Pinke G, Csiky J, Mesterházy A et al.: The impact of management on weeds... (2014)

Pinke G, Csiky J, Mesterházy A, Tari L, Pál RW, Botta-Dukát Z & Czúcz B
2014
The impact of management on weeds and aquatic plant communities in Hungarian rice crops.
Weed Research 54: 388–397
Összefoglaló: 

This study assessed the cultural and weed-management factors influencing the weed communities of Hungarian rice fields. Hungary is situated at the northern limit of rice production with about 300 years history of rice culture. We surveyed the weed flora and 25 background variables in 100 active rice fields. Using a minimal adequate model containing 11 terms, 48.5 % of the total variation in weed species data could be explained. The net effects of 9 variables on species composition were significant. Crop cover was found to be the most important explanatory variable, which was followed by the herbicides penoxsulam & azimsulfuron, tillage depth, phosphorous & potassium fertilisers, years after last rotation, water depth in May, sowing type, pendimethalin and water conductivity. Filamentous algae, as the most abundant group of weeds, were positively associated with deep tillage, deep water, and surface sowing. Echinochloa crus-galli, one of the most troublesome grass-weeds was associated with low rice cover, shallow water and later years after crop rotation, while weedy rice favoured high crop cover, deep water and soil sowing. These findings can be used to design improved weed management strategies. The occurrence of red list species and charophytes in diverse micro-mosaic patterns deserves attention from a conservation perspective as well. The maintenance of these unique charophyte communities can be facilitated by shallow tillage without soil inversion.

Angol nyelvű összefoglaló: 

This study assessed the cultural and weed-management factors influencing the weed communities of Hungarian rice fields. Hungary is situated at the northern limit of rice production with about 300 years history of rice culture. We surveyed the weed flora and 25 background variables in 100 active rice fields. Using a minimal adequate model containing 11 terms, 48.5 % of the total variation in weed species data could be explained. The net effects of 9 variables on species composition were significant. Crop cover was found to be the most important explanatory variable, which was followed by the herbicides penoxsulam & azimsulfuron, tillage depth, phosphorous & potassium fertilisers, years after last rotation, water depth in May, sowing type, pendimethalin and water conductivity. Filamentous algae, as the most abundant group of weeds, were positively associated with deep tillage, deep water, and surface sowing.