Soil Management Zones Research Articles

Soil Management Zone Determination by Yield Stability Analysis and Classification

Multiyear yield data may lead to more accurate determination of yield–soil relationships. This study was conducted to determine if stable yield classification zones could be found, if soil and/or topographical properties differed among yield classifications, and if soil and/or topographical properties could be used to classify field locations into yield classes. Soybean (Glycine max L.) yields over 4 yr in three fields were classified into four zones: consistent‐high, consistent‐average, consistent‐low, and inconsistent. Soil samples from all zones except the inconsistent zone were analyzed for pH, extractable nutrients, total C and N, texture, and elevation. Slope, plan curvature, and profile curvature at each sampling point were determined from elevation. Although differences existed, there were no consistently different soil or topographical properties among yield classes in each of the three fields. Linear discriminant analysis found unique yield‐affecting factors in each field. In the North field, sand, K, and pH influenced yield classification. In the South field, clay, sand, slope, Mg, and plan curvature predicted yield classification. In the East field, pH and clay significantly influenced yield classification. For individual yield classes, the derived functions classified sampling locations into appropriate yield classes 60 to 100% of the time. The most accurate prediction rate came when classifying the soil sampling points into the high yield zone in the East field. The highest error rate occurred in this field when attempting to predict which points fell into the average classification. The combination of yield classification and linear discriminant analysis seems to be promising for determining soil‐topography‐yield relationships and hence soil management zones.

Field Measurement of Soil Surface Chemical Transport Properties for Comparison of Management Zones

Management of chemicals in soil is important, yet the complexity of field soils limits prediction of management effects on transport. To date, few methods have been available for field measurement of chemical transport properties, but a recently developed dripper–time domain reflectometry technique allows rapid collection of data for determining these properties. The objective of this work was to apply this technique for comparison of chemical transport properties for different soil management zones. Experiments were conducted comparing four interrow management zones: no‐till nontrafficked, no‐till trafficked, chisel plow nontrafficked, and chisel plow trafficked. Drip emitters were positioned at 12 locations in each zone and used to apply water followed by a step input of CaCl2 tracer solution. Breakthrough curves were measured via electrical conductivity with time domain reflectometry probes. The mobile–immobile model was fit to the breakthrough curves to determine chemical transport properties. Mean chemical transport properties were 0.34, 0.11 h−1, 10 cm h−1, 164 cm2 h−1, and 5 cm, for the immobile water fraction, mass exchange coefficient, average pore‐water velocity, mobile dispersion coefficient, and dispersivity, respectively. All five properties showed significant differences between management zones. Differences in mass exchange and mobile dispersion coefficients coincided with differences in tillage, while differences in mean pore water velocities coincided with differences in traffic. The immobile water fraction was largest for the no‐till nontrafficked zone. These results represent one of very few reports for field measurement of chemical transport properties and the first application of this approach for comparison of chemical transport properties across management zones.

Soil management zones delineated by electrical conductivity to characterize spatial and temporal variations in potato yield and in soil properties

Within-field management zones (MZ) delineated using soil electrical conductivity (EC) may provide the basis for site-specific crop management (SSCM). The objective of this study was to evaluate the efficiency of EC for delineating homogenous soil MZ related to soil properties. Soil EC was measured on a 15-m×15-m grid using a Geonics EM38 on a 13.8-ha commercial field under potato (Solanum tuberosum L.) production. A subset of this grid (30 m×30 m) was used to collect soil samples (0–0.2 m) and to perform soil profile descriptions (1.2 m). Soil samples were analyzed for physico-chemical properties (texture, organic matter, pH, Mehlich-3 extractable elements). Potato tuber yields were measured using a yield monitor in 1998, 1999, and 2000. The K-means clustering algorithm was performed for delineating MZ using the soil EC kriged data matrix. Two MZ were found to be optimal for implementing SSCM management for potato in this field. These two MZ showed significant differences in soil water regime (thickness of sandy deposit over the clayey substratum, water table depth, water-holding capacity) and in some soil physico-chemical properties (soil organic matter, soil P, soil pH). Significant differences in potato yields (5.9 t ha−1) between the two MZ were attributed to differing water supply. Soil EC has the potential to be used efficiently for delineating within-field MZ for soils in which soil deposits and soil physical properties control soil moisture availability.

Management Zones based on Correlation between Soil Compaction, Yield and Crop Data

In 2003, soil and winter wheat crop information were gathered on an Arenic Cambisol field dominated by sandy silt loam and sandy loam soils according to the Belgium soil classification. Crop information consisted of spectral reflection measurements taken in May and yield mapping in August. Soil information, obtained after harvest, included moisture content and dry bulk density. The soil and crop information of this field were analysed to assess the effect of the measured soil dry bulk density on the crop and to test if the measured soil bulk density could contribute to better field management. Where dry soil bulk density was above 1·6 Mg/m3, the yield was limited, otherwise, no relation was observed between the yield and dry soil bulk density. Different methods of defining management zones based on soil and crop information were compared. Fuzzy clustering was used to make soil management zones based on the soil data only, but these clusters did not explain much of the yield variability. Another set of management zones was defined based on soil information and crop. These clusters provided a better description of the yield variation. A low-yielding area could be delineated related to high soil bulk density. Outside this area, yield was more affected by soil moisture variability and other factors.

Using geostatistical and remote sensing approaches for mapping soil properties

This paper attempts to compare various prediction methods for mapping soil properties (texture, organic matter (OM), pH, phosphorus and potassium) for precision farming approaches by incorporating secondary spatial information into the mapping. The primary information (or primary attribute) was obtained from an intensive grid soil sampling and the secondary spatial information from digital (or spectral) data from an aerial colour photograph of bare soil. The prediction methods were statistical (linear regression between soil properties and digital values) and geostatistical algorithms (ordinary kriging, ordinary kriging plus regression and kriging with varying local means). Mean square error (MSE) was used to evaluate the performance of the map prediction quality. The best prediction method for mapping organic matter, pH and potassium was kriging with varying local means in combination with the spectral data from the blue waveband with the smallest MSE indicating the highest precision. Maps from these kriged estimates showed that a combination of geostatistical techniques and digital data from aerial photograph could improve the prediction quality of soil management zones, which is the first step for site-specific soil management.

Efficacy of Grid and Zone Soil Sampling Approaches for Site-Specific Assessment of Phosphorus, Potassium, pH, and Organic Matter

Within-field variability of plant-available nutrients often results in different fertilizer requirements across a field. There is uncertainty concerning the efficacy of alternative sampling strategies suitable for site-specific management. This study compared various soil sampling approaches for P, K, pH, and organic matter (OM) in eight agricultural fields. Soil samples were collected using an intensive 0.2-ha grid-point procedure, and were used to compare less intensive sampling approaches. The approaches were based on 1.2–1.6-ha grid cells (Grid), soil series of digitized soil survey maps (SSM), soil series of detailed soil survey (1:12,000 scale) maps, elevation zones, and management zones based on various information layers (ZS). The approaches varied in reducing the within-unit soil-test variability and maximizing mean soil-test values across sampling units, but none was superior across all fields and nutrients. All approaches were less efficient for P and K than for pH or OM. The Grid and ZS approach were the most effective across all nutrients and fields. However, the Grid approach was more effective for P, the Grid and ZS approaches were better for K and pH, and the SSM and ZS approaches were better for OM. The ZS approach often resulted in fewer sampling zones than the Grid approach, which implies lower soil testing costs for producers, but required more knowledge and subjective judgement than a Grid approach to adapt it to field-specific conditions.

Rapid identification of soil textural and management zones using electromagnetic induction sensing of soils

Three surveys of a pastoral–cropping farming system were carried out over a period of 1 year, using an electromagnetic sensor and real-time-kinematic (RTK)-GPS. The maps produced delineated areas of different apparent soil electrical conductivity (ECa). These delineated areas were compared with soil units of a conventional soil map and results showed the ECa map related well to soil-particle-size classes. In addition ECa could be used to predict groupings of soil phases accurately within one soil type.Soil coring to depths of 1 m, to determine soil physical and chemical properties, showed ECa values were moderately well correlated (R2 = 0.72) to soil clay percentage, weighted for the soil profile. Soil fertility indicators, Olsen P (R2 = 0.61), cation exchange capacity (R2 = 0.59), and exchangeable magnesium (R2 = 0.76) also related well. The linear regression (R2 = 0.76) of ECa with exchangeable magnesium is thought to reflect the dominant clay mineralogy of the study area, i.e. chlorites weathering to illites and releasing magnesium to the soil solution. Discriminant statistical analysis of results showed point ECa values could be used to predict 2 major groupings of the mapped soil phases with 100% accuracy. More precise prediction of these mapped soil units is constrained by localised management effects. Elevated ECa values occur at areas of soil compaction, which have been deduced from measurements of soil strength, aggregate size distribution and visual soil assessment.

Delineation of Site-Specific Management Zones by Unsupervised Classification of Topographic Attributes and Soil Electrical Conductivity

The objective of this research was to determine if unsupervised classification of topographic attributes and soil electrical conductivity could identify management zones for use in precision agriculture. Data collected in two fields located in central Missouri were used to test the proposed methodology. Principal component analysis was used to determine which layers of data were most important for representing within-field variability. Unsupervised clustering algorithms implemented in geographic information system (GIS) software were then used to divide the fields into potential management zones. Grain yield data obtained using a full-size combine equipped with a commercial yield sensing system and global positioning system (GPS) receiver were used to analyze the "goodness" of the potential management zones defined for each field. Principal component analysis of input variables for Field 1 indicated that elevation and bulk soil electrical conductivity (EC) were more important attributes than slope and Compound Topographic Index (CTI) for defining claypan soil management zones. The optimum number of zones to use when dividing a field may vary from year to year and was mainly a function of weather and the crop planted. The number of zones decreased if adequate moisture conditions were present throughout the cropping season (unpredictable) or if crops tolerant to water stress were planted (predictable). This classification procedure is fast, can be easily automated in commercially available GIS software, and has considerable advantages when compared to other methods for delineating within-field management zones.

Site‐Specific Analysis of a Droughted Corn Crop: I. Growth and Grain Yield

Soil in the southeastern USA Coastal Plain exhibits marked variation, especially near shallow depressions called Carolina Bays. This variation causes correspondingly severe variation in yield, particularly for corn (Zea mays L.) during drought. Though important to precision farming, these features often are overlooked in 1:20000 scale county soil surveys. They are visible in 1:1200 scale soil surveys, but the ability to explain yield variation using soil map units at this scale must be unequivocally demonstrated before committing resources to such a detailed survey. Our objectives were (i) to compare paired samples of four soil map units to determine if grain yield variation were sufficiently explained to be of practical value, and (ii) to extend this evaluation to include data with greater spatial coverage. Corn grain yields were measured at 209 sites in an 8‐ha field, including two Carolina Bays near Florence, SC. Site‐specific effects of soil variation on crop phenology, biomass, and yield components were measured at 11 sites during a drought. Variations in yield components were large and sometimes compensatory (e.g., kernel number and mass), with distinctly different routes to sometimes similar final grain yields. Multiple sites within map units were frequently different at α = 0.05. Analysis of variance for grain yield on soil map unit was statistically significant (P < 0.001) but of limited explanatory value (r2 = 0.16). We conclude that to create soil management zones for precision farming, one must augment even detailed soil map units with additional spatial data, such as yield maps.

LABORATORY STUDY OF ZONAL MANAGEMENT EFFECTS ON PREFERENTIAL SOLUTE MOVEMENT IN SOIL1

Water quality in agricultural areas is often influenced by chemicals used in crop production. The application methods of agricultural chemicals can affect how these solutes move through soil. Precision management of zones within each crop row is often achieved via tillage (e.g., mechanical weed control in a standing crop), but few methods for specific management to reduce transport of chemicals from treated soils have been suggested. Management of separate soil zones during chemical application was investigated using solute breakthrough studies with undisturbed soil cores (fine-loamy, mixed Aquic Hapludoll). Treatments were the application of 13.8 g/m2 chloride (Cl−) using three strategies: (i) ponded application of the solute; (ii) unsaturated solute infiltration; and (iii) a zonal management technique, in which a small zone (volume) of soil was disturbed and mixed with solute before leaching. Column effluent was analyzed for Cl−. Columns were leached with Cl−-free solution before another treatment was applied. Each column received each treatment in succession. The solute breakthrough patterns during the first 2.5-cm drainage were influenced by both solute application method and soil column macroporosity. These results suggest that compared with broadcast applications, solutes restricted to soil management zones had slower transport through soil that, overall, had an abundance of macropores.

Development of an improved Vertisol stability test for SOILpak

The stability in water of soil from 3 contrasting Vertisols was measured using5 tests. Two end-over-end shaking procedures, the Loveday & Pyledispersion test, and the relatively rapid SOILpak procedure of Daniells & Larsen were assessed. The latter method has been modified to deal with severaldeficiencies such as its lack of score subdivisions; the new procedure isreferred to as the ‘aggregate stability in water’ (ASWAT) test. Wecorrelated data from all the tests under consideration to provide definitionsof the ‘critical’ point at which dispersion becomes a problem forland managers. Three soil management zones have been defined provisionallyusing data from the ASWAT and end-over-end ‘aggregate stability’tests. The scheme allows appropriate surface soil management strategies to bepredicted using the ASWAT test. The relationship between data from the ASWATtest and exchangeable sodium percentage indicated that factors other thanexchangeable sodium strongly influence dispersibility of the samples underconsideration.