Estimating soil aggregate size distribution from images using pattern spectra. (October 2020)

• Record Type: Journal Article
• Authors: Bosilj, Petra; Gould, Iain; Duckett, Tom; Cielniak, Grzegorz
• Is Part Of: Biosystems engineering. Volume 198(2020)
• Page Start: 63
• Page End: 77
• Publication Date: 2020-10
• Subjects: Pattern spectra -- Component trees -- Soil aggregate analysis; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2020.07.012
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : A method for quantifying aggregate size distribution from the images of soil samples is introduced. Knowledge of soil aggregate size distribution can help to inform soil management practices for the sustainable growth of crops. While current in-field approaches are mostly subjective, obtaining quantifiable results in a laboratory is labour- and time-intensive. Our goal is to develop an imaging technique for quantitative analysis of soil aggregate size distribution, which could provide the basis of a tool for rapid assessment of soil structure. The prediction accuracy of pattern spectra descriptors based on hierarchical representations from attribute morphology are analysed, as well as the impact of using images of different quality and scales. The method is able to handle greater sample complexity than the previous approaches, while working with smaller samples sizes that are easier to handle. The results show promise for size analysis of soils with larger structures, and minimal sample preparation, as typical of soil assessment in agriculture. Highlights: Trained regression models able to predict soil aggregate size distribution from images. Identification of the most suitable hierarchical representation for attribute pattern spectra. Comparison to the classical structuring element spectra. Publishing the dataset with RGB images of soil samples at different scales, with their aggregate size distribution.