In a thermic udic region, a summer crop species may be planted with or without tillage subsequent to a winter grain crop that was planted into a prepared seedbed. This study was conducted to identify the effect of tillage intensity associated with soybean [Glycine max (L.) Merr.] and grain sorghum [Sorghum bicolor (L.) Moench] crop sequences following winter wheat (Triticum aestivum L.), and the effect of summer crop species on selected physical characteristics of a Cecil sandy loam (clayey, kaolinitic, thermic Typic Kanhapludult). Through eight seasons, soybean and grain sorghum were grown in 10 crop sequences that were imposed on three tillage treatments: conventional tillage (CT), in‐row chisel (MT), and no‐tillage (NT). Following summer crop harvest in the eighth season, aggregate stability, organic C, bulk density, air‐filled pore space, particle‐size distribution, and infiltration of water were measured. Aggregate stability at 0 to 10 mm was significantly higher for MT and NT than for CT. The CT treatment exhibited significantly lower bulk density and higher air‐filled pore space than MT and NT. Infiltration was significantly greater on the MT than the CT and NT treatments. Greater aggregate stability, higher air‐filled pore space, and lower bulk density were measured after two or more years of grain sorghum than after soybean. The maintenance of wheat straw on the soil surface under the MT and NT treatment exhibited an effect to a depth of 75 mm and the in‐row chisel treatment affected infiltration. Crop‐rotational effects can be erased or modified by tillage and may only be observed under NT. Grain yield response of soybean and grain sorghum to changes in soil physical characteristics, as a consequence of crop sequence and tillage, may need to be interpreted in relation to crop species and cropping sequence.

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A method for quantifying fluctuations in time‐series data was developed and tested to aid the process of visualization. The methodology is based on free‐form sliding polynomials and identifies (a) short‐period variability about the mean value, (b) a long‐term trend or cycle, and (c) random errors residual to these two structured components. Consistent results were obtained for designed synthetic data and natural data from seven sites in Georgia. Statistics of fit of the analytical model for the natural data were not significant on a site‐by‐site basis. An unexpected finding for the study was obtained when the statistical results for the seven data sets for temperature were pooled. The smoothing model yielded consistent long‐term trends even though the individual station results were not significant. Also, the correlation coefficients, while low, showed a statistically significant trend toward higher values toward the northwest and away from the Georgia coast line. This study thus supports the concept that multiple‐site, and regionally based, analyses are necessary for the detection of trends. Secondarily, such consistency of results strengthens the conclusion that the proposed smoothing method is an effective procedure in the presence of varying amounts of random content in the natural data sets.