The use of livestock manure as a soil amendment to benefit soil health by improvements to soil physical, chemical, and biological properties, has been documented. However, quantification of the impact of improved soil health metrics on nutrient cycling has lagged. The soil your undies experiment has been implemented in the past to visually demonstrate microbial activity (Figure 1). However, this demonstration is seldom quantified, and does not have the capacity to statistically show that the effects of different management practices are distinct. The goal for this study was to quantify the degradation of fabric on a similar experiment, using cotton fabric on agricultural soils through photographic editing software. This study was designed to assess a visual method for quantifying carbon cycling in soil, observed through the degradation of buried organic materials.
What Did We Do?
White, 100% cotton fabric cloths were cut into 29.21 × 29.84 cm (871.62 cm2) (11.5 x 11.75 in, 135 in2) pieces and placed flat inside a non-degradable mesh bag (48 cm × 48 cm, 18.9 in x 18.9 in). Sixty of the mesh bags were buried at 5 cm (2 in) depth in a field planted with corn in May of 2021 (Figure 2). The sixty bags were arranged in 12 plots to which one of three soil treatments (swine slurry, swine slurry + woodchips, and control plots with no amendments) with four replications per treatment were also applied. Swine slurry was applied at a rate of 39,687.06 L-ha-1 (4,242 gal-ac-1) and woody biomass was applied at a rate of 21.52 Mg-ha-1 (9.6 tons-ac-1).
Five times during the growing season (25, 54, 81, 99 and 128 days after establishment), one bag was retrieved from each plot and returned to the lab for analysis. For each bag, soil was gently removed from the surface of the mesh and then the bag was cut open to observe the cotton fabric remaining. All the fabric pieces were photographed after retrieval. Photographs of the fabric were taken with an iPad mounted on a tripod. Fabric samples were photographed in a premeasured area of 29.21 × 29.84 cm (11.5 x 11.75 in) on a black surface (Figure 3).
Manual evaluation of percent fabric degradation for each sample was performed by overlaying a clear plastic grid (Figure 4) with primary graduations (darker lines) of 2.54 cm (1 in) and secondary graduations (lighter lines) of 6.4 mm (0.25 in) on fabric samples and counting grid squares that were void of fabric.
Each photograph was assessed using Adobe Photoshop 2020 and the free license program ImageJ. Briefly, each image was opened in the respective program and the initial fabric area (871.62 cm2) (135 in2) was delineated in the program, based on the premeasured area included in the photo to set a scale for the degradation measurement. The image was converted to black and white, and brightness and contrast were adjusted as needed to remove glare on the black background that might be misread by the program as fabric. Then, all the pixels within a specific color range – which was previously defined as fabric – were selected using the native editing tools in the two programs and this area was compared to the pixels in the initial fabric area to determine the percentage of fabric remaining.
What Have We Learned?
The three methods for estimating the area of the fabric did not show significant differences among each other, which means estimates of fabric degradation obtained with Photoshop and Image J accurately reflect manual hand counts, suggesting that these are reliable visual methods for determining the area of the remaining area of fabric (Figure 5, 6).
Future work will seek to validate this method according to standard measures of soil health and biological activity and ensure that the method has enough sensitivity to demonstrate statistical differences between soil treatments. Future studies should also focus on making the process of area estimation with the software an easier, less laborious process. Creating a cellphone app to determine degradation quickly and without the need for a computer could increase the adoption of the fabric degradation assessment method in field settings.
Amy Schmidt, Associate Professor, University of Nebraska-Lincoln
Corresponding author email address
Karla Melgar Velis, Graduate Research Assistant, University of Nebraska-Lincoln
Mara Zelt, Research Technologist, University of Nebraska-Lincoln
Andrew Ortiz Balsero, Undergraduate Research Assistant, University of Nebraska-Lincoln
Funding for this study was provided by the Nebraska Environmental Trust and Water for Food Global Institute at the University of Nebraska-Lincoln. Much gratitude is extended to collaborating members of the On-Farm Research Network, Nebraska Natural Resource Districts, Nebraska Extension Agents and Michael Hodges and family for providing the land, manure, and effort for this research project. Much appreciation to members of the Schmidt Lab who supported field and laboratory work: Juan Carlos Ramos Tanchez, Nancy Sibo, Andrew Lutt, Seth Caines and Jacob Stover.