EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATIONMODEL FOR USE IN IMPLEMENTING NUTRIENT

MANAGEMENT PLANS∗

STEPHEN F. HIGGINS1,∗, MARK S. COYNE2, SCOTT A. SHEARER1

and JOHN P. FULTON3

1Biosystems and Agricultural Engineering Department, University of Kentucky; 2Department ofPlant and Soil Sciences, University of Kentucky; 3Biosystems Engineering Department, Auburn

University, Auburn, Alabama (∗author for correspondence: e-mail: shiggins@bae.uky.edu)

(Received 30 June 2005; accepted 9 December 2005)

Abstract. Government regulatory agencies recommend nutrient management plans (NMPs) for an-

imal operations to reduce non-point source pollution. These plans require manure analysis for total

nitrogen (TN) and total phosphorus (TP), and use indices to determine nutrient availability. This

study evaluated a rapid on-farm method to predict TN and TP concentrations of swine slurries.

A field investigation based on this rapid assessment procedure was used to evaluate the effect of

a NMP on corn yield and soil fertility. Manure grab samples were collected to validate the rapid

on-farm model for predicting TN and TP. A corn crop was raised on two phosphorus (P) soil test

levels (medium and excessive) using three randomized complete blocks with two replications of

three treatments. Rapid on-farm models were accurate ( P ≤ 0.05) for predicting manure TN and

TP. The rapid model manure application rate produced grain yields that were significantly higher

than inorganic-N fertilization treatments (13,000 kg ha−1 versus 9,000 kg ha−1) ( P ≤ 0.05). Potas-

sium chloride extractable soil P and ammonium were not significantly different (P ≥ 0.05) in ma-

nure treatments compared with the inorganic-N treatment. Analysis of ear leaf N, P, and K and

grain yields demonstrated that the rapid model manure application developed by a NMP met crop

requirements.

Keywords: environment, nutrient, manure application, site-specific, precision agriculture, swine,

animal feeding operation

Introduction

Manure application rates are generally designed to meet crop growth requirementsfor N. However, the ratio of N to P, particularly in poultry and swine manure, using anN-based system typically supplies the soil with more P than crops can use. ManureP availability can be greater (Goss and Stewart, 1979) and also lower (Gracey, 1984)than inorganic-P sources. For example, Laboski and Lamb (2003) determined thathigh rates of injected swine manure provided more available P than inorganic P

∗The investigation reported in this paper (04-05-107) is in connection with a project of the Kentucky

Agricultural Experiment Station and is published with the approval of the Director. Mention of trade

names are for information purposes only and do not imply endorsement by the Kentucky Agricultural

Experiment Station.

Water, Air, and Soil Pollution (2006) 171: 333–358

DOI: 10.1007/s11270-005-9059-9 C© Springer 2006

334 S. F. HIGGINS ET AL.

fertilizers while Qian and Schoenau (2000) demonstrated that a single applicationof swine manure did not have an impact on increasing labile P forms in soils.

Thom and Dollarhide (2002) reported that soils with low initial P soil test valuesrequired more phosphate fertilizer to raise the soil test value by one unit than soilswith higher initial soil test values. Pote et al. (2003) supported this conclusionwhen they reported that poultry manure applied to the soil surface caused a greaterincrease in soil test P when applied to soil with higher initial soil test P values.

The specifications of manure equipment tend to apply manure as a waste ratherthan a resource, allowing manures to be over-applied effortlessly (Nowak et al.,1998). Mancl and Slates (2003) asked 101 farmers to estimate an application rateconducted at a field demonstration. Sixty-five percent of the farmers surveyed un-derestimated solid manure application rates; 50% of the farmers surveyed estimatedapplications rates of less than one-half the actual application rate, suggesting thatproducers may be applying twice as much material as needed. Although manureapplications are considered N-based, Schmidt et al. (1996), Sikora (2000), andDou et al. (2001) indicated that few animal producers submit manure samplesfor analysis, implying that manure application rates are not calculated for manyfarms.

The NRCS requires animal manure testing for total nitrogen (TN) and total phos-phorus (TP) to develop application rates for nutrient management plans (NMPs)(NRCS-590, 2001). Rapid on-farm methods for determining TN and TP could allowproducers to rapidly assess nutrient concentration in manure for calculating properapplication rates (Chescheir et al., 1985; Tunney and Bertrand, 1989; Stevens et al.,1995; Van Kessel et al., 1999). However, most of these methods are designed tomeasure N forms, and their use has not been widely adopted.

Chescheir et al. (1985), Tunney and Bertrand (1989), and Van Kessel et al. (1999)used the coefficient of determination (R2) from linear regression equations to eval-uate the accuracy of rapid nutrient determination methods. The aforementionedstudies also compared regression equations (slope and intercept) to previously con-ducted research. Van Kessel et al. (1999) plotted actual versus predicted values,evaluated regression equations by the R2 values, and determined if the slopes andintercepts, of regression equations, were significantly different from one and zero,respectively.

Manure TN and TP determination, along with soil fertility and crop information,would allow producers to concurrently meet crop needs and regulatory require-ments. There has been extensive research on the use of swine manure on yield andsoil fertility (Choudhary et al., 1996), but there is a lack of knowledge on whetherrecommended NMP practices attain their desired outcome. Although, the USDA-NRCS has been made responsible for developing NMPs, and State offices are ableto implement alternative best management practices (BMPs), and develop availablenutrient coefficients based on application method, physical and chemical propertiesof soils, and climatic conditions, these guidelines have seldom been verified withfield investigations.

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 335

The effect of a swine manure NMP on crop yield and soil fertility can be mea-sured using physical and analytical methods. Soil fertility can be assessed by mea-suring soil nitrate (NO−

3 ), ammonium (NH+4 ), soluble P (orthophosphate), and soil

test P (Mehlich III). Likewise, the effectiveness of manure nutrients relative to inor-ganic fertilizer applications can be conducted using crop yield and tissue analysis.However, luxury consumption of nutrients can provide similar dry matter yields,while demonstrating inefficient nutrient use. Consequently, evaluating nutrient suf-ficiency levels in crop tissues can be used as a measurement criterion.

The goal of this study was to conduct a field investigation to evaluate a rapidon farm TN and TP determination procedure, while simultaneously evaluating theeffect of a NMP on corn yield and soil fertility. The objectives of this study were to:

1. Verify an on-farm model to predict TN and TP in manure samples based onstandard evaluation indicators.

2. Conduct a field experiment to compare the effects on soil fertility and crop pa-rameters of a model based NMP versus a producer defined manure applicationrate using inorganic N-application as a control, in which the NMP manure ap-plication rate would be determined using a rapid on-farm nutrient determinationmodel.

Materials and Methods

MANURE SAMPLING

Manure for the experiment originated from a single anaerobic holding pit locatedunder a slatted finishing barn floor. The manure was agitated for approximatelyfive minutes using a vertical PTO powered centrifugal pump. Manure grab sampleswere collected from each load applied using a valve on the discharge side of themanure pump that loaded the manure wagons. Sub-samples were collected onone-minute intervals during wagon loading, which required approximately fiveminutes. These sub-samples were composited into a single one-liter sample bottle.The composited samples were transported on ice to the laboratory where they werestored in a refrigerated chamber at approximately 1.1◦C.

TN AND TP DETERMINATION

A sub-sample of manure from each manure sample bottle was evaluated analyti-cally to determine TN and TP and validate a rapid nutrient determination modelprocedure. The TN concentration was determined using a LECO (St. Joseph, MI)C and N analyzer (Peters, 2003). Total Pand K concentrations were determined viaashing and dissolution of the ash in HCl and HNO3 prior to analysis by inductivelycoupled plasma spectrophotometry (Peters, 2003). Solids content was measured

336 S. F. HIGGINS ET AL.

gravimetrically from 50–60 mL of liquid sample dried 48 h at 103 ± 2◦C. Testresults for TN, TP, and TS were reported on a percent of total mass wet-basis.

The remaining manure sample, which ranged from 600 to 800 ml, was processedusing a rapid on-farm determination model to predict TN and TP (Higgins et al.,2004a). The procedure consisted of transferring the manure to a 1000 ml graduatedcylinder (10-ml gradations) to record the initial sample volume, sieving the manurethrough an American Society for Testing and Materials (ASTM) standard wirescreen sieve (0.85 mm), then collecting and measuring the volume of the liquidportion passing through the sieve (filtrate). The filtrate volume divided by the initialvolume defined the “liquid ratio.” The liquid ratio value and the barn from which themanure was collected were entered into two model equations developed to predictTN and TP (Higgins et al., 2004a). Predicted TN and TP concentrations were usedto calculate manure application rates using worksheet No. 2 of the NRCS-590-KY(2001) guidelines. Plots of actual versus predicted nutrient concentrations and aregression of the data were used to evaluate model accuracy.

NMP DEVELOPMENT

The Kentucky Agriculture Water Quality Act of 1994 was passed to protect surfaceand groundwater resources from pollution caused by agricultural activities. This actrequires that all landowner/land users with ten or more acres used for agriculturaloperations must develop and implement a water quality plan. Livestock operationslocated on the acreage must also develop a nutrient management plan (NRCS-590)to protect natural resources.

A nutrient management plan involves sampling soils and manures, identifyingrealistic yield goals, and calculating manure application rates based on crop removalrates, application method, and soil test values. A N-based manure application wasimplemented because the Mehlich III soil test P values for the field were less than448 kg ha−1 (NRCS-590-KY, 2001). A realistic yield goal of 9,400 kg ha−1 of corngrain was assumed. The recommended N application rate for soils in these studiesranged from 159–196 kg ha−1 (AGR-1, 2003); 168 kg ha−1 was selected to matchthe inorganic-N treatment, which was applied on June 13, 2003.

FIELD EXPERIMENTS

Research plots were established in a cooperator’s field located in Shelby County,Kentucky. The plots were blocked based on soil test P levels (Mehlich III) as medium(30 < P < 67 kg ha−1, Experiment A) and excessive (P > 224 kg ha−1 ExperimentB) according to AGR-1 (2003) recommendations for corn-grain (Figure 1). Eachexperiment included three randomized complete blocks with two replications ofthree treatments (Figure 2). Plot width was influenced by the manure applicatorand was 12.2 m with a length of 60.8 m to reduce border effects. Each plot hadan effective harvest area of approximately 6 m by 52 m. The design tested two

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 337

Figure 1. Field diagram illustrating the soil series and location of the six blocks of the field experiments

(A, medium P soil; B, excessive P soil). (ShB – Shelbyville) (LoC – Lowell).

Figure 2. (A) Plot diagram illustrating the treatments and replications of the two experiments and

three blocks within each experiment.

different manure application rates and an inorganic fertilizer control, on the meansof yield and plant and soil nutrient composition.

Experiment A was conducted predominantly on a Shelbyville soil (Fine-silty,mixed, mesic Mollic Hapludalf) with a 2–6 percent slope. Experiment B was

338 S. F. HIGGINS ET AL.

Figure 2. (B) Actual versus predicted TN for finishing barn manure samples with a 1:1 reference

line.

conducted on Shelbyville soil with a 2–6 percent slope, and Lowell soil (Fine,mixed, active, mesic, Typic Hapludalf) with a 6–12 percent slope (Figure 1). Theresearch plots and the entire field were planted with corn (Zea mays) Pioneer 34B23at 68,400 plants ha−1 on April 15, 2003. A weather station located 3.9 km from thefield provided ambient temperature and rainfall data that was comparable to a Na-tional Weather Service (NWS) County weather station located 7.2 km from the field.

MANURE APPLICATION RATES AND PLOT TREATMENT

The “producer” manure specified application rate and the inorganic-N plot ratewere determined to be approximately 88 m3 ha−1 and 168 N kg ha−1, respectively.Manure was injected approximately 11.5 cm below the soil surface using four widesweeps on March 26, and the entire plot area was disked to a depth of approximately11.5 cm five days later.

PLANT TISSUE AND GRAIN ANALYSES

Ear leaf samples were collected at silking from 10–15 plants within each plot,and analyzed for TN, K, and P, to determine the effect of application strategiesand possible interactions. Ear leaf TN was determined using a LECO combustioninstrument (St. Joseph, MI). Ear leaf P and K were determined by subjecting samplesto wet acid digestion using a combination of HCl and HNO3 acids, which was

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 339

analyzed by an inductively coupled plasma spectroscopy (ICP) (adapted from EPA3050 and 6010a).

Grain was harvested from the center 8-rows of each plot on Sept 17, 2003 andweighed using a grain cart equipped with load cells. A grain sample (approximately5 kg) from each plot was collected, ground, and analyzed for N and P content. Grainsamples were digested in concentrated sulfuric acid, in which selenized boilingchips were added. Grain N was determined using a modified Kjeldahl method(Chaney and Marbach, 1962). Grain P was determined based on the method of Fiskeand Subbarow (1925). Grain moisture was determined by drying a sub-sample fromeach plot at 103◦C for 3–4 d to correct plot yields for dry matter content.

SOIL ANALYSIS

Ten soil cores were collected from 0–15 cm in each experimental block beforethe experiment, and were used to calculate fertilizer requirements based on AGR-1 (2003) requirements. In addition, ten pre-experiment soil cores were collectedat three depths (0–7, 7.5–15 and 15–23 cm) from random locations within eachblock. Four sets of samples were collected on a per plot basis using the samesampling regime at 37 (May 2) and 58 (May 23) days after manure application.Two other sets of soil samples were collected after harvesting corn on Sept 29,2003 and in the spring of 2004 (April 27) before planting soybeans. Soil samplescollected after manure applications were prepared by compositing five soil corescollected perpendicular to the transverse of the manure injection toolbar on 18 cmincrements.

Soil samples were air dried, ground, and passed through a 2 mm sieve beforeanalysis. A Mehlich III extract was analyzed by ICP to determine phosphorus (Pm),and potassium (Km). Potassium chloride was used to extract soil nitrate (NO−

3 ),which was determined by modified Cd reduction. Soil ammonium (NH+

4 ) (Dorichand Nelson, 1983) and phosphate (PO4) (D’Angelo et al., 2001) were determinedusing a KCl extraction method. Soil pH was determined in a 10:1 water to soilsolution ratio. Soil compaction data was collected using a hand penetrometer fittedwith a 1.9 cm cone from every plot to a 23 cm depth after corn was harvested.

STATISTICAL ANALYSIS

The SAS PROC MIXED (SAS Institute, 1999 version 8.02) procedure was usedto analyze manure nutrients applied to plots, ear leaf tissue and grain yields byplot, and soil fertility level by depth and by time, for each experiment. The PROCMIXED procedure was used instead of PROC GLM because PROC MIXED isconsidered more robust, especially when analyzing data with repeated measures.Pairwise comparisons of the means were determined using the PDIFF option onthe LSMEANS statement. The standard error (STD ERR) for the differences ofthe least squares means was calculated to depict differences between treatments.

340 S. F. HIGGINS ET AL.

Different letters, based on principles of the Duncan’s multiple range tests, wereadded to depict observed differences between the least squares means.

Results and Discussion

MANURE NUTRIENT DETERMINATION AND APPLICATION RATES

The first manure sample collected from the discharge pipe leading to the slurrytanker was evaluated using the rapid on-farm procedure and models, and predictedTN and TP concentrations of 8.79 kg m−3 and 2.57 kg m−3, respectively. Thesedata were inserted into NRCS-590 worksheet No. 2 along with additional data(soil fertility, yield goal, plant available N [PAN] based on application method), toyield an application rate of 32 m3 ha−1 to meet N requirements (the NMP rate).This application rate would apply approximately 169 kg ha−1 of PAN, using acoefficient of 0.6 (NRCS-590-KY, 2001). Subsequent loads were also sampled formodel prediction and validation (Table I).

Laboratory analysis of the first to the last manure sample indicated that theN-based manure application rate did not change sufficiently to justify altering

TABLE I

Predicted TN and TP versus actual laboratory analysis for sequential loads removed from an anaerobic

earthen holding pit

Application Rate

Based on analysis Based on models

Model vs analysis

differences

Load no Solids (%) N (m3/ha) P (m3/ha) N (m3/ha) P (m3/ha) N (m3/ha) P (m3/ha)

1 8.57 32.30 14.74 35.69 14.44 3.39 −0.30

2 8.91 32.54 14.72 35.60 14.33 3.07 −0.39

3 8.52 33.10 14.96 36.05 14.89 2.96 −0.07

4 8.22 32.40 15.08 36.65 15.68 4.25 0.60

5 8.20 32.84 15.10 36.93 16.08 4.09 0.98

6 8.25 32.59 14.95 36.64 15.67 4.05 0.73

7 8.17 32.67 15.04 36.21 15.10 3.54 0.05

8 9.44 31.82 13.33 34.99 13.61 3.17 0.29

9 9.35 31.78 13.40 34.98 13.60 3.20 0.19

10 8.86 31.84 13.52 35.29 13.96 3.45 0.44

11 8.36 32.28 13.99 36.15 15.02 3.87 1.03

12 9.00 32.03 12.95 35.35 14.02 3.31 1.07

13 10.28 31.44 11.86 34.19 12.74 2.75 0.88

Avg 8.78 32.28 14.13 35.75 14.55 3.47 0.42

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 341

TABLE II

As applied manure nutrient application rate differences

Type 3 tests of fixed effects (Probability > F)

Nutrient

Experiment A

Effect TN TP K

Block 0.37 0.19 0.69

Treatment 0.26 0.07 0.51

Block by Treatment 0.25 0.20 0.76

Experiment B

Effect TN TP K

Block 0.67 0.99 0.30

Treatment 0.15 0.11 0.92

Block by Treatment 0.99 0.99 0.79

application rates (Table I). Statistical analysis indicated that TN in manure loadswere not statistically different by block or treatment (Table II). The lack of vari-ability in TN applications was attributed to the fact that the change in TN be-tween the highest and lowest concentration tanker loads was only 0.50 g kg−1

(9.48 to 9.98 g kg−1) (Table I). Total solids, for these same loads, increasedfrom 8.52 to 10.28, which suggests TN is mostly in a soluble form (Table I).However, TP sample data that would be used for a P-based application rateshowed application rates would need to be changed from 14.74 m3 ha−1 forthe first load removed, to 11.86 m3 ha−1 for the last load removed (Table I).These data are in close agreement with Higgins et al. (2004b), who showedTP had a quadratic increase as loads were removed from a single manure stor-age facility. Manure application rates were not adjusted even though manure TPdata indicated increases in concentration (Table I). Statistical analysis of manureTP applications, by block and or treatment, indicated no statistical differences(Table II).

Manure TP was more variable than TN. Concentrations ranged from 2.22 to2.80 g kg−1, or 26% (Table I). The variability between lowest and highest con-centration of TN and TP occurred on the same loads (5 and 13, respectively)(Table I). Changes in TP and TN concentrations were attributed to changes in TS(%). Total solids increased in these loads from 8.20 to 10.28% (Table I), represent-ing an increase of 25.4%, which is comparable to the change in TP (25.4 versus26%). The relationship between TP and TS has been established by previous re-search (Picccini and Bortone, 1991; O’Dell et al., 1995; Rieck-Hinz et al., 1996;Scotford et al., 1998; Ndegwa et al., 2002). These data indicated that N basedapplication rates are easy to achieve using manures from the same storage facility.However, TP increased as loads were removed, suggesting producers need to be

342 S. F. HIGGINS ET AL.

aware of the TP concentration and the placement of these higher TP manure loads insoils.

Laboratory analysis of the first manure sample collected showed that therewere 9.7 kg m−3 TN and 2.52 kg m−3 TP. These data were inserted into theNRCS-590-KY (2001) worksheet in place of the predicted concentration to de-termine the application rate that should have been applied. The calculated manurerate was determined to be 29 m3 ha−1 representing a net difference of 3.0 m3 ha−1

between methods, or a difference of 17.5 kg ha−1 of PAN.Accuracy of the rapid models was determined by plotting the actual versus the

measured nutrient concentrations (Figures 3 and 4) and comparing to a 1:1 line,as demonstrated by Van Kessel et al. (1999), Agouridis and Edwards (2003) andHiggins et al. (2004a). Regressions of the actual versus predicted TN and TP valuesresulted in slopes and intercepts that were within the 95% confidence intervals of aslope of one and an intercept of zero. Additionally, the coefficient of determination(R2) provided by the regressions for verifying the models for TN and TP, 0.71 and0.79, respectively, was used to verify accuracy. Criteria outlined by Agouridis andEdwards (2003), used to evaluate the coefficient of determination, suggest thatthe rapid models were fairly successful at determining TN and TP. Manure TNprediction error was attributed to the fact that two loads of manure were removedfrom the holding pit in late December 2002 to prevent pit overflow, which alteredthe conditions of the anaerobic batch and for unknown reasons raised the TN level

Figure 3. Actual versus predicted TP for finishing barn manure samples with a 1:1 reference line.

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 343

Figure 4. Measured and historic (NWS) rainfall data by month of the year.

in the liquid fraction of the manure. This practice was documented by Higgins et al.(2004a). Quality of fit for these data suggests the models for predicting TN and TPare accurate. Therefore, the rapid nutrient determination procedure was assumed tobe an acceptable method for meeting NRCS-590 recommendations, providing theanimal operator does not alter management (diet formulation, duration of storage,etc.).

LAND APPLICATION AND FIELD MANAGEMENT

The sequence of management practices for the experimental plots is shown in Ta-ble III. The producer specified manure application rate was 88 m3 ha−1 or 512 kgha−1 of PAN, which was determined using tanker weights. Tanker weights showedthat an average of 34 m3 ha−1 or approximately 198 kg ha−1 of PAN was actuallyapplied to the NMP plots. Field application error was attributed to spillage at the be-ginning and end of each traverse resulting from the lag time between opening valvesand tractor motion combined with traveling a short distance. The difference betweencalculated and actual application rates provided an error of 18%, which was con-sidered an acceptable margin of error for a liquid material with the equipment used.

344 S. F. HIGGINS ET AL.

TABLE III

Sequence of plot management practices

Plot Management

Collected soil samples by block March 16

Injected manure March 25–26 in experiment plots (NMP rate was

approximately 29 m3 ha−1, producer rate was approximately 88 m3

ha−1). The NMP provided approximately 198 kg N ha−1 and 90 kg P

ha−1, respectively. The producer rate provided 512 kg N ha−1, 232 kg P

ha−1, respectively.

Marked plot boundaries with GPS March 28

Disked all plots March 28

Planted corn April 15

Collected soil samples by plot May 2

Collected soil samples by plot May 23

Applied inorganic N (168 kg ha−1) to control plots June 13

Collected ear leaf samples July 17

Harvested corn for grain September 17

Collected soil samples and soil compaction data by plot September 29

Collected soil samples by plot April 27

The Effects on Corn Yield and Soil Fertility froma Single Manure Application

SOIL FERTILITY

Fertilizer recommendations of 34 kg ha−1 P2O5 and 90 kg ha−1 K2O for Ex-periment A, and 34 kg ha−1 K2O for Experiment B were determined usingaveraged soil data (0–15 cm) (Table IV) collected by block before the experi-ments started. Block 1 of Experiment B was lower in P (Mehlich III) than sur-rounding blocks. Block 2 of Experiment B was also uncharacteristically higherin P and K than surrounding blocks. Extractable NH+

4 , NO−3 , and PO4 data are

included in Table IV to provide baseline data. Seeding rates of 68,400 seedsha−1 and plant populations of 67,400 plants ha−1 were not significantly differ-ent (P ≥ 0.05) across treatments, indicating germination was not affected by ma-nure application time and rate, which agrees with prior research (Sutton et al.,1982).

EAR LEAF DATA

In both experiments, leaf TN concentrations (Table V) were significantly lower(α = 0.05) in the inorganic-N fertilization treatment compared with manure treat-ments. In addition, ear leaf TN data for Experiment A showed that there were

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 345

TABLE IV

Pre-experiment soil sample data collected by block (0–15 cm)

Mehlich III KCl Extraction

P

(kg ha−1)

K

(kg ha−1)

NH4+

(mg kg−1)

NO3−

(mg kg−1)

PO4

(mg kg−1)

Medium P soil – Experiment A

Block 1 53 196 10.7 5.4 0.036

Block 2 46 176 8.6 6.3 0.020

Block 3 65 171 9.3 3.9 0.033

Avg 55 181 9.5 5.2 0.030

Excessive P soil – Experiment B

Block 1 110 204 7.1 6.9 0.101

Block 2 631 403 7.3 10.8 0.680

Block 3 529 206 9.2 8.0 0.260

Avg 423 271 7.9 8.6 0.347

TABLE V

Corn ear leaf nutrient concentrations†

Treatment Ear Leaf TN (%) Ear Leaf TP (%) Ear Leaf K (%)

Medium P soil – Experiment A

Inorganic N 2.38c 0.28a 0.98c

NMP Rate 2.59b 0.29a 1.65b

Producer Rate 2.81a 0.30a 1.98a

LSD 0.06 − 0.09

Excessive P soil – Experiment B

Inorganic N 2.38b 0.38a 1.30

NMP Rate 2.78a 0.36a 1.75

Producer Rate 2.71a 0.36a 1.81

LSD 0.10 − −†Different letters indicate statistically significant differences (P < 0.05) by column.

significant differences by treatment. Although there was approximately 2.5 timesmore manure applied using the producer application rate than the NMP applica-tion rate, ear leaf TN data for Experiment B indicated there was not a significantdifference between manure treatments (Table V). However, in Experiment B theNMP application rate produced higher, but not significantly higher, ear leaf TNconcentrations than the producer application rate.

Ear leaf TP data was not significant for any treatment in either experiment(Table V). Ear leaf K showed similar trends to the ear leaf TN data, in which all

346 S. F. HIGGINS ET AL.

the treatments in Experiment A were significantly different (P ≤ 0.05), and manuretreatments in Experiment B were not statistically different (P ≥ 0.05).

YIELDS

Grain yields in inorganic-N treatments were significantly lower (P ≤ 0.05) than ma-nure treatments in both experiments (Table VI), even though optimum agronomicN rates were used. Manure treatment grain yields (Table VI) were not statisticallydifferent (P ≥ 0.05) within field investigations, even though the producer rate ap-plied approximately 2.5 times more manure than the rapid model treatment. Thesedata indicate there was not a yield benefit for applying the additional manure.

Large differences between the inorganic-N and manure treatment yields raisedconcerns about the validity of the data especially considering that the rapid modelmanure application rate was supposed to apply the same amount of N as theinorganic-N treatment. A possible explanation for the yield difference could beattributed to a greater mineralization of organic-N. Nitrogen fractionation resultscompiled by Cabrera and Gordillo (1995) and Mathers and Goss (1979) showed

TABLE VI

Grain and surplus N and P data collected by treatment for two field experiments

Treatment

Grainyield(kg ha−1)

GrainN(%)

GrainP(%)

RemovedN(kg ha−1)

RemovedP(kg ha−1)

SurplusN(kg ha−1)

SurplusP(kg ha−1)

Medium P soil – experiment A

Inorganic N 9,100b 1.12b 0.24b 101b 22b 49b −22c

NMP Rate 12,840a 1.30a 0.27a 167a 35a 31b 55b

ProducerRate

13,210a 1.34a 0.27a 177a 35a 336a 197a

LSD 828 0.04 0.01 11 3 11 3

Excessive P soil – Experiment B

Inorganic N 9,340b 1.15b 0.27a 108b 25b 42b −25c

NMP Rate 13,000a 1.33a 0.29ab 173a 38a 25b 52b

ProducerRate

13,930a 1.38a 0.31b 192a 43a 321a 189a

LSD 1,000 0.03 0.02 9 3 13 4

Surplus N and P represent the amount of nutrient removed by the grain versus what was

applied by manure and inorganic sources.

† Different letters within the same column indicate statistically significant differences (P ≤0.05).

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 347

that PAN for swine manure was approximately 90% during the first year, which issubstantially higher than the NRCS coefficient of 60% used to calculate availableN in this study. Furthermore, research by Mikkelsen et al. (1995) suggests thatmoisture and temperature regimes are major factors controlling organic N reten-tion and mineralization. Weather data was compared to 30 year averages, whichindicated that spring and summer months were wetter than normal, which mighthave favored microbial activity and greater manure-N mineralization (Figure 4) aswell as promoting leaching and denitrification of inorganic N from the inorganicN fertilization treatment. This would have lead to continued availability of inor-ganic N in manure treatments relative to the inorganic N fertilizer treatment duringperiods of most rapid plant N uptake (July and August).

GRAIN QUALITY AND NUTRIENT REMOVAL

There were not significant differences (P ≥ 0.05) in grain N, which is correlatedto grain protein, between the two manure treatments for either experiment (TableVI). Although grain producers are not compensated for higher grain protein, onthis farm the grain harvested from manured fields was used as feed for the hogoperation. Market hogs for this swine enterprise demonstrated a positive responseto higher protein feeds, in that hogs are able to reach market weights quicker thanhogs on lower protein diets. Therefore, the higher protein diet provides potentialfinancial benefits to the producer. However, the additional manure provided by theproducer rate did not increase grain N concentrations beyond the NMP rate, andindicates that applying the additional manure was an inefficient use of nutrients.

Grain P (Table VI) was significantly different by treatment in Experiment A (P ≤0.05), and approached significance in Experiment B (P ≤ 0.10). In medium P soils(Experiment A), grain P was not significantly different in the manure treatments.In excessive P soils (Experiment B), the inorganic-N treatment and the rapid modeltreatments were not significantly different. Significant differences in the producergrain P data could be attributed to the higher manure TP applied using the producermanure rate. The excessive P soil experiment produced an imbalance of P, whichwas attributed to higher soil test P concentrations.

Nutrient removal and surplus N and P values (Table VI) were calculated by mul-tiplying element concentrations by yield, which was subtracted from the calculatedN and P in the manure applications. The surplus data, which was calculated usingSAS – PROC MIXED (SAS Institute, 1999) demonstrated that the producer ratesignificantly (P ≤ 0.001) over applied N in both experiments, whereas surplus Nfor the rapid model manure application rates were not significantly different fromthe inorganic-N treatment (Table VI). Surplus P data (Table VI) were significantlydifferent by treatment (P ≤ 0.001) and also indicated that the producer manureapplication rate provided a tremendous amount of unutilized P.

348 S. F. HIGGINS ET AL.

EXTRACTABLE NO−3 AND NH4

+

The primary reason for collecting manure samples on May 2 and 23 was to evaluatechanges in soil P. These samples were also used to evaluate extractible NO−

3 andNH+

4 . However, it should be noted that the inorganic-N application was not madeuntil June 13 (Table III). Therefore, the NO−

3 and NH+4 data for the inorganic-N

treatment on May 2 and 23 should not be compared against manure treatmentsuntil September 29 (Tables VII and VIII). Nitrate concentrations in the producerrate and NMP rate treatments were not significantly different (P ≥ 0.05) in soilsamples collected on May 2 and May 29 (Tables VII and VIII), with one exception;data from Experiment B (Table VIII) collected on May 2 for the 0 to 7.5 cm depthwere all different by treatment (P ≤ 0.05). Even though the manure was injected toa depth of approximately 11 cm, NO−

3 data by depth shows significant (P ≤ 0.05)migration into the 15–23 cm depths. On Sept. 29, NO−

3 concentrations of samplescollected at the 0 to 7.5 cm depth were not significantly different for the inorganic-Nand producer treatments (P ≥ 0.05) for Experiment A (Table VII), suggesting thatthe manure N had been depleted, lost, or immobilized.

The ear leaf N and K (Table V) and soil NO−3 (Tables VII and VIII) concentra-

tions demonstrated that the Experiment B NMP manure application rate producedhigher ear leaf N and K concentrations than the producer application rate. Thisobservation was considered an inconsistency in the data, because the producer rateapplied more N. Higher N and K concentrations in ear leaf and soil NO−

3 data wereattributed to greater denitrification of the mineralized manure N. Reduction in Nwould also prevent K from being taken up based on Atterburg’s principles (Black,1993).

Rainfall data shown in Figure 4, suggests precipitation events may havecontributed to denitrification. In addition, the soil hydrology was classified asmoderate and moderately slow for Experiment A and B, respectively, suggest-ing wetter conditions in Experiment B soils. Additionally, Sutton et al. (1995)showed that greater denitrification was obtained is soils with finer texturedsoils.

There was a significant decrease in pH in Experiment A soil (Table IX) asmanure rate increased (P ≤ 0.05) for samples collected at the 7.6 to 15 cm depth,which was the same depth where the manure was injected. However, a change inpH by treatment was not significant in Experiment B (Table X) suggesting thatnitrification was suppressed in Experiment (B).

Surplus N data (Table VI) showed that concentrations for the inorganic-N andNMP treatments were not statistically different (P ≥ 0.05), supporting the idea thatmost of the N in these treatments was utilized. Actually, grain N and yield datashowed that more N was used in the NMP rate than the inorganic-N treatment.In Experiment A (Table VII), nutrient concentrations measured in soil samplescollected at 7.5 to 23 cm depth on Sept. 29 were also not significantly different

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 349

between the inorganic-N and NMP rate treatments, indicating that the NMP ratemet the target N application, and were at background levels.

Nitrate data in Experiment B (Table VIII) was similar to Experiment A (TableVII), with the exception that none of the soil NO−

3 concentrations for inorganic-Nand the rapid model were significantly different (P ≤ 0.05) for Sept. 29 (Tables VIIand VIII). Nitrate data for May 2 and 29 were higher in the NMP rate treatmentthan the producer rate at the 7.5 to 23 cm depths.

TA

BL

EV

II

KC

lE

xtr

acti

ble

NO

− 3−

N,

NH

+ 4−

N,

and

PO

4−

P(m

gk

g−1

)in

Ex

per

imen

tA

(Med

ium

So

ilP

)†

2-M

ay2

9-M

ayS

ept.

29

Dep

th

(cm

)

Sta

rtN

O3−

(mg

kg

−1)

Ino

rgan

ic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

Ino

rgan

ic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

Ino

rgan

ic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

NO

3−

−N

(mg

kg

−1)

0–

7.5

7.3

11

.3b

66

.9a

93

.3a

15

.68

.8b

34

.1a

44

.4a

7.6

7.8

a5

.4b

9.4

a0

.9

7.5

–1

53

.16

.6b

48

.4a

70

.2a

13

.45

.9b

47

.0a

55

.4a

11

.43

.7b

3.5

b9

.4a

1.3

15

–2

32

.94

.6b

20

.8a

28

.4a

6.8

5.4

b3

8.4

a4

9.4

a9

.23

.1b

3.3

b1

3.0

a2

.4

NH

4+

−N

(mg

kg

−1)

Sta

rtN

H+ 4

(mg

kg

−1)

0–

7.5

10

.36

.3b

13

.7b

33

.8a

7.0

6.7

b8

.7b

12

.0a

1.7

4.2

3.8

4.3

7.5

–1

58

.75

.5b

27

.8b

17

2.2

a2

5.3

5.5

b2

4.3

b6

9.6

a1

1.0

2.4

b2

.9b

3.7

a0

.3

15

–2

37

.33

.8b

5.6

b4

1.6

a1

4.5

4.4

b7

.3b

27

.1a

5.2

3.4

2.9

3.2

PO

4−

N(m

gk

g−1

)S

tart

PO

4

(mg

kg

−1)

0–

7.5

0.0

44

0.0

7b

0.1

4ab

0.2

2a

0.0

60

.09

b0

.17

b0

.37

a0

.12

0.0

6b

0.0

8b

0.2

8a

0.1

7.5

–1

50

.01

50

.02

b0

.05

b0

.31

a0

.13

0.0

2b

0.0

6ab

0.1

0a

0.0

30

.02

b0

.02

b0

.10

a0

.02

15

–2

30

.01

60

.02

b0

.04

a0

.03

b0

.01

0.0

20

.03

0.0

2−

0.0

20

.02

0.0

3

†Dif

fere

nt

lett

ers

ind

icat

est

atis

tica

lly

sig

nifi

can

td

iffe

ren

ces.

Not

e:S

tati

stic

ald

iffe

ren

ces

are

dep

icte

do

ntr

eatm

ent

dif

fere

nce

sth

atw

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sig

nifi

can

tb

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ww

ith

ind

ate

usi

ng

ρ≤

0.1

0.

TA

BL

EV

III

KC

lE

xtr

acti

ble

NO

− 3−

N,

NH

+ 4−

N,

and

PO

4−

P(m

gk

g−1

)in

Ex

per

imen

tB

(Ex

cess

ive

So

ilP

)†

2-M

ay2

9-M

ayS

ept.

29

Dep

th

(cm

)

Sta

rtN

O3−

(mg

kg

−1)

Ino

rgan

ic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

NO

3−

−N

(mg

kg

−1)

0-7

.51

31

1.0

c7

0.3

b1

10

.4a

7.5

11

.6b

34

.5a

39

.7a

10

.38

.0b

7.9

b1

1.3

a1

.3

7.5

-15

4.1

7.3

b7

1.1

a5

7.2

a1

3.3

7.3

b5

2.9

a5

0.3

a1

6.3

3.3

b4

.5b

8.9

a1

.4

15

-23

2.7

56

.3b

29

.9a

26

.3a

8.1

6.1

b4

8.3

a4

3.7

a1

3.6

2.6

c4

.1b

11

.3a

0.7

NH

4+

−N

(mg

kg

−1)

Sta

rtN

H+ 4

(mg

kg

−1)

0-7

.58

.65

.7b

13

.8b

38

.5a

7.1

6.7

b9

.3ab

13

.0a

2.5

4.6

4.4

4−

7.5

-15

75

.7b

43

.5b

13

0.7

a2

3.2

5.4

b1

2.9

b7

8.9

a1

2.7

2.2

b2

.6b

3.4

a0

.2

15

-23

74

.3b

7.1

b1

7.8

a5

.84

.6b

8.8

b2

4.2

a5

.23

.63

.13

.6−

PO

4−

P(m

gk

g−1

)S

tart

PO

4

(mg

kg

−1)

0-7

.50

.45

50

.25

b0

.52

ab0

.65

a0

.01

60

.29

b0

.44

ab0

.68

a0

.15

0.2

40

.34

0.4

2−

7.5

-15

0.2

39

0.1

70

.24

0.3

3−

0.1

40

.24

0.3

4−

0.1

50

.18

0.4

2−

15

-23

0.1

83

0.1

70

.16

0.1

3−

0.1

30

.13

0.1

3−

0.1

70

.15

0.1

5−

†Dif

fere

nt

lett

ers

ind

icat

est

atis

tica

lly

sig

nifi

can

td

iffe

ren

ces.

Not

e:S

tati

stic

ald

iffe

ren

ces

are

dep

icte

do

ntr

eatm

ent

dif

fere

nce

sth

atw

ere

sig

nifi

can

tb

yro

ww

ith

ind

ate

usi

ng

ρ≤

0.1

0.

TA

BL

EIX

Meh

lich

III

extr

acti

ble

P(m

gk

g−1

)an

dp

Hd

ata

for

Med

ium

Pso

ils

(Ex

per

imen

tA

)†

2-M

ay2

9-M

ayS

ept.

29

Dep

th

(cm

)

Sta

rtP

m

(mg

kg

−1)

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

ST

D

ER

R

Meh

lich

III

Ex

trac

tib

le

0–

7.5

56

50

b7

8ab

91

a1

05

4b

87

b1

28

a2

24

6b

66

b1

34

a3

3

7.5

–1

52

62

4b

38

b1

41

a1

71

8b

53

a8

4a

17

20

b2

9b

94

a2

1

15

–2

32

51

5b

20

ab3

6a

61

41

52

3−

14

13

22

−P

H

Sta

rtp

H

0–

7.5

6.4

6.2

a5

.8b

5.6

b0

.26

.25

.75

.8−

6.4

a6

.1ab

5.9

b0

.2

7.5

–1

56

.66

.6a

6.2

b6

.7a

0.1

6.4

5.9

6.3

−6

.6a

6.2

b6

.2b

0.2

15

–2

36

.76

.6a

6.3

b6

.5ab

0.2

6.5

6.1

6.2

−6

.8a

6.4

b6

.4b

0.1

†Dif

fere

nt

lett

ers

ind

icat

est

atis

tica

lly

sig

nifi

can

td

iffe

ren

ces.

Not

e:S

tati

stic

ald

iffe

ren

ces

are

dep

icte

do

ntr

eatm

ent

dif

fere

nce

sth

atw

ere

sig

nifi

can

tb

yro

ww

ith

ind

ate

usi

ng

ρ≤

0.1

0.

TA

BL

EX

Meh

lich

III

extr

acti

ble

P(m

gk

g−1

)an

dp

Hd

ata

for

Ex

cess

ive

Pso

ils

(Ex

per

imen

tB

)

May

2M

ay2

9S

ept.

29

Dep

th

(cm

)

Sta

rtP

m

(mg

kg

−1)

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

Inorg

anic

N

NM

P

Rat

e

Pro

du

cer

Rat

e

Meh

lich

III

Ex

trac

tib

le

0–

7.5

35

72

80

29

83

21

26

93

02

34

42

62

29

63

38

7.5

–1

53

25

24

92

86

31

82

43

27

33

30

25

12

67

36

2

15

–2

33

17

33

92

65

27

42

74

26

02

56

29

12

74

28

3

pH

Sta

rtp

H

0–

7.5

6.4

6.2

5.9

5.9

6.3

6.0

5.9

6.3

6.2

6.1

7.5

–1

56

.56

.46

.26

.66

.56

.26

.46

.46

.46

.3

15

–2

36

.56

.36

.36

.46

.46

.36

.46

.56

.56

.5

†Dat

an

ot

stat

isti

call

yd

iffe

ren

tu

sin

gρ

≤0

.10

.

354 S. F. HIGGINS ET AL.

Adding the concentrations of NO3− and NH4

+ (Table VII and VIII), acrossdepths for May 2 and manure treatment, shows that the Experiment A manuretreatments gave concentration differences with a ratio of approximately 2.4:1, whichis in agreement with the difference in manure application rates. However, the ratiofor the Experiment B manure treatments for May 2 is less (1.8:1), suggesting thatgreater losses occurred in the producer rate treatment. In both experiments, theproducer rate treatment shows a migration of NH4

+ into the 15 to 23 cm depth,whereas in most cases the NMP rate treatment data is not significantly different(P ≥ 0.05) from the inorganic-N treatment, suggesting there was not movementthrough the soil profile.

EXTRACTABLE PO4 (PE)

Potassium chloride extractable P (PE) concentrations of soil samples collected forExperiment A (0–15 cm depth) were significantly higher (P ≤ 0.10) in the producermanure application rate than the inorganic or NMP rates (Table VII). Soil samplescollected on every date indicated that the PE concentrations for the NMP ratetreatment were not significantly different from the inorganic-N treatment. Analysisconducted on samples collected the following spring (data not shown) showed thatPE concentrations were significantly different (P ≤ 0.05) in the same depths asthe other dates (0–15 cm depth). The only other nutrient that showed statisticallysignificant differences, for either experiment, was soil test P in Experiment A soils.

Changes in PE concentrations over the dates were only significant in the NMPrate treatment, in which the concentrations merely decreased to approximately thesame level as the inorganic-N treatment. The PE data do not support a downwardmovement of PE, which has been shown in manure application research on fineparticle size soils (Sutton et al., 1995).

Extractible P (PE) data collected from Experiment B plots were significantlydifferent (P ≤ 0.05) only in the soils collected on the second date (May 29th) and atthe 0–7.5 cm depth, where the NMP rate treatment was not significantly different (P≥ 0.05) from the inorganic-N and producer rate treatments (Table VIII). Changesin PE were significant by date (P ≤ 0.10) for the inorganic–N treatment at the 15-23 cm depth, and for producer and NMP rate treatments at the 0–7.6 cm depth.Overall, the PE data were much higher in the excessive P soils than the medium Psoils (Tables IV, VII, and VIII).

Mehlich III P (M3P)Soil M3P was significantly different (P ≤ 0.05) by treatment in Experiment A(Table IX) for the first two depths, but not for Experiment B at any depth (TableX). Analysis of soil M3P by date of sample collection and depth indicated thattreatment concentrations did not change with time or move down through the soilprofile (P ≥ 0.05). Research suggests that soil texture influences whether P movesthrough the soil profile, wherein coarser textured soils allow infiltration through

EVALUATING A RAPID ON-FARM NUTRIENT DETERMINATION MODEL 355

the soil profile (Sutton et al., 1995). In addition, Laboski and Lamb (2003) showedthat manure applications did not change in most soils over a 9-month period.

Soil M3P data collected before the experiment began (Table IV) indicated thatP fertilizer was needed at 34 kg P2O5 ha−1 for the medium P soil (Experiment A).Although P fertilizer was not added to the inorganic-N treatment, manure applica-tions provided 90 kg P ha−1 and 232 kg P ha−1, for the NMP rate and producer ratetreatments, respectively (using load application averages). However, ear leaf P con-centrations indicated P was not significant by treatment in Experiment A plots. Inaddition, yield differences between the two experiments indicated that soil M3P didnot significantly contribute to yield, even though pre-experiment soil M3P levelswere approximately 55 and 423 kg ha−1 for Experiments A and B, respectively.

Conclusions

Regressions of actual versus predicted manure TN and TP concentrations showedthat a rapid on farm derived model was accurate in predicting manure TN and TP(P ≤ 0.05) and developing a nutrient management plan. The NMP manure applica-tion rate produced grain yields that were significantly higher than inorganic-N treat-ments, and the NMP rate also produced concentrations of extractable P and NH4

+

that were not significantly different (P ≥ 0.05) from the inorganic-N treatment.Crop yield and grain N concentrations were not significantly different between thetwo manure rates, even though the producer determined rate was approximately2.5 times higher than the NMP rate. Grain yields, ear leaf N, and surplus N dataindicated that the higher application rate determined by the producer did not con-tribute to yields and possibly became a potential pollutant. In one field experiment,ear leaf N and K, soil pH, NO3

−, and NH4+ data suggested the higher manure rate

led to denitrification in the soil.Analysis of grain N and P, and ear leaf tissue N and P demonstrated that the

NMP manure application rate that met crop requirements. Mehlich III extractible Pand KCl extractable PO4 in the producer rate treatments were significantly different(P ≤ 0.05) and approached significant differences (0.10), respectively, relative to theinorganic-N and NMP treatments, whereas the NMP rate and inorganic-N treatmentwere not significantly different from each other. The field experiment conductedin excessive P soils did not produce significant changes in Mehlich III P. A lackof significant Mehlich III P data in this experiment suggests that inferences aboutthe application of manure to soils containing high concentrations of extractable Pare not significant, which is contrary to previous research. It is believed that thesite specific variability or variance in soil sample analysis was sufficiently large toobscure differences.

The on-farm rapid model approach was a viable method for meeting NRCS-NMP recommendations while maintaining yields, and could be used to reduce the

356 S. F. HIGGINS ET AL.

increase in soil test P, soluble P, NO3−, and NH4

+ compared to the rate used by thisproducer. These data suggest that using an on-farm determined nutrient availabilitymode is a useful method for applying swine manure to meet regulatory requirementsand crop requirements. Using this approach will enable producers to take advan-tage of the fertility value of manures while minimizing potential environmentaldamage.

Acknowledgments

The authors extend their appreciation for the statistical assistance of Marie Gantz,Statistics Department; chemical analysis by Frank Sikora, Danny Reid, and RickWells, of Regulatory Services; the assistance of Jim Crutchfield and Tami Smithfor conducting lab analysis; and the cooperation of Jim Ellis, co-owner, Worth andDee Ellis Farms in Shelbyville KY. Without their assistance this study would nothave been possible. Funding for this project was provided in part by a grant fromthe General Assembly of the Commonwealth of Kentucky – Senate Bill 271.

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