Spatial distribution of Amaranthus retroflexus and Solanum nigrum under different weed control methods

Introduction
In each farm field and over time due to the long-term use of inputs and varied tillage practices as well as different management operations, the factors affecting plant yield would be complex (Liu et al., 2013). The impacts of these factors are not usually taken into consideration in farm management. For example, the herbicides are usually applied uniformly based on the mean weed pressure in the field. Uniform management in situations where there is spatial variation, not only will not be economically efficient but also will have detrimental environmental consequences. Cardina and Doohan (2008) reported that although weeds are often dense in some parts of the field, their density is not independent of each other. In other words, their density depends on the sampling distance of species. Identifying weed distribution on the farm is a necessary step before site-specific management. Site-specific management is in the direction of sustainable agricultural purposes. This thereby highlights the importance of the study of the spatial distribution of weeds. The aim of this study was to investigate the spatial distribution of pigweed and nightshade under different weed control methods.
Materials and Methods
This experiment was conducted at the experimental station of Ferdowsi University of Mashhad during the growing season of 2016. A plot of field measuring 56.25 × 21 m was selected and maize S.C 704 was planted in it. Each control method including chemical control, integrated control (mechanical+chemical) and weedy control was applied to one-third of the field. Data collected from sampling at 270 points based on a 1.87×2.5 m grid at two stages at the first and the last of corn growth season (30 and 90 days after corn planting). Amaranthus retroflexus and Solanum nigrum species had more than 96% density of total weeds.
The evaluating of the spatial distribution of weed species was done by a geostatistical analysis of the species counts. The principal tool of geostatistics is the variogram (Goudy et al., 2001). The function showed in equation (1) links the expected squared difference of a variable between any two places:

equation (1)
Where z(x) and z(x + h) are random variables at positions x and x + h. h is the distance of pair of points. Validation of the variogram model was determined by (equation 2) that calculating the root mean square error (RMSE):


equation (2)


Results and Discussion
According to the percentage of RMSE error, The fitted variogram models to density pigweed and nightshade were most often in accordance with the spherical model in integrated control, chemical control and weedy control at the beginning and end of the growing season. This result, in addition to indicating a patchy distribution of species, also showed that this structure in species has been preserved after mechanical and chemical control. In the integrated control, the range of pigweed and nightshade, decreased about 15.5 m (48%) and 2.8 m (30%), at the end of the growing season respectively, while in the weedy control, the range of these species increased about 0.5 m (6%) and 2 m (17%) at the end of the growing season, respectively. In the chemical control the range of pigweed decreased about 0.68 m, and the range of nightshade, increased about 0.6 m at the end of the growing season of corn.

Conclusion
The results of many studies indicate a patchy distribution of weeds. In this study, the patchy structure of weeds remained even after mechanical and chemical control of weeds. It can be said mechanical and chemical control of weeds destroy around of patches of weeds, but the center of the weed patches remains. Also in this study, the range of species was affected by weed control methods so that integrated control of weeds decreased the range of pigweed and nightshade and chemical control of weeds prevented expanding the range of pigweed.