The critical period of weed interference in upland rice in northern Guinea savanna: Field measurement and model prediction

Luxuriant weed growth destroying rice crops is a major problem in tropical Africa. The objective of this study was to determine the critical period of weed infestation in upland rice varieties in order to enable the development of more precise weed management recommendations for farmers. The effects of 10 differing periods of weed management on upland rice yield were studied in experiments with five rice varieties (three interspecific NERICA: NERICA1, NERICA2, and NERICA4) and the parents ( Oryza sativa WAB 56-104 and Oryza glaberrima CG 14) during the 2004 and 2005 rainy seasons at Farako (Mali). INTERCOM model was used to explore the relationship between duration and timing of weed competition and rice crop yield loss, and the applicability of the model in rice cropping based weed management. The critical period of weed infestation determined from the field experiment was similar for the three New Rice for Africa (NERICA) varieties and the O. sativa parent (WAB 56-104), and was between 14 and 42 days after seeding (DAS). For the O. glaberrima parent (CG 14), the critical period was between 28 and 42 DAS. Weed competition either before or after these critical periods had negligible effects on crop yield. During the 2 years, yields of NERICA varieties and WAB 56-104 averaged 2700 and 400 kg ha -1 under weed-free plots and no weed control plots, respectively, indicating a yield loss of 85%. For GG 14, yields averaged 900 and 300 kg ha -1 under weed-free plots and no weed control plots, respectively, resulting in a 66% yield loss. The occurrence and composition of weeds during the two years were similar with a mean of 40% broadleaves, 35% grasses and 25% sedges. The most important weeds were Imperata cylindrica , Cyperus sphacelatus and Digitaria longiflora . During both calibration and testing efforts, the INTERCOM model satisfactorily simulated rice NERICA1 LAI, shoot dry weight and yields ( r 2 ranging from 0.71 to 0.87). There appears to be room for improvement in the model with regard to the assumption that nutrients are not limiting to crop growth, but the use of the model for simulating the interactions between rice crop yield losses, weed density, and duration of weed competition appears promising. Results of this study can serve as a guide for optimum timing of weed control to maximize upland rice yield in West Africa.