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An unsolved problem in the digital mapping of categorical soil variables and soil types is the imbalanced number of observations, which leads to reduced accuracy and the loss of the minority class (the class with a significantly lower number of observations compared to other classes) in the final map. So far, synthetic over- and under-sampling techniques have been explored in soil science; however, more efficient approaches that do not have the drawbacks of these techniques and guarantee retention of the minority classes in the produced map are essentially required. Such approaches suggested in the present study for digital mapping of soil classes include machine learning models of ensemble gradient boosting, cost-sensitive learning and one-class classification (OCC) of the minority class combined with multi-class classification. In this regard, extreme gradient boosting (XGB) as an ensemble gradient learner, a cost-sensitive decision tree (CSDT) within the C5.0 algorithm, and a one-class support vector machine combined with multi-class classification (OCCM) were investigated to map eight soil great groups with a naturally imbalanced frequency of observations in northwest Iran. A total of 453 profile data points were used for mapping the soil great groups of the study area. A data split was done manually for each class separately, which resulted in an overall 70% of the data for calibration and 30% for validation. The bootstrapping approach of calibration (with 10 runs) was performed to produce multiple maps for each model. The 10 bootstraps were evaluated against the hold-out validation dataset. The average values of accuracy measures, including Kappa (K), overall accuracy (OA), producer's accuracy (PA) and user's accuracy (UA), were explored. In addition, the results of this study were compared with a previous study in the same area, in which resampling techniques were used to deal with imbalanced data for digital soil class mapping. The findings show that all three suggested methods can deal well with the imbalanced classification problem, with OCCM showing the highest K (= 0.76) and OA (= 82) in the validation stage. Also, this model can guarantee the retention of the minority classes in the final map. Comparing the present approaches with the previous study approach demonstrates that the three newly suggested methods can remarkably increase both overall and individual class accuracy for mapping. 相似文献
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Mansoor Sarani Mostafa Oveisi Hamid Rahimian Mashhadi Hassan Alizade Jose Luise Gonzalez‐Andujar 《Weed Biology and Management》2014,14(3):198-208
Field experiments were conducted in Iran in order to determine the interactions between the tillage system and crop rotation on weed seedling populations and crop yields from 2002 to 2005. No tillage, shallow tillage and deep tillage were the main plots and three crop sequences comprising continuous wheat (W‐W), wheat–canola–wheat–canola (C‐W) and wheat–safflower–wheat–safflower (S‐W) were the subplots. Bromus japonicus, Carthumus lanatus, Polygonum aviculare, Lolium temulentum and Avena ludoviciana were found to be the dominant species. The initial weed population in 2002 was estimated at 65 seedlings per m2 and B. japonicus (～35 seedlings per m2) was the most abundant species, followed by A. ludoviciana and L. temulentum. The dominant weed species mostly did not favor the combination of S‐W and C‐W with any tillage type. For the B. japonicus population, S‐W in combination with moldboard plowing indicated the lowest seedling population. In conclusion, the crop sequence in combination with tillage would help to control troublesome weed species. Safflower and canola were determined to be effective in reducing the grass weeds. The inclusion of these crops in rotation also increased the total revenue of the cropping systems because of the higher sale price of canola and safflower. 相似文献
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Fereydoon Sarani Ahmad Gholamalizadeh Ahangar 《Archives of Agronomy and Soil Science》2016,62(1):127-138
Monitoring exchangeable sodium percentage (ESP) and sodium adsorption ratio (SAR) variability in soils is both time-consuming and expensive. However, in order to estimate the amounts of amendments and land management, it is essential to know ESP and SAR variations and values in sodic or saline and sodic soils. Thus, presenting a method which uses easily obtained indices to estimate ESP and SAR indirectly is more optimal and economical. Input data of the current research were 189 soil samples collected based on a regular networking approach from Miankangi region, Sistan plain, Iran. Then, their physicochemical properties were measured. Results showed that SAR = 3.8 × ln(EC) + 22.83 × ln(pH) – 44.37, (R2 = 0.63), and ESP = 3.98×ln(EC) + 36.88(pH) – 56.98 (R2 = 0.78) are the best regression models for estimating SAR and ESP, respectively. Moreover, multilayer perceptron (MLP), which explains 95–97% of parameters of soil sodicity using EC and pH as inputs, was the best neural network model. Therefore, MLP could be applied for ESP and SAR evaluation with high accuracy in the Miankangi region. 相似文献
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Fereydoon Aflaki Nader Saemian Shahab Shiebani Maryam Salahinejad 《Journal Of Aquatic Food Product Technology》2017,26(1):43-53
The biogenic amine contents in fillets of three freshwater fish of kutum (Rutilus frisii), common carp (Cyprinus carpio), and Caspian salmon (Salmon caspius) were monitored during storage at 4°C for 20 days. The amounts of biogenic amines were determined at regular intervals using high performance liquid chromatography after derivatization with benzoyl chloride. Significant differences in the levels of selected biogenic amines among the fish samples were found (p < 0.05) during storage times. While the amount of putrescine, cadaverine, histamine, and tyramine in the fish fillets increased during the storage time, the changes in spermine and spermidine contents of the fish species were minor and both showed low and inverse correlations with storage time. For each of the three fish species, the sensory acceptability limit was found to be 4–8 days. The quality and biogenic amine indices of fish samples showed high correlation with storage time (r > 0.9). The principal component analysis of the results indicated that the formation of biogenic amines displays a certain behavioral pattern in all fish samples. 相似文献
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Javad Seyedmohammadi Fereydoon Sarmadian Ali Asghar Jafarzadeh Richard W. McDowell 《Archives of Agronomy and Soil Science》2019,65(8):1063-1079
Land suitability assessment can inform decisions on land uses suitable for maximizing crop yield while making best use, but not impairing the ability of natural resources such as soil to support growth. We assessed the suitability of maize to be produce in 12,000 ha land of Dasht-e-Moghan region of Ardabil province, northwest of Iran. Suitability criteria included soil depth, gypsum (%), CaCO3 (%), pH, electrical conductivity (EC), exchangeable sodium percentage (ESP), slope (%) and climate data. We modified and developed a novel set of techniques to assess suitability: fuzzy set theory, analytic network process (ANP), remote sensing and GIS. A map of suitability was compared a map created using a traditional suitability technique, the square root method. The coefficient of determination between the land suitability index and observed maize yield for square root and ANP-fuzzy methods was 0.747 and 0.919, respectively. Owing to greater flexibility to represent different data sources and derive weightings for meaningful land suitability classes, the ANP-fuzzy method was a superior method to represent land suitability classes than the square root method. 相似文献
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