-
Richards, R. A. Selectable traits to increase crop photosynthesis and yield of grain crops. J. Exp. Bot. 51, 447–458 (2000).
-
Ort, D. R. et al. Redesigning photosynthesis to sustainably meet global food and bioenergy demand. Proc. Natl. Acad. Sci. U. S. A. 112, 8529–8536 (2015).
-
Dohleman, F. G. & Long, S. P. More productive than maize in the Midwest: How does Miscanthus do it? Plant Physiol. 150, 2104–2115 (2009).
-
Milford, G. Plant Structure and Crop Physiology. in Sugar Beet 30–49 (2007). doi:10.1002/9780470751114.ch3.
-
Hoffmann, C. M. Importance of canopy closure and dry matter partitioning for yield formation of sugar beet varieties. F. Crop. Res. 236, 75–84 (2019).
-
Jannink, J. L., Orf, J. H., Jordan, N. R. & Shaw, R. G. Index selection for weed suppressive ability in soybean. Crop Sci. 40, 1087–1094 (2000).
-
Jannink, J. L., Jordan, N. R. & Orf, J. H. Feasibility of selection for high weed suppressive ability in soybean: Absence of tradeoffs between rapid initial growth and sustained later growth. Euphytica 120, 291–300 (2001).
-
Purcell, L. C. & Specht, J. E. Physiological traits for ameliorating drought stress. Soybeans Improv. Prod. uses 16, 569–620 (2004).
-
Boerma, H. R. & Specht, J. E. Soybeans: Improvement, Production, and Uses, 3rd edn. Madison, WI, USA: ASA, CSSA & SSSA. Inc. Publ. 562 (2004).
-
Horton, P. Prospects for crop improvement through the genetic manipulation of photosynthesis : morphological and biochemical aspects of light capture. 51, 475–485 (2000).
-
Guo, Y. et al. Parameter optimization and field validation of the functional-structural model GREENLAB for maize. Ann. Bot. 97, 217–230 (2006).
-
Zheng, B. et al. Comparison of architecture among different cultivars of hybrid rice using a spatial light model based on 3-D digitising. Funct. Plant Biol. 35, 900–910 (2008).
-
Zhu, X. G., Long, S. P. & Ort, D. R. What is the maximum efficiency with which photosynthesis can convert solar energy into biomass? Curr. Opin. Biotechnol. 19, 153–159 (2008).
-
Reynolds, M., Manes, Y., Izanloo, A. & Langridge, P. Phenotyping approaches for physiological breeding and gene discovery in wheat. Ann. Appl. Biol. 155, 309–320 (2009).
-
Sarlikioti, V., Visser, P. H. B. De & Marcelis, L. F. M. How plant architecture affects light absorption and photosynthesis in tomato : towards an ideotype for plant architecture using a functional – structural plant model. Ann. Botany. 1065–1073 (2011) doi:10.1093/aob/mcr221.
-
Zhu, X. G., Song, Q. & Ort, D. R. Elements of a dynamic systems model of canopy photosynthesis. Curr. Opin. Plant Biol. 15, 237–244 (2012).
-
Sheehy, J. E. & Mitchell, P. L. Field Crops Research Calculating maximum theoretical yield in rice. F. Crop. Res. 182, 68–75 (2015).
-
Burgess, A. J., Retkute, R., Herman, T. & Murchie, E. H. Exploring relationships between canopy architecture, light distribution, and photosynthesis in contrasting rice genotypes using 3D canopy reconstruction. Front. Plant Sci. 8, 1–15 (2017).
-
Zhu, X.-G., Long, S. P. & Ort, D. R. Improving Photosynthetic Efficiency for Greater Yield. Annu. Rev. Plant Biol. 61, 235–261 (2010).
-
Willcott, J., Herbert, S. J. & Zhi-Yi, L. Leaf area display and light interception in short-season soybeans. F. Crop. Res. 9, 173–182 (1984).
-
Srinivasan, V., Kumar, P. & Long, S. P. Decreasing, not increasing, leaf area will raise crop yields under global atmospheric change. Glob. Chang. Biol. 23, 1626–1635 (2017).
-
Ort, D. R. et al. Redesigning photosynthesis to sustainably meet global food and bioenergy demand. Proc. Natl. Acad. Sci. 112, 8529–8536 (2015).
-
Ainsworth, E. A., Yendrek, C. R., Skoneczka, J. A. & Long, S. P. Accelerating yield potential in soybean: Potential targets for biotechnological improvement. Plant, Cell Environ. 35, 38–52 (2012).
-
De Bruin, J. L. & Pedersen, P. Growth, yield, and yield component changes among old and new soybean cultivars. Agron. J. 101, 124–130 (2009).
-
Lee, C. D., Egli, D. B. & TeKrony, D. M. Soybean response to plant population at early and late planting dates in the Mid-South. Agron. J. 100, 971–976 (2008).
-
Jarquin, D., Howard, R., Xavier, A. & Choudhury, S. Das. Increasing predictive ability by modeling interactions between environments, genotype and canopy coverage image data for soybeans. Agronomy 8, (2018).
-
Drewry, D. T. et al. Ecohydrological responses of dense canopies to environmental variability: 1. Interplay between vertical structure and photosynthetic pathway. J. Geophys. Res. Biogeosciences 115, 1–25 (2010).
-
Drewry, D. T., Kumar, P. & Long, S. P. Simultaneous improvement in productivity, water use, and albedo through crop structural modification. Glob. Chang. Biol. 20, 1955–1967 (2014).
-
Xavier, A., Hall, B., Hearst, A. A., Cherkauer, K. A. & Rainey, K. M. Genetic Architecture of Phenomic-Enabled Canopy. Genetics 206, 1081–1089 (2017).
-
Kaler, A. S. et al. Association mapping identifies loci for canopy coverage in diverse soybean genotypes. Mol. Breed. 38, (2018).
-
Zhang, H. et al. Genetic dissection of the relationship between plant architecture and yield component traits in soybean (Glycine max) by association analysis across multiple environments. Plant Breed. 134, 564–572 (2015).
-
Han, Y. et al. Domestication footprints anchor genomic regions of agronomic importance in soybeans. New Phytol. 209, 871–884 (2016).
-
Shim, S., Kim, M. Y., Ha, J., Lee, Y. H. & Lee, S. H. Identification of QTLs for branching in soybean (Glycine max (L.) Merrill). Euphytica 213, 1–9 (2017).
-
Fang, C. et al. Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean. Genome Biol. 18, (2017).
-
Wang, L. et al. QTL fine-mapping of soybean (Glycine max L.) leaf type associated traits in two RILs populations. BMC Genomics 20, 1–15 (2019).
-
Diers, B. W. et al. Genetic architecture of soybean yield and agronomic traits. G3 Genes, Genomes, Genet. 8, 3367–3375 (2018).
-
Assefa, T. et al. Genome-wide associations and epistatic interactions for internode number, plant height, seed weight and seed yield in soybean. BMC Genomics 20, 1–12 (2019).
-
Wen, Z., Boyse, J. F., Song, Q., Cregan, P. B. & Wang, D. Genomic consequences of selection and genome-wide association mapping in soybean. BMC Genomics 16, 1–14 (2015).
-
Zhang, J. et al. Genome-wide association study for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm. BMC Genomics 16, 1–11 (2015).
-
Tian, Z. et al. Artificial selection for determinate growth habit in soybean. Proc. Natl. Acad. Sci. U. S. A. 107, 8563–8568 (2010).
-
Liu, B. et al. The soybean stem growth habit gene Dt1 is an ortholog of arabidopsis TERMINAL FLOWER1. Plant Physiol. 153, 198–210 (2010).
-
Ping, J. et al. Dt2 is a gain-of-function MADS-domain factor gene that specifies semideterminacy in soybean. Plant Cell 26, 2831–2842 (2014).
-
Jeong, N. et al. Ln is a key regulator of leaflet shape and number of seeds per pod in soybean. Plant Cell 24, 4807–4818 (2013).
-
Shim, S. et al. GmBRC1 is a candidate gene for branching in soybean (Glycine max (L.) Merrill). Int. J. Mol. Sci. 20, 135 (2019).
-
Li, Z. et al. Identification of the dwarf gene GmDW1 in soybean (Glycine max L.) by combining mapping-by-sequencing and linkage analysis. Theor. Appl. Genet. 131, 1001–1016 (2018).
-
Gao, J. et al. GmILPA1, encoding an APC8-like protein, controls leaf petiole angle in soybean. Plant Physiol. 174, 1167–1176 (2017).
-
Bandillo, N. et al. A Population Structure and Genome-Wide Association Analysis on the USDA Soybean Germplasm Collection. Plant Genome 8, plantgenome2015.04.0024 (2015).
-
Song, Q. et al. Development and Evaluation of SoySNP50K, a High-Density Genotyping Array for Soybean. PLoS One 8, 1–12 (2013).
-
Zabala, G. & Vodkin, L. O. A rearrangement resulting in small tandem repeats in the F3′5′H gene of white flower genotypes is associated with the soybean W1 locus. Crop Sci. 47, 113–124 (2007).
-
Zabala, G. & Vodkin, L. Cloning of the pleiotropic T locus in soybean and two recessive alleles that differentially affect structure and expression of the encoded flavonoid 3′ hydroxylase. Genetics 163, 295–309 (2003).
-
Bandillo, N. B. et al. Genome-wide Association Mapping of Qualitatively Inherited Traits in a Germplasm Collection. Plant Genome 10, plantgenome2016.06.0054 (2017).
-
Yan, F. et al. Loss-of-Function Mutation of Soybean R2R3 MYB Transcription Factor Dilutes Tawny Pubescence Color. Front. Plant Sci. 10, 1–12 (2020).
-
Xia, Z. et al. Positional cloning and characterization reveal the molecular basis for soybean maturity locus E1 that regulates photoperiodic flowering. Proc. Natl. Acad. Sci. U. S. A. 109, (2012).
-
Watanabe, S. et al. A map-based cloning strategy employing a residual heterozygous line reveals that the GIGANTEA gene is involved in soybean maturity and flowering. Genetics 188, 395–407 (2011).
-
Bernard, R. L. Two Genes Affecting Stem Termination in Soybeans 1. Crop Sci. 12, 235–239 (1972).
-
Wu, H. T., Zhang, Y., Su, B. H., Sobhi, L. F. & Qiu, L. J. Development of molecular markers and fine mapping of qBN-18 locus related to branch number in soybean (Glycine max L.). Acta Agron. Sin. 46, 1667–1677 (2020).
-
Kaler, A. S. et al. Association mapping identifies loci for canopy coverage in diverse soybean genotypes. Mol. Breed. 38, (2018).
-
Parvez, A. Q., Gardner, F. P. & Boote, K. J. Determinate-and indeterminate‐type soybean cultivar responses to pattern, density, and planting date. Crop Sci. 29, 150–157 (1989).
-
Sun, C. et al. Genome-Wide Association Study Dissecting the Genetic Architecture Underlying the Branch Angle Trait in Rapeseed (Brassica napus L.). Sci. Rep. 6, 1–11 (2016).
-
Liu, J. et al. Characterizing variation of branch angle and genome-wide association mapping in rapeseed (Brassica napus L.). Front. Plant Sci. 7, 1–10 (2016).
-
Li, H. et al. Genome-wide association mapping reveals the genetic control underlying branch angle in rapeseed (Brassica napus L.). Front. Plant Sci. 8, (2017).
-
Lin, C. & Poushinsky, G. G. A modified augmented design (type 2) for rectangular plots. 1985. Can. J. Plant Sci. 749, 743–749 (1985).
-
Dobbels, A. A. & Lorenz, A. J. Soybean iron deficiency chlorosis high throughput phenotyping using an unmanned aircraft system. Plant Methods 15, 1–9 (2019).
-
Bradbury, P. J. et al. TASSEL: Software for association mapping of complex traits in diverse samples. Bioinformatics 23, 2633–2635 (2007).
-
EVANNO, G., REGNAUT, S. & GOUDET, J. Detecting the number of clusters of individuals using the software structure: a simulation study. Mol. Ecol. 14, 2611–2620 (2005).
-
Earl, D. A. & vonHoldt, B. M. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361 (2012).
-
Barrett, J. C., Fry, B., Maller, J. & Daly, M. J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265 (2005).
-
Lipka, A. E. et al. GAPIT: genome association and prediction integrated tool. Bioinformatics 28, 2397–2399 (2012).
-
Zhang, Z. et al. Mixed linear model approach adapted for genome-wide association studies. Nat. Genet. 42, 355–360 (2010).