Soil Taxonomy Classification Research Articles

Characteristics and classification of the peat at Toba Highland, North Sumatera, Indonesia

Peatland serves as a crucial natural resource with hydrological and other environmental functions essential for all living organisms. In some regions, peat soil isn't limited to lowland areas, it is also found in highland areas. This study is a survey research aiming to examine the characteristics of the highland peatlands of Toba North Sumatera, namely in the Village of Matiti II, Humbang Hasundutan Regency, North Sumatera and lowland peatlands as control of peatlands in general in Sidomulyo Village, Bilah Hilir Subdistrict, Labuhan Batu. The study employed a survey research approach with a descriptive method to determine the differences in the characteristics of highland Toba peat soils. In each area, a representative profile was made, and the soil morphology, characteristics and classification were observed according to the 2014 soil taxonomic classification. Soil samples were taken from each layer in the soil profile for soil analysis in the laboratory. Soil analysis included bulk density, pH H₂O, pH NaF, CEC, base saturation, organic C, total N, C/N, electrical conductivity (EC) and ash content. The results showed that the difference in altitude directly affected the microclimate and the hydrologic conditions, which in turn affected the characteristics of the peat soil. In the context of the Toba highland, the main source of peat soils comes from rainfall. In contrast with the peatland of the lowlands, where the impact of tides is a significant factor, the peat of the Toba highland is affected by the surrounding hills.

Taxonomical Classification of soils of Asvaru Sub-watershed, Hunsur Taluk, Mysuru District

Soil characterization and classification is crucial to all soil studies, as it is an important tool for understanding the nature of soil along with successful transfer of research results from one study area to another. The proper understanding of the nature and properties of soil and their management based on their potential and problems is important for increasing crop production to the optimum level. For understanding the problems and potentials, detailed soil survey plays an important role which provides adequate information in terms of land form, slope, land use as well as characteristics of soils (viz., texture, depth, structure, stoniness, drainage, acidity, salinity etc.) which can be utilized for the planning and development. The purpose of the study is to classify the soils of Asavru sub-watershed in Mysuru district to categorize the soils into different soil order upto family level of Soil taxonomy Classification and enhance the productivity and profitability of the area. The detailed soil survey was carried out in Asvaru sub-watershed. Seventy two profiles were studied for its different morphology, physical and chemical properties. The subwatershed area was grouped into 75 mapping units consisting of 16 soil series. The soils were shallow to very deep with texture varying from sandy loam to sandy clay. The structure was sub-angular blocky in all profiles with friable consistency. Soil reaction varied from moderately acidic to moderately alkaline and non saline in +2 + + + nature. Exchangeable cations followed the pattern of Ca >Mg >Na >K . The soil series identified in the sub-watershed area were classified under different soil orders (Alfisols and Inceptisols) upto family level according to revision of Soil Taxonomy. Major proportion of the soils of the sub-watershed belonged to Alfisols (Pedons1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12 and 15) and Inceptisols (Pedon5, 13 and 16).

Semi-Detail Soil Survey and Land Suitability Evaluation for Sugarcane Production at Tungan Ahmadu District, Koko-Besse LGA Kebbi State Nigeria

A semi-detailed soil survey and land suitability evaluation for sugarcane production was conducted at Tungan Ahmadu Koko-Besse LGA, of Kebbi State Nigeria to obtain comprehensive soil data for characterization and classification. The aim was to generate detailed information on the properties, genesis, land characteristics, and classification of soils for their suitability for sugarcane production. The study was carried out in a 4,000ha land area. An interval of 250x250m was used for augering and surface sampling of the soils at a scale of 1:25.000. In each soil mapping unit that was identified a soil profile pit was dug, described and soils sampled in each horizon from bottom-up, to minimize contamination by falling debris and was analyzed in the laboratory. Each soil profile pit was dug to a standard size (200 cm long, 100 cm wide, and a maximum depth of 200 cm or until an impenetrable layer or water table was encountered. Each pit was described regarding its full range of morphological characteristics according to International Standard these include soil depth, horizon thickness, the color of matrix and mottles, texture, structure, consistency, porosity, included materials, roots, and horizon boundary. In addition, records of vegetation/land use, slope, depth to the water table, and internal drainage status was obtained for each profile. Measured variables in the data set were analyzed using descriptive statistics such as means and weighted average. Seven soil mapping units tagged TGA1, TGA2, TGA3, TGA4, TGA5, TGA6, and TGA7 were identified based on landforms and soil properties. The soils are slightly acidic (6.30) to moderately acidic (5.60) had low total nitrogen, organic carbon, and CEC hence low fertility. The soils in the study area are moderately deep, poorly drained, and generally loamy sand to sandy in texture. Based on the USDA Soil Taxonomy classification system, three soil units were identified as TGA1, TGA4, TGA5 and TGA6 (Haplustepts), TGA2 and TGA7 (Haplustalfs), and TGA3 (Terriorthents) which correlate according to the World Reference Base (WRB) as Luvisols, Arenosols, and Fluvisols respectively. Analyses on climate, topography, physical soil properties, wetness and fertility suitability at the research site returned results of TGA2, TGA3, TGA4, TGA5 and TGA6, moderately suitable (S2) while TGA1 and TGA7 are marginally suitable (S3) with limited factors of physical and chemical properties.

Soil Survey and Land Suitability Evaluation for Sugar Cane Production at Zagga District, Bagudo Local Government Area, Kebbi State, Nigeria

Semi-detail soil survey and land suitability evaluation for sugarcane production was carried out in Zagga, Bagudo LGA of Kebbi State Nigeria at scale of 1:25,000 on 8,000 ha of land. The objectives were to describe the morphological and chemical properties of the soils. The entire study area was classified in to five soil units named as ZG1, ZG2, ZG3, ZG4, and ZG5. Surface soil samples were examined and collected from 0-15cm, 15-30cm depth using soil auger at 200x200m interval. Five soil profile pits were dug, described and soils sampled from bottom up, to minimized contamination by falling debris. Each soil profile pit was described based on horizon thickness, depth, colour of matrix and mottles, consistency, included materials, roots, horizon boundary, vegetation/ land use, slope, depth to water table and drainage status. The soils are slightly acidic (6.30) to moderately acidic (5.60). The total nitrogen, organic carbon, available phosphorus, and basic cations (Ca, Mg, K, Na) were low to moderately low according to guidelines for nutrient rating and interpretation for Nigerian soils. The soils were moderately drained. According to USDA soil taxonomy classification the soils of ZG 1 and ZG 2 were classified as Dystrustepts while ZG 3, ZG 4 and ZG 5 were classified as Haplustepts and correlated with World Reference Based System as Arenosols and Luvisols. ZG1 and ZG2 were named as moderately suitable (S2) while ZG3, ZG4 and ZG5 were marginally suitable (S3) according to the guidelines of land suitability evaluation for sugarcane production.

Tropical soil order and suborder prediction combining optical and X-ray approaches

Proper soil taxonomic classification makes a significant contribution toward sustainable soil management, decision making, and soil conservation. For that, a quick, environmentally-friendly, non-invasive, cost-effective and reliable method for soil class assessment is desirable. As such, this study used NixPro color and portable X-ray fluorescence (pXRF) data to characterize seven different soil orders in Brazilian tropical soils, exploring the ability of three machine learning algorithms [Support Vector Machine with Linear Kernel (SVMLK), Artificial Neural Network (ANN), and Random Forest (RF)] with and without Principal Component Analysis (PCA) pretreatment for prediction of different soils at the order and suborder taxonomic levels under both dry and moist conditions. In total, 734 soil samples were collected from surface and subsurface horizons encompassing twelve suborders. The soil profiles were morphologically described and taxonomy classified per the Brazilian Soil Classification System and the approximate correspondence was made with the US Soil Taxonomy. Soil samples were separated into modeling (70%) and validation (30%) sub-datasets, overall accuracy and Cohen's Kappa coefficient evaluated model quality. Models generated from B horizon sample with pXRF and NixPro (moist samples) data combined delivered the best accuracy for order (81.19% overall accuracy and 0.71 Kappa index) and suborder predictions (74.35% overall accuracy and 0.65 Kappa index) through RF algorithm without PCA pretreatment. Summarily, the use of these two portable sensor systems was shown effective at accurately predicting different soil orders and suborders in tropical soils. Future works should extend the results of this study to temperate regions to corroborate the conclusions presented herein.

Building geochemically based quantitative analogies from soil classification systems using different compositional datasets.

Soil heterogeneity is a major contributor to the uncertainty in near-surface biogeochemical modeling. We sought to overcome this limitation by exploring the development of a new classification analogy concept for transcribing the largely qualitative criteria in the pedomorphologically based, soil taxonomic classification systems to quantitative physicochemical descriptions. We collected soil horizons classified under the Alfisols taxonomic Order in the U.S. National Resource Conservation Service (NRCS) soil classification system and quantified their properties via physical and chemical characterizations. Using multivariate statistical modeling modified for compositional data analysis (CoDA), we developed quantitative analogies by partitioning the characterization data up into three different compositions: Water-extracted (WE), Mehlich-III extracted (ME), and particle-size distribution (PSD) compositions. Afterwards, statistical tests were performed to determine the level of discrimination at different taxonomic and location-specific designations. The analogies showed different abilities to discriminate among the samples. Overall, analogies made up from the WE composition more accurately classified the samples than the other compositions, particularly at the Great Group and thermal regime designations. This work points to the potential to quantitatively discriminate taxonomically different soil types characterized by varying compositional datasets.

Determination of base saturation percentage in agricultural soils via portable X-ray fluorescence spectrometer

Soil base saturation percentage (BSP) plays an important role in the assessment of soil taxonomic classification and soil fertility. Conventionally, soil BSP measurement methods are fraught with many drawbacks such as being laborious, time consumptive, destructive to the samples, and can lead to the underestimation of true cation exchange capacity (CEC). Recently, proximal sensors such as portable X-ray fluorescence (PXRF) spectrometry have proven to be effective for rapid physicochemical analysis of soils. In this study, we proposed and examined a PXRF-based method to predict BSP using 300 soil samples from the active agricultural lands in six states across the USA; Colorado, California, Minnesota, Nebraska, Oklahoma, and Texas. An Olympus Vanta series PXRF analyzer was employed to measure Mg, Ca, and K for BSP prediction. Results were validated using four different multivariate models [generalized additive model (GAM), multiple linear regression (MLR), random forest (RF), regression tree (RT)] via R 3.5.1. Predictive model performance was assessed via root mean squared error (RMSE), coefficient of determination (R2), residual prediction deviation (RPD), the ratio of performance to interquartile (RPIQ) range, and bias. While predicting BSP from PXRF quantified elements, models exhibited R2, RMSE (%), and RPDs as follows: GAM = 0.58, 9.0, 1.6; MLR = 0.45, 10.4, 1.4; RF = 0.62, 8.7, 1.6; RT = 0.68, 7.9, 1.8, respectively. Soil cation exchange capacity was also predicted using a similar approach, with similar and moderate predictive performance; GAM produced R2, RMSE (cmolc kg−1), and RPD of 0.69, 5.6, 1.8, respectively, relative to laboratory data. This study showed that the PXRF elements can be used to predict BSP with fair accuracy for the range of agricultural soils examined. As such, further study and enhancement of the approach outlined herein on a wider array of soils is warranted.

Chemical weathering indices applied to soils developed on old lake sediments in a semi-arid region of Turkey

Climate is a major influence on weathering processes affecting soil parent materials. Important contributors to soil formation in arid and semi-arid climatic zones are the diurnal cycles of solar heating and cooling that cause mechanical or physical disintegration of rock or parent materials, and wind-blown sands that score and abrade exposed rock surfaces. By using the Soil Taxonomy classification system, the initial aim of this study was to carry out a pedological evaluation for four soil profiles, classified as Xeric Haplocalcid and Xeric Haplocambid, formed on different parent materials (limestone, marl and old alluvial deposits) under the same conditions, including topography and vegetation, in a semiarid region. The second stage was the exploration of the similarities and differences in the classifications resulting from either the pedogenic processes, or from other factors, by determining the degree of soil weathering using geochemical data. To achieve this, soil samples were collected from the horizons to investigate their mineralogical, geochemical and physiochemical properties. The study also considered other features, such as the pedogenic evolution of soils, through the use of weathering indices, namely the Chemical Index of Alteration (CIA), Chemical Index of Weathering (CIW), Base/R2O3 Ratio, Weathering Index of Parker (WIP) and Plagioclase Index of Alteration (PIA). The results clearly showed that soil development at the Altınova State Farm at Konya in the Central Anatolia region of Turkey is due to slow pr ogressive weathering. For this case, the main indicators are secondary calcium carbonate illuviation and weak structural development with a weathering ratio of silicon to aluminium greater than two in all profiles.

Soil classification of humid Western Ethiopia: A transect study along a toposequence in Didessa watershed

Little has been studied on genesis and properties of soils in Western Ethiopia. This study was conducted to understand the pedogenesis, and to classify benchmark soils in Didessa watershed along a toposequence. The six soil profiles are representative of low, mid and highland positions within an elevation range from 1273 to 2700m above sea level along a 53-km long transect. Their pedological processes, soil properties and classification are discussed in context of soil forming factors and sustainable soil use. Melanization, cheluviation (chelation) of organo-mineral substances, oxidation of iron and leaching of iron compounds and basic cations, clay translocation, de-alkalization, and acidification were major pedological processes at the upland soils while erosion took place at shoulder positions. Calcification and pedoturbation (vertization) were major pedological processes in the lowland and melanization was also observed there. The surface horizons of these very deep soils had loam a loamy texture while the subsurface horizons were clayey. Leaching of basic cations increased with elevation. The U.S. Soil Taxonomy classification identified a soil sequence consisting of Typic Hapludults, Typic Ferrudalfs, Typic Rhodudalfs and Typic Hapluderts while the World Reference Base classified the corresponding soils as Ferric Rhodic Alisols, Ferric Rhodic Luvisols, Ferric Chromic Luvisols, and Calcic Pellic Vertisols. Numerical hierarchical cluster analysis identified similar and dissimilar horizons in the soil catena. Ultisols were developed on tertiary basalt at midland, Alfisols were developed on tertiary basalts and granitic gneisses at midland and highland, and Vertisols were developed on alluvium and colluvium at lowland. The relief characteristics, lithologic units, agro-ecology and land use covered by the current study are typical of much of the Western and Southwestern Ethiopia. The study indicated that Didessa toposequence has three soil orders (reference groups) that need different management requirements for sustainable soil use. Thus, the transect serves as a model of soil development and soil management in humid Western Ethiopia.

Assessment of the impact of forest harvesting operations on the physical parameters and microbiological components on a Mediterranean sandy soil in an Italian stone pine stand

Forest harvesting operations may have a significant impact on soil physical properties by reducing its porosity and organic functions. Soil variations, in particular bulk density and total porosity, caused by external perturbations as soil becomes compacted due to machinery passes, can lead to changes in biogeochemical cycles that have consequences on soil ecosystems. This study investigated how the impact of forest operations and the elapsed time from harvest can influence: (1) the physical–chemical characteristics of soil and (2) the nitrogen-fixing and nitrifying microbial communities. The study area is located inside the Regional Park of Migliarino, San Rossore, Massaciuccoli (Pisa, Italy). In the study area, the soil has been classified as recent sands with sandy loam texture and slightly calcareous (USDA Soil Taxonomy classification). Soil samples were collected in patchy cut areas (strip cut) of Pinus pinea stand that was harvested in two steps: half area in 2006 and the rest in 2011. Soil samples were collected also in a control area (not harvested) with similar stand and soil characteristics. Statistical analysis was preceded by a test of normality (Kolmogorov–Smirnov test) and a variance homogeneity test (Levene’s test). Considering the dependence of the variables studied (physical and chemical soil characteristics), a MANOVA test and a post hoc Tukey HSD test were applied to determine statistical difference among the three treatments: harvested 2006, harvested 2011 and not harvested. The results did not indicate significant variations to the parameters of shear and penetration resistance, though soil bulk density and total porosity were significantly altered in the short period since forestry operations occurred. These physical changes induced qualitative (presence/absence and number of species) and quantitative (abundance and spatial evenness of the species) variations in the nitrogen-fixing and nitrifying microbial communities.

Soil taxonomy and distribution characteristics of the permafrost region in the Qinghai-Tibet Plateau, China

Understanding the soil taxonomy and distribution characteristics of the permafrost region in the Qinghai-Tibet Plateau (QTP) is very important. On the basis of extensive field surveys and experimental analysis, this study carries out soil taxonomic classification of the permafrost region in the QTP. According to Chinese Soil Taxonomy, the soil of the permafrost region in the QTP can be divided into 6 Orders (Histosols, Aridosols, Gleyosols, Isohumosols, Cambosols, Primosols), 11 Suborders, 19 Groups and 24 Subgroups. Cambosols are the dominant soil type in the permafrost region, followed by Aridosols. From the east to the west of the permafrost region in the QTP, the soil type gradually changes from Cambosols to Aridosols, showing a meridional zonality. The eastern region is dominated by Cambosols, with no obvious latitudinal zonality. From the south to the northwest of the western region, the dominance of Aridosols and Cambosols gradually transited to Aridosols, presenting a latitudinal zonality. The soil in the western region shows a poor vertical zonality, while the distribution of suborders of Cambosols in the eastern region shows a more obvious vertical zonality. The result indicates that precipitation and vegetation are the main factors that influence the zonal distribution of soil. The permafrost in the east has some effect on the vertical soil zonality, but the effect is weakened in the west.

Ethnopedology and soil properties in bamboo (Bambusa sp.) based agroforestry system in North East India

Bamboo (Bambusa cacharensis) stands are dominant ecosystems in the North East region of India, and have been intricately linked with the livelihood of the rural population for millennia. Therefore, indigenous people have classified soils under bamboos on the basis of their physical appearance for sustainable management of bamboo ecosystems. These traditional systems are still being practiced by the farmers' in the region. This article describes the available information on the system used by indigenous people for bamboo-based agroforestry systems in the Barak Valley, North East India. It also presents analytical data of different soils for their physico-chemical characteristics in relation to soil depth and the clump age. The objective of this study is to integrate farmer-led suitability assessment with that of scientific interpretation of the analytical data. The data presented indicate four basic soil (mati) types: kalo (black soil), lal (red soil), pathal (stony soil) and balu (sandy soil), of which, lal mati soil was the most predominant soil type (40%) in bamboo-based agroforestry system. Increasing clump age was positively correlated with the soil fertility for 0–10cm, 10–20cm and 20–30cm depth, respectively: soil organic carbon (R2=0.95*, 0.94*, 0.91*), total N (R2=0.95*, 0.88*, 0.69**), available P (R2=0.94*, 0.77**, 0.90*) and exchangeable K+ (R2=0.91*, 0.79*, 0.61**), suggesting significant impact of bamboo in improving soil fertility through profuse root system and onsite nutrient conservation (*significant at 0.001; **significant at 0.005). The data on scientific analyses are consistent with the traditional soil taxonomy classification used by the farmers. Soil carbon stock (26–35MgCha−1) and sequestration rate (0.28–0.59MgCha−1year−1) to 30cm soil depth of bamboo agroforestry suggest its potential role in soil carbon sink management.

The Study on Soil Classification in Sri Lanka

Land information is important for the international agricultural companies. This study investigated the agriculture and soil information in Sri Lanka. This study is the results from investigation of soil properties and agricultural properties determined by the Soil Taxonomy classification system for the soils in Sri Lanka. The order of the main agricultural imports in Sri Lanka was wheat > refined Sugar > dry Onion > Rice > Lentils. The climate of Sri Lanka is divided into three climatic zones. There are a wet zone, an intermediate zone, and a dry zone. Rainfall of the wet zone was <TEX>$3,000-5,000mm\;year^{-1}$</TEX>. The rainfall of the dry zone was less than <TEX>$1,000m^{-1}$</TEX>. The intermediate zone was in the middle area. Soil series of Sri Lanka were 109 in total. Detailed information of soil series was: 6 of soil Orders, 15 of Suborders, 39 of Great groups, and 56 of Subgroups. Soil texture of topsoil was much more coarse, but subsoil was gravelly coarse soil. Soil of Sri Lanka was classified as a Soil Order. The orders were Entisols > Alfisols > Ultisols > Inceptisols > Histosols > Vertisols.

Agronomic Evaluation of Dry Bean Genotypes for Potassium Use Efficiency

Dry bean is an important legume worldwide, and potassium (K) deficiency is one of the important constraints for bean production in most of the bean growing regions. A greenhouse experiment was conducted with the objective to evaluate fifteen dry bean genotypes grown on a Brazilian lowland (Inceptisol) United States Soil Taxonomy classification and Gley humic Brazilian Soil Classification system), locally known as “Varzea” soil. The K rate used was 0 mg kg−1 (low, natural soil level) and 200 mg kg−1 (high, applied as fertilizer). Straw yield, seed yield, pods per plant, seeds per pod, 100 seed weight, and seed harvest index were significantly increased with the addition of K fertilizer. These traits were also significantly influenced by genotypic treatment. Similarly, root length and root dry weight were also influenced significantly by K and genotype treatments. The K X genotype interactions for most of these traits were also significant, indicating variation in these traits with the variation in K level. Based on seed yield efficiency index (SYEI), genotypes were classified as efficient, moderately efficient, and inefficient in K use efficiency. Maximum grain yield was obtained with 74 mg K kg−1 extracted by Mehlich 1 extracting solution. Similarly, K saturation required for maximum grain yield was 1.1%.

Lowland Rice Genotypes Evaluation for Nitrogen Use Efficiency

Rice is important crop for world population, including Brazil. Nitrogen (N) is one of the most yield limiting nutrients in rice production under all agro-ecological conditions. A greenhouse experiment was conducted to evaluate N responses to 12 lowland rice genotypes. Soil used in the experiment was a Gley humic according to Brazilian soil classification system and Inceptisol according to USA soil taxonomy classification. The N rates used were 0 mg kg−1 (low) and 300 mg kg−1 (high) of soil. Plant height, straw yield, grain yield, panicle density, 1000 grain weight, and root dry weight were significantly increased with the addition of N fertilization. These growth, yield, and yield components were also significantly influenced by genotype treatment. Grain yield had significant linear or quadratic association with shoot dry weight, panicle number and 1000 grain weight Based on grain efficiency index genotypes were classified as efficient, moderately efficient and inefficient in N use. The N efficient genotypes were ‘BRS Tropical’, ‘BRS Jaçanã’, ‘BRA 02654’, ‘BRA 051077’, ‘BRA 051083’, ‘BRA 051108’, ‘BRA 051130’ and ‘BRA 051250’. Remaining genotypes fall into moderately efficient group. None of the genotypes were grouped as inefficient in N use efficiency.

Soil texture analyses using a hydrometer: modification of the Bouyoucos method

A.N. Beretta, A.V. Silbermann, L. Paladino, D. Torres, D. Bassahun, R. Musselli, and A. Garcia-Lamohte. 2014. Soil texture analyses by hydrometer: modifications of the Bouyoucos method. Cien. Inv. Agr. 41(2): 263-271. The Robinson pipette method (Pipette) is accurate and precise but time consuming. Bouyoucos (1936) proposed a more rapid and simpler procedure called the hydrometer method. Both analytical techniques are sedimentation procedures accepted as standard techniques for particle-size analysis. The sand, silt, and clay contents of several soil samples were determined using the Pipette method as a control and compared with the Bouyoucus, the Bouyoucos Modified (Bouyoucos_M) and the Bouyoucos Modified with gravimetric determination of the sand content (Bouyoucos_M-T) methods. Data obtained from these procedures was used to assess soil textural class, the soil erodibility coefficient (K), the water retained at field capacity (FC) and the permanent wilting point (PWP). In the Bouyoucos_M method, the soil organic matter (SOM) was destroyed and the dispersingagent concentration was increased. In the Bouyoucos_M-T method, the sand was quantified gravimetrically by sieving samples through a 53 µm mesh. The hydrometer and Pipette methods measurements correlated well. The Bouyoucos and the Bouyoucus-M methods overestimated the sand content. The performance of the Bouyoucos_M-T method did not differ from that of the Pipette method. Compared with the Pipette method, the Bouyoucus method underestimated the clay content, and the Bouyoucos_M method did not differ from the Pipette method. The values obtained with the Bouyoucos_M and the Bouyoucos methods underestimated the FC and the PWP, and Bouyoucos_M-T method did not differ from estimations based on the Pipette method data. The assessed K value was underestimated with the Bouyoucos_M method. The Bouyoucos and the Bouyoucos_M-T methods estimated the K values similar to the Pipette method. The Bouyucus_M-T method is suitable for determining the soil texture and inferring soil properties but is unacceptable for assessing the class texture for soil taxonomic classification.

Determining soil moisture regimes for viticultural zoning purposes

This paper aims to analyse the suitability of Soil Taxonomy to characterize the soil moisture regime for viticultural zoning studies, comparing the soil moisture parameters used in the Soil Taxonomy classification with soil moisture parameters relevant to the grapevine phenological stages. The results show that Soil Taxonomy does not adequately reflect the variability of soil moisture dynamics during vineyard growing. Then, a proposal for soil moisture regime classification is realised by means of a cluster analysis. This classification is based on determining dry days, as indicated by Soil Taxonomy, in different vine phenological periods, and grouping the cases according to their variability. The soil moisture regime classes, resulting from cluster analysis, show significant differences in soil moisture status in all phenological periods, and therefore present different implications for viticulture, related to potential for vegetative growth, grape production and the grape ripening process.

Ensemble Approach to Provide Uncertainty Estimates of Soil Bulk Density

Large scale environmental impact studies typically involve the use of simulation models and require a variety of inputs, some of which may need to be estimated in absence of adequate measured data. An important input, soil bulk density (Db) affects conditions for soil aeration, solute transport, and storage as well as the outcome of soil C stock calculations. Correct representation of Db in simulation studies is essential since any bias or uncertainty will propagate through a variety of processes and time steps. We used the U.S.‐wide NRCS National Soil Survey Characterization (NSSC) database of point measurements and the ‘k‐nearest neighbor’ (k‐NN) pattern recognition algorithm combined with random resampling without replacement to estimate Db and its uncertainty. Soil particle‐size distribution and organic C content were utilized as inputs and soil taxonomy classification, sample depth, and soil horizon notation were tested as optional grouping and limiting factors to the calibration (reference) data. We obtained an overall root‐mean‐squared error (RMSE) of 0.17 g cm−3 and mean error (ME) of 0.01 g cm−3 Grouping samples by taxonomic classification proved to be advantageous, while limiting samples by depth helped avoid depth‐specific bias in the estimations. Grouping samples by horizon notation did not yield significant improvement due to the great variability of bulk density within horizons of the same notation. Varying the proportion of data used in the resampled data subsets can be used to establish greater or lesser degree of confidence in mean estimates without affecting those mean estimates. Simulation based environmental impact and risk assessment studies can be direct beneficiaries of data with characterized uncertainty.

Micromorphological features of diagnostic horizons in several soils in southwest China: Implication for soil taxonomic classification

The comparative studies on micromorphological features in diagnostic horizons of Stagnic Anthrosols, Ustic Ferrosols and Ustic Vertosols in southwestern China were conducted to underpin the rationale for Chinese Soil Taxonomy. The following findings were explored: (1) Stagnic Anthrosols had the specific micromorphological features, e.g., the humic formation in anthrostagnic epipedon, the platy structures in plow subhorizon, the secondary formation of ferromanganese and the weakly optical-orientation clay domains in hydragric horizon, etc.: (2) The groundmasses of ferric horizon in Ustic Ferrosols appeared in hue of 2.5YR or redder, and had pellicular grain structure; (3) Ustic Vertosols had a crust horizon (Acr), and crack structure dominated in Acr and angular blocky structure in disturbed horizon; (4) Because of the distinct differences in micromorphological features among these three soils, the specific micromorphological features might be employed as diagnostic horizons to differentiate soils while the quantifiable micromorphological features might potentially be selected as diagnostic indices for Chinese soil taxonomic classification.

Designation of local varieties in the Hungarian soil classification system: Remarks from a viewpoint of land evaluation application

This paper examines the information transfer of soil taxonomic classification units of the Hungarian soil classification from the viewpoint of land productivity evaluation applications. For this purpose statistical analyses of a national soil and plant production database (with 80000 entries) have been applied.