Agricultural Prices: Average Weekly Prices: Producer: Buriti Fiber: 100 Splints: Pará data was reported at 100.000 BRL in 28 Apr 2017. This stayed constant from the previous number of 100.000 BRL for 21 Apr 2017. Agricultural Prices: Average Weekly Prices: Producer: Buriti Fiber: 100 Splints: Pará data is updated daily, averaging 100.000 BRL from Jan 2014 to 28 Apr 2017, with 57 observations. The data reached an all-time high of 100.000 BRL in 28 Apr 2017 and a record low of 75.000 BRL in 03 Feb 2017. Agricultural Prices: Average Weekly Prices: Producer: Buriti Fiber: 100 Splints: Pará data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Agriculture Sector – Table BR.RIH115: Agricultural Prices: Average Weekly Prices: Producer: Buriti.

Including the original data set and preprocessing data set two excel documents. The original dataset document contains time (month and year), wholesale price of agricultural products 200 index, industrial value-added growth rate, broad money supply, 7-day interbank lending rate, the Shanghai Composite Index, the area of sales of commercial properties, sales of commercial properties, housing sales prices and other 9 variables, totaling 459 records. The preprocessed data set document is the data document after preprocessing such as fixed-base conversion and reduction of serial fluctuation on the basis of the original data set, which contains 7 variables such as time (month and year), logarithm of wholesale price of agricultural products 200 index, logarithm of the year-on-year growth rate of value added of industry, logarithm of the supply of broad money, logarithm of 7-day interbank lending rate, logarithm of the Shanghai Composite Index, logarithm of the price of housing sales, etc., totaling 357 records.

This statistic indicates the quarterly fluctuation of gross agricultural products wholesale prices in France between the first quarter of 2012 and the third quarter of 2017. During the three-month period ending in June 2017, the wholesale volume of gross agricultural products had decreased by almost ***** points of balance of opinion, compared to the first quarter of the same year.

The dataset details the average gross commodity prices paid to farmers for various commodities for the period 2013 to 2017. Tea prices increased by 23.9 per cent from KSh 24,732.35 per 100 kilogram in 2016 to KSh 30,652.18 per 100 kilogram in 2017. Coffee prices paid to farmers improved by 16.5 per cent from KSh 40,815.54 per 100 kilogram in 2016 to KSh 47,547.71 per 100 kilogram in 2017. Favourable prices were also realized for maize, sugarcane, milk, beef and pork.

The Census of Agriculture, produced by the USDA National Agricultural Statistics Service (USDA), provides a complete count of America's farms, ranches and the people who grow our food. The census is conducted every five years, most recently in 2017, and provides an in-depth look at the agricultural industry.This layer summarizes payments made to producers by the Federal government from the 2017 Census of Agriculture at the county level. This layer was produced from data downloaded using the USDA's QuickStats Application. The data was transformed using the Pivot Table tool in ArcGIS Pro and joined to the county boundary file provided by the USDA. The layer was published as feature layer in ArcGIS Online.Dataset SummaryPhenomenon Mapped: Payments made to producers by the Federal government Coordinate System: Web Mercator Auxiliary SphereExtent: United States including Hawaii and AlaskaVisible Scale: All ScalesSource: USDA National Agricultural Statistics Service QuickStats ApplicationPublication Date: 2017AttributesThis layer provides values for the following attributes. Note that some values are not disclosed (coded as -1 in the layer) to protect the privacy of producers in areas with limited production.Federal Payments - Operations with ReceiptsFederal Payments - Receipts in US DollarsFederal Payments - Receipts in US Dollars per OperationFederal Payments not Including Conservation and Wetland Programs - Operations with ReceiptsFederal Payments not Including Conservation and Wetland Programs - Receipts in US DollarsFederal Payments not Including Conservation and Wetland Programs - Receipts in US Dollars per OperationFederal Payments for Conservation and Wetland Programs - Operations with ReceiptsFederal Payments for Conservation and Wetland Programs - Receipts in US DollarsFederal Payments for Conservation and Wetland Programs - Receipts in US Dollars per OperationConservation and wetland programs include:Conservation Reserve Program (CRP)Wetlands Reserve Program (WRP)Farmable Wetlands Program (FWP)Conservation Reserve Enhancement Program (CREP)Other programs with payments to producers include:2014 Agricultural Act (Farm Bill)Agriculture Risk Coverage (ARC)Price Loss Coverage (PLC)Commodity Credit Corporation (CCC)Loan Deficiency PaymentsDisaster Assistance ProgramsState and local government agricultural program payments and Federal crop insurance payments are not included.Additionally, attributes of State Name, State Code, County Name and County Code are included to facilitate cartography and use with other layers.What can you do with this layer?This layer can be used throughout the ArcGIS system. Feature layers can be used just like any other vector layer. You can use feature layers as an input to geoprocessing tools in ArcGIS Pro or in Analysis in ArcGIS Online. Combine the layer with others in a map and set custom symbology or create a pop-up tailored for your users. For the details of working with feature layers the help documentation for ArcGIS Pro or the help documentation for ArcGIS Online are great places to start. The ArcGIS Blog is a great source of ideas for things you can do with feature layers. This layer is part of ArcGIS Living Atlas of the World that provides an easy way to find and explore many other beautiful and authoritative layers, maps, and applications on hundreds of topics.

Agricultural Prices: Average Weekly Prices: Retail: Mimoso Common Corn Meal: Kg: Rio Grande do Norte data was reported at 1.250 BRL in 21 Jul 2017. This records a decrease from the previous number of 1.350 BRL for 14 Jul 2017. Agricultural Prices: Average Weekly Prices: Retail: Mimoso Common Corn Meal: Kg: Rio Grande do Norte data is updated daily, averaging 1.700 BRL from Mar 2016 (Median) to 21 Jul 2017, with 73 observations. The data reached an all-time high of 2.700 BRL in 23 Jun 2017 and a record low of 1.250 BRL in 21 Jul 2017. Agricultural Prices: Average Weekly Prices: Retail: Mimoso Common Corn Meal: Kg: Rio Grande do Norte data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Prices – Table BR.PA015: Agricultural Prices: CONAB: Average Weekly Prices: Retail: Corn Meal.

This annual report is a compendium of historical statistics covering the agriculture, forestry and fisheries sectors.

It provides a set of comprehensive statistical tables on Australian and world prices, production, consumption, stocks and trade for 19 rural commodities. The commodities covered include grains and oilseeds, livestock, livestock products, wool, horticulture, forestry products and fisheries products.

The report also contains statistics on agricultural water use and macroeconomic indicators such as economic growth, employment, balance of trade, exchange rates and interest rates.

The Census of Agriculture, produced by the USDA National Agricultural Statistics Service (USDA), provides a complete count of America's farms, ranches and the people who grow our food. The census is conducted every five years, most recently in 2017, and provides an in-depth look at the agricultural industry.This layer summarizes payments made to producers by the Federal government from the 2017 Census of Agriculture at the county level.This layer was produced from data downloaded using the USDA's QuickStats Application. The data was transformed using the Pivot Table tool in ArcGIS Pro and joined to the county boundary file provided by the USDA. The layer was published as feature layer in ArcGIS Online.Dataset SummaryPhenomenon Mapped: Payments made to producers by the Federal governmentCoordinate System: Web Mercator Auxiliary SphereExtent: United States including Hawaii and AlaskaVisible Scale: All ScalesSource: USDA National Agricultural Statistics Service QuickStats ApplicationPublication Date: 2017AttributesThis layer provides values for the following attributes. Note that some values are not disclosed (coded as -1 in the layer) to protect the privacy of producers in areas with limited production.Federal Payments - Operations with ReceiptsFederal Payments - Receipts in US DollarsFederal Payments - Receipts in US Dollars per OperationFederal Payments not Including Conservation and Wetland Programs - Operations with ReceiptsFederal Payments not Including Conservation and Wetland Programs - Receipts in US DollarsFederal Payments not Including Conservation and Wetland Programs - Receipts in US Dollars per OperationFederal Payments for Conservation and Wetland Programs - Operations with ReceiptsFederal Payments for Conservation and Wetland Programs - Receipts in US DollarsFederal Payments for Conservation and Wetland Programs - Receipts in US Dollars per OperationConservation and wetland programs include:Conservation Reserve Program (CRP)Wetlands Reserve Program (WRP)Farmable Wetlands Program (FWP)Conservation Reserve Enhancement Program (CREP)Other programs with payments to producers include:2014 Agricultural Act (Farm Bill)Agriculture Risk Coverage (ARC)Price Loss Coverage (PLC)Commodity Credit Corporation (CCC)Loan Deficiency PaymentsDisaster Assistance ProgramsState and local government agricultural program payments and Federal crop insurance payments are not included.Additionally, attributes of State Name, State Code, County Name and County Code are included to facilitate cartography and use with other layers.What can you do with this layer?This layer can be used throughout the ArcGIS system. Feature layers can be used just like any other vector layer. You can use feature layers as an input to geoprocessing tools in ArcGIS Pro or in Analysis in ArcGIS Online. Combine the layer with others in a map and set custom symbology or create a pop-up tailored for your users.For the details of working with feature layers the help documentation for ArcGIS Pro or the help documentation for ArcGIS Online are great places to start. The ArcGIS Blog is a great source of ideas for things you can do with feature layers.This layer is part of ArcGIS Living Atlas of the World that provides an easy way to find and explore many other beautiful and authoritative layers, maps, and applications on hundreds of topics.

Overview \r The March edition of Agricultural commodities contains ABARES' latest outlook for Australia's key agricultural commodities to 2021-22. \r The outlook will be an important focal point at the conference and underpin many presentations delivered by ABARES speakers at the conference. \r The report provides updated commodity forecasts, as well as articles on the EU sheep meat industry; farm performance of broadacre and dairy farms; productivity in Australia's broadacre and dairy industries; and disaggregating farm performance by size. \r \r Key Issues \r Commodity forecasts \r • The gross value of farm production is forecast to increase by 8.3 per cent to a record $63.8 billion in 2016-17 before easing by 3.9 per cent to a forecast $61.3 billion in 2017-18. Despite the forecast decline, the gross value of farm production in 2017-18 would be 17.3 per cent higher than the average of $52.3 billion over the five years to 2015-16 in nominal terms. \r • The gross value of livestock production is forecast to increase by around 4.4 per cent to $31.2 billion in 2017-18, following a forecast decrease of 2.6 per cent in 2016-17. If this forecast is realised, the gross value of livestock production in 2017-18 would be around 28 per cent higher than the average of $24.4 billion over the five years to 2015-16 in nominal terms. \r • The gross value of crop production is forecast to decrease by 11.3 per cent to $30 billion in 2017-18, after a forecast increase of 20.2 per cent in 2016-17. The decrease follows record production of wheat and barley in 2016-17, which resulted from favourable seasonal conditions during winter and spring. If this forecast is realised, the gross value of crop production in 2017-18 would be around 8 per cent higher than the average of $27.9 billion over the five years to 2015-16 in nominal terms. \r • In 2021-22 the gross value of farm production is projected to be around $59.6 billion (in 2016-17 dollars), 8.6 per cent higher than the average of $54.9 billion over the five years to 2015-16 (also in 2016-17 dollars). In 2021-22 the gross value of crop production is projected to be around $29.0 billion and the gross value of livestock production is projected to be around $30.6 billion (in 2016-17 dollars). \r • Export earnings from farm commodities are forecast to be around $48.7 billion in 2017-18, higher than the forecast $47.7 billion in 2016-17. \r • The agricultural commodities for which export earnings are forecast to rise in 2017-18 are beef and veal (up 1 per cent), wool (10 per cent), dairy products (11 per cent), sugar (10 per cent), cotton (35 per cent), wine (5 per cent), lamb (3 per cent), live feeder/slaughter cattle (4 per cent), rock lobster (6 per cent) and mutton (1 per cent). \r • Forecast increases in 2017-18 are expected to be partly offset by expected declines in export earnings for wheat (down 9 per cent), coarse grains (11 per cent), canola (6 per cent) and chickpeas (42 per cent). \r • In Australian dollar terms, export prices of wool, dairy products, sugar, wine, lamb, barley, canola, rock lobster and mutton are forecast to increase in 2017-18. Export prices for cotton and chickpeas are forecast to fall. Prices for beef and veal, wheat and live feeder/slaughter cattle are forecast to remain around the same as in 2016-17. \r • In 2021-22 the value of farm exports is projected to be around $46.6 billion (in 2016-17 dollars), 8 per cent higher than the average of $43.1 billion over the five years to 2015-16 in real terms. \r • The value of crop exports is projected to be $24.9 billion (in 2016-17 dollars) in 2021-22, 7 per cent higher than the average of $23.2 billion over the five years to 2015-16 in real terms. The value of livestock exports is projected to be $21.8 billion (in 2016-17 dollars) in 2021-22, 10 per cent higher than the average of $19.8 billion over the five years to 2015-16 in real terms. \r • Export earnings for fisheries products are forecast to increase by 2.3 per cent in 2017-18 to $1.5 billion, after decreasing by a forecast 3.4 per cent in 2016-17. \r \r Economic assumptions underlying this set of commodity forecasts \r \r In preparing this set of agricultural commodity forecasts: • World economic growth is assumed to be 3.3 per cent in 2017 and 3.4 per cent in 2018. Growth is expected to rise further to around 3.5 per cent in 2019 before declining to 3.4 per cent in 2021 and 3.3 per cent in 2022. \r • Economic growth in Australia is assumed to average 2.8 per cent in 2017-18. Over the medium term to 2021-22, economic growth is assumed to average around 3 per cent. \r • The Australian dollar is assumed to average US73 cents in 2017-18, slightly lower than the forecast average of US75 cents in 2016-17. It is assumed to appreciate slightly over the medium term, reaching US74 cents towards 2021-22. \r \r Articles on agricultural issues \r The EU sheep meat industry \r • The European Union is one of the world's largest consumers of sheep meat. Imports are controlled by import quotas and prohibitive out-of-quota tariffs. \r • Australia is the second largest exporter to the European Union, behind New Zealand, although its allocated quota is just 8 per cent that of New Zealand's. \r • As a high value market for sheep meat, expanding sheep meat exports to the European Union would benefit the Australian industry. However, until the trade outcomes of Brexit are known, opportunities for Australian sheep meat exporters are uncertain. \r \r Farm performance: broadacre and dairy farms, 2014-15 to 2016-17 \r • In 2016-17 farm cash income for Australian broadacre farms is projected to average $216,000 a farm, the highest recorded in the past 20 years. \r • Record broadacre farm cash incomes this year are the result of near record winter grain production in most regions and good prices for beef cattle, sheep, lamb and wool. \r • Average farm cash income is projected to increase for broadacre farms in all states except Tasmania in 2016-17. \r • Farm cash income for dairy farms is projected to decline by 17 per cent nationally to an average of $105,000 a farm in 2016-17, reflecting lower average farmgate milk prices and reduced milk production. \r \r Productivity in Australia's broadacre and dairy industries \r • From 1977-78 to 2014-15, productivity in the broadacre industries averaged 1.1 per cent a year as a result of declining input use (down 1 per cent a year) and modest output growth (up 0.1 per cent a year). \r • In the dairy industry, productivity growth averaged 1.5 per cent a year between 1978-79 and 2014-15. This reflected average annual growth of 1.3 per cent in output and an average annual decline of 0.2 per cent in input use. \r \r Disaggregating farm performance by size \r • The largest 10 per cent of broadacre farms produced 46 per cent of total output, while the smallest 50 per cent of farms produced 12 per cent of total output. \r • The average rate of return, including capital appreciation, generated by the largest 10 per cent of broadacre farms was 8.2 per cent, while the smallest 10 per cent generated average returns of -2.8 per cent. \r • The largest 10 per cent of broadacre farms had the lowest average equity ratio of all farms (79 per cent), while the smallest 10 per cent of farms had the highest average equity ratio (97 per cent). \r

Prices for most industrial commodities strengthened further in the first quarter (q/q), while global agricultural prices remained broadly stable. Crude oil prices are forecast to rise to an average of $55 per barrel (bbl) in 2017 from $43/ bbl in 2016. The oil forecast is unchanged since October 2016 and reflects balancing forces: upward pressure on prices from production cuts agreed by Organization of Petroleum Exporting Countries (OPEC) and non-OPEC producing countries, and downward pressure from persistently high stocks, supported by the faster-than-expected rebound of the U.S. shale oil industry. Metals prices are projected to increase 16 percent as a result of strong demand in China and various supply constraints, including labor strikes and contractual disputes in the case of copper, and environmental and export policies for nickel. Agricultural commodity prices, which gained 1 percent in the first quarter, are anticipated to remain broadly stable in 2017, with moderate increases in oils and meals and raw materials offset by declines in grains and beverages.

Agricultural Prices: Average Weekly Prices: Wholesale: Common Wheat Flour: 50 Kg: Mato Grosso do Sul data was reported at 100.460 BRL in 22 Sep 2017. This records an increase from the previous number of 87.800 BRL for 15 Sep 2017. Agricultural Prices: Average Weekly Prices: Wholesale: Common Wheat Flour: 50 Kg: Mato Grosso do Sul data is updated daily, averaging 95.000 BRL from Jan 2016 to 22 Sep 2017, with 88 observations. The data reached an all-time high of 106.500 BRL in 20 Jan 2017 and a record low of 87.800 BRL in 15 Sep 2017. Agricultural Prices: Average Weekly Prices: Wholesale: Common Wheat Flour: 50 Kg: Mato Grosso do Sul data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Agriculture Sector – Table BR.RIH092: Agricultural Prices: Average Weekly Prices: Wholesale: Wheat Flour.

According to the agricultural value-added data set of the year, the agricultural value-added was calculated. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 13 tables Agricultural added value (at current prices) 2000-2006.xls Agricultural added value (at current prices) 2000-2007.xls Agricultural added value (at current prices) 2000-2008.xls Agricultural added value (at current prices) 2005-2009.xls Agricultural added value (at current prices) 2005-2010.xls Agricultural added value (at current prices) 2006-2011.xls Agricultural added value (at current prices) 2007-2012.xls Agricultural added value (at current prices) 2008-2013.xls Agricultural added value (at current prices) 2008-2014.xls Agricultural added value (at current prices) 2010-2015.xls Agricultural added value (at current prices) 2011-2016.xls Agricultural added value (at current prices) 2012-2017.xls Agricultural added value (at current prices) 2013-2018.xls The data table structure is the same. For example, the data table of agricultural added value (calculated according to the price of the current year) from 2008 to 2013 has eight fields: Field 1: Indicators Field 2: item Field 3: 2008 Field 4: 2009 Field 5: 2010 Field 6: 2011 Field 7: 2012 Field 8:2013

Overview \r The June edition of Agricultural commodities contains ABARES latest outlook for Australia's key agricultural commodities in 2017-18, which updates the outlook released in March 2017. \r \r The report provides updated commodity forecasts, an article on China's grain policies and boxes on seasonal conditions in Australia and chilled beef exports to China. \r \r Key Issues \r Commodity forecasts \r \r • The gross value of farm production is expected to decrease slightly in 2017-18, reflecting an expected return to average seasonal conditions following record production in 2016-17. \r • The value of farm exports is forecast to remain relatively unchanged in 2017-18. \r \r Economic assumptions underlying this set of commodity forecasts \r \r In preparing this set of agricultural commodity forecasts: • World economic growth is assumed to be 3.3 per cent in 2017 and 3.4 per cent in 2018. \r • Economic growth in Australia is assumed to average 2.8 per cent in 2017-18. \r • The Australian dollar is assumed to average US73 cents in 2017-18, slightly lower than the estimated average of US75 cents in 2016-17. \r \r Articles and boxes on agricultural issues \r China's grain policies \r • Recent changes to China's price support policies signal a move towards a less regulated grain marketing system. China now recognises a role for imports to ensure a secure food supply and actively engages in world markets for grains. These changes have the potential to influence global markets given the size of China's agricultural sector. \r • The article examines China's domestic grains support policies and border measures. Minimum purchase prices and a grain reserve system for rice and wheat remain key policy instruments. A non-commodity-specific support policy is also being implemented. \r \r Seasonal conditions in Australia \r • A timely autumn break in south-eastern Australia has improved soil moisture and provided a good start to the winter cropping season. \r • Pasture growth and pasture biomass is close to average for this time of year across most of Australia. \r • Drier and warmer-than-average conditions are more likely for much of southern Australia during the 2017 winter, but this is unlikely to adversely affect crop and pasture growth in the short-term due to adequate soil moisture. \r \r Chilled beef exports to China heat up \r • Australian exports of chilled beef to China are becoming increasingly important as Australian frozen beef exports face strong competition from low-cost South American producers. \r • Australia and China recently signed the Joint Statement on Enhancing Inspection and Quarantine Cooperation between Australia and the People's Republic of China. This will facilitate an increase in the number of eligible establishments permitted to export chilled and frozen red meat to China, pending the outcome of an audit. \r

This statistic shows the average agricultural price of eggs per 100 Kilogram in the United Kingdom (UK) from 2013 to 2017. In 2017, the price for a 100 kilogram of eggs was ****** euros British Pounds.

China Agricultural Product Price Index 200: Wholesale: Food Basket data was reported at 97.300 2015=100 in 22 Jul 2018. This records an increase from the previous number of 95.460 2015=100 for 15 Jul 2018. China Agricultural Product Price Index 200: Wholesale: Food Basket data is updated daily, averaging 99.910 2015=100 from Jan 2017 (Median) to 22 Jul 2018, with 80 observations. The data reached an all-time high of 119.630 2015=100 in 25 Feb 2018 and a record low of 91.630 2015=100 in 16 Jul 2017. China Agricultural Product Price Index 200: Wholesale: Food Basket data remains active status in CEIC and is reported by Ministry of Agriculture and Rural Affairs. The data is categorized under China Premium Database’s Inflation – Table CN.IC: Agricultural Product Price Index: Wholesale: Weekly.

Agricultural Prices: Average Weekly Prices: Retail: Potato: Kg: Santa Catarina data was reported at 4.380 BRL in 27 Oct 2023. This records a decrease from the previous number of 4.550 BRL for 20 Oct 2023. Agricultural Prices: Average Weekly Prices: Retail: Potato: Kg: Santa Catarina data is updated daily, averaging 3.680 BRL from Mar 2017 (Median) to 27 Oct 2023, with 341 observations. The data reached an all-time high of 7.680 BRL in 18 Nov 2022 and a record low of 1.380 BRL in 29 Sep 2017. Agricultural Prices: Average Weekly Prices: Retail: Potato: Kg: Santa Catarina data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Prices – Table BR.PA020: Agricultural Prices: CONAB: Average Weekly Prices: Retail: Potato. [COVID-19-IMPACT]

Agricultural Prices: Average Weekly Prices: Producer: Fattened Cattle: Arroba: Tocantins data was reported at 186.670 BRL in 21 Jul 2023. This records an increase from the previous number of 185.000 BRL for 14 Jul 2023. Agricultural Prices: Average Weekly Prices: Producer: Fattened Cattle: Arroba: Tocantins data is updated daily, averaging 177.000 BRL from May 2017 (Median) to 21 Jul 2023, with 322 observations. The data reached an all-time high of 286.500 BRL in 21 Jan 2022 and a record low of 105.750 BRL in 21 Jul 2017. Agricultural Prices: Average Weekly Prices: Producer: Fattened Cattle: Arroba: Tocantins data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Prices – Table BR.PA129: Agricultural Prices: CONAB: Average Weekly Prices: Producer: Cattle. [COVID-19-IMPACT]

Agricultural Prices: Average Weekly Prices: Producer: Conifer Cone in Natura: Kg: Minas Gerais data was reported at 5.130 BRL in 02 May 2025. This records an increase from the previous number of 5.100 BRL for 25 Apr 2025. Agricultural Prices: Average Weekly Prices: Producer: Conifer Cone in Natura: Kg: Minas Gerais data is updated daily, averaging 1.780 BRL from Apr 2017 (Median) to 02 May 2025, with 131 observations. The data reached an all-time high of 13.130 BRL in 28 Apr 2017 and a record low of 0.880 BRL in 26 May 2017. Agricultural Prices: Average Weekly Prices: Producer: Conifer Cone in Natura: Kg: Minas Gerais data remains active status in CEIC and is reported by National Supply Company. The data is categorized under Brazil Premium Database’s Prices – Table BR.PA137: Agricultural Prices: CONAB: Average Weekly Prices: Producer: Conifer Cone. [COVID-19-IMPACT]