Economic analysis of high-oleic soybeans in dairy rations.

We evaluate the potential economic impact of using high-oleic soybeans (HOS) in dairy rations based on a synthesis of results from 5 prior feeding trials. Milk income less feed costs (MILFC) per cow per day is calculated based on assumed increases in milkfat production and increased cost of rations including HOS. The effects of changes in MILFC are evaluated for herds with different numbers of milking cows, and the total volume of HOS required to support different proportions of US dairy cows is calculated. A dynamic supply-chain model assesses the potential market impacts of increases in butterfat supply. The increase in milkfat from the substitution of 5% of ration dry matter with whole HOS (1.4 kg/cow per day) has the potential to increase MILFC by up to $0.27/cow per day or increase the average value of milk by $0.29/45.4 kg for a cow producing 41 kg/d. Changes in MILFC are highly correlated with the price of butter but were positive for butter prices observed from January 2014 to September 2020. The effects of HOS on MILFC suggest the potential for increases in farm profitability of $33,000/yr for a dairy feeding 500 milking cows. Scaled-up use of HOS by US dairy farmers would increase butterfat supplies and lower the butterfat price to a small extent, but these aggregated effects do not offset the positive effects of MILFC at the farm level.

Analysing the potential impacts of three interventions on fruit and vegetable consumption in urban Kenya using participatory systems modelling.

OBJECTIVE: This study uses participatory modelling with stakeholders to assess the potential impacts of three interventions intended to increase fruit and vegetable (F&V) consumption in urban Kenya. DESIGN: A participatory process using Group Model Building (GMB) developed a conceptual model of the determinants of vegetable consumption. A subsequent quantitative System Dynamics model using data from primary and secondary sources simulated vegetable consumption from 2020 to 2024 under three proposed interventions suggested by stakeholders: increasing consumer awareness, reducing post-harvest losses and increasing farm yields. Model analyses assumed mean parameter values and assessed uncertainty using 200 simulations with randomised parameter values. SETTING: The research was implemented in Nairobi, Kenya with simulation analyses of mean per capita consumption in this location. PARTICIPANTS: Workshops convened diverse F&V value chain stakeholders (farmers, government officials, NGO staff and technical experts) to develop the conceptual model, data inputs and intervention scenarios. RESULTS: Increasing consumer awareness was simulated to increase vegetable consumption by relatively modest amounts by 2024 (5 g/person/d from a base of 131 g/person/d) under mean assumed value of value chain response parameters. Reducing perishability was simulated to reduce consumption due to the higher costs required to reduce losses. Increasing farm yields was simulated to have the largest impact on consumption at assumed parameter values (about 40 g/person/d) but would have a negative impact on farm profits, which could undermine efforts to implement this intervention. CONCLUSIONS: The combination of GMB and simulation modelling informed intervention priorities for an important public health nutrition issue.

Multiple-year farm-level assessments of trade-offs between GHG emissions and income: case examples of two farming systems in Northern Nigeria.

This study quantifies the trade-offs between welfare (measured by income) and greenhouse gas (GHG) emissions in two farming systems of Northern Nigeria using data for 5 years from 2015 to 2019. The analyses employ a farm-level optimization model that maximizes the value of production less purchased input costs for agricultural activities including the production of trees, sorghum, groundnut or soybeans, and multiple livestock species. We compare income and GHG emissions without constraints to scenarios requiring reductions in emissions of either 10% or the maximum reduction feasible while maintaining minimum household consumption levels. For both locations and all years, we find that reductions in GHG emissions would lower household incomes and require substantive modifications to production patterns and input use. However, the extents to which reductions are possible and the patterns of income-GHG trade-offs vary, indicating that such effects are site-specific and time-variable. The variable nature of these trade-offs suggests challenges for the design of any program that would seek to compensate farmers for reductions in their GHG emissions.

High-yield dairy cattle breeds improve farmer incomes, curtail greenhouse gas emissions and reduce dairy import dependency in Tanzania.

Tanzania's dairy sector is poorly developed, creating reliance on imports for processed, value-added dairy products and threatening food security, particularly when supply chains are disrupted due to market volatility or armed conflicts. The Tanzanian Dairy Development Roadmap is a domestic development initiative that aims to achieve dairy self-sufficiency by 2030. Here, we model different outcomes of the roadmap, finding that adoption of high-yield cattle breeds is essential for reducing dairy import dependency. Avoided land use change resulting from fewer, higher yielding dairy cattle would lead to lower greenhouse gas emissions. Dairy producers' average incomes could increase despite capital expenditure and land allocation required for the adoption of high-yield breeds. Our findings demonstrate the importance of bottom-up development policies for sustainable food system transformations, which also support food sovereignty, increase incomes for smallholder farmers and contribute towards Tanzania's commitments to reduce greenhouse gas emissions.

Food value chain interventions and nutritional outcomes: a review of evidence and recommendations for future assessments.

Food value chains (FVC) have become an important framework for the assessment of interventions to improve nutritional outcomes during the past decade, and recent literature indicates considerable agreement about FVC importance and potential impact pathways. Despite the usefulness of the FVC framework, the majority of studies reviewed provide only conceptual models or descriptive analyses of linkages with nutrition, limiting their usefulness for quantitative assessment of intervention impacts. Fewer than five studies of 113 reviewed measure the impacts of FVC interventions on nutritional outcomes or provide study protocols for that purpose. In addition to randomized controlled trials, comparative analysis and systems modeling methods will provide relevant evidence about the effectiveness of FVCs for improvement of nutrition.

Conceptual frameworks linking agriculture and food security.

Many conceptual frameworks have been developed to facilitate understanding and analysis of the linkages between agriculture and food security. Despite having usefully guided analysis and investment, these frameworks exhibit wide diversity in perspectives, assumptions and application. This Review Article examines this diversity, providing an approach to assess frameworks and suggesting improvements in the way they are specified and applied. Using criteria-based systems modelling conventions, we evaluate 36 frameworks. We find that many frameworks are developed for the purpose of illustration rather than analysis and do not clearly indicate causal relationships, tending to ignore the dynamic (stability) dimensions of agriculture and food security and lacking clear intervention points for improving food security through agriculture. By applying system modelling conventions to a widely used framework, we illustrate how such conventions can enhance the usefulness of a framework for overall illustration purposes, delineate hypotheses on agriculture-food security links and examine potential impacts of interventions.

ASN-ASAS SYMPOSIUM: FUTURE OF DATA ANALYTICS IN NUTRITION: Modeling complex problems with system dynamics: applications in animal agriculture1.

Many problematic outcomes in agricultural and food systems have important dynamic dimensions and arise due to underlying system structure. Thus, understanding the linkages between system structure and dynamic behavior often is important for the design and implementation of interventions to achieve sustained improvements. System dynamics (SD) modeling represents system structure using stock-flow-feedback structures expressed as systems of differential equations solved by numerical integration methods. System dynamics methods also encompass a broader methodological approach that emphasizes model structural development and data inputs to replicate one of a limited number of problematic behavioral modes, anticipates dynamic complexity, and focuses on feedback processes arising from endogenous system elements. This paper highlights the process of SD modeling using 2 examples from animal agriculture at different scales. A dynamic version of the Cornell Net Carbohydrate and Protein System (CNCPS) that represents outcomes for an individual dairy cow is formulated as an SD model illustrates the benefits of the SD approach in modeling rumen fill and animal performance. At a very different scale, an SD model of the Brazilian dairy supply chain (farms, processing, and consumers) illustrates the country-level impacts of efforts to improve cow productivity and how impacts differ if productivity improvement occurs on small farms rather than large farms. The paper concludes with recommendations about how to increase awareness and training in SD methods to enhance their appropriate use in research and instruction.

Environmental and Economic Impacts of Localizing Food Systems: The Case of Dairy Supply Chains in the Northeastern United States.

We developed and evaluated an empirical model of the U.S. dairy supply chain with a high degree of spatial and product disaggregation to assess the impacts of increasing localization of the northeast region's fluid milk supply on food miles, supply chain costs, greenhouse gas and criteria pollutant emissions, economic activity, and employment. Evaluation included comparison to regional production values and sensitivity analysis of demand and unit cost assumptions. Our analysis compares a baseline to two localization scenarios based on state boundaries and multiple-state subregions. Localization scenarios increased total distances fluid milk traveled by 7-15%, overall supply chain costs by 1-2%, and emissions of greenhouse gases (CO2 equivalent) criteria pollutants such as oxides of nitrogen and particulate matter smaller than 2.5 µm associated with fluid milk transportation by 7-15% per month. The impacts of localization on employment and economic activity are positive, but changes are small on a percentage basis. Our analyses indicate that the definition used for localization has an impact on outcomes and that efforts to localize food systems may benefit from a more systems-oriented approach.

Economic analysis of alternative nutritional management of dual-purpose cow herds in central coastal Veracruz, Mexico.

Market information was combined with predicted input-output relationships in an economic analysis of alternative nutritional management for dual-purpose member herds of the Genesis farmer organization of central coastal Veracruz, Mexico. Cow productivity outcomes for typical management and alternative feeding scenarios were obtained from structured sets of simulations in a companion study of productivity limitations and potentials using the Cornell Net Carbohydrate and Protein System model (Version 6.0). Partial budgeting methods and sensitivity analysis were used to identify economically viable alternatives based on expected change in milk income over feed cost (change in revenues from milk sales less change in feed costs). Herd owners in coastal Veracruz have large economic incentives, from $584 to $1,131 in predicted net margin, to increase milk sales by up to 74% across a three-lactation cow lifetime by improving diets based on good quality grass and legume forages. This increment is equal to, or exceeds, in value the total yield from at least one additional lactation per cow lifetime. Furthermore, marginal rates of return (change in milk income over feed costs divided by change in variable costs when alternative practices are used) of 3.3 ± 0.8 indicate clear economic incentives to remove fundamental productivity vulnerabilities due to chronic energy deficits and impeded growth of immature cows under typical management. Sensitivity analyses indicate that the economic outcomes are robust for a variety of market conditions.

Limitations and potentials of dual-purpose cow herds in Central Coastal Veracruz, Mexico.

Feed chemical and kinetic composition and animal performance information was used to evaluate productivity limitations and potentials of dual-purpose member herds of the Genesis farmer organization of central coastal Veracruz, Mexico. The Cornell Net Carbohydrate and Protein System model (Version 6.0) was systematically applied to specific groups of cows in structured simulations to establish probable input-output relationships for typical management, and to estimate probable outcomes from alternative management based on forage-based dietary improvements. Key herd vulnerabilities were pinpointed: chronic energy deficits among dry cows of all ages in late gestation and impeded growth for immature cows. Regardless of the forage season of calving, most cows, if not all, incur energy deficits in the final trimester of gestation; thus reducing the pool of tissue energy and constraining milking performance. Under typical management, cows are smaller and underweight for their age, which limits feed intake capacity, milk production and the probability of early postpartum return to ovarian cyclicity. The substitution of good-quality harvested forage for grazing increased predicted yields by about one-third over typical scenarios for underweight cows. When diets from first parturition properly supported growth and tissue repletion, milk production in second and third lactations was predicted to improve about 60%. Judiciously supplemented diets based on good quality grass and legume forages from first calving were predicted to further increase productivity by about 80% across a three-lactation cow lifetime. These dual-purpose herd owners have large incentives to increase sales income by implementing nutritional strategies like those considered in this study.

Climate change impact of biochar cook stoves in western Kenyan farm households: system dynamics model analysis.

Cook stoves that produce biochar as well as heat for cooking could help mitigate indoor air pollution from cooking fires and could enhance local soils, while their potential reductions in carbon (C) emissions and increases in soil C sequestration could offer access to C market financing. We use system dynamics modeling to (i) investigate the climate change impact of prototype and refined biochar-producing pyrolytic cook stoves and improved combustion cook stoves in comparison to conventional cook stoves; (ii) assess the relative sensitivity of the stoves' climate change impacts to key parameters; and (iii) quantify the effects of different climate change impact accounting decisions. Simulated reductions in mean greenhouse gas (GHG) impact from a traditional, 3-stone cook stove baseline are 3.50 tCO(2)e/household/year for the improved combustion stove and 3.69-4.33 tCO(2)e/household/year for the pyrolytic stoves, of which biochar directly accounts for 26-42%. The magnitude of these reductions is about 2-5 times more sensitive to baseline wood fuel use and the fraction of nonrenewable biomass (fNRB) of off-farm wood that is used as fuel than to soil fertility improvement or stability of biochar. Improved cookstoves with higher wood demand are less sensitive to changes in baseline fuel use and rely on biochar for a greater proportion of their reductions.