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Journal of Integrative Agriculture  2024, Vol. 23 Issue (7): 2242-2254    DOI: 10.1016/j.jia.2023.07.013
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Increasing root-lower characteristics improves drought tolerance in cotton cultivars at the seedling stage

Congcong Guo*, Hongchun Sun*, Xiaoyuan Bao, Lingxiao Zhu, Yongjiang Zhang, Ke Zhang,  Anchang Li, Zhiying Bai, Liantao Liu#, Cundong Li#

State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province/College of Agronomy, Hebei Agricultural University, Baoding 071001, China

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摘要  
干旱是棉花生产中一个重要的非生物胁迫因素。在干旱胁迫(DS)下,棉花的根系结构(RSA)在缓解干旱相关胁迫方面表现出高度的可塑性;然而,这种缓解取决于栽培品种。 因此,本研究旨在估计棉花在DS下的RSA的遗传变异性。基于纸基培生长系统,我们评估了80个棉花栽培品种在苗期的RSA变异性,以0和10%的聚乙二醇6000(PEG6000)分别作为对照和DS处理。 对80个棉花栽培品种的23个地上部性状和根系性状的分析表明,不同品种对DS的响应有所不同。DS处理后的第10天,DS下RSA性状的变异程度(5-55%)大于对照(5-49%)。 根据抗旱性的综合评价值,将80个栽培品种分为耐旱型品种(第1组)、中度耐旱型品种(第2组)和干旱敏感型品种(第3组)。在DS条件下,与对照组相比,干旱敏感型品种的总根长-下部、总根表面积-下部、根体积-下部和根长密度-下部分别显著降低63、71、76和4%。值得注意的是,耐旱型品种保持了其总根长-下部、总根表面积-下部、根体积-下部和根长密度-下部。与对照组相比,DS条件下耐旱型品种的根系直径(0-2mm范围内)-下部增加了21%,但中度耐旱型品种和干旱敏感型品种分别降低3%和64%。 此外,耐旱型品种在DS下表现出较强的可塑性反应,其特征表现为根系-下部增加。抗旱性与总根表面积-下部和根长密度-下部呈正相关。总体而言,不同棉花栽培品种的RSA在DS下差异很大。因此,重要的根系性状,如根系-下部,为探索抗旱棉花栽培品种是否能有效地抵御恶劣环境提供了重要的见解。


Abstract  
Drought is an important abiotic stress factor in cotton production.  The root system architecture (RSA) of cotton shows high plasticity which can alleviate drought-related stress under drought stress (DS) conditions; however, this alleviation is cultivar dependent.  Therefore, this study estimated the genetic variability of RSA in cotton under DS.  Using the paper-based growth system, we assessed the RSA variability in 80 cotton cultivars at the seedling stage, with 0 and 10% polyethylene glycol 6000 (PEG6000) as the control (CK) and DS treatment, respectively.  An analysis of 23 above-ground and root traits in the 80 cotton cultivars revealed different responses to DS.  On the 10th day after DS treatment, the degree of variation in the RSA traits under DS (5–55%) was greater than that of CK (5–49%).  The 80 cultivars were divided into drought-tolerant cultivars (group 1), intermediate drought-tolerant cultivars (group 2), and drought-sensitive cultivars (group 3) based on their comprehensive evaluation values of drought resistance.  Under DS, the root length-lower, root area-lower, root volume-lower, and root length density-lower were significantly reduced by 63, 71, 76, and 4% in the drought-sensitive cultivars compared to CK.  Notably, the drought-tolerant cultivars maintained their root length-lower, root area-lower, root volume-lower, and root length density–lower attributes.  Compared to CK, the root diameter (0–2 mm)-lower increased by 21% in group 1 but decreased by 3 and 64% in groups 2 and 3, respectively, under DS.  Additionally, the drought-tolerant cultivars displayed a plastic response under DS that was characterized by an increase in the root-lower characteristics.  Drought resistance was positively correlated with the root area-lower and root length density-lower.  Overall, the RSA of the different cotton cultivars varied greatly under DS.  Therefore, important root traits, such as the root-lower traits, provide great insights for exploring whether drought-tolerant cotton cultivars can effectively withstand adverse environments.
Keywords:  cotton        root system architecture        drought stress        cultivars variability        root-lower  
Received: 17 April 2023   Accepted: 12 June 2023
Fund: 

We would like to thank the National Natural Science Foundation of China (31871569 and 32172120) and the Natural Science Foundation of Hebei Province, China (C2020204066).  

About author:  #Correspondence Cundong Li, E-mail: auhlcd@163.com; Liantao Liu, E-mail: liultday@126.com * These authors contributed equally to this study. * These authors contributed equally to this work.

Cite this article: 

Congcong Guo, Hongchun Sun, Xiaoyuan Bao, Lingxiao Zhu, Yongjiang Zhang, Ke Zhang, Anchang Li, Zhiying Bai, Liantao Liu, Cundong Li. 2024. Increasing root-lower characteristics improves drought tolerance in cotton cultivars at the seedling stage. Journal of Integrative Agriculture, 23(7): 2242-2254.

Ali M L, Luetchens J, Nascimento J, Shaver T M, Kruger G R, Lorenz A J. 2015. Genetic variation in seminal and nodal root angle and their association with grain yield of maize under water-stressed field conditions. Plant and Soil, 397, 213–225.

An D, Su J, Liu Q, Zhu Y, Tong Y, Li J, Jing R, Li B, Li Z. 2006. Mapping QTLs for nitrogen uptake in relation to the early growth of wheat (Triticum aestivum L.). Plant and Soil, 284, 73–84.

Atkinson J A, Wingen L U, Griffiths M, Pound M P, Gaju O, Foulkes M J, Le Gouis J, Griffiths S, Bennett M J, King J, Wells D M. 2015. Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat. Journal of Experimental Botany, 66, 2283–2292.

Avramova V, Nagel K A, AbdElgawad H, Bustos D, DuPlessis M, Fiorani F, Beemster G T S. 2016. Screening for drought tolerance of maize hybrids by multi-scale analysis of root and shoot traits at the seedling stage. Journal of Experimental Botany, 67, 2453–2466.

Bonser A M, Lynch J, Snapp S. 1996. Effect of phosphorus deficiency on growth angle of basal roots in Phaseolus vulgaris. New Phytologist, 132, 281–288.

Burridge J, Jochua C N, Bucksch A, Lynch J P. 2016. Legume shovelomics: High-throughput phenotyping of common bean (Phaseolus vulgaris L.) and cowpea (Vigna unguiculata subsp, unguiculata) root architecture in the field. Field Crops Research, 192, 21–32.

Burridge J D, Schneider H M, Huynh B L, Roberts P A, Bucksch A, Lynch J P. 2017. Genome-wide association mapping and agronomic impact of cowpea root architecture. Theoretical and Applied Genetics, 130, 419–431.

Christopher J, Christopher M, Jennings R, Jones S, Fletcher S, Borrell A, Manschadi A M, Jordan D, Mace E, Hammer G. 2013. QTL for root angle and number in a population developed from bread wheats (Triticum aestivum) with contrasting adaptation to water-limited environments. Theoretical and Applied Genetics, 126, 1563–1574.

Colombi T, Walter A. 2017. Genetic diversity under soil compaction in wheat: root number as a promising trait for early plant vigor. Frontires in Plant Science, 8, 420.

de Dorlodot S, Forster B, Pagès L, Price A, Tuberosa R, Draye X. 2007. Root system architecture: Opportunities and constraints for genetic improvement of crops. Trends in Plant Science, 12, 474–481.

Dupuy L X, Wright G, Thompson J A, Taylor A, Dekeyser S, White C P, Thomas W T B, Nightingale M, Hammond J P, Graham N S, Thomas C L, Broadley M R, White P J. 2017. Accelerating root system phenotyping of seedlings through a computer-assisted processing pipeline. Plant Methods, 13, 57.

Falk K G, Jubery T Z, Mirnezami S V, Parmley K A, Sarkar S, Singh A, Ganapathysubramanian B, Singh A K. 2020. Computer vision and machine learning enabled soybean root phenotyping pipeline. Plant Methods, 16, 5.

Falkenberg N R, Piccinni G, Cothren J T, Leskovar D I, Rush C M. 2007. Remote sensing of biotic and abiotic stress for irrigation management of cotton. Agricultural Water Management, 87, 23–31.

Fitter A H. 1986. The topology and geometry of plant root systems: Influence of watering rate on root system topology in Trifolium pratense. Annals of Botany, 58, 91–101.

Freschet G T, Pagès L, Iversen C M, Comas L H, Rewald B, Roumet C, Klimešová J, Zadworny M, Poorter H, Postma J A, Adams T S, Bagniewska-Zadworna A, Bengough A G, Blancaflor E B, Brunner I, Cornelissen J H C, Garnier E, Gessler A, Hobbie S E, Meier I C, et al. 2021. A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements. New Phytologist, 232, 973–1122.

Gioia T, Galinski A, Lenz H, Müller C, Lentz J, Heinz K, Briese C, Putz A, Fiorani F, Watt M, Schurr U, Nagel K A. 2017. GrowScreen-PaGe, a non-invasive, high-throughput phenotyping system based on germination paper to quantify crop phenotypic diversity and plasticity of root traits under varying nutrient supply. Functional Plant Biology, 44, 76–93.

Hoogenboom G, Huck M G, Peterson C M. 1987. Root growth rate of soybean as affected by drought stress. Agronomy Journal, 79, 607–614.

Hund A, Trachsel S, Stamp P. 2009. Growth of axile and lateral roots of maize: I development of a phenotying platform. Plant and Soil, 325, 335–349.

Johnson M G, Tingey D T, Phillips D L, Storm M J. 2001. Advancing fine root research with minirhizotrons. Environmental and Experimental Botany, 45, 263–289.

Kaspar T C, Taylor H M, Shibles R M. 1984. Taproot-elongation rates of soybean cultivars in the glasshouse and their relation to field rooting depth. Crop Science, 24, 916–920.

Kuijken R C P, van Eeuwijk Fred A, Marcelis L F M, Bouwmeester H J. 2015. Root phenotyping: From component trait in the lab to breeding. Journal of Experimental Botany, 66, 5389–5401.

Li C, Li L, Reynolds M P, Wang J, Chang X, Mao X, Jing R. 2021. Recognizing the hidden half in wheat: root system attributes associated with drought tolerance. Journal of Experimental Botany, 72, 5117–5133.

Liao H, Rubio G, Yan X, Cao A, Brown K M, Lynch J P. 2001. Effect of phosphorus availability on basal root shallowness in common bean. Plant and Soil, 232, 69–79.

Lynch J P. 2007. Roots of the second green revolution. Australian Journal of Botany, 55, 493–512.

Lynch J P. 2013. Steep, cheap and deep: An ideotype to optimize water and N acquisition by maize root systems. Annals of Botany, 112, 347–357.

Lynch J P, Wojciechowski T. 2015. Opportunities and challenges in the subsoil: Pathways to deeper rooted crops. Journal of Experimental Botany, 66, 2199–2210.

Mao L, Zhang L, Zhao X, Liu S, van der Werf W, Zhang S, Spiertz H, Li Z. 2014. Crop growth, light utilization and yield of relay intercropped cotton as affected by plant density and a plant growth regulator. Field Crops Research, 155, 67–76.

Maurel C, Nacry P. 2020. Root architecture and hydraulics converge for acclimation to changing water availability. Nature Plants, 6, 744–749.

Morris E C, Griffiths M, Golebiowska A, Mairhofer S, Burr-Hersey J, Goh T, von Wangenheim D, Atkinson B, Sturrock C J, Lynch J P, Vissenberg K, Ritz K, Wells D M, Mooney S J, Bennett M J. 2017. Shaping 3D root system architecture. Current Biology, 27, R919–R930.

Oikeh S O, Kling J G, Horst W J, Chude V O, Carsky R J. 1999. Growth and distribution of maize roots under nitrogen fertilization in plinthite soil. Field Crops Research, 62, 1–13.

Qiao S, Fang Y, Wu A, Xu B, Zhang S, Deng X, Djalovic I, Siddique K H M, Chen Y. 2019. Dissecting root trait variability in maize cultivarss using the semi-hydroponic phenotyping platform. Plant and Soil, 439, 75–90.

Ranjan A, Sinha R, Singla-Pareek S L, Pareek A, Singh A K. 2022. Shaping the root system architecture in plants for adaptation to drought stress. Physiologia Plantarum, 174, 1–16.

Silva B, Ana M, Torzillo G, Kopecký J, Masojídek J. 2013. Productivity and biochemical composition of Phaeodactylum tricornutum (Bacillariophyceae) cultures grown outdoors in tubular photobioreactors and open ponds. Biomass and Bioenergy, 54, 115–122.

de Sousa S M, Clark R T, Mendes F F, de Oliveira A C, de Vasconcelos M J V, Parentoni S N, Kochian L V, Guimarães C T, Magalhães J V. 2012. A role for root morphology and related candidate genes in P acquisition efficiency in maize. Functional Plant Biology, 39, 925–935.

Svačina P, Středa T, Chloupek O. 2014. Uncommon selection by root system size increases barley yield. Agronomy for Sustainable Development, 34, 545–551.

Tian X, Doerner P. 2013. Root resource foraging: Does it matter? Frontires in Plant Science, 4, 303.

Uzilday B, Turkan I, Sekmen A H, Ozgur R, Karakaya H C. 2012. Comparison of ROS formation and antioxidant enzymes in Cleome gynandra (C4) and Cleome spinosa (C3) under drought stress. Plant Science, 182, 59–70.

Wang X, Wang H, Liu S, Ferjani A, Li J, Yan J, Yang X, Qin F. 2016. Genetic variation in ZmVPP1 contributes to drought tolerance in maize seedlings. Nature Genetics, 48, 1233–1241.

Wang Z, Fan B, Guo L. 2019. Soil salinization after long-term mulched drip irrigation poses a potential risk to agricultural sustainability: Soil salinization under mulched drip irrigation. European Journal of Soil Science, 70, 20–24.

Wang Z, Ma B L, Gao J, Sun J. 2015. Effects of different management systems on root distribution of maize. Canadian Journal of Plant Science, 95, 21–28.

Wijesinghe D K, John E A, Beurskens S, Hutchings M J. 2001. Root system size and precision in nutrient foraging: responses to spatial pattern of nutrient supply in six herbaceous species: Root system size and precision in nutrient foraging. Journal of Ecology, 89, 972–983.

Wu X, Bao W. 2012. Statistical analysis of leaf water use efficiency and physiology traits of winter wheat under drought condition. Journal of Integrative Agriculture, 11, 82–89.

Xiao S, Liu L, Zhang Y, Sun H, Zhang K, Bai Z, Dong H, Li C. 2020. Fine root and root hair morphology of cotton under drought stress revealed with RhizoPot. Journal of Agronomy and Crop Science, 206, 679–693.

Ytting N K, Andersen S B, Thorup-Kristensen K. 2014. Using tube rhizotrons to measure variation in depth penetration rate among modern North-European winter wheat (Triticum aestivum L.) cultivars. Euphytica, 199, 233–245.

Zou J, Hu W, Li Y, He J, Zhu H, Zhou Z. 2020. Screening of drought resistance indices and evaluation of drought resistance in cotton (Gossypium hirsutum L.). Journal of Integrative Agriculture, 19, 495–508.

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