Efficacy of Nano and Conventional Zinc and Silicon Fertilizers for Nutrient Use Efficiency and Yield Benefits in Maize Under Saline Field Conditions

Abstract

The increasing severity of salinity stress, exacerbated by climate change, poses significant challenges to sustainable agriculture, particularly in salt-affected regions. Soil salinity, impacting approximately 20% of irrigated lands, severely reduces crop productivity by disrupting plants' physiological and biochemical processes. This study evaluates the effectiveness of zinc (Zn) and silicon (Si) nanofertilizers in improving maize (Zea mays L.) growth, nutrient uptake, and yield under both saline and non-saline field conditions. ZnO nanoparticles (NPs) were synthesized via the co-precipitation method due to its ability to produce highly pure and uniform particles, while the sol-gel method was chosen for SiO₂ NPs to ensure precise control over the particle size and enhanced surface activity. The NPs were characterized using UV-Vis spectroscopy, XRD, SEM, and TEM-EDX, confirming their crystalline nature, morphology, and nanoscale size (ZnO~12 nm, SiO₂~15 nm). A split-plot field experiment was conducted to assess the effects of the nano and conventional Zn and Si fertilizers. Zn was applied at 10 ppm (22.5 kg/ha) and Si at 90 ppm (201 kg/ha). Various agronomic, chemical, and physiological parameters were then evaluated. The results demonstrated that nano Zn/Si significantly enhanced the cob length and grain yield. Nano Si led to the highest biomass increase (110%) and improved the nutrient use efficiency by 105% under saline and 110% under non-saline conditions compared to the control. Under saline stress, nano Zn/Si improved the nutrient uptake efficiency, reduced sodium accumulation, and increased the grain yield by 66% and 106%, respectively, compared to the control. A Principal Component Analysis (PCA) highlighted a strong correlation between nano Zn/Si applications with the harvest index and Si contents in shoots, along with other physiological and yield attributes. These findings highlight that nanotechnology-based fertilizers can mitigate salinity stress and enhance crop productivity, providing a promising strategy for sustainable agriculture in salt-affected soils.

Keywords: maize; nanofertilizers; nutrient uptake; silicon; soil salinity; zinc.

Figure 1

Effect of different sources of silicon and zinc on agronomic parameters under non-saline and saline conditions. (a) Plant height, (b) Tassel length, (c) Cob length, and (d) Number of cobs. Error bars represent standard error (SE), and different letters above bars indicate significant differences among treatments based on LSD test after ANOVA (α = 0.05).

Figure 2

Effect of different sources of silicon and zinc on chemical parameters under non-saline and saline conditions. (a) Na⁺ in shoot (mg kg⁻¹ DW), (b) K⁺ shoot (mg kg⁻¹ DW), (c) Zn in shoot (mg/kg), (d) Si in shoot (mg/kg) DW, (e) Zn in grain (mg/kg) and (f) Si in grain (mg/g) DW. Error bars represent standard error (SE), and different letters above bars indicate significant differences among treatments based on LSD test after ANOVA (α = 0.05).

Figure 3

Effect of different sources of silicon and zinc on nutrient use efficiency and productivity parameters under non-saline and saline conditions. (a) Zn use efficiency (b) Si use efficiency (c) Harvest Index and (d) Partial factor productivity. Error bars represent standard error (SE), and different letters above bars indicate significant differences among treatments based on LSD test after ANOVA (α = 0.05).

Figure 4

Effect of different sources of silicon and zinc on yield parameters under non-saline and saline conditions. (a) Grain Yield (kg/ha), (b) Straw Yield (kg/ha), (c) Biological Yield (kg/ha), and (d) 100 grain Weight (g). Error bars represent standard error (SE), and different letters above bars indicate significant differences among treatments based on LSD test after ANOVA (α = 0.05).

Figure 5

The effect of different zinc and silicon treatments on agronomic traits under non-saline and saline conditions based on Principal Component Analysis (PCA). The color scale (cos2) indicates variable representation in PCA space, with higher values (red/orange) showing better representation and lower values (blue/green) indicating weaker contribution. The parameters include salinity stress (Sal), conventional (Conv), control (Con), nutrient use efficiency (NUE), grain yield (GY), tassel length (TL), shoot yield (SY), 100-grain weight (100 GW), cob length (CL), plant height (PH), partial factor productivity (PFP), cob diameter (CD), number of leaves (N Leaves), and biological yield (BY).

Figure 6

Heat map of the effect of different zinc and silicon treatments on agronomic traits under non-saline and saline conditions. The parameters include salinity stress (Sal), conventional (Conv), control (Con), nutrient use efficiency (NUE), grain yield (GY), tassel length (TL), shoot yield (SY), 100-grain weight (100 GW), cob length (CL), plant height (PH), partial factor productivity (PFP), cob diameter (CD), number of leaves (N Leaves), and biological yield (BY).

Figure 7

Visual representation of maize cobs subjected to different salinity levels (non-saline and saline) and nano and conventional Zn and Si treatments.