1
|
Gerard G, Mondal S, Piñera-Chávez F, Rivera-Amado C, Molero G, Crossa J, Huerta-Espino J, Velu G, Braun H, Singh R, Crespo-Herrera L. Enhanced radiation use efficiency and grain filling rate as the main drivers of grain yield genetic gains in the CIMMYT elite spring wheat yield trial. Sci Rep 2024; 14:10975. [PMID: 38744876 PMCID: PMC11094180 DOI: 10.1038/s41598-024-60853-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 04/29/2024] [Indexed: 05/16/2024] Open
Abstract
Common wheat (Triticum aestivum L.) is a major staple food crop, providing a fifth of food calories and proteins to the world's human population. Despite the impressive growth in global wheat production in recent decades, further increases in grain yield are required to meet future demands. Here we estimated genetic gain and genotype stability for grain yield (GY) and determined the trait associations that contributed uniquely or in combination to increased GY, through a retrospective analysis of top-performing genotypes selected from the elite spring wheat yield trial (ESWYT) evaluated internationally during a 14-year period (2003 to 2016). Fifty-six ESWYT genotypes and four checks were sown under optimally irrigated conditions in three phenotyping trials during three consecutive growing seasons (2018-2019 to 2020-2021) at Norman E. Borlaug Research Station, Ciudad Obregon, Mexico. The mean GY rose from 6.75 (24th ESWYT) to 7.87 t ha-1 (37th ESWYT), representing a cumulative increase of 1.12 t ha-1. The annual genetic gain for GY was estimated at 0.96% (65 kg ha-1 year-1) accompanied by a positive trend in genotype stability over time. The GY progress was mainly associated with increases in biomass (BM), grain filling rate (GFR), total radiation use efficiency (RUE_total), grain weight per spike (GWS), and reduction in days to heading (DTH), which together explained 95.5% of the GY variation. Regression lines over the years showed significant increases of 0.015 kg m-2 year-1 (p < 0.01), 0.074 g m-2 year-1 (p < 0.05), and 0.017 g MJ-1 year-1 (p < 0.001) for BM, GFR, and RUE_total, respectively. Grain weight per spike exhibited a positive but no significant trend (0.014 g year-1, p = 0.07), whereas a negative tendency for DTH was observed (- 0.43 days year-1, p < 0.001). Analysis of the top ten highest-yielding genotypes revealed differential GY-associated trait contributions, demonstrating that improved GY can be attained through different mechanisms and indicating that no single trait criterion is adopted by CIMMYT breeders for developing new superior lines. We conclude that CIMMYT's Bread Wheat Breeding Program has continued to deliver adapted and more productive wheat genotypes to National partners worldwide, mainly driven by enhancing RUE_total and GFR and that future yield increases could be achieved by intercrossing genetically diverse top performer genotypes.
Collapse
Affiliation(s)
- Guillermo Gerard
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico.
| | - Suchismita Mondal
- Plant Sciences and Plant Pathology Department, Montana State University, Bozeman, MT, 59717, USA
| | - Francisco Piñera-Chávez
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico
| | - Carolina Rivera-Amado
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico
| | - Gemma Molero
- KWS Momont Recherche, 59246, Mons-en-Pévèle, Hauts-de-France, France
| | - Jose Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico
- Colegio de Postgraduados, CP 56230, Montecillos, Mexico, Mexico
| | | | - Govindan Velu
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico
| | - Hans Braun
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico
| | - Ravi Singh
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico
| | - Leonardo Crespo-Herrera
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México- Veracruz Km. 45, El Batán, CP 56237, Texcoco, Mexico, Mexico.
| |
Collapse
|
2
|
Robles-Zazueta CA, Crespo-Herrera LA, Piñera-Chavez FJ, Rivera-Amado C, Aradottir GI. Climate change impacts on crop breeding: Targeting interacting biotic and abiotic stresses for wheat improvement. THE PLANT GENOME 2024; 17:e20365. [PMID: 37415292 DOI: 10.1002/tpg2.20365] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 05/23/2023] [Accepted: 05/30/2023] [Indexed: 07/08/2023]
Abstract
Wheat (Triticum aestivum L.) as a staple crop is closely interwoven into the development of modern society. Its influence on culture and economic development is global. Recent instability in wheat markets has demonstrated its importance in guaranteeing food security across national borders. Climate change threatens food security as it interacts with a multitude of factors impacting wheat production. The challenge needs to be addressed with a multidisciplinary perspective delivered across research, private, and government sectors. Many experimental studies have identified the major biotic and abiotic stresses impacting wheat production, but fewer have addressed the combinations of stresses that occur simultaneously or sequentially during the wheat growth cycle. Here, we argue that biotic and abiotic stress interactions, and the genetics and genomics underlying them, have been insufficiently addressed by the crop science community. We propose this as a reason for the limited transfer of practical and feasible climate adaptation knowledge from research projects into routine farming practice. To address this gap, we propose that novel methodology integration can align large volumes of data available from crop breeding programs with increasingly cheaper omics tools to predict wheat performance under different climate change scenarios. Underlying this is our proposal that breeders design and deliver future wheat ideotypes based on new or enhanced understanding of the genetic and physiological processes that are triggered when wheat is subjected to combinations of stresses. By defining this to a trait and/or genetic level, new insights can be made for yield improvement under future climate conditions.
Collapse
Affiliation(s)
- Carlos A Robles-Zazueta
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, México
| | | | | | - Carolina Rivera-Amado
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, México
| | | |
Collapse
|
3
|
Zhang Z, Sun W, Wen L, Liu Y, Guo X, Liu Y, Yao C, Xue Q, Sun Z, Wang Z, Zhang Y. Dynamic gene regulatory networks improving spike fertility through regulation of floret primordia fate in wheat. PLANT, CELL & ENVIRONMENT 2023; 46:3628-3643. [PMID: 37485926 DOI: 10.1111/pce.14672] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 07/09/2023] [Accepted: 07/11/2023] [Indexed: 07/25/2023]
Abstract
The developmental process of spike is critical for spike fertility through affecting floret primordia fate in wheat; however, the genetic regulation of this dynamic and complex developmental process remains unclear. Here, we conducted a high temporal-resolution analysis of spike transcriptomes and monitored the number and morphology of floret primordia within spike. The development of all floret primordia in a spike was clearly separated into three distinct phases: differentiation, pre-dimorphism and dimorphism. Notably, we identified that floret primordia with meiosis ability at the pre-dimorphism phase usually develop into fertile floret primordia in the next dimorphism phase. Compared to control, increasing plant space treatment achieved the maximum increasement range (i.e., 50%) in number of fertile florets by accelerating spike development. The process of spike fertility improvement was directed by a continuous and dynamic regulatory network involved in transcription factor and genes interaction. This was based on the coordination of genes related to heat shock protein and jasmonic acid biosynthesis during differentiation phase, and genes related to lignin, anthocyanin and chlorophyll biosynthesis during dimorphism phase. The multi-dimensional association with high temporal-resolution approach reported here allows rapid identification of genetic resource for future breeding studies to realise the maximum spike fertility potential in more cereal crops.
Collapse
Affiliation(s)
- Zhen Zhang
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- College of Biological Sciences, China Agricultural University, Beijing, China
| | - Wan Sun
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Liangyun Wen
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Yaqun Liu
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Xiaolei Guo
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Ying Liu
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Chunsheng Yao
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Qingwu Xue
- Texas A&M AgriLife Research and Extension Center at Amarillo, Amarillo, Texas, USA
| | - Zhencai Sun
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- Engineering Technology Research Center for Agriculture in Low Plain Areas, Hebei Province, China
| | - Zhimin Wang
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- Engineering Technology Research Center for Agriculture in Low Plain Areas, Hebei Province, China
| | - Yinghua Zhang
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- Engineering Technology Research Center for Agriculture in Low Plain Areas, Hebei Province, China
| |
Collapse
|
4
|
Pokhrel A, Virk S, Snider JL, Vellidis G, Hand LC, Sintim HY, Parkash V, Chalise DP, Lee JM, Byers C. Estimating yield-contributing physiological parameters of cotton using UAV-based imagery. FRONTIERS IN PLANT SCIENCE 2023; 14:1248152. [PMID: 37794937 PMCID: PMC10546020 DOI: 10.3389/fpls.2023.1248152] [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: 06/26/2023] [Accepted: 08/29/2023] [Indexed: 10/06/2023]
Abstract
Lint yield in cotton is governed by light intercepted by the canopy (IPAR), radiation use efficiency (RUE), and harvest index (HI). However, the conventional methods of measuring these yield-governing physiological parameters are labor-intensive, time-consuming and requires destructive sampling. This study aimed to explore the use of low-cost and high-resolution UAV-based RGB and multispectral imagery 1) to estimate fraction of IPAR (IPARf), RUE, and biomass throughout the season, 2) to estimate lint yield using the cotton fiber index (CFI), and 3) to determine the potential use of biomass and lint yield models for estimating cotton HI. An experiment was conducted during the 2021 and 2022 growing seasons in Tifton, Georgia, USA in randomized complete block design with five different nitrogen treatments. Different nitrogen treatments were applied to generate substantial variability in canopy development and yield. UAV imagery was collected bi-weekly along with light interception and biomass measurements throughout the season, and 20 different vegetation indices (VIs) were computed from the imagery. Generalized linear regression was performed to develop models using VIs and growing degree days (GDDs). The IPARf models had R2 values ranging from 0.66 to 0.90, and models based on RVI and RECI explained the highest variation (93%) in IPARf during cross-validation. Similarly, cotton above-ground biomass was best estimated by models from MSAVI and OSAVI. Estimation of RUE using actual biomass measurement and RVI-based IPARf model was able to explain 84% of variation in RUE. CFI from UAV-based RGB imagery had strong relationship (R2 = 0.69) with machine harvested lint yield. The estimated HI from CFI-based lint yield and MSAVI-based biomass models was able to explain 40 to 49% of variation in measured HI for the 2022 growing season. The models developed to estimate the yield-contributing physiological parameters in cotton showed low to strong performance, with IPARf and above-ground biomass having greater prediction accuracy. Future studies on accurate estimation of lint yield is suggested for precise cotton HI prediction. This study is the first attempt of its kind and the results can be used to expand and improve research on predicting functional yield drivers of cotton.
Collapse
Affiliation(s)
- Amrit Pokhrel
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - Simerjeet Virk
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - John L. Snider
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - George Vellidis
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - Lavesta C. Hand
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - Henry Y. Sintim
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - Ved Parkash
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - Devendra P. Chalise
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - Joshua M. Lee
- Department of Crop and Soil Sciences, University of Georgia, Tifton, GA, United States
| | - Coleman Byers
- College of Engineering, University of Georgia, Athens, GA, United States
| |
Collapse
|
5
|
Safdar LB, Dugina K, Saeidan A, Yoshicawa GV, Caporaso N, Gapare B, Umer MJ, Bhosale RA, Searle IR, Foulkes MJ, Boden SA, Fisk ID. Reviving grain quality in wheat through non-destructive phenotyping techniques like hyperspectral imaging. Food Energy Secur 2023; 12:e498. [PMID: 38440412 PMCID: PMC10909436 DOI: 10.1002/fes3.498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 08/10/2023] [Accepted: 08/14/2023] [Indexed: 03/06/2024] Open
Abstract
A long-term goal of breeders and researchers is to develop crop varieties that can resist environmental stressors and produce high yields. However, prioritising yield often compromises improvement of other key traits, including grain quality, which is tedious and time-consuming to measure because of the frequent involvement of destructive phenotyping methods. Recently, non-destructive methods such as hyperspectral imaging (HSI) have gained attention in the food industry for studying wheat grain quality. HSI can quantify variations in individual grains, helping to differentiate high-quality grains from those of low quality. In this review, we discuss the reduction of wheat genetic diversity underlying grain quality traits due to modern breeding, key traits for grain quality, traditional methods for studying grain quality and the application of HSI to study grain quality traits in wheat and its scope in breeding. Our critical review of literature on wheat domestication, grain quality traits and innovative technology introduces approaches that could help improve grain quality in wheat.
Collapse
Affiliation(s)
- Luqman B. Safdar
- International Flavour Research Centre, Division of Food, Nutrition and DieteticsUniversity of NottinghamLoughboroughUK
- International Flavour Research Centre (Adelaide), School of Agriculture, Food and Wine and Waite Research InstituteUniversity of AdelaideGlen OsmondSouth AustraliaAustralia
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamLoughboroughUK
- Plant Research Centre, School of Agriculture, Food and WineUniversity of AdelaideGlen OsmondSouth AustraliaAustralia
| | - Kateryna Dugina
- International Flavour Research Centre, Division of Food, Nutrition and DieteticsUniversity of NottinghamLoughboroughUK
| | - Ali Saeidan
- International Flavour Research Centre, Division of Food, Nutrition and DieteticsUniversity of NottinghamLoughboroughUK
| | - Guilherme V. Yoshicawa
- Plant Research Centre, School of Agriculture, Food and WineUniversity of AdelaideGlen OsmondSouth AustraliaAustralia
| | | | - Brighton Gapare
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamLoughboroughUK
| | - M. Jawad Umer
- Cotton Research InstituteChinese Academy of Agricultural SciencesAnyangChina
| | - Rahul A. Bhosale
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamLoughboroughUK
| | - Iain R. Searle
- School of Biological SciencesUniversity of AdelaideAdelaideSouth AustraliaAustralia
| | - M. John Foulkes
- Division of Plant and Crop Sciences, School of BiosciencesUniversity of NottinghamLoughboroughUK
| | - Scott A. Boden
- Plant Research Centre, School of Agriculture, Food and WineUniversity of AdelaideGlen OsmondSouth AustraliaAustralia
| | - Ian D. Fisk
- International Flavour Research Centre, Division of Food, Nutrition and DieteticsUniversity of NottinghamLoughboroughUK
- International Flavour Research Centre (Adelaide), School of Agriculture, Food and Wine and Waite Research InstituteUniversity of AdelaideGlen OsmondSouth AustraliaAustralia
| |
Collapse
|
6
|
Murchie EH, Reynolds M, Slafer GA, Foulkes MJ, Acevedo-Siaca L, McAusland L, Sharwood R, Griffiths S, Flavell RB, Gwyn J, Sawkins M, Carmo-Silva E. A 'wiring diagram' for source strength traits impacting wheat yield potential. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:72-90. [PMID: 36264277 PMCID: PMC9786870 DOI: 10.1093/jxb/erac415] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 10/18/2022] [Indexed: 05/06/2023]
Abstract
Source traits are currently of great interest for the enhancement of yield potential; for example, much effort is being expended to find ways of modifying photosynthesis. However, photosynthesis is but one component of crop regulation, so sink activities and the coordination of diverse processes throughout the crop must be considered in an integrated, systems approach. A set of 'wiring diagrams' has been devised as a visual tool to integrate the interactions of component processes at different stages of wheat development. They enable the roles of chloroplast, leaf, and whole-canopy processes to be seen in the context of sink development and crop growth as a whole. In this review, we dissect source traits both anatomically (foliar and non-foliar) and temporally (pre- and post-anthesis), and consider the evidence for their regulation at local and whole-plant/crop levels. We consider how the formation of a canopy creates challenges (self-occlusion) and opportunities (dynamic photosynthesis) for components of photosynthesis. Lastly, we discuss the regulation of source activity by feedback regulation. The review is written in the framework of the wiring diagrams which, as integrated descriptors of traits underpinning grain yield, are designed to provide a potential workspace for breeders and other crop scientists that, along with high-throughput and precision phenotyping data, genetics, and bioinformatics, will help build future dynamic models of trait and gene interactions to achieve yield gains in wheat and other field crops.
Collapse
Affiliation(s)
- Erik H Murchie
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Sutton Bonington LE12 5RD, UK
| | - Matthew Reynolds
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, Mexico
| | - Gustavo A Slafer
- Department of Crop and Forest Sciences, University of Lleida–AGROTECNIO-CERCA Center, Av. R. Roure 191, 25198 Lleida, Spain
- ICREA (Catalonian Institution for Research and Advanced Studies), Barcelona, Spain
| | - M John Foulkes
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Sutton Bonington LE12 5RD, UK
| | - Liana Acevedo-Siaca
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, Mexico
| | - Lorna McAusland
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Sutton Bonington LE12 5RD, UK
| | - Robert Sharwood
- Hawkesbury Institute for the Environment, Western Sydney University, Richmond NSW 2753, Australia
| | - Simon Griffiths
- John Innes Centre, Norwich Research Park, Colney Ln, Norwich NR4 7UH, UK
| | - Richard B Flavell
- International Wheat Yield Partnership, 1500 Research Parkway, College Station, TX 77843, USA
| | - Jeff Gwyn
- International Wheat Yield Partnership, 1500 Research Parkway, College Station, TX 77843, USA
| | - Mark Sawkins
- International Wheat Yield Partnership, 1500 Research Parkway, College Station, TX 77843, USA
| | | |
Collapse
|
7
|
Mohammed U, Davis J, Rossall S, Swarup K, Czyzewicz N, Bhosale R, Foulkes J, Murchie EH, Swarup R. Phosphite treatment can improve root biomass and nutrition use efficiency in wheat. FRONTIERS IN PLANT SCIENCE 2022; 13:1017048. [PMID: 36388577 PMCID: PMC9662169 DOI: 10.3389/fpls.2022.1017048] [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: 08/11/2022] [Accepted: 10/06/2022] [Indexed: 06/16/2023]
Abstract
Phosphite represents a reduced form of phosphate that belongs to a class of crop growth-promoting chemicals termed biostimulants. Previous research has shown that phosphite application can enhance root growth, but its underlying mechanism, especially during environmental stresses, remains elusive. To uncover this, we undertook a series of morphological and physiological analyses under nutrient, water and heat stresses following a foliar application in wheat. Non-invasive 3D imaging of root system architecture directly in soil using X-ray Computed Tomography revealed that phosphite treatment improves root architectural traits and increased root biomass. Biochemical and physiological assays identified that phosphite treatment significantly increases Nitrate Reductase (NR) activity, leaf photosynthesis and stomatal conductance, suggesting improved Nitrogen and Carbon assimilation, respectively. These differences were more pronounced under heat or drought treatment (photosynthesis and photosystem II stability) and nutrient deficiency (root traits and NR). Overall our results suggest that phosphite treatment improves the ability of plants to tolerate abiotic stresses through improved Nitrogen and Carbon assimilation, combined with improved root growth which may improve biomass and yield.
Collapse
Affiliation(s)
- Umar Mohammed
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
| | - Jayne Davis
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
| | - Steve Rossall
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
| | - Kamal Swarup
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
| | - Nathan Czyzewicz
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
- Mars Petcare, Melton Mowbray, United Kingdom
| | - Rahul Bhosale
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
- Future Food Beacon of Excellence, University of Nottingham, Nottingham, United Kingdom
| | - John Foulkes
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
| | - Erik H. Murchie
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
| | - Ranjan Swarup
- Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Nottingham, United Kingdom
- Centre for Plant Integrative Biology, University of Nottingham, Nottingham, United Kingdom
| |
Collapse
|
8
|
Robles-Zazueta CA, Pinto F, Molero G, Foulkes MJ, Reynolds MP, Murchie EH. Prediction of Photosynthetic, Biophysical, and Biochemical Traits in Wheat Canopies to Reduce the Phenotyping Bottleneck. FRONTIERS IN PLANT SCIENCE 2022; 13:828451. [PMID: 35481146 PMCID: PMC9036448 DOI: 10.3389/fpls.2022.828451] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 01/25/2022] [Indexed: 06/14/2023]
Abstract
To achieve food security, it is necessary to increase crop radiation use efficiency (RUE) and yield through the enhancement of canopy photosynthesis to increase the availability of assimilates for the grain, but its study in the field is constrained by low throughput and the lack of integrative measurements at canopy level. In this study, partial least squares regression (PLSR) was used with high-throughput phenotyping (HTP) data in spring wheat to build predictive models of photosynthetic, biophysical, and biochemical traits for the top, middle, and bottom layers of wheat canopies. The combined layer model predictions performed better than individual layer predictions with a significance as follows for photosynthesis R 2 = 0.48, RMSE = 5.24 μmol m-2 s-1 and stomatal conductance: R 2 = 0.36, RMSE = 0.14 mol m-2 s-1. The predictions of these traits from PLSR models upscaled to canopy level compared to field observations were statistically significant at initiation of booting (R 2 = 0.3, p < 0.05; R 2 = 0.29, p < 0.05) and at 7 days after anthesis (R 2 = 0.15, p < 0.05; R 2 = 0.65, p < 0.001). Using HTP allowed us to increase phenotyping capacity 30-fold compared to conventional phenotyping methods. This approach can be adapted to screen breeding progeny and genetic resources for RUE and to improve our understanding of wheat physiology by adding different layers of the canopy to physiological modeling.
Collapse
Affiliation(s)
- Carlos A. Robles-Zazueta
- Division of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Leicestershire, United Kingdom
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Francisco Pinto
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Gemma Molero
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - M. John Foulkes
- Division of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Leicestershire, United Kingdom
| | - Matthew P. Reynolds
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Erik H. Murchie
- Division of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Leicestershire, United Kingdom
| |
Collapse
|
9
|
Ma J, Zheng B, He Y. Applications of a Hyperspectral Imaging System Used to Estimate Wheat Grain Protein: A Review. FRONTIERS IN PLANT SCIENCE 2022; 13:837200. [PMID: 35463397 PMCID: PMC9024351 DOI: 10.3389/fpls.2022.837200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/10/2022] [Indexed: 06/01/2023]
Abstract
Recent research advances in wheat have focused not only on increasing grain yields, but also on establishing higher grain quality. Wheat quality is primarily determined by the grain protein content (GPC) and composition, and both of these are affected by nitrogen (N) levels in the plant as it develops during the growing season. Hyperspectral remote sensing is gradually becoming recognized as an economical alternative to traditional destructive field sampling methods and laboratory testing as a means of determining the N status within wheat. Currently, hyperspectral vegetation indices (VIs) and linear nonparametric regression are the primary tools for monitoring the N status of wheat. Machine learning algorithms have been increasingly applied to model the nonlinear relationship between spectral data and wheat N status. This study is a comprehensive review of available N-related hyperspectral VIs and aims to inform the selection of VIs under field conditions. The combination of feature mining and machine learning algorithms is discussed as an application of hyperspectral imaging systems. We discuss the major challenges and future directions for evaluating and assessing wheat N status. Finally, we suggest that the underlying mechanism of protein formation in wheat grains as determined by using hyperspectral imaging systems needs to be further investigated. This overview provides theoretical and technical support to promote applications of hyperspectral imaging systems in wheat N status assessments; in addition, it can be applied to help monitor and evaluate food and nutrition security.
Collapse
Affiliation(s)
- Junjie Ma
- Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bangyou Zheng
- CSIRO Agriculture and Food, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
| | - Yong He
- Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China
| |
Collapse
|