• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.483-493
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• 2022

It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R² of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.

• Korean Journal of Agricultural Science
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• v.47 no.1
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• pp.119-130
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• 2020

With the current rapid growth and increase in the world's population, the demand for nutritious food and fibers and fuel will increase. Therefore, there is a serious need for the use of breeding programs with the full potential to produce high-yielding crops. However, existing breeding techniques are unable to meet the demand criteria even though genotyping techniques have significantly progressed with the discovery of molecular markers and next-generation sequencing tools, and conventional phenotyping techniques lag behind. Well-organized high-throughput plant phenotyping platforms have been established recently and developed in different parts of the world to address this problem. These platforms use several imaging techniques and technologies to acquire data for quantitative studies related to plant growth, yield, and adaptation to various types of abiotic or biotic stresses (drought, nutrient, disease, salinity, etc.). Phenotyping has become an impediment in genomics studies of plant breeding. In recent years, phenomics, an emerging domain that entails characterizing the full set of phenotypes in a given species, has appeared as a novel approach to enhance genomics data in breeding programs. Imaging techniques are of substantial importance in phenomics. In this study, the importance of current imaging technologies and their applications in plant phenotyping are reviewed, and their advantages and limitations in phenomics are highlighted.

• Korean Journal of Agricultural Science
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• v.45 no.3
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• pp.317-323
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• 2018

The demand for crop production is increasingly becoming steeper due to the rapid population growth. As a result, breeding cycles should be faster than ever before. However, the current breeding methods cannot meet this requirement because traditional phenotyping methods lag far behind even though genotyping methods have been drastically developed with the advent of next-generation sequencing technology over a short period of time. Consequently, phenotyping has become a bottleneck in large-scale genomics-based plant breeding studies. Recently, however, phenomics, a new discipline involving the characterization of a full set of phenotypes in a given species, has emerged as an alternative technology to come up with exponentially increasing genomic data in plant breeding programs. There are many advantages for using new technologies in phenomics. Yet, the necessity of diverse man power and huge funding for cutting-edge equipment prevent many researchers who are interested in this area from adopting this new technique in their research programs. Currently, only a limited number of groups mostly in developed countries have initiated phenomic studies using high throughput methods. In this short article, we describe the strategies to compete with those advanced groups using limited resources in developing countries, followed by a brief introduction of high throughput phenotyping.

• Journal of Plant Biotechnology
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• v.48 no.3
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• pp.139-147
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• 2021

Since whole-genome duplication (WGD) of diploid Chrysanthemum nankingense and de novo assembly whole-genome of C. seticuspe have been obtained, they have afforded to perceive the diversity evolution and gene discovery in the improved investigation of chrysanthemum breeding. The robust tools of high-throughput identification and analysis of gene function and expression produce their vast importance in chrysanthemum genomics. However, the gigantic genome size and heterozygosity are also mentioned as the major obstacles preventing the chrysanthemum breeding practices and functional genomics analysis. Nonetheless, some of technological contemporaries provide scientific efficient and promising solutions to diminish the drawbacks and investigate the high proficient methods for generous phenotyping data obtaining and system progress in future perspectives. This review provides valuable strategies for a broad overview about the high-throughput identification, and molecular analysis of gene function and expression in chrysanthemum. We also contribute the efficient proposition about specific protocols for considering chrysanthemum genes. In further perspective, the proper high-throughput identification will continue to advance rapidly and advertise the next generation in chrysanthemum breeding.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• Genomics & Informatics
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• v.18 no.2
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• pp.14.1-14.11
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• 2020

Phenotyping is a major issue for wheat agriculture to meet the challenges of adaptation of wheat varieties to climate change and chemical input reduction in crop. The need to improve the reuse of observations and experimental data has led to the creation of reference ontologies to standardize descriptions of phenotypes and to facilitate their comparison. The scientific literature is largely under-exploited, although extremely rich in phenotype descriptions associated with cultivars and genetic information. In this paper we propose the Wheat Trait Ontology (WTO) that is suitable for the extraction and management of scientific information from scientific papers, and its combination with data from genomic and experimental databases. We describe the principles of WTO construction and show examples of WTO use for the extraction and management of phenotype descriptions obtained from scientific documents.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2002.04a
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• pp.19-25
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• 2002

Biotechnology in the 21st century will be driven by three emerging technologies: genomics, high-throughput biology, and bioinformatics. These technologies are complementary to one another. A large number of economically important crops are currently subjected to whole genome sequencing. Functional genomics for determining the functions of the genes comprising the given plant genome is under progress by using various means including phenotyping data from transgenic mutants, gene expression profiling data from DNA microarrays, and metabolic profiling data from LC/mass analysis. The aim of plant molecular breeding is shifting from introducing agronomic traits such as herbicide and insect resistance to introducing quality traits such as healthful oils and proteins, which will lead to improved and nutritional food and feed products. Plant molecular breeding is also expected to aim to develop crops for producing human therapeutic and industrial proteins.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2002.04b
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• pp.19-25
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• 2002

Biotechnology in the 21st century will be driven by three emerging technologies: genomics, high-throughput biology, and bioinformatics. These technologies are complementary to one another. A large number of economically important crops are currently subjected to whole genome sequencing. Functional genomics for determining the functions of the genes comprising the given plant genome is under progress by using various means including phenotyping data from transgenic mutants, gene expression profiling data from DNA microarrays, and metabolic profiling data from LC/mass analysis. The aim of plant molecular breeding is shifting from introducing agronomic traits such as herbicide and insect resistance to introducing quality traits such as healthful oils and proteins, which will lead to improved and nutritional food and feed products. Plant molecular breeding is also expected to aim to develop crops for producing human therapeutic and industrial proteins.

• Journal of Plant Biotechnology
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• v.29 no.3
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• pp.145-150
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• 2002

Biotechnology in the 21st century will be driven by three emerging technologies: genomics, high-throughput biology, and bioinformatics. These technologies are complementary to one another. A large number of economically important crops are currently subjected to whole genome sequencing. Functional genomics for determining the functions of the genes comprising the given plant genome is under progress by using various means including phenotyping data from transgenic mutants, gene expression profiling data from DNA microarrays, and metabolic profiling data from LC/mass analysis. The aim of plant molecular breeding is shifting from introducing agronomic traits such as herbicide and insect resistance to introducing quality traits such as healthful oils and proteins, which will lead to improved and nutritional food and feed products. Plant molecular breeding is also expected to aim to develop crops for producing human therapeutic and industrial proteins.

• Food Science and Industry
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• v.54 no.3
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• pp.145-159
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• 2021

Conventional nutrition services involve producer-oriented approaches without considering the differences in the characteristics and circumstances of each individual, whereas personalized nutrition services are consumer-oriented concepts that provide products and services for maintaining optimal health conditions based on the genetic, physiological, and metabolic characteristics of individuals, with these products based on balanced nutrition and healthy living. Currently, methods for evaluating dietary habits, monitoring dietary behaviors, deep phenotyping, and metabotyping via microbiota profiling, as well as methods for predicting big data by using machine learning, have been previously studied in Korea and abroad. With the development of medical technology and the improvement of hygiene, the demand for personalized nutrition and health services for healthier, happier, and more satisfying lives is rapidly increasing. Therefore, based on scientific technologies, attempts are needed to advance these services into global personalized markets and to boost the global competitiveness of countries and companies.