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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Wind Erosion and Water Conservation Research » Research » Publications at this Location » Publication #220883

Title: Comparison of two soil quality indexes to evaluate cropping systems in northern Colorado

Author
item Zobeck, Teddy
item Halvorson, Ardell
item Wienhold, Brian
item Acosta-Martinez, Veronica
item Karlen, Douglas

Submitted to: Journal of Soil and Water Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/4/2008
Publication Date: 9/1/2008
Citation: Zobeck, T.M., Halvorson, A.D., Wienhold, B.J., Acosta Martinez, V., Karlen, D.L. 2008. Comparison of two soil quality indexes to evaluate cropping systems in northern Colorado. Journal of Soil and Water Conservation. 63(5):329-338.

Interpretive Summary: Various methods have been proposed to evaluate the effects of land management practices on soil resources. The management systems are usually ranked using some type of land evaluation index. Two indexes currently proposed are the soil quality index (SQI) as determined by the soil management assessment framework (SMAF), based on measured soil properties, and the soil conditioning index (SCI) as determined using Natural Resources Conservation Service computer models. This study was conducted to compare the indexes and test whether the SQI can detect smaller changes in soil management than SCI. In a test of five cropping systems using three nitrogen levels, both SQI and SCI could separate the highest nitrogen level from the lowest level but the SCI seemed to more clearer separate the nitrogen levels than the SQI. However, the SQI seemed to place the management systems into more groups, after accounting for the effect of nitrogen level, suggesting it can detect smaller differences in crop management systems due to tillage and crop. Since the SCI is now used to determine compliance for several farm programs or land management standards, knowledge of its strengths and weaknesses is very important. Selection of the most appropriate soil evaluation index seems to be a tradeoff between an index that requires field data needed to make the evaluation (SQI) versus an index, such as SCI, that requires no field data but tends to make fewer distinctions among crop management systems.

Technical Abstract: Various soil management assessment tools have been proposed to evaluate the effects of land management practices on soil, air, and water resources, two of them are the soil management assessment framework (SMAF) and the soil conditioning index (SCI). This study was conducted to test the hypothesis that the soil quality index (SQI) produced by SMAF can detect more minute changes in soil management than SCI and to test SCI response to other soil quality indicators. These SQ indexes were tested on irrigated cropping systems near Fort Collins, Colorado that included no-till (NT) and conventionally-tilled (CT) corn (Zea mays L.), and NT corn with rotations including barley (Hordeum distichon L.), soybean (Glycine max (L.) Merr.), and dry bean (Phaeseolus vulgaris L.) at three levels of nitrogen varying from 0 to 224 kg N ha-1. Both SQ indexes seemed to differentiate among levels of N. The SQI and SCI clearly separated the plots with a very high level of N from plots with no N. However, for SQI the mid-level of N was statistically the same as both extreme levels. Statistical differences were observed for all N levels for the SCI. The SQI seemed to make more detailed differentiation among crop management systems than the SCI. The SCI separated the cropping systems into three groups with no overlap among groups. All NT systems had the statistically same higher SCI than the CT continual corn system. The SQI separated the cropping systems into three groups with decreasing SQI with increasing tillage and decreasing residue as lower residue crops are introduced in to the cropping system. The systems that included tillage and a low residue crop (soybean) had the lowest SQI. The SQI allowed overlap among cropping groups not recognized by SCI. Selection of the most appropriate SQ index seems to be a tradeoff between data requirements and resolution desired in the evaluation tool.