Cover crops (CCs) can provide multiple soil, agricultural production, and environmental benefits. However, a better understanding of such potential ecosystem services is needed. We summarized the current state of knowledge of CC effects on soil C stocks, soil erosion, physical properties, soil water, nutrients, microbial properties, weed control, crop yields, expanded uses, and economics and highlighted research needs. Our review indicates that CCs are multifunctional. Cover crops increase soil organic C stocks (0.1–1 Mg ha−1 yr−1) with the magnitude depending on biomass amount, years in CCs, and initial soil C level. Runoff loss can decrease by up to 80% and sediment loss from 40 to 96% with CCs. Wind erosion potential also decreases with CCs, but studies are few. Cover crops alleviate soil compaction, improve soil structural and hydraulic properties, moderate soil temperature, improve microbial properties, recycle nutrients, and suppress weeds. Cover crops increase or have no effect on crop yields but reduce yields in water‐limited regions by reducing available water for the subsequent crops. The few available studies indicate that grazing and haying of CCs do not adversely affect soil and crop production, which suggests that CC biomass removal for livestock or biofuel production can be another benefit from CCs. Overall, CCs provide numerous ecosystem services (i.e., soil, crop–livestock systems, and environment), although the magnitude of benefits is highly site specific. More research data are needed on the (i) multi‐functionality of CCs for different climates and management scenarios and (ii) short‐ and long‐term economic return from CCs.

The critical period for weed control (CPWC) is a period in the crop growth cycle during which weeds must be controlled to prevent yield losses. Knowing the CPWC is useful in making decisions on the need for and timing of weed control and in achieving efficient herbicide use from both biological and economic perspectives. An increase in the use of herbicide-tolerant crops, especially soybean resistant to gly-phosate, has stimulated interest in the concept of CPWC. Recently, several studies examined this concept in glyphosate-resistant corn and soybean across the midwest-ern United States. However, these studies presented various methods for data analysis and reported CPWC on the basis of a variety of crop-or weed-related parameters. The objectives of this study are (1) to provide a review of the concept and studies of the CPWC, (2) to suggest a common method to standardize the process of data analysis, and (3) to invite additional discussions for further debate on the subject. Wide adoption of the suggested method of data analysis will allow easier comparison of the results among sites and between researchers. Nomenclature: Glyphosate; corn, Zea mays L.; soybean, Glycine max (L.) Merr.

The critical period for weed control (CPWC) is the period in the crop growth cycle during which weeds must be controlled to prevent unacceptable yield losses. Field studies were conducted in 1999 and 2000 in eastern Nebraska to evaluate the influence of nitrogen application on the CPWC in dryland corn in competition with a naturally occurring weed population. Nitrogen fertilizer was applied at rates equivalent to 0, 60, and 120 kg N ha Ϫ1. A quantitative series of treatments of both increasing duration of weed interference and length of weed-free period were imposed within each nitrogen main plot. The beginning and end of the CPWC based on an arbitrarily 5% acceptable yield loss level were determined by fitting the logistic and Gompertz equations to relative yield data representing increasing duration of weed interference and weed-free period, respectively. Despite an inconsistent response of corn grain yield to applied nitrogen, there was a noticeable influence on the CPWC. The addition of 120 kg N ha Ϫ1 delayed the beginning of the CPWC for all site-years when compared with the 0-kg N ha Ϫ1 rate and for three of the four site-years when compared with the 60-kg N ha Ϫ1 rate. The addition of 120 kg N ha Ϫ1 also hastened the end of the CPWC at three of the four site-years when compared with both reduced rates. The yield component most sensitive to both nitrogen and interference from weeds was seed number per ear. Practical implications of this study are that reductions in nitrogen use may create the need for more intensive weed management.

A new maize (Zea mays L.) simulation model, Hybrid-Maize, was developed by combining the strengths of two modeling approaches: the growth and development functions in maize-specific models represented by CE-RES-Maize, and the mechanistic formulation of photosynthesis and respiration in generic crop models such as INTERCOM and WOFOST. It features temperature-driven maize phenological development, vertical canopy integration of photosynthesis, organ-specific growth respiration, and temperature-sensitive maintenance respiration. The inclusion of gross assimilation, growth respiration and maintenance respiration makes the Hybrid-Maize model potentially more responsive to changes in environmental conditions than models such as CERES-Maize. Hybrid-Maize also requires fewer genotype-specific parameters without sacrificing prediction accuracy. A linear relationship between growing degree-days (GDD) from emergence to silking and GDD from emergence to physiological maturity was used for prediction of day of silking when the former is not available. The total GDD is readily available for most commercial maize hybrids. Preliminary field evaluations at two locations under high-yielding growth conditions indicated close agreement between simulated and measured values for leaf area, dry matter accumulation, final grain and stover yields, and harvest index (HI). Key areas for further model improvement include LAI prediction at high plant density, and biomass partitioning, carbohydrate translocation, and maintenance respiration in response to above-average temperature, especially during reproductive growth. The model has not been evaluated under conditions of water and/or nutrient stress, and efforts are currently in progress to develop and validate water and nitrogen balance components for the Hybrid-Maize model.

and Amthor (1999) suggested that the RUE era in crop modeling should be closed. Accurate measurement of crop growth and radiation use efficiencyA number of factors contribute to the variation in (RUE) under optimal growth conditions is required to predict plant reported estimates of RUE (Sinclair and Muchow, 1999). dry matter accumulation and grain yield near the genetic growth potential. Research was conducted to quantify the biomass and leafEstimates of RUE depend on whether radiation is meaarea index (LAI) accumulation, extinction coefficient, and RUE of sured as total solar radiation or as PAR. While some maize (Zea mays L.) under conditions of optimal growth. Maize was authors suggest that conversion of RUE based on solar grown in two environments over five growing seasons (1998)(1999)(2000)(2001)(2002).radiation to that based on PAR is achieved simply by Total aboveground biomass at maturity ranged from 2257 g m Ϫ2 in multiplying by the fraction of total solar radiation that 1998 to 2916 g m Ϫ2 in 2001; values that are considerably greater than is photosynthetically active (usually 0.5, Sinclair and the biomass achieved in most previous studies on RUE in maize. Muchow, 1999), it has been pointed out that the appro-Peak LAI ranged from 4.8 to 7.8. Maize extinction coefficients during priate multiplication factor depends on canopy LAI vegetative growth (k ) were within the range of recently published (Bonhomme, 2000). The radiation intercepted by a crop values (0.49 Ϯ 0.03), with no clear pattern of differences in k among years. Seasonal changes in interception of photosynthetically active is different from that absorbed by it and, therefore, radiation (PAR) were similar across all but one year. Estimates of introduces variation in RUE calculations. In agreement RUE were obtained using the short-interval crop growth rate method with Sinclair and Muchow (1999), Bonhomme (2000) and the cumulative biomass and absorbed PAR (APAR) method. suggests that assuming 85% of intercepted PAR (IPAR) Values of RUE obtained using the two methods were 3.74 (Ϯ0.20) g is absorbed by the leaf canopy is accurate when canopy MJ Ϫ1 APAR and 3.84 (Ϯ0.08) g MJ Ϫ1 APAR, respectively, and did LAI is large, but the value is smaller when canopies not vary among years. This compares to a published mean RUE are less dense. Variation in estimates of RUE can be for maize of 3.3 g MJ Ϫ1 of intercepted PAR (Mitchell et al., 1998).substantially reduced by measuring both intercepted Moreover, RUE did not decline during grain filling. Differences in and absorbed radiation continuously during a sampling