Introduction: The detrimental impact of weeds and their inadequate management is a significant contributing factor to the decline in both the quality and quantity of crops. Weeds engage in competition with crops by depleting finite resources, including soil nutrients, moisture availability, and light, thereby leading to a decline in crop growth and yield. In conjunction with the non-uniformity induced by management practices in agricultural areas, weeds are also recognized as a contributing factor to the uneven distribution of crop productivity. Understanding the spatial distribution of weeds within a given field has the potential to enhance the effectiveness of weed management strategies. In light of this matter, a recent study was undertaken to assess the spatial arrangement of Chenopodium album and its impact on the productivity and various components of wheat yield.
Materials and Methods: This study was carried out in a field located in Mobarakeh county, within the Isfahan province, over the course of the 2019-2020 period, employing geostatistical techniques. Data on both weed (density and biomass of Chenopodium album) and wheat (including grain number per spike, number of spikes, 1000-grain weight, and grain yield) were gathered from 104 locations within a field, using a 2 × 2 m grid. The density and biomass of Chenopodium album, as well as the yield and yield components of wheat, were assessed in each sampling event using quadrats measuring 0.25 m². The cross-semivariogram was employed to elucidate the spatial correlation between two variables, namely weed population and wheat yield. The semivariograms and cross-semivariograms were computed using the GS+ and Variowin software packages, which are tools for analyzing spatial data in two dimensions (2D) (Spring Verlag, New York, USA). The estimation of Pearson correlation coefficients was conducted using the SPSS software.
Results and Discussion: The findings indicated that the average density and biomass of Chenopodium album were recorded as 2.42 individuals per square meter and 16.11 grams per square meter, respectively. Additionally, the findings revealed that 74% of the sampled locations exhibited an absence of Chenopodium album. The analysis of the semivariogram revealed that the distribution of Chenopodium album's density and biomass exhibited spatial heterogeneity within the field. The patchiness of Chenopodium album's density and biomass was observed to be moderate, with values of 64.7% and 50.0% respectively. According to the fitted models, the range for weed density and biomass was 3.68 and 20.42 meters, respectively.Weed patches frequently exhibited a greater elongation along the direction of the planting rows. The findings of the study revealed that the variables of 1000-grain weight, number of spikes, grain number per spike, and grain yield exhibited a non-uniform distribution pattern. The spatial autocorrelation values for the 1000-grain weight, number of spikes, grain number per spike, and grain yield were found to be 82.1%, 57.0%, 50.0%, and 50.2%, respectively. Semivariogram analysis showed that 1000-grain weight had a strong spatial autocorrelation. High spatial dependence was observed between the maps of grain yield and yield components (1000-grain weight, number of spike, grain number per spike) of wheat. Given the positive correlation between the yield components and grain yield in wheat, it is reasonable to anticipate a spatial congruence between these variables when represented on maps. Additionally, the Pearson correlation coefficients indicate a positive and statistically significant relationship between grain yield and the 1000-grain weight (0.24^*), number of spikes (0.84^**), and grain number per spike (0.82^**). The results of the Cross-semivariogram analysis demonstrated a statistically significant spatial association of 76.4% between weed density and reverse grain yield of wheat. The results of the cross-semivariogram showed that negative spatial correlation of 75.8% between weed biomass and grain yield in wheat. The maps revealed a strong correlation between areas characterized by high weed density and biomass, and areas exhibiting low wheat grain yield. The results of the Pearson correlation analysis revealed a statistically significant negative correlation between weed density and biomass with the grain yield of wheat. The correlation coefficients were -0.51^** and -0.45^**%, respectively. The findings of the study revealed that in instances where there existed a strong correlation coefficient between two variables, the cross-variogram also provided evidence of the spatial correlation between the two variables.
Conclusion: The findings from the analysis of cross-semivariograms, estimation of Pearson correlation coefficients, and comparison of the maps revealed a negative correlation between the grain yield of wheat and the presence of Chenopodium album in the field. In a broad sense, it can be asserted that the uneven distribution of weeds leads to an uneven distribution of crop yield and its various components within the agricultural field.