Peanuts are a versatile and widely consumed nut in the United States. In 2024, around 6.45 billion pounds of peanuts were produced in the United States, up from about 5.88 billion pounds of peanuts in 2023. Much of these peanuts were processed into peanut butter. Top Peanut Butter Brands Most Americans prefer to buy their peanut butter from the grocery store. The brand Jif was the leading peanut butter brand in the United States based on dollar sales. Private label peanut butter came in second place in the same period. Peanut Butter Consumption It is estimated that nearly 300 million Americans eat peanut butter, while about 32 million do not. It is extremely popular in sandwiches, as a baking ingredient, or on its own. There are many different varieties of peanut butter available in the market but the two most common types are creamy and crunchy. Creamy peanut butter is the most popular among U.S. consumers, by a wide margin. Another popular type of peanut butter is old fashioned/natural peanut butter which is produced without any preservatives or ingredients to keep the peanuts and the oil from separating in the jar.

United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing was 162.18000 Index Dec 2003=100 in July of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing reached a record high of 181.92300 in May of 2025 and a record low of 99.60000 in February of 2004. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing - last updated from the United States Federal Reserve on August of 2025.

United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: Primary Products was 165.08100 Index Dec 2003=100 in June of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: Primary Products reached a record high of 182.46200 in May of 2025 and a record low of 100.00000 in December of 2003. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: Primary Products - last updated from the United States Federal Reserve on August of 2025.

Graph and download economic data for Producer Price Index by Commodity: Processed Foods and Feeds: Peanut Butter (WPU02890158) from Jul 1998 to Jul 2025 about fat, nuts, processed, food, commodities, PPI, inflation, price index, indexes, price, and USA.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Peanuts (WPU01830111) from Jan 1947 to Jul 2025 about nuts, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

Statistics illustrates consumption, production, prices, and trade of Roasted Nuts and Peanut Butter in the United States from 2013 to 2024.

Graph and download economic data for Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing (PCU311911311911) from Dec 2003 to Jul 2025 about fat, nuts, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: Peanut Butter was 245.27100 Index Dec 1985=100 in June of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: Peanut Butter reached a record high of 271.90000 in April of 2012 and a record low of 100.00000 in December of 1985. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: Peanut Butter - last updated from the United States Federal Reserve on July of 2025.

Statistics illustrates consumption, production, prices, and trade of Peanut Butter and Prepared or Preserved Groundnuts in Argentina from 2007 to 2024.

Statistics illustrates consumption, production, prices, and trade of Peanut Butter and Prepared or Preserved Groundnuts in Belgium from 2007 to 2024.

United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: All Other Packaged Nuts, Including All Types of Seeds (Salted, Roasted, Cooked, or Blanched) was 288.51700 Index Jun 1991=100 in July of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: All Other Packaged Nuts, Including All Types of Seeds (Salted, Roasted, Cooked, or Blanched) reached a record high of 302.45400 in June of 2025 and a record low of 100.00000 in June of 1991. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: All Other Packaged Nuts, Including All Types of Seeds (Salted, Roasted, Cooked, or Blanched) - last updated from the United States Federal Reserve on September of 2025.

Philippines Production: Volume: Peanut data was reported at 29.400 Metric Ton th in 2017. This records an increase from the previous number of 27.900 Metric Ton th for 2016. Philippines Production: Volume: Peanut data is updated yearly, averaging 29.400 Metric Ton th from Dec 1987 (Median) to 2017, with 31 observations. The data reached an all-time high of 43.000 Metric Ton th in 1987 and a record low of 24.700 Metric Ton th in 1998. Philippines Production: Volume: Peanut data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.B015: Production: Volume: Agriculture (Annual).

Statistics illustrates consumption, production, prices, and trade of Peanut Butter and Prepared or Preserved Groundnuts in Benin from 2007 to 2024.

United States - Producer Price Index by Commodity: Processed Foods and Feeds: Peanut Butter was 170.66800 Index Jun 1991=100 in July of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Processed Foods and Feeds: Peanut Butter reached a record high of 189.00000 in April of 2012 and a record low of 80.00000 in August of 2002. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Processed Foods and Feeds: Peanut Butter - last updated from the United States Federal Reserve on September of 2025.

Graph and download economic data for Producer Price Index by Industry: Roasted Nuts and Peanut Butter Manufacturing: Secondary Products (PCU311911311911S) from Jun 1991 to Jul 2025 about fat, nuts, secondary, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

Accelerating crop improvement is critical to meeting food security demands in a changing climate. Long-read sequencing offers advantages over short reads in resolving structural variations (SVs) and aligning complex genomes, but its high cost has limited adoption in breeding programs. This study explores long-read low-pass (LRLP) sequencing as a cost-effective alternative for genomic analysis in a peanut multi-parent advanced generation intercross. Here we analyze LRLP using a variety of methodologies including Khufu on a linear graph, pangraph, and dynamic pangraph, as well as open source tools to analyze SVs and coverage. Consistently we find increased variants called for LRLP data compared to short read data. With a 1.63x average depth, LRLP sequencing covered 55% of the genome and 58% of gene space, outperforming short-read sequencing, which achieved only 17% and 11%, respectively even at a depth of 1.68x. Enhanced alignment accuracy and data retention further demonstrated LRLP’s efficacy.Our results highlight LRLP sequencing as a scalable, cost-effective tool for high-resolution trait mapping, with transformative potential for plant breeding and broader genomic applications.************* Files******************Short_linear_09.hapmap- A haplotype map of 125 individual peanut samples derived from a MAGIC breeding population. The file represents SNPs and was produced by Khufu, a proprietary genotyping pipeline. The input data for this analysis was low-depth short-read sequences.Long_linear_09.hapmap-A haplotype map of 125 individual peanut samples derived from a MAGIC breeding population. The file represents SNPs and was produced by Khufu, a proprietary genotyping pipeline. The input data for this analysis was low-depth long-read sequences.Short_linear_09_imputation_eval.txt- A file produced by Khufu that scores the accuracy of imputation.Long_linear_impuation_eval.txt- A file produced by Khufu that scores the accuracy of imputation.Long.panmap- A variant map of 125 individual peanut samples derived from a MAGIC breeding population produced by KhufuPan, a proprietary genotyping pipeline using a pangenome graph as a reference. SNPs, indels, and SVs are represented in this panmap. The input data for this analysis was low-depth long-read sequences.Long.panmap.fa- A file produced by KhufuPan, a proprietary genotyping pipeline using a pangenome graph as a reference. This file corresponds to Long.panmap and shows the sequences of the variants. The input data for this analysis was low-depth long-read sequences.Short.panmap- A variant map of 125 individual peanut samples derived from a MAGIC breeding population produced by KhufuPan, a proprietary genotyping pipeline using a pangenome graph as a reference. SNPs, indels, and SVs are represented in this panmap. The input data for this analysis was low-depth short-read sequences.Long.panmap.fa- A file produced by KhufuPan, a proprietary genotyping pipeline using a pangenome graph as a reference. This file corresponds to Short.panmap and shows the sequences of the variants. The input data for this analysis was low-depth short-read sequences.LRLP_Sequencing_Statistics.xlsx- Raw sequencing statistics from PacBio's Revio Sequencer of all peanut samples.LRLP_PBSV_info.xlsx- Data on structural variants called in all LRLP data using PacBio's tool PBMM2 and PBSV.LRLP_snpeff_summary.html- link to snpEff results for LRLP peanut samples.CostCalculationInfo.xlsx- Cost breakdowns used to calculate cost per value.

Resveratrol (trans-3,4′,5-trihydroxystilbene) is a natural stilbene phytoalexin which is also found to be good for human health. Cultivated peanut (Arachis hypogaea L.), a worldwide important legume crop, is one of the few sources of human's dietary intake of resveratrol. Although the variations of resveratrol contents among peanut varieties were observed, the variations across environments and its underlying genetic basis were poorly investigated. In this study, the resveratrol content in seeds of a recombination inbred line (RIL) population (Zhonghua 6 × Xuhua 13, 186 progenies) were quantified by high performance liquid chromatography (HPLC) method across four environments. Genotypes, environments and genotype × environment interactions significantly influenced the resveratrol contents in the RIL population. A total of 8,114 high-quality single nucleotide polymorphisms (SNPs) were identified based on double-digest restriction-site-associated DNA sequencing (ddRADseq) reads. These SNPs were clustered into bins using a reference-based method, which facilitated the construction of high-density genetic map (2,183 loci with a total length of 2,063.55 cM) and the discovery of several chromosome translocations. Through composite interval mapping (CIM), nine additive quantitative trait loci (QTL) for resveratrol contents were identified on chromosomes A01, A07, A08, B04, B05, B06, B07, and B10 with 5.07–8.19% phenotypic variations explained (PVE). Putative genes within their confidential intervals might play roles in diverse primary and secondary metabolic processes. These results laid a foundation for the further genetic dissection of resveratrol content as well as the breeding and production of high-resveratrol peanuts.

The global peanut butter market is expected to grow significantly over the next decade, with its value projected to increase from USD 5.68 billion in 2025 to USD 8.33 billion by 2035. This growth reflects a steady CAGR of 3.9% during the forecast period.

Analyzing Top Countries Producing and Supplying Peanut Butter

Statistics illustrates consumption, production, prices, and trade of Peanut Butter and Prepared or Preserved Groundnuts in Honduras from 2007 to 2024.

Peanut (Arachis hypogaea L.), a key oilseed crop in the U.S., plays a significant role in agriculture and the economy but faces challenges from biotic and abiotic stresses, including aflatoxin contamination caused by Aspergillus flavus and A. parasiticus. Despite many large-effect QTLs identified for yield and key traits, their use in breeding is limited by unfavorable genetic interactions. To overcome this, we aimed to identify consensus genomic regions and candidate genes linked to key traits by analyzing QTL data from 30 independent studies conducted over the past 12 years, focusing on biotic, abiotic, aflatoxin, morphological, nutritional, phenological, and yield-associated traits. Using genetic map information, we constructed consensus maps and performed a meta-analysis on 891 QTLs, leading to the identification of 70 Meta-QTLs (MQTLs) with confidence intervals ranging from 0.07 to 9.63 cM and an average of 2.33 cM. This reduction in confidence intervals enhances the precision of trait mapping, making the identified MQTLs more applicable for breeding purposes. Furthermore, we identified key genes associated with aflatoxin resistance in MQTL5.2 (serine/threonine-protein kinase, BOI-related E3 ubiquitin-protein ligase), MQTL5.3, MQTL7.3, and MQTL13.1. Similarly, for yield-related traits in MQTL3.1–MQTL3.4 (mitogen-activated protein kinase, auxin response factor), MQTL11.2 (MADS-box protein, squamosa promoter-binding protein), and MQTL14.1. Genes related to oil composition within MQTL5.2 (fatty-acid desaturase FAD2, linoleate 9S-lipoxygenase), MQTL9.3, MQTL19.1 (acyl-CoA-binding protein, fatty acyl-CoA reductase FAR1), MQTL19.4, and MQTL19.5. Nutritional traits like iron and zinc content are linked to MQTL1.1 (probable methyltransferase, ferredoxin C), MQTL10.1, and MQTL12.1. These regions and genes serve as precise targets for marker-assisted breeding to enhance peanut yield, resilience, and quality.