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. 2023 Mar 6:14:1147711.
doi: 10.3389/fpls.2023.1147711. eCollection 2023.

Optimizing plant spatial competition can change phytohormone content and promote tillering, thereby improving wheat yield

Pan Liu  1   2   3   4 , Baozhong Yin  5 , Xuejing Liu  1   2   3   4   6 , Limin Gu  1   2   3   4 , Jinkao Guo  1   2   3   4   7 , Mingming Yang  8 , Wenchao Zhen  1   2   3   4
Affiliations

Optimizing plant spatial competition can change phytohormone content and promote tillering, thereby improving wheat yield

Pan Liu et al. Front Plant Sci. .

Abstract

As an important type of interplant competition, line-spacing shrinkage and row-spacing expansion (LSRE) can increase the number of tillers and improve resource utilization efficiency in wheat. Wheat tillering is closely related to various phytohormones. However, it is unclear whether LSRE regulates phytohormones and their relationship to tillering and wheat yield. This study evaluated tillering characteristics, phytohormone content in tiller nodes at the pre-winter stage, and grain yield factors for the winter wheat variety Malan1. We used a two-factor randomized block trial design with two sowing spacings of 15 cm (15RS, conventional treatment) and 7.5 cm (7.5RS, LSRE treatment) at the same density and three sowing-date groups (SD1, SD2, and SD3). LSRE significantly promoted wheat tillering and biomass at the pre-winter stage (average increases of 14.5% and 20.9% in the three sowing-date groups, respectively) and shortened the accumulated temperature required for a single tiller. Changes in the levels of phytohormones, including decreased gibberellin and indole acetic acid and increased zeatin riboside and strigolactones, were determined by high-performance liquid chromatography and were shown to be responsible for the tillering process under LSRE treatment in winter wheat. LSRE treatment can improve crop yield by increasing the number of spikes per unit area and grain weight. Our results clarified the changes in tillering and phytohormones content of winter wheat under LSRE treatment and their correlation with grain yield. This study also provides insights into the physiological mechanisms of alleviating inter-plant competition to improve crop yield.

Keywords: grain yield; line-spacing shrinkage and row-spacing expansion; phytohormone; tiller; winter wheat.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Basic information of the test site: (A) distribution of test sites and (B) foundation soil capacity of the test field. (C, D) are the daily precipitation and average temperature during the test.
Figure 2
Figure 2
Spatial distribution of plants in different row spacing.
Figure 3
Figure 3
Sampling and determination date at pre-winter stage under different sowing dates.
Figure 4
Figure 4
Sampling position, tiller criteria, and nomenclature of tillers for wheat. (A) Sampling position and tiller criteria for wheat; (B) nomenclature of tillers for wheat.
Figure 5
Figure 5
Number of wheat tillers at pre-winter stage under different sowing dates and row spacings. (A, C, E) show the green tillers number for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (B, D, F) show the green tillers number for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. (G, H) show the quantity proportion of main stems and tillers for wheat in 2019 and 2020, respectively. “*, **” indicate significant difference at 0.05 level. **P<0.01; *P<0.05. Significant markers represent the differences between 7.5 cm and 15 cm row spacing treatments at the same sowing date and observation period. Number of wheat tillers at pre-winter stage under different sowing dates and row spacings.
Figure 6
Figure 6
Biomass of wheat tillers at pre-winter stage under different sowing dates and row spacings. (A, C, E) show the dry matter accumulation for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (B, D, F) show the dry matter accumulation for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. (G, H) show the biomass accumulation proportion of main stems and tillers for wheat in 2019 and 2020, respectively. ”*, ** ”indicate significant difference at 0.05 level. **P<0.01; *P<0.05. Significant markers represent the differences between 7.5 cm and 15 cm row spacing treatments at the same sowing date and observation period. MS stands for main stem, TI, TII, and TIII represent the first, second, and third tillers of the main stem respectively, and OT represents the fourth and other tillers of the main stem.
Figure 7
Figure 7
Accumulated temperature required for tillering at different tillers of wheat at pre-winter stage under different sowing dates and row spacings. (A) shows the AT required for different treatments of tillers at each level for wheat. (B) shows the linear fitting of AT required for wheat tillers with 7.5RS and 15RS. “*, ** ”indicate significant difference at 0.05 level. ** P<0.01; *P<0.05. Significant markers represent the differences between 7.5 cm and 15 cm row spacing treatments at the same sowing date and observation period. TI, TII, TIII, and TIV represent the first, second, and third tillers of the main stem, respectively. Taver represents the average of TI, TII, TIII, and TIV. 15RS and 7.5RS fitting equations are Y 15RS = +70.66+3.78x and Y 7.5RS = 73.3 + 0.55x, respectively.
Figure 8
Figure 8
IAA and ZR content of wheat tillers at pre-winter stage under different sowing dates and row spacings. (A, C, E) show the IAA content for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (B, D, F) show the IAA content for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. (G, I, K) show the ZR content for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (H, J, L) show the ZR content for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. “*, **” indicate significant difference at 0.05 level. **P<0.01; *P<0.05. Significant markers represent the differences between 7.5 cm and 15 cm row spacing treatments at the same sowing date and observation period.
Figure 9
Figure 9
SL and GA content of wheat tillers at pre-winter stage under different sowing dates and row spacings. (A, C, E) show the SLs content for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (B, D, F) show the SLs content for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. (G, I, K) show the GA content for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (H, J, L)show the GA content for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. “*, **” indicate significant difference at 0.05 level. **P<0.01; *P<0.05. Significant markers represent the differences between 7.5 cm and 15 cm row spacing treatments at the same sowing date and observation period.
Figure 10
Figure 10
IAA/ZRand SLs/GA of wheat tillers at pre-winter stage under different sowing dates and row spacings. (A, C, E) show the IAA/ZR for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (B, D, F) show the IAA/ZR for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. (G, I, K) show the SLs/GA for wheat in pre-winter stage for SD1, SD2 and SD3 in 2019, respectively. (H, J, L) show the SLs/GA for wheat in pre-winter stage of SD1, SD2 and SD3 in 2020, respectively. “*, **” indicate significant difference at 0.05 level. **P<0.01; *P<0.05. Significant markers represent the differences between 7.5 cm and 15 cm row spacing treatments at the same sowing date and observation period.
Figure 11
Figure 11
Correlation between tiller number, biomass and phytohormone contents of wheat tillers at pre-winter stage under different sowing dates and row spacings. (A–C) show the correlation data of SD1, SD2 and SD3, respectively. (D) shows the average correlation data of SD1-SD3. “r” is Person two tailed correlation coefficient, “*” indicate significant difference at 0.05 level. *P<0.05. (D) Figure D is the network diagram of the correlation coefficient adjacency matrix between indicators, and the node layout adopts the Kamada–Kawai algorithm. The connection represents r between each two nodes. The thicker the connection, the greater the absolute value of r, and the data of (D) comes from the mean of SD1, SD2, and SD3.
Figure 12
Figure 12
Path effect of different action factors (independent variables) on grain yield (dependent variables). X1 , X2 , X7 , X9 , X 12, X 13, X 14, and GY represent tillers in pre-winter stage (TP), tillers in spring stage (TS), effective spikes on main stem (ESM), percentage of effective tillers in spring (PESS), effective spikes in the whole growth period (ESW), kernel number per spike (KN), 1,000-grain weight (GW) and grain yield (GY) respectively. ANOVA: *P <0.05, it is the Pearson’s two tailed correlation coefficient between action factor (Xi ) and the GY. The arrow points to the effect of one factor on GY through another factor, and the thicker the line, the greater the indirect path coefficient (absolute value of IDC). Panels (A, B) show 15RS and 7.5RS treatment under SD1, respectively. Panels (C, D) show 15RS and 7.5RS treatment under SD2, respectively. Panels (E, F) show 15RS and 7.5RS treatment under SD3, respectively.
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