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20 April 2019 Genotypic differences in phosphorus acquisition efficiency and root performance of cotton (Gossypium hirsutum) under low-phosphorus stress
Bolang Chen, Qinghui Wang, Heike Bücking, Jiandong Sheng, Jia Luo, Zhongping Chai, Arjun Kafle, Yinying Hou, Gu Feng
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Abstract

Low availability of phosphorus (P) is a major constraint to production of cotton (Gossypium hirsutum L.). The extent to which genotypic variation in root traits exists or contributes to P-acquisition efficiency (PAE) in cotton is unknown. To assess genetic variation in PAE, the biomass and P-acquisition characteristics of 32 cotton genotypes were evaluated in a hydroponic experiment. Significant genotypic variation in biomass and P content was detected among the cotton genotypes in two seasons. We then conducted a 2-year pot experiment to compare P-efficiency traits between three P-efficient and two P-inefficient genotypes under P-deficient and P-sufficient conditions (0 and 75 mg P2O5 kg–1 soil, respectively). We detected significant differences in biomass accumulation and allocation, P accumulation and allocation, root traits and PAE among the five cotton genotypes under P-sufficient and P-deficient conditions. Compared with P-inefficient genotypes, P-efficient genotypes had longer surface fine roots, and greater total root surface area, total root length, surface root length, and P concentration (partitioning index) in bolls. Root morphology, especially surface fine root length and middle root length, played an important role in P uptake under P-deficient conditions.

© CSIRO 2019
Bolang Chen, Qinghui Wang, Heike Bücking, Jiandong Sheng, Jia Luo, Zhongping Chai, Arjun Kafle, Yinying Hou, and Gu Feng "Genotypic differences in phosphorus acquisition efficiency and root performance of cotton (Gossypium hirsutum) under low-phosphorus stress," Crop and Pasture Science 70(4), 344-358, (20 April 2019). https://doi.org/10.1071/CP18324
Received: 3 July 2018; Accepted: 10 March 2019; Published: 20 April 2019
KEYWORDS
acid phosphatase
biomass partitioning
harvest index
principle component analysis
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