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.     

Simulation of Cotton Production for Precision Farming

Most crop simulation models do not directly consider the spatial variability of inputs nor do they produce outputs that show the expected spatial variability of yield across a field. If such models were available for precision farming, then researchers could much better evaluate the effects of soil sampling densities to determine the number of samples necessary to adequately model a particular field. The objectives of this study were: (1) to design and implement a spatial simulation methodology for examining details of precision farming and (2) use this to evaluate the effects of different soil sampling resolutions on predicted yield and residual nitrates through spatially variable nitrogen applications. The GOSSYM/COMAX cotton growth model/expert system and the GRASS geographic information system were used to develop a spatial simulation that produces spatially variable outputs. Inputs to the model were collected from a 3.9-ha cotton field. Soil nitrate, a primary driver in fertilizer recommendations, was sampled on a 15.2-m regular grid for depths to 15 cm and on a 30.5-m regular grid at six 15-cm depth intervals (down to 90 cm). COMAX was used to determine spatially variable fertilizer recommendations. GOSSYM was used to simulate perfect application of these recommendations and predicted spatially variable yield and residual nitrates. Reductions in sampling density or resolution were simulated by systematically reducing the amount of data available to COMAX for calculating spatially variable fertilizer recommendations. GOSSYM subsequently used these recommendations (based upon less and less knowledge of soil nitrates) to simulate the effects of differing sampling resolutions on predicted yield and residual nitrates. For recommendations based upon a 15.2-m grid of inputs, 41.4 kg/ha of nitrate fertilizer produced 801.7 kg/ha of cotton and left an average of 9.4 ppm of nitrate in the soil profile. For a 30.5-m grid, 42.8 kg/ha of nitrate fertilizer resulted in a yield of 811.2 kg/ha and residual soil nitrate of 8.3 ppm. For 45.7-m and 61.0-m grids, the results were 43.3 kg/ha and 41.2 kg/ha of nitrate fertilizer, 755.3 kg/ha and 794.3 kg/ha of cotton, and 11.5 ppm and 8.1 ppm of residual soil nitrate, respectively. This study concluded that crop simulations and geographic information systems are a valuable combination for modeling the effects of precision farming and planning variable rate treatments. Simulation results indicate that excessive fertilization, while potentially damaging to the environment, may also have a negative impact on yield.     

Management zones delineation using fuzzy clustering techniques in grapevines

Precision viticulture aims at managing vineyards at a sub-field scale according to the real needs of each part of the field. The current study focused on delineating management zones using fuzzy clustering techniques and developing a simplified approach for the comparison of zone maps. The study was carried out in a 1.0 ha commercial vineyard in Central Greece during 2009 and 2010. Variation of soil properties across the field was initially measured by means of electrical conductivity, soil depth and topography. To estimate grapevine canopy properties, NDVI was measured at different stages during the vine growth cycle. Yield and grape composition (must sugar content and total acidity) mapping was carried out at harvest. Soil properties, yield and grape composition parameters showed high spatial variability. All measured data were transformed on a 48-cell grid (10 × 20 m) and maps of two management zones were produced using the MZA software. Pixel-by-pixel comparison between maps of electrical conductivity, elevation, slope, soil depth and NDVI with yield and grape composition maps, set as reference parameters, allowed for the calculation of the degree of agreement, i.e. the percentage of pixels belonging to the same zone. The degree of agreement was used to select the best-suited parameters for final management zones delineation. For the year 2009 soil depth, early and mid season NDVI were used for yield-based management zones while for quality-based management zones ECa, early and mid season NDVI were utilized. For the year 2010 ECa, elevation and NDVI acquired during flowering and veraison were used for the delineation of yield-based management zones while for quality-based management zones ECa and NDVI acquired during flowering and harvest were utilized. Results presented here could be the basis for simple management zone delineation and subsequent improved vineyard management.     

Oenological significance of vineyard management zones delineated using early grape sampling

Early definition of oenologically significant zones within a vineyard is one of the main goals of precision viticulture, as it would allow an increase in profitability through the adaptation of agronomic practices to the specific requirements of each zone, and/or segregation of the harvest into different batches to produce wines with different qualities. The aim of this work was to evaluate whether early grape sampling is a relevant tool for within-vineyard zone definition. The study was carried out in 2010 and 2011 in a 4.2 ha vineyard, where a grid of 60 sampling points was defined. 300-berry samples were picked from each sampling point after veraison and at harvest, post-veraison information being used to define zones within the vineyard after fuzzy k-means analysis and subsequent application of a zoning procedure that took into account membership degree and neighbourhood criteria. Two variations of the zoning procedure were used, standard (StdZ) and top (TopZ) zoning. Each was designed to meet different requirements of wineries; StdZ gave the same oenological relevance to all the zones, and TopZ differentiated the zones producing “top class” grapes, minimizing the within-zone variability in the top-class zone. Grape composition obtained at harvest from the zones delineated post-veraison was compared. Zone delineation using post-veraison data was proved to be oenologically relevant, provided sampling is performed once veraison is completed. The two zoning algorithms designed were shown to be suitable for objective zone delineation according to the goals intended for each.     

Spatial Variability of Agricultural Soil Fertility Parameters in a Gleyic Podzol of Belgium

Precise information about the spatial variability of soil nutrients is essential in developing site-specific management, e.g., variable rate application of nutrients. In this study 5 fields (4 grassland, 1 arable land) on a Gleyic Podzol, each of about 1 ha, were sampled according to a 20 m×20 m grid. On these samples pH, carbon content and nutrient status (P, K, Ca, Mg, and Na) were measured. The variogram analysis of the different soil fertility parameters revealed quite different ranges for these parameters. Carbon content, pH and calcium have high ranges, between 110 and 170 m. On the other hand, ranges for potassium and sodium are much smaller, 60 m and 30 m respectively. For the elements potassium and sodium, high coefficients of variation are found, especially on the grassland fields. These differences in ranges of spatial relationship indicate that the sampling strategy for estimating variability of soil fertility, should be adopted to the different selected soil parameters and the soil use.     

Relationship Between Spectral Data from an Aerial Image and Soil Organic Matter and Phosphorus Levels

Early ventures into site-specific management involved fertilizer management decisions based on soil chemical properties characterized by some form of grid sampling. This is both labor and capital intensive and practitioners quickly began investigating other methods to get a measure of spatial variability. Aerial photographs, which were mainly used to evaluate and assess crop status, allow for the collection of whole-field data at relatively low cost. Our objective is to determine what relationships exist between aerial spectral data and intensive grid soil test results and whether this information can be used to improve future soil sampling strategies. Soil-test organic matter (OM) and Bray-1 P concentrations were measured on soil samples taken using an alternating 12.2- by 24.4-m grid in late March 1994 from a quarter section under center pivot irrigation. Spectral data were collected in the spring of 1996 prior to planting using a multispectral network of digital cameras. Correlations of brightness values from the blue, green, and NIR bands with both OM and Bray-1 P were significant, but relatively low. Normality tests revealed that brightness values for the spectral data sets were generally evenly distributed while those of the soil test OM and Bray-1 P were positively skewed. Many of the very high soil-test data values were due to past management. When those values were removed from the database, greater correlations between spectral data and soil test data were obtained. These results substantiated that aerial imagery can be used to improve sampling strategies, but it must be used in conjunction with existing knowledge and past management histories.     

Soil Nutrient Relationships with Topography as Influenced by Crop

Variable-rate fertilizer application is often based on grid soil sample data from a single year of data in an annual crop rotation. The objectives of this study were to determine if crop history influences spatial dependence (the degree of spatial variability) of nutrients in a rotation including both annual crops and alfalfa, and to compare grid-based and topography-based sampling strategies for representing within-field nutrient levels. A site in the Red River Valley of North Dakota was observed over three years from 1994–1996. The site was divided into one field of continuous alfalfa (Medica sativa L.) and an adjacent field seeded to spring wheat (Triticum aestivum L.) in 1994, barley (Hordeum vulgare L.) in 1995 and alfalfa in 1996. Samples were taken from a 16.2-ha site each fall in a 33-m grid and analyzed for NO₃-N, P, SO₄-S and Cl. Topography was determined by measuring elevation in a 33-m grid with a laser-surveying device. Spatial dependence was determined by calculating the semivariogram and using regression analysis to assess the relationship between the semivariogram and the semivariogram model. Spatial dependence of NO₃-N and P was strongest following spring wheat and barley, while spatial dependence for SO₄-S and C1 was strongest for vigorous stands of alfalfa. When the continuous alfalfa stand declined following winter kill, NO₃-N and P spatial dependence intensified. Topography based sampling was correlated with the 33-m grid by giving each 33-m sampling location its value as directed by a topography sampling, then correlating that topography based value with the original 33-m sampling value. Topography-based sampling was correlated with the 33-m sampling grid for all nutrients following spring wheat and barley, but not in continuous alfalfa until the stand began to decline in vigor. Following alfalfa seeding in the annual crop field, topography relationships with NO₃-N and P decreased, while topography relationships with SO₄-S and Cl increased. Topography samplings of sulfate-S and chloride were most highly correlated to 33-m grid values in vigorous alfalfa. Lack of NO₃-N spatial dependence in the vigorous alfalfa stands suggests that a composite or field average soil test might be sufficient to provide soil NO₃-N information under similar conditions.     

应用地理信息系统研究土壤养分变异

采用网格取样,应用土壤养分系统法,结合地理信息系统(GIS)、全球定位系统(GPS)技术,研究了分散经营条件下村级尺度土壤养分空间变异。结果表明,研究区土壤养分普遍分布不均,存在着变异,土壤养分N,P和有机质的变异较大,与氮磷化肥和有机肥的投入有密切关系;Ca,Mg,K,Cu,Fe,Mn等养分土壤变异表现相对较小。     

湖北省粮食主产区土壤养分的空间变异性研究

利用"网格"取样、土壤养分状况系统研究法和GIS技术探讨了湖北省粮食主产区3个自然村土壤养分的空间变异特性.结果表明,pH值和有机质相对稳定,在整个研究区域其变异较小,近似于正态分布,施肥元素的变异则较大,表现出明显的负偏峰分布特征;土壤有效P、K和Zn等重要施肥元素的空间变异主要是受土壤利用方式和施肥水平等随机因素的影响,同时其缺乏又更多地出现在水田中.     

Vineyard zone delineation by cluster classification based on annual grape and vine characteristics

This study describes a method for vineyard zone delineation based on spatial interpolation of data on annual monitoring of grape and vine growth from 2007 to 2012 for four commercial vines (Cabernet Sauvignon, Mencía, Merlot and Tempranillo) located in the Bierzo Denomination of Origen (NW Spain). A sampled grid of 20 × 29 m (14 vines/ha) was defined for each vineyard and data were collected for ten soil, six grape composition, three grape production and five vine vigour variables. Continuous maps of each variable were created by spatial interpolation from the sampled points. Several zone delineations were obtained by clustering—using the iterative self-organizing data analysis (ISODATA) algorithm—according to different combinations of the studied variables. The resulting zone delineations were analysed (ANOVA) in order to determine whether the variables in the two cluster classifications for two or three zones were statistically different from each other. The selected delineation was the cluster that included total soluble solids, titratable acidity, total phenolic content, pH, mean cluster weight and length of the internode in two zones. The results point to the feasibility of this approach to vineyard zone delineation. Further research is necessary to confirm the effectiveness of this approach for other locations and evaluate the usefulness of introducing new grape and vine variables.     

The use of scaled semivariograms to plan soil sampling in sugarcane fields

Spatial sampling designs used to characterize the spatial variability of soil attributes are crucial for science studies. Sample planning for the interpolation of a regionalized variable may use several criteria, which could be best selected from an estimated semivariogram from a previously established grid. The objective of this study was to optimize the procedure for scaled semivariogram use to plan soil sampling in sugarcane fields in the Alfisol and Oxisol regions of Jaboticabal Town in S?o Paulo State, Brazil. A scaled semivariogram for several soil chemical attributes was estimated from the data obtained from two grids positioned on a sugarcane field area, sampled at a depth of 0.0?C0.5?m. The research showed that regular grids with uniform intervals did not express the real spatial variability of the soil attributes of Oxisols and Alfisols in the study area. The calculated final sampling density based on the scaled parameters of the semivariogram was one sample for each 2?ha in Area 1 (convex landscape) and one sample for each 1?ha in Area 2 (linear landscape), as indicated by SANOS 0.1 software. The combined use of the simulation programs and scaled semivariograms can be used to define sampling points. These results may help in soil fertility mapping and thereby improve nutrient management in sugarcane crops.     

Optimised Spatial Sampling Scheme for Soil Electriclal Conductivity Based on Variance Quad-Tree （VQT） Method

The acquisition of precise soil data representative of the entire survey area,is a critical issue for many treatments such as irrigation or fertilization in precision agriculture.The aim of this study was to investigate the spatial variability of soil bulk electrical conductivity(ECb)in a coastal saline field and design an optimized spatial sampling scheme of ECb based on a sampling design algorithm,the variance quad-tree(VQT)method.Soil ECb data were collected from the field at 20m interval in a regular grid scheme.The smooth contour map of the whole field was obtained by ordinary kriging interpolation,VQT algorithm was then used to split the smooth contour map into strata of different number desired,the sampling locations can be selected within each stratum in subsequent sampling.The result indicated that the probability of choosing representative sampling sites was increased significantly by using VQT method with the sampling number being greatly reduced compared to grid sampling design while retaining the same prediction accuracy.The advantage of the VQT method is that this scheme samples sparsely in fields where the spatial variability is relatively uniform and more intensive where the variability is large.Thus the sampling efficiency can be improved,hence facilitate an assessment methodology that can be applied in a rapid,practical and cost-effective manner.     

不同布点方式的膜下滴灌棉田土壤水分的空间变异研究

以新疆生产建设兵团石河子国家农业科技园区的膜下滴灌棉田作为试验区,采用随机法布点方式和均匀布点方式,利用地统计学理论分析了棉花膜下滴灌条件下土壤含水率的空间变异规律。结果表明,随机采样布点方式优于均匀采样布点方式;膜下滴灌棉田不同采样方式下的0~20 cm层的变异性变化最大,其它层的变化较小;膜下滴灌棉田土壤含水率20~40 cm和40~60 cm层的空间变异强度属弱变异,60~80 cm和80~100 cm层的空间变异强度属弱变异及中等变异。     

A Model for Agro-Economic Analysis of Soil pH Mapping

Core soil sampling followed by laboratory analysis is the traditional method used to map soil pH prior to variable rate application (VRA) of lime on cropland. A recently developed automated soil sampling system capable of measuring soil pH on-the-go has significantly increased sampling resolution. However, adoption of such systems must be justified economically. This paper presents a method for assessing the economic benefit from automated mapping of soil pH prior to variable rate lime application. In this work, geostatistical, agronomic, and economic methods were used to generate a comprehensive numerical model for quantitative assessment of the net return over cost of liming for different lime management strategies. The strategies included: automated pH mapping, manual grid soil sampling, and whole field sampling used in combination with either variable or fixed rate liming. The model was demonstrated using a simulated field with known average pH and semivariogram model. The analysis showed the largest benefit ($6.13ha^–1year^–1) from using VRA with automated soil pH mapping versus VRA based on 1ha (2.5acres) manual grid point sampling for the selected simulated field conditions. A sensitivity analysis demonstrated that for a wide range of field conditions and crop prices, VRA plus automated mapping promises higher relative benefits than VRA based on either manual grid point or grid cell sampling.     

Mobile TDR for geo-referenced measurement of soil water content and electrical conductivity

The development of site-specific crop management is constrained by the availability of sensors for monitoring important soil and crop related conditions. A mobile time-domain reflectometry (TDR) unit for geo-referenced soil measurements has been developed and used for detailed mapping of soil water content and electrical conductivity within two research fields. Measurements made during the early or late season, when soil moisture levels are close to field capacity, are related to the amount of plant available water and soil texture. Combined measurements of water content and electrical conductivity are closely related to the clay and silt fractions of a variable field. The application to early season field mapping of water content, electrical conductivity and clay content is presented. The water and clay content maps are to be used for automated delineation of field management units. Based on a spatial analysis of the soil water measurements, recommendations are made with respect to sampling strategies. Depending on the variability of a given area, between 15 and 30 ha can be mapped with respect to soil moisture and electrical conductivity with sufficient detail within 8 h.     

Ground-Sensor Soil Reflectance as Related to Soil Properties and Crop Response in a Cotton Field

Bare soil reflectance from airborne imagery or laboratory spectrometers has been used to infer soil properties such as soil texture, organic matter, water content, salinity and crop residue cover. However, the relation of soil properties to reflectance data often varies with soil type and conditions and surface reflectance may not be representative of the conditions in the root zone. The objectives of this study were to assess the soil reflectance data obtained by ground-based sensors and to model soil properties in the root zone as a function of surface soil reflectance and plant response. Ground-based sensors were used to simultaneously monitor soil and canopy reflectance in the visible and near-infrared (VNIR) along six rows and in two growth stages in a 7 ha cotton field. The reflectance data were compared to soil properties, leaf nutrients and biomass measured at 33 sampling positions along the rows. Brightness values of the blue and green bands of soil reflectance were better correlated to soil water content, particulate organic matter and extractable potassium and phosphorus, while those in the red and NIR bands were correlated to soil carbonate content, total nitrogen, electrical conductivity and foliar nutrients. The correlation of red soil reflectance with canopy reflectance was significant and indicated an indirect inverse relationship between soil fertility and plant stress. The integration of surface soil reflectance and plant response variables in a multiple regression model did not substantially improve the prediction of soil properties in the root zone. However, crop nutrient status explained a significant portion of the spatial variability of soil properties related to nitrification processes when soil reflectance did not. The implication of these findings to agricultural management is discussed.     

土壤养分变异及合理取样数的初步研究

利用地统计学方法、地理信息技术对土壤养分变异及合理取样数做了初步研究.结果表明大部分土壤养分都具有良好的半方差结构及强烈的空间相关性.统计分析结果表明土壤养分变异越大,相应要达到一定精确度的取样数量也会增大,研究区域各种养分变异系数大小及其取样数量的排列顺序基本一致,为速效磷>全氮>碱解氮>有机质>速效钾. 用纯随机取样法初步探讨了研究区域土壤养分合理取样数.速效磷取样以90;置信水平20;相对误差为宜,取样数量为4个;速效钾取样以10;相对误差为宜,取样数量为5个;碱解性氮取样以20;相对误差为宜,取样数量为1个;有机质取样以10;相对误差为宜,取样数量为5个;全氮取样以10;相对误差为宜,取样数量为14个.     

Estimating Average and Proportional Variograms of Soil Properties and Their Potential Use in Precision Agriculture

Precision Agriculture requires a method of gathering information about the spatial variability of soil that reduces the need for expensive and intensive sampling. This can be achieved through the use of what we term average and proportional variograms. A literature search has enabled the gathering of variograms for multiple soil properties, allowing comparison of the magnitude of variability and the construction of averages. For soil properties that display proportionality between their mean squared and variance, the variogram can be predicted from a mean value. These average and proportional variograms are potentially beneficial to implementers of Precision Agriculture as they can be used to plan optimal soil sampling and management schemes. It was found that if wishing to implement site-specific management to a resolution of 20×20 m then grid soil sampling will generally have to be performed at 20–30 m intervals depending on the attribute of interest. A decision-support chart for differential soil management based on a variogram's comparative magnitude to the average is presented. Further work needs to be done on increasing the data base these results are based on and refining the proportional variogram parameters to site-specificity.     

东南地区土壤养分的空间变异性与取样策略I．土壤属性与大量元素

在我国东南6省(市)选择代表性区域(自然村),采用ASI和地统计学等方法对耕作土壤的pH值、有机质、有效氮、磷和钾的空间变异性与合理取样数量进行了研究。结果表明,①pH值和有机质是相对稳定的土壤属性,在整个研究区域其变异较小,近似于正态分布;施肥元素的变异则较大,表现出明显的负偏峰分布特征。②尽管某些土壤属性或大量元素的总体变异性相似,但在各研究区域,其实际半方差结构并不相同。③对于明显偏峰分布的土壤养分来说,建议采用最适分配法确定合理取样数量。纯随机合理取样数量可在一定程度作为参考。