Advances in statistical software allow statistical methods for nonlinear regression analysis of dose-response curves to be carried out conveniently by non-statisticians. One such statistical software is the program R with the drc extension package. The drc package can: (1) simultaneously fit multiple dose-response curves; (2) compare curve parameters for significant differences; (3) calculate any point along the curve at the response level of interest, commonly known as an effective dose (e.g., ED30, ED50, ED90), and determine its significance; and (4) generate graphs for publications or presentations. We believe that the drc package has advantages that include: the ability to relatively simply and quickly compare multiple curves and select ED-levels easily along the curve with relevant statistics; the package is free of charge and does not require licensing fees, and the size of the package is only 70 MB. Therefore, our objectives are to: (1) provide a review of a few common issues in dose-response-curve fitting, and (2) facilitate the use of up-to-date statistical techniques for analysis of dose-response curves with this software. The methods described can be utilized to evaluate chemical and non-chemical weed control options. Benefits to the practitioners and academics are also presented.

Weeds are a major biotic constraint to aerobic rice production in Asia. Research is needed on the effects of cultural practices on weed management in aerobic rice, including techniques such as planting pattern and competitive cultivars. Field experiments were conducted in Punjab, India, in the wet seasons of 2008 and 2009 to study the growth of weeds and two rice cultivars [PR 115 and Punjab (P.) Mehak 1] in relation to planting pattern (uniform rows [23-cm row spacing] and paired rows [15-, 30-, and 15-cm row spacings]) under aerobic conditions. Junglerice and rice flatsedge were the dominant weed species during the early stages of the crop, while Chinese sprangletop and large crabgrass were the predominant species during flowering stage of the crop. Weed dry matter was not affected by planting pattern of P. Mehak 1; however, for PR 115, weed dry matter was greater in rice grown in uniform rows (244 g m−2) than in paired rows (183 g m−2). Planting patterns did not affect weed-free crop growth and yield, but weeds tended to be more abundant in the uniform planting system, particularly under cultivar PR 115. Consequently, this cultivar grew and yielded better under the paired rows when weeds were present. The cultivar PR 115 had greater yield potential than P. Mehak 1, but growth and productivity of P. Mehak 1 were unaffected by the planting patterns, suggesting better competitive ability against weeds than PR 115. The results imply that yield of some aerobic rice cultivars may be improved by exploring competitiveness of rice cultivars through paired row planting patterns. There is a need to study plasticity changes for cultivars which respond with more competiveness in paired rows. The identified traits could be useful as selection criteria for screening weed-competitive cultivars in paired row pattern.