Soil Test for Active Organic Matter: A Tool to Help Assess Soil Quality

Soil Test for Active Organic Matter: A Tool to Help Assess Soil Quality

Summary

We developed a dynamic soil quality concept that relates active organic matter and soil functional capacity. Integrating farmer experience with measured chemical, physical, and biological soil properties, we developed a soil quality index sensitive to agronomic management. To develop a routine soil test for active C, we simplified alternative organic matter methods and correlated them to the index. The best method was based on permanganate-oxidation, and we developed versions for soil test labs and a farmer-friendly field kit. Long-term on-farm research was initiated to assess how the new test predicts crop response to improved soil organic matter management.

Objectives
Integrate key chemical, physical and biological soil properties into a working soil quality index (SQI) that rates soil function and reflects the impacts of soil management.

Document farmers' judgments of soil quality and incorporate them into the SQI.

Develop a quick, easy test for active soil C that correlates well with the SQI.

Refine the active C soil test with appropriate sampling times (seasonality) and sample-handling (fresh v. dried) procedures to optimize convenience and accuracy.

Evaluate the ability of the active C test to predict where improved organic matter management will increase crop yields.

Educate agriculturalists about the potential uses and limitations of the new soil test.

Methods
Over the course of three sampling seasons, the project team interviewed over 40 farmers and sampled soils from 45 paired sites on 32 farms in Maryland, Pennsylvania, Delaware, West Virginia and Virginia. The sites in each pair were identified by their farmer as having soils in either relatively good or poor condition or health. Samples were also collected from replicated experimental plots in five ongoing cropping systems studies. We then analyzed these and other soil samples for several active C fractions, as well as microbial biomass, microbial activity, and aggregate stability that were used to calculate two SQIs.

Both the test results and SQIs were evaluated for agreement with farmer SQ ratings and their sensitivity to management treatments. Experiments were conducted with several new chemistries and sample-handling protocols to refine an active C test and adapt it for routine soil testing lab use and to develop an environmentally safe, farmer-friendly field kit. Finally, we initiated a series of collaborative on-farm experiments designed to evaluate the ability of the new active C tests to predict in which fields crop yields will most benefit from investments improved soil organic matter management.

Selection of farmers for SQ ratings and contrast sites: Between the summer of 1996 and the fall of 1997, approximately 75 mid-Atlantic farmers with an interest in soil conservation were identified as potential farmer collaborators by county extension agents, Natural Resources Conservation Service (NRCS) conservationists, or the principal investigator. During short telephone interviews, perspective farmer-collaborators were asked to describe paired sites on their farm or adjacent land that they perceived to have contrasting SQ. It was stipulated that the paired sites must have similar inherent soil properties (preferably were mapped as the same soil series) but differences in SQ (one soil being in better condition than the other). Paired sites with similar inherent soil properties (such as texture, drainage, and slope) were sought, to reduce the likelihood that inherent differences would obscure relationships between management sensitive soil properties and farmer SQ ratings.

Based on the availability of paired sites and our goal of including a range of enterprises, scales of operation and geographic locations, 32 farmers were selected for participation in the study. Their farm enterprises included vegetable, fruit, and livestock operations, but cash grain production was the most common enterprise. Cropland per farm ranged from 4 to 2800 ha. On those farms with livestock enterprises, the number of animal units ranged fro 50 to 2260.

During initial farm visits, farmers showed the investigators the paired sites that they perceived to have contrasting SQ. Some of the contrasting sites were adjacent fields while others were distinct areas within the same field. Farmers were interviewed at the sites about the management history of each site, the evidence of SQ differences between paired sites, and best management practices for improving SQ. Within each pair included in the study, the soils were of similar landscape position.

Soil sampling for SQ contrast pairs: Soil samples were collected from 45 pairs of sites on 32 farms located in five mid-Atlantic states (26 in Maryland, one in Delaware, two in Pennsylvania, two in Virginia, and one in West Virginia). Following the location of the paired sites, soil samples were collected one, two, or three times, depending on the initial sampling season. Samples were collected prior to spring tillage or planting and after harvest but before tillage in the fall, to avoid periods of recent physical disturbance. At the time of each sampling, 12 to 14 cores (0-7.5 cm) were collected from each site (total volume =380 cm3 ). Samples were sealed in plastic lined bags and transported on ice to a cold storage facility where they were kept at 5oC until processed.

After drying a small subsample to determine the soil dry weight equivalent (for bulk density calculation), the sample was processed to obtain fresh, refrigerated subsamples sieved to < 4 mm for microbial analyses, an air-dry 1 to 4 mm subsample for analysis of aggregate stability, and an air-dry <2 mm subsample for chemical and physical analysis.

Soil analyses: The fresh moist soil was analyzed for the following labile C parameters: 0.5 M K2 SO4 extractable C from microwave (MW) irradiated soil (CMW), 0.5 M K2 SO4 extractable C from unmicrowaved soil (CNMW), anthrone reactive C (reducing sugar carbohydrates) in 0.5 M K2 SO4 extracts of microwave irradiated soil (CAR), and substrate induced respiration (CSIR) by the Van de Werf and Verstrate method (1987). Prior to the initiation of CSIR incubations or MW irradiation, the soil was allowed to acclimatize at room temperature for three hours. The total microbial biomass (CMB) was calculated using the function: CMB = (CMW - CNMW )* k-1 where CMW is the C extractable from MW irradiated soil, CNMW is the C extractable from non-irradiated soil and k = 0.21 is the efficiency coefficient determined by Islam and Weil (1998).
Total C and N analysis by LECO dry combustion analyzer and particle size analysis by a modified pipette method were performed on oven dry soil (0-2mm). Air-dry soil (0-2mm) was analyzed for standard soil test parameters (pH and Mehlich I extractable Mg, Ca, P and K). Macroaggregate stability (AGSTAB) analysis was performed on a 1-4 mm size fraction of air dry soil as this size range has been shown to be sensitive to soil management practices and to contain elevated concentrations of recent crop residue C (Six et. al. 2000).

The ratio between microbial biomass (CMB ) and total soil C (CT) was calculated using the function: qCMB = CMB /CT *100. The ratio between extractable C from non-irradiated soil (CNMW) and extractable C from MW irradiated soil (CMW ) was calculated using the function: qCNMW = CNMW /CMW *100.

Calculating a SQ index and three soil discrimination indices: A soil quality index (SQI) was calculated by averaging normalized values of the five individual SQ parameters that best agreed with farmer SQ ratings. The component parameters were normalized around a mean value of 50 and a standard deviation of 10 as follows: SQI = (10*pstd-1)(pi-pmean)*n-1 + 50, where n is the total number of parameters integrated, pi is the value of an individual component parameter, pstd is the standard deviation of the component parameter within a database and pmean is the mean value of the component parameter within a database. The relationship between individual soil parameters or SQIs and farmer SQ ratings was evaluated using paired T-tests on up to 75 SQ contrast site pairs (Dp = parametergood rated soil - parameterpoor rated soil). Parameters with greater positive t-scores and p(H0) < 0.05 were interpreted to be in closer agreement with farmer SQ ratings.

Development of Active Soil Carbon Test: Previous work in our lab showed that CAR is a good measure of active fraction C in soils, but the anthrone method is tedious, uses concentrated sulfuric acid and a hot water bath, is highly subject to operator variability and soil interferences, and requires fresh, field-moist soil samples. Having concluded that the method is not well suited to either a field kit application or rapid, routine laboratory soil testing, we put considerable effort into developing an alternative chemistry for determining active C in soils. A number of soil samples were used to evaluate various aspects of the alternative methods. These soils either represented farmer fields or replicated experimental plots in Maryland, New Jersey, North Dakota, Pennsylvania, central Honduras and southern Brazil. All samples were obtained from the upper 7.5 cm of the soil. The soils ranged in pH from 4.5 to 7.4, in clay content from 15 to 50%, and in total organic C content from 4 to 69 g/kg.

In order to isolate a fraction of the soil carbohydrate C that included those in the microbial biomass, we extracted soil with a salt solution after lysing the microbial cells with microwave irradiation totaling of 480 J/g of soil, applied in two steps (Islam and Weil, 1998). Neutral 0.5M potassium sulfate was used to extract the carbohydrates, followed by centrifugation and filtering to obtain soil-free clear filtrate. Aliquots of the clarified extract were then analyzed by five published methods: a) Anthrone-sulfuric acid method (Brink et al. 1960), b) phenol-sulfuric acid method, c) orcinol-ferric chloride method, d) alkaline ferrocyanide method, and e) the p-hydroxybenzoic acid hydrazide method.

We also tried several non-carbohydrate approaches. These included treating air-dry soil with a dilute H2O2 solution and measuring the carbon dioxide evolved or shaking with several concentrations of potassium dichromate to oxidize a fraction of the soil C. The final published approach tried was the 0.333M potassium permanganate oxidizable C method of Blair (1995). Although it gives potentially useful results, we found the Blair method to have several important drawbacks, including the difficulty in working with a solution as concentrated as 0.33 M, and little specificity for active fraction C. Several experiments were conducted adjusting the concentration, wavelength at which absorbance is measured, shake time, soil drying, solution concentration, soil to solution ratio, and other factors in order to develop a more soil-management-sensitive, reliable, rapid, and user friendly laboratory method to measure labile C oxidizable by neutral KMnO4. For each experimental factor, we conducted several experiments to test the effect of the modification on precession, accuracy and sensitivity to management of the C fraction measured. We used a wide a range of soils in developing the new permanganate oxidation active C test. A number of experimental field treatments were compared in order to evaluate the ability of various permutations of oxidizable C analysis to detect or account significant differences resulting from soil management practices (tillage, manuring, etc.). Soil samples collected from sites with various management histories in Pennsylvania, Brazil, Honduras and North Dakota were analyzed for several SQ parameters (above) and tested for correlation with KMnO4 oxidizable C.

We further modified the KMnO4 method for use in a field kit by eliminating the need for repeated dilution steps, and for such expensive lab equipment as centrifuge, rotary shaker, and balance. In particular, the use of a salt (0.1M CaCl2) to stimulate sedimentation in soil-KMnO4 suspension was evaluated as an alternative to centrifugation (3000 rpm for 5 min) the original method. Our final procedure for active carbon field kit is attached as Appendix 3.

Simultaneous to the development of the active C chemistry, we initiated a series of on-farm field calibration trials. To make the calibration with crop response possible, these trials required a set of rather difficult to find conditions, including: a) a pair of fields or parts of a field that the farmer considers to be contrasting in soil quality or condition, possibly due to differences in management history; b) the active C measured in the two sites must be contrasting in agreement with the farmer rating; c) both sites in a pair should have the same or similar soil types, slopes and other inherent soil properties, ideally being adjacent; d) the farmer has to be willing to establish and manage a total of 16 replicated experimental plots or strips representing two contrasting organic matter management practices of his or her choosing; e) the farmer must be willing, in any given year, to plant the same crop and provide the same management to both sites in a pair; and, finally, f) the farmer must be willing to continue the experimental treatments for several consecutive years. Such trials were established on two farms in 1999 and on three on 2000. Our goal is to run them on four or five farms, since the within-farm plots are only pseudo-replicated, the true replicates being the farms themselves. Data we collect on these trials includes a minimum set of soil quality parameters measured in spring and fall, as well as the biomass and marketable yields of the crop, and of the cover crop, if present.

Results
As seen in Table 1 (see appendix for tables and figures), in the pairs of soils identified by farmers as being in “good” or “poor” condition, soil organic matter associated parameters (microbial biomass, active C, aggregate stability) were much more closely related to farmer soil quality rating than were standard soil fertility tests (pH, available nutrients). Since the “poor” soils were usually those that farmers considered to be problem areas that produced lower yields, the data suggest that today’s mid-Atlantic farmers have typically corrected most nutrient deficiencies and pH problems, and now may find yields limited by organic matter management. The distinction between soil quality pairs was especially clear for the various C fractions measured after microwave irradiation lysed microbial cells in the soil. Among these, the CAR (anthrone reactive carbohydrate C in microwaved soil) was intended initially to be used as the active C test because earlier work had showed that it was the best predictor of a soil quality index that combined 11 different soil parameters.

Similar results were obtained from the sampling of five long-term cropping system experiments in the mi-Atlantic region. Results for the well-known Farming Systems Trial™ at the Rodale research Institute are shown in Table 2. The CAR active C parameter was the best able to distinguish among the different cropping systems, especially between the animal and a cash grain organic systems. This is important because the soils in these two systems have been reported to differ significantly with regard to their water retention, nutrient cycling and crop production soil quality functions (e.g., Drinkwater, et. al. 1998). The anthrone method we developed for active C, despite its good indication of soil quality status, was seen as problematic because of the toxic and caustic chemical involved, the tediousness of the procedure and the sensitivity to level of operator skill and experience. A one-reagent, non-toxic method for active or labile C published by Blair et al. (1995) seemed to hold promise for this use. Our early tests of this methods indicated that it, too, had serious limitations. These were mainly the difficulty of making and using the highly concentrated KMnO4 solution, and the high amount of C oxidized in the soil. The latter characteristic made the results correlate more closely with total organic C than is desirable for an active C test. An example of this problem is illustrated in Figure 1. Particular pedogenic factors such as cold temperature or poor drainage favor the accumulation of organic C in soils over long periods and most of this C is found in the highly stable passive fractions that are not actively involved with most soil quality functions. The Blair permanganate method reflected the high passive C, while our new permanganate method was more selective for the active fraction.

One of the changes we made in the permanganate method was to greatly reduce the concentration of the permanganate solution used, from 0.33 molar (so concentrated it is difficult to get that much KMnO4 to dissolve) to 0.025 molar (a 13-fold dilution). Later we further reduced this to 0.02 molar. We based this change on the reasoning that the dilute solution would react only with the most labile soil C. When we tested various solution concentration for their ability to distinguish between soils with contrasting management histories, we found that the higher concentrations were gave far lower, even non-significant, F values when an analysis of variance (ANOVA) was performed on replicated treatment plots (Figure 2). Our new dilute permanganate active carbon test proved a better predictor of soil microbial functions (such as basal respiration rate, Figure 3) than total organic matter methods. These results support the contention that the method actually estimates the active fraction of C in soils.

During the early stages of this project, the project team was also engaged with the USDA NRCS in the development of a soil health assessment guide for farmers. This work led us to see the need for a more farmer-friendly, easy to use field method for active carbon. After several false starts, our modifications of the permanganate method allowed us to develop an active C soil test kit based on a single, safe reagent. By adding a calcium salt to the solution, by altering the soil to solution ratios, and by making numerous other changes, we were able to eliminates the need for a centrifuge and other expensive lab equipment. Collaboration with NRCS scientist in North Dakota has proved that our kit is very easy to use and give repeatable results. The new active carbon method was more sensitive to soil management than were several active carbon methods we had considered earlier or methods that measure total carbon. For instance, in a sample exchange with our USDA/NRCS collaborators, the active C kit easily detected the differences between conventional tillage, no-tillage fields and native pasture on a North Dakota Mollisol. The results using the inexpensive and easy to use field kit correlated very closely (r2 = 0.98) with results obtained using a more elaborate procedure involving much more expensive laboratory equipment.

The final major focus the continued development of a program of on-farm trials designed to validate and calibrate the active carbon test and field kit. The 1999 growing season was extremely dry and a good test of the ability of our active carbon analysis to predict where better organic matter management was needed. The results from Steve Groff’s farm for 1999 are very encouraging in this regard (see Figure 1, appendix). This figure shows the results for one pair of adjacent, farmer-identified “good” and “poor” quality fields in which we established replicated plots with and without cover crops. The 2000 growing season in our region was nearly ideal in terms of temperature and rainfall distribution. Therefore, crop growth was not highly dependent on the water conserving effects of enhanced soil organic matter and structure. Corn (~180 bu/A) or soybean yields (~50 bu/A) on the collaborating farms were therefore equally outstanding with or without a cover crop. Sadly, one of our farmer-collaborators died during the year and trials on that farm came to an abrupt halt. Because of the slowness of soil changes, and the practical difficulties of on-farm research, these trials will continue for several years beyond the project-funding period in order to obtain reliable results.

Soil organic matter (total C content) was mentioned by 86 percent of the farmers interviewed as an SQ indicator that they used to rate the condition of their soils. Other SQ indicators mentioned were crop condition (69 percent) hydrologic functions (59 percent) and erosion (50 percent). Measured SQ parameters such as aggregate stability, soil carbohydrates and microbial biomass were significantly greater for the farmer-rated “good” soil in each pair of sites. Standard soil fertility test parameters such a pH and levels of available Ca, Mg, K and P did not differ between the farmer rated “good” and “poor” soils. An SQI that combined six measured parameters by standardizing each for its mean (pmean) and its standard deviation (pstd) in the entire data set of n samples [SQI = (10/pstd) *((pi-pmean)/n )+ 50] scored higher as a discriminator (paired t-test) between farmer rated “good” and “poor” soils than did any single measured parameter. A permanganate-oxidation method of measuring active C was developed as a safe, inexpensive, farmer-friendly field kit which produced results that were highly repeatable and well correlated with soil organic C and with soil functions. In preliminary results, farmer fields measuring deficient in active C by the kit gave bigger responses to the use of winter cover crops as a soil organic matter improving practice.

Impacts and Potential Contributions
Increasing numbers of farmers, especially those concerned for the sustainability of their operations, are finding that soil organic matter management is a limiting part of their production systems. Our presentations have heightened farmer interest in soil organic matter. The active carbon test and field kit developed by this project will provide a much needed tool to assess the state of soil health and direct management efforts toward those parts of a given farm that are most in need of improvements in soil organic matter. Because of our collaboration with the USDA/NRCS, we anticipate wide national dissemination and adoption of the field kit once calibration trials are completed.

Increasing numbers of farmers, especially those concerned for the sustainability of their operations, are finding that soil organic matter management is a limiting part of their production systems. Our presentations have heightened farmer interest in soil organic matter. The active carbon test and field kit under development by this project will provide a much needed tool to assess the state of soil health and direct management efforts toward those parts of a given farm that are most in need of improvements in soil organic matter.

Economic analysis
As this project did not address itself to an economic farming practice, per se, an economic analysis was not attempted. However, our findings show soils farmers identify as being problem soils and low yielding are often limited by organic matter related factors rather than fertility factors. Information on the active organic matter status of soils should have real economic value if it guides a farmer to put extra investment in organic matter (via manure, cover crops, reduced tillage, etc.) in field where crops are more likely to respond to these improvements.
Areas needing further study
Except for the recent collaboration with NRCS in North Dakota, all the soils used in this project are from high rainfall regions and are acid in nature. Further study is planned using the more alkaline soils of drier regions.

As with any soil test, field calibration is a difficult but critical task. More soils deficient in the factor in question must be evaluated under conditions that have the potential to foster a response to improvements in this variable.

Outreach
We made ten extension outreach presentations and workshops presenting project results or developing project information for farmers and agriculturalists. We also made nine presentations of results to professional scientific audiences at conferences. In addition, three refereed papers were published and three more have been submitted or are in preparation. See Appendix 5 of this report for details. We are working with USDA/NRSC on final testing of the active C kit and the NRSC plans to use it internet and local level programs to widely disseminate the kit information.
To see how one farmer-collaborator has used the project research data see Steve Groff’s Cedar Meadow Farm website “Enhancing the Environment” at http://www.cedarmeadowfarm.com/

Reported April, 2001