Comparing placentas from normal and abnormal pregnancies

This report describes work carried out at a Mathematics-in-Medicine Study Group. It is believed that placenta shape villous network characteristics are strongly linked to the placenta’s efficiency, and hence to pregnancy outcome. We were asked to consider mathematical ways to describe the shape and other characteristics of a placenta, as well as forming mathematical models for placenta development. In this report we propose a number of possible measure of placental shape, form, and efficiency, which can be computed from images already obtained. We also consider various models for the early development of placentas and the growth of the villous tree

TetraploidSNPMap: Software for Linkage Analysis and QTL Mapping in Autotetraploid Populations Using SNP Dosage Data

An earlier software application of ours, TetraploidMap for Windows, enabled linkage analysis and quantitative trait locus interval mapping to be carried out in an experimental cross of an autotetraploid species, using both dominant markers such as amplified fragment length polymorphisms and codominant markers such as simple sequence repeats. The size was limited to 800 markers, and quantitative trait locus mapping was conducted for each parent separately due to the difficulties in obtaining a reliable consensus map for the 2 parents. Modern genotyping technologies now give rise to datasets of thousands of single nucleotide polymorphisms, and these can be scored in autotetraploid species as single nucleotide polymorphism dosages, distinguishing among the heterozygotes AAAB, AABB, and ABBB, rather than simply using the presence or absence of an allele. The dosage data is more informative about recombination and leads to higher density linkage maps. The current program, TetraploidSNPMap, makes full use of the dosage data, and has new facilities for displaying the clustering of single nucleotide polymorphisms, rapid ordering of large numbers of single nucleotide polymorphisms using a multidimensional scaling analysis, and phase calling. It also has new routines for quantitative trait locus mapping based on a hidden Markov model, which use the dosage data to model the effects of alleles from both parents simultaneously. A Windows-based interface facilitates data entry and exploration. It is distributed with a detailed user guide. TetraploidSNPMap is freely available from our GitHub repository

Analysis of the Effect of Tilling and Crop Type on Soil Structure Using 3D Laser Profilometry

Background and aim: Soil structure is an important indicator of the quality of soil, but detecting the early signs of soil degradation from soil structure is difficult. Developing precise instruments able to diagnose soil structure quickly is therefore critical to improve management practices. Here, the objective is to develop an instrument analysing the roughness of surfaces resulting from the fracture of soil cores, and to test the instrument’s ability to detect changes in soil structure cause by crop type and tillage. We have designed and constructed a 3D laser profilometer suitable for analysing standard soil cores. The 3D soil profiles were first assembled into a 3D surface using image analysis before roughness indicators could be computed. The method was tested by analysing how soil surface roughness was affected by crop varieties (barley and bean) and tillage (conventional tillage and no tillage). Results showed the method is precise and could reliably detect an influence of crop type and tillage on the roughness indicator. It was also observed that tillage reduced the difference in soil structure between the different cultures. Also, the soil in which barley grew had significantly lower roughness, irrespective of the tillage method. This could indicate that the roughness indicator is affected by biopores created by the root system. In conclusion, roughness indicators obtained from the fracture of soil cores can be easily obtained by laser profilometry and could offer a reliable method for assessing the effect of crop types and soil management on soil quality.</p

Analysis of the Effect of Tilling and Crop Type on Soil Structure Using 3D Laser Profilometry

Background and aim: Soil structure is an important indicator of the quality of soil, but detecting the early signs of soil degradation from soil structure is difficult. Developing precise instruments able to diagnose soil structure quickly is therefore critical to improve management practices. Here, the objective is to develop an instrument analysing the roughness of surfaces resulting from the fracture of soil cores, and to test the instrument’s ability to detect changes in soil structure cause by crop type and tillage. We have designed and constructed a 3D laser profilometer suitable for analysing standard soil cores. The 3D soil profiles were first assembled into a 3D surface using image analysis before roughness indicators could be computed. The method was tested by analysing how soil surface roughness was affected by crop varieties (barley and bean) and tillage (conventional tillage and no tillage). Results showed the method is precise and could reliably detect an influence of crop type and tillage on the roughness indicator. It was also observed that tillage reduced the difference in soil structure between the different cultures. Also, the soil in which barley grew had significantly lower roughness, irrespective of the tillage method. This could indicate that the roughness indicator is affected by biopores created by the root system. In conclusion, roughness indicators obtained from the fracture of soil cores can be easily obtained by laser profilometry and could offer a reliable method for assessing the effect of crop types and soil management on soil quality.</p

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution