Abstract Cereal rye (CR; Secale cereale L.) is widely used as a winter cover crop in soybean ( Glycine max L.) production systems to reduce soil erosion and capture residual soil nitrogen (N). However, soybean responses to CR residue depend on biomass quantity and residue quality, both of which are strongly influenced by CR seeding rate. To evaluate the effects of CR seeding rate on biomass production, residue carbon (C) and N dynamics, and subsequent soybean performance, a two-year field experiment was conducted during the 2022–2023 and 2023–2024 growing seasons in southern Illinois. This study was arranged in a randomized complete block design with four replications and included a no-cover crop control and four CR seeding rates (14, 28, 42, and 56 kg ha −1 ). CR biomass increased linearly with increasing seeding rate across years, whereas C accumulation showed a significant year × seeding rate interaction, increasing linearly with seeding rate in 2024 but not in 2023, while tissue N concentration declined with increasing seeding rate across years and residue C:N ratio increased in both years, with a stronger response in 2024. Soybean biological yield was not affected by CR seeding rate; however, soybean grain yield remained stable at low to moderate seeding rates (14–42 kg ha −1 ) and declined at the highest rate (56 kg ha −1 ). Yield reductions at high seeding rates were driven primarily by decreases in seed number and harvest index. Principal component analysis showed that seeding rate was the dominant driver of CR biomass and residue quality, whereas environmental conditions explained most year-to-year variation. Economic analysis indicated that net returns were maximized at moderate seeding rates, particularly at the minimum financial incentive-eligible rate of 34 kg ha −1 . These results suggest that moderate CR seeding rates can optimize residue benefits while maintaining soybean yield and profitability.
Crop diversification plays a central role in agricultural sustainability transitions, which require not only ecological innovation but also economic viability at the farm level. Despite robust evidence of ecological benefits, the socioeconomic implications of diversification remain insufficiently examined. This study analyzes the economic performance of crop diversification and community-supported agriculture (CSA) schemes in small-scale horticultural systems in Northern Patagonia, Argentina. Drawing on detailed production and marketing data from three farms and using a participatory action research (PAR) approach, we simulated farm performance with the Profit Impact Simulator for Horticultural Farms, a framework that calculates profitability based on the temporal dynamics of cash flow. We modeled three crop portfolio scenarios-a highly diversified system (BES1, 35 crops), a moderately diversified system (BES2, 6 crops), and a low-diversity system (BES3, 3 crops)-and identified a systematic diversification gradient: profit rates decline from 409% (BES1) to 347% (BES2) to 239% (BES3). This gradient is driven not by differences in end-of-cycle revenues but by the temporal structure of cash flows each portfolio generates: in highly diversified systems, short-cycle crops generate early income that offsets the financing needs of longer-cycle crops, reducing committed capital and increasing capital efficiency. CSA participation further improved financial viability, reducing committed capital by 24% and raising the profit rate from 409% to 519%. These findings suggest that diversification and consumer-based financing are complementary strategies that enhance liquidity stability and reduce dependence on external credit, with important implications for smallholder economic sustainability and sustainable food system transitions.
Agricultural land in many countries is increasingly leased. This shift presents a unique set of challenges for decision-makers in the context of the European green transition. The objective of the present paper is to explore how agricultural land management and production differ based on whether land is owner-operated or leased and to understand the impacts of these dynamics on food system resilience and sustainability. Harnessing the high level of detailed field data for 2.5 million hectares and accurate land ownership records in Denmark, the present paper explores field-scale agricultural land use differences by tenure across broad categories (e.g., agroforestry, permanent grasses), and within crop rotations (based on distinct crop categories over 7 years, e.g., wheat, legumes, intercropping). Across broad categories, a higher proportion of owned land was utilized for forestry, agroforestry, and energy forestry, whereas a higher proportion of leased land was managed under environmental policies (low-input managed fields such as set aside buffer zones, flower strips, and mini wetlands). Most agricultural land is managed in rotation (approximately 70%). The average length of crop rotations was similar between owned and leased land. The crop categories included in rotation also varied little for legumes and intercrops, with marginally more maize, vegetables, and rye grown on leased land and marginally more environmental, mixed cereals and barley on owned land. Future research exploring how ownership, policy initiatives, and decision-making interact with farm-scale variables, detailed soil maps, and agricultural and natural land use decisions at various landscape scales could further the European transition toward sustainable and resilient agricultural land use and food systems.
Abstract The use of digital tools could optimise farm management by facilitating data collection and processing. The literature provides an overall view of what digital tools represent in ruminant livestock farming and highlights the importance of studying digital toolkits. In sheep farming systems, the diversity of production systems could lead farmers to combine digital tools to meet their specific needs. This article examines how farmers use digital tools to understand how sheep farmers build their digital toolkits. The present study contributes to this objective by providing feedback on the tools used by sheep farmers and the integration of these tools into farms. The study was carried out in four French regions where sheep production is well established. A total of 75 surveys on farms were conducted, and the data were analysed using descriptive statistics. A variety of digital tools were recorded, with each farm using, on average, three tools. The 22 tools identified were grouped into five categories. Digital management tools were the most widely used (85% of farmers used at least one tool in this category), while automation tools were the least used category. The diversity of tools observed may be due to the specific characteristics of each farm and the way farmers perceive the digital tools they use. An analysis of farmers’ digital toolkits, defined as all of the tools a farmer owns, highlights the absence of a standard configuration. Each farmer builds a digital toolkit tailored to their operating conditions and objectives. Furthermore, two levels of digital tool use emerged: digital tools integrated into the routine management of farms, which are used more frequently, and digital tools used with greater variability, reflecting targeted or periodic use. Future research into the data used by farmers could provide a better understanding of how they use digital tools to manage their flocks and contribute to the development of tools that align with their practices and needs. This would involve identifying the data used by farmers, their role in the decision-making process, and any changes (or lack thereof) in animal management and farmers’ work.
