{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/113198"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/113198","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"High throughput phenotyping and quantitative genetics of leaf functional traits in C4 grasses","abstract":"The challenge of meeting the global demand for food and fuel is exacerbated by the need to increase plant productivity to maintain aboveground biomass and crop yield in suboptimal and resource limited environments. Improving crop productivity without increased resource use requires greater in whole plant water and nutrient use efficiencies. To meet these challenges, functional processes related to crop performance need to be better understood. Phenotyping complex traits such as water and nitrogen use efficiency in genetically diverse populations is currently a bottleneck in crop improvement because it is time and labor intensive. To harness the diversity available to improve crop productivity, high throughput phenotyping (HTP) methods for measuring leaf functional traits need to be evaluated beyond proof-of-concept studies. Chapter 2 and Chapter 3 aimed to understand the scope in which statistical models developed from hyperspectral reflectance measurements could be applied to predict key leaf functional traits. PLSR models for SLA presented in Chapter 2 were successfully applied across broad genetic variation of hundreds of genotypes in both maize and sorghum. In contrast, work presented in Chapter 3 showed that performance of PLSR models to predict leaf nitrogen are more context dependent, thus resulting in poor performance when applied across the same species. Within Setaria, the performance of the PLSR model for SLA and the model for leaf nitrogen varied with environmental conditions. Together, Chapters 2 and 3 highlight that more work needs to be done to understand leaf level hyperspectral reflectance as a high- throughput phenotyping tool before it can be broadly applied to answer physiological questions across diverse germplasm and environmental conditions. Analysis of genetic variation in leaf morphology, plant architecture, and biomass accumulation provides a complement to physiological and ecological studies of plant form and function. Chapter 4 took an integrative approach to evaluate phenotypic variation and trait coordination in a Setaria recombinant inbred line (RIL) population in well-watered and water-limited conditions. The contrasting response of the wild parent versus the cultivated parent to water limitation was consistent with ecological theory and comparative studies addressing the impact domestication had on crop response to environmental stress. The analysis of phenotypic and genotypic variation among the RILs revealed phenotypic coordination and genetic tradeoffs associated with domestication. At the same time, it highlighted the importance of leaf functional traits, especially those traits reflected in carbon isotope composition (δ13C) and leaf nitrogen content, as possible avenues for improving crop performance. Further work focusing on the role of leaf functional traits in crop performance and the physiological mechanisms involved in phenotypic integration of leaf functional traits and plant architecture has the potential to inform efforts to develop crops that are simultaneously high performing and climate resilient.","abstract_html":"The challenge of meeting the global demand for food and fuel is exacerbated by the need to increase plant productivity to maintain aboveground biomass and crop yield in suboptimal and resource limited environments. Improving crop productivity without increased resource use requires greater in whole plant water and nutrient use efficiencies. To meet these challenges, functional processes related to crop performance need to be better understood. Phenotyping complex traits such as water and nitrogen use efficiency in genetically diverse populations is currently a bottleneck in crop improvement because it is time and labor intensive. To harness the diversity available to improve crop productivity, high throughput phenotyping (HTP) methods for measuring leaf functional traits need to be evaluated beyond proof-of-concept studies. Chapter 2 and Chapter 3 aimed to understand the scope in which statistical models developed from hyperspectral reflectance measurements could be applied to predict key leaf functional traits. PLSR models for SLA presented in Chapter 2 were successfully applied across broad genetic variation of hundreds of genotypes in both maize and sorghum. In contrast, work presented in Chapter 3 showed that performance of PLSR models to predict leaf nitrogen are more context dependent, thus resulting in poor performance when applied across the same species. Within Setaria, the performance of the PLSR model for SLA and the model for leaf nitrogen varied with environmental conditions. Together, Chapters 2 and 3 highlight that more work needs to be done to understand leaf level hyperspectral reflectance as a high- throughput phenotyping tool before it can be broadly applied to answer physiological questions across diverse germplasm and environmental conditions. Analysis of genetic variation in leaf morphology, plant architecture, and biomass accumulation provides a complement to physiological and ecological studies of plant form and function. Chapter 4 took an integrative approach to evaluate phenotypic variation and trait coordination in a Setaria recombinant inbred line (RIL) population in well-watered and water-limited conditions. The contrasting response of the wild parent versus the cultivated parent to water limitation was consistent with ecological theory and comparative studies addressing the impact domestication had on crop response to environmental stress. The analysis of phenotypic and genotypic variation among the RILs revealed phenotypic coordination and genetic tradeoffs associated with domestication. At the same time, it highlighted the importance of leaf functional traits, especially those traits reflected in carbon isotope composition (δ13C) and leaf nitrogen content, as possible avenues for improving crop performance. Further work focusing on the role of leaf functional traits in crop performance and the physiological mechanisms involved in phenotypic integration of leaf functional traits and plant architecture has the potential to inform efforts to develop crops that are simultaneously high performing and climate resilient.","abstract_has_math":false,"creators":["Paul, Rachel Elizabeth"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Plant Biology","degree_department":null,"school":null,"contributors":["Leakey, Andrew DB","Ort, Donald R","Bernacchi, Carl J","Bohn, Martin O"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-01-12T22:35:16Z","date_published":"2022-01-12T22:35:16Z","updated_at":"2026-07-22T22:24:53Z","subjects":["C4 grasses","setaria","high-throughput phenotyping","drought","leaf functional traits","leaf reflectance"],"languages":["en"],"rights":["Copyright 2021 Rachel Paul"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/113198","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Leakey, Andrew DB","Ort, Donald R","Bernacchi, Carl J","Bohn, Martin O"]},{"key":"dc:creator","label":"Author","values":["Paul, Rachel Elizabeth"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-01-12T22:35:16Z","2024-01-12T22:35:30Z","2021-07-15","2021-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Plant Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["C4 grasses","setaria","high-throughput phenotyping","drought","leaf functional traits","leaf reflectance"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Rachel Paul"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/113198"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The challenge of meeting the global demand for food and fuel is exacerbated by the need to increase plant productivity to maintain aboveground biomass and crop yield in suboptimal and resource limited environments. Improving crop productivity without increased resource use requires greater in whole plant water and nutrient use efficiencies. To meet these challenges, functional processes related to crop performance need to be better understood. Phenotyping complex traits such as water and nitrogen use efficiency in genetically diverse populations is currently a bottleneck in crop improvement because it is time and labor intensive. To harness the diversity available to improve crop productivity, high throughput phenotyping (HTP) methods for measuring leaf functional traits need to be evaluated beyond proof-of-concept studies. Chapter 2 and Chapter 3 aimed to understand the scope in which statistical models developed from hyperspectral reflectance measurements could be applied to predict key leaf functional traits. PLSR models for SLA presented in Chapter 2 were successfully applied across broad genetic variation of hundreds of genotypes in both maize and sorghum. In contrast, work presented in Chapter 3 showed that performance of PLSR models to predict leaf nitrogen are more context dependent, thus resulting in poor performance when applied across the same species. Within Setaria, the performance of the PLSR model for SLA and the model for leaf nitrogen varied with environmental conditions. Together, Chapters 2 and 3 highlight that more work needs to be done to understand leaf level hyperspectral reflectance as a high- throughput phenotyping tool before it can be broadly applied to answer physiological questions across diverse germplasm and environmental conditions. Analysis of genetic variation in leaf morphology, plant architecture, and biomass accumulation provides a complement to physiological and ecological studies of plant form and function. Chapter 4 took an integrative approach to evaluate phenotypic variation and trait coordination in a Setaria recombinant inbred line (RIL) population in well-watered and water-limited conditions. The contrasting response of the wild parent versus the cultivated parent to water limitation was consistent with ecological theory and comparative studies addressing the impact domestication had on crop response to environmental stress. The analysis of phenotypic and genotypic variation among the RILs revealed phenotypic coordination and genetic tradeoffs associated with domestication. At the same time, it highlighted the importance of leaf functional traits, especially those traits reflected in carbon isotope composition (δ13C) and leaf nitrogen content, as possible avenues for improving crop performance. Further work focusing on the role of leaf functional traits in crop performance and the physiological mechanisms involved in phenotypic integration of leaf functional traits and plant architecture has the potential to inform efforts to develop crops that are simultaneously high performing and climate resilient.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01","The student, Rachel Paul, accepted the attached license on 2021-07-14 at 15:22.","The student, Rachel Paul, submitted this Dissertation for approval on 2021-07-14 at 15:35.","This Dissertation was approved for publication on 2021-07-15 at 17:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16938 on 2022-01-12 at 12:55:10","Made available in DSpace on 2022-01-12T22:35:16Z (GMT). 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Improving crop productivity without increased resource use requires greater in whole plant water and nutrient use efficiencies. To meet these challenges, functional processes related to crop performance need to be better understood. Phenotyping complex traits such as water and nitrogen use efficiency in genetically diverse populations is currently a bottleneck in crop improvement because it is time and labor intensive. To harness the diversity available to improve crop productivity, high throughput phenotyping (HTP) methods for measuring leaf functional traits need to be evaluated beyond proof-of-concept studies. Chapter 2 and Chapter 3 aimed to understand the scope in which statistical models developed from hyperspectral reflectance measurements could be applied to predict key leaf functional traits. PLSR models for SLA presented in Chapter 2 were successfully applied across broad genetic variation of hundreds of genotypes in both maize and sorghum. In contrast, work presented in Chapter 3 showed that performance of PLSR models to predict leaf nitrogen are more context dependent, thus resulting in poor performance when applied across the same species. Within Setaria, the performance of the PLSR model for SLA and the model for leaf nitrogen varied with environmental conditions. Together, Chapters 2 and 3 highlight that more work needs to be done to understand leaf level hyperspectral reflectance as a high- throughput phenotyping tool before it can be broadly applied to answer physiological questions across diverse germplasm and environmental conditions. Analysis of genetic variation in leaf morphology, plant architecture, and biomass accumulation provides a complement to physiological and ecological studies of plant form and function. Chapter 4 took an integrative approach to evaluate phenotypic variation and trait coordination in a Setaria recombinant inbred line (RIL) population in well-watered and water-limited conditions. The contrasting response of the wild parent versus the cultivated parent to water limitation was consistent with ecological theory and comparative studies addressing the impact domestication had on crop response to environmental stress. The analysis of phenotypic and genotypic variation among the RILs revealed phenotypic coordination and genetic tradeoffs associated with domestication. At the same time, it highlighted the importance of leaf functional traits, especially those traits reflected in carbon isotope composition (δ13C) and leaf nitrogen content, as possible avenues for improving crop performance. Further work focusing on the role of leaf functional traits in crop performance and the physiological mechanisms involved in phenotypic integration of leaf functional traits and plant architecture has the potential to inform efforts to develop crops that are simultaneously high performing and climate resilient.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01","The student, Rachel Paul, accepted the attached license on 2021-07-14 at 15:22.","The student, Rachel Paul, submitted this Dissertation for approval on 2021-07-14 at 15:35.","This Dissertation was approved for publication on 2021-07-15 at 17:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16938 on 2022-01-12 at 12:55:10","Made available in DSpace on 2022-01-12T22:35:16Z (GMT). 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