In the Midwestern United States, winter hilling, consisting of two tillage activities per year, is required in vinifera-grape vineyards for winter protection. However, this practice often leads to severe soil erosion and pesticide offsite movement. The effectiveness of wheat straw mulch as a replacement for soil mounding was investigated as a way of providing winter protection and to mitigate pesticide leaching and runoff. A laboratory experiment was conducted where simazine was applied to wheat straw or bare soil and then followed by simulated rainfalls. When compared with bare soil, straw reduced simazine leaching and runoff by 40 and 68%, respectively. Adsorption or interception, or both, of simazine by straw were responsible for this effect. Additionally, straw reduced soil erosion by 95% and would largely reduce simazine runoff associated with sediment displacement. The first simulated rainfall contributed 70 and 34% of total simazine runoff from bare soil and straw, respectively. In conclusion, mulching with straw during winter months to provide winter protection could be an effective practice for controlling simazine offsite movement and soil erosion in vinifera vineyards.

Assessing belowground plant interference in rice has been difficult in the past because intertwined weed and crop roots cannot be readily separated. A 13C discrimination method has been developed to assess distribution of intermixed roots of barnyardgrass and rice in field soils, but the suitability of this approach for other rice weeds is not known. 13C depletion levels in roots and leaves of rice were compared with those of 10 troublesome weed species grown in monoculture in the greenhouse or field. Included were C4 tropical grasses: barnyardgrass, bearded sprangletop, Amazon sprangletop, broadleaf signalgrass, fall panicum, and large crabgrass; C4 sedge, yellow nutsedge; and C3 species: red rice, gooseweed, and redstem. Rice root δ13C levels averaged ∼ −28‰, indicating that these roots are highly 13C-depleted. Root δ13C levels ranged from −12‰ to −17‰ among the tropical grasses, and were −10‰ in yellow nutsedge, indicating that these species were less 13C depleted than rice, and were C4 plants suitable for 13C discrimination studies with rice. Among the C4 species, bearded sprangletop and yellow nutsedge were most and least 13C depleted, respectively. δ13C levels in shoot and root tissue of pot-grown plants averaged 6% greater for C4 plants and 9% greater for rice in the field than in the greenhouse. In pots, shoots of rice typically were slightly more 13C depleted than roots. A reverse trend was seen in most C4 species, particularly for broadleaf signalgrass and plants sampled from field plots. Corrections derived from inputs including the total mass, carbon mass, carbon fraction, and δ13C levels of roots and soil increased greatly the accuracy of root mass estimates and increased slightly the accuracy of root δ13C estimates (∼ 0.6 to 0.9%) in samples containing soil. Similar corrective equations were derived for mixtures of rice and C4 weed roots and soil, and are proposed as a labor-saving option in 13C discrimination root studies.

Although foliar herbicide absorption has been studied intensively, there is currently no standardized method for data analysis when evaluating herbicide absorption over time. Most peer-reviewed journals require the treatment structure of data be incorporated in the analysis; however, many herbicide absorption studies published in the past 5 yr do not account for the time structure of the experiment. Herbicide absorption studies have been presented in a variety of ways, making it difficult to compare results among studies. The objective of this article is to propose possible nonlinear models to analyze herbicide absorption data and to provide a stepwise framework so that researchers may standardize the analysis method in this important research area. Asymptotic regression and rectangular hyperbolic models with similar parameterizations are proposed, so that the maximum herbicide absorption and absorption rate may be adequately modeled and statistically compared among treatments. Adoption of these models for herbicide absorption analysis over time will provide a standardized method making comparison of results within and among studies more practical.