Weed communities in Italian maize fields as affected by pedo-climatic traits and sowing time

• Study on relations between weed communities and pedoclimatic traits in maize fields.
• 120 weed species found, only five were present on more than 50% of sites.
• Sand and alkaline soils favored monocotyledonous species.
• Clay and alkaline soils favored dicotyledonous species.
• Soil texture, CEC, pH, and nutrient contents predicted some weed indices.

This study examined relationships between weed communities and some pedo-climatic traits in Italian maize cultivation areas. A weed dataset was amassed from studies conducted independently by research groups during 1998–2013. Included were herbicide efficacy field trials and weed surveys from about 600 sites representing 175 northern and central Italy maize fields. The dataset was honed to results from untreated plots in which weed data were collected at least once (June/July) each season. For sites observed more often, only the survey with the highest weed species count was used.Of the approximate 120 species found, just five were present on more than 50% of sites: Chenopodium album, Echinochloa crus-galli, Amaranthus retroflexus, Solanum nigrum, and Persicaria maculosa. Indices were calculated to describe weed community structure: total weed species count, monocotyledonous and dicotyledonous species counts, and total weed density. Additional soil and climate site data were collected or obtained from regional databases: pH reaction, texture, organic matter content, total nitrogen, Mg/K ratio, assimilable phosphorus, cation exchange capacity (CEC), and C/N ratio, annual total precipitation, annual mean temperature, and Thornthwaite climate classification. Pedo-climatic traits and weed indices relationships were investigated using linear correlation analysis (CA), discriminant analysis (DA), and principal component analysis (PCA).CA and PCA highlighted a weak bias (higher count and density) by monocotyledonous species for sand and alkaline soils, while clay and alkaline soils favored dicotyledonous species. DA classified the sites well based on weed indices using soil parameters as predictor variables, in particular for a Piemonte region (northwest Italy) data subset. Soil texture, CEC, pH, and some nutrient contents significantly predicted some weed indices. This study pointed out that Italian maize field weed communities are influenced by some pedoclimatic traits; the weak relationships observed might be mitigated by the overall influence of crop practices on weed dynamics.