Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Yield Editor 2.0.7

Metadata Updated: April 21, 2025

Yield Editor is a tool which allows the user to select, apply and analyze a variety of automated filters and editing techniques used to process and clean yield data. The software imports either AgLeader advanced or Greenstar text file formats, and exports data in a delimited ASCII format. Yield Editor 2.0.7 includes some of the improvements and updates that users of the software have asked to be included. It provides three major improvements over version 1.0.2. The most important of these is the inclusion of a module for automated selection of many yield filter values, as well as a couple of additional automated filter types. A legend tool has been added which allows for the viewing of multiple data streams. Finally, a command line interface language under development allows for automated batch mode processing of large yield datasets. Yield maps provide important information for developing and evaluating precision management strategies. The high-quality yield maps needed for decision-making require screening raw yield monitor datasets for errors and removing them before maps are made. To facilitate this process, we developed the Yield Editor interactive software which has been widely used by producers, consultants and researchers. Some of the most difficult and time consuming issues involved in cleaning yield maps include determination of combine delay times, and the removal of “overlapped” data, especially near end rows. Our new Yield Editor 2.0 automates these and other tasks, significantly increasing the reliability and reducing the difficulty of creating accurate yield maps. This paper describes this new software, with emphasis on the Automated Yield Cleaning Expert (AYCE) module. Application of Yield Editor 2.0 is illustrated through comparison of automated AYCE cleaning to the interactive approach available in Yield Editor 1.x. On a test set of fifty grain yield maps, AYCE cleaning was not significantly different than interactive cleaning by an expert user when examining field mean yield, yield standard deviation, and number of yield observations remaining after cleaning. Yield Editor 2.0 provides greatly improved efficiency and equivalent accuracy compared to the interactive methods available in Yield Editor 1.x. Resources in this dataset:Resource Title: Yield Editor 2.0.7. File Name: Web Page, url: https://www.ars.usda.gov/research/software/download/?softwareid=370&modecode=50-70-10-00 download page: https://www.ars.usda.gov/research/software/download/?softwareid=370&modecode=50-70-10-00

Access & Use Information

Public: This dataset is intended for public access and use. License: Creative Commons CCZero

Downloads & Resources

Dates

Metadata Created Date March 30, 2024
Metadata Updated Date April 21, 2025

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date March 30, 2024
Metadata Updated Date April 21, 2025
Publisher Agricultural Research Service
Maintainer
Identifier 10113/AA22668
Data Last Modified 2024-02-13
Public Access Level public
Bureau Code 005:18
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id f7ebb726-053c-45b5-a223-e23e0f73ac36
Harvest Source Id d3fafa34-0cb9-48f1-ab1d-5b5fdc783806
Harvest Source Title USDA JSON
License https://creativecommons.org/publicdomain/zero/1.0/
Program Code 005:040
Source Datajson Identifier True
Source Hash 9ead616a65ded002b7f916912bf9bf8f64d6ba375ef724a33ad6cd752176073f
Source Schema Version 1.1

Didn't find what you're looking for? Suggest a dataset here.