The yield on US 30 Year Bond Yield eased to 4.87% on July 31, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.10 points and is 0.59 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. United States 30 Year Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

Long Term Real Rate Average: The Long-Term Real Rate Average is the unweighted average of bid real yields on all outstanding TIPS with remaing maturities of more than 10 years and is intended as a proxy for long-term real rates.

Long term government bond yields

A long-term field experiment was conducted from 1989 to 2007 in northern France in a laomy soil to assess the cumulative effects of cropping systems on soil compaction, soil porosity, soil structure, crop emergence and yield. Three cropping systems (CSs), including different crop rotations and cultivations (early or late sowing and harvesting), were compared. CS I was the succession of spring pea /winter wheat/oilseed rape (flax from 2001)/winter wheat while CSs II and III were the succession of sugar beet/winter wheat/maize/winter wheat. The latter two CSs consisted of different sowing dates, based on two distinct decision rules aimed at minimizing the risk of soil compaction in the CS II or maximizing the duration of the crop in the CS III. From 2000, a new treatment with superficial tillage (i.e. at 6 cm depth) was introduced into the experiment in order to compare the effects of annual ploughing and reduced tillage on change in soil structure over time. Soil water content was measured for each field operation by taking samples every 0.05 m up to a depth of 0.30 m in the topsoil. Soil compaction and soil structure was evaluated after each sowing using a morphological approach and soil bulk density measurements. The proportion of highly compacted zones, i.e. the zones with a massive structure and no visible macropores in the soil profile, were evaluated with the “profil cultural” method. Dry bulk density was measured with a gamma-ray transmission probe. Seedling emergence rates and crop yield were also measured in relation to cropping systems. This dataset represents an important description of the change in soil compaction level, crop emergence rates and yield, in relation to CSs and climate, and the overall impact on seedbed structure variations for major field crops under northern France conditions. This information can be used as input variables of several soil-crop models aiming at evaluating the impact of CSs and climate on soil compaction and seedbed structures.

The yield on US 10 Year Note Bond Yield rose to 4.38% on July 30, 2025, marking a 0.05 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.14 points and is 0.34 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. US 10 Year Treasury Bond Note Yield - values, historical data, forecasts and news - updated on July of 2025.

Graph and download economic data for Interest Rates: Long-Term Government Bond Yields: 10-Year: Main (Including Benchmark) for United States (IRLTLT01USM156N) from Apr 1953 to May 2025 about long-term, 10-year, bonds, yield, government, interest rate, interest, rate, and USA.

A grand challenge facing humanity is how to produce food for a growing population in the face of a changing climate and environmental degradation. Though empirical evidence remains sparse, management strategies that increase environmental sustainability, like increasing agroecosystem diversity through crop rotations, may also increase resilience to weather extremes without sacrificing yields. We used multilevel regression analyses of long-term crop yield datasets across a continental precipitation gradient to assess how temporal crop diversification affects maize yields in intensively-managed grain systems. More diverse rotations increased maize yields over time and across all growing conditions (28.1% on average), including in favorable conditions (22.6%). Notably, more diverse rotations also showed positive effects on yield under unfavorable conditions, with yield losses reduced by 14.0 to 89.9% in drought years. Systems approaches to environmental sustainability and yield resilience ...

The yield on 10 Year TIPS Yield rose to 1.96% on July 30, 2025, marking a 0.04 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.01 points and is 0.08 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for the United States 10 Year TIPS Yield.

The Long-Term Composite Rate is the unweighted average of bid yields on all outstanding fixed-coupon bonds neither due nor callable in less than 10 years. Dataset updated daily every weekday.

This dataset is part of the database compiled as an outcome of Work Area 1 in project OrganicYieldsUP. Variable definitions can be found here: https://doi.org/10.5281/zenodo.15276082

Work Package 3 (WP3) of the OrganicYieldsUP project focused on compiling off-site data from peer-reviewed scientific literature to complement the on-site experimental data gathered in WP2. The goal was to identify, extract, and structure data on yield-enhancing strategies under organic management across Europe and comparable climate zones. This process was essential for broadening the project’s evidence base and informing subsequent analysis and modelling activities in WP4 and WP5. WP3 followed a systematic approach aligned with PRISMA methodology to ensure transparent and consistent literature screening. A total of 751 publications were initially identified based on defined search criteria. After applying inclusion and exclusion filters, 170 studies passed the first screening phase. From these, data were successfully extracted from 60 scientific publications and entered into the standard WP2/WP3 data template developed in WP1.

The screening of published scientific papers focused on papers published between 2009 and 2024. This time frame was chosen to ensure the use of the most current and relevant studies reflecting recent developments in organic farming methods, data quality standards, and policy frameworks. The screening prioritized English-language publications to maintain consistency in terminology and ensure broad understanding across project partners. Only original peer-reviewed research articles were considered, including case study reports where applicable. The search excluded reviews, editorials, and opinion papers due to the risk of duplicating data already included in WP2. Studies needed to focus explicitly on the impact of organic crop management strategies on yields. Only field trials, long-term experiments, and case studies were included, while pot experiments and single-year studies were excluded to avoid misleading conclusions caused by seasonal anomalies or short-term effects. All included studies had to come from Europe or similar climate zones such as North America or North Africa. During initial screening, titles, abstracts, and keywords had to contain terms related to "yield" and "organic" to be considered relevant. Full-text screening followed, using specific keywords aligned with the WP1 database. Only studies containing the obligatory data fields identified in WP1 were accepted. Publications that had already been included in the WP2 analysis were not considered again in WP3.

Tillage x Fertility Crop Yields 1970-2015, Soils, and Plant TissueThese data represent crop yield data from 1970 to 2015 for the long-term Tillage x Fertility trial started by Dr. George Kapusta at the Southern Illinois University Belleville Research Center in Belleville, IL. Some other agronomic data are also included.BRC_TxF_yield_1970-2015.csvTxF soils increment data 1990 and 2013These data were used for the Cook and Trlica 2016 publication. Soil plow layer (0-15 cm) was constructed from 5-cm increments. Metadata is included with the yield README file.BRC_TxF_soils_increments_1990_2013.csvTxF Corn plant tissue 1990 and 2014These data were analyzed for the Cook and Trlica 2016 publication. Metadata are found in the yield README file.BRC_TxF_Plant_tissue_1990_2014 Corn.csvTxF historic soils composites 1978 1983 1990 1999 2011 2013These data were NOT included in the Cook and Trlica 2016 publication. Curation for the historic soils data was imperfect and any use of this data should be co...

Long-term Crop Rotation Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Lincoln, Nebraska Lincoln NE Long-term Crop Rotation Project Overview of NEMLTCRS: Long-term Crop Rotation Study (Ithaca, NE) Crop rotation and fertilizer N management are common practices that affect productivity and input use efficiency. Evaluating these practices in a long-term setting provides the opportunity to assess their influence across a wide range of growing conditions and to determine their effect on yield stability (performance across a wide range of environmental conditions). Previous publications from this experiment have evaluated the response of corn, soybean, and sorghum production to these treatments under conventional tillage during an earlier time period (e.g., Peterson and Varvel, 1989a,b,c; Varvel, 2000), concluding that diversified crop rotations generally enhance grain production. Following conversion to no-till, yield trends from 2007 to 2013 indicate that: • Diversified 2- and 4-yr crop rotations increased corn and grain sorghum yields. • Corn and grain sorghum grain yields in 2- and 4-yr rotations were more resilient to variable growing conditions.• Soybean was less sensitive than corn and grain sorghum to crop rotation. Excerpted from: Sindelar et al., 2016 (Agron. J. 108: 1592-1602) viewed as an unfassirable management practice in soybean because it can inhibit nodular:ion (Salvagiotti et aL. 2008). However. responses to early-season fertilizer N are inconsistent. For example. Varvd and Peterson (1992) reported a decrease with fertilizer N input. yet Osborne and Riedell (2006) reported a grain yield increase with fertilizer N addition. Therefore. additional work is needed to clarify this particular response of soybean to early-season N fenilization. Crop rotation and fertilizer N management arc common practices that affect productivity and input use efficiency. Evaluating these practices in a long-term setting provides the opportunity to assess their influence across a wide range of growing conditions and to determine their effect on yield stability (performance across a wide range of environmental conditions). Previous publications from this experiment have evaluated the response acorn. soybean. and sorghum produc-tion to these treatments under conventional tillage during an earlier time period (e.g.. Peterson and VarveL 1989a.b.c: Varvel. 2000). concluding that diversified crop rotations gener-ally enhance grain production. Information has not yet been reported from this study naluacing the treatments under no-till (2007-2013). To our knowledge. no studies have simul-taneously evaluated the stability of continuous and diversified rotations of corn. grain sorghum. and soybean. The objective of this study was to evaluate long-term yield performance. yield stability. and fertilizer N of corn. grain sorghum. and soybean as affected by crop rotation and fertilizer N under no-till in the western Corn Belt. MATERIALS AND METHODS A field experiment was established in 1972 on a Yuan silty clay loam-Tomek salt barn compkx (fine-silty. mired. supaac-tire. mesic Mollie Hapkidalfs and fine. smecutic. mimic Pachic Argiudolls. resik.l.didy) near Ithaca. NE (31•10'N. 96'25'W). Elevation of the site is 366 rn. and mean annual temperature and precipitation arc 10.5*C and 765 mm. respectively. In-season air temperature. soil temperature. precipitation. and open pan evaporation measured on-site during this time period arc shown in Tabk I. The experiment was a randomized complete block design in a split plot arrangement with five replications. Crop rotation was the main ploc, and fertilizer N rate was the split plot. Crop rotations included continuous crops (continuous corn (CC). continuous grain sorghum IGGI. and continuous soybean (SS]). 2-yr (CS and OS) and 4-yr crop rotations (corn-soybean-grain sorghum-ad/clover vocation ((:5C01 and corn-cut/clover - grain sorghum-soybean rotation (COGS]). Continuous rota-tions that also included a fallow treatment were established in 1972 (with three replications). In 1983. the 2- and 4-yr rotation treatments were added. fallow treaunenrs were dropped. and the experiment was expanded to five replications. For the 4-yr rota-tions, all crops were present in the roudon, but the sequences differed. Each phase of every crop rotation was present each year. Fertilizer N treatments were initiated in 1984 and included 0. 90. and 180 kg N ha-1 for corn and grain sorghum and 0.34. and 69 kg N ha-I for soybean and oat/clover. Split plots were 9 m wide (76-an nivrs.n = 12) and 10 m king. The study was annu-ally disked mice in the spring from 1983 until 2006. In 2007. the study was converted to no-till.Agronomy Journal • Volume 108. Issue 4 • 2016 1593. Resources in this dataset:Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/aff301fc-8105-4248-ab72-8add051a222e

Long term government bond yields are calculated as monthly averages (non seasonally adjusted data). They refer to central government bond yields on the secondary market, gross of tax, with a residual maturity of around 10 years. The bond or the bonds of the basket have to be replaced regularly to avoid any maturity drift. This definition is used in the convergence criteria of the Economic and Monetary Union for long-term interest rates, as required under Article 121 of the Treaty of Amsterdam and the Protocol on the convergence criteria. Data are presented in raw form. Source: European Central Bank (ECB)

This dataset provides values for 30 YEAR BOND YIELD reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The Long-Term Composite Rate is the unweighted average of bid yields on all outstanding fixed-coupon bonds neither due nor callable in less than 10 years. Dataset updated daily every weekday.

Content

Kim and Wright (2005) produced this data by fitting a simple three-factor arbitrage-free term structure model to U.S. Treasury yields since 1990, in order to evaluate the behavior of long-term yields, distant-horizon forward rates, and term premiums. For the full paper, please go to http://www.federalreserve.gov/pubs/feds/2005/200533/200533abs.html

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1990-01-02

• Observation End : 2019-09-30

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Ian Schneider on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

EE: Yield 10- Year Government Bonds data was reported at 3.547 % in 2024. This records a decrease from the previous number of 3.901 % for 2023. EE: Yield 10- Year Government Bonds data is updated yearly, averaging 2.916 % from Dec 2021 (Median) to 2024, with 4 observations. The data reached an all-time high of 3.901 % in 2023 and a record low of 0.063 % in 2021. EE: Yield 10- Year Government Bonds data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Estonia – Table EE.OECD.MEI: Long Term Interest Rates: OECD Member: Annual. [STAT_CONC_DEF] Data refer to the long-term interest rate for convergence pruposes - 10 years maturity.

The dataset shows structure of interest rates

Note: 1. For the year 1995-96, interest rate on deposits of maturity above 3 years, and from 1996-97 onwards, interest rates on deposit for all the maturities refer to the deposit rates of 5 major public sector banks as at end-March. 2. From 1994-95 onwards, data on minimum general key lending rates prescribed by RBI refers to the prime lending rates of 5 major public sector banks. 3. For 2011-12, data on deposit rates and Base rates of 5 major public sector banks refer to the period up to July 31, 2010. From July 1, 2010 BPLR System is replaced by Base Rate System. Accordingly the data reflects the Base Rate of five major public sector banks. Data for 2010-11 for Call/Notice Money rates are average of April-July 2010. 4. Data for dividend rate and yield rate for units of UTI are based on data received from Unit Trust of India. 5. Data on annual(gross) redemption yield of Government of India securities are based on redemption yield which is computed from 2000-01 as the mean of the daily weighted average yield of the transactions in each traded security. The weight is calculated as the share of the transaction in a given security in the aggregated value. 6. Data on prime lending rates for IDBI, IFCI and ICICI for the year 1999-00 relates to long-term prime lending rates in January 2000. 7. Data on prime lending rates for State Financial Corporation for all the years and for other term lending institutions from 2002-03 onwards relate to long-term (over 36-month) PLR. 8. Data on prime lending rate of IIBI/ IRBI from 2003-04 onwards relate to single PLR effective July 31, 2003. 9. IDBI ceased to be term lending institution on its conversion into a banking entity effective October 11, 2004. 10. ICICI ceased to be a term-lending institution after its merger with ICICI Bank. 11. Figures in brackets indicate lending rate charged to small-scale industries. 12. IFCI has become a non-bank financial company. 13. IIBI is in the process of voluntary winding up. 14. Figures for 2015-16 are as on July 14, 2015. 15. 2024-25 data : As on September 1, 2024; except for WALRs, WADTDR and 1-year median MCLR (July 2023). 16. * : Data on deposit and lending rates relate to five major Public Sector Banks up to 2003-04. While for the subsequent years, they relate to five major banks. 17. # : Savings deposit rate from 2011-12 onwards relates to balance up to 1 lakh. Savings deposit rate was deregulated with effect from October 25, 2011. 18. $ : Data on Weighted Average Lending Rates (WALRs), weighted Average Domestic Term Deposit Rate (WADTDR) and 1-year median marginal cost of funds-based lending rate (MCLR) pertain to all scheduled commercial banks (excluding RRBs and SFBs). 19. Data on lending rates in column (7) relate to Benchmark Prime Lending Rate (BPLR) for the period 2004-05 to 2009-10; Base Rate for 2010-11 to 2015-16 and Marginal Cost of Funds Based Lending Rate (MCLR) (overnight) for 2016-17 onwards. BPLR system was replaced by the Base Rate System from July 1, 2010, which, in turn, was replaced by the MCLR System effective April 1, 2016.

This work was conducted by the Diverse Rotations Improve Valuable Ecosystem Services (DRIVES) project, based in the USDA-ARS Sustainable Agricultural Systems Lab in Beltsville, MD. The DRIVES team compiled a database of 20-plus long-term cropping systems experiments in North America in order to conduct cross-site research. This repository contains all scripts from our first research paper from the DRIVES database: "Rotational complexity increases cropping system output under poorer growing conditions," published in One Earth (in press). This analysis uses crop yield and experimental design data from the DRIVES database and public data sources for crop prices and inflation. This repository includes limited datasets derived from public sources or lacking connection to site IDs. We do not have permission to share the full primary dataset, but can provide data upon request with permission from site contacts.The scripts show all data setup, analysis, and visualization steps used to investigate how crop rotation diversity (defined by rotation length and the number of species) impacts productivity of whole rotations and component crops under varying growing conditions. We used Bayesian multilevel modeling fit to data from 20 long-term cropping systems datasets in North America (434 site-years, 36,000 observations). Rotation- and crop-level productivity were quantified as dollar output, using price coefficients derived from National Agriculture Statistics Service (NASS) price data (included in repository). Growing condtions were quantified using an Environmental Index calculated from site-year average output. Bayesian multilevel models were implemented using the 'brms' R package, which is a wrapper for Stan. Descriptions of all files are included in README.pdf.

A long-term data series, at 1-km resolution, of crop yield (kg/ha) and crop water productivity (kg/m3) for maize and wheat across China, based on the MOD16 ET product, multiple remotely sensed crop physiological and environmental indicators, and crop phenological information, using a random forest algorithm. Results showed that MOD16 products are an accurate alternative to eddy covariance flux tower data to describe crop evapotranspiration (maize and wheat RMSE: 4.42 and 3.81 mm/8d, respectively) and the proposed yield estimation model showed accuracy at local (maize and wheat rRMSE: 26.81 and 21.80%, respectively) and regional (maize and wheat rRMSE: 15.36 and 17.17%, respectively) scales. These high-resolution crop yield and CWP datasets generated in this study revealed spatiotemporal patterns of agricultural production in China and may be applied to many scenarios, including understanding effects of climate change on agricultural production capacity in China under increasing demand for food security to optimize agricultural production strategies.