Bio-based energy is key to developing a globally sustainable low-carbon economy. Lignocellulosic feedstock production on marginally productive croplands is expected to provide substantial climate mitigation benefits, but long-term field research comparing greenhouse gas (GHG) outcomes during the production of annual versus perennial crop-based feedstocks is lacking. Here, we show that long-term (16 years) switchgrass (Panicum virgatum L.) systems mitigate GHG emissions during the feedstock production phase compared to GHG-neutral continuous corn (Zea mays L.) under conservation management on marginally productive cropland. Increased soil organic carbon was the major GHG sink in all feedstock systems, but net agronomic GHG outcomes hinged on soil nitrous oxide emissions controlled by nitrogen (N) fertilizer rate. This long-term field study is the first to demonstrate that annual crop and perennial grass systems respectively maintain or mitigate atmospheric GHG contributions during the agronomic phase of bioenergy production, providing flexibility for land-use decisions on marginally productive croplands.

Switchgrass (Panicum virgatum L.) is a C4, perennial grass that is being developed as a bioenergy crop for the United States. While aboveground biomass production is well documented for switchgrass ecotypes (lowland, upland), little is known about the impact of plant belowground productivity on microbial communities down deep in the soil profiles. Microbial dynamics in deeper soils are likely to exert considerable control on ecosystem services, including C and nutrient cycles, due to their involvement in such processes as soil formation and ecosystem biogeochemistry. Differences in root biomass and rooting characteristics of switchgrass ecotypes could lead to distinct differences in belowground microbial biomass and microbial community composition. We quantified root abundance and root architecture and the associated microbial abundance, composition, and rhizodeposit C uptake for two switchgrass ecotypes using stable-isotope probing of microbial phospholipid fatty acids (PLFAs) after 13CO2 pulse–chase labeling. Kanlow, a lowland ecotype with thicker roots, had greater plant biomass above- and belowground (g m−2), greater root mass density (mg cm−3), and lower specific root length (m g−1) compared to Summer, an upland ecotype with finer root architecture. The relative abundance of bacterial biomarkers dominated microbial PLFA profiles for soils under both Kanlow and Summer (55.4 and 53.5 %, respectively; P = 0.0367), with differences attributable to a greater relative abundance of Gram-negative bacteria in soils under Kanlow (18.1 %) compared to soils under Summer (16.3 %; P = 0.0455). The two ecotypes also had distinctly different microbial communities process rhizodeposit C: greater relative atom % 13C excess in Gram-negative bacteria (44.1 ± 2.3 %) under the thicker roots of Kanlow and greater relative atom % 13C excess in saprotrophic fungi under the thinner roots of Summer (48.5 ± 2.2 %). For bioenergy production systems, variation between switchgrass ecotypes could alter microbial communities and impact C sequestration and storage as well as potentially other belowground processes.

Harvesting of corn stover (plant residues) for cellulosic ethanol production must be balanced with the requirement for returning plant residues to agricultural fields to maintain soil structure, fertility, crop protection, and other ecosystem services. High rates of corn stover removal can be associated with decreased soil organic matter (SOM) quantity and quality and increased highly erodible soil aggregate fractions. Limited data are available on the impact of stover harvesting on soil microbial communities which are critical because of their fundamental relationships with C and N cycles, soil fertility, crop protection, and stresses that might be imposed by climate change. Using fatty acid and DNA analyses, we evaluated relative changes in soil fungal and bacterial densities and fungal-to-bacterial (F:B) ratios in response to corn stover removal under no-till, rain-fed management. These studies were performed at four different US locations with contrasting soil-climatic conditions. At one location, residue removal significantly decreased F:B ratios. At this location, cover cropping significantly increased F:B ratios at the highest level of residue removal and thus may be an important practice to minimize changes in soil microbial communities where corn stover is harvested. We also found that in these no-till systems, the 0- to 5-cm depth interval is most likely to experience changes, and detectable effects of stover removal on soil microbial community structure will depend on the duration of stover removal, sampling time, soil type, and annual weather patterns. No-till practices may have limited the rate of change in soil properties associated with stover removal compared to more extensive changes reported at a limited number of tilled sites. Documenting changes in soil microbial communities with stover removal under differing soil-climatic and management conditions will guide threshold levels of stover removal and identify practices (e.g., no-till, cover cropping) that may mitigate undesirable changes in soil properties.

Harvesting crop residue needs to be managed to protect agroecosystem health and productivity. DAYCENT, a process-based modeling tool, may be suited to accommodate region-specific factors and provide regional predictions for a broad array of agroecosystem impacts associated with corn stover harvest. Grain yield, soil C, and N2O emission data collected at Corn Stover Regional Partnership experimental sites were used to test DAYCENT performance modeling the impacts of corn stover removal. DAYCENT estimations of stover yields were correlated and reasonably accurate (adjusted r 2 = 0.53, slope = 1.18, p << 0.001, intercept = 0.36, p = 0.11). Measured and simulated average grain yields across sites did not differ as a function of residue removal, but the model tended to underestimate average measured grain yields. Modeled and measured soil organic carbon (SOC) change for all sites were correlated (adjusted r 2 = 0.54, p << 0.001), but DAYCENT overestimated SOC loss with conventional tillage. Simulated and measured SOC change did not vary by residue removal rate. DAYCENT simulated annual N2O flux more accurately at low rates (≤2-kg N2O-N ha−1 year−1) but underestimated when emission rates were >3-kg N2O-N ha−1 year−1. Overall, DAYCENT performed well at simulating stover yields and low N2O emission rates, reasonably well when simulating the effects of management practices on average grain yields and SOC change, and poorly when estimating high N2O emissions. These biases should be considered when DAYCENT is used as a decision support tool for recommending sustainable corn stover removal practices to advance bioenergy industry based on corn stover feedstock material.

Advanced biofuels will be developed using cellulosic feedstock rather than grain or oilseed crops that can also be used for food and feed. To be sustainable, these new agronomic production systems must be economically viable without degrading the soil and other natural resources. This review examines six agronomic factors that collectively define many of the limits and opportunities for harvesting crop residue for biofuel feedstock in the midwestern United States. The limiting factors include soil organic carbon, wind and water erosion, plant nutrient balance, soil water and temperature dynamics, soil compaction, and off-site environmental impacts. These are discussed in relationship to economic drivers associated with harvesting corn (Zea mays L.) stover as a potential cellulosic feedstock. Initial evaluations using the Revised Universal Soil Loss Equation 2.0 (RUSLE2)

Sequestration and storage of carbon (C) by agricultural soils has been cited as one potential part of the solution to soil degradation and global climate change. However, C sequestration in soils is a slow and dynamic process. The objective of this study was to evaluate the effects of crop rotation and N fertilizer management on soil organic C (SOC) levels at several points in time during 18 yr of a long‐term study in the Western Corn Belt. Seven cropping systems (three monoculture, two 2‐yr, and two 4‐yr rotations) with three levels of N fertilizer were compared. Soil samples were taken in the spring in 1984, 1992, 1998, and 2002 to a depth of 30 cm in 0‐ to 7.5‐, 7.5‐ to 15‐, and 15‐ to 30‐cm increments. No differences were obtained in SOC levels in 1984 at the beginning of the study. After 8 yr, rotation significantly increased SOC 449 kg ha−1 across all cropping systems. From 1992 to 2002, SOC levels in the 0‐ to 7.5‐cm depth decreased by 516 kg ha−1 across all cropping systems. Soil organic C levels in the 7.5‐ to 15‐cm depths in 1992 and 2002 demonstrated similar rotation effects to those in the surface 0‐ to 7.5‐cm, being not significantly affected from 1984 to 1992 but being significantly decreased from 1992 to 2002 (568 kg SOC ha−1 across all cropping systems). Many of the SOC gains in the surface 30 cm measured during the first 8 yr of the study were lost during the next 10 yr in all but the 4‐yr cropping systems after 18 yr. The loss of SOC in this latter period occurred when depth of tillage was increased by using a tandem disk with larger‐diameter disks. These results demonstrate that more than one point‐in‐time measurement from long‐term experiments is necessary to monitor SOC changes when several management variables, such as cropping system and N fertilizer, are being used. They also indicate that apparent small changes in cultural practices, such as in depth of tillage in this experiment, can significantly change SOC dynamics in the soil. Subtle changes in cultural practices (e.g., tillage depth) can have significant long‐term results, but long‐term experiments are required to quantify their impact under variable climatic conditions.

Soils perform a number of essential functions affecting management goals. Soil functions were assessed by measuring physical, chemical, and biological properties in a regional assessment of conventional (CON) and alternative (ALT) management practices at eight sites within the Great Plains. The results, reported in accompanying papers, provide excellent data for assessing how management practices collectively affect agronomic and environmental soil functions that benefit both farmers and society. Our objective was to use the regional data as an input for two new assessment tools to evaluate their potential and sensitivity for detecting differences (aggradation or degradation) in management systems. The soil management assessment framework (SMAF) and the agro-ecosystem performance assessment tool (AEPAT) were used to score individual soil properties at each location relative to expected conditions based on inherent soil-forming factors and to compute index values that provide an overall assessment of the agronomic and environmental impact of the CON and ALT practices. SMAF index values were positively correlated with grain yield (an agronomic function) and total organic matter (an agronomic and environmental function). They were negatively correlated with soil nitrate concentration at harvest (an indicator of environmental function). There was general agreement between the two assessment tools when used to compare management practices. Users can measure a small number of soil properties and use one of these tools to easily assess the effectiveness of soil management practices. A higher score in either tool identifies more environmentally and agronomically sustainable management. Temporal variability in measured indicators makes dynamic assessments of management practices essential. Water-filled pore space, aggregate stability, particulate organic matter, and microbial biomass were sensitive to management and should be included in studies aimed at improving soil management. Reductions in both tillage and fallow combined with crop rotation has resulted in improved soil function (e.g., nutrient cycling, organic C content, and productivity) throughout the Great Plains.

The end‐of‐season stalk nitrate test provides a method of assessing the N available to the corn (Zea mays L.) crop during the latter part of the season. This study was conducted to determine how stalk nitrate test results and interpretations are affected by sample composition. Stalks were collected from three field sites and separated into phytomers (node plus internode above), which were subdivided into three or five segments after length was measured. Nitrate‐N concentration of phytomers decreased linearly from the soil to the ear. Within a phytomer, segments also decreased acropetally (from base to apex). Node tissue NO3–N concentration did not differ from that of the internode segment immediately above the node. Weighted means were used to compute NO3–N concentration of stalk samples collected 5 cm higher (from 20 to 40 cm above the soil) or lower (from 10 to 30 cm above the soil) on the stalk than in the original method (from 15 to 35 cm above the soil). Although the three samples (10–30, 15–35, and 20–40 cm) differed in NO3–N concentration, the difference was only about 15% compared with the 25% difference in sampling position (±5 cm of 20‐cm sample length). The phytomer nearest the soil had 35 to 40% greater NO3–N concentrations than the section of stalk 15 to 35 cm above the soil. Critical values delineating yield‐limiting, adequate, and excessive N availability should be modified if stalk sections other than the standard 15 to 35 cm section are used. However, the qualitative nature of the stalk nitrate test and the range of NO3–N concentrations observed with reasonable corn cultural practices (1000×) make this test quite robust and precise definition of sample composition and critical values less necessary.

Approaches to assess the effects of management practices on agro-ecosystem functions are needed. This paper describes a computer program designed to assess the relative sustainability of management practices using agronomic and environmental data. The program, entitled AgroEcosystem Performance Assessment Tool (AEPAT), utilizes performance-based index methodology to derive a relative ranking of agroecosystem performance among management practices for functions and indicators included in the procedure. The program is organized into eight major steps: Introduction, Input Files, Assign Indicators to Functions, Describe Indicators, Assign Weights, Select Output File, Calculate Agroecosystem Performance Scores, and Save Agroecosystem Project. Help windows as well as a tutorial are provided within the program to assist users through each step. Users must keep in mind the assumptions and drawbacks inherent to performance-based indices while using AEPAT. Additionally, the program requires data on many indicators to provide useful information on agroecosystem performance. Therefore, its use is intended primarily for clientele conducting long-term agroecosystem experiments.

Agricultural sustainability is enhanced by management practices that optimize the performance of multiple agroecosystem functions. The performance of western Corn Belt cropping systems was evaluated based on four agroecosystem functions: food production, raw materials production, nutrient cycling, and greenhouse gas regulation. A simple multiattribute ranking procedure was used to quantify agroecosystem performance using data from a long-term cropping systems experiment near Mead, NE. Treatments included in the procedure were continuous corn ( Zea mays L.) (CC), corn–soybean [ Glycine max (L.) Merr.] (C–SB), corn–oat ( Avena sativa L.) + clover [80% sweet clover ( Melilotus officinalis L.) and 20% red clover ( Trifolium pratense L.)]–sorghum [ Sorghum bicolor (L.) Moench]–soybean (C–OCL–SG–SB), and corn–soybean–sorghum–oat + clover (C–SB–SG–OCL) each at three N fertilization levels (ZERO, LOW, and HIGH). Based on treatment averages of soil and crop indicators from 1983 to 1998, agroecosystem performance scores ranged from 66.6 to 77.3, with a least significant difference (LSD) between treatments of 2.2 ( P < 0.05). Treatments with the highest scores included C–OCL–SG–SB/LOW (77.3), C–SB/LOW (76.9), CC/LOW (76.7), CC/HIGH (76.6), and C–SB–SG–OCL/LOW (75.3). Among these treatments, those fertilized at the LOW N rate attained high scores through moderate performance in all four agroecosystem functions. The CC/HIGH treatment, however, attained a high score solely through its superior capacity to be highly productive, as its scores for the two environmental quality–related functions were the lowest among all treatments. Correlations between production- and environmental protection–related functions were negative, emphasizing the importance of employing management practices that are productive yet minimize deleterious environmental impacts.

Increased N availability is often associated with the beneficial effects of rotating grain and legume crops. Our objective was to utilize yield response data from two long‐term studies to determine the amount of N supplied by soybean [Glycine max (L.) Merr.] for subsequent nonlegume crops in 2‐yr rotations. The experiments were located in eastern Nebraska (Mead) (rainfed) and central Nebraska (Shelton) (irrigated). Continuous corn (Zea mays L.) and soybean–corn cropping systems were present in both experiments while continuous sorghum [Sorghum bicolor (L.) Moench] and soybean–sorghum cropping systems were present at Mead only. Three N fertilizer rates were used for the study at Mead and five at Shelton. Nitrogen fertilizer replacement values were estimated using graphical and regression techniques. Results from both techniques indicated that corn in the rainfed experiment at Mead (20 yr) and irrigated experiment at Shelton (10 yr) obtained approximately 65 kg N ha−1 yr−1 from soybean in a 2‐yr rotation with soybean at both locations. Sorghum in the rainfed experiment at Mead (20 yr) obtained approximately 80 kg N ha−1 yr−1 from soybean in a soybean–sorghum rotation. Current fertilizer N applications based on fall or early‐spring soil tests used extensively in this area need to be reduced by these amounts for corn and sorghum grown in 2‐yr rotations with soybean when grown on medium‐ to fine‐textured soils in the western Corn Belt to reduce excess N available for loss and to reduce unnecessary input costs.

Soils with high levels of P can contribute to excess P in runoff and subsequently pollute the surface water. Excess P in the soil can be removed from the system by harvesting crops. The objectives of this study were to evaluate corn ( Zea mays L.) P removal effects on soil P reduction, and to evaluate various corn hybrids and soybean [ Glycine max (L.) Merr.] varieties for differences in grain P concentration and P removal. Soil with varying P levels as a result of annual or biennial beef cattle ( Bos taurus ) feedlot manure or compost application was cropped to corn for 4 yr without any P addition. In other studies under various water and N regimes, corn hybrids and soybean varieties were evaluated for grain P concentration and P removal. Four years of corn production without P addition lowered surface soil (0–15 cm) extractable P level (Bray and Kurtz no. 1) from 265 mg kg −1 to 171 mg kg −1 in the biennial N‐based compost treatment. Based on a decay equation, it would have required 10 yr of corn P removal to lower the soil P level to the original 69 mg kg −1 that existed before treatment application. The rate of decrease in extractable soil P was greater when soil P was higher and reduced with decreasing soil P level. Most of the P in the plants was absorbed from the 0‐ to 15‐cm soil depth since no significant reduction in soil P level was observed from 1996 to 1999 in the 15‐ to 30‐cm soil depth. Across 2 yr, there was as much as 54% difference among corn hybrids for grain P removal. The differences in P concentrations among corn hybrids indicated that hybrids could be selected for low P uptake when lower P level in ethanol production by‐product or in animal ration and subsequently in manure is desired. Soybean grain P concentration was nearly twice that for corn but grain P removal was less for soybean than for corn. Crop P removal can significantly reduce soil P level with time.

Understanding long‐term management effects on soil properties is necessary to determine the relative sustainability of cropping systems. Soil physical, chemical, and biological properties were measured in a long‐term cropping system study in the Western Corn Belt. Properties were evaluated after 16 yr in four crop sequences [continuous corn ( zea mays L.) (CC), corn–soybean [Glycine max. (L.)] (C–SB), corn–oat ( Avena sativa L.) + clover (80% sweet clover [ Melilotus officinalis L.] and 20% red clover [ Trifolium pratense L.])–grain sorghum [( Sorghum bicolor (L.) Moench)–soybean (C–OCL–SG–SB), and corn–soybean‐grain sorghum–oat + clover (C–SB–SG–OCL)] each at three N fertilization rates (ZERO, LOW, and HIGH) to a soil depth of 30.5 cm on a Sharpsburg silty clay loam (fine, smectitic, mesic Typic Argiudolls). Nitrogen fertilization had a greater impact on soil properties than crop sequence, with management effects most pronounced at 0 to 7.6 cm. Increased N rate resulted in greater organic C, total N, and particulate organic matter (POM), but lower soil pH. Increased N rate also reduced microbial biomass by ∼20% between the HIGH and ZERO N‐rate treatments. The C–SB–SG–OCL sequence possessed more potentially mineralizable N (PMN) (57 vs. 46 kg ha −1 for average of CC and C–SB) and a higher percentage of POM present as soil organic matter (17.1% for the C–SB–SG–OCL sequence vs. 13.9% for other sequences). Within the context of soil functions and cropping system performance, results from this study indicate the C–SB–SB–OCL sequence enhanced nutrient cycling efficiency, while N fertilization resulted in a trade‐off between its positive effect on biological productivity and negative effect on nutrient cycling efficiency.

Assessing effects of cropping systems on soil organic matter (SOM) and soil carbon (C) changes are necessary to make accurate projections regarding sequestration and emission of CO2 by agricultural soils. This process requires substantial annual management inputs and large outlays for soil sampling and analyses. Our objectives were (1) to evaluate and test an alternative method for soil organic matter determination, (2) to determine if crop rotation and N fertilizer management significantly affected soil organic matter at the beginning (1986) or after 12 yrs (1998), and (3) to determine if total soil. organic matter levels have changed after 12 years in a long-term cropping system study. Soil samples were taken in 1986 and 1998 to a depth of 150 cm in 30 cm increments. Total soil organic C and organic matter by weight loss-on-ignition concentrations were determined for the soil samples taken in 1998. Results from both methods of analyses for the 1998 samples were highly correlated. No significant differences in soil organic matter by weight loss-on-ignition or total soil organic C concentrations between crop rotations or nitrogen (N) fertilizer rates were obtained for either sampling date, in the change in soil organic matter concentrations between dates, or total soil C amounts in the profile (0 to 150 cm) after 12 yrs (1998). Although no differences in soil organic matter (soil C) were obtained in the study, the excellent correlation between results of the two methods of organic matter analyses demonstrates that the less expensive and easier to use weight loss-on-ignition method can be used to make these types of assessments.

It has been commonly accepted that crop rotations reduce risk compared with monoculture systems. Quantifying this phenomenon requires that effects of yield stability on risk (positive or negative) arising from rotating crops be separated from other risk elements. Using an ARS-University of Nebraska series of yields for corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] grown over a 14-yr period, both in rotation and in monoculture, the impact of crop rotation on risk was isolated and estimated. Risk was defined as the failure to meet an annual per-hectare net return target. A corn-soybean rotation had significantly less risk than monoculture practices. Diversification was found to contribute to part of this reduction while higher yields and reduced cost contributed to the remainder. This reduction in risk occurred even though the corn-soybean rotation had a higher yield variance.

Remote sensing—the process of acquiring information about objects from remote platforms such as ground‐based booms, aircraft, or satellites—is a potentially important source of data for site‐specific crop management, providing both spatial and temporal information. Our objective was to use remotely sensed imagery to compare different vegetation indices as a means of assessing canopy variation and its resultant impact on corn (Zea maysL.) grain yield. Treatments consisted of five N rates and four hybrids, which were grown under irrigation near Shelton, NE on a Hord silt loam in 1997 and 1998. Imagery data with 0.5‐m spatial resolution were collected from aircraft on several dates during both seasons using a multispectral, four‐band [blue, green, red, and near‐infrared reflectance] digital camera system. Imagery was imported into a geographical information system (GIS) and then georegistered, converted into reflectance, and used to compute three vegetation indices. Grain yield for each plot was determined at maturity. Results showed that green normalized difference vegetation index (GNDVI) values derived from images acquired during midgrain filling were the most highly correlated with grain yield; maximum correlations were 0.7 and 0.92 in 1997 and 1998, respectively. Normalizing GNDVI and grain yield variability within hybrids improved the correlations in both years, but more dramatic increases were observed in 1997 (0.7 to 0.82) than in 1998 (0.92 to 0.95). This suggested GNDVI acquired during midgrain filling could be used to produce relative yield maps depicting spatial variability in fields, offering a potentially attractive alternative to use of a combine yield monitor.

Effects of year-to-year variability in agricultural production systems have always been a concern, but few studies are conducted for a long enough period of time where management system evaluations and assessments can be made. Given this limitation, questions about whether management systems are effective at reducing temporal variability remain in production agriculture. These questions prompted investigation of a long-term crop rotation study to determine effects of crop rotation and N fertilization practices in a rainfed environment on normalized grain yields. Sixteen years of grain yield data from an experiment with seven cropping systems (three monoculture, two 2-yr rotations, and two 4-yr rotations) and three N fertilizer rates are included in the study. Grain yields from 1983 through 1998 for each crop and N fertilizer treatment were normalized and then relative grain yield within a cropping system and N fertilizer treatment were combined, which resulted in relative yields for each cropping system and N fertilizer treatment combination in each year. Using the normalized yields, overall analyses of the 16 yr of data were conducted to assess what effects cropping systems and N fertilizer have on yield variability. These analyses demonstrated that crop rotation systems are more effective at reducing long-term yield variability than monoculture systems, even with N fertilizer. As expected, N fertility, obtained from either fertilizer or legumes in monoculture or rotation systems, is probably one of the most, if not the most important aspect in reducing yield variability. Analyses of normalized yields also demonstrated that reductions in yield variability could be obtained in many of our cropping systems with proper management.

In July of 1993 and 1994, southern Nebraska experienced devastating windstorms, with winds estimated to exceed 45 m s -1 . These storms resulted in severe brittle-snap of corn (Zea mays L.), with stalks breaking near the primary ear node in the basal portion of an elongating internode. In the storm path were several experiments established on a Hord silt loam (Cumulic Haplustolls) to determine the effect of selected management practices (crop rotation, hybrid selection, planting date, and N fertilization) on nitrate leaching to ground water from irrigated cropland. After the storms, the number of broken plants was determined in these experiments to evaluate how management practices influenced severity of the damage. In 1993. crop rotation, hybrid, planting date, and N fertilization, and their interactions, all affected the amount of brittle-snap. Treatments that resulted in more rapid growth (optimum to excess N rates, corn rotated with soybean [Glycine max (L.) Merr.], and early planting) increased the severity of damage. In continuous corn, 7% of the plants broke, compared with 33for rotated corn; damage ranged from 4 to 33 among hybrids; and percent broken plants increased quadratically. from 8for the 0 kg N ha 1 treatment to 24at N rates equal to or greater than 80 kg N ha -1 . Only the hybrid factor was significant in 1994. Amount of brittle-snap was related to stage of development (r = 0.55, n = 160, P < 0.001). The great difference in severity of damage among hybrids indicates that the current best management strategy to limit brittle-snap losses is to plant hybrids less prone to breakage. Alternative management strategies, such as late planting, suboptimal N rates, and continuous cropping of corn, all are known to limit yield regardless of windstorms, There is a need for greater knowledge of cell and tissue characteristics that render hybrids susceptible or resistant to brittle-snap. Also, methods for simulating brittle-snap are needed to foster effective selection for resistant lines in breeding programs.

Early ventures into site-specific management involved fertilizer management decisions based on soil chemical properties characterized by some form of grid sampling. This is both labor and capital intensive and practitioners quickly began investigating other methods to get a measure of spatial variability. Aerial photographs, which were mainly used to evaluate and assess crop status, allow for the collection of whole-field data at relatively low cost. Our objective is to determine what relationships exist between aerial spectral data and intensive grid soil test results and whether this information can be used to improve future soil sampling strategies. Soil-test organic matter (OM) and Bray-1 P concentrations were measured on soil samples taken using an alternating 12.2- by 24.4-m grid in late March 1994 from a quarter section under center pivot irrigation. Spectral data were collected in the spring of 1996 prior to planting using a multispectral network of digital cameras. Correlations of brightness values from the blue, green, and NIR bands with both OM and Bray-1 P were significant, but relatively low. Normality tests revealed that brightness values for the spectral data sets were generally evenly distributed while those of the soil test OM and Bray-1 P were positively skewed. Many of the very high soil-test data values were due to past management. When those values were removed from the database, greater correlations between spectral data and soil test data were obtained. These results substantiated that aerial imagery can be used to improve sampling strategies, but it must be used in conjunction with existing knowledge and past management histories.

Crop rotation offers several advantages to improve farmers' systems worldwide. The positive attributes of rotations are usually dependent upon crop choices, cropping sequence, soil fertility management, and weather factors. Of these, weather is most uncontrollable, but its effects can be partially manipulated through management. This study presents information on how weather affected cropping systems in a 12-yr span. The study also illustrates the use of indices of weather (composite) variables to predict yields. The composite variables are three biological windows (BW) and a standardized precipitation index (SPI). Biological windows based on soil temperature and soil moisture indicate the number of days favorable for or detrimental to crop growth. Biological window 2 (temperature > 41°F+moist soil) in combination with May temperature explained more than 80% of the variability in corn (Zea mays) and soybean (Glycine max) yields. August temperature negatively affected corn and soybean yields, especially in continuous monocrops. Preseason 9-mo SPI (September-May) explained up to 50% of the subsequent season's corn yields, and this information could influence crop choice. Overall, yields in rotations were higher than in continuous monocropping systems. Nitrogen fertilization increased cereal yields more in continuous monocropping than in rotations with legumes. Corn and soybean appeared more sensitive to soil moisture and temperature variability (P 0.05). Risk as measured by standard deviation in yields or incomes did not differ significantly among systems.