Mechanistic framework to link root growth models with weather and soil physical properties, including example applications to soybean growth in Brazil

Background and aimsRoot elongation is generally limited by a combination of mechanical impedance and water stress in most arable soils. However, dynamic changes of soil penetration resistance with soil water content are rarely included in models for predicting root growth. Better modelling frameworks are needed to understand root growth interactions between plant genotype, soil management, and climate. Aim of paper is to describe a new model of root elongation in relation to soil physical characteristics like penetration resistance, matric potential, and hypoxia.MethodsA new diagrammatic framework is proposed to illustrate the interaction between root elongation, soil management, and climatic conditions. The new model was written in Matlab®, using the root architecture model RootBox and a model that solves the 1D Richards equations for water flux in soil. Inputs: root architectural parameters for Soybean; soil hydraulic properties; root water uptake function in relation to matric flux potential; root elongation rate as a function of soil physical characteristics. Simulation scenarios: (a) compact soil layer at 16 to 20 cm; (b) test against a field experiment in Brazil during contrasting drought and normal rainfall seasons.Results(a) Soil compaction substantially slowed root growth into and below the compact layer. (b) Simulated root length density was very similar to field measurements, which was influenced greatly by drought. The main factor slowing root elongation in the simulations was evaluated using a stress reduction function.ConclusionThe proposed framework offers a way to explore the interaction between soil physical properties, weather and root growth. It may be applied to most root elongation models, and offers the potential to evaluate likely factors limiting root growth in different soils and tillage regimes

Selecting Monitoring Variables in the Manual Composting of Municipal Solid Waste Based on Principal Component Analysis

This paper proposes the use of principal component analysis performed on the correlation matrix for identifying the best variables for monitoring the composting of municipal solid wastes. Accordingly, 12 physicochemical and two microbiological parameters have been measured throughout the 7 weeks in which the compositing of 1300 kg of organic wastes obtained from MSW was carried out. All the analyses confirm a correct development of the composting process, and the final values fulfil the requirements of the Colombian legislation. The statistical analysis shows that four variables are sufficient for ensuring a suitable process development and, based on economic criteria and technical simplicity, the selected ones are as follows: respirometry, water retention capacity, ash content and moisture content. © 2018 Springer Science+Business Media B.V., part of Springer Natur