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. 2023 Oct 31:14:1283588.
doi: 10.3389/fpls.2023.1283588. eCollection 2023.

Enhancing physiological metrics, yield, zinc bioavailability, and economic viability of Basmati rice through nano zinc fertilization and summer green manuring in semi-arid South Asian ecosystem

Affiliations

Enhancing physiological metrics, yield, zinc bioavailability, and economic viability of Basmati rice through nano zinc fertilization and summer green manuring in semi-arid South Asian ecosystem

Kirttiranjan Baral et al. Front Plant Sci. .

Abstract

During the summer and rainy seasons (April-October) of 2020 and 2021, two consecutive field experiments were conducted at the research farm of the ICAR-Indian Agricultural Research Institute, New Delhi, India. In this study, we examined the effects of summer green manuring crops (GM) and a variety of zinc fertilizers (ZnF) on Basmati rice (Oryza sativa L.) growth, physiological development, yield response, zinc nutrition and economic returns. A combination of GM residues and nano zinc fertilization helped significantly enhancing Basmati rice's growth and its physiological development. Following the incorporation of Sesbania aculeata (Sesbania), successive Basmati rice physiological parameters were significantly improved, as well as grain, straw, biological yields, harvest index and economic returns. The highest Zn content of 15.1 mg kg -1 and the lowest of 11.8 mg kg -1 in milled rice grain were recorded in Sesbania green manuring (G2) and control i.e., in the fallow (G1), respectively. Coating onto urea with 0.2% nano zinc oxide (NZnCU) was observed to be more effective than other zinc sources in terms of growth parameters, yield attributes, zinc nutrition, grain and straw yields for succeeding Basmati rice crop; however, the effects were comparable to those of bulk zinc oxide-coated urea (BZnCU) of 1%. The highest Zn content of 15.1 mg kg -1 was recorded with the application of 1% BZnCU and the lowest of 11.96 mg kg -1 with the soil application of 5 kg Zn ha -1 through bulk ZnO in the milled rice grain. Application of 1% BZnCU led to a 26.25% increase in Zn content of milled rice grain compared to soil application of 5 kg Zn ha -1 through bulk ZnO. As a result, the combination of inclusion of Sesbania aculeata (Sesbania) residue and 0.2% NZnCU was identified as the most effective treatment, for Basmati rice growth and physiological development. A combination of nano Zn fertilization in conjunction with the incorporation of green manure can be advocated for better growth, physiological performance, zinc dense grains, and higher profitability of Basmati rice for farmers and consumers.

Keywords: economics; green manuring; growth; nano Zn; yields; zinc biofortification.

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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
(A) Effect of summer green manuring on the plant height (cm) of Basmati rice (pooled data of 2 years). (B) Effect of Zn fertilizer sources on the plant height (cm) of Basmati rice (pooled data of 2 years). Boxplot of same letter(s) don’t differ significantly at 5% probability level by DMRT. DAT, Days after transplanting.
Figure 2
Figure 2
(A) Effect of summer green manuring on the dry matter accumulation (g hill–1) of Basmati rice (pooled data of 2 years). (B) Effect of Zn fertilizer sources on the dry matter accumulation (g hill–1) of Basmati rice (pooled data of 2 years). Boxplot of same letter(s) don’t differ significantly at 5% probability level by DMRT. DAT, Days after transplanting.
Figure 3
Figure 3
(A) Effect of summer green manuring on the yields and harvest index of Basmati rice (pooled data of 2 years). (B) Effect of Zn fertilizer sources on the yields and harvest index of Basmati rice (pooled data of 2 years). Boxplot of same letter(s) don’t differ significantly at 5% probability level by DMRT.
Figure 4
Figure 4
(A) Experimental field view. (B) Fallow+ 5 kg Zn ha–1 as bulk ZnO. (C) Sesbania + 5 kg Zn ha–1 as bulk ZnO. (D) Fallow + 0.2% NZCU. (E) Sesbania + 0.2% NZCU. (F) Cowpea + 0.2% NZCU.
Figure 5
Figure 5
Correlation matrix depicting correlation co–efficient (upper half), density plot (diagonal) and scatter plot (lower half). LAI_30, Leaf area index at 30 DAT; LAI_60, Leaf area index at 60 DAT; LAI_90, Leaf area index at 90 DAT; CGR_0–30, Mean CGR 0–30 DAT; CGR_30–60, Mean CGR 30–60 DAT; RGR_30–60, Mean RGR 30–60 DAT; NAR_30–60, Mean NAR 30–60 DAT; DAT, Days after transplanting; *, Significant at p=0.05; **, Significant at p=0.01; ***, Significant at p=0.001.
Figure 6
Figure 6
(A) Regression between grain yield and LAI at 30 DAT. (B) Regression between grain yield and LAI at 60 DAT. (C) Regression between grain yield and LAI at 90 DAT. DAT, Days after transplanting.
Figure 7
Figure 7
(A) Regression between grain yield and mean CGR 0–30 DAT. (B) Regression between grain yield and mean CGR 30–60 DAT. (C) Regression between grain yield and mean RGR 30–60 DAT. (D) Regression between grain yield and mean NAR 30–60 DAT. DAT, Days after transplanting.
Figure 8
Figure 8
(A) Regression between grain yield and Zn content in milled rice. (B) Regression between grain yield and Zn content in straw.
Figure 9
Figure 9
(A) Effect of summer green manuring on the zinc nutrition of Basmati rice (pooled data of 2 years). (B) Effect of Zn fertilizer sources on the zinc nutrition of Basmati rice (pooled data of 2 years). Boxplot of same letter(s) don’t differ significantly at 5% probability level by DMRT.

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