Soil Science Society of America Journal 64:774-780 (2000)
© 2000 Soil Science Society of America
DIVISION S-8-NUTRIENT MANAGEMENT & SOIL & PLANT ANALYSIS
Soil and Crop Response to Variable-Rate Liming for Two Michigan Fields
F.J. Pierce and
D.D. Warncke
Crop and Soil Sci. Dep., Michigan State Univ., East Lansing, MI 48824 USA
piercef{at}msu.edu
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ABSTRACT
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Soil pH is known to vary spatially, making variable-rate lime application attractive where soil acidity occurs. This study examined the efficacy of variable-rate lime applications based on grid sampling at various scales on soil pH and the yield of corn (Zea mays L.) and soybean [Glycine max L. (Merr.)] during 3 yr. Lime was applied in two fields according to five lime management strategies: lime requirement (LR) estimated from maps interpolated from soil samples obtained from 30.5-, 61-, and 91.5-m grids; LR determined for the plot; and no lime. The LR interpolations consistently underestimated and were not correlated with LR measured on each plot. Granulated lime, used to insure uniform lime application, was slow to react in the field and a lab incubation verified that it reacted much slower than agricultural lime. Changes in pH occurred in the surface 10 cm, reflecting the depth of lime incorporation by chisel plowing. Corn yield did not respond to liming in 1995 and 1996. Soybean yield in 1997 increased due to liming at the Durand field, which had a lower range of soil pH values. Normalized soybean yields at both fields followed the same linear-plateau response to pH, with soybean yields declining below a threshold pH of about 5.9. While there is need for improvements in grid sampling design, variable lime applications under all of the grid sampling scales increased soil pH above the threshold pH for soybean in these fields, resulting in an improvement compared with whole field management.
Abbreviations: LR, lime requirement
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INTRODUCTION
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SPATIAL VARIATION IN SOIL PH is often observed in grid sampling soil tests, indicating a potential for site-specific lime management in agricultural soils (Peck and Melsted, 1973; Laslett et al., 1987; Tevis et al., 1991; Franzen and Peck, 1995; Pierce et al., 1995). The value of variable-rate liming is found in the expectation that managing areas within fields requiring lime will increase yields beyond the cost of lime application or that overliming areas not needing lime is costly and potentially yield reducing (Pierce and Nowak, 1999). While variable liming is often identified as a major benefit of precision agriculture, few published studies have evaluated soil and plant responses to variable lime applications.
Borgelt et al. (1994) showed that 9 to 12% of an 8.8-ha field would have been overlimed and 37 to 41% of the field underlimed with a uniform application, with the range in percentages corresponding with different methods of lime determination used in their study. While these estimates were based on a rigorous sampling design with a sampling density of 7.7 samples per hectare, they did not evaluate map accuracy. Additionally, variable-rate lime applications were not made, so crop response was not determined. Peck and Melsted (1973) sampled soils from two 16.2-ha fields in Illinois in 1961 on a systematic grid spacing of 25.2 m and found pH averaged 6.6 and 6.2 for the two fields but ranged from 5.5 to 8.0 for the two fields. One site, the Mansfield field, was sampled and limed periodically, but the spatial pattern of soil pH remained similar between the 1961 and 1991 sampling dates (Franzen and Peck, 1995; Hergert et al., 1997). Franzen and Peck (1995) applied lime to the Mansfield field at a uniform rate of 4.48 Mg ha-1 and evaluated the change in soil pH and Ca and Mg concentrations in leaf tissue of corn and soybean. Hergert et al. (1997) reported that grain yields were positively correlated with soil pH in 1991 before liming, but soybean yield was unrelated to soil pH in 1992 after lime application, indicating a threshold pH for soybean response to pH had been exceeded. Crops vary in their response to soil pH, responding to lime applications only if pH levels limit crop performance (Black, 1993). McLean and Brown's (1984) summary of crop response to soil pH in the Midwest showed that corn frequently did not respond to soil pH in the range of 5 to 6, while alfalfa (Medicago sativa L.) was strongly affected by this pH range, with soybean intermediate in response. It was the beneficial effects of lime on legumes that formed the basis for lime applications prior to the 1950s, after which the need for lime was based on neutralizing soil acidity resulting from additions of large quantities of residually acid fertilizers (McLean and Brown, 1984).
Farmers may or may not experience yield changes from liming depending on the accuracy of their soil tests, spatial variability in pH, and the sensitivity of each crop in their rotation to pH. Yields may not decline from overliming, as liming soils of high pH may or may not have detrimental effects on the crop. Negative effects of overliming are usually tied to pH-induced nutrient deficiencies or toxicities at high pH (Adams, 1984). However, Christensen et al. (1998) reported that applications of sugar beet (Beta vulgaris L.) lime, a biproduct of beet processing, to the high pH (7.2–7.8) lake-bed soils of the Thumb region of Michigan increased soil pH by 0.3 to 0.5 pH units but had no detrimental effects on crop yield while improving sucrose content in sugar beets during the first 2 yr of their 5-yr study.
The keys to variable liming are an accurate prediction of the lime application map, accurate lime application control, and a sufficient crop response to lime application or lime material savings to pay for soil sampling and variable lime application. An accurate map requires a soil sampling strategy that will adequately describe the spatial distribution of reserve acidity in soil currently measured using buffer pH procedures that estimate lime requirement. In 1995, when this study was initiated, commercial variable-rate lime recommendations called for variable-rate lime application maps based on grid soil sampling using 1-ha regular grid spacings and interpolated using inverse distance squared interpolation methods. The general assumption was that such maps were accurate and lime applied site-specifically was an improvement over the traditional uniform field management. Furthermore, there was an expectation that variably liming fields cropped to corn and soybean would increase yields.
We examined the effect of grid sampling at various scales on the efficacy of site-specific lime management on soil pH and the yield of corn and soybean in two fields with variable soil pH. Additionally, laboratory incubation studies were conducted to compare the kinetics of granulated (pelletized) lime with agricultural lime to confirm field observations of slow rates of reaction of granulated lime in field experiments.
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Materials and methods
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Two fields, one near Durand, MI (16 ha), and the other near Plainwell, MI (23 ha), had been soil sampled in May 1993 on a 30.5-m regular grid (Pierce et al., 1995). The field average pH (average of all grid points) was 6.7 for the Plainwell field and 6.6 and 6.0 for the 0- to 5- and 5- to 20-cm depths, respectively, for the Durand field. A pH of 6.5 would be considered sufficient for corn and soybean production and no lime would be recommended, even for the Durand field since it was under long-term no-tillage management and surface applications of lime would primarily affect the surface soil pH. The spatial pattern of soil pH and LR determined from the SMP buffer pH procedure of Watson and Brown (1998) indicated a potential for variable lime application for both fields (Fig. 1)
. Due to sampling costs, commercial lime applicators usually sample soils on 1-ha grids and create maps by interpolation using inverse distance squared methods. Using subsets of the 30.5-m grids, we prepared additional LR maps for 91.5- and 61-m grid spacings by interpolation of LR using inverse distance squared. For both fields, each grid spacing produced different LR maps, as illustrated for the Durand field in Fig. 2
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Fig. 1 Soil pH and lime requirement maps for the Durand and Plainwell fields sampled June, 1993. The experimental area is delineated by a rectangle on each map and consisted of nine replications arranged in a three by three pattern
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Fig. 2 Interpolated maps of lime requirement for the Durand field derived from three regular grid sampling scales: (a) 30.5, (b) 61, and (c) 91.5 m
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Experiments to evaluate the effects of variable liming for various grid spacings were conducted on a 1-ha block within each field where lime applications were recommended according to the interpolated LR maps (Fig. 1). Soils at the Durand field were formed in loamy glacial till and at the Plainwell field were formed in glacial outwash (Table 1)
. Both experimental fields for the variable lime study have sandy loam texture in the surface horizon and both fields have been cropped to corn or a corn–soybean rotation for the last decade or more, with continuous no-tillage management at the Durand field. The dominant soil map unit within the experimental field was the Conover loam (fine-loamy, mixed, mesic Udollic Ochraqualf) at Durand and the Bronson sandy loam (coarse-loamy, mixed, mesic Aquic Hapludalf) at Plainwell (Table 1). Five liming treatments were evaluated as follows: three variable liming treatments corresponding with the LR predicted from 30.5-, 61-, and 91.5-m grid samples obtained in 1993; lime application based on the LR of a composite soil sample obtained from each plot in March 1995; and no lime, since the field average pH in 1993 indicated no lime was required. The experiment was a randomized complete block factorial design with nine replications arranged in a three by three block arrangement with an individual plot size of 4.5 by 30.5 m (Fig. 1). Composite soil samples were obtained from the 0- to 20-cm depth of each plot in March of 1995 prior to the application of lime and analyzed for pH in water (1:1) and SMP buffer pH using standard procedures (Watson and Brown, 1998). Lime recommendations were calculated from the SMP buffer pH to increase soil pH to 6.5 according to Vitosh et al. (1996)
The LR rates for three grid spacing treatments were read from the LR maps prepared from the original 1993 grid soil samples (e.g., Fig. 2, Durand field) and the weighted average used where more than one rate appeared within a plot. We used granulated lime rather than agricultural lime since granulated lime was suitable for precise application with a Gandy Orbit-Air fertilizer spreader (Gandy Company, Owatonna, MN).1
The granulated lime was applied at 0.8 of the calculated LR based on industry recommendations for lower rates of granulated lime than traditional agricultural lime sources. Corn was grown in 1995 and 1996 and soybean in 1997 using varieties and cultural practices selected by each farmer.
Prior to corn, each field was spring chisel plowed to a depth of 25 cm and received one or two passes of a field cultivator as needed to prepare an adequate seed bed each year prior to corn planting. Soybean was direct drilled in 1997 at both fields. To evaluate the effect of liming on soil pH, each plot was soil sampled periodically from 1995 to 1997 at 0- to 10- and 10- to 20-cm depths in March 1995, June 1995, and December 1996 at both fields, plus November 1995 at the Durand field and April 1996 at the Plainwell field. Corn was harvested from the center two rows of each six-row plot using a two-row plot combine that automated grain weight and grain moisture. Soybean was harvested using a plot combine with a 1.42-m swath grain table. Grain moisture was determined on subsamples after harvest. Reported grain yields are corrected to 155 g kg-1 moisture for corn and to 140 g kg-1 for soybean.
Soil samples taken during and after the 1995 growing season indicated that the granulated lime had little if any effect on soil pH. A lime equilibration study was performed in the laboratory to evaluate the rate of reaction of granulated lime compared with agricultural lime. Soil was obtained from the no lime application plots from the 0- to 10- and 10- to 20-cm depths from each field and air dried. Granulated lime used at each location and a dolomitic agricultural lime obtained from a local source were analyzed for neutralizing value (CaCO3 equivalent), MgCO3 content, and size distribution (Table 2)
. A quantity of granulated lime from the Durand field and of the agricultural lime were sieved to a yield a size fraction that passed a 2-mm (10-mesh) sieve and was retained on a 1.7-mm (12-mesh) sieve. This size fraction was selected in order to standardize the lime materials by increasing uniformity (see neutralizing values in Table 2) since lime sources are too heterogeneous to ensure comparability among lime sources and types. Each lime material was mixed with a 100-g sample of each soil at rates equivalent to 0, 2.25, 4.5, 9.0, and 18 Mg ha-1 of a liming material having a neutralizing value of 80%. Sufficient replications of each soil and lime rate combination were prepared to allow determination of pH and SMP buffer pH after 1, 2, 4, 8, and 16 wk of equilibration with four replications per sampling date. The containers were left open to allow soil moisture to vary through several wetting and drying cycles across the range of soil moisture contents from field capacity to air dry.
Analysis of variance was performed using spatial covariance for adjustment to remove the spatial correlation to obtain more accurate estimates of treatment means and differences for the field study (Littell et al., 1996). The response of soybean yield to soil pH in 1997 was modeled using a linear plateau by nonlinear least squares regression in the NLIN procedure in SAS (Littell et al., 1996). An outlier was detected in the regression analysis for the Durand field, and this point was removed from the regression analysis.
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Results and discussion
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Soil and Plant Response to Variable Liming
On the average, LR predicted by interpolation of LR from the grid samples obtained in 1993 consistently underestimated the LR measured in March 1995 in the experimental plots (Table 3)
. None of the LRs based on the three grid scale interpolations corresponded with the actual lime recommendation obtained for individual plots (Fig. 3)
. This lack of correlation was true even where the average LR predicted was similar to the average measured LR, as was the case for the 30-m grid LR for both fields (Table 3, Fig. 3). Therefore, grid soil sampling on regular grids did not accurately predict LR for these fields. At both locations, the range (Fig. 3) and the standard deviation (Table 3) in interpolated LR for individual plots was lower than measured values, an inherent consequence of interpolation procedures. Furthermore, because areas requiring lime may be patchy, using grid points outside a patch to interpolate values within the area needing lime will affect the LR estimates, which in our case were consistently lower than measured values (Table 3). The influence of the grid points outside a patch will depend on the search radius used in the interpolation and the sampling design. For these fields, grid sampling identified that parts of each field needed lime but did a poor job delineating those areas and underestimated LR. One solution for increasing accuracy is to increase sampling intensity. However, sampling costs increase in proportion to the inverse of the sampling distance squared, making intense soil sampling too expensive. Soil pH sensors for on-the-go measurements would solve this sampling dilemma but are not yet commercially available (Adamchuk et al., 1999). We recognize that the soil samples were obtained 
2 yr apart and that soil pH may have changed during that time. However, the spatial pattern of pH values was probably stable, as indicated by the data of Franzen and Peck (1995) and Hergert et al. (1997), suggesting that the correlation should have remained during that time.
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Fig. 3 Scatterplots of lime requirement (LR) measured on experimental plots vs. LR predicted by interpolation of grid points at scales of 30.5, 61, and 91.5 m for fields in Durand and Plainwell, MI. Each point represents one replication of each treatment in each of nine blocks. The 1:1 line is shown
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The granulated lime was slow to react, as soil pH changed slowly at both locations (Fig. 4)
. The lime applied in March did not affect soil pH by June 1995 (Fig. 4). Schulte and Kelling (1987) similarly found granulated lime slow to change soil pH when applied to soil for alfalfa production. Actually, the measured water pH decreased, probably due to a salt effect related to fertilizer application, tillage, and drying of the soil. Corn yields were not affected by treatment in 1995 at either location (Table 4)
. By November 1995 at the Durand field and April 1996 at the Plainwell field, some increase in soil pH was evident in the surface 10 cm, with no effect on soil pH in the 10- to 20-cm depth (Fig. 4). The degree of pH change related to the amount of lime applied. Corn yields in 1996 did not respond to lime application at either field (Table 4). While the slow reaction of granulated lime may have limited the response of corn to liming, limited response to liming is supported by other studies that suggest corn is not as sensitive to soil pH as other crops, particularly legumes (Adams and Pearson, 1967; McLean and Brown, 1984).
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Fig. 4 Temporal variation in soil pH as affected by lime treatment for fields in Durand and Plainwell, MI, for the 0- to 10- and 10- to 20-cm depths
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Table 4 Yield of corn and soybean as affected by variable lime application in a 3-yr period at Durand and Plainwell, MI, fields
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By the fall of 1996, soil pH had risen in response to lime application but only in the surface 10 cm for the Plainwell field (Fig. 4). Soil pH was increased in the 10- to 20-cm depth at the Durand field, with the greatest increase in the measured treatment where the highest rate of lime was applied. The limited lime effect below 10 cm reflects the shallow depth of incorporation characteristic of chisel plowing (Allmaras et al., 1996). Soybean yields were not affected by lime treatment at the Plainwell field, but yields at the Durand field were significantly lower for the no lime treatment than all other treatments where lime was applied (Table 4). Therefore, some lime application at the Durand field was sufficient to raise pH beyond a level critical to soybean. This response is related to the fact that symbiotic N-fixing bacteria are intolerant to soil acidity in the range of 4.0 to 6.0 (Graham and Parker, 1964; Keyser and Munns, 1979). A plot of soil pH and soybean yield reveals that soybean yields decline rapidly below soil pH of about 5.9 for the Durand field (Fig. 5)
. While a similar relationship is not as evident at the Plainwell field alone (Fig. 5), when soybean yields are normalized by dividing by the maximum yield at each field and data combined from the two fields, the linear plateau analysis shows the same relationship holds across locations, with a critical pH of 5.89. Therefore, a response from soybean to liming will increase with decreasing soil pH below some threshold pH, which in these fields was about pH 5.9, based on the linear-plateau analysis in Fig. 5. The data in Fig. 5 are consistent with the report of Adams and Pearson (1967) that soybean responds to lime up to about pH 6.0.
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Fig. 5 Soybean yield response in 1997 to soil pH measured in December 1996 for fields in Durand and Plainwell, MI, and normalized yield response for the two fields combined. Data were fitted to a linear-plateau model
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In the last soil measurement, the change in soil pH was approximately linearly related to the lime application rate regardless of treatment (Fig. 6)
. The change in pH was greater at the Durand field than at the Plainwell field and more pronounced in the surface 10 cm than in the 10- to 20-cm depth (Fig. 6). While slow to react, the granulated lime did increase pH as expected.
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Fig. 6 Response of soil pH to lime applied according to lime requirement (LR) for fields in Durand and Plainwell, MI, at the last soil sampling date in December 1996
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Lime Equilibration
The initial pH of the four bulk soil samples collected from the two fields and two depths used in this study were 5.7 and 5.6 for the Plainwell field, respectively, and 5.1 and 4.9 for the Durand field, respectively. While the initial pH varied for the soil samples, the relative changes in soil pH for the equilibration period were similar, so only the data from the surface soil from the Durand field will be discussed here. The dolomitic agricultural lime increased soil pH more rapidly and more completely than the granulated lime during the 16 wk of incubation (Fig. 7)
. The effect of lime rate was more evident with the agricultural lime than the granulated lime. The slow rate of reaction of granulated lime in the incubation study is consistent with field measurements. Kelling and Schulte (1988) similarly found a granulated calcitic lime to bring about soil pH change more slowly than a calcitic agricultural lime. Both the field and laboratory results go against the conventional understanding that granulated lime reacts more quickly and thoroughly than agricultural lime. While the slow reaction of granulated lime is confirmed in these studies, the reasons for this can only be surmised from the chemistry of the granulation process. Granulated lime materials are made by granulating finely ground agricultural lime (99% <0.84 mm diameter [20 mesh] and 60% <0.15 mm diameter [100 mesh]) and aggregating the fine lime particles using lignosulfonates during the granulation process. For the lime to become reactive, the lignosulfonates must break down by solubilization or microbial action. Apparently, under the conditions in our field studies and in the laboratory incubations, the lignosulfonate binder was retarding the breakdown or dissolution of the lime pellets. The lime pellets behaved more like large particles of dolomitic lime, which dissolve and react slowly. The large lime pellets also come in contact with less soil and so do not neutralize soil as completely as agriculture lime with 100% passing a 2.36-mm (8-mesh) sieve and 25% passing a 0.25-mm (60-mesh) sieve in order to be in compliance with Michigan lime standards.
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Fig. 7 Change in soil pH in the surface 10 cm of soil from the Durand field for incubation time in response to agricultural lime and granulated lime at five rates of lime application
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Conclusions
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Grid soil sampling did not accurately predict site-specific soil pH or LR. A better sampling design or higher sampling intensity may be needed to accurately define variable lime application zones, which to be economical for farmers may require sensors for soil pH or LR. Granulated lime reacted slower in the field than expected, and laboratory experiments showed that granulated lime reacted slower than comparably sized agricultural lime. We suspect the slow reaction time to be in part related to the lignosulfonates used to aggregate the lime into pellets. Across the duration of the study, liming increased soil pH but primarily in the surface 10 cm, indicating a shallow depth of lime incorporation with chisel plowing. Soybean responded to liming where soil pH was below a threshold of about pH 5.9, while corn did not respond to liming in the 2 yr. While problems in variable liming were evident in this study, no lime would have been applied under a whole field management approach resulting in reduced soybean yields in parts of these fields. Grid sampling and variable lime applications under any of the grid sampling scales would have increased soil pH above the threshold pH for soybean in these fields. Hence, variable liming was an improvement compared with whole field management, albeit an approach needing improvement.
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ACKNOWLEDGMENTS
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We appreciate the cooperating farmers, John Anibal and Dan Klein, for allowing us to conduct this research on their farms. We thank Dr. Oliver Schabenberger for his assistance in the linear plateau regression analysis of the yield response to soil pH and Brian Long for his assistance in field work and data collection.
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NOTES
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1 Mention of a specific proprietary product does not constitute a recommendation by Michigan State University and does not imply their approval to the exclusion of other suitable products. 
Received for publication February 23, 1999.
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TOP
ABSTRACT
INTRODUCTION
