New technologies related to the identification of bacterial communities in fresh forage and silage may give valuable detailed information on the best practices to produce animal feeds. The objective was to evaluate how management conditions during silage making manipulate the profile of bacterial communities and fermentation quality of grass silages. Silages were prepared from mixed timothy and meadow fescue grass using two compaction levels. As an additional treatment the grass was contaminated with soil and feces prior to tight compaction. Four additive treatments with different modes of action were applied: control without additive, formic acid-based additive, homofermentative lactic acid bacteria and salt-based additive. After 93 days the silos were opened, samples were taken and routinely analyzed. DNA extraction was carried out and PCR amplification of the bacterial 16S rRNA gene V4 region was performed using universal primers. The silage pH was higher for loose than tight compaction and higher for non-contaminated than for contaminated silages. Great shift was observed in bacterial profiles from fresh material towards silage. Lactobacillus genus was barely found on the relative abundance of fresh grass but became predominant in the final silage along with Sphingomonas genus. Use of additives improved fermentation quality and modified the bacterial profiles of grass ensiled under different management conditions.

The need for high-quality communications networks is urgent in data-based farming. A particular challenge is how to achieve reliable, cost-efficient, secure, and broadband last-mile data transfer to enable agricultural machine control. The trialed ad hoc private communications networks built and interconnected with different alternative wireless technologies, including 4G, 5G, satellite and tactical networks, provide interesting practical solutions for connectivity. A remotely controlled tractor is exemplified as a use case of machine control in the demonstrated private communication network. This paper describes the results of a comparative technology analysis and a field trial in a realistic environment. The study includes the practical implementation of video monitoring and the optimization of the control channel for remote-controlled unmanned agricultural tractors. The findings from this study verify and consolidate the requirements for network technologies and for cybersecurity enablers. They highlight insights into the suitability of different wireless technologies for smart farming and tractor scenarios and identify potential paths for future research.