Rice Science
  • 首页
  • 期刊介绍
  • 编委会
  • 学术伦理
  • 投稿指南
  • 期刊订阅
  • 联系我们
  • English

Rice Science ›› 2023, Vol. 30 ›› Issue (4): 321-334.DOI: 10.1016/j.rsci.2023.02.002

• • 上一篇    下一篇

  • 收稿日期:2022-10-13 接受日期:2023-02-24 出版日期:2023-07-28 发布日期:2023-05-26

RichHTML

PDF

补充材料

1

可视化

0
  • 1. supplemental data.pdf(701KB)

摘要/Abstract

引用本文

. [J]. Rice Science, 2023, 30(4): 321-334.

使用本文

0
    /   推荐

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.ricesci.org/CN/10.1016/j.rsci.2023.02.002

               http://www.ricesci.org/CN/Y2023/V30/I4/321

图/表 6

Table 1. Individual effect of genotype and iron (Fe) level on germination parameters of tested rice genotypes.
Factor Final germination (%) Germination energy (%) Mean germination time (d) Germination rate index (seed/d) Root length
(cm)
Shoot length (cm) Seedling vigor index
Genotype (G)
RD31 82.1 ± 1.4 f 64.8 ± 1.4 f 4.8 ± 0.03 a 55.0 ± 1.0 g 2.5 ± 0.1 b 5.3 ± 0.2 d 679.1 ± 23.9 ef
RD41 83.9 ± 1.4 ef 72.2 ± 1.7 de 4.8 ± 0.02 b 58.4 ± 1.0 ef 1.9 ± 0.1 de 5.5 ± 0.1 cd 644.8 ± 20.7 f
RD57 85.4 ± 1.4 de 71.7 ± 1.4 de 4.6 ± 0.03 ef 61.7 ± 1.1 d 2.7 ± 0.2 ab 5.6 ± 0.2 bc 733.0 ± 17.1 cd
RD71 85.4 ± 1.5 de 67.4 ± 1.2 f 4.8 ± 0.03 bc 57.5 ± 1.1 f 2.0 ± 0.1 cd 4.9 ± 0.1 e 603.3 ± 18.1 g
RD77 86.9 ± 1.3 cd 74.1 ± 1.3 cd 4.7 ± 0.01 de 61.3 ± 0.8 d 2.1 ± 0.1 cd 5.8 ± 0.1 b 702.3 ± 17.5 de
RD79 83.6 ± 1.1 ef 70.7 ± 1.3 e 4.7 ± 0.03 cd 58.7 ± 1.0 ef 2.2 ± 0.1 c 5.3 ± 0.1 d 651.2 ± 14.0 f
RD85 91.9 ± 0.9 a 88.0 ± 0.9 a 4.5 ± 0.01 h 73.6 ± 0.6 a 2.7 ± 0.1 ab 6.5 ± 0.1 a 851.0 ± 11.4 a
RD87 88.5 ± 1.1 bc 81.0 ± 1.0 b 4.5 ± 0.02 h 69.4 ± 0.6 b 2.8 ± 0.1 a 5.9 ± 0.1 b 771.6 ± 17.7 b
RD35 89.7 ± 1.0 ab 83.6 ± 1.3 b 4.6 ± 0.03 fg 66.8 ± 0.9 c 1.9 ± 0.1 de 6.3 ± 0.1 a 750.7 ± 12.4 bc
Azucena 85.9 ± 1.4 cde 75.0 ± 1.5 c 4.7 ± 0.02 cd 59.1 ± 0.9 ef 2.8 ± 0.1 ab 5.5 ± 0.1 cd 728.7 ± 15.1 cd
IR64 78.3 ± 1.3 g 73.2 ± 1.3 cde 4.6 ± 0.02 g 60.4 ± 1.0 de 1.8 ± 0.1 e 4.8 ± 0.1 e 554.7 ± 13.2 h
Fe level (Fe, mg/L)
0 (control) 92.9 ± 1.2 a 92.9 ± 1.3 a 4.4 ± 0.01 d 78.8 ± 0.9 a 3.2 ± 0.1 b 7.0 ± 0.1 b 950.5 ± 21.9 b
150 90.6 ± 1.4 b 90.6 ± 1.4 b 4.4 ± 0.01 d 76.5 ± 1.1 b 3.7 ± 0.1 a 7.5 ± 0.1 a 1 014.0 ± 24.2 a
300 88.4 ± 1.1 c 75.9 ± 1.2 c 4.6 ± 0.02 c 62.9 ± 0.8 c 2.2 ± 0.1 c 5.5 ± 0.1 c 684.9 ± 14.1 c
600 84.0 ± 1.1 d 65.5 ± 1.2 d 4.8 ± 0.03 b 53.4 ± 0.8 d 1.4 ± 0.1 d 4.6 ± 0.1 d 516.1 ± 11.6 d
900 72.1 ± 1.4 e 48.6 ± 1.4 e 5.1 ± 0.04 a 38.3 ± 0.9 e 1.1 ± 0.1 e 3.3 ± 0.1 e 321.0 ± 10.6 e
G ** ** ** ** ** ** **
Fe ** ** ** ** ** ** **
G × Fe ** ** ** ** ** ** **

Table 1. Individual effect of genotype and iron (Fe) level on germination parameters of tested rice genotypes.

Factor Final germination (%) Germination energy (%) Mean germination time (d) Germination rate index (seed/d) Root length
(cm)
Shoot length (cm) Seedling vigor index
Genotype (G)
RD31 82.1 ± 1.4 f 64.8 ± 1.4 f 4.8 ± 0.03 a 55.0 ± 1.0 g 2.5 ± 0.1 b 5.3 ± 0.2 d 679.1 ± 23.9 ef
RD41 83.9 ± 1.4 ef 72.2 ± 1.7 de 4.8 ± 0.02 b 58.4 ± 1.0 ef 1.9 ± 0.1 de 5.5 ± 0.1 cd 644.8 ± 20.7 f
RD57 85.4 ± 1.4 de 71.7 ± 1.4 de 4.6 ± 0.03 ef 61.7 ± 1.1 d 2.7 ± 0.2 ab 5.6 ± 0.2 bc 733.0 ± 17.1 cd
RD71 85.4 ± 1.5 de 67.4 ± 1.2 f 4.8 ± 0.03 bc 57.5 ± 1.1 f 2.0 ± 0.1 cd 4.9 ± 0.1 e 603.3 ± 18.1 g
RD77 86.9 ± 1.3 cd 74.1 ± 1.3 cd 4.7 ± 0.01 de 61.3 ± 0.8 d 2.1 ± 0.1 cd 5.8 ± 0.1 b 702.3 ± 17.5 de
RD79 83.6 ± 1.1 ef 70.7 ± 1.3 e 4.7 ± 0.03 cd 58.7 ± 1.0 ef 2.2 ± 0.1 c 5.3 ± 0.1 d 651.2 ± 14.0 f
RD85 91.9 ± 0.9 a 88.0 ± 0.9 a 4.5 ± 0.01 h 73.6 ± 0.6 a 2.7 ± 0.1 ab 6.5 ± 0.1 a 851.0 ± 11.4 a
RD87 88.5 ± 1.1 bc 81.0 ± 1.0 b 4.5 ± 0.02 h 69.4 ± 0.6 b 2.8 ± 0.1 a 5.9 ± 0.1 b 771.6 ± 17.7 b
RD35 89.7 ± 1.0 ab 83.6 ± 1.3 b 4.6 ± 0.03 fg 66.8 ± 0.9 c 1.9 ± 0.1 de 6.3 ± 0.1 a 750.7 ± 12.4 bc
Azucena 85.9 ± 1.4 cde 75.0 ± 1.5 c 4.7 ± 0.02 cd 59.1 ± 0.9 ef 2.8 ± 0.1 ab 5.5 ± 0.1 cd 728.7 ± 15.1 cd
IR64 78.3 ± 1.3 g 73.2 ± 1.3 cde 4.6 ± 0.02 g 60.4 ± 1.0 de 1.8 ± 0.1 e 4.8 ± 0.1 e 554.7 ± 13.2 h
Fe level (Fe, mg/L)
0 (control) 92.9 ± 1.2 a 92.9 ± 1.3 a 4.4 ± 0.01 d 78.8 ± 0.9 a 3.2 ± 0.1 b 7.0 ± 0.1 b 950.5 ± 21.9 b
150 90.6 ± 1.4 b 90.6 ± 1.4 b 4.4 ± 0.01 d 76.5 ± 1.1 b 3.7 ± 0.1 a 7.5 ± 0.1 a 1 014.0 ± 24.2 a
300 88.4 ± 1.1 c 75.9 ± 1.2 c 4.6 ± 0.02 c 62.9 ± 0.8 c 2.2 ± 0.1 c 5.5 ± 0.1 c 684.9 ± 14.1 c
600 84.0 ± 1.1 d 65.5 ± 1.2 d 4.8 ± 0.03 b 53.4 ± 0.8 d 1.4 ± 0.1 d 4.6 ± 0.1 d 516.1 ± 11.6 d
900 72.1 ± 1.4 e 48.6 ± 1.4 e 5.1 ± 0.04 a 38.3 ± 0.9 e 1.1 ± 0.1 e 3.3 ± 0.1 e 321.0 ± 10.6 e
G ** ** ** ** ** ** **
Fe ** ** ** ** ** ** **
G × Fe ** ** ** ** ** ** **
Fig. 1. Leaf-bronzing score (LBS) of 11 rice genotypes exposed to five iron (Fe) levels at 55 d after transplanting. Data are Mean ± SE (n = 3). Different lowercase letters on bars for mean LBS are significantly different based on the Tukey’s honest significant difference test at P ≤ 0.05.

Fig. 1. Leaf-bronzing score (LBS) of 11 rice genotypes exposed to five iron (Fe) levels at 55 d after transplanting. Data are Mean ± SE (n = 3). Different lowercase letters on bars for mean LBS are significantly different based on the Tukey’s honest significant difference test at P ≤ 0.05.

Table 2. Individual effect of genotype and iron (Fe) level on growth characteristics and physiochemical parameters of tested rice genotypes.
Factor Plant height (cm) Root length
(m)
Shoot dry matter (g/plant) Root dry matter (g/plant) Tiller number per plant Panicle number per plant Filled grain ratio (%) 1000-grain weight (g) Grain yield
(g/plant)
Genotype (G)
RD31 92.1 ± 1.9 bc 128.9 ± 6.4 a 86.5 ± 3.0 bc 13.3 ± 0.5 cd 23.6 ± 0.6 ab 16.6 ± 0.7 ab 78.6 ± 0.2 gh 16.8 ± 0.7 cd 19.1 ± 1.1 c
RD41 90.6 ± 3.6 bc 129.1 ± 6.2 a 71.9 ± 1.8 d 13.4 ± 0.7 cd 19.7 ± 0.5 d 14.1 ± 0.8 cd 81.6 ± 0.1 cde 19.0 ± 0.8 ab 19.4 ± 1.2 c
RD57 93.5 ± 2.0 b 127.2 ± 7.7 a 84.3 ± 1.4 c 12.0 ± 1.2 d 22.4 ± 0.5 bc 16.5 ± 0.8 ab 79.2 ± 0.1 fgh 18.3 ± 0.3 b 18.8 ± 1.0 c
RD71 91.7 ± 1.7 bc 125.4 ± 7.7 a 73.3 ± 1.3 d 13.0 ± 0.5 cd 21.4 ± 0.5 bcd 14.8 ± 0.9 bcd 81.2 ± 0.1 def 19.2 ± 0.7 ab 20.5 ± 0.8 bc
RD77 90.1 ± 2.7 bcd 121.4 ± 6.7 a 69.1 ± 2.3 de 11.6 ± 0.7 d 22.1 ± 0.8 bc 16.4 ± 0.8 ab 78.9 ± 0.2 gh 18.8 ± 0.4 ab 20.6 ± 0.8 bc
RD79 90.9 ± 2.4 bc 121.4 ± 6.8 a 90.1 ± 2.0 b 13.8 ± 0.6 bcd 21.7 ± 0.8 bcd 16.1 ± 1.2 abc 80.3 ± 0.4 efg 18.8 ± 0.4 b 20.9 ± 0.8 bc
RD85 84.8 ± 1.0 d 125.9 ± 4.4 a 68.5 ± 2.1 de 17.2 ± 1.1 a 22.2 ± 0.7 bc 17.1 ± 0.7 a 84.9 ± 0.3 b 20.3 ± 0.5 a 23.5 ± 0.8 a
RD87 87.9 ± 2.8 cd 120.1 ± 6.9 a 73.5 ± 1.8 d 15.9 ± 1.4 ab 21.0 ± 0.7 cd 15.0 ± 1.1 bc 82.9 ± 0.1 bcd 19.5 ± 0.8 ab 21.8 ± 0.5 ab
RD35 88.4 ± 3.4 bcd 128.9 ± 8.0 a 69.9 ± 1.0 de 16.2 ± 0.5 a 23.3 ± 0.8 zb 15.2 ± 0.9 abc 83.6 ± 0.3 bc 18.2 ± 0.5 bc 22.4 ± 0.8 ab
Azucena 129.3 ± 2.7 a 120.3 ± 10.2 a 106.3 ± 1.8 a 15.0 ± 0.6 abc 11.3 ± 0.5 e 7.0 ± 0.3 e 93.7 ± 0.1 a 18.8 ± 0.6 ab 16.4 ± 0.6 d
IR64 76.0 ± 1.6 e 126.7 ± 7.0 a 64.6 ± 4.0 e 16.5 ± 0.9 a 24.7 ± 1.0 a 13.0 ± 1.1 d 78.0 ± 0.2 h 16.5 ± 0.5 d 19.0 ± 1.0 c
Fe level (Fe, mg/L)
0 (control) 92.1 ± 2.2 ab 121.1 ± 8.8 c 80.9 ± 1.6 c 13.7 ± 0.8 c 21.5 ± 0.7 bc 15.5 ± 0.8 b 81.3 ± 0.8 bc 18.8 ± 0.4 c 21.0 ± 0.9 c
150 94.3 ± 2.8 a 134.6 ± 5.6 b 89.6 ± 1.5 b 17.5 ± 0.7 b 22.5 ± 0.7 ab 16.9 ± 0.9 a 83.0 ± 1.2 ab 19.9 ± 0.6 b 23.6 ± 1.2 b
300 94.9 ± 2.7 a 149.7 ± 7.1 a 97.7 ± 2.4 a 21.0 ± 1.0 a 23.3 ± 0.7 a 16.5 ± 1.0 ab 83.2 ± 0.8 a 20.8 ± 0.9 a 25.2 ± 1.3 a
600 91.1 ± 1.6 b 115.2 ± 7.5 c 69.5 ± 2.2 d 11.6 ± 0.9 d 20.6 ± 0.6 c 13.2 ± 0.8 c 81.9 ± 1.0 c 17.7 ± 0.4 d 18.8 ± 0.4 d
900 89.1 ± 2.3 b 104.6 ± 6.5 d 52.3 ± 2.5 e 7.9 ± 0.5 e 18.2 ± 0.6 d 11.3 ± 0.8 d 81.0 ± 0.9 c 15.6 ± 0.5 e 12.5 ± 0.5 e
G ** ns ** ** ** ** ** ** **
Fe ** ** ** ** ** ** ** ** **
G × Fe ns ns ** ** * * ** ** **
Factor SPAD value Net photosynthetic rate
[μmol/(m2∙s)]
Membrane stability index
(%)
Leaf Fe content
(mg/g)
Root Fe content
(mg/g)
Genotype (G)
RD31 36.9 ± 0.4 cd 18.6 ± 0.6 b 72.8 ± 0.5 cd 7.2 ± 0.2 b 11.8 ± 0.4 b
RD41 37.8 ± 0.5 abcd 18.2 ± 0.7 b 75.2 ± 0.5 abcd 3.7 ± 0.1 f 10.9 ± 0.4 f
RD57 38.3 ± 0.3 abc 18.8 ± 1.0 b 77.1 ± 0.5 abc 5.7 ± 0.1 e 11.0 ± 0.2 d
RD71 38.1 ± 0.4 abc 19.6 ± 0.8 b 75.3 ± 0.6 abcd 5.3 ± 0.1 d 11.4 ± 0.3 e
RD77 35.7 ± 0.4 d 19.3 ± 0.6 b 74.5 ± 0.5 bcd 6.2 ± 0.1 c 11.6 ± 0.5 c
RD79 39.1 ± 0.2 abc 19.4 ± 0.8 b 77.2 ± 0.5 abc 3.9 ± 0.1 f 11.0 ± 0.3 e
RD85 39.2 ± 0.5 abc 23.0 ± 0.9 a 80.4 ± 0.2 ab 2.3 ± 0.1 h 10.1 ± 0.3 i
RD87 40.1 ± 0.3 a 22.4 ± 1.2 a 78.5 ± 0.4 abc 3.1 ± 0.1 g 10.6 ± 0.4 g
RD35 39.3 ± 0.5 ab 21.8 ± 0.8 a 78.4 ± 0.4 abc 2.6 ± 0.1 h 10.4 ± 0.2 h
Azucena 39.2 ± 0.6 ab 19.8 ± 0.7 b 81.3 ± 0.6 a 2.5 ± 0.1 h 9.9 ± 0.5 j
IR64 37.6 ± 0.5 bcd 19.2 ± 0.8 b 70.0 ± 0.4 d 8.7 ± 0.3 a 12.3 ± 0.5 a
Fe level (Fe, mg/L)
0 (control) 38.4 ± 0.4 bc 20.5 ± 0.7 c 84.1 ± 0.4 a 0.7 ± 0.0 e 4.1 ± 0.5 e
150 39.3 ± 0.4 ab 22.4 ± 0.5 b 83.9 ± 0.5 a 1.2 ± 0.0 d 8.0 ± 0.2 d
300 40.1 ± 0.4 a 25.0 ± 1.2 a 77.9 ± 0.4 b 2.0 ± 0.1 c 10.8 ± 0.2 c
600 37.5 ± 0.4 c 18.4 ± 0.5 d 71.4 ± 0.5 c 6.5 ± 0.1 b 13.3 ± 0.2 b
900 36.1 ± 0.4 d 13.7 ± 1.1 e 64.7 ± 0.6 d 12.8 ± 0.4 a 18.7 ± 0.5 a
G ** ** ** ** **
Fe ** ** ** ** **
G × Fe ** ** ** ** **

Table 2. Individual effect of genotype and iron (Fe) level on growth characteristics and physiochemical parameters of tested rice genotypes.

Factor Plant height (cm) Root length
(m)
Shoot dry matter (g/plant) Root dry matter (g/plant) Tiller number per plant Panicle number per plant Filled grain ratio (%) 1000-grain weight (g) Grain yield
(g/plant)
Genotype (G)
RD31 92.1 ± 1.9 bc 128.9 ± 6.4 a 86.5 ± 3.0 bc 13.3 ± 0.5 cd 23.6 ± 0.6 ab 16.6 ± 0.7 ab 78.6 ± 0.2 gh 16.8 ± 0.7 cd 19.1 ± 1.1 c
RD41 90.6 ± 3.6 bc 129.1 ± 6.2 a 71.9 ± 1.8 d 13.4 ± 0.7 cd 19.7 ± 0.5 d 14.1 ± 0.8 cd 81.6 ± 0.1 cde 19.0 ± 0.8 ab 19.4 ± 1.2 c
RD57 93.5 ± 2.0 b 127.2 ± 7.7 a 84.3 ± 1.4 c 12.0 ± 1.2 d 22.4 ± 0.5 bc 16.5 ± 0.8 ab 79.2 ± 0.1 fgh 18.3 ± 0.3 b 18.8 ± 1.0 c
RD71 91.7 ± 1.7 bc 125.4 ± 7.7 a 73.3 ± 1.3 d 13.0 ± 0.5 cd 21.4 ± 0.5 bcd 14.8 ± 0.9 bcd 81.2 ± 0.1 def 19.2 ± 0.7 ab 20.5 ± 0.8 bc
RD77 90.1 ± 2.7 bcd 121.4 ± 6.7 a 69.1 ± 2.3 de 11.6 ± 0.7 d 22.1 ± 0.8 bc 16.4 ± 0.8 ab 78.9 ± 0.2 gh 18.8 ± 0.4 ab 20.6 ± 0.8 bc
RD79 90.9 ± 2.4 bc 121.4 ± 6.8 a 90.1 ± 2.0 b 13.8 ± 0.6 bcd 21.7 ± 0.8 bcd 16.1 ± 1.2 abc 80.3 ± 0.4 efg 18.8 ± 0.4 b 20.9 ± 0.8 bc
RD85 84.8 ± 1.0 d 125.9 ± 4.4 a 68.5 ± 2.1 de 17.2 ± 1.1 a 22.2 ± 0.7 bc 17.1 ± 0.7 a 84.9 ± 0.3 b 20.3 ± 0.5 a 23.5 ± 0.8 a
RD87 87.9 ± 2.8 cd 120.1 ± 6.9 a 73.5 ± 1.8 d 15.9 ± 1.4 ab 21.0 ± 0.7 cd 15.0 ± 1.1 bc 82.9 ± 0.1 bcd 19.5 ± 0.8 ab 21.8 ± 0.5 ab
RD35 88.4 ± 3.4 bcd 128.9 ± 8.0 a 69.9 ± 1.0 de 16.2 ± 0.5 a 23.3 ± 0.8 zb 15.2 ± 0.9 abc 83.6 ± 0.3 bc 18.2 ± 0.5 bc 22.4 ± 0.8 ab
Azucena 129.3 ± 2.7 a 120.3 ± 10.2 a 106.3 ± 1.8 a 15.0 ± 0.6 abc 11.3 ± 0.5 e 7.0 ± 0.3 e 93.7 ± 0.1 a 18.8 ± 0.6 ab 16.4 ± 0.6 d
IR64 76.0 ± 1.6 e 126.7 ± 7.0 a 64.6 ± 4.0 e 16.5 ± 0.9 a 24.7 ± 1.0 a 13.0 ± 1.1 d 78.0 ± 0.2 h 16.5 ± 0.5 d 19.0 ± 1.0 c
Fe level (Fe, mg/L)
0 (control) 92.1 ± 2.2 ab 121.1 ± 8.8 c 80.9 ± 1.6 c 13.7 ± 0.8 c 21.5 ± 0.7 bc 15.5 ± 0.8 b 81.3 ± 0.8 bc 18.8 ± 0.4 c 21.0 ± 0.9 c
150 94.3 ± 2.8 a 134.6 ± 5.6 b 89.6 ± 1.5 b 17.5 ± 0.7 b 22.5 ± 0.7 ab 16.9 ± 0.9 a 83.0 ± 1.2 ab 19.9 ± 0.6 b 23.6 ± 1.2 b
300 94.9 ± 2.7 a 149.7 ± 7.1 a 97.7 ± 2.4 a 21.0 ± 1.0 a 23.3 ± 0.7 a 16.5 ± 1.0 ab 83.2 ± 0.8 a 20.8 ± 0.9 a 25.2 ± 1.3 a
600 91.1 ± 1.6 b 115.2 ± 7.5 c 69.5 ± 2.2 d 11.6 ± 0.9 d 20.6 ± 0.6 c 13.2 ± 0.8 c 81.9 ± 1.0 c 17.7 ± 0.4 d 18.8 ± 0.4 d
900 89.1 ± 2.3 b 104.6 ± 6.5 d 52.3 ± 2.5 e 7.9 ± 0.5 e 18.2 ± 0.6 d 11.3 ± 0.8 d 81.0 ± 0.9 c 15.6 ± 0.5 e 12.5 ± 0.5 e
G ** ns ** ** ** ** ** ** **
Fe ** ** ** ** ** ** ** ** **
G × Fe ns ns ** ** * * ** ** **
Factor SPAD value Net photosynthetic rate
[μmol/(m2∙s)]
Membrane stability index
(%)
Leaf Fe content
(mg/g)
Root Fe content
(mg/g)
Genotype (G)
RD31 36.9 ± 0.4 cd 18.6 ± 0.6 b 72.8 ± 0.5 cd 7.2 ± 0.2 b 11.8 ± 0.4 b
RD41 37.8 ± 0.5 abcd 18.2 ± 0.7 b 75.2 ± 0.5 abcd 3.7 ± 0.1 f 10.9 ± 0.4 f
RD57 38.3 ± 0.3 abc 18.8 ± 1.0 b 77.1 ± 0.5 abc 5.7 ± 0.1 e 11.0 ± 0.2 d
RD71 38.1 ± 0.4 abc 19.6 ± 0.8 b 75.3 ± 0.6 abcd 5.3 ± 0.1 d 11.4 ± 0.3 e
RD77 35.7 ± 0.4 d 19.3 ± 0.6 b 74.5 ± 0.5 bcd 6.2 ± 0.1 c 11.6 ± 0.5 c
RD79 39.1 ± 0.2 abc 19.4 ± 0.8 b 77.2 ± 0.5 abc 3.9 ± 0.1 f 11.0 ± 0.3 e
RD85 39.2 ± 0.5 abc 23.0 ± 0.9 a 80.4 ± 0.2 ab 2.3 ± 0.1 h 10.1 ± 0.3 i
RD87 40.1 ± 0.3 a 22.4 ± 1.2 a 78.5 ± 0.4 abc 3.1 ± 0.1 g 10.6 ± 0.4 g
RD35 39.3 ± 0.5 ab 21.8 ± 0.8 a 78.4 ± 0.4 abc 2.6 ± 0.1 h 10.4 ± 0.2 h
Azucena 39.2 ± 0.6 ab 19.8 ± 0.7 b 81.3 ± 0.6 a 2.5 ± 0.1 h 9.9 ± 0.5 j
IR64 37.6 ± 0.5 bcd 19.2 ± 0.8 b 70.0 ± 0.4 d 8.7 ± 0.3 a 12.3 ± 0.5 a
Fe level (Fe, mg/L)
0 (control) 38.4 ± 0.4 bc 20.5 ± 0.7 c 84.1 ± 0.4 a 0.7 ± 0.0 e 4.1 ± 0.5 e
150 39.3 ± 0.4 ab 22.4 ± 0.5 b 83.9 ± 0.5 a 1.2 ± 0.0 d 8.0 ± 0.2 d
300 40.1 ± 0.4 a 25.0 ± 1.2 a 77.9 ± 0.4 b 2.0 ± 0.1 c 10.8 ± 0.2 c
600 37.5 ± 0.4 c 18.4 ± 0.5 d 71.4 ± 0.5 c 6.5 ± 0.1 b 13.3 ± 0.2 b
900 36.1 ± 0.4 d 13.7 ± 1.1 e 64.7 ± 0.6 d 12.8 ± 0.4 a 18.7 ± 0.5 a
G ** ** ** ** **
Fe ** ** ** ** **
G × Fe ** ** ** ** **
Table 3. Magnitude of stress tolerance indices among rice genotypes at different iron (Fe) levels.
Genotype Tolerance (TOL) Stress tolerance index (STI)
150 mg/L 300 mg/L 600 mg/L 900 mg/L Mean# 150 mg/L 300 mg/L 600 mg/L 900 mg/L Mean#
RD31 -2.92 ± 0.26 g -5.24 ± 0.69 i 1.83 ± 0.62 e 10.16 ± 1.75 b 5.99 ± 1.19 c 1.00 ± 0.01 b 1.03 ± 0.01 d 0.83 ± 0.01 g 0.66 ± 0.01 g 0.75 ± 0.01 f
RD41 -3.79 ± 0.15 i -5.32 ± 0.29 j 1.31 ± 0.38 f 7.23 ± 1.08 i 4.27 ± 0.78 h 1.04 ± 0.00 a 1.10 ± 0.01 a 0.85 ± 0.01 f 0.81 ± 0.01 c 0.83 ± 0.01 d
RD57 -4.10 ± 0.51 j -5.68 ± 0.61 k 2.73 ± 0.68 b 8.34 ± 1.13 e 5.54 ± 0.91 d 1.01 ± 0.02 b 1.11 ± 0.00 a 0.88 ± 0.02 de 0.77 ± 0.01 e 0.83 ± 0.02 d
RD71 -2.66 ± 0.19 e -4.88 ± 0.25 f 2.32 ± 0.60 c 8.16 ± 1.24 g 5.24 ± 0.92 f 1.01 ± 0.01 b 1.08 ± 0.01 c 0.87 ± 0.00 ef 0.77 ± 0.02 e 0.82 ± 0.01 d
RD77 -2.19 ± 0.11 c -4.91 ± 0.82 g 2.29 ± 0.81 d 8.32 ± 1.38 f 5.30 ± 1.10 e 1.01 ± 0.01 b 1.10 ± 0.02 ab 0.85 ± 0.01 f 0.75 ± 0.01 f 0.80 ± 0.01 e
RD79 -3.04 ± 0.28 h -5.01 ± 0.26 h 2.28 ± 0.75 d 9.77 ± 1.13 c 6.03 ± 0.94 b 1.02 ± 0.01 ab 1.10 ± 0.00 ab 0.90 ± 0.01 d 0.79 ± 0.01 cd 0.84 ± 0.01 c
RD85 -2.46 ± 0.12 d -3.79 ± 0.82 b 1.21 ± 0.39 g 6.93 ± 1.20 j 4.07 ± 0.80 j 1.01 ± 0.03 b 1.12 ± 0.02 a 0.94 ± 0.02 ab 0.83 ± 0.02 b 0.88 ± 0.02 b
RD87 -1.03 ± 0.09 a -4.06 ± 0.71 d 0.86 ± 0.57 h 9.48 ± 1.79 d 5.17 ± 1.18 g 1.01 ± 0.02 b 1.08 ± 0.01 bc 0.91 ± 0.01 c 0.78 ± 0.02 de 0.85 ± 0.02 c
RD35 -2.77 ± 0.14 f -4.29 ± 0.95 e 0.73 ± 0.90 i 7.78 ± 1.67 h 4.26 ± 1.29 i 1.01 ± 0.01 b 1.11 ± 0.00 a 0.92 ± 0.01 bc 0.83 ± 0.01 b 0.87 ± 0.01 b
Azucena -1.19 ± 0.17 b -3.87 ± 0.43 c 0.45 ± 0.45 j 4.36 ± 0.98 k 2.40 ± 0.72 k 1.02 ± 0.01 ab 1.10 ± 0.00 ab 0.95 ± 0.02 a 0.85 ± 0.02 a 0.90 ± 0.02 a
IR64 -3.02 ± 0.35 h 1.16 ± 0.67 a 8.15 ± 1.79 a 12.95 ± 1.34 a 10.55 ± 1.57 a 1.00 ± 0.01 b 0.91 ± 0.01 e 0.70 ± 0.01 h 0.58 ± 0.01 h 0.64 ± 0.01 g

Table 3. Magnitude of stress tolerance indices among rice genotypes at different iron (Fe) levels.

Genotype Tolerance (TOL) Stress tolerance index (STI)
150 mg/L 300 mg/L 600 mg/L 900 mg/L Mean# 150 mg/L 300 mg/L 600 mg/L 900 mg/L Mean#
RD31 -2.92 ± 0.26 g -5.24 ± 0.69 i 1.83 ± 0.62 e 10.16 ± 1.75 b 5.99 ± 1.19 c 1.00 ± 0.01 b 1.03 ± 0.01 d 0.83 ± 0.01 g 0.66 ± 0.01 g 0.75 ± 0.01 f
RD41 -3.79 ± 0.15 i -5.32 ± 0.29 j 1.31 ± 0.38 f 7.23 ± 1.08 i 4.27 ± 0.78 h 1.04 ± 0.00 a 1.10 ± 0.01 a 0.85 ± 0.01 f 0.81 ± 0.01 c 0.83 ± 0.01 d
RD57 -4.10 ± 0.51 j -5.68 ± 0.61 k 2.73 ± 0.68 b 8.34 ± 1.13 e 5.54 ± 0.91 d 1.01 ± 0.02 b 1.11 ± 0.00 a 0.88 ± 0.02 de 0.77 ± 0.01 e 0.83 ± 0.02 d
RD71 -2.66 ± 0.19 e -4.88 ± 0.25 f 2.32 ± 0.60 c 8.16 ± 1.24 g 5.24 ± 0.92 f 1.01 ± 0.01 b 1.08 ± 0.01 c 0.87 ± 0.00 ef 0.77 ± 0.02 e 0.82 ± 0.01 d
RD77 -2.19 ± 0.11 c -4.91 ± 0.82 g 2.29 ± 0.81 d 8.32 ± 1.38 f 5.30 ± 1.10 e 1.01 ± 0.01 b 1.10 ± 0.02 ab 0.85 ± 0.01 f 0.75 ± 0.01 f 0.80 ± 0.01 e
RD79 -3.04 ± 0.28 h -5.01 ± 0.26 h 2.28 ± 0.75 d 9.77 ± 1.13 c 6.03 ± 0.94 b 1.02 ± 0.01 ab 1.10 ± 0.00 ab 0.90 ± 0.01 d 0.79 ± 0.01 cd 0.84 ± 0.01 c
RD85 -2.46 ± 0.12 d -3.79 ± 0.82 b 1.21 ± 0.39 g 6.93 ± 1.20 j 4.07 ± 0.80 j 1.01 ± 0.03 b 1.12 ± 0.02 a 0.94 ± 0.02 ab 0.83 ± 0.02 b 0.88 ± 0.02 b
RD87 -1.03 ± 0.09 a -4.06 ± 0.71 d 0.86 ± 0.57 h 9.48 ± 1.79 d 5.17 ± 1.18 g 1.01 ± 0.02 b 1.08 ± 0.01 bc 0.91 ± 0.01 c 0.78 ± 0.02 de 0.85 ± 0.02 c
RD35 -2.77 ± 0.14 f -4.29 ± 0.95 e 0.73 ± 0.90 i 7.78 ± 1.67 h 4.26 ± 1.29 i 1.01 ± 0.01 b 1.11 ± 0.00 a 0.92 ± 0.01 bc 0.83 ± 0.01 b 0.87 ± 0.01 b
Azucena -1.19 ± 0.17 b -3.87 ± 0.43 c 0.45 ± 0.45 j 4.36 ± 0.98 k 2.40 ± 0.72 k 1.02 ± 0.01 ab 1.10 ± 0.00 ab 0.95 ± 0.02 a 0.85 ± 0.02 a 0.90 ± 0.02 a
IR64 -3.02 ± 0.35 h 1.16 ± 0.67 a 8.15 ± 1.79 a 12.95 ± 1.34 a 10.55 ± 1.57 a 1.00 ± 0.01 b 0.91 ± 0.01 e 0.70 ± 0.01 h 0.58 ± 0.01 h 0.64 ± 0.01 g
Fig. 2. Unweighted pair group method with arithmetic means-based neighbor-jointing dendrogram and co-cluster heatmap analysis of tested rice genotypes. Genotypes were categorized into three clusters based on the Euclidean distance matrix. Color shades in heatmap express the intensity of the stress tolerance index (STI) values on tested parameters. Avg. STI, Average stress tolerance index; Avg. TOL, Average tolerance; SPAD, Soil and plant analyzer development.

Fig. 2. Unweighted pair group method with arithmetic means-based neighbor-jointing dendrogram and co-cluster heatmap analysis of tested rice genotypes. Genotypes were categorized into three clusters based on the Euclidean distance matrix. Color shades in heatmap express the intensity of the stress tolerance index (STI) values on tested parameters. Avg. STI, Average stress tolerance index; Avg. TOL, Average tolerance; SPAD, Soil and plant analyzer development.

Fig. 3. Principal component analysis (PCA)-biplot of tested rice genotypes and selected parameters. Genotypes are dispersed in different ordinates based on their dissimilarities among them. The length of vectors in the biplot reflects their contribution on the principal component and the angles between them (from the middle point) indicate their positive or negative interactions. Larger points indicate the centroid of the corresponding cluster.

Fig. 3. Principal component analysis (PCA)-biplot of tested rice genotypes and selected parameters. Genotypes are dispersed in different ordinates based on their dissimilarities among them. The length of vectors in the biplot reflects their contribution on the principal component and the angles between them (from the middle point) indicate their positive or negative interactions. Larger points indicate the centroid of the corresponding cluster.

参考文献 62

[1] Abdi H, Williams L J. 2010. Principal component analysis. WIREs Comp Stat, 2(4): 433-459.
[2] Ali J, Jewel Z, Mahender A, Anandan A, Hernandez J, Li Z K. 2018. Molecular genetics and breeding for nutrient use efficiency in rice. Int J Mol Sci, 19(6): 1762.
[3] Asch F, Becker M, Kpongor D S. 2005. A quick and efficient screen for resistance to iron toxicity in lowland rice. J Plant Nutr Soil Sci, 168(6): 764-773.
[4] Audebert A, Fofana M. 2009. Rice yield gap due to iron toxicity in West Africa. J Agron Crop Sci, 195(1): 66-76.
[5] Audebert A, Sahrawat K L. 2000. Mechanisms for iron toxicity tolerance in lowland rice. J Plant Nutr, 23(11/12): 1877-1885.
[6] Bahrami F, Arzani A, Karimi V. 2014. Evaluation of yield-based drought tolerance indices for screening safflower genotypes. Agron J, 106(4): 1219-1224.
[7] Becker M, Asch F. 2005. Iron toxicity in rice: Conditions and management concepts. J Plant Nutr Soil Sci, 168(4): 558-573.
[8] Chan-Rodriguez D, Walker E L. 2018. Analysis of yellow striped mutants of Zea mays reveals novel loci contributing to iron deficiency chlorosis. Front Plant Sci, 9: 157.
PMID
[9] Cha-um S, Supaibulwatana K, Kirdmanee C. 2006. Water relation, photosynthetic ability and growth of Thai jasmine rice (Oryza sativa L. ssp. indica cv. KDML 105) to salt stress by application of exogenous glycinebetaine and choline. J Agron Crop Sci, 192(1): 25-36.
[10] Chérif M, Audebert A, Fofana M, Zouzou M. 2009. Evaluation of iron toxicity on lowland irrigated rice in West Africa. Tropicultura, 27(2): 88-92.
[11] Ellis R H, Roberts E H. 1981. The quantification of ageing and survival in orthodox seeds. Seed Sci Technol, 9: 373-409.
[12] Engel K, Asch F, Becker M. 2012. Classification of rice genotypes based on their mechanisms of adaptation to iron toxicity. J Plant Nutr Soil Sci, 175(6): 871-881.
[13] Fageria N K. 2007. Yield physiology of rice. J Plant Nutr, 30(6): 843-879.
[14] Fageria N K, Baligar V C, Li Y C. 2008. The role of nutrient efficient plants in improving crop yields in the twenty first century. J Plant Nutr, 31(6): 1121-1157.
[15] Fernandez G C. 1992. Effective selection criteria for assessing plant stress tolerance. In: Proceeding of the International Symposium on Adaptation of Vegetables and other Food Crops in Temperature and Water Stress. 13-16 Aug 1992, Taiwan, China: 257-270.
[16] Harahap S M, Ghulamahdi M, Aziz S A, Sutandi A, Miftahudin Dr. 2014. Relationship of ethylene production and aerenchyme formation on oxidation ability and root surfaced-iron (Fe2+) accumulation under different iron concentrations and rice genotypes. Int J Appl Sci, 4(1): 186-194.
[17] Hayat S, Hasan S A, Fariduddin Q, Ahmad A. 2008. Growth of tomato (Lycopersicon esculentum) in response to salicylic acid under water stress. J Plant Interact, 3(4): 297-304.
[18] Hellal F A, El-Shabrawi H M, Abd El-Hady M, Khatab I A, El-Sayed S A, Abdelly C. 2018. Influence of PEG induced drought stress on molecular and biochemical constituents and seedling growth of Egyptian barley cultivars. J Genet Eng Biotechnol, 16(1): 203-212.
PMID
[19] Hernández-Herrera R M, Santacruz-Ruvalcaba F, Ruiz-López M A, Norrie J, Hernández-Carmona G. 2014. Effect of liquid seaweed extracts on growth of tomato seedlings (Solanum lycopersicum L.). J Appl Phycol, 26(1): 619-628.
[20] Hussain F, Bronson K F, Yadvinder S, Singh B, Peng S. 2000. Use of chlorophyll meter sufficiency indices for nitrogen management of irrigated rice in Asia. Agron J, 92(5): 875-879.
[21] Ishimaru Y, Suzuki M, Tsukamoto T, Suzuki K, Nakazono M, Kobayashi T, Wada Y, Watanabe S, Matsuhashi S, Takahashi M, Nakanishi H, Mori S, Nishizawa N K. 2006. Rice plants take up iron as an Fe3+-phytosiderophore and as Fe2+. Plant J, 45(3): 335-346.
PMID
[22] Jain A, Connolly E L. 2013. Mitochondrial iron transport and homeostasis in plants. Front Plant Sci, 4: 348.
PMID
[23] Kar S, Panda S K. 2020. Iron homeostasis in rice: Deficit and excess. Proc Natl Acad Sci India Sect B Biol Sci, 90(2): 227-235.
[24] Keita A, Yacouba H, Hayde L G, Schultz B. 2013. A single-season irrigated rice soil presents higher iron toxicity risk in tropical savannah valley bottoms. Open J Soil Sci, 3(7): 314-322.
[25] Khan F U, Mohammad F. 2016. Application of stress selection indices for assessment of nitrogen tolerance in wheat (Triticum aestivum L.). J Anim Plant Sci, 26(1): 201-210.
[26] Kirk G. 2004. The biogeochemistry of submerged soils. Chichester, UK: John Wiley & Sons, Ltd.: 304.
[27] Krohling C A, Eutrópio F J, Bertolazi A A, Dobbss L B, Campostrini E, Dias T, Ramos A C. 2016. Ecophysiology of iron homeostasis in plants. Soil Sci Plant Nutr, 62(1): 39-47.
[28] Lê S, Josse J, Husson F. 2008. FactoMineR: An R package for multivariate analysis. J Stat Softw, 25: 1-18.
[29] Lestari A P, Suwarno, Trikoesoemaningtyas, Sopandie D, Aswidinnoor H. 2019. Estimation for stress tolerance indices of rice genotypes in low nitrogen condition. Thai J Agric Sci, 52(4): 180-190.
[30] Li G J, Kronzucker H J, Shi W M. 2016. Root developmental adaptation to Fe toxicity: Mechanisms and management. Plant Signal Behav, 11(1): e1117722.
[31] López-Millán A F, Duy D, Philippar K. 2016. Chloroplast iron transport proteins: Function and impact on plant physiology. Front Plant Sci, 7: 178.
PMID
[32] Maguire J D. 1962. Speed of germination: Aid in selection and evaluation for seedling emergence and Vigor. Crop Sci, 2(2): 176-177.
[33] Mahender A, Swamy B P M, Anandan A, Ali J. 2019. Tolerance of iron-deficient and -toxic soil conditions in rice. Plants, 8(2): 31.
[34] Matthus E, Wu L B, Ueda Y, Höller S, Becker M, Frei M. 2015. Loci, genes, and mechanisms associated with tolerance to ferrous iron toxicity in rice (Oryza sativa L.). Theor Appl Genet, 128(10): 2085-2098.
PMID
[35] Mohi-Ud-Din M, Hossain M A, Rohman M M, Uddin M N, Haque M S, Ahmed J U, Hossain A, Hassan M M, Mostofa M G. 2021. Multivariate analysis of morpho-physiological traits reveals differential drought tolerance potential of bread wheat genotypes at the seedling stage. Plants, 10(5): 879.
[36] Müller C, Kuki K N, Pinheiro D T, de Souza L R, Silva A I S, Loureiro M E, Oliva M A, Almeida A M. 2015. Differential physiological responses in rice upon exposure to excess distinct iron forms. Plant Soil, 391(1): 123-138.
[37] Nugraha Y, Rumanti I A, Guswara A, Ardie S W, Suwarno, Ghulammahdi M, Aswidinnoor H. 2016. Response of selected rice varieties under excess iron condition in media culture at seedling stage. J Pen Pert Tan Pangan, 35(3): 181-190.
[38] Onaga G, Edema R, Asea G. 2013a. Tolerance of rice germplasm to iron toxicity stress and the relationship between tolerance, Fe2+, P and K content in the leaves and roots. Arch Agron Soil Sci, 59(2): 213-229.
[39] Onaga G, Egdane J, Edema R, Abdelbagi I. 2013b. Morphological and genetic diversity analysis of rice accessions (Oryza sativa L.) differing in iron toxicity tolerance. J Crop Sci Biotechnol, 16(1): 53-62.
[40] Onaga G, Dramé K N, Ismail A M. 2016. Understanding the regulation of iron nutrition: Can it contribute to improving iron toxicity tolerance in rice? Funct Plant Biol, 43(8): 709-726.
PMID
[41] Onyango D A, Entila F, Dida M M, Ismail A M, Drame K N. 2018. Mechanistic understanding of iron toxicity tolerance in contrasting rice varieties from Africa: 1. Morpho-physiological and biochemical responses. Funct Plant Biol, 46(1): 93-105.
PMID
[42] Pawar S, Pandit E, Mohanty I C, Saha D, Pradhan S K. 2021. Population genetic structure and association mapping for iron toxicity tolerance in rice. PLoS One, 16(3): e0246232.
[43] Pereira E G, Oliva M A, Rosado-Souza L, Mendes G C, Colares D S, Stopato C H, Almeida A M. 2013. Iron excess affects rice photosynthesis through stomatal and non-stomatal limitations. Plant Sci, 201/202: 81-92.
[44] Phukunkamkaew S, Tisarum R, Pipatsitee P, Samphumphuang T, Maksup S, Cha-Um S. 2021. Morpho-physiological responses of indica rice (Oryza sativa sub. indica) to aluminum toxicity at seedling stage. Environ Sci Pollut Res Int, 28(23): 29321-29331.
[45] Quinet M, Vromman D, Clippe A, Bertin P, Lequeux H, Dufey I, Lutts S, Lefèvre I. 2012. Combined transcriptomic and physiological approaches reveal strong differences between short- and long-term response of rice (Oryza sativa) to iron toxicity. Plant Cell Environ, 35(10): 1837-1859.
[46] Ray D K, Mueller N D, West P C, Foley J A. 2013. Yield trends are insufficient to double global crop production by 2050. PLoS One, 8(6): e66428.
[47] Rout G R, Sunita S, Das A B, Das S R. 2014. Screening of iron toxicity in rice genotypes on the basis of morphological, physiological and biochemical analysis. J Exp Biol Agric Sci, 2(6): 567-582.
[48] Rout G R, Sahoo S. 2015. Role of iron in plant growth and metabolism. Rev Agric Sci, 3: 1-24.
[49] Roy S C, Sharma B D. 2014. Assessment of genetic diversity in rice [Oryza sativa L.] germplasm based on agro-morphology traits and zinc-iron content for crop improvement. Physiol Mol Biol Plants, 20(2): 209-224.
[50] Santiago-Arenas R, Fanshuri B A, Hadi S N, Ullah H, Datta A. 2020. Nitrogen fertiliser and establishment method affect growth, yield and nitrogen use efficiency of rice under alternate wetting and drying irrigation. Ann Appl Biol, 176(3): 314-327.
[51] Sikirou M, Saito K, Achigan-Dako E G, Dramé K N, Adam A, Venuprasad R. 2015. Genetic improvement of iron toxicity tolerance in rice-progress, challenges and prospects in West Africa. Plant Prod Sci, 18(4): 423-434.
[52] Sikirou M, Saito K, Dramé K N, Saidou A, Dieng I, Ahanchédé A, Venuprasad R. 2016. Soil-based screening for iron toxicity tolerance in rice using pots. Plant Prod Sci, 19(4): 489-496.
[53] Stein R J, Lopes S I G, Fett J P. 2014. Iron toxicity in field- cultivated rice: Contrasting tolerance mechanisms in distinct cultivars. Theor Exp Plant Physiol, 26(2): 135-146.
[54] Streck E A, Aguiar G A, Facchinello P H K, Perin L, da Silva P U, de Magalhães Júnior A M. 2019. Tolerance and phenotypic analysis of irrigated rice genotypes under iron toxicity. J Exp Agric Int, 31: 1-11.
[55] Tarantino T B, Barbosa I S, Lima D, Pereira M, Teixeira L S G, Korn M G A. 2017. Microwave-assisted digestion using diluted nitric acid for multi-element determination in rice by ICP OES and ICP-MS. Food Anal Method, 10(4): 1007-1015.
[56] Tennant D. 1975. A test of a modified line intersect method of estimating root length. J Ecol, 63: 995-1001.
[57] Tripathi D K, Singh S, Gaur S, Singh S, Yadav V, Liu S L, Singh V P, Sharma S, Srivastava P, Prasad S M, Dubey N K, Chauhan D K, Sahi S. 2018. Acquisition and homeostasis of iron in higher plants and their probable role in abiotic stress tolerance. Front Environ Sci, 5: 86.
[58] Ullah H, Datta A, Shrestha S, Ud Din S. 2017. The effects of cultivation methods and water regimes on root systems of drought-tolerant (RD6) and drought-sensitive (RD10) rice varieties of Thailand. Arch Agron Soil Sci, 63(9): 1198-1209.
[59] Ullah H, Giri S, Attia A, Datta A. 2020. Effects of establishment method and water management on yield and water productivity of tropical lowland rice. Exp Agr, 56(3): 331-346.
[60] Wickham H. 2016. ggplot2: Elegant Graphics for Data Analysis. New York, USA: Springer.
[61] Wu L B, Shhadi M Y, Gregorio G, Matthus E, Becker M, Frei M. 2014. Genetic and physiological analysis of tolerance to acute iron toxicity in rice. Rice, 7(1): 8.
[62] Zaid A, Ahmad B, Jaleel H, Wani S H, Hasanuzzaman M. 2020. A critical review on iron toxicity and tolerance in plants: Role of exogenous phytoprotectants. In: Aftab T, Hakeem K R. Plant Micronutrients. Cham, the Switzerland: Springer: 83-99.

相关文章 0

No related articles found!

编辑推荐

Metrics

阅读次数
全文


摘要

  • 摘要
  • 图/表
  • 参考文献
  • 相关文章
  • 编辑推荐
  • Metrics
回顶部
浙ICP备05004719号-15   公安备案号:33010302003355
版权所有 © 《Rice Science》编辑部
地址:浙江省杭州市体育场路359号 邮编:310006 电话:0571-63371017 E-mail:crrn@fy.hz.zn.cn; cjrs278@gmail.com
本系统由北京玛格泰克科技发展有限公司设计开发
总访问量: 今日访问: 在线人数: