Innovations through crop switching happen on the diverse margins of US agriculture.

Crop switching, in which farmers grow a crop that is novel to a given field, can help agricultural systems adapt to changing environmental, cultural, and market forces. Yet while regional crop production trends receive significant attention, relatively little is known about the local-scale crop switching that underlies these macrotrends. We characterized local crop-switching patterns across the United States using the US Department of Agriculture (USDA) Cropland Data Layer, an annual time series of high resolution (30 m pixel size) remote-sensed cropland data from 2008 to 2022. We found that at multiple spatial scales, crop switching was most common in sparsely cultivated landscapes and in landscapes with high crop diversity, whereas it was low in homogeneous, highly agricultural areas such as the Midwestern corn belt, suggesting a number of potential social and economic mechanisms influencing farmers' crop choices. Crop-switching rates were high overall, occurring on more than 6% of all US cropland in the average year. Applying a framework that classified crop switches based on their temporal novelty (crop introduction versus discontinuation), spatial novelty (locally divergent versus convergent switching), and categorical novelty (transformative versus incremental switching), we found distinct spatial patterns for these three novelty dimensions, indicating a dynamic and multifaceted set of cropping changes across US farms. Collectively, these results suggest that innovation through crop switching is playing out very differently in various parts of the country, with potentially significant implications for the resilience of agricultural systems to changes in climate and other systemic trends.

Revisions to USDA biotechnology regulations: The SECURE rule.

In keeping with the directive in Executive Order 13874 (Modernizing the Regulatory Framework for Agricultural Biotechnology Products) to adopt regulatory approaches that are proportionate to risk and avoid arbitrary distinctions across like products, the US Department of Agriculture (USDA) revised its biotechnology regulations by promulgating the Sustainable, Ecological, Consistent, Uniform, Responsible, and Efficient (SECURE) rule. Specifically, the SECURE rule 1) establishes exemptions for plants modified by genetic engineering where the modification could otherwise have been made through conventional breeding, 2) uses risk posed by the introduced trait to determine whether an organism is regulated, rather than relying on whether the organism was developed using a plant pest, and 3) provides a mechanism for a rapid initial review to efficiently distinguish plants developed using genetic engineering that do not pose plausible pathways to increased plant pest risk from those that do. As a result of the focused oversight on potentially riskier crops developed using genetic engineering, USDA is expected to improve the efficiency and effectiveness of its oversight program. The reduced regulatory burden is expected to promote innovation by expanding the number and diversity of developers to include smaller businesses and academics and to increase the number and variety of traits being developed through biotechnology.

A new decade and new data at SoyBase, the USDA-ARS soybean genetics and genomics database.

SoyBase, a USDA genetic and genomics database, holds professionally curated soybean genetic and genomic data, which is integrated and made accessible to researchers and breeders. The site holds several reference genome assemblies, as well as genetic maps, thousands of mapped traits, expression and epigenetic data, pedigree information, and extensive variant and genotyping data sets. SoyBase displays include genetic, genomic, and epigenetic maps of the soybean genome. Gene expression data is presented in the genome viewer as heat maps and pictorial and tabular displays in gene report pages. Millions of sequence variants have been added, representing variations across various collections of cultivars. This variant data is explorable using new interactive tools to visualize the distribution of those variants across the genome, between selected accessions. SoyBase holds several reference-quality soybean genome assemblies, accessible via various query tools and browsers, including a new visualization system for exploring the soybean pan-genome. SoyBase also serves as a nexus of announcements pertinent to the greater soybean research community. The database also includes a soybean-specific anatomic and biochemical trait ontology. The database can be accessed at https://soybase.org.

Qualitative crop condition survey reveals spatiotemporal production patterns and allows early yield prediction.

Large-scale continuous crop monitoring systems (CMS) are key to detect and manage agricultural production anomalies. Current CMS exploit meteorological and crop growth models, and satellite imagery, but have underutilized legacy sources of information such as operational crop expert surveys with long and uninterrupted records. We argue that crop expert assessments, despite their subjective and categorical nature, capture the complexities of assessing the "status" of a crop better than any model or remote sensing retrieval. This is because crop rating data naturally encapsulates the broad expert knowledge of many individual surveyors spread throughout the country, constituting a sophisticated network of "people as sensors" that provide consistent and accurate information on crop progress. We analyze data from the US Department of Agriculture (USDA) Crop Progress and Condition (CPC) survey between 1987 and 2019 for four major crops across the US, and show how to transform the original qualitative data into a continuous, probabilistic variable better suited to quantitative analysis. Although the CPC reflects the subjective perception of many surveyors at different locations, the underlying models that describe the reported crop status are statistically robust and maintain similar characteristics across different crops, exhibit long-term stability, and have nation-wide validity. We discuss the origin and interpretation of existing spatial and temporal biases in the survey data. Finally, we propose a quantitative Crop Condition Index based on the CPC survey and demonstrate how this index can be used to monitor crop status and provide earlier and more precise predictions of crop yields than official USDA forecasts released midseason.

Genome-Wide Association Study of Resistance to Pseudomonas syringae in the USDA Collection of Citrullus amarus.

Pseudomonas leaf spot (PLS), caused by Pseudomonas syringae pv. syringae, is an emerging disease of watermelon in the United States with the potential to severely reduce yield under humid conditions. The genetic basis of resistance to this disease is not known and no resistant germplasm is available. Because Citrullus amarus is an important reservoir of resistance genes for the cultivated watermelon, C. lanatus, we screened the United States Department of Agriculture plant introduction collection of C. amarus for resistance to PLS. Accessions (n = 117) were phenotyped for their level of resistance to PLS in two separate tests. Accession means of percent leaf area affected ranged from 1.5 to 99.4%. The broad-sense heritability for the trait was 0.51. Whole-genome resequencing generated 2,126,759 single-nucleotide polymorphisms (SNPs) which were used to perform a genome-wide association study (GWAS) aimed at discovering molecular markers for resistance. Three different models-BLINK, FarmCPU, and MLM-were included in the GWAS analyses. BLINK and FarmCPU, which are multilocus models, found eight SNPs, located on chromosomes Ca01, Ca05, Ca06, Ca08, and Ca10, that were significantly associated with resistance to PLS. Two of these SNPs were found by both BLINK and FarmCPU. The MLM model did not detect any significant associations. BLINK and FarmCPU estimated an explained phenotypic variance of 43.6 and 28.5%, respectively, for SNP S6_19327000 and 25.0 and 26.0%, respectively, for SNP S1_33362258, the two most significant SNPs found. In total, 43 candidate genes with known involvement in disease resistance were discovered within the genomic intervals of seven of the eight peak SNPs. Eleven of the candidate genes that were found have been reported to be involved in resistance to P. syringae in other plant species. Two significant SNPs were within resistance genes previously documented to play important roles of plant resistance specific to P. syringae in other pathosystems. The SNPs identified in this study will be instrumental in finding causal genes involved in PLS resistance in watermelon and developing resistant germplasm through breeding.

Genome-Wide Association Mapping and Genomic Prediction of Fusarium Wilt Race 2 Resistance in the USDA Citrullus amarus Collection.

Fusarium wilt caused by Fusarium oxysporum f. sp. niveum (Fon) race 2 is a serious disease in watermelon and can reduce yields by 80%. Genome-wide association studies (GWAS) are a valuable tool in dissecting the genetic basis of traits. Citrullus amarus accessions (n = 120) from the USDA germplasm collection were genotyped with whole-genome resequencing, resulting in 2,126,759 single nucleotide polymorphic (SNP) markers that were utilized for GWAS. Three models were used for GWAS with the R package GAPIT. Mixed linear model (MLM) analysis did not identify any significant marker associations. FarmCPU identified four quantitative trait nucleotides (QTN) on three different chromosomes (i.e., chromosomes 1, 5, and 9), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) identified one QTN on chromosome 10 as significantly associated with Fon race 2 resistance. FarmCPU identified four QTN that explained 60% of Fon race 2 resistance, and the single QTN from BLINK explained 27%. Relevant candidate genes were found within the linkage disequilibrium (LD) blocks of these significant SNPs, including genes encoding aquaporins, expansins, 2S albumins, and glutathione S-transferases which have been shown to be involved in imparting resistance to Fusarium spp. Genomic predictions (GP) for Fon race 2 resistance using all 2,126,759 SNPs resulted in a mean prediction accuracy of 0.08 with five-fold cross-validation employing genomic best linear unbiased prediction (gBLUP) or ridge-regression best linear unbiased prediction (rrBLUP). Mean prediction accuracy with gBLUP leave-one-out cross-validation was 0.48. Thus, along with identifying genomic regions associated with Fon race 2 resistance among the accessions, this study observed prediction accuracies that were strongly influenced by population size.

Future of biomedical, agricultural, and biological systems research using domesticated animals.

Increased knowledge of reproduction and health of domesticated animals is integral to sustain and improve global competitiveness of U.S. animal agriculture, understand and resolve complex animal and human diseases, and advance fundamental research in sciences that are critical to understanding mechanisms of action and identifying future targets for interventions. Historically, federal and state budgets have dwindled and funding for the United States Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA) competitive grants programs remained relatively stagnant from 1985 through 2010. This shortage in critical financial support for basic and applied research, coupled with the underappreciated knowledge of the utility of non-rodent species for biomedical research, hindered funding opportunities for research involving livestock and limited improvements in both animal agriculture and animal and human health. In 2010, the National Institutes of Health and USDA NIFA established an interagency partnership to promote the use of agriculturally important animal species in basic and translational research relevant to both biomedicine and agriculture. This interagency program supported 61 grants totaling over $107 million with 23 awards to new or early-stage investigators. This article will review the success of the 9-year Dual Purpose effort and highlight opportunities for utilizing domesticated agricultural animals in research.

Modeling Dairy-Free Vegetarian and Vegan USDA Food Patterns for Nonpregnant, Nonlactating Adults.

BACKGROUND: The 2020-2025 Dietary Guidelines for Americans (2020 DGA) recommend 3 dietary patterns for Americans, including a Healthy Vegetarian Dietary Pattern (HVDP). OBJECTIVES: The objective of this study was to assess whether nutritionally adequate dairy-free and vegan adaptations to the HVDP can be modeled with foods already in the DGA. METHODS: Using similar food pattern modeling procedures as the 2020 DGA, the nutrient composition of 2 alternative models-dairy-free and vegan-of the 1800-, 2000-, 2200-, and 2400-kcal/d HVDPs was assessed. The dairy food group was replaced with a dairy alternative group comprised of soy milk and soy yogurt fortified with calcium, vitamin A, and vitamin D. For the vegan model, eggs were replaced with equal proportions of vegetarian protein foods. RESULTS: Dairy-free and vegan models required minimal changes to the HVDP. Cup-equivalents and/or ounce-equivalents of vegetables, fruits, grains, oils, and discretionary calories remained unchanged. Content of total fat, polyunsaturated fat, linoleic acid (18:2n-6), linolenic acid, iron, copper, vitamin D, riboflavin, vitamin B-12, and vitamin K increased in both models by ≥10% (all comparisons relative to the original HVDP). Choline increased ≥25% in the dairy-free models. Protein decreased 11% in both 1800-kcal/d models and 10% in both 2000-kcal/d models. Sodium, cholesterol, zinc, and phosphorus decreased across all energy levels in both models, and selenium decreased in the vegan model. Carbohydrate, fiber, saturated fat, EPA, DHA, calcium, magnesium, potassium, vitamin A, vitamin E, vitamin C, thiamin, folate, and vitamin B-6 changed ≤10%. Both models contained adequate nutrients to meet Dietary Reference Intakes (DRIs) for most age and sex groups for which 1800-, 2000-, 2200-, and 2400-kcal/d diets are appropriate. Zinc was the only nutrient below the DRI for males. CONCLUSIONS: The dairy-free and vegan HVDP models could help adults who do not consume dairy foods and/or other animal products to meet nutrition recommendations.

Strengthening Research that Answers Nutrition Questions of Public Health Importance: Leveraging the Experience of the USDA Nutrition Evidence Systematic Review Team.

The Nutrition Evidence Systematic Review (NESR) team conducts nutrition- and public health-related systematic reviews and is within the USDA's Center for Nutrition Policy and Promotion. NESR has collaborated with scientific experts to conduct systematic reviews on nutrition and public health topics for more than a decade and is uniquely positioned to share recommendations with the research community to strengthen research quality and impact, especially the evidence base that supports public health nutrition guidance, including future editions of the Dietary Guidelines for Americans. Leveraging the expertise of NESR and its systematic review process resulted in the following recommendations for the research community: a) use the strongest study design feasible with sufficient sample size(s); b) enroll study participants who reflect the diversity of the population of interest and report participant characteristics; c) use valid and reliable dietary assessment methods; d) describe the interventions or exposures of interest and use standard definitions to promote consistency; e) use valid and reliable health outcome measures; f) account for variables that may impact the relationship between nutrition-related interventions or exposures and health outcomes; g) carry out studies for a sufficient duration and include repeated measures, as appropriate; and h) report all relevant information to inform accurate interpretation and evaluation of study results. Implementing these recommendations can strengthen nutrition and public health evidence and increase its utility in future public health nutrition systematic reviews. However, implementation will require additional support from the entire research community, including scientific journals and funding agencies.

Genome-wide association mapping identifies common bunt (Tilletia caries) resistance loci in bread wheat (Triticum aestivum) accessions of the USDA National Small Grains Collection.

KEY MESSAGE: Association mapping and phenotypic analysis of a diversity panel of 238 bread wheat accessions highlights differences in resistance against common vs. dwarf bunt and identifies genotypes valuable for bi-parental crosses. Common bunt caused by Tilletia caries and T. laevis was successfully controlled by seed dressings with systemic fungicides for decades, but has become a renewed threat to wheat yield and quality in organic agriculture where such treatments are forbidden. As the most efficient way to address this problem is the use of resistant cultivars, this study aims to broaden the spectrum of resistance sources available for breeders by identifying resistance loci against common bunt in bread wheat accessions of the USDA National Small Grains Collection. We conducted three years of artificially inoculated field trials to assess common bunt infection levels in a diversity panel comprising 238 wheat accessions for which data on resistance against the closely related pathogen Tilletia controversa causing dwarf bunt was already available. Resistance levels against common bunt were higher compared to dwarf bunt with 99 accessions showing [Formula: see text] 1% incidence. Genome-wide association mapping identified six markers significantly associated with common bunt incidence in regions already known to confer resistance on chromosomes 1A and 1B and novel loci on 2B and 7A. Our results show that resistance against common and dwarf bunt is not necessarily controlled by the same loci but we identified twenty accessions with high resistance against both diseases. These represent valuable new resources for research and breeding programs since several bunt races have already been reported to overcome known resistance genes.

The introduced strain Mesorhizobium ciceri USDA 3378 is more competitive than an indigenous strain in nodulation of chickpea in newly introduced areas of China.

The present study aimed to compare the competitive advantage of two chickpea nodulating rhizobia strains (an indigenous strain Mesorhizobium muleiense CCBAU 83963T and an introduced strain Mesorhizobium ciceri USDA 3378) in different soils originated from new chickpea cultivation areas of China. The results showed that USDA 3378 had a significant competitive advantage in nodulation, with nodulation occupation rates ranging from 84·6% to 100% in all the sampled soils. According to the efficiency of symbiosis under single inoculation, chickpea plants inoculated with USDA 3378 showed better symbiotic performance based on the plant dry weight, leaf chlorophyll content and nodule numbers. The chickpea plants inoculated with USDA 3378 formed nodules about 2 days earlier than those inoculated with CCBAU 83963T . The higher growth in media and the stronger adsorption on chickpea roots of USDA 3378 when mixed with CCBAU 83963T may explain why USDA 3378 shows a competitive advantage. The results from this study will contribute towards the development of effective chickpea rhizobial inoculants for soil conditioning and more environmentally friendly production of chickpeas in China.

Impact of the United States Department of Agriculture, Agricultural Research Service on Plant Pathology: 2015-2020.

There is an increasing need to supply the world with more food as the population continues to grow. Research on mitigating the effects of plant diseases to improve crop yield and quality can help provide more food without increasing the land area devoted to farming. National Program 303 (NP 303) within the U.S. Department of Agriculture, Agricultural Research Service is dedicated to research across multiple fields in plant pathology. This review article highlights the research impact within NP 303 between 2015 and 2020, including case studies on wheat and citrus diseases and the National Plant Disease Recovery System, which provide specific examples of this impact.

Genome-wide association studies of ionomic and agronomic traits in USDA mini core collection of rice and comparative analyses of different mapping methods.

BACKGROUND: Rice is an important human staple food vulnerable to heavy metal contamination leading to serious concerns. High yield with low heavy metal contamination is a common but highly challenging goal for rice breeders worldwide due to lack of genetic knowledge and markers. RESULTS: To identify candidate QTLs and develop molecular markers for rice yield and heavy metal content, a total of 191 accessions from the USDA Rice mini-core collection with over 3.2 million SNPs were employed to investigate the QTLs. Sixteen ionomic and thirteen agronomic traits were analyzed utilizing two univariate (GLM and MLM) and two multivariate (MLMM and FarmCPU) GWAS methods. 106, 47, and 97 QTLs were identified for ionomics flooded, ionomics unflooded, and agronomic traits, respectively, with the criterium of p-value < 1.53 × 10- 8, which was determined by the Bonferroni correction for p-value of 0.05. While 49 (~ 20%) of the 250 QTLs were coinciding with previously reported QTLs/genes, about 201 (~ 80%) were new. In addition, several new candidate genes involved in ionomic and agronomic traits control were identified by analyzing the DNA sequence, gene expression, and the homologs of the QTL regions. Our results further showed that each of the four GWAS methods can identify unique as well as common QTLs, suggesting that using multiple GWAS methods can complement each other in QTL identification, especially by combining univariate and multivariate methods. CONCLUSIONS: While 49 previously reported QTLs/genes were rediscovered, over 200 new QTLs for ionomic and agronomic traits were found in the rice genome. Moreover, multiple new candidate genes for agronomic and ionomic traits were identified. This research provides novel insights into the genetic basis of both ionomic and agronomic variations in rice, establishing the foundation for marker development in breeding and further investigation on reducing heavy-metal contamination and improving crop yields. Finally, the comparative analysis of the GWAS methods showed that each method has unique features and different methods can complement each other.

Strengthening the Public Health Impacts of the Supplemental Nutrition Assistance Program Through Policy.

The US Department of Agriculture (USDA) Supplemental Nutrition Assistance Program (SNAP) is the cornerstone of the US nutrition safety net. Each month, SNAP provides assistance to 40 million low-income Americans-nearly half of them children. A number of changes could strengthen the public health impacts of SNAP. This review first presents a framework describing the mechanisms through which SNAP policy can influence public health, particularly by affecting the food security, the diet quality, and, subsequently, the health of SNAP participants. We then discusspolicy opportunities with the greatest potential to strengthen the public health impacts of SNAP, organized into three areas: (a) food production and distribution, (b) benefit allocation, and (c) eligibility and enrollment. For each section, we describe current policy and limitations of the status quo, suggest evidence-based opportunities for policy change to improve public health, and identify important areas for future research.

Trends in Sodium Intake in Children and Adolescents in the US and the Impact of US Department of Agriculture Guidelines: NHANES 2003-2016.

OBJECTIVE: To examine trends in sodium intake and the impact of nutritional guidelines in the US pediatric population. STUDY DESIGN: Sodium intake data collected between 2003 and 2016 in the US National Health and Nutrition Examination Surveys (NHANES) were analyzed. Trends in intake for individuals aged 4-17 years and subgroups based on age, sex, and race and ethnicity were examined. Adherence to US Department of Agriculture guidelines was assessed. RESULTS: A total of 16 013 individuals (50.6% male) were included in the analysis. The median sodium intake was 2840 mg/day (95% CI, 2805-2875 mg/day), decreasing from 2912 mg/day (95% CI 2848-2961 mg/day) in 2003-2004 to 2787 mg/day (95% CI, 2677-2867 mg/day) in 2015-2016 (P = .005). Intake increased with age (2507 mg/day for individuals aged 4-8, 2934 mg/day for those aged 9-13 years, and 3124 mg/day for those aged 14-17 years; P < .001) and was greater in males than in females (3053 mg/day vs 2624 mg/day; P < .001). Caucasians, Hispanics, and African Americans consumed 2860, 2733, and 2880 mg/day, respectively (P < .001). Population adherence to US Department of Agriculture recommendations was 25.0% in 2003-2010 and 25.5% in 2011-2016 (P = .677). No age, sex, or racial/ethnicity subgroup had an adherence rate >30% after implementation of pediatric guidelines in 2010. CONCLUSIONS: Sodium intake remains elevated in all pediatric population segments, and guideline adherence is poor. A greater effort to reduce sodium consumption is needed to mitigate future cardiovascular disease risk.

Genetic characterization and genome-wide association mapping for dwarf bunt resistance in bread wheat accessions from the USDA National Small Grains Collection.

KEY MESSAGE: Dwarf bunt-resistant bread wheat accessions and SNP markers associated with DB resistance identified in this study are valuable resources for characterization and deployment of DB resistance in bread wheat. Dwarf bunt (DB), caused by Tilletia controversa J.G. Kühn, can significantly reduce grain yield and quality on autumn-sown wheat in regions with prolonged snow cover. DB can be managed with the use of resistant cultivars. The objectives of the present study were to characterize DB resistance in a large set of bread wheat accessions from the National Small Grains Collection and use a genome-wide association study approach to identify genetic loci associated with DB resistance. A total of 292 accessions were selected using historical DB resistance data recorded across many trials and years in the Germplasm Resources Information Network (GRIN) and re-tested for DB resistance in replicated field nurseries in Logan, UT, in 2017, 2018, and 2019. Ninety-eight accessions were resistant with DB normalized incidence ≤ 10%, and twenty-eight of these were highly resistant with DB normalized incidence ≤ 1% in both GRIN and the field nurseries. Based on the presence of marker haplotypes of the four published dwarf bunt QTL on 6DS, 6DL, 7AL, and 7DS, highly resistant accessions identified in this study may provide novel resistance and should be further evaluated. This study validated one previously identified QTL on 6DS and identified an additional locus on 6DS. These loci explained 9-15% of the observed phenotypic variation. The resistant accessions and molecular markers identified in the present study may provide valuable resources for characterization and deployment of DB resistance in bread wheat.

Addressing Food Insecurity through a Health Equity Lens: a Case Study of Large Urban School Districts during the COVID-19 Pandemic.

Reduced access to school meals during public health emergencies can accelerate food insecurity and nutritional status, particularly for low-income children in urban areas. To prevent the exacerbation of health disparities, there is a need to understand the implementation of meal distribution among large urban school districts during emergencies and to what degree these strategies provide equitable meal access. Our case study of four large urban school districts during the COVID-19 pandemic aims to address these knowledge gaps. Guided by the Getting to Equity (GTE) framework, we conducted a mixed-methods study evaluating emergency meal distribution and strategy implementation in four large urban school districts (Chicago Public Schools, Houston Independent School District, Los Angeles Unified School District, and New York City Department of Education). We gathered data from school district websites on (1) meal service and delivery sites and (2) district documents, policies, communication, and resources. Using qualitative coding approaches, we identified unique and shared district strategies to address meal distribution and communications during the pandemic according to the four components of the GTE framework: increase healthy options, reduce deterrents, build on community capacity, and increase social and economic resources. We matched district census tract boundaries to demographic data from the 2018 American Community Survey and United States Department of Agriculture food desert data, and used geographic information systems (GIS) software to identify meal site locations relative to student population, areas of high poverty and high minority populations, and food deserts. We found that all districts developed strategies to optimize meal provision, which varied across case site. Strategies to increase healthy options included serving adults and other members of the general public, providing timely information on meal site locations, and promoting consumption of a balanced diet. The quantity and frequency of meals served varied, and the degree to which districts promoted high-quality nutrition was limited. Reducing deterrents related to using inclusive language and images and providing safety information on social distancing practices in multiple languages. Districts built community capacity through partnering with first responder, relief, and other community organizations. Increased social and economic resources were illustrated by providing technology assistance to families, childcare referrals for essential workers, and other wellness resources. Geospatial analysis suggests that service locations across cities varied to some degree by demographics and food environment, with potential gaps in reach. This study identifies strategies that have the potential to increase equitable access to nutrition assistance programs. Our findings can support (1) ongoing efforts to address child food insecurity during the pandemic and (2) future meal provision through programs like the Summer Food Service Program and Seamless Summer Option. Future research should further examine the rationale behind meal site placement and how site availability changed over time.

The Supplemental Nutrition Assistance Program (SNAP): History, Politics, and Public Health Implications.

This commentary introduces a special section of AJPH on the Supplemental Nutrition Assistance Program (SNAP), the US government's largest antihunger program and third-largest antipoverty program. SNAP demonstrably lifts adults, children, and families out of poverty, thereby constituting a vital component of this nation's public health safety net.Despite its well-documented benefits, SNAP is under political and budgetary siege, mainly from congressional representatives and lobbying groups opposed to a federal role in welfare. In part, SNAP is protected from total annihilation by its unusual authorizing legislation-the Farm Bill.This commentary provides a brief overview of the political history of SNAP and its Farm Bill location as background to the deeper analyses provided in this series of articles.

Supplemental Nutrition Assistance Program Data: Why Disclosure Is Needed.

The Supplemental Nutrition Assistance Program (SNAP) provides funding to low-income households to purchase food at participating stores. The goals of the program include reducing hunger, improving nutrition, and strengthening the US food system. These are interrelated, as food access and choice depend on availability.SNAP generates data that could be useful for program evaluation and evidence-based policymaking to reach public health goals. However, the US Department of Agriculture (USDA) does not collect or disclose all SNAP-related data. In particular, the USDA does not systematically collect food expenditure data, and although it does collect transaction (sales) and redemption data (the amount retailers are reimbursed through SNAP), it does not release these data at the store level.In 2018, Congress quietly changed the law to prohibit the USDA from disclosing store-level transaction and redemption data, and in 2019, the US Supreme Court blocked disclosure of these data. These federal proceedings can inform the outcome of additional efforts to disclose SNAP-related data, as well as future research and policy evaluation to support improved public health outcomes for SNAP beneficiaries.

Is vegetarianism healthy for children?

According to the Academy of Nutrition and Dietetics' influential position statement on vegetarianism, meat and seafood can be replaced with milk, soy/legumes, and eggs without any negative effects in children. The United States Department of Agriculture endorses a similar view. The present paper argues that the Academy of Nutrition and Dietetics ignores or gives short shrift to direct and indirect evidence that vegetarianism may be associated with serious risks for brain and body development in fetuses and children. Regular supplementation with iron, zinc, and B12 will not mitigate all of these risks. Consequently, we cannot say decisively that vegetarianism or veganism is safe for children.