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The Agricultural Act of 2014 replaced dairy product price supports and countercyclical income support payments with the Margin Protection Program for Dairy Producers. Using farm-level data, producer decisions and aggregate policy costs under a variety of risk environments and policy design alternatives are simulated. Fixed premium rates may result in budget outlays that are substantially higher than for equivalent variable-rate insurance subsidized at levels observed in revenue-based crop insurance policies. Due to the absence of adjusted gross income or production eligibility constraints, a significant portion of benefits may accrue to a small share of large dairy farms.

With the 1996 Farm Act, the United States introduced payments that were designed to be \"decoupled.\" Labor allocation choices are likely to be affected by receipt of payments, and income from off-farm jobs has been the major source of income for most farm households for sometime. This article examines whether the 1996 change has affected the off-farm labor participation of farm households. We conclude that the observed increase in off-farm participation of farm operators who received payments was not the result of the 1996 policy change. Government payments, whether coupled or decoupled, have a negative effect on off-farm labor participation.

The price fluctuation in agricultural markets is an obstacle to poverty reduction for small-scale farmers in developing countries. We build a microfoundation to study how farmers with heterogeneous production costs, under price fluctuations, make crop-planting decisions over time to maximize their individual welfare. We consider both strategic farmers, who rationally anticipate the near-future price as a basis for making planting decisions, and naïve farmers, who shortsightedly react to the most recent crop price. The latter behavior may cause recurring overproduction or underproduction, which leads to price fluctuations. We find it important to cultivate a sufficient number of strategic farmers because their self-interested behavior alone, made possible by sufficient market information, can reduce price volatility and improve total social welfare. In the absence of strategic farmers, a well-designed preseason buyout contract, offered by a social entrepreneur or a for-profit firm to a fraction of contract farmers, brings benefit to farmers as well as to the firm itself. More strikingly, the contract not only equalizes the individual welfare in the long run among farmers of the same production cost, but it also reduces individual welfare disparity over time among farmers with heterogeneous costs regardless of whether they are contract farmers or not. On the other hand, a nonsocially optimal buyout contract may reflect a social entrepreneur’s over-subsidy tendency or a for-profit firm’s speculative incentive to mitigate but not eliminate the market price fluctuation, both preventing farmers from achieving the most welfare. This paper was accepted by Vishal Gaur, operations management.

PurposePrecision technologies have been available at the farm level for decades. Some technologies have been readily adopted, while the adoption of other technologies has been slower. The purpose of this study is to examine the factors influencing farmers' time-to-adoption decisions as duration between year of commercialization of precision agriculture (PA) technologies and year of adoption, at the farm level.Design/methodology/approachTime-to-adoption, which is the difference in years between technologies becoming commercially available and the year of adoption was determined using non-parametric duration analysis, and the impact of specific farm/farmer characteristics on time-to-adoption were estimated using a semi-parametric Cox proportional-hazard (CPH) model, based on a panel dataset of 316 Kansas farms from 2002 to 2018.FindingsThe findings indicate that, time-to-adoption for embodied-knowledge technologies such as automated guidance and section control were statistically shorter than for information-intensive technologies such as yield monitors, precision soil sampling and variable rate fertility. Duration was indirectly (directly) proportional to commercialization date of embodied-knowledge (information-intensive) technology. More so, time-to-adoption statistically differed among technologies within these two broad categories. Time-to-adoption varies across farm location and between both types of technologies. Millennial farmers are more likely to adopt both types of technologies sooner compared to baby boomers. Net farm income, percentage changes in debt-to-asset ratio, corn to total crop acres and machinery investment had no significant impact on the time-to-adoption for both information-intensive and embodied-knowledge technologies. On the other hand, while variations exist, time-to-adoption of PA technologies is mainly driven by location of farm, generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance.Originality/valueThis study investigates how the financial position of farms, amongst other important factors might influence time-to-adoption of PA technologies. Results are useful to extension personnel and retailers for planning marketing or farm outreach programs taking into consideration that, time-to-adoption differs across regions and by specific characteristics, key amongst them: generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance.

In the present era of agricultural digitalization, documenting on-farm operations is critical. These records contextualize other layers of data and underpin economic analysis and informed decision-making. On-farm recordkeeping is rooted in an ancient tradition and has evolved from pen and paper to digital means integrating diverse tools and methods. These tools vary widely in mode of data recording and this presents challenges in achieving complete, accurate and interoperable data. Assessing this diversity of existing recordkeeping systems is a key step toward the improvement in recordkeeping systems that enhance data quality and interoperability. Despite the importance, as of present, comprehensive studies addressing this challenge are lacking. A systematic review of existing on-farm recordkeeping systems was carried out to address their advantages and weaknesses and to analyze their features and traits, focusing on interoperability and adherence to efficient and comprehensive on-farm recordkeeping. Paper-based recordkeeping, a longstanding and reliable method, is gradually being replaced by digital platforms. Many universities and agencies have released farm management spreadsheets and interactive database forms representing the initial step toward intuitive recordkeeping. Furthermore, farm management software, web apps, and user-friendly smartphone apps are increasingly crucial for handling agricultural big data. Notably, among the surveyed software packages and apps, most of them are not free and only a few support data interoperability. The survey also indicates a scope for further development in open-source tools with automation in recordkeeping. Adopting digital on-farm recordkeeping tools can positively impact both on and off the farm, fostering data interoperability, controlled yet flexible data access, completeness, and appropriate accuracy.

In the mid-1990s, fairtrade-organic registration data showed that only 9 % of Oaxaca, Mexico’s organic coffee ‘farm operators’ were women; by 2013 the female farmer rate had increased to 42 %. Our research investigates the impact of this significant increase in women’s coffee association participation among 210 members of two coffee producer associations in Oaxaca, Mexico. We find that female coffee organization members report high levels of household decision-making power and they are more likely than their male counterparts to report control over their coffee income. These significant advances in women’s agency within the household are offset by the fact that the women experience significant time poverty as they engage in coffee production while bearing a disproportionate share of domestic labor obligations. The women coffee producers view organizational labor as a third burden on their time, after their reproductive and productive labor. The time poverty they experience limits their ability to fully participate in coffee organizational governance and consequently there are few women leaders at all levels of the coffee producer businesses. This is problematic because it limits women’s ability to fully benefit from organizational membership: when women fully participate in governance they gain valuable business and leadership skills and producer associations with active female members may also be more likely to develop and maintain programs and policies that enhance gender equity. Our findings indicate that targeted agricultural development programs to improve gender equity among agricultural smallholders should involve creative ways to ease women’s labor burdens and reduce their time poverty in order to facilitate full organizational participation. The research findings fill a gap in existing studies of agricultural global value chains (GVCs) by demonstrating how the certified coffee GVC depends on women’s under and un-paid labor not only within the household but also within producer organizations.

The production of high-quality and safe milk is closely associated with the udder health of dairy cows. While there are many mastitis diagnostic tests/methods available, choosing the most appropriate diagnostic test for a sustainable udder health control program could be a challenge. This study was aimed at selecting tests for the screening of subclinical mastitis on small- and large-scale dairy farms in Türkiye, using multi-criteria decision-making methods. An integrated approach employing the analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) together was used to select subclinical mastitis screening tests for on-farm use. While the AHP determines the weights of the evaluation criteria, the TOPSIS provides a final ranking. Nine different subclinical mastitis screening (SCM) methods (DeLaval somatic cell counter, PortaSCC test, California mastitis test (CMT), rapid culture, portable/hand-held electrical conductivity meter, infrared thermography, leukocyte esterase strip test, milk pH, UdderCheck test) were analyzed on the basis of five selection criteria (the market availability of the test, the diagnostic accuracy of the test, the cost of the test, the cow-side use of the test, and the practicality of the test). The selection criteria were determined based on literature review and stakeholder input. The weighting of the criteria with the AHP was based on the pairwise comparison of the criteria by stakeholders. The criteria were weighted from 1 to 9 according to their relative importance as follows: “1: equally important,” “3: moderately important,” “5: strongly important,” “7: very strongly important,” “9: extremely important,” and “2, 4, 6, 8: intermediate values.” Final ranking of SCM tests with the TOPSIS was based on the stakeholder evaluations of fulfillment of the criteria by the alternatives. The most appropriate screening test for both large- and small-scale dairy farms was determined to be the CMT. The CMT is a very useful, easy to perform, and low-cost tool for detecting subclinical mastitis. Being a major element of udder health control programs, the CMT, if regularly used on dairy farms in Türkiye, would enable the culling of chronically infected animals and the reduction of mastitis-associated economic losses. Furthermore, regular CMTs would contribute to reducing milk SCC and improving milk quality. In conclusion, multi-criteria decision-making methods not only provide a systematic approach that may assist both veterinarians and farmers in deciding on the best choice among the different tests available for the screening of subclinical mastitis but also offer potential benefits to policymakers, researchers, and other industry stakeholders.

Organic, grassfed (OGF) dairy, which requires higher pasture and forage dry matter intake compared with standard organic dairy practices, is unique both in its management needs and in production challenges. The OGF dairy sector is rapidly growing, with the expansion of this industry outpacing other dairy sectors. There is a lack of research outlining OGF dairy production practices, producer-identified research needs or social factors that affect OGF systems. The objectives of this study were to, with a group of OGF dairy producers, (1) assess information regarding current production practices and producer knowledge, and (2) identify agronomic and social factors that may influence milk production on OGF farms across the United States. A mail survey, focused on demographics, forage and animal management, knowledge, and satisfaction of their farm, was developed and distributed in 2019, with 167 responses (47% response rate). The majority of producers indicated they belonged to the plain, or Amish-Mennonite, community. Milk production was greater on farms that had Holstein cattle, as compared to farms with Jerseys and mixed breeds, and employed intensive pasture rotation. Furthermore, most producers reported the use of supplements such as molasses and kelp meal, which can improve milk production, but also increase feed costs. Producers who indicated that they were at least satisfied with their milk production also reported high levels of knowledge of grazing management and cow reproductive performance. Comparison of response data from plain/non-plain respondents revealed that those that did not identify as plain were more likely to utilize certain government programs, had different priorities and utilized technology more frequently. Based on these results, more research exploring financial and production benchmarks, effective communication strategies to reach OGF producers and methods to improve cattle production through improved forage quality is needed.

Rapid and accurate detection and identification of bovine mastitis-causing pathogens are crucial for treatment decisions and dairy farm management. In this work, we developed and validated a diagnostic system for point-of-care applications that may properly detect and identify , non- staphylococci, and other species, which are all considered as relevant pathogenic species for bovine mastitis in Colombia. The diagnostic system is supported by a mobile application, +tiApp, that facilitates result interpretation, digital record keeping, and provides evidence-based treatment recommendations to assist on-farm decisions. A total of 520 milk samples from cows with somatic cell count (SCC) < 200,000 cells/ml, or < 100,000 cells/ml for primiparous cows, which were deemed free of intramammary infection, and subclinical mastitis cows (>200,000 cells/ml, or >100,000 cells/ml for primiparous cows) were analyzed using the +tiDx system and a composite reference standard (CRS), which included standard microbiological culture (SMC) and SCC as testing conditions, to assess diagnostic performance for detection and identification of Gram-positive pathogens. We evaluated our diagnostic system by REASSURED criteria against the SMC. The +tiDx diagnostic system demonstrated adequate overall performance relative to CRS for the detection of mastitis caused by Gram-positive bacteria, achieving a sensitivity of 0.98 and a specificity of 0.94 relative to CRS. Regarding its performance relative to CRS against specific pathogens, the system yielded varied yet noteworthy results depending on the evaluated species: a sensitivity of 0.65 and specificity of 0.94 for ; 0.82 sensitivity and 0.93 specificity for ; 0.36 sensitivity and 0.98 specificity for non- staphylococci; and values of 0.98 sensitivity and 0.92 specificity for other species. Cohen's kappa coefficient was 0.92, indicating high concordance between the in-laboratory diagnostic system and CRS, while concordance between the on-field diagnostic system and CRS was 0.74. +tiDx is a practical and reliable on-farm diagnostic tool for Gram-positive intramammary infections, combining timeliness and ease of use with appropriate user training to ensure accurate result interpretation and support effective mastitis control.

One of the key elements of precision agriculture is the farm management information system (FMIS) that is responsible for data management, analytics and subsequent decision support. Various FMISs have been developed to support the management of farm businesses. A key artefact in the development of FMISs is the software architecture that defines the gross level structure of the system. The software architecture is important for understanding the system, analysing the design decisions and guiding the further development of the system based on the architecture. To assist in the design of the FMIS architecture, several reference architectures have been provided in the literature. Unfortunately, in practice, it is less trivial to derive the application architecture from these reference architectures. Two underlying reasons for this were identified. First of all, it appears that the proposed reference architectures do not specifically focus on FMIS but have a rather broad scope of the agricultural domain in general. Secondly, the proposed reference architectures do not seem to have followed the proper architecture documentation guidelines as defined in the software architecture community, lack precision, and thus impeding the design of the required application architectures. Presented in this article is a novel reference architecture that is dedicated to the specific FMIS domain, and which is documented using the software architecture documentation guidelines. In addition, the systematic approach for deriving application architectures from the proposed reference architecture is provided. To illustrate the approach, the results of multi-case study research are shown in which the presented reference architecture is used for deriving different FMIS application architectures.