Thomas C. Kaspar

Winter cover crops have the potential to increase soil organic C in the corn ( Zea mays L.)–soybean [ Glycine max (L.) Merr.] rotation in the upper Midwest. Management effects on soil C, however, are often difficult to measure because of the spatial variation of soil C across the landscape. The objective of this study was to determine the effect of oat ( Avena sativa L.), rye ( Secale cereale L.), and a mixture of oat and rye used as winter cover crops following soybean on soil C levels over 3 yr and both phases of a corn–soybean rotation using terrain attributes as covariates to account for the spatial variability in soil C. A field experiment was initiated in 1996 with cover crop treatments, both phases of a corn–soybean rotation, and a controlled‐traffic no‐till system. Oat, rye, and oat–rye mixture cover crop treatments were overseeded into the soybean phase of the rotation in late August each year. Cover crop treatments were not planted into or after the corn phase of the rotation. Soil C concentration was measured on 450 samples taken across both rotation phases in a 7.62‐m grid pattern in the late spring of 2000, 2001, and 2002. Slope, relative elevation, and wetness index (WI) were used as covariates in the analysis of variance to remove 77% of the variation of soil C caused by landscape driven patterns of soil C. Soil C concentrations were 0.0023 g C g soil ⁻¹ higher in 2001 and 0.0016 g C g soil ⁻¹ higher in 2002 than in 2000. The main effects of cover crops were not significant, but the interaction of cover crops and rotation phase was significant. The rye cover crop treatment had 0.0010 g C g soil ⁻¹ higher soil C concentration than the no‐cover‐crop control in the soybean phase of the rotation, which included cover crops, but had 0.0016 g C g soil ⁻¹ lower C concentrations than the control in the corn phase of the rotation, which did not have cover crops. Using terrain covariates allowed us to remove most of the spatial variability of soil C, but oat and rye cover crops planted every other year after soybean did not increase soil C concentrations averaged over years and rotation phases.

Farmers will be better able to implement site‐specific management practices when they understand the causes of spatial and temporal variability of corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yield in their fields. Our objectives were to determine if a data set containing 20 soil and terrain variables could explain spatial yield variability better than a subset of seven more easily measured variables and to determine whether the relative importance of factors in explaining yield variability differed between corn and soybean or between wet and dry years. Yield data were collected for 11 yr in a 16‐ha field in central Iowa. Soil and terrain variables measured included: A horizon depth, carbonate depth, pH, coarse sand, sand, silt, clay, organic C, N, Fe, K, P, and Zn; and seven easily measured variables: electrical conductivity, soil color, elevation, slope, profile curvature, plan curvature, and depression depth. Factor analysis of the variables followed by regression of yield on the resulting factors showed that the 20‐variable set explained more of the spatial variation in yield than the subset of seven variables. Further, the analysis of the 20‐variable data set showed that soybean yield was affected more by pH, more by closed depressions in wet years, and less by curvature in dry years than corn yield. Similarly, yield was negatively affected by closed depressions and lower landscape positions in wet years, whereas these factors had either no effect or a positive effect in dry years. Alternately, curvature had a negative effect in dry years and no effect in wet years.

Decomposition and mineralization of cover crop roots needs to be understood to determine if N taken up by cover crops is mineralized during main crop growth. Two experiments were conducted in a controlled environment to measure decomposition of oat ( Avena sativa L. ‘Ogle’) and rye ( Secale cereale L. ‘Rymin’) root residues and to examine its effect on soil N mineralization. In the first, oat and rye roots were mixed with soil and in the second, roots were grown in situ. At 7, 14, 28, 56, 84, and 112 d after the start of decomposition, denitrification, soil NO ⁻ ₃ , and soil NH ⁺ ₄ were measured to determine net mineralized N. Soil respiration and C and N contained in roots and coarse soil organic matter were measured to determine decomposition. All treatments in both experiments showed an increase in net mineralized N during the first 56 d. After 56 d, net mineralized N in the control remained relatively constant, whereas mineral N continued to accumulate in the treatments with root residues. Net N mineralization of the rye and oat root treatments did not differ. Roots mixed with soil had high respiration rates during the first 3 d and there were no differences between oat and rye root treatments. In the roots in situ experiment, however, respiration peaked for oat roots at Day 12 and for rye roots at Day 33. The oat treatment also had less C and N remaining in roots and coarse organic matter throughout the experiment. Even though oat roots decomposed faster than the rye roots, we predict that <55% of the N contained in the roots of a spring‐killed oat or rye cover crop will become available to the following crop.

One approach for measuring the length of roots washed from soil samples is to use a desktop scanner to acquire binary images and then use image analysis procedures to determine root length. Normally, this approach requires user‐adjusted exposure thresholding. The objectives of this study were to develop a procedure for obtaining binary images of root samples with a desktop scanner that does not require user‐adjusted exposure thresholding of each image and to test the performance of the newly developed ROOTEDGE program by using images containing single or multiple root segments of corn (Zea mays L.). ROOTEDGE was developed for measuring the length of digitized roots using the edge chord algorithm. It is insensitive to object orientation, has four image‐processing operations, and holds only seven lines of the image in memory. Visual comparisons of digitized images with actual root segments showed that root segments with diameters less than 0.15 mm were not being completely digitized by the image acquisition procedure and were fragmented in the images. The most complete root images were produced by using the highest available scanner resolution and the lowest scanner threshold level for exposure. Using the closing image‐processing operation in ROOTEDGE with a test coefficient of 1 also helped to join fragmented objects within images and improved the correlation of ROOTEDGE measurements to direct measurements. Ratios of ROOTEDGE length measurements to manual line‐intersection length measurements ranged from 0.98 to 0.88 for four corn root samples of different sizes. In general, the ROOTEDGE software and image acquisition system accurately measured corn root length without user‐adjusted exposure thresholding.

Controlled wheel traffic is one way to manage compaction in no‐till and ridge‐till systems. This study was conducted from 1990 to 1992 at Kanawha, IA, on a Webster silty clay loam (fine‐loamy, mixed, mesic Typic Haplaquoll) to examine the effect of a wheel traffic pattern on corn (Zea mays L.) root distribution, shoot growth, and yield in no‐till, ridge‐till, and chisel‐plow tillage systems. The wheel traffic pattern was configured so that some rows would have wheel tracks on both sides, on one side, or on neither side. Bulk density, hydraulic conductivity, root length density, shoot dry weight, and yield were measured at several positions across the traffic pattern. In general, the effect of tillage systems was not significant averaged across positions. Position relative to the traffic pattern had some effect, however, on all measured parameters. Bulk density was greatest in trafficked interrows (1.36 Mg m~3) and least in untrafficked interrows (1.09 Mg m⁻³). Hydraulic conductivity near saturation was less in trafficked (39.4 μm s⁻¹) than in untrafficked (104.7 μm s⁻¹) interrows. Root length density in trafficked interrows was on average one‐third of that in untrafficked interrows. Root length density in a particular interrow also was influenced by the traffic pattern in the adjacent interrows. In 2 of the 3 yr, yields of rows with a trafficked interrow on only one side were 7% less than those of rows without trafficked interrows on either side. The wheel traffic pattern, and not just the presence or absence of wheel traffic, affected corn root growth and yield.

A greater understanding of maize (Zea mays L.) nodal root response to soil ridging and tillage systems is needed to maximize the benefits of ridge‐till and other conservation tillage systems. Field (1992 and 1993 near Marshalltown, IA) and greenhouse (two studies with two trials each) experiments were conducted to examine the effect of soil ridging, height of ridging, and three tillage systems (no‐till, ridge‐till, and chisel‐plow) on the number and stem node position of maize nodal roots and on internode length. Field plants were ridged during cultivation. In the greenhouse, ridging was simulated by using polyvinyl chloride rings to hold soil around the base of plants. Numbers of nodal roots, numbers of nodes developing functional roots, internode lengths, shoot dry weights, and grain yields (field study) were determined. In one greenhouse experiment, unridged plants developed an average of 38.4 functional nodal roots, while ridged plants developed 50.0, an increase of 30%. In the same greenhouse experiment, ridging significantly increased lengths of Internodes 6 and 7, which were covered with soil during ridging. Average length of Internode 7 increased from 64 mm to 101 mm with ridging. Increasing ridge height increased internode length and number of nodal roots in the controlled greenhouse experiments, but not in the field. In field experiments, ridge‐till caused development of significantly more functional nodal roots as compared with no‐till (1992 and 1993) and chisel‐plow (1992). Plants from no‐tiil developed 53.1 and 46.0 functional nodal roots in 1992 and 1993, respectively, while plants from ridgetill developed 58.7 and 49.1 roots. Shoot dry weight and grain yield were not affected by ridging or tillage treatments in the greenhouse or field.