Drying the mystery: a novel electronic sensor to quantify soft-tissue desiccation and natural mummification for forensic taphonomy

Abstract

This study investigates the desiccation process of soft-tissue in South Africa, analyzing its interaction with environmental parameters and its implications for estimating the post-mortem interval. Through the examination of four decomposing porcine bodies across two summer seasons and one winter season, the research quantifies desiccation patterns using custom-designed and constructed printed circuit boards to measure the moisture content of body tissue over time. Generalized additive models were used to determine the environmental forces driving desiccation. Tissue resistivity was tested against the environmental predictor variables to determine the amount of variation they account for, and predicted values of the region-specific tissue resistivity variables were measured for each decomposing body. Results reveal distinct desiccation trajectories between summer and winter, with summer conditions conducive to precocious natural mummification. Environmental factors, particularly temperature and solar radiation, emerge as significant drivers of desiccation. This study represents the first quantitative analysis of deep tissue desiccation internationally, but also the first quantitative assessment of desiccation and natural precocious mummification in the Western Cape, South Africa. The exploration of desiccation as a potential indicator for estimating PMI opens new avenues for research and the integration of innovative methodologies and technologies promises to revolutionize forensic taphonomy practices.

Figure 1

Schematic of the printed circuit boards (PCBs).

Figure 2

Weight loss (kg) of each porcine body from the following deployments: University of Cape Town Summer 2022 (UCT S2022), Medical Research Council Summer 2022 (MRC S2022), University of Cape Town Summer 2023 (UCT S2023).

Figure 3

(a) Digitized model of the desiccation sensor and (b) desiccation sensor insertion sites on the porcine bodies (circled in red).

Figure 4

Average of resistance levels (Ω) for University of Cape Town Summer 2022 (UCT S2022), Medical Research Council Summer 2022 (MRC S2022), University of Cape Town Summer 2023 (UCT S2023).

Figure 5

Scatterplot with LOWESS curve data, the y-axis represents moisture content while the x-axis represents accumulated degree days. The blue shaded area represents the statically smoothed (bootstrapped) data. Each graph represents the following (a) head measurements for summer; (b) head measurements for winter; (c) abdomen measurements for summer; (d) abdomen measurements for winter; (e) full body measurements for summer; (f) full body measurements for winter: (g) lower-body measurements for summer.

Figure 6

Predictive models where the y-axis represents moisture content while the x-axis represents accumulated degree days. Each graph represents (a) head (summer); (b) head (winter); (c) abdomen (summer); (d) abdomen (winter); (e) full body (summer); (f) full (winter); (g) lower- (summer).

Figure 7

(a) Population density of Cape Town suburbs with the research sites indicated on the original map from the 2011 census at the “small area” level, 2015 (https://commons.wikimedia.org/wiki/File:Cape_Town_2011_population_-density_map.svg) (b) Murder rate by suburb (2023) with research locations indicated on the original map from Crime statistics South Africa, (http://www.crimestatssa.com); the legend represents heat-mapping to show the quintiles of contact crimes (murders) in South Africa, where police precincts in the fifth quintile (top 20%) in terms of the numbers of murders nationally are indicated in red, (c) MRC research site located in Delft indicated on the map using Google Earth, (d) UCT research site located in Rosebank indicated on the map using Google Earth. This figure is modified from Adams et al. 2024.