Elements of Social Sustainability among Austrian Hay Milk Farmers: Between Satisfaction and Stress

Zearalenone and Its Emerging Metabolites Promptly Affect the Rumen Microbiota in Holstein Cows Fed a Forage-Rich Diet

The study investigated the short-term effects of a single oral bolus of zearalenone (ZEN) on the rumen microbiota and fermentation patterns in four rumen-cannulated Holstein cows fed a forage diet with daily 2 kg/cow concentrate. During the baseline day, cows received uncontaminated concentrate, followed by ZEN-contaminated concentrate on the second day, and again the uncontaminated concentrate on day three. Free rumen liquid (FRL) and particle-associated rumen liquid (PARL) were collected at different hours post-feeding on all days to analyze the prokaryotic community composition, absolute abundances of bacteria, archaea, protozoa, and anaerobic fungi, as well as short-chain fatty acid (SCFA) profiles. The ZEN reduced the microbial diversity in FRL but not in the PARL fraction. The abundance of protozoa was higher after ZEN exposure in PARL, which may be related to their strong biodegradation capacity that, therefore, promoted protozoal growth. In contrast, α-zearalenol might compromise anaerobic fungi as indicated by reduced abundances in FRL and fairly negative correlations in both fractions. Total SCFA significantly increased in both fractions after ZEN exposure, while the SCFA profile only changed marginally. Concluding, a single ZEN challenge caused changes in the rumen ecosystem soon after intake, including ruminal eukaryotes, that should be the subject of future studies.

Partnership 4.0: smallholder farmer partnership solutions

The current pseudo-partnership pattern causes the farmers' income to be low from the results of their farming activities, so a partnership pattern is needed that is able to create a mutual partnership. The research which was conducted in Cikarawang Village, Bogor Regency, West Java Province - Indonesia aims; (1) recognize the existing condition of farmers and the use of agricultural land; (2) knowing the distribution of agricultural commodities; (3) identify existing partnership patterns; and (4) provide solutions for partnership patterns that benefit farmers. By using mixed-methods combined with the Drone Participatory Mapping (DPM) approach to produce Data Desa Presisi (DDP), this study succeeded in identifying three statuses of farmers, namely: cultivators, owners and cultivators of their own land, and owners who work on their own land at the same time working on other people's land, with an average access to land management of 3,437.32 m². The small access of each farmer in land management is further exacerbated by the variety of agricultural commodities that are cultivated by farmers. There are at least 19 types of agricultural commodities that are cultivated, but do not meet the economic scale that is able to improve the welfare of farmers. This condition opens up opportunities for the partnership pattern between farmers and middlemen to continue to survive which is actually detrimental to farmers. Partnership 4.0 innovation is present to replace the old partnership pattern by focusing on the basis of technology and information that is fully accessible to farmers to jointly control agricultural activities (upstream-downstream). Partnership 4.0 places farmers and offtakers on an equal footing, so that smallholders can benefit and help achieve the welfare of smallholders.

Sociotechnological Sustainability in Pasture Management: Labor Input and Optimization Potential of Smart Tools to Measure Herbage Mass and Quality

Investing labor time in herbage measurements is important for precision pasture management. In this study, the labor input of three smart herbage measurement tools—multispectral imagery linked to an unmanned aerial vehicle (UAV), a semi-automated rising plate meter (RPM), and near-infrared reflectance spectroscopy (NIRS) of cut herbage samples—and of direct observation was modeled based on the REFA work element method. Three to five users were observed during work execution to identify best-practice workflows. Time measurements were conducted using video footage. The resulting standard times of work elements were used to model labor input for herbage measurements in different farm sizes (i.e., milking platforms of 6–100 ha) and subdivisions of a farm’s milking platform (i.e., 4–45 paddocks). Labor time requirement differed between the smart farming tools (0.7–5.9 h) depending on the farm size and milking platform scenario. The labor time requirement increased for all tools with an increase in farm size and was lowest for the RPM. For the UAV tool, it did not increase noticeably when the division of the milking platform changed. Nevertheless, the potential to save time was identified for the UAV and the NIRS. Therefore, the automation of certain steps in the workflows would contribute to sociotechnological sustainable pasture management.

Models Underlying the Success Development of Family Farms in Romania

A family farm is an important part of the countryside, both economically and especially socially. In recent years, legislative measures have encouraged the development of large farms, ensuring food security while neglecting family farms, which are characterised by a lack of organisation, the absence of proper classification and the absence of measures to encourage their development and protection. In order to identify the premises underlying the development of family farms, and to create a development model for those family farms in a poor economic situation, the BMC method and SWOT analysis of seven family farms considered successful models were used. The development of these types of farms could provide a solution to a major problem facing the Romanian countryside: the depopulation of rural areas. The results of the study show that the development of these types of farms is based on joining an associative form (cooperatives) and/or making investments in the processing/storage line of agricultural products.