Identification of superior genotypes for leaf architecture traits in Sorghum bicolor through GGE biplot analysis
Runfeng Wang A B , Yingxing Zhao A B , Hailian Wang A B , Erying Chen A B , Feifei Li A B , Shaoming Huang C , Ling Qin A B , Yanbing Yang A B , Yan’an Guan A B , Bin Liu A B and Huawen Zhang A B *A
B
C
Abstract
Well-organised leaf architecture produces compact canopies and allows for greater sunlight penetration, higher photosynthetic rates, and thus greater yields. Breeding for enhanced leaf architecture of sorghum (Sorghum bicolor L.), a key food source in semi-arid regions, benefits its overall production.
The study focuses on selecting useful genotypes with excellent leaf architecture for grain sorghum improvement.
In total, 185 sorghum genotypes were subjected to multi-environment trials. Leaf flagging-point length, leaf length, leaf width, leaf angle and leaf orientation value (LOV) were characterised under field conditions. Genotype + genotype × environment interaction (GGE) biplot analysis was used to identify the most stable genotypes with the highest LOV.
Statistical analysis showed significant effects of genotype × environment interaction (P < 0.001), and high broad-sense heritability for the traits. Correlation analysis demonstrated negative correlations (P < 0.001) between LOV and its components. Singular value decomposition of LOVs in the first two principal components explained 89.19% of the total variation. GGE biplot analysis identified G55 as the ideotype with the highest and most stable LOV.
Leaf architecture optimisation should be given greater attention. This study has identified a genotype with optimal and stable leaf architecture, laying the foundation for improvement in breeding to increase overall yields of sorghum.
Genotype G55 can be utilised as a parent with other parents that display economically important characteristics in breeding programs to produce offspring that can be planted densely to increase population yields. Genotypes identified with loose leaf architecture are useful in dissecting genes controlling leaf architecture by crossing with G55 to construct genetic mapping populations.
Keywords: genotype by environment interaction, germplasm collection, GGE biplot, grain sorghum, leaf architectural traits, leaf orientation value, multi-environment trials, stability test.
References
Akcura M, Taner S, Kaya Y (2011) Evaluation of bread wheat genotypes under irrigated multi-environment conditions using GGE biplot analyses. Zemdirbyste-Agriculture 98, 35-40.
| Google Scholar |
Alkharabsheh HM, Seleiman MF, Hewedy OA, Battaglia ML, Jalal RS, Alhammad BA, Schillaci C, Ali N, Al-Doss A (2021) Field crop responses and management strategies to mitigate soil salinity in modern agriculture: a review. Agronomy 11, 2299.
| Crossref | Google Scholar |
Bakari H, Djomdi D, Ruben ZF, Roger DD, Cedric D, Guillaume P, Pascal D, Philippe M, Gwendoline C (2023) Sorghum (Sorghum bicolor L. Moench) and its main parts (by-products) as promising sustainable sources of value-added ingredients. Waste and Biomass Valorization 14, 1023-1044.
| Crossref | Google Scholar |
Balestre M, Von Pinho RG, Souza JC, Oliveira RL (2009) Genotypic stability and adaptability in tropical maize based on AMMI and GGE biplot analysis. Genetics and Molecular Research 8, 1311-1322.
| Crossref | Google Scholar | PubMed |
Bao Y, Tang L, Srinivasan S, Schnable PS (2019) Field-based architectural traits characterisation of maize plant using time-of-flight 3D imaging. Biosystems Engineering 178, 86-101.
| Crossref | Google Scholar |
Bojovic R, Popovic VM, Ikanovic J, Zivanovic L, Rakascan N, Popovic S, Ugrenovic V, Simic D (2019) Morphological characterization of sweet sorghum genotypes across environments. Journal of Animal and Plant Sciences 29, 721-729.
| Google Scholar |
Cai Y, Wang J, Sun H, Wang G (2002) Genetic model of several plant-type characters and their canonical correlation with ear-kernel characters in maize. Acta Agronomica Sinica 28, 829-834.
| Google Scholar |
Carvalho MP, Nunes JAR, Carmo ELd, Simon GA, Moraes RNO (2021) Adaptability and stability of conventional soybean by GGE biplot analysis. Pesquisa Agropecuaria Tropical 51, e67995.
| Crossref | Google Scholar |
Dehghani MR, Majidi MM, Saeidi G, Mirlohi A, Amiri R, Sorkhilalehloo B (2015) Application of GGE biplot to analyse stability of Iranian tall fescue (Lolium arundinaceum) genotypes. Crop & Pasture Science 66, 963-972.
| Crossref | Google Scholar |
Eberhart SA, Russel WA (1966) Stability parameters for comparing varieties. Crop Science 6, 36-40.
| Crossref | Google Scholar |
Fang W, Feng H, Yang W, Duan L, Chen G, Xiong L, Liu Q (2016) High-throughput volumetric reconstruction for 3D wheat plant architecture studies. Journal of Innovative Optical Health Sciences 9, 1650037.
| Crossref | Google Scholar |
FAOSTAT (2021) Food and Agriculture Data. Available at https://www.fao.org/faostat/en/
Ghazvini H, Bagherikia S, Pour-Aboughadareh A, Sharifalhossaini M, Razavi SA, Mohammadi S, GhasemiKalkhoran M, Fathihafshejani A, Khakizade G (2022) GGE biplot analysis of promising barley lines in the cold regions of Iran. Journal of Crop Improvement 36, 461-472.
| Crossref | Google Scholar |
Gungor H, Cakir MF, Dumlupinar Z (2022) Evaluation of wheat genotypes: genotype × environment interaction and GGE biplot analysis. Turkish Journal of Field Crops 27, 149-157.
| Crossref | Google Scholar |
Hailemariam Habtegebriel M (2022) Adaptability and stability for soybean yield by AMMI and GGE models in Ethiopia. Frontiers in Plant Science 13, 950992.
| Crossref | Google Scholar |
Han LP, Wang X, Gu X, Rao MS, Steinberger Y, Cheng X, Xie GH (2011) Effects of plant growth regulators on growth, yield and lodging of sweet sorghum. Research on Crops 12, 372-382.
| Google Scholar |
Hashim N, Rafii MY, Oladosu Y, Ismail MR, Ramli A, Arolu F, Chukwu S (2021) Integrating multivariate and univariate statistical models to investigate genotype-environment interaction of advanced fragrant rice genotypes under rainfed condition. Sustainability 13, 4555.
| Crossref | Google Scholar |
Htet MNS, Feng B, Wang H, Tian L, Yadav V (2022) Comparative assessment of nutritional and functional properties of different sorghum genotypes for ensuring nutritional security in dryland agro-ecosystem. Frontiers in Nutrition 9, 1048789.
| Crossref | Google Scholar | PubMed |
Iancu P, Soare M, Panita O (2021) Contributions regarding the study of genotype-environment relationship to some cyclic wheat combinations. AgroLife Scientific Journal 10, 77-82.
| Crossref | Google Scholar |
Iwata H, Nesumi H, Ninomiya S, Takano Y, Ukai Y (2002) The evaluation of genotype × environment interactions of citrus leaf morphology using image analysis and elliptic Fourier descriptors. Breeding Science 52, 243-251.
| Crossref | Google Scholar |
Kang MS (1988) A rank-sum method for selecting high-yielding, stable corn genotypes. Cereal Research Communication 16, 113-115.
| Google Scholar |
Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M (2021) AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranea L. Verdc.) genotypes under the multi-environmental trails (METs). Scientific Reports 11, 22791.
| Crossref | Google Scholar |
Kokten K, Kaplan M, Akcura M (2017) Green herbage yield assessments of maize cultivars through GGE biplot analysis method. Turkish Journal of Field Crops 22, 235-242.
| Google Scholar |
Kumar P, Singh J, Kaur G, Adunola PM, Biswas A, Bazzer S, Kaur H, Kaur I, Kaur H, Sandhu KS, Vemula S, Kaur B, Singh V, Tseng TM (2022) OMICS in fodder crops: applications, challenges, and prospects. Current Issues in Molecular Biology 44, 5440-5473.
| Crossref | Google Scholar | PubMed |
Li A, Hao C, Wang Z, Geng S, Jia M, Wang F, Han X, Kong X, Yin L, Tao S, Deng Z, Liao R, Sun G, Wang K, Ye X, Jiao C, Lu H, Zhou Y, Liu D, Fu X, Zhang X, Mao L (2022) Wheat breeding history reveals synergistic selection of pleiotropic genomic sites for plant architecture and grain yield. Molecular Plant 15, 504-519.
| Crossref | Google Scholar | PubMed |
Liu S, Martre P, Buis S, Abichou M, Andrieu B, Baret F (2019) Estimation of plant and canopy architectural traits using the digital plant phenotyping platform. Plant Physiology 181, 881-890.
| Crossref | Google Scholar | PubMed |
Liu C, Ma C, Lu J, Ye Z (2022) Yield stability analysis in maize hybrids of southwest China under genotype by environment interaction using GGE biplot. Agronomy 12, 1189.
| Crossref | Google Scholar |
Lu Y-L, Li S-K, Bai Y-L, Jones CL, Wang J-H (2009) Canopy spatial distribution and identification using hyperspectal data in winter wheat. Communications in Soil Science and Plant Analysis 40, 1240-1253.
| Crossref | Google Scholar |
Lu S, Zhang M, Zhang Z, Wang Z, Wu N, Song Y, Wang P (2018) Screening and verification of genes associated with leaf angle and leaf orientation value in inbred maize lines. PLoS ONE 13, e0208386.
| Crossref | Google Scholar |
Meng Y, Li J, Liu J, Hu H, Li W, Liu W, Chen S (2016) Ploidy effect and genetic architecture exploration of stalk traits using DH and its corresponding haploid populations in maize. BMC Plant Biology 16, 50.
| Crossref | Google Scholar |
Mulugeta G, Dessalegn Y (2014) Genotype by environment interaction analysis for tuber yield of potato (Solanum tuberosum L.) using a GGE biplot method in Amhara Region, Ethiopia. Agricultural Sciences 5, 239-249.
| Crossref | Google Scholar |
Oladosu Y, Rafii MY, Abdullah N, Magaji U, Miah G, Hussin G, Ramli A (2017) Genotype × Environment interaction and stability analyses of yield and yield components of established and mutant rice genotypes tested in multiple locations in Malaysia. Acta Agriculturae Scandinavica, Section B – Soil & Plant Science 67, 590-606.
| Crossref | Google Scholar |
Olivoto T, Lucio ADC (2020) metan: an R package for multi-environment trial analysis. Methods in Ecology and Evolution 11, 783-789.
| Crossref | Google Scholar |
Pepper GE, Pearce RB, Mock JJ (1977) Leaf orientation and yield of maize. Crop Science 17, 883-886.
| Crossref | Google Scholar |
Pour-Aboughadareh A, Yousefian M, Moradkhani H, Poczai P, Siddique KHM (2019) STABILITYSOFT: a new online program to calculate parametric and non-parametric stability statistics for crop traits. Applications in Plant Sciences 7, e01211.
| Crossref | Google Scholar | PubMed |
Rakshit S, Ganapathy KN, Gomashe SS, Swapna M, More A, Gadakh SR, Ghorade RB, Kajjidoni ST, Solanki BG, Biradar BD, Prabhakar R (2014) GGE biplot analysis of genotype × environment interaction in rabi grain sorghum [Sorghum bicolor (L.) Moench]. Indian Journal of Genetics and Plant Breeding 74, 558-563.
| Crossref | Google Scholar |
Sayar MS, Hang Y, Basbag M (2022) Forage yield and forage quality traits of sainfoin (Onobrychis viciifolia Scop.) genotypes and evaluations with biplot analysis. Fresenius Environmental Bulletin 31, 4009-4017.
| Google Scholar |
Shibayama M, Sakamoto T, Kimura A (2011) A Multiband polarimetric imager for field crop survey: instrumentation and preliminary observations of heading-stage wheat canopies. Plant Production Science 14, 64-74.
| Crossref | Google Scholar |
Shukla GK (1972) Some statistical aspects of partitioning genotype-environmental components of variability. Heredity 29, 237-245.
| Crossref | Google Scholar | PubMed |
Solonechnyi P, Vasko N, Naumov A, Solonechnaya O, Vazhenina O, Bondareva O, Logvinenko Y (2015) GGE biplot analysis of genotype by environment interaction of spring barley varieties. Zemdirbyste-Agriculture 102, 431-436.
| Crossref | Google Scholar |
Tas I, Akcura M, Coskun Y, Tutenocakli T (2023) Fast selection opportunity of salt tolerant guar bean genotypes with GGE biplot method. Archives of Agronomy and Soil Science 69, 1933-1945.
| Crossref | Google Scholar |
Tesso T, Tirfessa A, Mohammed H (2011) Association between morphological traits and yield components in the durra sorghums of Ethiopia. Hereditas 148, 98-109.
| Crossref | Google Scholar | PubMed |
Truong SK, McCormick RF, Rooney WL, Mullet JE (2015) Harnessing genetic variation in leaf angle to increase productivity of Sorghum bicolor. Genetics 201, 1229-1238.
| Crossref | Google Scholar | PubMed |
Wang R, Gangola MP, Irvine C, Gaur PM, Baga M, Chibbar RN (2019a) Co-localization of genomic regions associated with seed morphology and composition in a desi chickpea (Cicer arietinum L.) population varying in seed protein concentration. Theoretical and Applied Genetics 132, 1263-1281.
| Crossref | Google Scholar | PubMed |
Wang D, Fahad S, Saud S, Kamran M, Khan A, Khan MN, Hammad HM, Nasim W (2019b) Morphological acclimation to agronomic manipulation in leaf dispersion and orientation to promote “Ideotype” breeding: evidence from 3D visual modeling of “super” rice (Oryza sativa L.). Plant Physiology and Biochemistry 135, 499-510.
| Crossref | Google Scholar | PubMed |
Wricke G (1962) Übereine Methode zur Erfassung der ökologischen Streubreite in Feldversuchen. Zeitschrift für Pflanzenzüchtung 47, 92-96.
| Google Scholar |
Xiao J, Liu Z, Kong F, Xin Z, Wu H (2018) Effects of planting pattern and density on population structure and yield of sorghum. Scientia Agricultura Sinica 51, 4264-4276.
| Crossref | Google Scholar |
Xiao-ping L, Jin-feng Y, Cui-ping G, Acharya S (2011) Quantitative trait loci analysis of economically important traits in Sorghum bicolor × S. sudanense hybrid. Canadian Journal of Plant Science 91, 81-90.
| Crossref | Google Scholar |
Yan W, Tinker NA (2006) Biplot analysis of multi-environment trial data: principles and applications. Canadian Journal of Plant Science 86, 623-645.
| Crossref | Google Scholar |
Yan W, Hunt LA, Sheng Q, Szlavnics Z (2000) Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science 40, 597-605.
| Crossref | Google Scholar |
Yan W, Kang MS, Ma B, Woods S, Cornelius PL (2007) GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Science 47, 643-653.
| Crossref | Google Scholar |
Yanli L, Shaokun L, Jihua W, Carol LJ, Ruizhi X, Zhijie W (2007) Differentiating wheat varieties with different leaf angle distributions using NDVI and canopy cover. New Zealand Journal of Agricultural Research 50, 1149-1156.
| Crossref | Google Scholar |
Zhang H, Wang R, Liu B, Chen E, Yang Y, Qin L, Li F, Gao F, Cao P, Wang H, Guan Y (2019) Inclusive composite-interval mapping reveals quantitative trait loci for plant architectural traits in sorghum (Sorghum bicolor). Crop & Pasture Science 70, 659-668.
| Crossref | Google Scholar |
Zhao J, Mantilla Perez MB, Hu J, Salas Fernandez MG (2016) Genome-wide association study for nine plant architecture traits in sorghum. The Plant Genome 9(2), plantgenome2015.06.0044.
| Crossref | Google Scholar |
Zhi X, Tao Y, Jordan D, Borrell A, Hunt C, Cruickshank A, Potgieter A, Wu A, Hammer G, George-Jaeggli B, Mace E (2022) Genetic control of leaf angle in sorghum and its effect on light interception. Journal of Experimental Botany 73, 801-816.
| Crossref | Google Scholar | PubMed |