Plant Phenotyping And Phenomics For Plant Breeding

As a consequence of the global climate change, both the reduction on yield potential and the available surface area of cultivated species will compromise the production of food needed for a constant growing population. There is consensus about the significant gap between world food consumption projected for the coming decades and the expected crop yield-improvements, which are estimated to be insufficient to meet the demand. The complexity of this scenario will challenge breeders to develop cultivars that are better adapted to adverse environmental conditions, therefore incorporating a new set of morpho-physiological and physico-chemical traits; a large number of these traits have been found to be linked to heat and drought tolerance. Currently, the only reasonable way to satisfy all these demands is through acquisition of high-dimensional phenotypic data (high-throughput phenotyping), allowing researchers with a holistic comprehension of plant responses, or ‘Phenomics’. Phenomics is still under development. This Research Topic aims to be a contribution to the progress of methodologies and analysis to help understand the performance of a genotype in a given environment.

This book represents a pioneer initiative to describe the new technologies available for next-generation phenotyping and applied to plant breeding. Over the last several years plant breeding has experienced a true revolution. Phenomics, i.e., high-throughput phenotyping using automation, robotics and remote data collection, is changing the way cultivars are developed. Written in an easy to understand style, this book offers an indispensable reference work for all students, instructors and scientists who are interested in the latest innovative technologies applied to plant breeding.

Identification of desirable genotypes with traits of interest is discernible for making genetic improvement of crop plants. In this direction, screening of a large number of germplasm for desirable traits and transfer of identified traits into agronomic backgrounds through recombination breeding is the common breeding approach. Although visual screening is easier for qualitative traits, its use is not much effective for quantitative traits and also for those, which are difficult to score visually. Therefore, it is imperative to phenotype the germplasm accessions and breeding materials precisely using high throughput phenomics tools for challenging and complex traits under natural, controlled and harsh environmental conditions. Realizing the importance of phenotyping data towards identification and utilization of a germplasm as donors, global scientific community has exerted increased focus on advancing phenomics in crop plants leading to development of a number of techniques and methodologies for screening of agronomic, physiological, and biochemical traits. These technologies have now become much advanced and entered the era of digital science. This book provides exhaustive information on various aspects related to phenotyping of crop plants and offers a most comprehensive reference on the developments made in traditional and high throughput phenotyping of agricultural crops.

Plant phenotyping is the thorough assessment of plant traits such as growth, development, adaptation, yield, quality, tolerance, resistance, architecture, and the basic measurement of individual quantitative parameters that form the basis for understanding of traits. Genetic approaches to understand plant growth and development have always benefitted from phenotyping techniques that are simple, rapid and measurable in units. The forward genetics approach is all about understanding the trait inheritance using the phenotypic data and in most cases it is the mutant phenotypes that formed the basis for understanding of gene functions. With rapid advancement of genotyping techniques, high throughput genotyping has become a reality at costs people never imagined to be that low, but the phenotypic methods did not receive same attention. However, without quality phenotyping data the genotyping data cannot be effectively put to use in plant improvement. Therefore efforts are underway to develop high-throughput phenotyping methods in plants to keep pace with revolutionary advancement in genotyping techniques to enhance the efficiency of crop improvement programs. Keeping this in mind, we described in this book the best phenomic tools available for trait improvement in some of the world’s most important crop plants.

Plant phenotyping is an emerging technology that involves the quantitative analysis of structural and functional plant traits. However, it is widely recognised that phenotyping needs to match similar advances in genetics if it is to not create a bottleneck in plant breeding. Advances in plant phenotyping for more sustainable crop production reviews the wealth of research on advances in plant phenotyping to meet this challenge, such as the development of new technologies including hyperspectral sensors such as LIDAR, NIR/SWIR, as well as alternative delivery/carrier systems, such as ground-based proximal distance systems and UAVs. The book details the development of plant phenotyping as a technique to analyse crop roots and functionality, as well as its use in understanding and improving crop response to biotic and abiotic stresses.

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.

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.