Foreword: Plant phenomics: from gene to form and function

doi:10.1071/fpv36n11_fo

Cited by 26 publications

(5 citation statements)

References 19 publications

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“…This 'systems biology continuum' extends through the transcriptome for global RNA synthesis, the proteome for total protein content, the interactome for protein-protein interactions, the glycome and ionome for carbohydrates and small charged molecules respectively, the hormonome for phytohormone signaling, and the metabolome for metabolite analysis for understanding and measuring phenotypes (Mochida and Shinozaki, 2011). The continuum further extends into phenomics for whole plants, based on real-time measurements of plant growth and development using glasshouse-based imaging facilities (Furbank, 2009;Furbank and Tester, 2011;Houle et al, 2010) or through infield use of imaging equipment (Araus and Cairns, 2014). Metabolomic methods would enable the sugar and starch profiles of tubers to be more closely examined, whereas high-throughput imaging will allow plant biomass accumulation to be monitored under various biotic and abiotic stress conditions.…”

Section: Increasing the Suite Of Traits That Can Be Evaluated Or Sele...mentioning

confidence: 99%

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato

et al. 2016

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Potato (Solanum tuberosum L.) breeders consider a large number of traits during cultivar development and progress in conventional breeding can be slow. There is accumulating evidence that some of these traits, such as yield, are affected by a large number of genes with small individual effects. Recently, significant efforts have been applied to the development of genomic resources to improve potato breeding, culminating in a draft genome sequence and the identification of a large number of single nucleotide polymorphisms (SNPs). The availability of these genome-wide SNPs is a prerequisite for implementing genomic selection for improvement of polygenic traits such as yield. In this review, we investigate opportunities for the application of genomic selection to potato, including novel breeding program designs. We have considered a number of factors that will influence this process, including the autotetraploid and heterozygous genetic nature of potato, the rate of decay of linkage disequilibrium, the number of required markers, the design of a reference population, and trait heritability. Based on estimates of the effective population size derived from a potato breeding program, we have calculated the expected accuracy of genomic selection for four key traits of varying heritability and propose that it will be reasonably accurate. We compared the expected genetic gain from genomic selection with the expected gain from phenotypic and pedigree selection, and found that genetic gain can be substantially improved by using genomic selection.

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Section: Increasing the Suite Of Traits That Can Be Evaluated Or Sele...mentioning

confidence: 99%

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato

et al. 2016

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“…Plant phenotyping is defined as the assessment of complex traits such as growth, development, tolerance, resistance, architecture, physiology, ecology, yield, and the basic measurement of individual quantitative parameters that form the basis for complex trait assessment [ 2 ]. Scientists are increasingly interested in the use of phenomic-level data to aid in the correlation between genomics and the variation in crop yields and plant health [ 3 , 4 , 5 ]. In this way, plant phenotyping has become an important aspect of crop improvement, availing data to assess traits for variety selection in order to identify desirable traits and eliminate undesirable traits during the evaluation of plant populations [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Review: Application of Artificial Intelligence in Phenomics

Nabwire

Suh

Kim

et al. 2021

Sensors

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Plant phenomics has been rapidly advancing over the past few years. This advancement is attributed to the increased innovation and availability of new technologies which can enable the high-throughput phenotyping of complex plant traits. The application of artificial intelligence in various domains of science has also grown exponentially in recent years. Notably, the computer vision, machine learning, and deep learning aspects of artificial intelligence have been successfully integrated into non-invasive imaging techniques. This integration is gradually improving the efficiency of data collection and analysis through the application of machine and deep learning for robust image analysis. In addition, artificial intelligence has fostered the development of software and tools applied in field phenotyping for data collection and management. These include open-source devices and tools which are enabling community driven research and data-sharing, thereby availing the large amounts of data required for the accurate study of phenotypes. This paper reviews more than one hundred current state-of-the-art papers concerning AI-applied plant phenotyping published between 2010 and 2020. It provides an overview of current phenotyping technologies and the ongoing integration of artificial intelligence into plant phenotyping. Lastly, the limitations of the current approaches/methods and future directions are discussed.

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“…High-throughput sequencing techniques have been enabled by increased the new knowledge of modern plant genomes (Furbank 2009). The applicable genomic data have been obtained with accommodate technologies to be enable to identify the functional of plant genes such as photonics applications (Yeong et al 2019), functional plant biology (Poorter et al 2012), phenotyping computers vision-based (Mochida et al 2018), and robotics (Coppens et al 2017).…”

Section: Introductionmentioning

confidence: 99%

High-throughput identification of chrysanthemum gene function and expression: An overview and an effective proposition

Nguyen

Lim

2021

J Plant Biotechnol

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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.

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Foreword: Plant phenomics: from gene to form and function

Cited by 26 publications

References 19 publications

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato

Review: Application of Artificial Intelligence in Phenomics

High-throughput identification of chrysanthemum gene function and expression: An overview and an effective proposition

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