Download or read book Mobile High throughput Phenotyping Using Watershed Segmentation Algorithm written by Shravan Dammannagari Gangadhara and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This research is a part of BREAD PHENO, a PhenoApps BREAD project at K-State which combines contemporary advances in image processing and machine vision to deliver transformative mobile applications through established breeder networks. In this platform, novel image analysis segmentation algorithms are being developed to model and extract plant phenotypes. As a part of this research, the traditional Watershed segmentation algorithm has been extended and the primary goal is to accurately count and characterize the seeds in an image. The new approach can be used to characterize a wide variety of crops. Further, this algorithm is migrated into Android making use of the Android APIs and the first ever user-friendly Android application implementing the extended Watershed algorithm has been developed for Mobile field-based high-throughput phenotyping (HTP).

Download or read book Artificial Intelligence and Image Processing Applications for High throughput Phenotyping written by Venkata Siva Kumar Margapuri and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The areas of Computer Vision and Scientific Computing have witnessed rapid growth in the last decade with the fields of industrial robotics, automotive and healthcare acting as the primary vehicles for research and advancement. However, related research in other fields, such as agriculture, remains an understudied problem. This dissertation explores the application of Computer Vision and Scientific Computing in an agricultural domain known as High-throughput Phenotyping (HTP). HTP is the assessment of complex seed traits such as growth, development, tolerance, resistance, ecology, yield, and the measurement of parameters that form more complex traits. The dissertation makes the following contributions: The first contribution is the development of algorithms to estimate morphometric traits such as length, width, area, and seed kernel count using 3-D graphics and static image processing, and the extension of existing algorithms for the same. The second contribution is the development of lightweight frameworks to aid in synthetic image dataset creation and image cropping for deep neural networks in HTP. Deep neural networks require a plethora of training data to yield results of the highest quality. However, no such training datasets are readily available for HTP research, especially on seed kernels. The proposed synthetic image generation framework helps generate a profusion of training data at will to train neural networks from a meager samples of seed kernels. Besides requiring large quantities of data, deep neural networks require the input to be a certain size. However, not all available data are in the size required by the deep neural networks. The proposed image cropper helps to resize images without resulting in any distortion, thereby, making image data fit for consumption. The third contribution is the design and analysis of supervised and self-supervised neural network architectures trained on synthetic images to perform the tasks of seed kernel classification, counting and morphometry. In the area of supervised image classification, state-of-the-art neural network models of VGG-16, VGG-19 and ResNet-101 are investigated. A Simple framework for Contrastive Learning of visual Representations (SimCLR) [137], Momentum Contrast (MoCo) [55] and Bootstrap Your Own Latent (BYOL) [123] are leveraged for self-supervised image classification. The instance-based segmentation deep neural network models of Mask R-CNN and YOLO are utilized to perform the tasks of seed kernel classification, segmentation and counting. The results demonstrate the feasibility of deep neural networks for their respective tasks of classification and instance segmentation. In addition to estimating seed kernel count from static images, algorithms that aid in seed kernel counting from videos are proposed and analyzed. Proposed is an algorithm that creates a slit image which can be analyzed to estimate seed count. Upon the creation of the slit image, the video is no longer required to estimate seed count, thereby, significantly lowering the computational resources required for the estimation. The fourth contribution is the development of an end-to-end, automated image capture system for single seed kernel analysis. In addition to estimating length and width from 2-D images, the proposed system estimates the volume of a seed kernel from 2-D images using the technique of volume sculpting. The relative standard deviation of the results produced by the proposed technique is lower (better) than the relative standard deviation of the results produced by volumetric estimation using the ellipsoid slicing technique. The fifth contribution is the development of image processing algorithms to provide feature enhancements to mobile applications to improve upon on-site phenotyping capabilities. Algorithms for two features of high value namely, leaf angle estimation and fractional plant cover estimation are developed. The leaf angle estimation feature estimates the angle between stem and leaf for images captured using mobile phone cameras whereas fractional plant cover is to determine companion plants i.e., plants that are able to co-exist and mutually benefit. The proposed techniques, frameworks and findings lay a solid foundation for future Computer Vision and Scientific Computing research in the domain of agriculture. The contributions are significant since the dissertation not only proposes techniques, but also develops low-cost end-to-end frameworks to leverage the proposed techniques in a scalable fashion.

Download or read book High Throughput Crop Phenotyping written by Jianfeng Zhou and published by Springer Nature. This book was released on 2021-07-17 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book High Throughput Plant Phenotyping written by Argelia Lorence and published by Springer Nature. This book was released on 2022-07-27 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume looks at a collection of the latest techniques used to quantify the genome-by-environment-by-management (GxExM) interactions in a variety of model and plant crops. The chapters in this book are organized into five parts. Part One discusses high-throughput plant phenotyping (HTPP) protocols for plants growing under controlled conditions. Part Two present novel algorithms for extracting data from seed images, color analysis from fruits, and other digital readouts from 2D objects. Part Three covers molecular imaging protocols using PET and X-ray approaches, and Part Four presents a collection of HTPP techniques for crops growing under field conditions. The last part focuses on molecular analysis, metabolomics, network analysis, and statistical methods for the quantitative genetic analysis of HTP data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and practical, High-Throughput Plant Phenotyping: Review and Protocols is a valuable resource for both novice and expert researchers looking to learn more about this important field. Chapter 21 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Download or read book Big Data Analytics in High throughput Phenotyping written by Chaney Lee Courtney and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As the global population rises, advancements in plant diversity and crop yield is necessary for resource stability and nutritional security. In the next thirty years, the global population will pass 9 billion. Genetic advancements have become inexpensive and widely available to address this issue; however, phenotypic acquisition development has stagnated. Plant breeding programs have begun to support efforts in data mining, computer vision, and graphics to alleviate the gap from genetic advancements. This dissertation creates a bridge between computer vision research and phenotyping by designing and analyzing various deep neural networks for concrete applications while presenting new and novel approaches. The significant contributions are research advancements to the current state-of-the-art in mobile high-throughput phenotyping (HTP), which promotes more efficient plant science workflow tasks. Novel tools and utilities created for automatic code generation, maintenance, and source translation are featured. Promoted tools replace boiler-plate segments and redundant tasks. Finally, this research investigates various state-of-the-art deep neural network architectures to derive methods for object identification and enumeration. Seed kernel counting is a crucial task in the plant research workflow. This dissertation explains techniques and tools for generating data to scale training. New dataset creation methodologies are debuted and aim to replace the classical approach to labeling data. Although HTP is a general topic, this research focuses on various grains and plant-seed phenotypes. Applying deep neural networks to seed kernels for classification and object detection is a relatively new topic. This research uses a novel open-source dataset that supports future architectures for detecting kernels. State-of-the-art pre-trained regional convolutional neural networks (RCNN) perform poorly on seeds. The proposed counting architectures outperform the models above by focusing on learning a labeled integer count rather than anchor points for localization. Concurrently, pre-trained models on the seed dataset, a composition of geometrically primitive-like objects, boasts improvements to evaluation metrics in comparison to the Common Object in Context (COCO) dataset. A widely accepted problem in image processing is the segmentation of foreground objects from the background. This dissertation shows that state-of-the-art regional convolutional neural networks (RCNN) perform poorly in cases where foreground objects are similar to the background. Instead, transfer learning leverages salient features and boosts performance on noisy background datasets. The accumulation of new ideas and evidence of growth for mobile computer vision surmise a bright future for data-acquisition in various fields of HTP. The results obtained provide horizons and a solid foundation for future research to stabilize and continue the growth of phenotypic acquisition and crop yield.

Download or read book High Throughput Field Phenotyping to Advance Precision Agriculture and Enhance Genetic Gain Volume II written by Andreas Hund and published by Frontiers Media SA. This book was released on 2024-03-01 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Research Topic is part of the High-Throughput Field Phenotyping to Advance Precision Agriculture and Enhance Genetic Gain series. The discipline of “High Throughput Field Phenotyping” (HTFP) has gained momentum in the last decade. HTFP includes a wide range of disciplines such as plant science, agronomy, remote sensing, and genetics; as well as biochemistry, imaging, computation, agricultural engineering, and robotics. High throughput technologies have substantially increased our ability to monitor and quantify field experiments and breeding nurseries at multiple scales. HTFP technology can not only rapidly and cost-effectively replace tedious and subjective ratings in the field, but can also unlock the potential of new, latent phenotypes representing underlying biological function. These advances have also provided the ability to follow crop growth and development across seasons at high and previously inaccessible spatial and temporal resolutions. By combining these data with measurements of all environmental factors affecting plant growth and yield (“Envirotyping”), genotypic-specific reaction norms and phenotypic plasticity may be elucidated.

Download or read book Fundamentals of Field Crop Breeding written by Devendra Kumar Yadava and published by Springer Nature. This book was released on 2022-05-05 with total page 1389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an advanced textbook and a reference book for the post-graduate plant-breeding students and the plant breeders. It consolidates fundamental concepts and also the latest advances in plant-breeding practices including development in crop genomics. It contains crop wise explanation on origin, reproduction, genetics of yield contributing traits, biotic and abiotic stresses, nutritional improvement and crop specific plant-breeding procedures and techniques. The chapters are planned to describe crop-focused breeding procedure for the major crop plants as per their economic importance. The recent developments in breeding of field crops have been reported. The recent progress made in mapping traits of economic importance has been critically reviewed for each crop. The progress made in markers assisted selected in few crops has been summarized. This book bridges the knowledge gap and bring to the researchers and students information on modern breeding tools for developing biotic and abiotic stress tolerant, climate resilient and micronutrient rich varieties of field crops. The chapters in book are contributed by experienced Plant Breeders.

Download or read book Plant Roots written by Yoav Waisel and published by . This book was released on 1996 with total page 1064 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of a standard resource, this book offers a state-of-the-art, multi-disciplinary presentation of plant roots. It examines structure and development, assemblage of root systems, metabolism and growth, stressful environments, and interactions at the rhizosphere. Reflecting the explosion of advances and emerging technologies in the field, the book presents developments in the study of root origin, composition, formation, and behavior for the production of novel pharmaceutical and medicinal compounds, agrochemicals, dyes, flavors, and pesticides. It details breakthroughs in genetics, molecular biology, growth substance physiology, biotechnology, and biomechanics.

Download or read book High Throughput Phenotyping in the Genomic Improvement of Livestock written by Fabyano Fonseca Silva and published by Frontiers Media SA. This book was released on 2021-08-03 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book High Throughput Field Phenotyping to Advance Precision Agriculture and Enhance Genetic Gain written by Urs Schmidhalter and published by Frontiers Media SA. This book was released on 2021-08-10 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Machine Vision and Machine Learning for Plant Phenotyping and Precision Agriculture written by Huajian Liu and published by Frontiers Media SA. This book was released on 2024-01-18 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mobile Applications for High throughput Seed Characterization written by Siddharth Amaravadi and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Kansas State University is a world leader in the study of small grain genetics to develop new varieties which tolerate a wide range of environmental conditions. A phenotype is a composite of a plants observable traits. Several mobile applications, called PhenoApps, have been developed for field-based, high-throughput phenotyping (HTP) to advance plant breeding programs around the world. These applications require novel image analysis algorithms to be developed to model and extract plant phenotypes. Some of the first algorithms developed were focused on using static image analysis to count and characterize a wide variety of seeds in a single image with a static colored background. This thesis describes both a static algorithm and development of a hopper system for a dynamic, real-time algorithm to accurately count and characterize seeds using a modest mobile device. The static algorithm analyzes a single image of a particular seed sample, captured on a mobile device; whereas, the dynamic algorithm analyzes multiple frames from the video input of a mobile device in real time. Novel 3D models are designed and printed to set a steady flow rate for the seeds, but the analysis is also completed to consider seeds flowing at variable rates and to determine the range of allowable flow rates and achievable precision for a wide variety of seeds. Both algorithms have been implemented in user-friendly mobile applications for realistic, field-based use. A plant breeder can use the applications to both count and characterize a smaller sample using the static approach or a larger sample using the dynamic approach, with seeds sampled in real time without the need to analyze multiple static images. There are many directions for future research to enhance the algorithms performance and accuracy.

Download or read book High Throughput Phenotyping in Plants written by Jennifer Normanly and published by Humana Press. This book was released on 2017-04-30 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic approaches to understanding plant growth and development have always benefitted from screens that are simple, quantitative and rapid. Visual screens and morphometric analysis have yielded a plethora of interesting mutants and traits that have provided insight into complex regulatory pathways, and yet many genes within any given plant genome remain undefined. The premise underlying High Throughput Phenotyping in Plants: Methods and Protocols is that the higher the resolution of the phenotype analysis the more likely that new genes and complex interactions will be revealed. The methods described in this volume can be generally classified as quantitative profiling of cellular components, ranging from ions to small molecule metabolites and nuclear DNA, or image capture that ranges in resolution from chlorophyll fluorescence from leaves and time-lapse images of seedling shoots and roots to individual plants within a population at a field site. Written in the successful Methods in Molecular BiologyTM series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and easily accessible, High Throughput Phenotyping in Plants: Methods and Protocols serves as an invaluable guide to plant researchers and all scientists who wish to better understand plant growth and development.

Download or read book Phenomics written by John Doonan and published by Frontiers Media SA. This book was released on 2018-11-08 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Phenomics" is an emerging area of research whose aspiration is the systematic measurement of the physical, physiological and biochemical traits (the phenome) belonging to a given individual or collection of individuals. Non-destructive or minimally invasive techniques allow repeated measurements across time to follow phenotypes as a function of developmental time. These longitudinal traits promise new insights into the ways in which crops respond to their environment including how they are managed. To maximize the benefit, these approaches should ideally be scalable so that large populations in multiple environments can be sampled repeatedly at reasonable cost. Thus, the development and validation of non-contact sensing technologies remains an area of intensive activity that ranges from Remote Sensing of crops within the landscape to high resolution at the subcellular level. Integration of this potentially highly dimensional data and linking it with variation at the genetic level is an ongoing challenge that promises to release the potential of both established and under-exploited crops.

Download or read book State of the art Technology and Applications in Crop Phenomics written by Wanneng Yang and published by Frontiers Media SA. This book was released on 2021-12-01 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book IPPS 2022 Plant Phenotyping for a Sustainable Future written by Ulrich Schurr and published by Frontiers Media SA. This book was released on 2024-03-06 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book TILLING and Eco TILLING for Crop Improvement written by Anjanabha Bhattacharya and published by Springer Nature. This book was released on 2023-07-10 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book is a comprehensive compilation of deliberations in the field of agriculture, food security, climate resilient crops and on the relevance of the popular TILLING technique in the era of precise genome editing (CRISPR/Cas9). This book particularly deliberates on new developments in this field, such as, induced mutagenesis techniques, mutagenesis in somatic tissues, bio-informatics analysis and gene mining. This volume also focuses on next generation mutation detection techniques, exome capture, forward and reverses genetics, trait selection and, finally deliberates on the future of TILLING in plant breeding and product development. TILLING (Targeting Induced Local Lesions in Genome) is a popular molecular biology technique for detecting polymorphism in a mutagenized population. Eco-TILLING refers to natural TILLING. This technique can be applied to a wider range of crops. Products developed through TILLING are not regulated throughout the world, thus having a wider acceptance among various stakeholders. This volume is timely and looks into the updated aspects of mutagenesis, TILLING, Eco-TILLING along with OMIC tools, their amalgamated applications towards crop improvement. This book contains 11 chapters and 250 pages authored by globally reputed scientists on the field of mutagenesis, TILLING and Eco-TILLING. This book is useful for research scholars, students, teachers and scientists in the academia, policy makers, relevant public, plant breeding companies, private companies and cooperatives interested in understanding or applying mutagenesis, TILLING for editing gene of interest and develop new products in agriculture.