Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.
A study of taxonomic quality of soil algae was conducted with some environmental variables in three sites of local gardens (Kadhimiya, Adhamiya and Dora) within the governorate of Baghdad for the period from October 2016 to March 2017. The study identified 28 species belonging to 16 species in which the predominance of blue green algae (18 species) Followed by Bacillarophyta algae (7 species) and three types of Chlorophyta. The study showed an increase in species of Oscillatoria. The results showed no significant differences between sites in temperature, pH and relative humidity, while there were clear differences between sites for salinity and nutrient The study showed a difference of irrigation water quality and use of different fertilize
... Show MoreIn this study, the CR-39 detector technique was used, to estimate the uranium concentration from the soil in midland refineries Company (Doura refine (, Baghdad, Iraq. Uranium concentrations in soil samples have been measured using solid state nuclear track detector type CR-39. Nine soil samples were collected from different areas within the Doura refinery and other soil samples were collected form Abu Tayara Street and ALshortaa District outside the refinery for comparison. The results showed variable values for uranium concentrations. The average value of uranium concentration was found to be 0.37 ppm in doura refinery. For areas outside the refinery, the concentration of uranium was 0.008 ppm. Thes
... Show MoreThe present study took up the different ways to cultivate the species Epipremnum aureum by two habitat water and soil and comber the anatomical features of the root, stem, and leaf. The results showed amazing significant anatomical features to the ecosystem. The root and stem anatomy showing decrease in all characters that studied but the leaf anatomy showing increase of palisade, spongy tissue thickness, midrib thickness, number of vessels in the xylem also the long and width of stomata of the soilless plants than soil ones. The upper epidermis empty from the stomata for the two treatment and the stoma diffuse in the lower epidermis, the type of it paracytic type. Also the total of flavonoids in the plant that were growth in soil reached 1
... Show MoreANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreOne of the Iraqi geotechnical problems is the presence of gypseous soils covering about (27-36) percentage of Iraq soils containing gypsum between (10-70) ratios. The main reason for soil problematic is the gypsum dissolution when these soils are inundated. However, the soluble gypsum can be leached out of the soil particles, so these problems can be led to cracking, tilting, and collapsing the related soil structure and changing the soil properties. The aim of this work is to investigate the performance of under-reamed piles as a new, improved method to reduce the moisture sensitive and the primary triggering mechanism for the volume reduction of collapsible soil, which is considered as a non-elastic deformation; this was done by c
... Show MoreBy definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb
... Show More