What's Cropping Up? Blog

Articles from the bi-monthly Cornell Field Crops newsletter

February 7, 2017
by Cornell Field Crops
Comments Off on What’s Cropping Up? Volume 27 Number 1 – January/February 2017

What’s Cropping Up? Volume 27 Number 1 – January/February 2017

The full version of What’s Cropping Up? Volume 27 No. 1 is available as a downloadable PDF and on issuu.  Individual articles are available below:

February 3, 2017
by Cornell Field Crops
Comments Off on The Soil Health Manual Series: Fact Sheets from the Comprehensive Assessment of Soil Health Training Manual

The Soil Health Manual Series: Fact Sheets from the Comprehensive Assessment of Soil Health Training Manual

Lindsay Fennell, Aaron Ristow, Robert Schindelbeck, Kirsten Kurtz and Harold van Es
Soil and Crop Sciences Section, Cornell University

The Comprehensive Assessment of Soil Health (CASH) provides a framework for measuring the physical, biological and chemical aspects of soil functioning. The assessment includes specific measurements, selected from an original list of 42 potential soil health indicators, evaluated for their relevance to key soil processes (Table 1), sensitivities to changes in management, and cost of analysis.

As a framework, CASH encompasses not only soil health testing, but also outlines field-specific planning strategies and management approaches.  In 2016, the Cornell Soil Health Laboratory released the third edition of the Comprehensive Assessment of Soil Health Training Manual (bit.ly/SoilHealthTrainingManual) (Fig. 1). The manual contains information on introductory soil health concepts, a detailed discussion of individual soil health indicators, laboratory procedures, a step-by-step guide to our soil health management framework, and an extensive list of additional resources.

Figure 1. The third edition of the Comprehensive Assessment of Soil Health Cornell Framework Manual is now available. Printed copies can be purchased or it can be downloaded for free from the CASH website.

Out of this training manual, we have developed the Soil Health Manual Series of Fact Sheets (bit.ly/SoilHealthFactSheets) to further facilitate the guide’s utility as an educational tool for growers, extension agents, and Ag Service Providers. The fact sheets are one page, two-sided handouts, designed to explain different soil health concepts and show how we measure soil health. Purveyors of soil health can easily download and print the sheets to be handed out at field days and other outreach events (Figure 2). They are available on the CASH website (http://soilhealth.cals.cornell.edu/).The entire collection is also available as a booklet or “mini-manual”.

Figure 2. The Soil Health Manual Series fact sheets are designed to explain different soil health concepts and show how we measure soil health in downloadable, one page, two sided, easy to read handouts.

Below are links to the fact sheets that are currently available online. New handouts will be posted as they are added to the series.

16-01 – Soil Health Sampling Protocols

16-02 – What is Soil Health?

16-03 – Common Soil Constraints

16-04 – Soil Texture

16-05 – Available Water Capacity

16-06 – Surface and Subsurface Hardness

16-07 – Wet Aggregate Stability

16-08 – Soil Organic Matter

16-09 – Soil Protein

16-10 – Soil Respiration

16-11 –  Active Carbon

Comprehensive Assessment of Soil Health Laboratory Soil Health Manual Series mini-manual

For more information, please visit our website: soilhealth.cals.cornell.edu

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December 7, 2016
by Cornell Field Crops
Comments Off on What’s Cropping Up? – Volume 26 No. 6 – November/December Edition

What’s Cropping Up? – Volume 26 No. 6 – November/December Edition

The full version of What’s Cropping Up? Volume 26 No. 6 is available as a downloadable PDF and on issuu.  Individual articles are available below:

December 5, 2016
by Cornell Field Crops
Comments Off on Comparing Soil Health Test Results from Northeast, Midwest and Mid-Atlantic Regions

Comparing Soil Health Test Results from Northeast, Midwest and Mid-Atlantic Regions

Aubrey K. Fine, Aaron Ristow, Robert Schindelbeck and Harold van Es
Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University

Comprehensive Assessment of Soil Health
Soil health refers to the ability of a soil to function and provide valuable ecosystem services. The Comprehensive Assessment of Soil Health (CASH) is a testing approach developed at Cornell University that measures multiple physical, biological, and chemical soil properties linked to key soil processes (Table 1). It remains largely unclear how soil health varies in different agro-ecological regions, and whether interpretation schemes should therefore be adjusted.  As a preliminary investigation into these questions, we used the CASH sample database to compare the soil health status of 5,767 samples collected from the Mid-Atlantic, Midwest, and Northeast regions of the United States.

scoring-functions-table-1

Database Analysis
CASH uses scoring functions that are developed using the cumulative normal distribution (CND) of measured values in our database for each indicator. Scoring functions for physical and biological CASH indicators are calculated using the CND, whereas chemical indicators are scored based on experimentally-established thresholds. Some, but not all, indicators showed texture-dependence; in these cases, separate scoring functions for coarse, medium, and fine textures were developed. The scoring function allows for the interpretation of the measured value for each indicator on a scale ranging from 0 to 100. This approach lets us assess how a particular soil sample scores relative to other similarly-textured soil samples in our records, and thereby make some judgment on the relative health of that soil to identify possible problems.

Since it began offering soil health testing services in 2006, the Cornell Soil Health Lab (CSHL) sample database has grown considerably in size and geographic scope. After evaluating the number of samples analyzed from each of the 48 continental United States, we identified three regions having sufficient sample size (n=5,676 total) including the Mid-Atlantic, Midwest, and Northeast. These regions align with the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Major Land Resource Areas (MLRA) (Fig. 1). Descriptive statistics and ANOVAs of sub-datasets by region and soil textural class for all CASH indicators were performed, allowing comparisons among these three regions in measured values of soil health indicators. The medium textural group made up the largest proportion of our database, and for brevity we only report this textural group results here (Table 2). A manuscript that also includes results of fine and coarse textural groups is in preparation for publication by Fine et al. (2017).

Figure 1. Mid-Atlantic, Midwest, and Northeast regions of the United States. Soil health samples from each region were aggregated into sub-datasets for statistical analyses and regional comparisons.

Figure 1. Mid-Atlantic, Midwest, and Northeast regions of the United States. Soil health samples from each region were aggregated into sub-datasets for statistical analyses and regional comparisons.

scoring-functions-table-2

Results
With this investigation, we observed significant regional differences in mean measured values for most physical, biological and chemical indicators (Table 2).

For medium-textured soils, significant differences between regions were observed for most indicators except subsurface compaction (PR45) and extractable potassium. In general, soil health values for the Midwest region were less favorable compared to the Mid-Atlantic and Northeast, notably for Wet Aggregate Stability, Organic Matter, Active Carbon, Protein, Respiration, and Root Health. Extractable phosphorus levels were notably higher in the Mid-Atlantic region. Although sample sizes between regions were unequal, Midwestern soils generally showed lower variability (standard deviations) in measured values.

These results offer insights into regional soil health differences that can be attributed to genetic and management factors. The lower mean values observed for biological indicators and Wet Aggregate Stability in Midwest soils counter the common notion that Midwestern soils are of superior quality than those in other regions.  How can this be explained?  First, there are likely differences in cropping systems.  Northeast and Mid-Atlantic soils generally receive more organic inputs (especially manure) and are often managed to include diverse rotations with perennial crops, as opposed to typical corn-soybean rotations in the Midwest. Second, the standard CASH is limited to the 0-to-6 inch depth interval, and, therefore, the deeper soils and organic matter accumulation in many fertile Midwestern prairie soils is not captured by the test.  Finally, these findings could suggest an inherent bias in our data set, so conclusions should be interpreted with some caution.

Conclusion
What have we learned?  An investigation into regional soil health status (Mid-Atlantic, Midwest, and Northeast) showed significant differences in mean measured values for most physical, biological, and chemical indicators. Evidence suggests that the development of region-specific scoring functions may be appropriate, but would require more complete regional soil health data collection and analysis. In all, this project provided valuable insights into the soil health status of three different agro-ecological environments.  We conclude that the CASH approach can be successfully applied to evaluate the health status of soils of differing agro-ecological environments, but that interpretations likely need to be regionally adapted to be most meaningful.

For more details about the CASH framework, visit bit.ly/SoilHealthTrainingManual for a free download of the third edition of the training manual.

Reference
Fine, A.K., van Es, H.M., and R. R. Schindelbeck.  2017. Statistics, Scoring Functions and Regional Analysis of a Comprehensive Soil Health Database.  Soil Science Soc. Am. J. (in preparation).

 

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November 30, 2016
by Cornell Field Crops
Comments Off on Update of Scoring Functions for Cornell Soil Health Test

Update of Scoring Functions for Cornell Soil Health Test

Aubrey K. Fine, Aaron Ristow, Robert Schindelbeck and Harold van Es
Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University

Comprehensive Assessment of Soil Health
Soil health refers to the ability of a soil to function and provide ecosystem services. The Cornell Comprehensive Assessment of Soil Health (CASH), initially referred to as the Cornell Soil Health Test, is a tool designed to aid landowners and managers in the evaluation of their soil health status. When a soil is not functioning to its full capacity, sustainable productivity, environmental quality, and net farmer profits are jeopardized over the long term.

Soil health cannot be determined directly, so it is assessed by measuring indicators that relate to soil quality. The CASH approach broadens the scope of conventional soil testing by evaluating the integration of biological, physical, and chemical properties, including soil texture, available water capacity, soil penetration resistance (i.e., compaction), wet aggregate stability, organic matter content, soil proteins, respiration, active carbon, and macro- and micro-nutrient content (see soilhealth.cals.cornell.edu/ for more details). Results from testing are interpreted using scoring functions, which are equations quantifying the relationship between measured indicator values and soil health status. Scores from all indicators are synthesized into a comprehensive report, which identifies specific soil constraints and provides management suggestions for clients.

A challenge of assessing soil health in this way is the interpretation of measured values for each soil property. For example, what does a 30% value for wet aggregate stability mean? Is it an indication of a problem, or does it signify a good soil? Should the interpretation be different depending on soil texture? The CASH scoring functions and interpretative color code for each indicator were developed to address this issue. The scoring functions for the original Cornell Soil Health Test, first made publically available in 2006, were based on soils data collected from the Northeastern United States. In the decade since, the Cornell Soil Health Laboratory (CSHL) database has expanded to include data for a much greater number and more geographically diverse set of samples representing over 60% of the United States and areas overseas.  This project reports on the most recent analysis of the CSHL database, performed in 2016. The results of this work allowed us to refine the scoring functions and incorporate regional differences that broaden the scope of the CASH outside of the Northeast.

Scoring Functions
The CASH scoring functions are based on the distribution of measured values for each indicator from all samples in the CSHL database.  This approach allows us to assess whether a particular soil sample shows low, medium, or high values relative to other soils in our database, and thereby make some judgment on the health of that soil and possible problems.  This is similar to many medical tests where an individual’s health measure (e.g., blood potassium level) is scored based on the values measured from a large population to assess whether or not it is within normal range.

For most CASH scoring functions, we use the mean and standard deviation of our data set to calculate the cumulative normal distribution (CND). The CND function is essentially the scoring function, as it translates measured values to a unit-less score ranging from 0-100. Scoring functions for all indicators and textural groups (i.e., coarse, medium, fine) were calculated this way. This approach can be adapted to other regions with different soils and climate, as scoring functions can be attuned to fit different conditions.

As an illustration on how scoring functions are developed, the histogram in Figure 1 shows the observed distribution of measured values of active carbon (Active C) for medium textured soils. The height of the bars depicts the frequency of measured values that fall within a range (bin) of 100 ppm along the horizontal axis. For instance, approximately 24% of the soil samples in this set had measured Active C concentration between 500 and 600 parts per million (ppm). The normal distribution, or bell curve, superimposed over the bars was calculated using the mean (531 ppm) and standard deviation (182 ppm) of all medium textured soils.  Using these two parameters, we can develop a scoring curve (Fig. 2e) representing the CND having the same parameters (i.e., the mean and standard deviation).

FIGURE 1. Example of the distribution of active carbon indicator data in medium textured soils used to determine the scoring curve.

Figure 1. Example of the distribution of active carbon indicator data in medium textured soils used to determine the scoring curve.

Three general types of scoring are used, whether the curve shape is normal, linear, or otherwise:

  • More is better, where a higher measured value of the indicator implies a higher score. We use this type of scoring curve for most soil health indicators.
  • Less is better, where higher measured values are assigned a lower score and are associated with poorer soil functioning. This is the case for Surface and Subsurface Hardness and the Root Health Bioassay Rating. Manganese and Iron are also scored as ‘less is better’ because these micronutrients are associated with a risk of toxicity from excess levels.
  • Optimum curve, where the scoring curve has an optimum range and the scores are lower when measured values fall either below or above this range. Extractable Phosphorous and pH are both scored using an optimum curve.

In general, scoring functions are texture group-dependent for physical and biological indicators, with higher scores associated with better soil health. For example, an Active Carbon measurement of 600 may be quite good for a sand, but low for a clay.

Database Analysis
In 2016, we examined samples analyzed using CASH from the continental US states. We identified three regions having suitable sample sizes (n=5,767 total) for further analysis, including the Mid-Atlantic, Midwest, and Northeast. These regions align with the United States Dept. of Agriculture Natural Resources (USDA) Conservation Service (NRCS) Major Land Resource Areas (MLRA) delineations. For each region, samples were identified by textural grouping to create a number of sub-datasets. Descriptive statistics and ANOVAs were performed to evaluate the mean and standard deviation of each region and texture. Based on these findings, we adjusted scoring functions for physical and biological indicators to account for observed statistically significant regional differences in mean indicator values. Chemical indicators are scored using experimentally-established thresholds, rather than the CND (see below), so they were left largely unchanged.

New Scoring Functions
Figures 2 and 3 show the updated scoring functions for each soil health indicator.  Most of these are universally applied to all soils analyzed with the CASH, but in some cases, special considerations are required.  For example, a separate scoring function for pH is now used for acid-loving crops (e.g., blueberries or potatoes; Fig. 3a), set one pH unit lower (5.2-to-6.3 are optimum, etc.).   Modified-Morgan-P also uses an optimum scoring function (Fig. 3b), where concentrations ranging from 3.5-21.5 ppm are scored at 100. Negative impacts are expected when P is deficient ([P] ≤ 0.45 ppm) or excessive ([P] ≥ 100 ppm).  Secondary (Mg) and trace (Fe, Mn, Zn) nutrients are scored using a sub-scoring system (Fig. 3d). Each nutrient is assigned a sub-score of either 0 (suboptimum) or 100 (optimum) depending on measured values. The average of the four nutrient sub-scores is used to determine the secondary nutrient score.

Figure 2. Comprehensive Assessment of Soil Health scoring functions for physical (a.-c.) and biological (d.-h.) soil health indicators. Functions are shown overlying a five color scheme (red-orange-yellow-light green-dark green), used to classify scores as very low (0-20), low (20-40), medium (40-60), high (60-80), and very high (80-100), respectively.

Figure 2. Comprehensive Assessment of Soil Health scoring functions for physical (a.-c.) and biological (d.-h.) soil health indicators. Functions are shown overlying a five color scheme (red-orange-yellow-light green-dark green), used to classify scores as very low (0-20), low (20-40), medium (40-60), high (60-80), and very high (80-100), respectively.

 

Figure 3. Comprehensive Assessment of Soil Health scoring functions for chemical indicators: pH (a) and Modified Morgan Extractable Phosphorus (b), Potassium (c), and secondary/trace nutrients (Mg, Fe, Mn, Zn) (d). Scores are coded using a five-color scheme (red-orange-yellow-light green-dark green), used to classify scores as very low (0-20), low (20-40), medium (40-60), high (60-80), and very high (80-100), respectively.

Figure 3. Comprehensive Assessment of Soil Health scoring functions for chemical indicators: pH (a) and Modified Morgan Extractable Phosphorus (b), Potassium (c), and secondary/trace nutrients (Mg, Fe, Mn, Zn) (d). Scores are coded with a five color scheme (red-orange-yellow-light green-dark green), which classifies scores as very low (0-20), low (20-40), medium (40-60), high (60-80), and very high (80-100), respectively.

The CASH Report Summary has traditionally used a three-color system (green-yellow-red; or low-medium-high) for interpreting measured indicator values. This system provided limited resolution for detecting changes in soil health over time, as scores ranging from 30-to-70 would be interpreted as ‘medium’ in the report. To address this, we adjusted to a five-color scale (red-orange-yellow-light green-dark green) to classify values as very low (0-20), low (20-40), medium (40-60), high (60-80), and very high (80-100), respectively.  This visual change more easily demonstrates subtle soil health improvements.

The lower the CASH score, the greater the constraint in the proper functioning of processes as represented by the indicator. Land management decisions should, therefore, place priority on correcting very low scores (red). Low and medium scores (orange and yellow) do not necessarily represent a major constraint to proper soil functions, but rather suggested improvements that can be made in management planning. High or very high scores (light green and dark green) indicate that the soil processes represented by these indicators are likely functioning well. As such, management goals should aim to maintain those conditions.

Conclusion
The initial CASH soil health scoring functions were developed using data collected from Northeastern soil samples analyzed in the early 2000s.  Ten years of soil health testing allowed us to build on a robust database including measured data for multiple soil health indicators. In 2016, we revisited the scoring functions used to score physical and biological indicators to increase the scope of the CASH to soils outside of the Northeast US. These changes have been incorporated into the CASH, most of which effectively increase the score associated with a given measured indicator value. These adjustments, in addition to the expanded five-color scheme, have helped address some of the concerns expressed by clients who found the CASH interpretations to be slightly off in some cases.

A full manuscript of this article titled “Statistics, Scoring Functions, and Regional Analysis of a Comprehensive Soil Health Database” is currently under review by the Soil Science Society of America Journal.  For more details about the CASH framework, visit bit.ly/SoilHealthTrainingManual for a free download of the third edition of the training manual.

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July 29, 2016
by Cornell Field Crops
Comments Off on What’s Cropping Up? Volume 26 No. 4 – July/August Edition

What’s Cropping Up? Volume 26 No. 4 – July/August Edition

The full version of What’s Cropping Up? Volume 26 No. 4 is available as a downloadable PDF and on issuu.  Individual articles are available below:

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