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Agriculture contributes nearly a quarter of global greenhouse gas (GHG) emissions, which is motivating interest in certain farming practices that have the potential to reduce GHG emissions or sequester carbon in soil. The related GHG emission (including N2O and CH4) and changes in soil carbon stock are defined here as “agricultural carbon outcomes”. Accurate quantification of agricultural carbon outcomes is the basis for achieving emission reductions for agriculture, but existing approaches for measuring carbon outcomes (including direct measurements, emission factors, process-based modeling) fall short of achieving the required accuracy and scalability necessary to support credible, verifiable, and cost-effective measurement and improvement of these carbon outcomes. Here we propose a foundational and scalable framework to quantify field-level carbon outcomes for farmland, which is based on the holistic carbon balance of the agroecosystem: Agroecosystem Carbon Outcomes = Crops (C) × Management (M) × Environment (E). Following a comprehensive review of the scientific challenges associated with existing approaches, as well as their tradeoffs between cost and accuracy, we propose that the most viable path for the quantification of field-level carbon outcomes in agricultural land is through an effective integration of various approaches (e.g. diverse observations, sensor/in-situ data, modeling), defined as the “system- of-systems” solution. Such a “system-of-systems” solution should simultaneously comprise the following components: (1) scalable collection of ground truth data and cross-scale sensing of crop conditions (C), management practices (M), and environment (E) at the local field level; (2) advanced modeling with necessary processes to support the quantification of carbon outcomes; (3) systematic Model-Data Fusion (MDF), i.e. robust and efficient methods to integrate sensing data and models at each local farmland level; (4) high computation efficiency and artificial intelligence (AI) to scale to millions of individual fields with low cost; and (5) robust and multi-tier validation systems and infrastructures to ensure solution fidelity and true scalability, i.e. the ability of a solution to perform robustly with accepted accuracy on all targeted fields. In this regard, we provide here the detailed scientific rationale, current progress, and future R&D priorities to achieve different components of the “system-of-systems” solution, thus accomplishing the Crop×Management×Environment framework to quantify field-level agricultural carbon outcomes.

Cover crops have critical significance for agroecosystem sustainability and have been long promoted in the U.S. Midwest. Knowledge of the variations of cover cropping and the impacts of government policies remains very limited. We developed an accurate and cost-effective approach utilizing multi-source satellite fusion data, environmental variables, and machine learning to quantify cover cropping in corn and soybean fields from 2000 to 2021 in the U.S. Midwest. We found that cover crop adoption in most counties has significantly increased in the recent 11 years from 2011 to 2021. The adoption percentage of the year 2021 is 3.3 times that of the year 2011, primarily driven by federal and state conservation programs. Particularly, the year 2021 has rapidly increased 63.6% of planting acreage compared to 2020, however, the percentage is still low (7.2%). Our work highlights the importance of incentives from the public and private sectors on promoting sustainable agricultural practices.

Impacts from the coronavirus pandemic have depressed market returns to corn and soybean farmers in the Midwest, extending pressures that have existed since 2013 and which were made worse by trade disputes with China. Without large ad hoc Federal aid, income on Midwest grain farms would have been quite low and the ongoing cash flow crunch much worse. Farmland prices have not adjusted downward, in part due to continuing ad hoc Federal aid, but also because interest rates have been historically very low. The financial (solvency) position of Midwest grain farms is surprisingly strong because of the strength in land values. However, the financial condition of Midwest row‐crop agriculture could deteriorate markedly if recent and large infusions of ad hoc Federal aid dissipates or if interest rates rise sharply.

The 2014 Farm Bill continued the trend towards more risk management-based support for U.S. farmers. However, it also represents a major departure from previous legislation by introducing multiple program options among which producers had the ability to choose. While allowing producers to have choices creates flexibility, the design of the program required producers to consider potential outcomes for crop prices and production levels in future periods when making their decisions. Experience over the first two years of program implementation suggests that while programs are working as designed, not all producers are fully satisfied with their enrollment decisions. This will lead to proposals for further modification to programs, and to questions about whether program choice should be a component of the next Farm Bill.

The 2014 Farm Bill required farmers and landowners to make a set of one-time, irrevocable decisions lasting for the duration of the farm bill. The decisions included the choice between three program alternatives with uncertain payments. To aid in making those decisions, the farm bill funded two key educational efforts: (a) the development of two online decision tools and (b) additional funding to support land grant institutions and extension systems to educate farmers through more traditional extension mediums, particularly in-person meetings. This paper provides an evaluation of both types of farm bill education through two case studies.

Purpose – The purpose of this paper is to discuss the growth and rising costs association with the Federal Crop Insurance program in the USA, justifications for public support, and recent reforms that have been implemented or proposed to reduce program costs. It also analyzes a specific policy to reduce premium assistance spending. Design/methodology/approach – Data from the Risk Management Agency are used to illustrate historical trends in crop insurance program costs and to analyze the impacts of imposing a per acre cap on premium assistance. Findings – Imposing a per acre cap on premium assistance could achieve significant savings. A $20 per acre cap is estimated to reduce premium subsidy expenditures by more than 40 percent. However, the impact of such a policy would be most severe on crops currently receiving the largest subsidies per acre, which happen to be some of the largest program crops in the USA. Originality/value – This paper adds to the literature analyzing potential reform in crop insurance industry. The subsidy cap considered has been proposed and considered by policy makers, and this paper provides estimates for its potential savings.