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Published online 16 June 2008
Published in Agron J 100:1070-1076 (2008)
DOI: 10.2134/agronj2007.0285
© 2008 American Society of Agronomy
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NITROGEN MANAGEMENT

Evaluation of the Illinois Soil Nitrogen Test in the North Central Region of the United States

C. A. M. Laboskia,*, J. E. Sawyerb, D. T. Waltersc, L. G. Bundya, R. G. Hoeftd, G. W. Randalle and T. W. Andraskia

a Dep. Soil Sci., Univ. of Wisconsin-Madison, 1525 Observatory Dr., Madison, WI 53706
b Dep. of Agronomy, 2104 Agronomy Hall, Iowa State Univ., Ames, IA 50011
c Dep. of Agronomy, Univ. of Nebraska, 261 Plant Sci. Building, Lincoln, NE 68583
d Dep. of Crop Sci., Univ. of Illinois at Urbana-Champaign, 1102 S. Goodwin Ave., Urbana, IL 61801
e Univ. of Minnesota, Southern Research and Outreach Center, 35838 120th St., Waseca, MN 56093

* Corresponding author (laboski{at}wisc.edu).


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Recently the Illinois soil nitrogen test (ISNT) was proposed as a means to identify fields where corn (Zea mays L.) will not respond to additional N fertilizer and which may also be used to predict the economic optimum N rate (EONR). Data from 96 corn N rate response trials across Iowa, Illinois, Michigan, Minnesota, Nebraska, and Wisconsin were compiled to evaluate the usefulness of the ISNT in identifying nonresponsive fields, predicting EONR, and estimating mineralizable N. At each trial site, multiple rates of fertilizer N were applied, including zero N and nonyield limiting rates. Corn was grown following several crops. The ISNT could not accurately predict nonresponsive sites, nor could it reliably estimate EONR. Subsetting the data based on soil drainage class and previous crop did not improve the predictive capability of the ISNT even though ISNT values were significantly different among previous crops and soil drainage classes. The ISNT was strongly correlated to soil organic matter (OM) and was apparently measuring a constant fraction of total soil N (TN). The lack of correlation between the ISNT and relative N uptake (check plot N uptake/N uptake at the maximum N rate) suggests that the ISNT is not measuring the readily mineralizable fraction of soil N. Based on results of this project, the ISNT is not suggested for use in adjusting N rate recommendations for corn in the North Central Region (Corn Belt) of the United States.

Abbreviations: {Delta}Y, delta yield • EONR, economic optimum nitrogen rate • ISNT, Illinois soil nitrogen test • NFR, nitrogen fertilizer response • OM, soil organic matter • PPN, nitrate N concentration in the 0- to 30-cm soil depth at preplant sampling • PSN, nitrate N concentration in the 0- to 30-cm soil depth at pre-sidedress sampling • RUN, relative nitrogen uptake • RY, relative yield • TN, total soil nitrogen • UN0, nitrogen uptake with no nitrogen applied • YEONR, yield at the economic optimum nitrogen rate • YN0, yield with no nitrogen applied • YYMNR, yield at the yield maximizing nitrogen rate • YMNR, yield maximizing nitrogen rate


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher.

Received for publication August 23, 2007.
   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
THE ISNT WAS initially developed as a means to identify fields where corn would not respond to the addition of N fertilizer (Khan et al., 2001). The ISNT was developed by Mulvaney and Khan (2001) as a simplified version of a diffusion technique that determines different forms of N in soil hydrolysates. Based on the analysis of archived soil samples collected from N rate trials, Mulvaney et al. (2001) found that N fertilizer response in corn was related to soil amino-sugar N. They also found that as amino-sugar N increased, corn N fertilizer response decreased to zero and remained nonresponsive to the application of N fertilizer above a threshold amino-sugar N value. The ISNT was subsequently shown to be strongly correlated to amino-sugar N (Khan et al., 2001). Favorable characteristics of the ISNT that could aid in the adoption of the test are that soil samples can be taken from the 0- to 15-cm soil depth at the same time as routine soil sampling (Khan et al., 2001) and samples can be taken in the fall or spring before applying N (Barker et al., 2006a; Hoeft et al., 2001).

Other researchers have since evaluated the ISNT in other geographic regions. The ISNT was shown to predict potentially mineralizable N (R2 = 0.51) in a 24-wk laboratory incubation (Sharifi et al., 2007) using soils from New Brunswick, Quebec, Manitoba, Saskatchewan, and Maine. However, total soil N (TN) and total soil organic C along with NaHCO3 extractable-N and NaOH direct distillation-N were more highly correlated (R2 ranged from 0.60–0.74) with potentially mineralizable N than was the ISNT. Klapwyk and Ketterings (2006) compared the ability of the ISNT and pre-sidedress nitrate test (PSNT) to predict sidedress N response in corn silage production in New York. They confirmed that the PSNT is a good predictor of sidedress N response and found that ISNT alone was not. However, ISNT combined with OM concentration did provide an adequate predictor of the probability of sidedress N response. Klapwyk and Ketterings (2006) concluded that ISNT critical values above which no N response is expected should be adjusted for soil OM. In North Carolina, Williams et al. (2007b) found that the ISNT could predict economic optimum N rate (EONR), delta yield ({Delta}Y, yield at the yield maximizing N rate–zero N control yield), and N fertilizer response in corn for mineral soils only. In a followup study, the ability of the ISNT to predict EONR increased substantially when sites were separated into well or poorly drained classes (Williams et al., 2007a). Very poorly drained soils, which had the highest ISNT values with approximately average EONR, were excluded from the analysis because the authors felt that the high humic matter concentrations might be affecting the ISNT threshold levels. Because both studies (Williams et al., 2007a, 2007b) lacked nonresponsive sites, the validity of the ISNT critical level proposed by Khan et al. (2001) could not be evaluated.

In contrast, separate studies in Iowa (Barker et al., 2006b) and Wisconsin (Osterhaus et al., 2008) found that the ISNT was not predictive of the EONR for corn and could not be used to separate responsive from nonresponsive sites. In fact, in these studies, using the ISNT critical threshold proposed by Khan et al. (2001) would result in many responsive sites being categorized as nonresponsive and many nonresponsive sites being declared responsive. Both of these studies found that the ISNT was measuring a constant fraction of total soil N (TN) and was not sensitive to mineralizable N.

Additionally, Mulvaney et al. (2005) reported data from 102 N response studies conducted in Illinois in 1990 to 1992 and 2001 to 2003. They found that the ISNT had an overall failure rate of 20.6% and incorrectly identified 6.0% of the nonresponsive sites (nonresponsive sites were identified as being responsive, TYPE B failures, results in overapplication of N fertilizer) and 27.5% of the responsive sites (responsive sites were identified as nonresponsive, TYPE A failures, results in yield loss from underfertilization). Mulvaney et al. (2005) hypothesized that these failures may have resulted from a limitation to soil N mineralization or crop N utilization caused by moisture stress, weed competition, soil fertility limitation, quality/quantity of carbon inputs, or corn plant population. However, they did acknowledge that experimental data to substantiate these hypotheses was not collected. Incorrectly classifying responsive sites as nonresponsive could have a large negative economic impact to farmers as yield losses from under fertilization would have occurred, and would result in their losing confidence in the test. Fully understanding factors affecting ISNT performance is essential to providing farmers with criteria for successful use of the test.

The objectives of this paper were to use data on corn yield response to applied N from response trials across the North Central Region of the United States to assess the effectiveness of the ISNT for: (i) predicting fields where corn will not respond to additional N fertilizer; (ii) estimating optimum N fertilizer application rates; and (iii) estimating mineralizable soil N.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Data were compiled from 96 N rate studies in Iowa, Illinois, Michigan, Minnesota, Nebraska, and Wisconsin that were conducted from 2001 to 2004 as part of the regional CSREES NC-218 project, Assessing Nitrogen Mineralization and Other Diagnostic Criteria to Refine Nitrogen Rates for Crops and Minimize Losses. Results of some of these studies have been published or reported by Osterhaus et al. (2008), Barker et al. (2006b), and Laboski (2004). Summary information such as previous crop, manure history, soil texture, and drainage class for each site is provided in Table 1 .


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  		Table 1. Sites, soil characteristics, tillage, and crop history, 2001 to 2004.

 
Nitrogen rate trials consisted of either small plots or field strips where N fertilizer was applied at multiple rates, including a zero N rate and several rate increments up to a nonyield limiting rate (typically 202–375 kg N ha–1 depending on the rotation, environment, and soil series). Each rate was replicated four times. Nitrogen fertilizer was applied as anhydrous ammonia, urea–ammonium nitrate, or urea at preplant, sidedress, or split (starter plus sidedress or preplant plus sidedress). All N applications were made to minimize potential N losses. Sites were either on experimental research farms or farmer's fields. Corn was grown using locally adapted cultural practices to optimize yield.

One composite soil sample (20 cores per sample) was collected per replication before planting at depths of 0- to 15, 15- to 30, and/or 0- to 30-cm and in late spring before sidedress N application to a depth of 30 cm. However, samples were not collected from all sampling depths at each site. Preplant soil samples were analyzed for nitrate N (Brown, 1998), TN (dry combustion), OM (loss on ignition or calculation from dry combustion C analysis), and ISNT (Khan et al., 2001). For all samples, the ISNT analysis was performed at the University of Illinois within a year after sample collection to eliminate any potential lab to lab variation in ISNT values. Soil samples taken in late spring were analyzed for nitrate N. Pertinent soil data for each site are provided in Table 2 .


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  		Table 2. Soil pH, organic matter (OM), total nitrogen (TN), Illinois soil nitrogen test (ISNT), preplant soil nitrate-nitrogen (PPN), pre-sidedress soil nitrate-nitrogen (PSN), corn grain yield without nitrogen (Y0N), yield maximizing nitrogen rate (YMNR), yield at the YMNR (YYMNR), economic optimum nitrogen rate (EONR), and yield at the EONR (YEONR) at the 96 sites.

 
At physiological maturity, final plant populations were counted and whole aboveground plant samples were collected and analyzed for total N. Plant samples were not collected at every site or in all plots at a given site. At sites where plant uptake was determined, relative N uptake (RUN) was calculated as the N uptake in the zero N control treatments (UN0) divided by the N uptake in the highest N rate treatment. Corn grain yield and moisture were measured and grain yield was adjusted to 155 g kg–1 moisture content.

Analysis of variance was performed to determine N rate treatment effects on grain yield. Corn yield response to applied N was fit to either linear, linear plateau, quadratic, quadratic plateau, or spherical models. The model with the best R2 for each site was chosen by each respective researcher to represent the yield response. The yield maximizing N rate (YMNR) was determined for each site using the response model and is the N rate where yield was maximized. Delta yield ({Delta}Y) was calculated as YYMNR– yield at zero N (Y0N). Relative yield (RY) was calculated as the Y0N divided by YYMNR. Nitrogen fertilizer response (NFR) was calculated as {Delta}Y divided by Y0N. The EONR and yield at the EONR (YEONR) were calculated at the first derivative for each response model using $0.14 kg–1 ($0.30 lb–1) N fertilizer and $0.0243 kg–1 ($3.00 bu–1) corn grain. The Y0N, YMNR, yield at the YMNR (YYMNR), EONR, and YEONR for each site are provided in Table 2.

All statistical analyses were computed in SAS 9.1 (SAS Institute, 2002). For correlation and regression analyses, statistical significance was determined at a maximum probability level of 0.01, unless specifically stated otherwise, because the number of observations in the various analyses was large (n ranged from 49–96).


   RESULTS AND DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Effectiveness of the Illinois Soil N Test for Predicting N Fertilizer Response and Rate Requirement
The correlation between ISNT measured at the 0- to 15-cm and 0- to 30-cm soil depths was very strong (r = 0.98, P < 0.001), substantiating the conclusions of Khan et al. (2001) and Barker et al. (2006a). This indicates that conclusions which may be drawn based on one sampling depth are applicable to the other sampling depth as well. Thus, statistical analysis of all soil test data presented here are based on the 0- to 15-cm soil depth because there are more sites with data for all analyses from that depth. The exceptions to this are the preplant and pre-sidedress samples for nitrate N (PPN and PSN, respectively) which were collected from the 0- to 30-cm depth, and comparisons of ISNT for the 0- to 30-cm soil depth with RY.

A correlation matrix was initially used to explore whether any soil test (ISNT, OM, TN) was related to various measures of yield (Y0N, YYMNR, YEONR), crop response to additional N fertilizer (RY, {Delta}Y, NFR), and crop fertilizer N requirements (YMNR, EONR). Both ISNT and OM were significantly (P < 0.001) correlated to YMNR, YYMNR, EONR, and YEONR with r values ranging from 0.32 to 0.41 (Table 3 ) but were not significantly correlated to RY, {Delta}Y, or NFR. Soil TN was not significantly correlated to any measure of yield, crop response, or fertilizer N requirement. Lory and Scharf (2003) reported a strong linear relationship (R2 = 0.47) between EONR and {Delta}Y and suggested that {Delta}Y might be useful for developing N fertilizer recommendations. In the present study, {Delta}Y was significantly correlated to EONR (r = 0.68). The ISNT was significantly and negatively correlated (r = –0.41, P < 0.001) to EONR but was not significantly correlated to {Delta}Y (r = –0.27). Thus, the ISNT and {Delta}Y apparently explain different types and amounts of variability in EONR between sites. Additionally, the relationship between ISNT and EONR in the present study is not nearly as strong as that found by Williams et al. (2007b) (R2 = 0.90).


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  		Table 3. Correlation (r) matrix of soil test values, total N uptake in corn, and various measures of corn yield, crop response to applied N, and N fertilizer requirement. The number of observations is shown in parentheses.{dagger}

 
The relationship between ISNT and EONR was further explored with linear regression analysis (Fig. 1 , Table 3). Though statistically significant, the relationship between ISNT and EONR (R2 = 0.17) is not strong enough to use the ISNT as a practical means to predict the amount of N needed for a crop as evidenced by a low R2 and a wide range (often >100 kg N ha–1) in EONR for most ISNT values. Additionally, ISNT values above the critical level of 230 mg N kg–1 proposed by Khan et al. (2001) are associated with sites with both zero and high N requirements. Khan et al. (2001) used NFR to develop the ISNT critical level. In the present study, there was no correlation between ISNT and NFR (Fig. 1, Table 3). Even though there were several nonresponsive sites in this data set, no ISNT critical level could be determined that would separate sites with large or small NFR. These findings contradict the work of Khan et al. (2001).


Figure 1
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  		Fig. 1. Relationship between Illinois soil nitrogen test (ISNT) at the 0- to 15-cm depth and economic optimum nitrogen rate (EONR) and nitrogen fertilizer response (NFR) for 96 sites. ***Statistically significant at the 0.001 probability level. {dagger} Not statistically significant at the 0.05 probability level.

 
Critical levels for soil tests are often determined using the relationship between RY and the soil test value. There is no relationship between RY and ISNT in the present study (Fig. 2 , Table 3). Furthermore, the 230 mg kg–1 ISNT critical level published by Khan et al. (2001) was evaluated for its failure rate with regard to identifying responsive and nonresponsive sites on the basis of RY above and below the critical level. TYPE A failure rates were defined as sites with an ISNT value >230 mg kg–1 and a RY <90%. For all sites with an ISNT value >230 mg kg–1, the TYPE A failure rate was 76.1%. TYPE B failure rates were defined as sites with an ISNT ≤230 mg kg–1 and a RY ≥90%. For all sites with an ISNT value ≤230 mg kg–1, the TYPE B failure rate was 14.0%. For all 96 site-years in this study, there was an overall (TYPE A and TYPE B) failure rate of 43.8%.


Figure 2
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  		Fig. 2. Evaluation of the Illinois soil nitrogen test (ISNT) critical level (230 mg kg–1) published by Khan et al. (2001) using the relationship between INST at the 0- to 30-cm depth and relative yield (RY). TYPE A failures = ISNT > 230 mg kg–1 and RY <90%. TYPE B failures = ISNT ≤ 230 mg kg–1 and RY ≥ 90%.

 
Mulvaney et al. (2005) found that when the ISNT incorrectly predicted responsive sites (ISNT classified them as nonresponsive), the previous crop was most often soybean [Glycine max L. Merr.]. This observation is also true for the present study. Mulvaney et al. (2005) furthered suggested that a higher ISNT critical level may be needed for corn grown after soybean. In an effort to quantify the effect that previous crop had on ISNT interpretation, ANOVA with Fisher's protected LSD was used to compare the mean EONR, YENOR, {Delta}Y, and ISNT values for each previous crop (Table 4 ). There were no significant (P = 0.08) differences among mean YEONR for any previous crop. Sites with corn as the previous crop had significantly (P < 0.01) greater EONR and {Delta}Y compared to soybean and dry bean [Phaseolus vulgaris L.]. The average ISNT where soybean was the previous crop was significantly (P < 0.01) greater than the ISNT for corn and dry bean. The EONR decreased in the following order: corn > dry bean = soybean. However, ISNT increased in the following order: dry bean = corn < soybean. Linear regression was used to define the relationship between ISNT and EONR for each previous crop and for the data set as a whole (Table 5 ). Subsetting the data based on previous crop did not improve the relationship between ISNT and EONR (R2 values remained low) compared to using the whole data set. Based on our evaluation, the ISNT could not be effectively calibrated for the determination of EONR for corn regardless of previous crop.


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  		Table 4. Effect of previous crop and drainage class on mean economic optimum nitrogen rate (EONR), yield at EONR (YEONR), delta yield ({Delta}Y), and Illinois soil nitrogen test (ISNT) values.

 

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  		Table 5. Regression equations for the relationship between Illinois soil nitrogen test (ISNT) at the 0- to 15-cm soil depth and economic optimum nitrogen rate (EONR) for all data and for subsets of data based on previous crop and drainage class.

 
In research on North Carolina soils, Williams et al. (2007a) found that the ability of the ISNT to predict EONR was improved when the data were separated into soil drainage classes. In the present study, drainage class had no significant effect on EONR, YEONR, and {Delta}Y; however, the ISNT was significantly (P < 0.01) greater for poorly drained soils compared to all other drainage classes (Table 4). Furthermore, as drainage class became more poorly drained, the ISNT increased, reflecting a greater OM content under more poorly drained conditions. Williams et al. (2007a) also found that more poorly drained soils had greater ISNT values. The relationship between ISNT and EONR was evaluated for the data set as a whole and when subsetted based on drainage class (Table 5). Subsetting the data resulted in marginal change in R2 values (difference in R2 of –0.02 to 0.03).

Multiple regression was pursued as another means to evaluate the ability of ISNT to predict EONR. A stepwise regression procedure using maximum R2 and C(p) statistics was used to evaluate multi-parameter models (Freund and Littell, 2000). The best regression models for predicting EONR included two parameters, ISNT and previous crop. Adding previous crop into the model improved R2 from 0.17 to 0.26. Addition of any other parameter into the model increased R2 by <0.01. Overall the two parameter model, though significant, does not predict EONR well enough to be useful for making N rate recommendations.

Illinois Soil Nitrogen Test as a Measure of Mineralizable Soil Nitrogen
Relative N uptake (RUN) can be considered an in situ index of the relative amount of N that was available to the crop from all sources (net N mineralization, residual inorganic N, precipitation, or irrigation water) other than fertilizer N. Sites with low RUN had high NFR, although this relationship is distinctly not linear (Fig. 3 ). The RUN was also significantly (P < 0.001) correlated to the other measures of crop responsiveness ({Delta}Y and RY; r = –0.85 and 0.91, respectively), but was not significantly correlated to N fertilizer requirement (EONR or YMNR; r = –0.13 and –0.29, respectively) (data not shown). The ISNT was not significantly correlated to RUN (r = –0.24) and was moderately correlated to UN0 (r = –0.37, P < 0.01) (Table 3, Fig. 4 ). The amount of net N mineralized and nitrified between the pre-sidedress and preplant soil sampling dates was also not significantly correlated to ISNT (r = –0.26) (data not shown). The negative correlations between ISNT and RUN, UN0, and early season net N mineralization indicate that the ISNT is apparently not measuring a fraction of mineralizable and crop available soil N.


Figure 3
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  		Fig. 3. Relationship between corn nitrogen fertilizer response (NFR) and relative nitrogen uptake (RUN) for 49 sites. ***Statistically significant at the 0.001 probability level.

 

Figure 4
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  		Fig. 4. Relationship between relative nitrogen uptake (RUN) and Illinois soil nitorgen test (ISNT) for 49 sites. {dagger} Not statistically significant at the 0.05 probability level.

 
The ISNT was found to be strongly correlated to OM (r = 0.96, P < 0.001) across a wide range of OM levels (<10 to >90 g kg–1) at the sites studied. Using OM and ISNT data reported by Klapwyk and Ketterings (2006) for soils in New York, we determined that their OM and ISNT values were also strongly correlated (r = 0.95, P < 0.001). In the present study, ISNT is strongly correlated to TN (r = 0.90, P < 0.001) and seems to be measuring a relatively constant fraction of TN (Fig. 5 ). In work published by Khan et al. (2001) and Klapwyk and Ketterings (2005), the ISNT was also correlated to soil TN (Fig. 5), although those authors did not explore that relationship. The slopes of the linear regression for TN and ISNT for each data set in Fig. 5 are not significantly (P > 0.05) different from each other (data not shown). Based on the slope of the regression lines, the ISNT is measuring 14.7% of TN when all data sets are combined, with a range from 13.5 to 16.4% for the individual data sets. By comparison, the ISNT was 15.0, 13.5, and 12.6% of TN as reported by Barker et al. (2006b), Marriott and Wander (2006), and Osterhaus et al. (2008), respectively. Thus, the ISNT is apparently measuring a constant fraction of TN for a wide range of soils rather than the readily mineralizable fraction of soil organic N as would be required to assess the soil's contribution to the available N supply.


Figure 5
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  		Fig. 5. Relationship between Illinois soil nitrogen test (ISNT) and total soil nitrogen (TN) for 0- to 15-cm depth samples. NC-218 data are from the present study. Other data were published by Khan et al. (2001) and Klapwyk and Ketterings (2005). **Statistically significant at the 0.001 probability level.

 

   CONCLUSIONS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
The ISNT was not a good predictor of {Delta}Y, RY, NFR, YEONR, or YYMNR in the North Central Region and did not provide reliable estimates of EONR or YMNR. Additionally, the ISNT was unable to differentiate responsive from nonresponsive sites. The overall failure rate for the ISNT in this 96 site-year study was 43.8% with the majority of the test failures as TYPE A failures where sites predicted as nonresponsive were found to need substantial N fertilizer additions. Subsetting the data based on previous crop or drainage class did not improve the ability of the ISNT to predict EONR. Results of this work indicate that the ISNT is not a useful predictor of N fertilizer need because it is measuring a constant fraction of TN rather than a specific fraction of mineralizable N as evidenced by the lack of correlation between ISNT and RUN. Based on results of this multi-state project, the ISNT is not suggested for use in adjusting corn N rate applications in the North Central Region (Corn Belt) of the United States.


   ACKNOWLEDGMENTS
 
The authors thank Mr. Bonner Karger for his assistance in creating the database file used to archive the compiled data. We would also like to thank everyone who worked on various aspects of data collection.

All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 





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