Omics Approaches for Crop Improvement

The growing human population and climate change are imposing unprecedented challenges on the global food supply. Crop improvement demands enhancing agronomical essential traits such as yield, resistance, and nutritional value by pivoting direct and indirect genetically assisted approaches to cope wi...

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collection Directory of Open Access Books
description The growing human population and climate change are imposing unprecedented challenges on the global food supply. Crop improvement demands enhancing agronomical essential traits such as yield, resistance, and nutritional value by pivoting direct and indirect genetically assisted approaches to cope with these pressures. The development of last-generation high-throughput screening technologies, known as omics, promises to speed up plant trait improvement. Large-scale techniques such as genomics, transcriptomics, proteomics, metabolomics, and phenomics have already retrieved large volumes of data, as never before, which merged through bioinformatics and machine learning approaches; they are helping us to understand the mechanisms behind crop features. Omics datasets are not only generated from the tissues of a single genotype but also permeate macro-scale interactions to deepen our knowledge of crop behavior across the microbial and environmental continua. However, despite these massive technological and computational developments, cohesive efforts to combine contrasting omics studies within common pathways and cellular networks of crop systems are in their infancy. Therefore, this reprint envisions offering updated views on multidimensional large-scale omics-based approaches by compiling studies that explore the uses of the omics paradigm and their integration through trans-disciplinary bioinformatics as tools to improve the qualitative and quantitative traits in crop species.
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language eng
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publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-1438062024-09-06T08:30:03Z Omics Approaches for Crop Improvement Yockteng, Roxana Cortés, Andrés J. Castillejo, María Ángeles background selection foreground selection gene pyramiding marker-assisted breeding submergence tolerance yield component QTL bioinformatics comparative genomics molecular markers next-generation sequencing omics papaya gibberellic acid-stimulated Arabidopsis (GASA) gene expression phylogenetics Phytophthora megakarya abiotic stresses biotic stresses Theobroma cacao malvaceae magnesium transporter comparative analysis Malvaceae Theobroma Gossypium Corchorus expression analysis gene structure phylogenetic analysis polygenic adaptation abiotic stress tolerance congruity backcrosses germplasm characterization plant genetic resources multi-local analysis AMMI model ecophysiology biofortification Caribbean coast of northern South America Botrytis fabae faba bean resistance proteomic analysis photosystem II repair cycle composite mix genetic structure multi-line variety single nucleotide polymorphism markers varietal purity irrigation root-softening antioxidant ebb-and-flow tandem mass tag HPLC-MS transcriptomics co-expression network modular analysis drought stress hub gene Abp57 rice improvement peanut phenomics high-throughput phenotyping ground penetrating radar tomato spotted wilt virus leaf spot pod weight n/a thema EDItEUR::P Mathematics and Science thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming The growing human population and climate change are imposing unprecedented challenges on the global food supply. Crop improvement demands enhancing agronomical essential traits such as yield, resistance, and nutritional value by pivoting direct and indirect genetically assisted approaches to cope with these pressures. The development of last-generation high-throughput screening technologies, known as omics, promises to speed up plant trait improvement. Large-scale techniques such as genomics, transcriptomics, proteomics, metabolomics, and phenomics have already retrieved large volumes of data, as never before, which merged through bioinformatics and machine learning approaches; they are helping us to understand the mechanisms behind crop features. Omics datasets are not only generated from the tissues of a single genotype but also permeate macro-scale interactions to deepen our knowledge of crop behavior across the microbial and environmental continua. However, despite these massive technological and computational developments, cohesive efforts to combine contrasting omics studies within common pathways and cellular networks of crop systems are in their infancy. Therefore, this reprint envisions offering updated views on multidimensional large-scale omics-based approaches by compiling studies that explore the uses of the omics paradigm and their integration through trans-disciplinary bioinformatics as tools to improve the qualitative and quantitative traits in crop species. 2024-09-06T08:29:54Z 2024-09-06T08:29:54Z 2024 book ONIX_20240906_9783725814947_168 9783725814947 9783725814930 https://directory.doabooks.org/handle/20.500.12854/143806 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9549 https://mdpi.com/books/pdfview/book/9549 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-1493-0 10.3390/books978-3-7258-1493-0 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725814947 9783725814930 open access
spellingShingle background selection
foreground selection
gene pyramiding
marker-assisted breeding
submergence tolerance
yield component QTL
bioinformatics
comparative genomics
molecular markers
next-generation sequencing
omics
papaya
gibberellic acid-stimulated Arabidopsis (GASA)
gene expression
phylogenetics
Phytophthora megakarya
abiotic stresses
biotic stresses
Theobroma cacao
malvaceae
magnesium transporter
comparative analysis
Malvaceae
Theobroma
Gossypium
Corchorus
expression analysis
gene structure
phylogenetic analysis
polygenic adaptation
abiotic stress tolerance
congruity backcrosses
germplasm characterization
plant genetic resources
multi-local analysis
AMMI model
ecophysiology
biofortification
Caribbean coast of northern South America
Botrytis fabae
faba bean
resistance
proteomic analysis
photosystem II repair cycle
composite mix
genetic structure
multi-line variety
single nucleotide polymorphism markers
varietal purity
irrigation
root-softening
antioxidant
ebb-and-flow
tandem mass tag
HPLC-MS
transcriptomics
co-expression network
modular analysis
drought stress
hub gene
Abp57
rice improvement
peanut
phenomics
high-throughput phenotyping
ground penetrating radar
tomato spotted wilt virus
leaf spot
pod weight
n/a
thema EDItEUR::P Mathematics and Science
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming
Omics Approaches for Crop Improvement
title Omics Approaches for Crop Improvement
title_full Omics Approaches for Crop Improvement
title_fullStr Omics Approaches for Crop Improvement
title_full_unstemmed Omics Approaches for Crop Improvement
title_short Omics Approaches for Crop Improvement
title_sort omics approaches for crop improvement
topic background selection
foreground selection
gene pyramiding
marker-assisted breeding
submergence tolerance
yield component QTL
bioinformatics
comparative genomics
molecular markers
next-generation sequencing
omics
papaya
gibberellic acid-stimulated Arabidopsis (GASA)
gene expression
phylogenetics
Phytophthora megakarya
abiotic stresses
biotic stresses
Theobroma cacao
malvaceae
magnesium transporter
comparative analysis
Malvaceae
Theobroma
Gossypium
Corchorus
expression analysis
gene structure
phylogenetic analysis
polygenic adaptation
abiotic stress tolerance
congruity backcrosses
germplasm characterization
plant genetic resources
multi-local analysis
AMMI model
ecophysiology
biofortification
Caribbean coast of northern South America
Botrytis fabae
faba bean
resistance
proteomic analysis
photosystem II repair cycle
composite mix
genetic structure
multi-line variety
single nucleotide polymorphism markers
varietal purity
irrigation
root-softening
antioxidant
ebb-and-flow
tandem mass tag
HPLC-MS
transcriptomics
co-expression network
modular analysis
drought stress
hub gene
Abp57
rice improvement
peanut
phenomics
high-throughput phenotyping
ground penetrating radar
tomato spotted wilt virus
leaf spot
pod weight
n/a
thema EDItEUR::P Mathematics and Science
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming
topic_facet background selection
foreground selection
gene pyramiding
marker-assisted breeding
submergence tolerance
yield component QTL
bioinformatics
comparative genomics
molecular markers
next-generation sequencing
omics
papaya
gibberellic acid-stimulated Arabidopsis (GASA)
gene expression
phylogenetics
Phytophthora megakarya
abiotic stresses
biotic stresses
Theobroma cacao
malvaceae
magnesium transporter
comparative analysis
Malvaceae
Theobroma
Gossypium
Corchorus
expression analysis
gene structure
phylogenetic analysis
polygenic adaptation
abiotic stress tolerance
congruity backcrosses
germplasm characterization
plant genetic resources
multi-local analysis
AMMI model
ecophysiology
biofortification
Caribbean coast of northern South America
Botrytis fabae
faba bean
resistance
proteomic analysis
photosystem II repair cycle
composite mix
genetic structure
multi-line variety
single nucleotide polymorphism markers
varietal purity
irrigation
root-softening
antioxidant
ebb-and-flow
tandem mass tag
HPLC-MS
transcriptomics
co-expression network
modular analysis
drought stress
hub gene
Abp57
rice improvement
peanut
phenomics
high-throughput phenotyping
ground penetrating radar
tomato spotted wilt virus
leaf spot
pod weight
n/a
thema EDItEUR::P Mathematics and Science
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming
url ONIX_20240906_9783725814947_168