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Monday, July 27, 2020 | History

3 edition of Estimating corn yields from precipitation records. found in the catalog.

Estimating corn yields from precipitation records.

Estimating corn yields from precipitation records.

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Published by USDA-ARS, USDA-NRCS, Colorado Conservation Tillage Association in [Akron, Colo, Greeley, Colo.?, Colo .
Written in English

    Subjects:
  • Corn -- Forecasting -- Great Plains,
  • Corn -- Yields -- Great Plains,
  • Precipitation (Meteorology) -- Great Plains

  • Edition Notes

    SeriesConservation tillage facts -- 2-96., Conservation tillage facts -- #96-2.
    ContributionsUnited States. Agricultural Research Service., United States. Central Great Plains Research Station.
    The Physical Object
    Pagination[2] p. ;
    ID Numbers
    Open LibraryOL17616913M
    OCLC/WorldCa39220295

    exception, irrigated yields substantially exceeded non-irrigated yields in all years. For example, for corn, irrigation increased yields over rainfed yields by over % on average and by over % in • GX, GX, GX, GX, and GX are true and accurate copies of the.   For example, Descartes can look at satellite data of agriculture in Brazil, Argentina, and China, and make predictions on global corn yields and prices. Or it can assess construction rates and.

    Global solar radiation R g is an important input for crop models to simulate crop responses. Because the scarcity of long and continuous records of R g is a serious limitation in many countries, R g is estimated using models. For crop-model application, empirical R g models that use commonly measured meteorological variables, such as temperature and precipitation, are generally by: The Northeast Ohio Agri-Culture newsletter is a free e-newsletter published by Andrew Holden for farmers in Ashtabula and Trumbull Counties. Above Normal temperatures and Precipitation Will Rule July; Estimating Corn Yields; Northeast Ohio Cover Crops Field Night Scheduled for .

    Estimating corn yields from precipitation records. ([Akron, Colo.: USDA-ARS ; Greeley, Colo.?: USDA-NRCS ; Colo.: Colorado Conservation Tillage Association, ?]), by United States. Central Great Plains Research Station and United States. Agricultural Research Service (page images at HathiTrust) Managing residue & storing precipitation.   Additional details on the total cost of production for each tillage system for the period prior to the experimental phase analyzed in this study are described in Chase and Duffy. 25 To determine gross returns, we used average annual prices for corn and soybeans from NASS county data records and annual yields reported by the Nashua experiment Cited by: 2.


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Estimating corn yields from precipitation records Download PDF EPUB FB2

Get this from a library. Estimating corn yields from precipitation records. [David C Nielsen; United States. Agricultural Research Service.; United States. Central Great Plains Research Station.; United States.

Natural Resources Conservation Service.; Colorado Conservation Tillage Association.;]. A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text.

PDF | Satellite remote sensing is commonly used to monitor crop yield in wide areas. Because many parameters are necessary for crop yield estimation, | Find, read and cite all the research you. Corn Disease Management: Corn Disease Loss Estimates From the United States and Ontario, Canada - This is the Estimating corn yields from precipitation records.

book year that plant pathologists around the North Central region have coordinated their efforts to document disease-related losses in corn yields across the region.

Precipitation records amount to more than annual / seasonal rainfall numbers ml can fall in an hour or across several days, the latter being much better for crop yields than the former. This is obvious, and yet Spencer ignores it totally over the last few decades and the last one in particular.

This publication discusses when corn is most susceptible to hail damage, determining yield loss due to stand reduction and defoliation, determining direct ear damage, bruising and stalk damage, and estimating total yie More.

Maize yield and soil properties are strongly related to landscape position. As a result, terrain information should be useful for interpreting yield maps and identifying recurring spatial patterns in agricultural fields. The objectives of our study were to examine the relationship between six years of maize (Zea mays) yield data and elevation, slope, and curvature and to develop a regression Cited by: 2.

@article{osti_, title = {Recent changes in county-level corn yield variability in the United States from observations and crop models}, author = {Leng, Guoyong}, abstractNote = {The United States is responsible for 35% and 60% of global corn supply and exports.

Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global. Unfortunately, this book can't be printed from the OpenBook. If you need to print pages from this book, we recommend downloading it as a PDF.

Visit to get more information about this book, to buy it in print, or to download it as a free PDF. Most of the recent studies on the consequences of extreme weather events on crop yields are focused on droughts and warming climate.

The knowledge of the consequences of excess precipitation on the crop yield is lacking. We attempted to fill this gap by estimating reductions in rainfed grain sorghum yields for excess precipitation. The historical grain sorghum yield and corresponding Cited by: 1. Results from field experiments in New York establish realistic yield levels for the Three Sisters, a polycultural cropping system of inter-planted corn, bean, and squash which was used by Iroquoian farmers in the 16th, 17th, and 18th centuries.

A traditional open-pollinated white flour corn yielded from 22 to 76 bu/acre ( to kg/ha); the higher yields were obtained in New York's Cited by: @article{osti_, title = {Evidence for a weakening strength of temperature-corn yield relation in the United States during –}, author = {Leng, Guoyong}, abstractNote = {Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO2 fertilization effects.

Data used in this study comprised of locally observed meteorological times series, records of southern oscillation index (SOI) and crop yields. Crop yield data spanned a period from /79 to /14 prompting the use of climatic data covering the same time period. Climatic dataCited by: 5.

The variability in precipitation beyond one and two standard deviations severely affects corn yields (Figure 10(b)).For instance, the corn yields are very weakly related (R 2 = ) to precipitation during the grain-filling general, above-normal precipitation supports corn yields; however, the flood event (when the precipitation exceeded two standard deviations from the mean.

Manure is an excellent source of many essential plant nutrients and, with proper management, can meet nearly all crop nutrient needs. Sampling manure for analysis is an essential and valuable nutrient management tool for determining the nutrients available in manure.

Crop yields are strongly dependent on the average climate, extreme temperatures, and carbon dioxide concentrations, all of which are projected to increase in the coming century. In this study, a statistical model was created to predict US yields to for three crops using low and high-emissions future scenarios (RCP and ).

The model is based on linear regressions between historical Author: Lillian Kay Petersen. Scott Irwin and Darrel Good • USDA reports • We have written extensively about U.S. corn yield forecasts issued by the National Agricultural Statistics Service (NASS) of the USDA. The purpose of this article is to review the information in these scientific articles and provide a more informed understanding of the role of the ASB in generating these important market-moving forecasts.

adapt the Corn Belt equation to cropland in other regions. This committee reappraised the Corn Belt factor values and Developmentsadded a rainfall factor. The resulting formula, generally known as the Mus- grave Equation (31), has been widely used forfor estimating gross erosion from watersheds in flood abatement programs.

A graphical solution. Though conceptually appealing, it is impossible to fully account in practice for all the individual decisions and behaviors that constitute the nation’s water use.

Nevertheless, statistical sampling and indirect methods can be used to estimate aggregate water use. The diverse goals of water use. Climate characteristics and their relationship with soybean and maize yields in Argentina, Brazil and the United States (e.g.

precipitation and temperature) affect crop growth, causing variations in yields. where they determinate relationship between corn and Cited by: 3. Development of a stochastic storm generator using high-resolution precipitation records - (Peer Reviewed Journal) Revuelta-Acosta, J.D., Flanagan, D.C., Engel, B.A.

Development of a stochastic storm generator using high-resolution precipitation records.Drought at any other time reduces yield of grass more than corn so low annual grass yields resulting from moisture deficits can coincide with reasonable corn yields.

In the years with favorable moisture supply (,and ), average grass and corn yields excee kg/ha.Assessing correlations of satellite-derived evapotranspiration, precipitation and leaf area index anomalies with yields of major Brazilian crops.

Remote Sensing of Environment. Framework for automated spatio-temporal enhancement of coarse resolution leaf area index (FASE-LAI) – Application to MODIS LAI - (Peer Reviewed Journal).