Weed infestations and associated yield losses require effective weed control measures in soybean and sugar beet. Besides chemical weed control, mechanical weeding plays an important role in integrated weed management systems. Field experiments were conducted at three locations for soybean in 2013 and 2014 and at four locations for sugar beet in 2014 to investigate if automatic steering technologies for inter-row weed hoeing using a camera or RTK-GNSS increase weed control efficacy, efficiency and crop yield. Treatments using precision farming technologies were compared with conventional weed control strategies. Weed densities in the experiments ranged from 15 to 154 plants m⁻² with Chenopodium album, Polygonum convolvulus, Polygonum aviculare, Matricaria chamomilla and Lamium purpureum being the most abundant species. Weed hoeing using automatic steering technologies reduced weed densities in soybean by 89% and in sugar beet by 87% compared to 85% weed control efficacy in soybean and sugar beet with conventional weeding systems. Speed of weed hoeing could be increased from 4 km h⁻¹ with conventional hoes to 7 and 10 km·h⁻¹, when automatic steering systems were used. Precision hoeing technologies increased soybean yield by 23% and sugar beet yield by 37%. After conventional hoeing and harrowing, soybean yields were increased by 28% and sugar beet yield by 26%.

Soybean field experiments were performed to investigate the weed-suppressing effects of different tillage systems and cover crop mulches at two locations in southwest Germany during 2014 and 2015. The influence of three different tillage systems on weed control efficacy, soybean plant density, and crop yield was determined. In the no-till system (NT), two different cover crops, (rye and barley), were treated by a roller-crimper before soybean sowing. For the reduced tillage system (RT), shallow soil cultivation (7.5 cm depth) using a cultivator after cover crop harvest was performed. The third system was conventional tillage (CT), which used a plow (25 cm depth) without any previous cover crop treatment. Finally, a CT system without weed control was used as a control treatment (C). Weed densities in the field experiments ranged from 1 to 164 plants m⁻² with Chenopodium album (L.), Echinochloa crus-galli (L.) P. Beauv., and Sonchus arvensis (L.) as the predominant weed species. No difference in weed suppression was found between the two cover crops. The highest cover crop soil coverage was measured in the NT treatment. The greatest weed density (164 plants m⁻²) was measured in the untreated control. CT, RT and NT reduced weed density up to 71%, 85%, and 61%, respectively, to C, across both locations and years. Soybean plant density was reduced in NT (−36%) and CT (−18%) based on aimed sown plant density. Highest crop yields up to 2.4 t ha⁻¹ were observed in RT, while NT resulted in lower yields (1.1 t ha⁻¹). Our work reveals the importance of cover crops for weed suppression in soybean cropping systems without herbicide application.

Herbicides may damage soybean in conventional production systems. Chlorophyll fluorescence imaging technology has been applied to identify herbicide stress in weed species a few days after application. In this study, greenhouse experiments followed by field experiments at five sites were conducted to investigate if the chlorophyll fluorescence imaging is capable of identifying herbicide stress in soybean shortly after application. Measurements were carried out from emergence until the three-to-four-leaf stage of the soybean plants. Results showed that maximal photosystem II (PS II) quantum yield and shoot dry biomass was significantly reduced in soybean by herbicides compared to the untreated control plants. The stress of PS II inhibiting herbicides occurred on the cotyledons of soybean and plants recovered after one week. The stress induced by DOXP synthase-, microtubule assembly-, or cell division-inhibitors was measured from the two-leaf stage until four-leaf stage of soybean. We could demonstrate that the chlorophyll fluorescence imaging technology is capable for detecting herbicide stress in soybean. The system can be applied under both greenhouse and field conditions. This helps farmers to select weed control strategies with less phytotoxicity in soybean and avoid yield losses due to herbicide stress.

Sensor technologies are expedient tools for precision agriculture, aiming for yield protection while reducing operating costs. A portable sensor based on chlorophyll fluorescence imaging was used in greenhouse experiments to investigate the response of sugar beet and soybean cultivars to the application of herbicides. The sensor measured the maximum quantum efficacy yield in photosystem II (PS-II) (F_v/F_m). In sugar beet, the averageF_v/F_mof 9 different cultivars 1 d after treatment of desmedipham plus phenmedipham plus ethofumesate plus lenacil was reduced by 56% compared to the nontreated control. In soybean, the application of metribuzin plus clomazone reducedF_v/F_mby 35% 9 d after application in 7 different cultivars. Sugar beets recovered within few days from herbicide stress while maximum quantum efficacy yield in PS-II of soybean cultivars was reduced up to 28 d. At the end of the experiment, approximately 30 d after treatment, biomass was reduced up to 77% in sugar beet and 92% in soybean. Chlorophyll fluorescence imaging is a useful diagnostic tool to quantify phytotoxicity of herbicides on crop cultivars directly after herbicide application, but does not correlate with biomass reduction.