Pipette Method Research Articles

Variations in soil erodibility (K-factor) for the Chernozems depending on the method of texture determination

Soil erodibility (K-factor) is an important parameter in erosion modeling, is one of five factors of the Revised Universal Soil Loss Equation (RUSLE), and generally represents the soil's response to rainfall and run-off erosivity. The erodibility could be determined based on direct measurements of soil properties and mathematical calculations. In this study, the K-factor was calculated based on a formula from RUSLE, proposed by Renard et al. (1997). All input parameters: soil organic carbon (SOC), soil structure, and permeability classes were measured by one method, but particle size distribution – in two ways by sedimentation and laser diffraction methods to assess the impact the K-factor variability and the values of soil erosion rates. The 107 soil samples of Chernozems from Kursk Oblast (Russia) were studied. The texture for the most of samples was classified as silty loam in both analyses. However, the laser diffraction underestimates the clay content by an average of 13.2% compared to the pipette method. The average K-factor estimated based on laser diffraction data was 0.050, and 0.034 t ha h ha−1 MJ−1 mm−1 – sedimentation method. Thus, depending on the method of soil texture analysis, the RUSLE calculated soil loss could underestimated/overstated by 32% (or 4 t ha-1 yr-1 on average in the study site). Therefore, we propose a regression equation-based conversion method of laser diffraction data to sedimentation method data for Chernozems.The Laska-TM laser analyzer measured on ∼ 13% less clay fraction (more on ∼ 8% silt and ∼ 5% fine sand) compared with sedimentation method data.For erosional researchers/modelers it is suggested to state the method of soil texture analysis (based on sedimentation law or laser diffraction) was used for RUSLE K-factor calculations.To convert K-factor values (for Chernozems) calculated and based on data of the sedimentation method to laser sedimentation – it suggested utilize the coefficient 1.47 (0.68 – vice versa).

Distribution of 210Po activity and soil texture in agricultural soil.

The assessment of 210Po in agricultural soil matrices in different regions of Kerala and Karnataka was studied. The wet ash method was used to find the activity concentration of 210Po. The alpha activity was counted using a silver-activated zinc sulfide counter of 30% efficiency, and the activity was calculated. The average concentration of 210Po activity in soil samples ranged from 0.09 to 20.52Bqkg-1, with an average value of 4.47Bqkg-1. The soil texture was measured using the International Pipette method. Using the IBM Statistical Package of Social Science Software, the frequency distribution curve of 210Po is plotted and found to be lognormal. The data of 210Po are highly skewed, and the Kurtosis has a significant positive value. The 210Po activity concentrations are substantially within the World Health Organization's recommended limits.

Morphometric and soil texture analysis of soil material from wasp nests Sceliphron destillatorium (Illiger, 1807) (Apoidea: Sphecidae)

Background. The article presents the data obtained as a result of our research on the nests of an aboriginal wasp species on the territory of Ukraine – Sceliphron destillatorium (Illiger, 1807) that belongs to the family Sphecidae. We collected 54 wasp nests in different regions: Zakarpattia (n = 4), Ivano-Frankivsk (n = 1), Rivne (n = 12) and Lviv (n = 35) Regions. The data are presented as a result of measuring the main morphometric parame­ters of nests (length, width of cells and mass of nests) which are typical of the species under study. The paper also reports the results of the soil texture analysis of the soil material of twelve wasp nests from four different places of “mass nesting” and compares the results with the control samples of the surrounding soils in the corresponding areas. The study aimed at investigating the structure of the nests of S. destillatorium wasps, determining the soil texture of the soil material of nests from different regions of Ukraine and comparing them. Material and Methods. The nests of Sceliphron destillatorium wasps were the object of the study. The morphometric parameters of nests were measured with an automatic digital caliper 0–150 mm and Axis A500 technical chemical scales. The soil texture analysis was performed by the pipette method. The potentiometric method was used to determine the pH of the soil material. In addition, the determination of the CO2 carbonates was carried out according to the volumetric method. Results. We have analysed 54 nests of S. destillatorium. 46 nests were found in “mass nesting places” (in some places several samples were found): in Lviv (3 sites) and Rivne Regions (1 site – Rivne Nature Reserve). The content of granulometric elements was determined in twelve wasp nests from these places and twelve control soil samples were taken around the places of “mass nesting” (three samples of surrounding soil from each location). In order to compare the particle size distribution of elements in all analysed samples (24), we drew cumulative curves and determined coefficients of uniformity and curvature. Conclusions. Nest weighing revealed considerable variations in the mass of the nests – from 10.06 to 222.56 g – depending on the number of cells in a nest. The size of the nests also varied. The number of cells in the nests varied from 2 to 37 (mean = 13; n = 54 nests). As a result of the soil texture analysis of the nest soil material, we determined the percentage of granulometric elements used by the wasps for the construction of their nests. It was found that fine sand was one of the predominant fractions in all twelve nests. The similar content of all five fractions of soil material of wasp nests from different areas indicates that the soil texture of the nests which were built by S. destillatorium probably does not depend on their geographical location.

Understanding sedimentary dynamics and bottom sediment characteristics in Bons Sinais Estuary – Mozambique: Insights from statistical analysis and Pejrup diagram

This article addresses the Bons Sinais Estuary sedimentary dynamics and bottom sediment characterization and its implication to pollution, based on bottom sediment grain size and statistical parameters. There were collected 15 bottom sediment samples with a Van veen sampler, which were further analysed by sieve and pipette methods. Sand was the most dominant textural class (51%), followed by silt (25%) and clay (24%). The sedimentary dynamics have varied from moderate to high. Both size of sediments and Pejrup diagram suggests that the hydrodynamics of this Estuary is high. Although the percentage of coarse sediments is higher, the estuary is susceptible to pollution, as the amount of thinner sediments is considerable regarding the values of skewness. These results may be useful to environmental management actions including pollutants tracking.

Soil depth constraints in the revegetation of reclaimed coal mine land

Abstract. Hartati W, Syahrinudin, Sudarmadji T. 2024. Soil depth constraints in the revegetation of reclaimed coal mine land. Biodiversitas 25: 1838-1845. Plants require adequate root space, nutrients, water, and air for optimal growth. This study analyzed the relationship between plant growth (i.e., diameter) and soil properties (i.e., thickness, organic matter content, texture) on revegetated post-coal mining land in East Kalimantan, Indonesia. Field research was conducted at revegetated area primarily planted with four species (Hibiscus tiliaceus, Enterolobium cyclocarpum, Samanea saman and Acacia sp.) with age of 8 years. Data was collected from 30 plots of 0.05 ha. Plant diameter were recorded and soil samples were taken from 0-10, 10-30, and >30 cm depths using soil auger at three points per plot. Organic matter content was determined by the Walkley-Black method, and texture by the Pipette method. Multiple regression analysis was used to used to investigate the relationship between plant diameter and soil properties. The study found that different species showed varying correlations between soil properties and growth. Acacia sp. and S. saman exhibited strong correlations (r=0.78), while E. cyclocarpum had a low correlation (r=0.35), and H. tiliaceus a moderate one (r=0.49). Soil thickness had a stronger influence on H. tiliaceus (?=0.05) and S. saman (?=0.01) than other tested properties. For some species, diameter growth was primarily determined by soil thickness in the revegetated area. The study highlights the importance of considering species-specific soil requirements for successful revegetation and plant growth on post-coal mining sites.

Development and field evaluation of a novel sugar bait device for controlling residential vector mosquitoes in Zhejiang Province, China.

Mosquito-borne diseases pose serious public health threats in Zhejiang Province, China, and vector control is believed to be the primary method for reducing transmission. Due to severe resistance problems, effective and sustainable methods without chemical insecticides are urgently required to control mosquito vectors. Attractive toxic sugar baits (ATSB) are newly developed methods to control mosquitoes in recent decades with the core element sugar bait, which was invented according to the sugar-feeding behavior of mosquitoes. In this study, we developed a Novel Sugar Bait Device (NSBD) trap by combining sugar bait and physical adhesive capture technology. The study aimed to evaluate the effect of the NSBD trap on controlling mosquitoes in residential environments and to identify the optimal sugar solution concentration in the sugar bait of the NSBD for real use. Four residential villages in Ningbo City with similar geographic environments and mosquito densities were selected for field trials in 2022. One village (site 1) was designated as the control group, and three villages (sites 2-4) served as the test groups to assess the effectiveness of NSBD traps with different sugar solution concentrations (6, 8, and 10%) in the sugar bait. Larval and adult mosquito densities were monitored monthly before and semi-monthly after the trials using the CDC light trap and larval pipette method. Before the trials, we monitored mosquito density for 3 months to confirm the baseline mosquito density among the four sites, and no statistical differences in adult and larval mosquitoes were found (adult, F = 3.047, p > 0.05; larvae, F = 0.436, p > 0.05). After the trials, all NCBD traps effectively controlled larval and adult mosquito densities, with the highest standard decrease rates of larval and adult mosquito densities at 57.80 and 86.31%, respectively, observed in site 4. The most suitable sugar solution concentration in the sugar bait was 10%. NSBD traps effectively controlled mosquitoes in residential environments during field trials. Without the use of insecticides, this may be a promising choice for mosquito vector control to prevent mosquito-borne diseases.

Enhancing clay content estimation through hybrid CatBoost-GP with model class selection

Excessive soil swelling, triggered by variations in moisture content, is recognized as one of the most severe geo-hazards. Swelling Potential (SP) is closely correlated with Clay Content (CC), Plasticity Index (PI), and Activity (A = PI/CC), which are crucial input features for SP prediction models. Traditional methods for determining CC, such as the hydrometer and pipette methods, are labor-intensive and time-consuming. Employing easily accessible soil properties to predict CC directly not only enhances the modeling efficiency of SP prediction models but also mitigates the impact of laboratory test errors on model performance. This study leveraged two databases encompassing a broad spectrum of soil classifications and developed three ensemble learning models (RF, XGBoost, and CatBoost) to predict CC efficiently. Sequential model-based optimization algorithms (SMBO) were employed to effectively identify the optimal hyperparameters for these models. To further refine the model, the Shapley additive explanation (SHAP) method was utilized to ascertain the most influential soil properties. The findings revealed that the CatBoost model, optimized via GP, achieved the highest level of predictive accuracy. Three easily measurable soil properties — the percentage of soil particles passing through 0.075 mm and 0.425 mm sieves, along with the plasticity index — were identified as key predictors for CC. The estimated CC values were instrumental in constructing various empirical and machine learning models to predict SP, all of which exhibited exceptional performance. This research advances the modeling efficiency of SP prediction models, making it particularly relevant for rapid-response scenarios in transportation infrastructure projects.

Field assessment of the operating procedures of a semi-quantitative G6PD Biosensor to improve repeatability of routine testing.

In remote communities, diagnosis of G6PD deficiency is challenging. We assessed the impact of modified test procedures and delayed testing for the point-of-care diagnostic STANDARD G6PD (SDBiosensor, RoK), and evaluated recommended cut-offs. We tested capillary blood from fingerpricks (Standard Method) and a microtainer (BD, USA; Method 1), venous blood from a vacutainer (BD, USA; Method 2), varied sample application methods (Methods 3), and used micropipettes rather than the test's single-use pipette (Method 4). Repeatability was assessed by comparing median differences between paired measurements. All methods were tested 20 times under laboratory conditions on three volunteers. The Standard Method and the method with best repeatability were tested in Indonesia and Nepal. In Indonesia 60 participants were tested in duplicate by both methods, in Nepal 120 participants were tested in duplicate by either method. The adjusted male median (AMM) of the Biosensor Standard Method readings was defined as 100% activity. In Indonesia, the difference between paired readings of the Standard and modified methods was compared to assess the impact of delayed testing. In the pilot study repeatability didn't differ significantly (p = 0.381); Method 3 showed lowest variability. One Nepalese participant had <30% activity, one Indonesian and 10 Nepalese participants had intermediate activity (≥30% to <70% activity). Repeatability didn't differ significantly in Indonesia (Standard: 0.2U/gHb [IQR: 0.1-0.4]; Method 3: 0.3U/gHb [IQR: 0.1-0.5]; p = 0.425) or Nepal (Standard: 0.4U/gHb [IQR: 0.2-0.6]; Method 3: 0.3U/gHb [IQR: 0.1-0.6]; p = 0.330). Median G6PD measurements by Method 3 were 0.4U/gHb (IQR: -0.2 to 0.7, p = 0.005) higher after a 5-hour delay compared to the Standard Method. The definition of 100% activity by the Standard Method matched the manufacturer-recommended cut-off for 70% activity. We couldn't improve repeatability. Delays of up to 5 hours didn't result in a clinically relevant difference in measured G6PD activity. The manufacturer's recommended cut-off for intermediate deficiency is conservative.

Comparative assessment of gravitational sedimentation methods for the evaluation of particle-size distribution in soils

The aim of the study was to carry out a comparative analysis of the results by determining of the particle-size distribution in different soil types by the 1) pipette method and 2) measurement device PARIO, using Integral Suspension Pressure plus method (ISP+). Location and time of the study. The study was performed in the Core Research Facility "Physico-chemical Methods of Soil and Ecosystem Research" and in the Department of Soil Cryology of the Institute of Physical-Chemical and Biological Problems of Soil Science the Russian Academy of Sciences. Methods. The determination of the particle-size distribution in soils was carried out by the pipette method and ISP+. Statistical processing of the analytical data was performed by Microsoft Excel and Statistica 12. Results. The determination of the degree of discrepancy between the results of repeated determinations of the particle-size distribution in soils obtained by the pipette method and ISP+ showed that the coefficients of variation (CV) were different for different fractions. High reproducibility of the results was obtained for the clay fraction. For fractions of the coarse and middle silt, the CV values did not exceed 10-20%. The largest variation in the between repeated measurements using both methods was obtained for the fine silt fraction. The assessment of the average difference and its significance for fine silt and clay fractions by the pipette method and ISP+ showed that there were no significant discrepancies. For the coarse and middle silt, such assessment showed significant differences. Most of the studied soils (14 out of 17) obtained the same classification according to the determinations of the soil particle-size distribution by the compared methods. Conclusions. The use of the PARIO measurement device for determining soil particle-size distribution allows to exclude disturbance of the suspension during the test run, to track the time and depth of sampling and to reduce measurement time significantly. This study showed the importance of taking into consideration the method of soil granulometry assessment, as results may be quite different, especially for the fractions of coarse and medium silt, thus affecting soil taxonomic attribution.

Metrological characteristic of the pipette method (GOST 12536-2014) for determining soil granulometric composition

The aim of the study. To calculate precision indicators (repeatability and reproducibility) and uncertainty in determining the granulometric (grain) composition of soils using the pipette method. Methods. Using the pipette method the content of the following granulometric fractions was determined in soil samples: 0,1–0,05 mm, 0,05–0,01 mm, 0,01–0,005 mm, 0,005–0,002 mm, 0,002–0,001 mm, less than 0,01 mm, less than 0,001 mm. The determination of pH of the salt extract was carried out by potentiometric technique, and organic matter was measured photometrically. For each aliquot of the sample 16 single measurements were obtained for each soil fraction. Based on these data, precision indicators were assessed under conditions of intra-laboratory repeatability and reproducibility, uncertainty indicators were assessed as well. Main results. The following intralaboratory quality indicators were obtained for the method of determining the granulometric (grain) composition of soils using the pipette method: 1) The value of the intralaboratory repeatability indicator of analysis results (σr) ranged 0,4–1,8%. 2) The relative indicator of intralaboratory precision (σR) was within the 0,7–2,9% range. 3) Expanded uncertainty (U) for different soil fractions ranged from 0,9 to 3,9%. Conclusions. The calculated metrological characteristics of determining the granulometric (grain) composition of soils using the pipette method facilitates the internal control of the measurements quality, promoting the quality and confidence in the laboratory work.

Analysis of the Morphology and Lithology of the Kisangani–Yangambi Section of the Congo River in the Democratic Republic of Congo

Vol. 19, Issue 1, 2024: 59–80 DOI: 10.15170/MG.2024.19.01.0459 Mawa Mukulia, Prométhée1 – Katembo Kasekete, Désiré2 – Makabu Kayembe, Gabriel3 – Muhindo Sahani, Walere 4 – Kahindo Muhongya, Jean-Marie5 Analysis of the Morphology and Lithology of the Kisangani–Yangambi Section of the Congo River in the Democratic Republic of Congo 6 ABSTRACT The Congo River, which is between 900 and 300 metres wide between the city of Kisangani and the town of Yangambi, is characterised by important socio-economic and conservation activities but also by a lack of knowledge on morphological and lithological matters. To fill the gaps, the lithology and the morphological dynamics of the riverbed were studied through a description of islands (between 1984 and 2017) and banks thanks to remote sensing and field work, respectively. With regard to the number of islands, the study revealed a loss of 5.13% and a recovery of 28.21% between 1984 and 2017. The direct factors of this dynamism are the erosion and landslides observed both on the banks and on the islands. The geological survey method allowed the collection of 4 samples of sound indurated rocks and 50 samples of loose rocks on the soil profiles of the islands and banks. The macroscopic description and sieving of the samples with 63 mm and 2 mm mesh size allowed the lithology map to be drawn up. The fine soil particles were analysed in the soil laboratory using the Robinson–Köhn pipette method to determine their texture. The USDA textural classification was used. The results of the analysis showed that sand is the predominant rock element in the area. Such a lithology would increase the sensitivity of the banks to mass movements observed here and there along the Kisangani–Yangambi river section.

A new algorithmic approach for predicting the particle size distribution of dispersed soil suspensions using an automated optical settling column

Analyzing a large number of samples for their dispersive properties and particle size distribution (PSD) is often cumbersome and time-consuming, particularly when using traditional hydrometer or pipette-based methods. In this study, we analyzed the efficacy and rapidity of an automated, optical settling column (OSC) to measure the PSD of soils. The OSC provided backscattering and transmission intensity profiles at preprogrammed time intervals that illustrated sedimentation/flocculation processes of suspended particles, making the approach desirable for soil dispersion studies. Settling experiments were performed using 177 soil samples collected from 59 sampling locations across the United States. All soil samples were pretreated with sodium hexametaphosphate (HMP) to achieve maximum dispersion and analyzed with the OSC. The effects of settling run time and sampling frequency were also investigated. The results were compared with separate soil PSD data obtained using the common particle sizing analysis, the pipette method. Using feature engineering and dimensionality reduction, we created different novel methods of modeling the PSD data. Resampling was employed to compare accuracy of these novel methods by generating 300 instances of model performance for each method. We further estimated model generalization using two techniques: (i) a holdout (HO) estimation approach to suggest the “best-case” performance and (ii) an averaged model performance to provide a more conservative performance estimate. The best method studied here provided PSD values that deviated from those gathered through the pipette method by between 2.8% − 3.3% for clay, 5.7% − 9.4% for silt, and 6.5% − 9.6% for sand.

TEKSTUR DAN BAHAN ORGANIK TANAH SERTA HUBUNGANNYA DENGAN BATAS ATTERBERG DAN AKTIVITAS LIAT

Clay minerals are an important indicator of soil plasticity, influencing clay activity. This study aimed to elucidate the effect of clay minerals, organic C and primary minerals on the Atterberg limit and clay activity. The study was conducted in the Kemuning sub-watershed, Jember, East Java. The study began by preparing a thematic map to determine sample points with stratified random sampling. They were taken as many as 35 disturbed soil sample points at 0-20 cm from the surface. Soil texture was determined using the pipette method, and organic C was determined by the spectrophotometer method. The liquid limit and plastic limit were used to determine the plasticity index. A microscopic analysis of sand mineralogy was carried out to compare activity values with a magnification of 20-40 times to assess the primary soil minerals. The results showed that clay and C-organic affect fluidity, plastic limit, and plasticity index. The presence of andesine, albite, olivine, and orthoclase in the sand fraction and the low clay activity indicated that kaolinite dominated the study area, with smaller amounts of illite and halloysite.

A systematic approach to predicting and mapping soil particle size distribution from unknown samples using large mid-infrared spectral libraries covering large-scale heterogeneous areas

Soil spectroscopy has the potential to replace wet chemical methods. However, high prediction accuracy of unknown samples is necessary to confidently map predicted values across large spatial scales. This study developed a systematic approach using MIR spectroscopy to predict soil particle size of 9,009 unknown samples, representing an area of approximately 35,716 km2 in Ireland. A systematic approach for MIR spectroscopy combined with chemometrics was augmented by including spectral control charts to identify unrepresentative spectra in predicting of unknown samples. Moreover, ∼2% of the predicted values (external validation) were selected, covering a wide range of clay, sand and silt, and analysing them using the classical reference method. This step assesses the accuracy of predicted values and provided confidence when projecting predicted values onto soil particle size maps at multiple regional scales.The MIR models were based on the support vector regression algorithm, and were built using a calibration dataset of ∼1,000 mineral and organo-mineral (MOM) soils, i.e., non-peat soils, analysed using the pipette method. The model was used to predict soil particle size from 9009 unknown samples described as MOM soils. Spectral control charts correctly identified 97.59% of the peat soils (3078 out of 3154 samples) as ‘out of control’ samples, which the spectral model should not predict, and about 90% of the MOM soils (5254 out of 5855 samples) were classified as ‘under control’ samples, which the spectra models can predict. The accuracy calculated for the ∼2% of samples selected from the MOM unknown samples (n = 5254) was similar to the accuracy in the internal validation set (n = 280), with R2val values of 0.90, 0.84 and 0.71, RMSEP values of 2.21, 4.31 and 3.91%; RPIQval values of 4.97, 3.71 and 2.30, for clay, sand and silt prediction, respectively. This systematic approach can predict soil attributes using large spectral libraries, providing confidence for building regional and national scale soil maps.

Study of Soil Erodibility in Various Agroforestry Systems Based on Elephant Foot Yam (Amorphophallus oncophyllus) in Bayan District, North Lombok Regency

Bayan District has a wavy to mountainous topography. The type of soil in the area is classified as Inceptisol, so it is very susceptible to erosion. An agroforestry system, with various stands of perennial crops, has been developed in the area, as a conservative measure to support the sustainability of land resources. This study aims to assess the value of soil erodibility in Elephant foot yam-based agroforestry systems in five types of stands, namely: Teak (A1), Cashew (A2), “Gamal” and Banana (A3), Cocoa (A4), and Coffee (A5). The method used is descriptive method with survey technique. Determination of the research location was carried out by purposive sampling with the criteria of land having a rather steep slope (15-17%), the soil order Inceptisol, located in the upper slope, and a high level of stand vegetation homogeneity. Soil samples (undisturbed and disturbed) were collected using the diagonal method on 10 x 10 m plots randomly placed in each agroforestry system with a depth of 0-20 cm. Parameters observed were soil texture (pipette method), soil permeability (constant head), soil structure (qualitative in the field), and soil organic matter (Walkley and Black). The result showed that the value of soil erodibility, in agroforestry systems with different stands, was significantly difference, with the lowest value was found in the Coffee agroforestry system (A5) of 0,416 and the highest was found in the Cashew system (A2) of 0,661. The effectiveness of improvement soil erodibility in the agroforestry system of A5 was 37% better than A2.

ГРАНУЛОМЕТРИЧЕСКИЙ СОСТАВ КАК ВАЖНЫЙ ЭКОЛОГИЧЕСКИЙ ПОКАЗАТЕЛЬ ПЛОДОРОДИЯ ПОЧВ БАГАЕВСКОГО РАЙОНА

Purpose: to study the effect of granulometric texture on soil fertility, especially on the humus content and its structural state in the soils of Bagaevsky district Rostov region. Materials and methods. The studies were carried out on the soils of Bagaevsky district Rostov region. Samples were taken from the main genetic soil horizons. The granulometric texture was determined by the pipette method according to N. A. Kachinsky, and the soil structure was determined according to N. I. Savinov or granulometric (grain). Statistical data processing was carried out according to B. A. Dospekhov using the Microsoft Excel software product. Results. The main soil of Bagaevsky district is chernozems, they occupy about 64 % of the total land area of the district, chestnut soils occupy more than 26 % of the total area of the district, and floodplain soils occupy more than 7 %. The relationship with an approximation coefficient R² = 0.51 was revealed between the content of the fraction of physical clay and humus in the studied soils. Our studies of humus amount in the soils of Bagaevsky district showed that they are characterized by a very low and low content. In the studied soils, a close relationship between the structural state and the content of physical clay was determined (R² = 0.83). An analysis of soil humus status shows that the balance of organic matter is unfavorable for the prevailing part of arable land. An analysis of the research results by some authors shows that for the period from 1960 to 2021, the decrease in the humus content in arable soils of Bagaevsky district was 0.7 %. For its deficit-free balance, it is necessary to apply up to 6 t/ha of organic fertilizers. Conclusions. Our studies, combined with data analyses of studies conducted in Rostov region by a number of authors, made it possible to identify a significant effect of granulometric texture on the humus content and, as a consequence, soil fertility in general.

Deep learning based multi-labelled soil classification and empirical estimation toward sustainable agriculture

Agriculture is the underlying occupation of the vast people in India and it is a major economic contribution. Soil is prime for the vital nutrient supply to the crops and its yield. Determination of the type of soil which comprises of the clay, sand and silt particles in the respective proportion is indeed significant for the suitable crop selection and to identify the weeds growth. The most commonly utilized soil determination methods were International Pipette method and Pressure-plate apparatus method. In this research work, multiclass soil classification using machine learning and deep learning models for the appropriate determination of the soil type as Multi-Stacking ensemble model and a novel feature selection algorithm Q-HOG is proposed; since the Artificial Intelligence has led to furtherance in the smart agriculture. Besides, the images are collected from the exploration site vriddhachalam along with the soil datasets will increase the classification accuracy. The deep learning models Recurrent Neural Network(RNN), Long Short Term Memory(LSTM), Gated Recurrent Unit(GRU) and VGG16 are considered and the comprehensive evaluation of these different deep learning architectures and also the machine learning algorithms such as Naïve-bayes, KNN, SVM are carried out and the obtained results are tabulated. Multi-stacking ensemble model for multi-classification is proposed with the Machine learning and deep learning algorithms and evaluated the performance with increased computation time. Among these models the proposed model outperformed in soil classification in-terms of accuracy as 98.96 percent, achieved precision as 96.14 percent, recall as 99.65 percent and the achieved F1-Score is 97.87 percent.

Smartphone assisting convolutional neural networks for soil texture classification in dry and wet humid conditions in West Guwahati, Assam

Soil texture using a hydrometer or pipette method requires expertise, although these are accurate. A soil expert may help the farmer to detect the soil texture by analyzing the visual texture of the soil, which is not always accurate. This paper presents the smartphone image-based sand and clay soil classification in wet and dry humid conditions using Self Convolution Neural Network (SCNN) and finetuned MobileNet.A soil dataset of 576 soil images was prepared using a low-cost smartphone under natural light conditions. Different augmentation techniques such as shift, range, rotation, and zoom were applied to the soil dataset to increase the number of images in the soil dataset. The best performance of the MobileNet was reported at epoch 15 with a testing and training loss of 0.0091 and 0.0194, respectively. Though the SCNN model performed best at epoch 10 with a testing accuracy of 99.85%, the MobileNet reported less computation time (167.8s) than the SCNN (273.2s). The precision and recall of the models were 99.62 (MobileNet) and 99.84 (SCNN). The accuracy of the SCNN reported itself as the best model, whereas the computing time of the MobileNet reported itself as the best model in different humid conditions. The model can be used to replicate the traditional soil texture analysis method and the farmers can use it for better productivity.

Influence of Robinia pseudoacacia L. and Quercus robur L. artificial forest plantations on the particle-size distribution of calcic chernozem

The particle-size distribution is one of the most important characteristics of soils, which determines most of their properties and features of the main regimes. Artificial forest plantations in the steppe act as a powerful environment-transforming factor, which over time is capable of changing even quite conservative properties of soils, including their particle-size distribution. The study of the influence of forest plantations on the particle-size distribution was carried out using soil samples taken from calcic chernozem, chernozem under the plantation of R. pseudoacacia L. and under the plantation of Q. robur L. The determination of the particle-size distribution was carried out by the pipette method, with the preparation of the sample by trituration with a solution of sodium pyrophosphate. The classification of granulometric fractions is given according to N. A. Kaczynskii. The analysis of the characteristics of the ratio of particle-size distribution of the studied chernozems revealed that the zonal chernozem is characterized by an increased content of the sand fraction and a reduced content of the silt fraction in the H1 and H2 horizons compared to the lower horizons. The calcic chernozem under the plantation of R. pseudoacacia L. is characterized by a relatively uniform distribution of the content of sand, dust and silt fractions along the soil profile. In calcic chernozem under the plantation of Q. robur L., the maximum content of the sand fraction was found in the surface horizon, with a gradual decrease in the content of this fraction with depth, while the content of dust and silt fractions increased with depth. The growth of R. pseudoacacia L. and Q. robur L. plantations on calcic chernozems leads to an increase in the content of sand fractions and a decrease in dust and physical clay fractions. There is also a certain change in the profile distribution of fractions, especially sand, under the influence of the growth of forest plantations. Each of the investigated calcic chernozems is characterized by a specific ratio of «sand : dust : silt» fractions, which indicates a different genesis of granulometric fractions.

PECULIARITIES OF EPIZOOTOLOGY OF MULLERIOSIS OF SHEEP AND GOATS IN THE REPUBLIC OF BELARUS AND IMPROVEMENT OF ITS DIAGNOSTICS METHODS

The data on the infection of animals with muelleriosis and pathogens of other parasitoses of the respiratory and digestive systems in sheep and goat farms of the Republic of Belarus have been established. The larvamigration (pipette) method for detecting the larvae of Muellerius capillaris, which is superior in efficiency to the existing meth-ods, has been developed.