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Murata H, Noshita K. Three-Dimensional Leaf Edge Reconstruction Combining Two- and Three-Dimensional Approaches. PLANT PHENOMICS (WASHINGTON, D.C.) 2024; 6:0181. [PMID: 38726389 PMCID: PMC11079596 DOI: 10.34133/plantphenomics.0181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 03/29/2024] [Indexed: 05/12/2024]
Abstract
Leaves, crucial for plant physiology, exhibit various morphological traits that meet diverse functional needs. Traditional leaf morphology quantification, largely 2-dimensional (2D), has not fully captured the 3-dimensional (3D) aspects of leaf function. Despite improvements in 3D data acquisition, accurately depicting leaf morphologies, particularly at the edges, is difficult. This study proposes a method for 3D leaf edge reconstruction, combining 2D image segmentation with curve-based 3D reconstruction. Utilizing deep-learning-based instance segmentation for 2D edge detection, structure from motion for estimation of camera positions and orientations, leaf correspondence identification for matching leaves among images, and curve-based 3D reconstruction for estimating 3D curve fragments, the method assembles 3D curve fragments into a leaf edge model through B-spline curve fitting. The method's performances were evaluated on both virtual and actual leaves, and the results indicated that small leaves and high camera noise pose greater challenges to reconstruction. We developed guidelines for setting a reliability threshold for curve fragments, considering factors occlusion, leaf size, the number of images, and camera error; the number of images had a lesser impact on this threshold compared to others. The method was effective for lobed leaves and leaves with fewer than 4 holes. However, challenges still existed when dealing with morphologies exhibiting highly local variations, such as serrations. This nondestructive approach to 3D leaf edge reconstruction marks an advancement in the quantitative analysis of plant morphology. It is a promising way to capture whole-plant architecture by combining 2D and 3D phenotyping approaches adapted to the target anatomical structures.
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Affiliation(s)
- Hidekazu Murata
- Department of Biology,
Kyushu University, Fukuoka, Fukuoka 819–0395, Japan
| | - Koji Noshita
- Department of Biology,
Kyushu University, Fukuoka, Fukuoka 819–0395, Japan
- Plant Frontier Research Center,
Kyushu University, Fukuoka, Fukuoka 819–0395, Japan
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2
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Stirbet A, Guo Y, Lazár D, Govindjee G. From leaf to multiscale models of photosynthesis: applications and challenges for crop improvement. PHOTOSYNTHESIS RESEARCH 2024:10.1007/s11120-024-01083-9. [PMID: 38619700 DOI: 10.1007/s11120-024-01083-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 01/29/2024] [Indexed: 04/16/2024]
Abstract
To keep up with the growth of human population and to circumvent deleterious effects of global climate change, it is essential to enhance crop yield to achieve higher production. Here we review mathematical models of oxygenic photosynthesis that are extensively used, and discuss in depth a subset that accounts for diverse approaches providing solutions to our objective. These include models (1) to study different ways to enhance photosynthesis, such as fine-tuning antenna size, photoprotection and electron transport; (2) to bioengineer carbon metabolism; and (3) to evaluate the interactions between the process of photosynthesis and the seasonal crop dynamics, or those that have included statistical whole-genome prediction methods to quantify the impact of photosynthesis traits on the improvement of crop yield. We conclude by emphasizing that the results obtained in these studies clearly demonstrate that mathematical modelling is a key tool to examine different approaches to improve photosynthesis for better productivity, while effective multiscale crop models, especially those that also include remote sensing data, are indispensable to verify different strategies to obtain maximized crop yields.
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Affiliation(s)
| | - Ya Guo
- Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education Jiangnan University, Wuxi, 214122, China
| | - Dušan Lazár
- Department of Biophysics, Faculty of Science, Palacký Univesity, Šlechtitelů 27, 78371, Olomouc, Czech Republic
| | - Govindjee Govindjee
- Department of Biochemistry, Department of Plant Biology, and the Center of Biophysics & Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
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3
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Wu A, Truong SH, McCormick R, van Oosterom EJ, Messina CD, Cooper M, Hammer GL. Contrasting leaf-scale photosynthetic low-light response and its temperature dependency are key to differences in crop-scale radiation use efficiency. THE NEW PHYTOLOGIST 2024; 241:2435-2447. [PMID: 38214462 DOI: 10.1111/nph.19537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 12/31/2023] [Indexed: 01/13/2024]
Abstract
Radiation use efficiency (RUE) is a key crop adaptation trait that quantifies the potential amount of aboveground biomass produced by the crop per unit of solar energy intercepted. But it is unclear why elite maize and grain sorghum hybrids differ in their RUE at the crop level. Here, we used a non-traditional top-down approach via canopy photosynthesis modelling to identify leaf-level photosynthetic traits that are key to differences in crop-level RUE. A novel photosynthetic response measurement was developed and coupled with use of a Bayesian model fitting procedure, incorporating a C4 leaf photosynthesis model, to infer cohesive sets of photosynthetic parameters by simultaneously fitting responses to CO2 , light, and temperature. Statistically significant differences between leaf photosynthetic parameters of elite maize and grain sorghum hybrids were found across a range of leaf temperatures, in particular for effects on the quantum yield of photosynthesis, but also for the maximum enzymatic activity of Rubisco and PEPc. Simulation of diurnal canopy photosynthesis predicted that the leaf-level photosynthetic low-light response and its temperature dependency are key drivers of the performance of crop-level RUE, generating testable hypotheses for further physiological analysis and bioengineering applications.
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Affiliation(s)
- Alex Wu
- Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
| | - Sandra Huynh Truong
- Predictive Agriculture, Research & Development, Corteva Agriscience, Johnston, IA, 50131, USA
| | - Ryan McCormick
- Predictive Agriculture, Research & Development, Corteva Agriscience, Johnston, IA, 50131, USA
- Gro Intelligence, New York, NY, 10022, USA
| | - Erik J van Oosterom
- Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
| | - Carlos D Messina
- Predictive Agriculture, Research & Development, Corteva Agriscience, Johnston, IA, 50131, USA
- Horticultural Sciences Department, University of Florida, Gainesville, FL, 32611, USA
| | - Mark Cooper
- Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
| | - Graeme L Hammer
- Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St. Lucia, Brisbane, Qld, 4072, Australia
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4
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Moroyoqui‐Parra MA, Molero G, Reynolds MP, Gaju O, Murchie EH, Foulkes MJ. Interaction of planting system with radiation-use efficiency in wheat lines. CROP SCIENCE 2024; 64:314-332. [PMID: 38516200 PMCID: PMC10952436 DOI: 10.1002/csc2.21115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 09/22/2023] [Indexed: 03/23/2024]
Abstract
Radiation-use efficiency (RUE) is an important trait for raising biomass and yield potential in plant breeding. However, the effect of the planting system (PS) on genetic variation in RUE has not been previously investigated. Our objectives were to quantify genetic variation in RUE, biomass and grain yield in raised-bed and flat-basin planting systems, and associations with canopy-architecture traits (flag-leaf angle and curvature). Twelve spring wheat (Triticum aestivum L.) cultivars were evaluated under irrigated conditions for 3 years in North West Mexico using raised-bed and flat-basin planting systems. Canopy architecture traits were measured at booting and anthesis + 7 days. Grain yield (10.6%), biomass (7.6%), and pre-grain-filling RUE (9.7%) were higher in raised beds than flat basins, while a significant planting system × genotype interaction was found for grain yield. Genetic variation in pre-grain-filling RUE was associated with biomass and grain yield in beds and basins. In flat basins, higher pre-grain-filling RUE was correlated with a more upright flag-leaf angle but not in raised beds. In raised beds, cultivars with less upright flag-leaf angle had greater fractional light interception pre-anthesis. Taller semi-dwarf cultivars intercepted relatively more radiation in the beds than the flats before anthesis, consistent with the taller cultivars showing relatively greater increases in yield in beds compared to flats. Our results indicated that the evaluation of genotypes for RUE and biomass in wheat breeding should take into account planting systems to capture genotype × PS effects. In addition, the results demonstrate how flag-leaf angle has a different effect depending on the planting system.
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Affiliation(s)
- Marcela A. Moroyoqui‐Parra
- Division of Plant and Crop Science, School of BiosciencesUniversity of NottinghamLeicestershireUK
- Global Wheat ProgramInternational Maize and Wheat Improvement Center (CIMMYT)TexcocoMexico
| | - Gemma Molero
- Global Wheat ProgramInternational Maize and Wheat Improvement Center (CIMMYT)TexcocoMexico
- KWS Momont RechercheMons‐en‐PeveleFrance
| | - Matthew P. Reynolds
- Global Wheat ProgramInternational Maize and Wheat Improvement Center (CIMMYT)TexcocoMexico
| | - Oorbessy Gaju
- Lincoln Institute for Agri‐Food and TechnologyUniversity of LincolnLincolnUK
| | - Erik H. Murchie
- Division of Plant and Crop Science, School of BiosciencesUniversity of NottinghamLeicestershireUK
| | - Michael John Foulkes
- Division of Plant and Crop Science, School of BiosciencesUniversity of NottinghamLeicestershireUK
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5
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Zhang P, Huang J, Ma Y, Wang X, Kang M, Song Y. Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0091. [PMID: 37780969 PMCID: PMC10538623 DOI: 10.34133/plantphenomics.0091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 08/26/2023] [Indexed: 10/03/2023]
Abstract
Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.
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Affiliation(s)
- Pengpeng Zhang
- School of Agronomy, Anhui Agricultural University, Hefei, Anhui Province 230036, China
| | - Jingyao Huang
- School of Agronomy, Anhui Agricultural University, Hefei, Anhui Province 230036, China
| | - Yuntao Ma
- College of Land Science and Technology, China Agricultural University, Beijing 100094, China
| | - Xiujuan Wang
- The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Mengzhen Kang
- The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Youhong Song
- School of Agronomy, Anhui Agricultural University, Hefei, Anhui Province 230036, China
- Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD 4350, Australia
- Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD 4350, Australia
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6
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Song Q, Liu F, Bu H, Zhu XG. Quantifying Contributions of Different Factors to Canopy Photosynthesis in 2 Maize Varieties: Development of a Novel 3D Canopy Modeling Pipeline. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0075. [PMID: 37502446 PMCID: PMC10371248 DOI: 10.34133/plantphenomics.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 07/01/2023] [Indexed: 07/29/2023]
Abstract
Crop yield potential is intrinsically related to canopy photosynthesis; therefore, improving canopy photosynthetic efficiency is a major focus of current efforts to enhance crop yield. Canopy photosynthesis rate (Ac) is influenced by several factors, including plant architecture, leaf chlorophyll content, and leaf photosynthetic properties, which interact with each other. Identifying factors that restrict canopy photosynthesis and target adjustments to improve canopy photosynthesis in a specific crop cultivar pose an important challenge for the breeding community. To address this challenge, we developed a novel pipeline that utilizes factorial analysis, canopy photosynthesis modeling, and phenomics data collected using a 64-camera multi-view stereo system, enabling the dissection of the contributions of different factors to differences in canopy photosynthesis between maize cultivars. We applied this method to 2 maize varieties, W64A and A619, and found that leaf photosynthetic efficiency is the primary determinant (17.5% to 29.2%) of the difference in Ac between 2 maize varieties at all stages, and plant architecture at early stages also contribute to the difference in Ac (5.3% to 6.7%). Additionally, the contributions of each leaf photosynthetic parameter and plant architectural trait were dissected. We also found that the leaf photosynthetic parameters were linearly correlated with Ac and plant architecture traits were non-linearly related to Ac. This study developed a novel pipeline that provides a method for dissecting the relationship among individual phenotypes controlling the complex trait of canopy photosynthesis.
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Affiliation(s)
- Qingfeng Song
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Fusang Liu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Hongyi Bu
- Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China
| | - Xin-Guang Zhu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
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7
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Hoover DL, Abendroth LJ, Browning DM, Saha A, Snyder K, Wagle P, Witthaus L, Baffaut C, Biederman JA, Bosch DD, Bracho R, Busch D, Clark P, Ellsworth P, Fay PA, Flerchinger G, Kearney S, Levers L, Saliendra N, Schmer M, Schomberg H, Scott RL. Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 864:160992. [PMID: 36535470 DOI: 10.1016/j.scitotenv.2022.160992] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/17/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
Understanding the relationship between water and production within and across agroecosystems is essential for addressing several agricultural challenges of the 21st century: providing food, fuel, and fiber to a growing human population, reducing the environmental impacts of agricultural production, and adapting food systems to climate change. Of all human activities, agriculture has the highest demand for water globally. Therefore, increasing water use efficiency (WUE), or producing 'more crop per drop', has been a long-term goal of agricultural management, engineering, and crop breeding. WUE is a widely used term applied across a diverse array of spatial scales, spanning from the leaf to the globe, and over temporal scales ranging from seconds to months to years. The measurement, interpretation, and complexity of WUE varies enormously across these spatial and temporal scales, challenging comparisons within and across diverse agroecosystems. The goals of this review are to evaluate common indicators of WUE in agricultural production and assess tradeoffs when applying these indicators within and across agroecosystems amidst a changing climate. We examine three questions: (1) what are the uses and limitations of common WUE indicators, (2) how can WUE indicators be applied within and across agroecosystems, and (3) how can WUE indicators help adapt agriculture to climate change? Addressing these agricultural challenges will require land managers, producers, policy makers, researchers, and consumers to evaluate costs and benefits of practices and innovations of water use in agricultural production. Clearly defining and interpreting WUE in the most scale-appropriate way is crucial for advancing agroecosystem sustainability.
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Affiliation(s)
- David L Hoover
- USDA-ARS, Rangeland Resources and Systems Research Unit, Crops Research Laboratory, Fort Collins, CO, USA.
| | - Lori J Abendroth
- USDA-ARS, Cropping Systems and Water Quality Research Unit, Columbia, MO, USA
| | - Dawn M Browning
- USDA-ARS, Range Management Research Unit, Las Cruces, NM, USA
| | - Amartya Saha
- Archbold Biological Station, Agroecology Laboratory, Lake Placid, FL, USA
| | - Keirith Snyder
- USDA-ARS, Great Basin Rangelands Research Unit, Reno, NV, USA
| | - Pradeep Wagle
- USDA-ARS, Grazinglands Research Laboratory, El Reno, OK, USA
| | | | - Claire Baffaut
- USDA-ARS, Cropping Systems and Water Quality Research Unit, Columbia, MO, USA
| | | | - David D Bosch
- USDA-ARS, Southeast Watershed Research Laboratory, Tifton, GA, USA
| | - Rosvel Bracho
- School of Forests, Fisheries and Geomatics Sciences, University of Florida, Gainesville, FL, USA
| | - Dennis Busch
- School of Agriculture, University of Wisconsin-Platteville, Platteville, WI, USA
| | - Patrick Clark
- USDA-ARS, Northwest Watershed Research Center, Boise, ID, USA
| | | | - Philip A Fay
- USDA-ARS, Grassland Soil and Water Research Laboratory, Temple, TX, USA
| | | | - Sean Kearney
- USDA-ARS, Rangeland Resources and Systems Research Unit, Crops Research Laboratory, Fort Collins, CO, USA
| | - Lucia Levers
- USDA-ARS, Sustainable Agriculture Water Systems, Davis, CA, USA
| | - Nicanor Saliendra
- USDA-ARS, Northern Great Plains Research Laboratory, Mandan, ND, USA
| | - Marty Schmer
- USDA-ARS, Agroecosystems Management Research Unit, Lincoln, NE, USA
| | - Harry Schomberg
- USDA-ARS, Sustainable Agricultural Systems Laboratory, Beltsville Agricultural Research Center, Beltsville, MD, USA
| | - Russell L Scott
- USDA-ARS, Southwest Watershed Research Center, Tucson, AZ, USA
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8
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Chang TG, Shi Z, Zhao H, Song Q, He Z, Van Rie J, Den Boer B, Galle A, Zhu XG. 3dCAP-Wheat: An Open-Source Comprehensive Computational Framework Precisely Quantifies Wheat Foliar, Nonfoliar, and Canopy Photosynthesis. PLANT PHENOMICS 2022; 2022:9758148. [PMID: 36059602 PMCID: PMC9394111 DOI: 10.34133/2022/9758148] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 06/18/2022] [Indexed: 11/24/2022]
Abstract
Canopy photosynthesis is the sum of photosynthesis of all above-ground photosynthetic tissues. Quantitative roles of nonfoliar tissues in canopy photosynthesis remain elusive due to methodology limitations. Here, we develop the first complete canopy photosynthesis model incorporating all above-ground photosynthetic tissues and validate this model on wheat with state-of-the-art gas exchange measurement facilities. The new model precisely predicts wheat canopy gas exchange rates at different growth stages, weather conditions, and canopy architectural perturbations. Using the model, we systematically study (1) the contribution of both foliar and nonfoliar tissues to wheat canopy photosynthesis and (2) the responses of wheat canopy photosynthesis to plant physiological and architectural changes. We found that (1) at tillering, heading, and milking stages, nonfoliar tissues can contribute ~4, ~32, and ~50% of daily gross canopy photosynthesis (Acgross; ~2, ~15, and ~-13% of daily net canopy photosynthesis, Acnet) and absorb ~6, ~42, and ~60% of total light, respectively; (2) under favorable condition, increasing spike photosynthetic activity, rather than enlarging spike size or awn size, can enhance canopy photosynthesis; (3) covariation in tissue respiratory rate and photosynthetic rate may be a major factor responsible for less than expected increase in daily Acnet; and (4) in general, erect leaves, lower spike position, shorter plant height, and proper plant densities can benefit daily Acnet. Overall, the model, together with the facilities for quantifying plant architecture and tissue gas exchange, provides an integrated platform to study canopy photosynthesis and support rational design of photosynthetically efficient wheat crops.
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Affiliation(s)
- Tian-Gen Chang
- National Key Laboratory for Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China
| | - Zai Shi
- National Key Laboratory for Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China
| | - Honglong Zhao
- National Key Laboratory for Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China
| | - Qingfeng Song
- National Key Laboratory for Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China
| | - Zhonghu He
- Insitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jeroen Van Rie
- BASF Belgium Coordination Center-Innovation Center Gent, Technologiepark-Zwijnaarde 101, 9052 Gent, Belgium
| | - Bart Den Boer
- BASF Belgium Coordination Center-Innovation Center Gent, Technologiepark-Zwijnaarde 101, 9052 Gent, Belgium
| | - Alexander Galle
- BASF Belgium Coordination Center-Innovation Center Gent, Technologiepark-Zwijnaarde 101, 9052 Gent, Belgium
| | - Xin-Guang Zhu
- National Key Laboratory for Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China
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9
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Zhao HL, Chang TG, Xiao Y, Zhu XG. Potential metabolic mechanisms for inhibited chloroplast nitrogen assimilation under high CO2. PLANT PHYSIOLOGY 2021; 187:1812-1833. [PMID: 34618071 PMCID: PMC8566258 DOI: 10.1093/plphys/kiab345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 06/28/2021] [Indexed: 05/31/2023]
Abstract
Improving photosynthesis is considered a major and feasible option to dramatically increase crop yield potential. Increased atmospheric CO2 concentration often stimulates both photosynthesis and crop yield, but decreases protein content in the main C3 cereal crops. This decreased protein content in crops constrains the benefits of elevated CO2 on crop yield and affects their nutritional value for humans. To support studies of photosynthetic nitrogen assimilation and its complex interaction with photosynthetic carbon metabolism for crop improvement, we developed a dynamic systems model of plant primary metabolism, which includes the Calvin-Benson cycle, the photorespiration pathway, starch synthesis, glycolysis-gluconeogenesis, the tricarboxylic acid cycle, and chloroplastic nitrogen assimilation. This model successfully captures responses of net photosynthetic CO2 uptake rate (A), respiration rate, and nitrogen assimilation rate to different irradiance and CO2 levels. We then used this model to predict inhibition of nitrogen assimilation under elevated CO2. The potential mechanisms underlying inhibited nitrogen assimilation under elevated CO2 were further explored with this model. Simulations suggest that enhancing the supply of α-ketoglutarate is a potential strategy to maintain high rates of nitrogen assimilation under elevated CO2. This model can be used as a heuristic tool to support research on interactions between photosynthesis, respiration, and nitrogen assimilation. It also provides a basic framework to support the design and engineering of C3 plant primary metabolism for enhanced photosynthetic efficiency and nitrogen assimilation in the coming high-CO2 world.
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Affiliation(s)
- Hong-Long Zhao
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Key Laboratory for Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Tian-Gen Chang
- National Key Laboratory for Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yi Xiao
- National Key Laboratory for Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200031, China
- Department of Crop Sciences, University of Illinois at Urbana Champaign, Urbana, Illinois 61801, USA
- Department of Plant Biology, University of Illinois at Urbana Champaign, Urbana, Illinois 61801, USA
| | - Xin-Guang Zhu
- National Key Laboratory for Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200031, China
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10
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Liu F, Song Q, Zhao J, Mao L, Bu H, Hu Y, Zhu XG. Canopy occupation volume as an indicator of canopy photosynthetic capacity. THE NEW PHYTOLOGIST 2021; 232:941-956. [PMID: 34245568 DOI: 10.1111/nph.17611] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 07/03/2021] [Indexed: 06/13/2023]
Abstract
Leaf angle and leaf area index together influence canopy light interception and canopy photosynthesis. However, so far, there is no effective method to identify the optimal combination of these two parameters for canopy photosynthesis. In this study, first a robust high-throughput method for accurate segmentation of maize organs based on 3D point clouds data was developed, then the segmented plant organs were used to generate new 3D point clouds for the canopy of altered architectures. With this, we simulated the synergistic effect of leaf area and leaf angle on canopy photosynthesis. The results show that, compared to the traditional parameters describing the canopy photosynthesis including leaf area index, facet angle and canopy coverage, a new parameter - the canopy occupation volume (COV) - can better explain the variations of canopy photosynthetic capacity. Specifically, COV can explain > 79% variations of canopy photosynthesis generated by changing leaf angle and > 84% variations of canopy photosynthesis generated by changing leaf area. As COV can be calculated in a high-throughput manner based on the canopy point clouds, it can be used to evaluate canopy architecture in breeding and agronomic research.
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Affiliation(s)
- Fusang Liu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Qingfeng Song
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jinke Zhao
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Linxiong Mao
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hongyi Bu
- Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, 200083, China
| | - Yong Hu
- Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, 200083, China
| | - Xin-Guang Zhu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200031, China
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11
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Changes in peanut canopy structure and photosynthetic characteristics induced by an arbuscular mycorrhizal fungus in a nutrient-poor environment. Sci Rep 2021; 11:14832. [PMID: 34290277 PMCID: PMC8295368 DOI: 10.1038/s41598-021-94092-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 06/15/2021] [Indexed: 11/25/2022] Open
Abstract
A well-developed canopy structure can increase the biomass accumulation and yield of crops. Peanut seeds were sown in a soil inoculated with an arbuscular mycorrhizal fungus (AMF) and uninoculated controls were also sown. Canopy structure was monitored using a 3-D laser scanner and photosynthetic characteristics with an LI-6400 XT photosynthesis system after 30, 45 and 70 days of growth to explore the effects of the AMF on growth, canopy structure and photosynthetic characteristics and yield. The AMF colonized the roots and AMF inoculation significantly increased the height, canopy width and total leaf area of the host plants and improved canopy structure. AMF reduced the tiller angle of the upper and middle canopy layers, increased that of the lower layer, reduced the leaf inclination of the upper, middle and lower layers, and increased the average leaf area and leaf area index after 45 days of growth, producing a well-developed and hierarchical canopy. Moreover, AMF inoculation increased the net photosynthetic rate in the upper, middle and lower layers. Plant height, canopy width, and total leaf area were positively correlated with net photosynthetic rate, and the inclination angle and tiller angle of the upper leaves were negatively correlated with net photosynthetic rate. Overall, the results demonstrate the effects of AMF inoculation on plant canopy structure and net photosynthetic rate.
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12
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Slattery RA, Ort DR. Perspectives on improving light distribution and light use efficiency in crop canopies. PLANT PHYSIOLOGY 2021; 185:34-48. [PMID: 33631812 PMCID: PMC8133579 DOI: 10.1093/plphys/kiaa006] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 10/03/2020] [Indexed: 05/22/2023]
Abstract
Plant stands in nature differ markedly from most seen in modern agriculture. In a dense mixed stand, plants must vie for resources, including light, for greater survival and fitness. Competitive advantages over surrounding plants improve fitness of the individual, thus maintaining the competitive traits in the gene pool. In contrast, monoculture crop production strives to increase output at the stand level and thus benefits from cooperation to increase yield of the community. In choosing plants with higher yields to propagate and grow for food, humans may have inadvertently selected the best competitors rather than the best cooperators. Here, we discuss how this selection for competitiveness has led to overinvestment in characteristics that increase light interception and, consequently, sub-optimal light use efficiency in crop fields that constrains yield improvement. Decades of crop canopy modeling research have provided potential strategies for improving light distribution in crop canopies, and we review the current progress of these strategies, including balancing light distribution through reducing pigment concentration. Based on recent research revealing red-shifted photosynthetic pigments in algae and photosynthetic bacteria, we also discuss potential strategies for optimizing light interception and use through introducing alternative pigment types in crops. These strategies for improving light distribution and expanding the wavelengths of light beyond those traditionally defined for photosynthesis in plant canopies may have large implications for improving crop yield and closing the yield gap.
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Affiliation(s)
- Rebecca A Slattery
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Donald R Ort
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Departments of Plant Biology & Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Author for communication:
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13
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Lv Y, Xu J, Liu X. A process-based coupled model of stomatal conductance-photosynthesis-transpiration during leaf ontogeny for water-saving irrigated rice. PHOTOSYNTHESIS RESEARCH 2021; 147:145-160. [PMID: 33389443 DOI: 10.1007/s11120-020-00797-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 11/06/2020] [Indexed: 06/12/2023]
Abstract
Process-based coupled model of stomatal conductance-photosynthesis-transpiration was developed to estimate simultaneously stomatal conductance gsw, photosynthetic rate Pn, and transpiration rate Tr during leaf ontogeny. The modified Jarvis model was constructed by superposing the influence of leaf age LA on gsw in traditional Jarvis model. And the modified Farquhar model was constructed by incorporating the relationships of the LA with parameters in Farquhar model into traditional Farquhar model. The average and leaf-age-based coupled models were constructed, respectively, by combining traditional Farquhar and Penman-Monteith models with traditional Jarvis, and combining modified Farquhar and Penman-Monteith models with modified Jarvis. The results showed that the gsw, the maximum rate of carboxylation, maximum rate of electron transport, rate of triose phosphates utilization, and mitochondrial respiration rate varied in a positive skew pattern, while the mesophyll diffusion conductance decreased linearly with increase in LA. The average coupled model underestimated gsw, Pn, and Tr for young leaves and overestimated gsw, Pn, and Tr for old leaves. And the leaf-age-based coupled model generally perfected well in estimating gsw, Pn, and Tr for all leaves during leaf ontogeny. The study will provide basic information for either modeling leaf gsw, Pn, and Tr continuously, or upscaling them from leaf to canopy scale by considering the variation of LA within canopy.
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Affiliation(s)
- Yuping Lv
- College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, 225009, Jiangsu, China
| | - Junzeng Xu
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, 1 Xikang Road, Nanjing, 210098, Jiangsu, China.
- College of Agricultural Science and Engineering, Hohai University, Nanjing, 210098, Jiangsu, China.
| | - Xiaoyin Liu
- College of Agricultural Science and Engineering, Hohai University, Nanjing, 210098, Jiangsu, China
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14
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Waite JM, Dardick C. The roles of the IGT gene family in plant architecture: past, present, and future. CURRENT OPINION IN PLANT BIOLOGY 2021; 59:101983. [PMID: 33422965 DOI: 10.1016/j.pbi.2020.101983] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 11/13/2020] [Accepted: 12/02/2020] [Indexed: 05/03/2023]
Abstract
Genetic improvement of architectural traits offers tremendous opportunities to dramatically improve crop densities, productivity, and ultimately sustainability. Among these, the orientation, or gravitropic set point angle (GSA), of plant organs is critical to optimize crop profiles, light capture, and nutrient acquisition. Mutant GSA phenotypes have been studied in plants since the 1930's but only recently have the underlying genes been identified. Many of these genes have turned out to fall within the IGT (LAZY1/DRO1/TAC1) family, which initially was not previously recognized due to the lack of sequence conservation of homologous genes across species. Here we discuss recent progress on IGT family genes in various plant species over the past century, review possible functional mechanisms, and provide further analysis of their evolution in land plants and their past and future roles in crop domestication.
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Affiliation(s)
- Jessica Marie Waite
- USDA Tree Fruit Research Laboratory, 1104 N Western Avenue, Wenatchee, WA, USA
| | - Christopher Dardick
- United States Department of Agriculture (USDA) Appalachian Fruit Research Station, 2217 Wiltshire Road, Kearneysville, WV, USA.
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15
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Lv Y, Xu J, Liu X, Wang H. Vertical profile of photosynthetic light response within rice canopy. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2020; 64:1699-1708. [PMID: 32564191 DOI: 10.1007/s00484-020-01950-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 03/15/2020] [Accepted: 03/29/2020] [Indexed: 06/11/2023]
Abstract
Measured leaf photosynthetic light response (PLR) curves at different positions were fitted by non-rectangular hyperbola (NRH) equation to characterize vertical profile of parameters in NRH equation, namely maximum net photosynthetic rate Pnmax, initial quantum yield of assimilation φ, dark respiration rate Rd, and convexity of the curve k, at both jointing and heading stages within rice canopy. And leaf-position-specific and canopy average NRH equations were constructed respectively based on measured PLR curves at each specific leaf position and all measured PLR curves within rice canopy. The results showed that the Pnmax, φ, and Rd reached the maximum at the top second leaf and then decreased at jointing stage and decreased in downward leaves at heading stage. The k increased with lowering leaf position at both stages. The leaf-position-specific NRH equation performed well in estimating net photosynthetic rate Pn for all leaves at different positions and stages, while the canopy average NRH equation underestimated leaf Pn at upper canopy and overestimated Pn at lower canopy. The top fourth leaf was suitable for estimating photosynthetic parameters at canopy scale, as the Pnmax, φ, Rd, and k of the top fourth leaf were near to these parameters of rice canopy, and the canopy average NRH equation performed well in estimating leaf Pn for the top fourth leaf. The results will provide basic information for upscaling leaf photosynthesis to canopy scale.
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Affiliation(s)
- Yuping Lv
- College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, 225009, Jiangsu, China
| | - Junzeng Xu
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, Jiangsu, China.
- College of Agricultural Engineering, Hohai University, Nanjing, 210098, Jiangsu, China.
| | - Xiaoyin Liu
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, Jiangsu, China
- College of Agricultural Engineering, Hohai University, Nanjing, 210098, Jiangsu, China
| | - Haiyu Wang
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, Jiangsu, China
- College of Agricultural Engineering, Hohai University, Nanjing, 210098, Jiangsu, China
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16
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Vidal T, Andrieu B. Contrasting phenotypes emerging from stable rules: A model based on self-regulated control loops captures the dynamics of shoot extension in contrasting maize phenotypes. ANNALS OF BOTANY 2020; 126:615-633. [PMID: 31630162 PMCID: PMC7489064 DOI: 10.1093/aob/mcz168] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 10/16/2019] [Indexed: 05/28/2023]
Abstract
BACKGROUND AND AIMS The dynamics of plant architecture is a central aspect of plant and crop models. Most models assume that whole shoot development is orchestrated by the leaf appearance rate, which follows a thermal time schedule. However, leaf appearance actually results from leaf extension and taking it as an input hampers our ability to understand shoot construction. The objective of the present study was to assess a modelling framework for grasses, in which the emergence of leaves and other organs is explicitly calculated as a result of their extension. METHODS The approach builds on a previous model, which uses a set of rules co-ordinating the timing of development within and between phytomers. We first assessed rule validity for four experimental datasets, including different cultivars, planting densities and environments, and accordingly revised the equations driving the extension of the upper leaves and of internodes. We then fitted model parameters for each dataset and evaluated the ability to simulate the measured phenotypes across time. Finally, we carried out a sensitivity analysis to identify the parameters that had the greatest impact and to investigate model behaviour. KEY RESULTS The modified version of the model simulated correctly the contrasting maize phenotypes. Co-ordination rules accounted for the observations in all studied cultivars. Factors with major impact on model output included extension rates, the time of tassel initiation and initial conditions. A large diversity of phenotypes could be simulated. CONCLUSIONS This work provides direct experimental evidence for co-ordination rules and illustrates the capacity of the model to represent contrasting phenotypes. These rules play an important role in patterning shoot architecture and some of them need to be assessed further, considering contrasting growth conditions. To make the model more predictive, several parameters could be considered in the future as internal variables driven by plant status.
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Affiliation(s)
- T Vidal
- UMR ECOSYS, INRA, AgroParisTech, Université Paris-Saclay, Thiverval-Grignon, France
| | - B Andrieu
- UMR ECOSYS, INRA, AgroParisTech, Université Paris-Saclay, Thiverval-Grignon, France
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Prieto JA, Louarn G, Perez Peña J, Ojeda H, Simonneau T, Lebon E. A functional-structural plant model that simulates whole- canopy gas exchange of grapevine plants (Vitis vinifera L.) under different training systems. ANNALS OF BOTANY 2020; 126:647-660. [PMID: 31837221 PMCID: PMC7489073 DOI: 10.1093/aob/mcz203] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 12/12/2019] [Indexed: 05/28/2023]
Abstract
BACKGROUND AND AIMS Scaling from single-leaf to whole-canopy photosynthesis faces several complexities related to variations in light interception and leaf properties. To evaluate the impact of canopy strucuture on gas exchange, we developed a functional-structural plant model to upscale leaf processes to the whole canopy based on leaf N content. The model integrates different models that calculate intercepted radiation, leaf traits and gas exchange for each leaf in the canopy. Our main objectives were (1) to introduce the gas exchange model developed at the plant level by integrating the leaf-level responses related to canopy structure, (2) to test the model against an independent canopy gas exchange dataset recorded on different plant architectures, and (3) to quantify the impact of intra-canopy N distribution on crop photosynthesis. METHODS The model combined a 3D reconstruction of grapevine (Vitis vinifera) canopy architecture, a light interception model, and a coupled photosynthesis and stomatal conductance model that considers light-driven variations in N distribution. A portable chamber device was constructed to measure whole-plant gas exchange to validate the model outputs with data collected on different training systems. Finally, a sensitivity analysis was performed to evaluate the impact on C assimilation of different N content distributions within the canopy. KEY RESULTS By considering a non-uniform leaf N distribution within the canopy, our model accurately reproduced the daily pattern of gas exchange of different canopy architectures. The gain in photosynthesis permitted by the non-uniform compared with a theoretical uniform N distribution was about 18 %, thereby contributing to the maximization of C assimilation. By contrast, considering a maximal N content for all leaves in the canopy overestimated net CO2 exchange by 28 % when compared with the non-uniform distribution. CONCLUSIONS The model reproduced the gas exchange of plants under different training systems with a low error (10 %). It appears to be a reliable tool to evaluate the impact of a grapevine training system on water use efficiency at the plant level.
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Affiliation(s)
- Jorge A Prieto
- INTA EEA Mendoza, San Martín 3853, Luján de Cuyo (5507), Mendoza, Argentina
| | - Gaetan Louarn
- INRA, UR4 P3F, Route de Saintes, BP 6, F-86600 Lusignan, France
| | - Jorge Perez Peña
- INTA EEA Mendoza, San Martín 3853, Luján de Cuyo (5507), Mendoza, Argentina
| | | | - Thierry Simonneau
- INRA Montpellier SupAgro, UMR759 LEPSE, 2 place Viala, 34060 Montpellier Cedex 01, France
| | - Eric Lebon
- INRA Montpellier SupAgro, UMR759 LEPSE, 2 place Viala, 34060 Montpellier Cedex 01, France
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Chang S, Chang T, Song Q, Wu J, Luo Y, Chen X, Zhu XG, Deng Q. Architectural and Physiological Features to Gain High Yield in an Elite Rice Line YLY1. RICE (NEW YORK, N.Y.) 2020; 13:60. [PMID: 32844350 PMCID: PMC7447700 DOI: 10.1186/s12284-020-00419-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 08/10/2020] [Indexed: 06/11/2023]
Abstract
Identification of traits strongly associated with high yield can help future gene engineering towards improvements of productivity. Here we systematically determine the major architectural and physiological features associated with high yield in two elite historical hybrid rice cultivars, i.e., YLY1 and LYP9. Data from a six-year experiment show that high yield of YLY1 are related to a number of architectural and physiological parameters. Compared to LYP9, YLY1 had 5.5% and 47.3% higher canopy photosynthesis under high and low photosynthetic photon flux densities, respectively, during the grain filling stage, an average 1.5% higher proportion of biomass allocation to above-ground tissues, a 4.5%-10.5% higher photosynthate reserve in leaf sheath before grain filling, and a more efficient photosynthate translocation during grain filling and finally an average 25.2% higher number of productive tillers. These features differ dramatically from features associated with high yield in YLY900 and Yongyou12#, two other high-yielding rice cultivars in China. These identified features and their combinations can support designing new strategies in the future high-yield rice breeding.
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Affiliation(s)
- Shuoqi Chang
- State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center (HHRRC), Changsha, 410125, China
- National Key Laboratory of Plant Molecular Genetics, CAS Center of Excellence for Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, CAS, Shanghai, 200032, China
| | - Tiangen Chang
- National Key Laboratory of Plant Molecular Genetics, CAS Center of Excellence for Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, CAS, Shanghai, 200032, China
| | - Qingfeng Song
- State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center (HHRRC), Changsha, 410125, China
- National Key Laboratory of Plant Molecular Genetics, CAS Center of Excellence for Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, CAS, Shanghai, 200032, China
| | - Jun Wu
- State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center (HHRRC), Changsha, 410125, China
| | - Yi Luo
- State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center (HHRRC), Changsha, 410125, China
| | - Xiaolong Chen
- State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center (HHRRC), Changsha, 410125, China
| | - Xin-Guang Zhu
- National Key Laboratory of Plant Molecular Genetics, CAS Center of Excellence for Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, CAS, Shanghai, 200032, China.
| | - Qiyun Deng
- State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center (HHRRC), Changsha, 410125, China.
- BioRice (Hunan) Co Ltd., Changsha, 410100, China.
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19
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Chang TG, Song QF, Zhao HL, Chang S, Xin C, Qu M, Zhu XG. An in situ approach to characterizing photosynthetic gas exchange of rice panicle. PLANT METHODS 2020; 16:92. [PMID: 32647532 PMCID: PMC7336644 DOI: 10.1186/s13007-020-00633-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 06/24/2020] [Indexed: 05/05/2023]
Abstract
BACKGROUND Photosynthesis of reproductive organs in C3 cereals is generally regarded as important to crop yield. Whereas, photosynthetic characteristics of reproductive organs are much less understood as compared to leaf photosynthesis, mainly due to methodological limitations. To date, many indirect methods have been developed to study photosynthesis of reproductive organs and its contribution to grain yield, such as organ shading, application of herbicides and photosynthetic measurement of excised organs or tissues, which might be intrusive and cause biases. Thus, a robust and in situ approach needs to be developed. RESULTS Here we report the development of a custom-built panicle photosynthesis chamber (P-chamber), which can be connected to standard infrared gas analyzers to study photosynthetic/respiratory rate of a rice panicle. With the P-chamber, we measured panicle photosynthetic characteristics of seven high-yielding elite japonica, japonica-indica hybrid and indica rice cultivars. Results show that, (1) rice panicle is photosynthetically active during grain filling, and there are substantial inter-cultivar variations in panicle photosynthetic and respiratory rates, no matter on a whole panicle basis, on an area basis or on a single spikelet basis; (2) among the seven testing cultivars, whole-panicle gross photosynthetic rates are 17-54 nmol s-1 5 days after heading under photon flux density (PFD) of 2000 μmol (photons) m-2 s-1, which represent some 20-38% of that of the corresponding flag leaves; (3) rice panicle photosynthesis has higher apparent CO2 compensation point, light compensation point and apparent CO2 saturation point, as compared to that of a typical leaf; (4) there is a strong and significant positive correlation between gross photosynthetic rate 5 days after heading on a single spikelet basis and grain setting rate at harvest (Pearson correlation coefficient r = 0.93, p value < 0.0001). CONCLUSIONS Rice panicle gross photosynthesis is significant, has great natural variation, and plays an underappreciated role in grain yield formation. The P-Chamber can be used as a tool to study in situ photosynthetic characteristics of irregular non-foliar plant organs, such as ears, culms, leaf sheaths, fruits and branches, which is a relatively less explored area in current cereal breeding community.
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Affiliation(s)
- Tian-Gen Chang
- National Key Laboratory for Plant Molecular Genetics, Center of Excellence for Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, 200031 China
| | - Qing-Feng Song
- National Key Laboratory for Plant Molecular Genetics, Center of Excellence for Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, 200031 China
| | - Hong-Long Zhao
- National Key Laboratory for Plant Molecular Genetics, Center of Excellence for Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, 200031 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Shuoqi Chang
- State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center, Changsha, China
| | - Changpeng Xin
- CAS Key Laboratory for Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031 China
| | - Mingnan Qu
- National Key Laboratory for Plant Molecular Genetics, Center of Excellence for Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, 200031 China
| | - Xin-Guang Zhu
- National Key Laboratory for Plant Molecular Genetics, Center of Excellence for Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, 200031 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
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Muller B, Martre P. Plant and crop simulation models: powerful tools to link physiology, genetics, and phenomics. JOURNAL OF EXPERIMENTAL BOTANY 2019; 70:2339-2344. [PMID: 31091319 DOI: 10.1093/jxb/erz175] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Affiliation(s)
- Bertrand Muller
- UMR LEPSE, Univ Montpellier, INRA, Montpellier SupAgro, Montpellier, France
| | - Pierre Martre
- UMR LEPSE, Univ Montpellier, INRA, Montpellier SupAgro, Montpellier, France
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