on phenotypes measured from individual plants under controlled experimental conditions, which are widely available in high-throughput systems. Features: Presents methodologies for image processing, including data-driven and machine learning techniques for plant phenotyping. Features information on advanced techniques for extracting phenotypes through images and image sequences captured in a variety of modalities. Includes real-world scientific problems, including predicting yield by modeling interactions between plant data and environmental information. Discusses the challenge of translating images into biologically informative quantitative phenotypes. A practical resource for students, researchers, and practitioners, this book is invaluable for those working in the emerging fields at the intersection of computer vision and plant sciences.
Author : Yongliang Qiao,João Valente,Yu Jiang,Zhao Zhang,Dongjian He,Daobilige Su
Publisher : Frontiers Media SA
Page : 266 pages
File Size : 53,8 Mb
Release : 2023-07-03
Category : Science
ISBN : 9782832527450
Author : Jianfeng Zhou,Henry T. Nguyen
Publisher : Springer Nature
Page : 249 pages
File Size : 51,7 Mb
Release : 2021-07-17
Category : Science
ISBN : 9783030737344
This book provides an overview of the innovations in crop phenotyping using emerging technologies, i.e., high-throughput crop phenotyping technology, including its concept, importance, breakthrough and applications in different crops and environments. Emerging technologies in sensing, machine vision and high-performance computing are changing the world beyond our imagination. They are also becoming the most powerful driver of the innovation in agriculture technology, including crop breeding, genetics and management. It includes the state of the art of technologies in high-throughput phenotyping, including advanced sensors, automation systems, ground-based or aerial robotic systems. It also discusses the emerging technologies of big data processing and analytics, such as advanced machine learning and deep learning technologies based on high-performance computing infrastructure. The applications cover different organ levels (root, shoot and seed) of different crops (grains, soybean, maize, potato) at different growth environments (open field and controlled environments). With the contribution of more than 20 world-leading researchers in high-throughput crop phenotyping, the authors hope this book provides readers the needed information to understand the concept, gain the insides and create the innovation of high-throughput phenotyping technology.
Author : Achim Walter
Publisher : Unknown
Page : 0 pages
File Size : 51,9 Mb
Release : 2022
Category : Crop science
ISBN : 1786768577
Author : Wanneng Yang,John Doonan,Tony Pridmore,Malcolm John Hawkesford,Ji Zhou
Publisher : Frontiers Media SA
Page : 267 pages
File Size : 46,7 Mb
Release : 2021-12-01
Category : Science
ISBN : 9782889717545
Author : S Dutta Gupta,Yasuomi Ibaraki
Publisher : CRC Press
Page : 422 pages
File Size : 55,9 Mb
Release : 2014-09-17
Category : Science
ISBN : 9781466583016
The application of imaging techniques in plant and agricultural sciences had previously been confined to images obtained through remote sensing techniques. Technological advancements now allow image analysis for the nondestructive and objective evaluation of biological objects. This has opened a new window in the field of plant science. Plant Image Analysis: Fundamentals and Applications introduces the basic concepts of image analysis and discusses various techniques in plant imaging, their applications, and future potential. Several types of imaging techniques are discussed including RGB, hyperspectral, thermal, PRI, chlorophyll fluorescence, ROS, and chromosome imaging. The book also covers the use of these techniques in assessing plant growth, early detection of disease and stress, fruit crop yield, plant chromosome analysis, plant phenotyping, and nutrient status both in vivo and in vitro. The book is an authoritative guide for researchers and those teaching in the fields of stress physiology, precision agriculture, agricultural biotechnology, and cell and developmental biology. Graduate students and professionals using machine vision in plant science will also benefit from this comprehensive resource.
Author : Mohammad Shorif Uddin,Jagdish Chand Bansal
Publisher : Unknown
Page : 0 pages
File Size : 40,9 Mb
Release : 2022
Category : Electronic
ISBN : 9811699925
This book is as an extension of previous book "Computer Vision and Machine Learning in Agriculture" for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.
Author : Daoliang Li,Chunjiang Zhao
Publisher : Springer
Page : 559 pages
File Size : 50,5 Mb
Release : 2019-01-09
Category : Computers
ISBN : 9783030061371
The two volumes IFIP AICT 545 and 546 constitute the refereed post-conference proceedings of the 11th IFIP WG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2017, held in Jilin, China, in August 2017. The 100 revised papers included in the two volumes were carefully reviewed and selected from 282 submissions. They cover a wide range of interesting theories and applications of information technology in agriculture. The papers focus on four topics: Internet of Things and big data in agriculture, precision agriculture and agricultural robots, agricultural information services, and animal and plant phenotyping for agriculture.
Author : Mohammad Shorif Uddin,Jagdish Chand Bansal
Publisher : Springer Nature
Page : 269 pages
File Size : 45,5 Mb
Release : 2022-03-13
Category : Technology & Engineering
ISBN : 9789811699917
This book is as an extension of previous book “Computer Vision and Machine Learning in Agriculture” for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.
Author : Daoliang Li,Chunjiang Zhao
Publisher : Springer
Page : 521 pages
File Size : 42,8 Mb
Release : 2019-01-08
Category : Computers
ISBN : 9783030061791
The two volumes IFIP AICT 545 and 546 constitute the refereed post-conference proceedings of the 11th IFIP WG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2017, held in Jilin, China, in August 2017. The 100 revised papers included in the two volumes were carefully reviewed and selected from 282 submissions. They cover a wide range of interesting theories and applications of information technology in agriculture. The papers focus on four topics: Internet of Things and big data in agriculture, precision agriculture and agricultural robots, agricultural information services, and animal and plant phenotyping for agriculture.
Author : Man Zhang,Han Li,Wenyi Sheng,Ruicheng Qiu,Zhao Zhang
Publisher : Springer Nature
Page : 144 pages
File Size : 53,8 Mb
Release : 2023-12-29
Category : Technology & Engineering
ISBN : 9789819979271
This book focuses on state-of-the-art sensing and automation technologies for field crops and in-house product production and provides a lot of innovative knowledge on image processing, AI algorithms and applications in agriculture, and robotics. This book provides undergraduate or graduate students with take-away knowledge for unmanned agricultural production, including but not limited to corn disease detection, wheat head detection and counting, and soil nutrient condition monitoring. The first three chapters focus on reviewing plant phenotyping sensing technology and robotics and soil nutrient monitoring, followed by in-house crop sensing robotics. Then two case studies on corn and the other two case studies on wheat are presented.
Author : Ashok Samal,Sruti Das Choudhury
Publisher : CRC Press
Page : 271 pages
File Size : 51,5 Mb
Release : 2020-10-21
Category : Computers
ISBN : 9781351709989
Domesticated crops are the result of artificial selection for particular phenotypes or, in some cases, natural selection for an adaptive trait. Plant traits can be identified through image-based plant phenotyping, a process that was, until recently, strenous and time-consuming. Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques, using computer vision and imaging technologies. These methodologies provide an automated, non-invasive, and scalable mechanism by which to define and collect plant phenotypes. Beautifully illustrated, with numerous color images, the book focuses on phenotypes measured from individual plants under controlled experimental conditions, which are widely available in high-throughput systems. Features: Presents methodologies for image processing, including data-driven and machine learning techniques for plant phenotyping. Features information on advanced techniques for extracting phenotypes through images and image sequences captured in a variety of modalities. Includes real-world scientific problems, including predicting yield by modeling interactions between plant data and environmental information. Discusses the challenge of translating images into biologically informative quantitative phenotypes. A practical resource for students, researchers, and practitioners, this book is invaluable for those working in the emerging fields at the intersection of computer vision and plant sciences.
Author : Lourdes Agapito,Michael M. Bronstein,Carsten Rother
Publisher : Springer
Page : 396 pages
File Size : 46,7 Mb
Release : 2015-03-18
Category : Computers
ISBN : 9783319162201
The four-volume set LNCS 8925, 8926, 8927, and 8928 comprises the thoroughly refereed post-workshop proceedings of the Workshops that took place in conjunction with the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 203 workshop papers were carefully reviewed and selected for inclusion in the proceedings. They where presented at workshops with the following themes: where computer vision meets art; computer vision in vehicle technology; spontaneous facial behavior analysis; consumer depth cameras for computer vision; "chalearn" looking at people: pose, recovery, action/interaction, gesture recognition; video event categorization, tagging and retrieval towards big data; computer vision with local binary pattern variants; visual object tracking challenge; computer vision + ontology applies cross-disciplinary technologies; visual perception of affordance and functional visual primitives for scene analysis; graphical models in computer vision; light fields for computer vision; computer vision for road scene understanding and autonomous driving; soft biometrics; transferring and adapting source knowledge in computer vision; surveillance and re-identification; color and photometry in computer vision; assistive computer vision and robotics; computer vision problems in plant phenotyping; and non-rigid shape analysis and deformable image alignment. Additionally, a panel discussion on video segmentation is included.