Zinc deficiency takes a huge toll on farmers, impacting plant growth and ultimately crop yield. Using micro-computed tomography, researchers at Sheffield Multimodal Imaging Centre (SMIC) have examined the effectiveness of commercial seed film coatings. The study is providing insights that could improve product performance and give crops a much-needed zinc boost.

The importance of zinc

Of all nutrient deficiencies, zinc is the most detrimental for agricultural plants¹. It’s a key nutrient in the enzymatic processes for cell development and directly impacts plant growth.

To aid crop yield, seeds can be coated with chemical solutions prior to sowing. These coatings provide a variety of benefits to seedlings by delivering essential micronutrients like zinc. 

To improve the effectiveness of these commercial products, suppliers need to know how their coatings are distributed across seeds. But at the microscopic scale, it’s difficult to see things clearly.

Testing the coatings

Research at SMIC analysed how micro-computed tomography (µ-CT) can be used to image the surface of a wheat seed and detect zinc oxide (ZnO) distribution and particle size. 

To mirror the conditions of commercial products, wheat seeds were treated with a solution containing ZnO solution and stored for 12 months before scanning.

The seeds were mounted in dental putty and analysed using the SkyScan 1272 (Bruker, MA, USA) with no filter and a spot size of 5.19 µm. Untreated control seeds were then compared to ZnO-coated ‘Reference’ treated samples. 

The resulting 3D images of untreated and Reference coated seeds were pseudo-coloured for density. This provided a clear picture of how the seed coatings were distributed, as shown below.

The results

From the 3D reconstructions, areas of higher density (> 0.6, Red) were identified on the Reference coated seed which did not appear on the untreated seed. 

Since the only difference between the two seeds was the presence of the seed coating, there is a strong likelihood that the areas of higher density corresponded to the seed coating on the seed surface. This hypothesis is supported by recent work in which µCT was able to detect the presence of ZnO nanoparticles on the eyes of rodents².

CTAn software was used to carry out analysis between the untreated and treated seeds, using a threshold discrimination method to exclude the density signals associated with the seed tissue. Particles of increased density were present in the treated seed and absent in the untreated control as shown in Figure 2.

Looking forward 

Future work will include ZnO quantification, enabling comparison of surface particle volume and dispersion between treatment formulations. µCT imaging may also be used to assess the impact of seed coating formulations on the volume and distribution of root growth. 

This case study has highlighted the potential use of µCT in the analysis of ZnO containing seed coatings and the ability to map coating dispersion across a 3-dimensional surface. 

Further analysis may identify an optimum coating formulation, leading to increased nutrient delivery and an enhanced crop yield if successful.