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a Monsanto Company, 1920 Fifth St., Davis, CA 95616
b Dep. of Agronomy, 1575 Linden Dr., Univ. of Wisconsin, Madison, WI 53706
c Dep. of Agricultural and Applied Economics, 427 Lorch St., Univ. of Wisconsin, Madison, WI 53706. Funded by CSREES project WIS0 142-4897
* Corresponding author (trenton.floyd.stanger{at}monsanto.com).
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ABSTRACT |
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 TOPNOTES ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Abbreviations: AA, continuous alfalfa • CA, corn-alfalfa • CC, continuous corn • CCCAA, corn-corn-corn-alfalfa-alfalfa • CCOaAA, corn–corn–oat with alfalfa seeding–alfalfa–alfalfa • CS, corn–soybean • CSCOaA, corn–soybean-corn-oat with alfalfa seeding-alfalfa • FDSD, first-degree stochastic dominance • N, nitrogen • NASS, National Agricultural Statistics Service • SDSD, second-degree stochastic dominance. Italics in a rotation code indicate the phase of the rotation under discussion.
a Monsanto Company, 1920 Fifth St., Davis, CA 95616
b Dep. of Agronomy, 1575 Linden Dr., Univ. of Wisconsin, Madison, WI 53706
c Dep. of Agricultural and Applied Economics, 427 Lorch St., Univ. of Wisconsin, Madison, WI 53706. Funded by CSREES project WIS0 142-4897
* Corresponding author (trenton.floyd.stanger{at}monsanto.com).
Received for publication November 17, 2006.
Yield comparisons do not provide the appropriate basis for decision-making regarding cropping systems. The dominant factor influencing the adoption of cropping systems is economics. The objective of this 15-yr study was to evaluate the long-term effect of four N fertilization treatments on the economic returns of seven crop rotations in Wisconsin, based on annual market prices and production costs. The seven crop rotations were continuous corn (Zea mays L.) (CC), continuous alfalfa (Medicago sativa L.) (AA), corn-soybean [Glycine max (L.) Merr.] (CS), corn-alfalfa (CA), corn-corn-corn-alfalfa-alfalfa (CCCAA), corn-corn-oat (Avena sativa L.) with alfalfa seeding-alfalfa-alfalfa (CCOaAA), and corn-soybean-corn-oat with alfalfa seeding-alfalfa (CSCOaA). The four N treatments were 0, 56, 112, and 224 kg N ha–1 for the corn phase. Across all crop rotations, the average return was greatest for the 112 and 224 kg N ha–1 treatments, which returned on average $32 and $85 ha–1 more than the 56 and 0 kg N ha–1 treatments, respectively. Across all N rates, average returns were highest for the CS rotation. The CS rotation returned $58 ha–1 more than the CSCOaA and CCOaAA rotations, $129 ha–1 more than the CCCAA rotation and AA, $224 ha–1 more than the CA rotation, and $269 ha–1 more than CC. Under second degree stochastic dominance, the stochastically efficient treatments were CS at all N rates and CC at 224 kg N ha–1. All other cropping systems were inefficient relative to these five treatments (i.e., they would not be chosen by a risk-averse decision maker). This research shows that the most profitable systems (CS) remain the most efficient when risk is taken into consideration. However, these results also show that when 224 kg N ha–1 is added, risk can be reduced for continuous corn. Individual circumstances will dictate the optimal choice among the efficient rotations.
Abbreviations: AA, continuous alfalfa • CA, corn-alfalfa • CC, continuous corn • CCCAA, corn-corn-corn-alfalfa-alfalfa • CCOaAA, corn–corn–oat with alfalfa seeding–alfalfa–alfalfa • CS, corn–soybean • CSCOaA, corn–soybean-corn-oat with alfalfa seeding-alfalfa • FDSD, first-degree stochastic dominance • N, nitrogen • NASS, National Agricultural Statistics Service • SDSD, second-degree stochastic dominance. Italics in a rotation code indicate the phase of the rotation under discussion.
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INTRODUCTION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Crop rotation has been shown to increase corn yield 5 to 30% and soybean yield from 8 to 16% compared to continuous production of either crop (Copeland et al., 1993; Crookston et al., 1991; Lund et al., 1993; Peterson and Varvel, 1989a, b; Singer and Cox, 1998a; West et al., 1996). Crop rotation has also been shown to improve N use efficiency by reducing requirements for external input of fertilizer N. Compared to CC, Kanwar et al. (1997) reduced fertilizer N inputs 17% for a CS rotation and reduced NO3–N leaching loss through subsurface tile lines. Bruulsema and Christie (1987) found that a single-year of alfalfa or red clover (Trifolium pretense L.) was equivalent to corn yields obtained from applying 90 to 124 kg ha–1 of fertilizer N. Fox and Piekielek (1988) extended the evaluation period to 3 yr of alfalfa managed as hay and reported that there was no significant grain yield response to fertilizer N for first-year corn.
One result of increased crop yield and improved N use efficiency with crop rotation may be more favorable economics or net return to producers. Profit margins for production of most crops are very narrow, and producers seek sustainable cropping systems that provide consistent return on investment (Clegg and Francis, 1994). For example, when averaged for moldboard plow and chisel tillage systems in an Iowa study, Chase and Duffy (1991) reported a return to land, labor, and management for CC of $351 ha–1 compared to $363 ha–1 for CS. The CS rotation also required 17% less N fertilizer (168 vs. 202 kg ha–1). In New York, Singer and Cox (1998b) reported greater net return for a CS rotation ($250 ha–1) than for CC ($193 ha–1) or a 3-yr soybean-wheat/red clover-corn rotation ($133 ha–1) with reduced inputs. Katsvairo and Cox (2000) calculated that a CS rotation with reduced inputs returned $99 ha–1 compared to $12 ha–1 in CC with full inputs and chisel tillage. Zacharias and Grube (1984) reported that in an Illinois study, a soybean-corn-corn rotation had greater net returns ($286 ha–1) compared with a corn-soybean-wheat rotation ($224 ha–1) and continuous corn ($188 ha–1) in the presence of herbicides. Similarly, Hesterman et al. (1986) compared the profitability of CA, CC, and CS rotations and concluded that a CA rotation provided the greatest returns. They also concluded that to amortize alfalfa establishment costs over a longer period of time, the crop should be managed as forage rather than a green manure.
The merits of extended crop rotations that include forage or pasture crops have been debated for centuries (Karlen et al., 1994). Key benefits include increased carbon retention in the surface horizon and a more even distribution of labor needs and risk due to climate or market conditions than those involving only grain or fiber crops (Magdoff and van Es, 2000). Despite those benefits, the infrastructure developed and devoted to corn and soybean has resulted in a 500% increase in harvested area and 800% increase in soybean production between 1950 and 2003 (USDA-NASS, 2004). During that same period, oat production declined 90%, and although hay production increased because of better yields, the land area devoted to it decreased more than 15%. This occurred for several reasons including simplicity and similar equipment requirements as farm size increased, commodity programs that emphasized short-term profit, public and private research, and development efforts devoted to genetic improvement of corn and soybean, and increased food and industrial uses for both corn and soybean oils and various by-products (Karlen, 2004). Expansion of the simplified corn/soybean system has tremendous economic and world trade benefits because of the many products and materials developed from those crops (Karlen et al., 2006).
Although the net returns are often the most requested piece of data when crop rotation studies are reported to producers, very few experiments have provided that information, especially those that include both forage and grain crops (Singer et al., 2003). Farmers must select cropping systems based on expected market returns and risks associated with those returns (Young and Westcott, 1996). Cropping systems depend greatly on the mix and sequence of crops or crop rotations that farmers select (Francis and Clegg, 1990). Crop rotations, however, interact with management inputs (Riedell et al., 1998). An economic analysis of cropping systems that include different crop rotation and management inputs is important, because it helps in identifying the most profitable cropping systems based on current market prices.
An economic analysis should be the dominant factor for evaluating different cropping systems (Wesley et al., 1995) and assessing the riskiness of alternative rotations requires yield data on complete rotations over time (Meyer-Aurich et al., 2006). The objective of this study was to determine the economic profitability and risk based on annual market prices and production costs of 28 crop rotation by N treatments that feature seven crop rotations (CC, AA, CS, CA, CCCAA, CCOaAA, and CSCOaA) and four N treatments (0, 56, 112, and 224 kg N ha–1) for the corn phase.
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MATERIALS AND METHODS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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The study was located on Rozetta silt loam (fine-silty, mixed, superactive, mesic Typic Hapludalfs) soil. A randomized complete block in a split-plot design with two replications of 28 rotation by N rate treatments was established. Main plots consisted of seven crop rotations (CC, AA, CS, CA, CSCOaA, CCCAA, and CCOaAA). Subplots consisted of four N treatments (0, 56, 112, and 224 kg N ha–1), for the corn phase. There were some changes in N rate since the study was initiated, but since 1977, the annual rates have not changed. To test the rotation effect each crop phase of every rotation is represented each year. To accommodate all possible crop phases of the rotations and four fertilizer treatments, 168 plots (6.1 by 9.1 m) were established in 1966. Thus, for CC, there was one plot within each replication, and for CS there was one corn plot and one soybean plot within each replication.
Nitrogen fertilizer treatments were broadcast by hand each spring as ammonium nitrate (NH4NO3). Tillage has varied over time. Corn following corn and oat and alfalfa seedbed preparation has always been fall chisel plowed followed by spring disking and cultimulching before planting. Corn following soybean has been no-till since 1994, while corn following alfalfa and soybean following corn have been no-till since 1999. Soil fertility samples were collected and analyzed every 3 yr, and uniform rates of P and K fertilizers were applied as needed to maintain optimum to high soil-test levels. Herbicides and cultivation were used for weed control as needed following best management practices. Cultivars varied over time but were always improved selections developed for the region. The alfalfa, which was seeded with oat, has not been harvested during the seeding year following oat harvest. For alfalfa that was independently established, two harvests were taken during the seeding year, except for rotations with 1-yr alfalfa, where the alfalfa was killed during the fall of the same year following a third cutting by plowing (before 1999) or through the use of appropriate herbicides (2000 onward). For rotations with 2 or 3 yr of alfalfa following establishment, three harvests were taken. The continuous alfalfa plots were established in 1977 and the prior rotation was a corn-oat with alfalfa seeding-alfalfa-alfalfa-alfalfa rotation with four N rates. Even though, no N treatments have been applied to AA, the established plots were maintained and will be reported separately in the analysis.
Profit associated with the various crop rotations was computed by estimating the variable and fixed costs of production as outlined by Duffy (1993–2004) and subtracting them from the potential income calculated using actual yields and the marketing year average Wisconsin crop prices received for those years from the NASS (National Agricultural Statistics Service) database. The potential impact of government support payments on cropping system choices was considered, but we chose not to use them for this analysis, as one of the goals of this research was to investigate cropping systems that do not rely on subsidies to be profitable. Production costs were estimated for each year using the actual cultural operations and equipment used, as listed in the field records. Pesticide and fertilizer rates have been adjusted to reflect what was actually applied on the various crops in the rotations. Sources for pesticide prices came from field records, NASS, and University of Wisconsin Extension specialists. Based on soil tests, lime was applied before the 1992 and 2004 growing seasons. Cost of lime was based on purchase price, spreading cost, and amounts applied, and then prorated over 10 yr to determine the cost per year (L.G. Bundy, personal communication, 2006). Crop insurance costs reflect the mix of multiple peril, revenue, and hail insurance, as well as noninsured acres. Labor has been treated as a fixed cost, since most labor on Wisconsin farms is supplied by the operator, family, or permanent hired labor. The hours per crop acre includes not only field work but also time for maintenance, travel, and other activities related to crop production. Equipment costs reflect a fleet consisting of both new and used machinery. Costs of machine operations were based on the 1989, 1996, 1998, and 2000 Crop Production Practices Survey conducted by the Iowa Agricultural Statistics Service (Duffy, 1993–2004). Data on oat straw which was removed following harvest was not kept. Straw yields were assumed to be 2,240 kg ha–1 according to Duffy (2004) and price based on the average auction price for straw from Weekly Indiana Hay and Straw Prices (Sept. 2000–Jan. 2004) at http://www.agry.purdue.edu/ext/forages/links.htm; verified 21 Sept. 2007.
Yield and profitability data were subjected to an analysis of variance using the PROC MIXED procedure (Littell et al., 1996) of SAS (SAS Inst., 2002). For determining the expected mean squares and appropriate F tests in the analysis of variance, random effects were year, rep(year), and rep by rotation (year). Least square means of the fixed effects were computed, and the PDIFF option of the LSMEANS statement was used to display the differences among least square means for comparison. This option uses Fisher's protected least significant difference, and comparison was conducted at P 
0.05. For calculating individual crop rotation by N rate standard errors, repeated measures analysis (SAS Inst., 2002) with a group effect was used.
To compare risk among the four N treatments by seven crop rotations, stochastic dominance analyses (Hanoch and Levy, 1969) were performed. Our approach was similar to Lowenberg-Deboer and Aghib (1999), who employed stochastic dominance to evaluate the economics of site-specific management. Using stochastic dominance, we complete a pair-wise ranking of net income from the treatments. Both first-degree stochastic dominance (FDSD) and second-degree stochastic dominance (SDSD) analyses were performed.
Stochastic dominance compares cumulative distributions of net income based on two observations about human nature: (i) most people prefer more to less, and (ii) most people prefer less risky outcomes (Lambert and Lowenberg-DeBoer, 2003). First-degree stochastic dominance assumes decision makers prefer more to less, and states that an alternative is preferred over others if it provides a higher outcome at every level of probability. A sufficient condition for one treatment, with cumulative density function F, to first-order dominate another treatment with cumulative density function G, is
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Stochastic dominance tests were performed by covariate analysis of net income using the PROC MIXED procedure (Littell et al., 1996) of SAS (SAS Inst., 2002). The covariate was year. For determining the expected mean squares and appropriate F tests in the analysis of covariance, random effects were rep and rep by rotation. Repeated measures analysis (SAS Inst., 2002) with the compound symmetry variance structure was used to evaluate time and space effects on risk.
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RESULTS AND DISCUSSION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Corn yields were also affected by rotation and N rate when the various rotations (CC, CCCAA, CCOaAA, and CSCOaA) were planted to a second-year corn (Table 1). For second-year corn a significant rotation by N rate was observed. Second-year corn yields were highest for CSCOaA followed by CCOaAA, CCCAA, and CC which yielded 9.3, 8.8, 8.4, and 6.5 Mg ha–1, respectively. This difference was due to adding 1 yr of soybean between the first and second phases of corn in this rotation. Soybean can supply up to 45 kg N ha–1 for a subsequent corn crop (Bundy et al., 1990). Previous research has demonstrated that when corn is grown in rotation with soybean, it yields greater than CC (Baldock et al., 1981; Crookston et al., 1991; Meese et al., 1991; Porter et al., 1997; Pedersen and Lauer, 2002, 2003). Our data also suggests that alfalfa supplied a lower but still significant amount of the total N requirement of second-year corn in the rotation sequence; however, the effect of rotating corn for improved corn grain yield appears to have diminished when comparing the second year of corn with CC.
Corn yields were also affected by rotation and N rate when the various rotations (CC and CCCAA) were planted to third-year corn (Table 1). For third-year corn a significant rotation by N rate was observed.
Crop rotation did not affect oat yields (Table 1); however residual N left over from previous corn years did affect oat yields. Oat yields following a corn N treatment of 224 kg N ha–1 averaged 0.3 Mg ha–1 (11%) greater than the 112 and 56 kg N ha–1 treatments and 0.6 Mg ha–1 (23%) greater than the 0 kg N ha–1 treatment. Previous research (Dumenil, 1954; White et al., 1958; White and Pesek, 1959; Vanotti and Bundy, 1994b) also indicates that oat yields responded significantly to fertilizer N applied in previous growing seasons and that the response was correlated with soil NO3–N resulting from previous N applications.
For first-year alfalfa a significant rotation by N rate was observed. This response varied by rotation treatment with yield increases for CA, CCCAA, and CCOaAA of 0.4, 0.2, and 0.2 Mg ha–1, respectively, while for CSCOaA alfalfa yields decreased 0.1 Mg ha–1 with increasing N rates in corn (Table 1). In each N treatment, first-year alfalfa yields were greatest and did not differ among the two 5-yr rotations when alfalfa was seeded with an oat crop (CCOaAA and CSCOaA) and lowest when alfalfa was planted without a nurse crop. This was because for rotations CCOaAA and CSCOaA alfalfa was not harvested until the year following seeding and when alfalfa was planted without a nurse crop, alfalfa was harvested the seeding year. Across all N rates, first-year alfalfa yields did differ among the six rotations. First-year alfalfa yields were highest for CSCOaA and CCOaAA followed by AA which yielded 8.5, 8.4, and 7.0 Mg ha–1, respectively. These were followed by CA and CCCAA which yielded significantly less at 4.3 and 4.1 Mg ha–1, respectively. These results appear to be driven by the fact that alfalfa yields the seeding year are significantly less than those rotations using oats as a nurse crop the previous year. Alfalfa yields were only affected by rotation when the various rotations (AA, CCCAA, CCOaAA) were followed with a second-year of alfalfa (Table 1). Second-year alfalfa yields were highest for CCCAA followed by CCOaAA and lowest for AA, yielding 8.7, 8.5, and 7.0 Mg ha–1, respectively.
Cost, Profitability, and Risk
Costs of production varied among the various crops with the highest cost associated with corn at 224 kg N ha–1 (Table 2
). Oat had the lowest production costs, which were 50% of the cost associated with corn production using the highest N rate. Production costs of soybean and first- and second-year alfalfa were higher than for oat. Higher corn production costs were mostly attributed to seed, fertilizer, and chemical costs that were relatively higher than for the other crops (Table 2). Meyer-Aurich et al. (2006) reported similar findings with corn having the highest associated costs. However, they reported soybean with the lowest production costs, which were 60% less than the costs associated with corn production, compared to our results of 53% less. Higher first-year alfalfa costs were due to seed costs when compared to the second-year alfalfa.
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A significant rotation by N rate was observed for first-year alfalfa. The highest return for the AA rotation was for the 56 kg N ha–1 treatment which averaged $18 ha–1 (12%) more than the 112 kg N ha–1 treatment. Whereas, due to establishment costs and low yields (Table 1), the smallest return in the CA rotation was at 224 kg N ha–1 treatment which lost $26 ha–1 (18%) more than the 0 and 56 kg N ha–1 treatments (Table 3). Across all N rates, average returns for first-year alfalfa were positive for the AA, CCOaAA, and CSCOaA rotations, which average $141 ha–1, while those rotations, CA and CCCAA, which were not continuous or followed a nurse crop year, averaged $–174 ha–1 (Table 3).
Overall net returns were affected by rotation, with the magnitude of the rotation response affected by applied N rates. Overall returns for CC had highest returns at 112 and 224 kg N ha–1 averaging $269 ha–1 (two-fold) more than the 0 and 56 kg N ha–1 treatments. These results show that CC is not profitable using <112 kg N ha–1. The highest returns in the CCCAA rotation were at 112 and 224 kg N ha–1 averaging $81 ha–1 (51%) more than the 0 kg N ha–1 treatment. In the CS rotation the 112 kg N ha–1 treatment averaged $92 ha–1 (30%) more than the 0 kg N ha–1 treatment, however it was not found to be significantly different from the 56 and 224 kg N ha–1 treatments. Across all crop rotations, the average return was greatest for the 112 and 224 kg N ha–1 treatments, which returned on average $32 ha–1 (19%) more than the 56 kg N ha–1 treatment and $85 ha–1 (49%) more than the 0 kg N ha–1 treatment. Across all N rates, average returns were highest for the CS rotation. The CS rotation returned $58 ha–1 (22%) more than the CSCOaA and CCOaAA rotations, $129 ha–1 (48%) more than the CCCAA rotation and AA, $224 ha–1 (84%) more than the CA rotation, and $269 ha–1 (one-fold) more than CC (Table 3). Our results were similar with Chase and Duffy (1991) and Katsvairo and Cox (2000) where they reported that CC had the least net returns and a CS rotation had the highest net returns among rotations in a chisel tillage system.
Stochastic dominance analysis of net income per hectare was conducted across systems. First degree stochastic dominance analysis failed to identify any cropping system dominating the others. The reason is that the distribution functions of net income from any two systems were found to cross (as illustrated in Fig. 1b). Given this result, we proceeded to conduct second degree stochastic dominance, under the assumption that decision makers are risk averse. Twenty-eight empirical distributions were used to compare and evaluate alternative cropping systems (Lowenberg-Deboer and Aghib, 1999). The empirical distribution was obtained by combining yield, prices, and cost for each system over the 15-yr study period. This generates a consistent estimate of the true underlying distributions, providing a basis for a stochastic dominance evaluation of profitability across cropping systems under risk (Pope and Ziemer, 1984). Stochastic dominance has the advantage of generating relative ranking without imposing a parametric structure on the distribution functions. For example, it does not require a normal distribution (Buccola, 1986). As such, using empirical distributions provides an appropriate basis for a stochastic dominance analysis of net returns across cropping patterns.
The selection of rotation and N rates by a producer depends on the net returns of the whole system and not just individual components in isolation of the other elements. When choosing among cropping systems, producers are often faced with a trade-off between increases in annual net returns and increases in income variability or financial risk. As producers become increasingly risk averse, they tend to choose cropping systems that display lower income variability (Meyer-Aurich et al., 2006).
Of the 28 crop rotation by N rate treatments, five were found to be second-degree stochastically efficient (in the sense that they were not dominated by any other cropping systems). The five stochastically efficient treatments were CS at all N rates and CC at 224 kg N ha–1 (data not shown). All other cropping systems were inefficient when compared to these five treatments. All other treatments were dominated by at least one other treatment. This means that these dominated treatments would not be chosen by any risk-averse decision maker. To the extent that most decision makers are risk averse, this provides useful information on the economic performance of the various cropping patterns. This is likely due to establishment costs related to alfalfa (machinery, seed, and fertilizer; see Table 2), higher overall prices for corn and soybean when compared to oat and alfalfa, or due to lower yield variability associated with corn and soybean when compared to oat and alfalfa.
This research shows that the most profitable systems (CS) remain the most efficient when risk is considered. According to Meyer-Aurich et al. (2006), the diversification of the rotation reduces production risk in contrast to planting corn continuously. Similar findings have been observed by Helmers et al. (2001), where they compared a CS rotation with corn and soybean planted continuously and found that production risk was reduced when the crops were planted in rotation, even though yield variance was higher in the rotated crops than for the sole crops planted continuously. Zentner et al. (2002) also found that crop diversification reduces business risk for wheat-based crop rotations in western Canada. According to Helmers et al. (2001), the benefit of crop rotations in reducing risk involves three distinct influences. First, conventionally practiced rotations involve diversification, an offsetting phenomenon where low returns in 1 yr for one crop are combined with relatively high returns from a different crop. Second, rotation cropping is generally thought to reduce yield variability compared with monoculture practices. Finally, rotations, as opposed to monoculture cropping, may result in overall higher crop yields as well as reduced production costs. However, in addition to these facts, these results also show that when 224 kg N ha–1 is added, risk can be reduced for continuous corn, by reducing yield variability.
The choice between the stochastically dominant cropping systems of CS at all N rates and CC at 224 kg N ha–1 is driven by several factors. This includes the degree of risk aversion of the producer. Note that the degree of risk aversion may vary across decision makers (e.g., depending on their wealth, credit availability, age, and familiarity/experience with these cropping systems). Individual circumstances will dictate the optimal choice among the efficient set (DeVuyst and Halvorson, 2004). This choice is further influenced by the joint distribution of yields and prices. Our analyses are based on historical prices and yields. So we have determined the ex-post ranking of cropping systems. For a decision maker, expected yields and prices are used to make decisions. If past yields and prices are judged to be good predictors of future outcomes, our analyses are appropriate. If not, a formal expectations model is needed to generate forecasted yields and prices (DeVuyst and Halvorson, 2004).
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CONCLUSIONS |
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ACKNOWLEDGMENTS |
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NOTES |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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REFERENCES |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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