Secondary Salinization of Reclaimed Solonetzes and Its Aftereffect

Eurasian Soil Science - The studies were performed at the long-term stationary experiment on crusty hydromorphic solonetzes of the Baraba Plain during 1986–2017. In the humid year of 2013,...     

Russian Soil Classification System: Towards the Next Approximation

Eurasian Soil Science - The current status of soil classification in Russia is considered: its usage; difference among variants of 1997, 2004, and 2008; and reasons, means, and methods for its...     

International Environmental Legislation on the Content of Chemical Elements in Soils: Guidelines and Schemes

Eurasian Soil Science - We analyzed the original and most developed environmental legislation of the Netherlands, Germany, the United States, and Canada, as well as the systems of Finland, the...     

GPR Diagnostics of Chernozem Humus Horizon Thickness

This work aimed to search for indicators of the thickness of the humus horizon of chernozem soils based on the data of ground-penetrating radar (GPR) surveying. The investigation was carried out on a test site located in Russia’s Tula oblast. The area is dominated by arable podzolized chernozems, including ones eroded to a varying extent. In parallel with GPR profiling in the field, soil was drilled to determine the lower boundary of the humus horizon. Based on the conjugate analysis of GPR profiling data and the field determination of the thickness of the humus horizon, a new indicator was proposed: the coefficient of asymmetry of the modal value of the peak of the spectral density of the first-period reflected GPR pulse obtained at a frequency of 100 MHz. The proposed indicator demonstrates a good statistical relationship with the thickness of the humus horizon of chernozem soils. For the test region, a regression model of this relationship was constructed with a determination coefficient of approximately 0.82. To calculate the thickness of the humus horizon (A+AB), it is suggested to use the lower boundary of the second period of the spectral density of the reflected signal, which correlates well with the actual data. The developed approach can be used to map the thickness of the humus horizon in the chernozem soils of the research region. Theoretically, this approach can be extended to soils of other regions.     

Molecular markers in identification of sunflower pollen fertility restorer genes

The presence of the Rf1 gene (pollen fertility restorer of CMS PET1) in genotypes of most restorer lines is confirmed by molecular and hybridological analysis methods. Molecular markers of the Rf1 locus are identified for the first time in genotypes of autofertile lines of the collection of the Vavilov All-Russian Research Institute of Plant Industry (VIR) as well as in genomes of perennial and annual wild species of the genus Helianthus. The possibility of introgression of the fertility restorer gene into the genome of the cultivated sunflower during distant hybridization is shown.     

Use of an axial rotary threshing device for threshing clover seed

The effect of the parameters and operating regime of an axial rotary threshing device on the quality indices of the technological process of threshing clover seeds is shown. Their optimal values are determined.     

The use of k-means and artificial neural network to classify cotton lint

The use of High Volume Instrument (HVI) to measure cotton lint characteristics produces high dimensional data. A model which utilized Kohonen Self Organizing Maps (SOM) to visualize cotton lint HVI data, k-means clustering technique to cluster the data and Probabilistic Neural Network (PNN) for data classification was designed and tested using Kenyan cotton lint. According to the model the Kenyan cotton lint can be grouped into four clusters, which were successfully classified by using PNN with a correlation coefficient (R-value) of 1.