Page Banner

United States Department of Agriculture

Agricultural Research Service

Research Project: IMPROVING SOILS AND THEIR MANAGEMENT FOR MORE EFFICIENT WATER USE IN ENVIRONMENTALLY SUSTAINABLE AGRICULTURE

Location: Coastal Plain Soil, Water and Plant Conservation Research

Title: Comparison of soil amendments to decrease high strength in SE USA Coastal Plain soils using fuzzy decision-making analyses

Authors
item Busscher, Warren
item Krueger, Elena - IND. RESEARCHER, DENVER
item Novak, Jeffrey
item Kurtener, Dmitry - AGRO RES INST, RUSSIA

Submitted to: International Agrophysics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 5, 2007
Publication Date: September 3, 2007
Citation: Busscher, W.J., Krueger, E., Novak, J.M., Kurtener, D. 2007. Comparison of soil amendments to decrease high strength in SE USA Coastal Plain soils using fuzzy decision-making analyses. International Agrophysics 21:225-231.

Interpretive Summary: Fuzzy logic analysis is a unique method that allows researchers to assign weighting factors of validity or significance to data. It also allows analysis of several independent parameters at a time when considering combinations of treatment options. We applied the principles of fuzzy logic to analyses of data on amendments added to a hard-layer soil that would reduce strength and promote root growth and productivity. Amendments included ground wheat straw mixed with moderate or high rates of a proven ecologically safe formulation of polyacrylamide (PAM). Data collected from the treatments included development of soil aggregates, water content, and soil strength. Fuzzy data analysis maximized benefits such as development of aggregates and minimized deficits such as water needed and soil strength. When physical parameters were analyzed, the best treatment combination was addition of wheat straw and the moderate amount of PAM, whereas amendment with wheat straw and the high rate of PAM had been selected as the best treatment with more traditional analysis because it did not take all soil attributes into account at the same time. When economic parameters covering the cost of amendments and their incorporation were included in the analyses, the best treatment combination was wheat straw with the high rate of PAM while wheat straw with the moderate rate of PAM was second best. Using a fuzzy logic approach allowed analysis of several variables simultaneously when developing the best treatment options; however, judgment of researchers was needed to determine which variables to use and how to weight them. In this case, all variables were weighted equally.

Technical Abstract: Cemented subsurface layers restrict root growth in many southeastern USA Coastal Plain soils. Though cementation is usually reduced by tillage, soil amendments can offer a more permanent solution if they develop aggregation. To increase aggregation, we amended 450 g of a Norfolk soil blend of 90% E horizon (the hard layer) and 10% Ap horizon with 0 or 6.44 g/kg ground wheat (Triticum aestivum L.) residue and 0, 30, or 120 mg/kg polyacrylamide (PAM, 12 x 106 Da anionic, linear, and 35% charge density). During a 60-d incubation, parameters measured included water added to maintain 10% soil moisture, soil strength, bulk density, and aggregation. Data were analyzed using a cost-benefit approach with normalized fuzzy logic indicators. Analyses included building normalized decision matrices, calculating weighting vectors, ranking alternatives, and defining the best alternatives. When only physical parameters were analyzed using fuzzy logic indicators, addition of wheat with 30 mg/kg PAM proved to be the best alternative whereas 120 mg/kg PAM had been selected as the best alternative with more traditional analysis because it did not simultaneously analyze independent variables. When both physical and economic parameters were included, the treatment option with wheat and 120 mg/kg PAM was best. When using fuzzy logic, judgment of the user was needed to determine which parameters to include and how to weight them.

Last Modified: 7/22/2014