Final Report for LNC00-179
Project Information
The effects of management on soil quality in a long-term field experiment were investigated. The trial compared two sites of differing initial fertility; management differences included rotation length, input level and type, and tillage intensity. Overall, LPI and ORG had the highest soil quality ratings. The two-year HPI, representing the vast majority of acreage in Southwest Minnesota, had the lowest soil quality. The four-year rotation was less variable and generally had higher soil quality than the two-year rotation, due to the soil-improving effects of oats and alfalfa.
Introduction:
Over the last 50 years, crop production in the Midwestern United States has become increasingly reliant on the corn and soybean rotation. Crop suitability, effective agro-chemicals, government policy, and economics have all aided in this shift (Porter et al., 2003). However producers have begun to recognize the need for alternative crops in response to increasing economic difficulty associated with the bi-culture rotation, rising environmental concerns, and the declining health of rural communities. Many traditional corn-soybean growers acknowledge the benefits of alternative managements and diversified rotations, but feel locked into the two-year rotation despite increased economic and biological sustainability in more diverse systems (Mahoney, 2001). While management decisions are normally based on marketing options and economics, soil quality is becoming a legitimate consideration in the decision making process. In a recent organic farming survey, three of the top five research priorities chosen by growers were topics related to soil management (Walz, 1999). A separate Wisconsin survey showed that farmers were interested in soil quality as a way to evaluate how well they are managing their land (Romig et al., 1995).
Cultivation of native land results in the loss of organic matter because it changes soil drainage, disturbance patterns, and amounts and types of residues put into the soil (Balesdent et al., 2000). The magnitude of this change depends largely on the type of management system used. It is estimated that the current mix of tillages used in the cornbelt will lose 3.2 x 106 t-C yr-1 over the next 100 years; widespread adoption of no-tillage would reduce this loss by 70% (Lee & Phillips, 1993). Associated with cultivation is an increase in soil erosion that often surpasses sustainable rates (Wander & Drinkwater, 2000). Twenty percent of the difference between the two systems mentioned above is attributed to a reduction in erosion (Lee & Phillips, 1993). Erosion can account for a large amount of SOM loss.
Alternative practices can have a beneficial effect on soil quality and organic matter loss. No-tillage management strategies have been shown to increase the labile organic matter fractions and percentage of stable macroaggregates in multiple studies (Wander & Bollero, 1999; Balesdent et al., 2000; Beare et al., 1994b; Wander & Yang, 2000). Organic matter content is also directly related to organic input levels (Gilley & Risse, 2000; Sommerfeldt, 1988). And crop rotation influences soil quality through both the residues the different crops return to the soil and the cultural practices associated with specific crops (Havlin et al., 1990; Grandy et al., 2002).
The objectives of this study were to comprehensively examine the soil quality differences between management systems that integrate different crop rotation lengths, tillage intensities, and conventional and organic inputs.
1) Characterize the effect of rotation and management systems on soil quality and biomass production in long-term experiments with previous high and low fertility management.
2) Evaluate the same soil quality characteristics for similar soils using paired-field or paired-farm comparisons of long-term alternative production systems with those in conventional systems or systems recently converted to alternative management.
3) Develop and implement an outreach component for dissemination of information concerning the impact of soil quality of alternative management systems.
Cooperators
Research
This study was conducted on the Variable Input Crop Management Systems (VICMS) plots at the Southwest Research and Outreach Center in Lamberton, MN. This area of southwest Minnesota is characterized by Mollisols formed in glacial till on gently undulating landscapes. The site is located on the border between the ustic and udic moisture regimes and is in the mesic temperature regime. The VICMS plots were established in 1989, and consist of two fields and eight treatments. VICMS 1 (V1) is an initially low fertility, high weed pressure site, which has had fertility built up over the years since the study began. VICMS 2 (V2) is an initially high fertility site that was historically managed according to University of Minnesota recommendations. The eight treatments represented are two crop rotations (corn-soybean two-year rotation and corn-soybean-oat/alfalfa-alfalfa four-year rotation), each managed under one of four different management systems (high, low, minimum, or organic inputs) (Table 1). Each component crop of these cropping systems is represented every year. In addition, at the V1 site there are replicate restored prairie strips in every block that serve as a “natural,” baseline comparison to the cultivated treatments.
The VICMS plots are laid out in a randomized complete block split plot design. Management types were randomly assigned to plots within crop blocks, which in turn were randomly placed within replicates. Each field is comprised of three replicates, 18 crop blocks, and 72 management plots. The plots in VICMS I are 54.8 m by 30.5 m and the plots in VICMS II are 19.8 m by 9.1 m. The restored prairie strips in V1 are located within the minimum management plots. Each prairie strip is 12.2 m by 54.8 m and the corresponding MIN plots are 18.3 m by 54.8 m.
Soil samples were collected in the fall, from Sept. 20 - Oct. 17, 2000 and Sept. 19 - 26, 2001 from each plot. Due to the high variability of the soil in VICMS I, some plots were subsampled in fall 2000 according to soil types delineated on a detailed soil map created for the station. Plots were subsampled in fall 2001 according to the variability in elevation detected from a 15m resolution digital elevation model (DEM). Plots were broken into either one, two, or three equal subplots depending on the amount of elevation change within a plot as seen on the DEM, with larger changes equaling more sampling.
Bulk soil samples were collected as cores from each plot or subplot area at a depth of 0-8 cm and 8-20 cm for biological and chemical analysis. Approximately 15 cores of 1.9 cm diameter were collected. Approximately 950 cubic centimeters of soil was collected for aggregate analysis from the 0-8 cm depth using a shovel. Every attempt was made to collect equal amounts of soil from all depth increments. The soil on the cutting edge of the shovel was discarded and not included in the sample to avoid the use of smashed or disrupted aggregates. Samples were then stored at 4¢ª C until analysis could be undertaken.
A subset of plots was used to obtain infiltration and bulk density measurements. These measures were made on a single soybean replicate set of plots in V1 and V2 that was subsampled three times, in an attempt to minimize variability.
Soils collected were evaluated using the parameters listed in Table 2.
Soil quality parameters evaluated:
Aggregate stability & size distribution (wet), wet sieving with nested sieves (Kemper & Chepil, 1965)
Bulk density, tube sampler (Blake & Hartge, 1986)
Penetration resistance, cone penetrometer
Infiltration, single ring infiltrometer (Ogden et al., 1997)
Microbial biomass carbon, chloroform fumigation/incubation (Jenkinson & Powlson, 1976)
Potentially mineralizable nitrogen, aerobic 28 d incubation (Bredja et al., 2000)
Potentially mineralizable carbon, aerobic 28 d incubation (Bredja et al., 2000)
Total organic matter carbon and nitrogen, loss-on-ignition and dry combustion (Leco Corp., St Joseph, MI)
Particulate organic matter, size fractionation (Wander and Bollero, 1999)
P, K, ca, Mg, nitrate, pH, Bray or Olsen-P, ammonium acetate extractable K, KCl extractable nitrate (Recommended Chemical Soil Test Procedures for the North Central Region, 1998)
All of the statistical analyses were conducted using the SAS V8 software (SAS Institute, 1999). The Shapiro-Wilke test was used to test the data for normal residuals, using PROC UNIVARIATE. All parameters with p-values smaller than 0.05 for this test statistic were determined to have non-normal residuals. Data was then either log or square root transformed to improve normality. If the transformations did not normalize the residuals, the data was analyzed in its original state.
The data was analyzed as a split plot design with crop blocks as whole plots split into management sub-plots. ANOVA tables and protected least significant differences (LSD) were determined using the GLM procedure. If the ANOVA indicated that a particular treatment type (crop or management) was not significant for a specific parameter, the LSD for that parameter and factor was considered not significant. When comparing managements and crops to each other, the restored prairie was excluded from the data set. Prairie was included in a separate analysis of variance to determine how it compared to the cultivated systems.
Results are summarized in the following text. Data is presented in attached tables and graphs.
Physical Soil Quality Indicators
Physical soil quality indicators provide information about how and with what strength the soil is structured. These properties are indicative of soil workability, how water will move in the soil, and how the soil will physically support plant growth. The physical soil quality indicators we tested included bulk density, water infiltration, and aggregate stability.
Bulk density was measured on a subset of plots in both V1 and V2. Although there were no significant differences (p > 0.05), bulk density across all management systems tended to increase with depth (up to 20 cm depth). The trend in surface bulk density (0-5 cm) was LPI < ORG < MIN, HPI (Figure 1). A tendency for higher bulk densities in the HPI system could be a result of greater tillage frequency. Water infiltration rates tested in V1 and V2 on a sub-set of plots showed no significant differences among management systems (p > 0.05). The percent of large stable aggregates ( > 1 mm) was greatest in LPI and lowest in HPI (Figure 2). In the two-year rotation, LPI had a significantly greater percent of stable aggregates (> 1 mm) than either MIN or HPI, with ORG equal to LPI in three of four cases. In the four-year rotation, only HPI had fewer macroaggregates (in three of four cases); and the differences between management systems were smaller (Figure 2). This suggests that the four-year rotation counteracted some of the negative effects of no organic inputs and increased tillage intensity. In both years in V1 and V2, percent aggregates greater than 1 mm were greater in the four-year rotation than the two-year rotation, but they were significantly different only in 2000 (Table 3). This is largely due to the alfalfa and oat phases of the four-year rotation; both the extensive root systems of these crops and the reduced field operations while they are growing lead to the formation and stabilization of macroaggregates. Percent stable aggregates increased by 40% (2000) and 60% (2001) during the alfalfa phase compared to corn and soybeans grown in the four-year rotation. Percent water stable aggregates in the oats were significantly greater than in soybean plots (Table 4). In this study, four-year soybeans in all years and both fields had the lowest aggregate stability compared to other crops (Table 4).
Generally, the LPI system, with reduced tillage intensity, had better results for soil physical properties than systems with higher tillage frequency, although organic inputs and the four-year rotation seemed to ameliorate the effects of tillage.
Biological Soil Quality Indicators
Biological properties are strongly affected by amendment types, residue inputs and soil disturbance patterns. Biological soil quality indicators were clearly improved in the four-year rotation for MIN and HPI at the V1 site (Figure 3). Better soil quality in the four-year rotation corresponded with yield results from 1989 until 1999, which showed that soybean yields were greater in four-year rotations across all managements, and that corn yielded better in four-year rotations in all managements except for HPI (Porter et al., 2003). Overall, the biological soil quality indicators in ORG were greater than for the other management systems, as illustrated in Figures 3 and 4 by the larger area delineated in the ORG systems than the other management systems. In almost all cases, measures of biomass, labile C and N, and total C and N were highest for the ORG system, although not always significantly so (Table 5). Measures of basal respiration showed that the ORG system was 65% higher than the other management systems in V2 and more than twice as high as the other three management systems in V1 (Table 5). All the Min-C and basal respiration data reflect the same trends and show that any one of these measures could serve as an indicator of the most labile C pool. Despite enhanced basal respiration and Min-C moist in V2 in the oat/alfalfa plots (Table 6), overall the four-year rotation tended to have lower labile carbon concentrations (although not significantly so in most cases) (Table 7). Basal soil respiration and Min-C were superior after alfalfa compared to corn and soybeans, but the effect did not carry over into subsequent years.
Two-year corn had significantly (p < 0.05) higher values than four-year corn for the following parameters: in V1 Min-C dry; in V2 basal soil respiration, surface POM-C and Min-N; and in both fields Min-C moist (Table 6). Additionally aggregate stability tended to be better in two-year corn compared to four-year corn (Table 4). This might indicate that the two-year rotation allows more active C to be maintained in the soil. However, Min-N and POM-C in deeper samples (8-20 cm) showed that these parameters tended to be greater in corn grown in a four-year rotation compared to a two-year rotation (Table 6), with significant differences in POM-C at the V1 site. This suggests that the four-year rotation may be storing organic matter a little deeper in the soil. Microbial biomass carbon was the same for ORG and LPI at both sites for both rotations, probably because lower tillage intensity in LPI compensated for its lack of organic matter inputs in LPI. Our study showed a negative response to high tillage intensity and/or chemical fertilizer; HPI, which receives the highest amounts of both fertilizer and tillage, had MBC values as low as the MIN management that receives no nutrients. MBC was significantly higher in V1 alfalfa plots than in corn plots. Despite reliance on nutrient mining in the MIN system, the naturally high organic matter content of the soils at this site allowed it to continue to support crops and maintain decent soil quality. However, yield was significantly lower in the MIN system (Porter et al., 2003) reducing the crop demand on the soil. POM-C was significantly greater in ORG at both sites, both rotations and all depths (Table 5). At both sites, POM-C in the two-year HPI surface soil (0-8 cm) was significantly lower than LPI and ORG (Table 5); this could be the combined result of no external organic matter additions and a more intense tillage regime than LPI. Some stratification was seen in LPI at V1, where POM was higher than HPI in the surface soil (0-8 cm), but at depth (8-20 cm) HPI had higher concentrations than LPI (Table 5). POM levels were expected to follow the same trends as other labile fractions, but in surface soils (0-8 cm) the POM content was greater in the two-year rotation than in the four-year rotation. However, in deeper samples (8-20 cm) POM was greater in the four-year rotation than the two-year rotation. This suggests that the four-year rotation is storing more carbon deeper in the soil, or is more dependent on root biomass as a source of organic C inputs. Surface POM-C in alfalfa plots was 34% and 40% higher than the other crops in the four-year rotation in V1 and V2 respectively. However the oat phase had less POM-C than other crops in the rotation (Table 6). Mineralizable-N in ORG was significantly (p < 0.05) greater than Min-N in any of the other managements in both V1 and V2 for both depths and both rotations (Table 5). In surface soil (0-8 cm), Min-N was greater in LPI than HPI. Min-N is affected by tillage intensity because tillage influences the amount of organic matter in the soil. Although differences were significant only at the 8-20 cm depth, Min-N tended to be greater in the four-year rotation than in the two-year rotation in V1 (Table 7). The four-year rotation also had greater amounts of total nitrogen available in V1 (0-20 cm) and the deeper layer (8-20 cm) of V2. Mineralizable N in V2 was also found to be significantly greater in alfalfa than in corn, soybean, or oat plots in the four-year rotation (Table 6). In V1, Min-N followed the same trend but the differences were not significant. In 2001, TOC was generally highest in ORG followed by LPI, which was higher than MIN and HPI. In V2 in the two-year rotation, TOC concentration in ORG (2.73%) was significantly (p < 0.05) greater than all other managements (mean: 2.44%) (Table 5). In V1 ORG also tended to be greater than HPI and MIN in the two-year rotation, although this difference was not significant (p > 0.05). In the four-year rotation ORG was only significantly greater than HPI and MIN in V1and MIN in V2. At V1, there was a trend for increased C storage in the four-year rotation, especially with depth; this could be attributed to the alfalfa and oat years of the rotation. Soils after soybeans had lower TOC than either oats or alfalfa. Due to lower residue inputs, soybeans are expected to be the crop that does the least to improve soil quality. Compared to the corn and soybean crops, soil in the oat-alfalfa plots in V1 and V2 had greater TOC, and surface TON (Table 6 and 4). Total carbon in alfalfa plots was also 16% and 17% greater than corn and soybeans in the same rotation in V1 and V2 respectively, indicating that alfalfa should help the four-year rotation store more carbon than the two-year rotation. Alfalfa can be expected to have these effects because its extensive root system significantly adds belowground biomass to the soil, and as a legume, its roots and residue naturally have relatively low C:N ratios. Additionally minimal field operations are required while alfalfa is growing, allowing stable aggregates to form and organic matter to turn over at lower rates. However during subsequent row crop years, much of this protected OM can be readily lost when tillage disrupts aggregates and the readily mineralizable alfalfa residues are decomposed.
Chemical Indicators:
Chemical analysis was performed for fall 2000 and 2001. The pH in V2 tended to be lowest in HPI and LPI (Table 8). Inorganic-N fertilization has been found to decrease pH; organic amendments on the other hand often increase pH (Rasmussen et al., 1998).
The Bray-P available phosphorus analysis indicated that the organic management system could be accumulating P although the levels are not yet excessive. This was especially evident in the two-year rotation where P levels were found to be more than two times higher in ORG than the other managements (Figure 5). In the four-year rotation, ORG was only 20% higher than HPI and LPI (Figure 5). This result could indicate that the four-year rotation uses P more effectively, or may reflect the differences in the types of manure applied in the two- and four-year rotation prior to 1997 (Table 1). In the early years of the experiment (1989 - 1996), 55% less P was applied to four-year ORG plots than two-year ORG plots on average. In the four-year rotation, alfalfa as well as the manure supply crop N needs. As a result less manure is applied to the soil. In addition alfalfa has higher P requirements than the other crops in the rotation and tended to have lower available soil P levels in the fall after it was grown. Available P was significantly greater in the two-year rotation than the four-year rotation (Table 3). Most of this difference can be attributed to the ORG treatment (Figure 5) where more P is applied in the two-year rotation.
In V2, four-year MIN had greater depletion of P than two-year MIN. This could be because overall crop growth is better in the four-year rotation due to nitrogen fixation from alfalfa. The greater crop growth results in a higher demand for P.
Over time, fertility status in the VICMS plots has decreased in all management systems except for ORG. This is especially evident in V2 (Table 8 and 9). Despite an overall decrease in fertility, none of the crops showed signs of deficiency. Nor do the recommendation tables suggest that these levels are problematic.
Restored prairie strips located within the V1 site had significantly greater amounts of all measures of labile carbon organic matter compared to the cultivated systems (Table 5). Min-N, on the other hand, was significantly lower in the prairie than LPI or ORG, which regularly receive nitrogen additions through amendments or N fixation (Table 5). The C:N ratio was significantly higher in prairie soil (12.4) compared to MIN (12.0), LPI (12.0), and HPI (12.0). Aggregate stability was significantly greater in the restored prairie (64.1 % stable aggregates > 1mm) than any of the other systems, with more than twice the large stable aggregates of LPI. Surprisingly, TOC in the prairie was not different from the cultivated management systems (Table 5).
Because of the inherent soil heterogeneity at the V1 site, we were concerned that differences in soil quality measurements would be masked by soil variability. The topographic changes in V1 are not large, but there is enough relief to create swales and swells that shed or hold water differently, causing inherent soil variability.
Stepwise regression of the V1 data set using terrain attributes as the explanatory variables in the model indicated that over 20% of the variance in TOC (r2 = 0.207, p < 0.0001) and TN (r2= 0.212, p < 0.0001) could be explained by the slope and CTI terrain attributes. Terrain attributes explained less than 4% of the variance in the labile organic matter fractions. This may be because labile organic matter fractions are more responsive to changes in management practice, while stable SOM fractions are more indicative of long-term conditions. In order to look more specifically at the effect of topography, the data was sorted by management system and the effect of terrain attribute within each management was examined (Table 10). By running the regression within management systems, more than 20% of the variance of some of the labile organic matter fractions could be explained by terrain attribute. As a whole, less of the variance in soil quality parameters was explained by terrain attributes in ORG than the other managements. This could be caused by the organic additions (manure) in ORG masking the terrain created background levels. The parameters that are more commonly thought of as slow to change or those that are affected by water status, like pH, gravimetric moisture, TOC, and TN, were better described by the regression model than the more responsive measures, Min-N, Min-C dry, basal respiration, and POM.
Biological indicators showed that organic management improved soil quality more than the other management systems in most instances. This is likely because of the manure application that increases the organic inputs into the system. LPI had better aggregate stability, which in turn should affect infiltration, water holding capacity, soil workability, and, potentially, organic matter protection. LPI had better aggregation because it had the least intensive tillage regime of all the management systems. Two-year HPI seems to lag behind the other strategies for most soil quality indicators. This could be due to a combination of the most intense tillage regime combined with no organic input additions. It was expected that MIN would perform poorly because it is an unrealistically poor management strategy. The crops grown on MIN are mining the soil of its inherent fertility without replenishment. Chemical analysis of N and P reflected this. Lowered fertility also decreases the biomass production and subsequent residue inputs in MIN, resulting in lower levels for biological and other soil quality parameters. However, MIN did not always perform the worst. This reflects well on the inherent high quality of this soil and its ability to buffer against abuse.
The four-year rotation may not have had better soil quality in all areas, but it did appear to decrease the differences among management systems, making management systems in the four-year rotation more uniform than in the two-year rotation. Alfalfa and oats appear to be the workhorses of the four-year rotation, increasing aggregate stability, reducing potential P-overloading, and increasing microbial activity. However it also appears that, in the four-year rotation, the corn and soybeans were harder on soil quality (as seen by lower parameter measurements) than the same crops in the two-year rotation.
Examining the relationship between terrain attributes and soil quality parameters indicated that topographic attributes were most powerful in explaining more stable soil quality parameters that are less sensitive to management practices. These results suggest the potential for estimating organic matter content based on topographic measurements.
Paired t-tests were used to compare soil measurements from on-farm plots in conventional and organic fields. Averaged over both years, the conventional fields had higher gravimetric moisture contents at the time of sampling (p = 0.06). Total organic carbon tended to be higher in soil planted to corn in three instances out of four (Table C-1).
Our experimental plots had shown evidence of available P building up in the organic management system. However, available P measured in both 2000 and 2001 showed that P levels were significantly higher (p=0.06) in conventional compared to organic farm fields (Table C-2). Each individual year showed the same trend but the difference was not significant.
Although aggregate stability was not significantly different in either year, it was on average higher in conventional fields in 2000 but lower in conventional fields in 2001 compared to organic fields. This could be caused by the presence of a small grain in the organic rotation. In 2000 the farmer pairs compared the same crop in the different management systems (corn to corn or soybean to soybean). Due to the different rotations each organic farmer is using, in 2001 only two of the six farmer pairs were growing the same crops and 50% of the organic fields were in small grains.
Nitrate was significantly higher in the conventional fields. This is quite likely the result of higher levels of more available nitrogen being applied as fertilizer in these fields. For the most part, nutrient status tended to be higher in the conventional fields (Table C-2).
Balesdent, J., Chenu, C., & Balabane, M. 2000. Relationships of soil organic matter dynamics to physical protection and tillage. Soil Tillage and Research. 53:215-230.
Beare, M.H., Cabrera, M.L., Hendrix, P.F., & Coleman, D.C. 1994b. Aggregate-protected and unprotected organic matter pools in conventional- and no-tillage soils. Soil Sci. Soc. Am. J. 58:787-795.
Blake, G.R. and Hartge, K.H. 1986. Bulk Density. pp. 363-367. In A. Klute (ed). Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods. Agronomy monograph no. 9. (2nd edition). American Society of Agronomy. Madison, WI.
Brejda, J.J., Moorman, T.B., Smith, J.L., Karlen, D.L., Allan, D.L., & Dao, T.H. 2000. Distribution and variability of surface soil properties at a regional scale. Soil Sci. Soc. Am. J. 64:974:982.
Grandy, A.S., Porter, G.A., & Erich, M.S. 2002. Organic amendment and rotation crop effects on the recovery of soil organic matter and aggregation in potato cropping systems. Soil Sci. Soc. Am. J. 66(4):1311-1319.
Gilley, J.E. and Risse, L.M. 2000. Runoff and soil loss as affected by the application of manure. Trans. ASAE 43:1583-1588.
Havlin, J.L., Kissel, D.E., Maddux, L.D., Classen, M.M., and Long, J.H. 1990. Crop rotation and tillage effects on soil organic carbon and nitrogen. Soil Sci. Soc. Am. J. 54:448-450.
Jenkinson, D.S. and Powlson, D.S. 1976. The effects of biocidal treatment on metabolism in soil. V. A method for measuring soil biomass. Soil Biol. Biochem. 8:209-213.
Kemper, W.D. & Chepil, W.S. 1965. Size distribution of aggregates. In C.A. Black, et al. (eds.), Methods of Soil Analysis, Part 1. American Society of Agronomy, Monograph 9, pp. 499-510.
Lee, J.J. & Phillips, D.L. 1993. The effects of trends in tillage practices on erosion and carbon content of soils in the U.S. corn belt. Water, Air, and Soil Pollution. 70:389-401.
Mahoney, P.R. 2001. Profitability and risk analysis of organic vs. conventional cropping systems in Minnesota. M.S. thesis. Dept. of Appl. Econ., Univ. of Minnesota, St. Paul.
Ogden, C.B., Van Es, H.M., and Schindelbeck, R.R. 1997. Miniature rain simulator for field measurement of soil infiltration. Soil Sci. Soc. Am. J. 61:1041-1043.
Porter, P.M., Huggins, D.R., Perillo, C.A., Quiring, S.R., & Crookston, R. K. 2003. Organic and other management strategies with two- and four- year crop rotations in Minnesota. Agron. J. 95:233-244.
Recommended Chemical Soil Test Procedures for the North Central Region. 1998. North Central Region Research Publication No. 221 (revised Jan, 1998). Missouri Ag. Experiment Station. SB 1001.
Romig, D.E., Garlyng, M.J., Harris, R.F., and McSweeney, K. 1995. How farmers assess soil health and quality. Journal of Soil and Water Conservation. 50:229-236.
SAS Institute. 1999. SAS procedures guide. Version 8. SAS Inst., Cary, NC.
Sommerfeldt, T.G., Chang, C., and Entz, T. 1988 Long-term annual manure applications increase soil organic matter and nitrogen, and decrease carbon to nitrogen ratio. Soil Sci Soc. Am. J. 52:1668-1672.
Walz, E. 1999. Final results of the third biennial national organic farmer’s survey. Organic Farmers Research Foundation. Santa Cruz, CA.
Wander, M.M. and Drinkwater, L.E. 2000. Fostering soil stewardship through soil quality assessment. Appl. Soil Ecology. 15:61-73.
Wander, M.M. & Yang, X. 2000. Influence of tillage on the dynamics of loose- and occluded- particulate and humified organic matter fractions. Soil Biol. and Biochem. 32:1151-1160.
Wander, M.M. and Bollero, G.A. 1999.Soil quality assessment of tillage impacts in Illinois. Soil Sci. Soc. Am. J. 63:961-971.
The results of this study suggest that increased organic inputs, reduced tillage, and rotations utilizing crops that minimize disturbance are the best practices to increase soil quality.
Specific outcomes of this study included:
(1) The effect of perennial forages and small grains in rotations shows that they are the most valuable components of an extended rotation in terms of improving soil quality.
(2)High tillage intensity can reduce soil quality. Hopefully organic managers will realize that strategic timing of tillage can reduce the overall amount of tillage needed and improve their soil.
(3)For producers who use manure as a primary fertility source, we showed that manure phosphorus can build up in the soil, posing a potential environmental hazard. Other sources of nitrogen should be used (such as more legumes in the rotation or as cover crops) in order to reduce the amount of manure needed to supply crop needs.
Economic Analysis
An economic analysis of the crop management systems used in the VICMS study was completed in 2001. The following MS thesis reports the findings.
Mahoney, P.R. 2001. Profitability and risk analysis of organic vs. conventional cropping systems in Minnesota. M.S. thesis. Dept. of Appl. Econ., Univ. of Minnesota, St. Paul.
Educational & Outreach Activities
Participation Summary:
Allan, D. 2001. Organic Field Day. 17 Aug., Southwest Research and Outreach Center, Lamberton, MN.
Kuratomi, M. 2002. Winter Organic Farmer Meeting. 19 Jan., Southwest Research and Outreach Center, Lamberton, MN.
Kuratomi, M. 2002. Organic Field Day. 26 July, Southwest Research and Outreach Center, Lamberton, MN.
Kuratomi, M., Allan, D.L., & Dyck, E.A. 2002. Soil quality assessment in alternative and conventional cropping systems. In Am. Soc. of Agronomy Abstr. p.151 (Poster presentation, Am. Soc. Agron. Ann. Meetings, Indianapolis, IN, 11 November).
Allan, D.L., Dyck, E.A., & Olsen, K.D. 2002. Soil quality, profitability and risk of conventional and organic cropping systems. In Am. Soc. Agron. Abstr. p.409 (Oral presentation, Am. Soc. Agron. Ann. Meetings, Indianapolis, IN, 14 November).
Allan, D.L. 2003. Minnesota Organic and Grazing Conference. 25 Jan., St. Cloud, MN.
Allan, D.L. 2003. Upper Midwest Organic Farming Conference. 28 Feb, La Crosse, WI.
Allan, D. 2003. Organic Field Day. 25 July, Southwest Research and Outreach Center, Lamberton, MN.
Kuratomi, M., Allan, D.L., & Dyck, E.A. 2003. Assessing soil quality in conventional and alternative cropping systems. (Poster presentation, ARS Dynamic Cropping Systems Symposium, Bismarck, ND, 5 Aug).
Kuratomi, M., Allan, D.L., & Dyck, E. 2003. Soil quality of alternative and conventional cropping systems in SW Minnesota. (Oral presentation, Am. Soc. Agron. Ann. Meetings, Denver, CO, 5 Nov.).