Yield Monitoring Systems: Understanding how we Estimate Yield

Similar documents
Combine Calibration : S Series Harvest Monitor. Accessing User Calibrations. Temperature Calibration

Yield Calibration Procedure S-Series Combines

S600/2630 Display Combine Yield Calibration Procedure

Cut Crop Edge Detection Using a Laser Sensor

How to do Geo-fencing with the FM200

Precision Ag: Profitability and Use. Ken O Brien 17 April 2008

Nebraska 4-H Robotics and GPS/GIS and SPIRIT Robotics Projects

How is GPS Used in Farming? Equipment Guidance Systems

DEVELOPMENT OF AN INTELLIGENT YIELD MONITOR FOR GRAIN COMBINE HARVESTER

3/7/2015. Wind Data. Finding Historical Wind Data. Finding Historical Wind Data. Finding Historical Wind Data. Wind Power Management

GNSS-Based Auto-Guidance Accuracy Testing

Automatic Guidance System Development Using Low Cost Ranging Devices

Department of Mechanical and Aerospace Engineering. MAE334 - Introduction to Instrumentation and Computers. Final Examination.

GPS for Snowmobilers. By Wayne Fischer. November 14, 2006

Foundation Specifications for 5.6-Meter Modular Earth Station Antennas

November 11, Chapter 8: Probability: The Mathematics of Chance

Foundation Specifications for 7.6-Meter Modular Earth Station Antennas

SL-RAT Acoustic Inspection Sewer Line Assessment Report

GNSS-Based Auto-Guidance Test Program Development

Grade 3 Measurement and Data 3.MD.7a-d

ME 365 FINAL EXAM. Monday, April 29, :30 pm-5:30 pm LILY Problem Score

Northern NY Agricultural Development Program Project Report Reducing Phosphorus and Nitrogen Loss with Aerway Incorporation of Manure

NNY Agricultural Development Program Project Report

4 th Grade Mathematics Learning Targets By Unit

Case IH Series

3. GPS receiver instruction cards GPS receivers

Real Time Kinematic VALUE GUIDE (US, Canada, Australia & New Zealand) CLICK THE ARROW TO GET STARTED

Singapore Math 4-U.S. Edition Class Description: Singapore math says that Singapore Primary Mathematics U.S. Edition "is a series of rigorous

Importance of Grounding in Power System. Presented by Mr. H Jayakumar Ex- Joint Director CPRI

The effects of uncertainty in forest inventory plot locations. Ronald E. McRoberts, Geoffrey R. Holden, and Greg C. Liknes

Mrs. Polk s 4 th Grade Area and Perimeter Extension Unit

March 1, Mr. Russell Walls, Senior Engineer Regional Water Quality Control Board, Central Valley Region 1685 E Street Fresno, CA 93706

Answer Sheets Cover Page

For more information on the Common Core State Standards, visit Beast Academy Grade 4 Chapters 1-12:

Solid State Science and Technology, Vol. 12, No. 1 (2004) DUAL FREQUENCY MULTI-PURPOSE MOISTURE SENSOR BASED ON MICROSTRIP PATCH ANTENNA

Learning Log Title: CHAPTER 2: ARITHMETIC STRATEGIES AND AREA. Date: Lesson: Chapter 2: Arithmetic Strategies and Area

PRE-LAB for: Introduction to Aerial Photographs and Topographic maps (Ch. 3)

Shape File Attribute Grain Harvest

Lawrence A. Soltis, M. and Robert J. Ross, M. 1

Case IH Series

SeaSonde Radial Site Release 6 CrossLoopPatterner Application Guide Apr 21, 2009 Copyright CODAR Ocean Sensors, Ltd

Central Platte Natural Resources District-Remote Sensing/Satellite Evapotranspiration Project. Progress Report September 2009 TABLE OF CONTENTS

Manufactured by M-Sens 2 Online-Moisture Meter for Solids. Moisture % Product Information.

Design Nailed and Wood Screwed Connections with Spreadsheet. Course Content

Figure 1 - The Main Screen of the e-foto Photogrammetric Project Creation and Management

A Performance Evaluation Device for Vibration Absorption Unit of Grain Loss Monitoring Device of Combine Harvester

PROPERTIES OF PLANTATION GROWN KOA (ACACIA KOA A. GRAY )

9/10/2013. Incoming energy. Reflected or Emitted. Absorbed Transmitted

ENVI.2030L Topographic Maps and Profiles

9 Moisture Monitoring

Pennsylvania System of School Assessment

DESIGN OF SENSOR NETWORK FOR REAL TIME DATA ACQUISITION OF WATER LEVEL IN THE AGRICULTURAL FIELD

Brazilian Amazon Fire Frequency Data in Raster Format. Summary:

GPS Errors. Figure 1. Four satellites are required to determine a GPS position.

Remote Sensing in Daily Life. What Is Remote Sensing?

nineteen Wood Construction 1 and design APPLIED ARCHITECTURAL STRUCTURES: DR. ANNE NICHOLS FALL 2016 lecture STRUCTURAL ANALYSIS AND SYSTEMS ARCH 631

Test Protocol for the Rolling Density Meter

90 Indexable Positive Milling Cutter

4.00 ULTRASONIC ANALYZER

LI-1500 Light Sensor Logger

Appendix B: Descriptions of Virtual Instruments (vis) Implemented

Northern York County School District Curriculum

This is an example of a Class 3 FAA/AST submittal package.

Coordinates, Datums, and Map Projection

Examples of Design for Cathodic Protection Systems

Second Quarter Benchmark Expectations for Units 3 and 4

Foundation Specifications

Estimation of Moisture Content in Soil Using Image Processing

GreenSeeker Handheld Crop Sensor Features

Location Tracking. Current Technologies 1/19/2011. Not one, single technology Convergence of several technologies. Systems for

Canopy Interception and Leaf Area Index

RECOMMENDATION ITU-R P The radio refractive index: its formula and refractivity data

Specifications and Dimensions

Guide to observation planning with GREAT

Electromagnetic flowmeters and switches DWM 1000/2000

Photosynthetically Active Radiation (PAR) Smart Sensor (Part # S-LIA-M003)

Algorithm Development of a Multi-Section Crop Detection System for a Corn Head

Telemetry formats and equations of Painani-2 Satellite

Decision support system for sensor-based autonomous filling of grain containers

Working with Formulas and Functions

SUGAR_GIS. From a user perspective. Provides spatial distribution of a wide range of sugarcane production data in an easy to use and sensitive way.

Datums for a Dynamic Earth

Study Guide: Slope and Linear Equations

Chapter 6 Navigation and Field Mapping

Numerical Roots and Radicals

MAE334 - Introduction to Instrumentation and Computers. Final Exam. December 11, 2006

Department of Civil and Environmental Engineering

1 (5) + b (x, y ) = (5, 0), m =

Office 2016 Excel Basics 16 Video/Class Project #28 Excel Basics 16: Mixed Cell References in Formulas & Functions to Save Time

Screw Withdrawal A Means to Evaluate Densities of In-situ Wood Members

Module 1 Study Guide

Forming and Shoring Product Selector

HCGG Bulk Density Sensor (BDS) Load Cell Replacement

Future City s 2018 Eye on Engineering Webinar October 24 th, The webinar will begin in a moment

Brian Arnall Precision Nutrient Management Oklahoma State University

Leonard C. Thomas TA Instruments, 109 Lukens Drive, New Castle DE 19720

ICBO ES ER-5598 n HUD MR 1310 DSA PA-123 n LAC RR25448 n CCMC R. Limit States Design

Homework #3 Water Distribution Pipe Systems

Square Shear Beam Mounting Guidelines

Chapter 2 Descriptive Statistics: Tabular and Graphical Methods

Transcription:

Monitoring Systems: Understanding how we Estimate Joe D. Luck, Precision Agriculture Engineer University of Nebraska-Lincoln Extension Department of Biological Systems Engineering Discussion Topics monitor components Calibrating the yield monitor Moisture sensing monitor output Estimating crop yield Making yield maps 1

Basic Monitor Components Mass Flow Sensor GPS System Moisture Sensor Field Computer Header Sensor Monitor Component Functions Field Computer Monitors all sensors Displays harvest functions Logs data for storage and transfer GPS System Provides field position Header Status Sensor Logs data when down Stops logging when up 2

Monitor Component Functions Mass Flow Sensor Impt plate sensor (most popular) Mounted in clean grain elevator Grain impts plate Force of impt deflects load cell Voltage output from load cell Voltage is proportional to mass flow Trimble.com Calibrating the Monitor Why calibration is necessary: We only know the voltage output from the sensor We need to relate that to something real (lbs or ) Calibration procedure is specific to eh yield monitor Collect mass of grain per time Computer records sensor output Enter grain mass into computer Computer develops equation to estimate mass flow from voltage output 3

Grain Mass Flow Rate (lb/sec) 12/20/2013 Static Mass Flow Sensor Measurements Sensor output at a constant mass flow rate: Two-Point Calibration 6 Day one: High Flow 5 4 3 2 1 0 Low Flow 0 0.5 1 Mass Flow 1.5Sensor Output 2 (V) 2.5 3 3.5 4

Monitor Error (%) Grain Mass Flow Rate (lb/sec) 12/20/2013 Two-Point Calibration Errors 9 6 3 0-3 -6-9 5 15 25 35 45 55 Grain Flow Rate (/min) 6 Multi-Point Calibration Day one: High Flow 5 4 3 2 1 Low Flow 0 0 0.5 1 Mass Flow 1.5Sensor Output 2 (V) 2.5 3 3.5 5

Monitor Error (%) 12/20/2013 Multi-Point Calibration Errors 9 6 3 0-3 5 15 25 35 45 55 Grain Flow Rate (/min) Calibration Notes Mass Flow Sensor Accurate calibration is critical! Our goal is to calibrate mass flow rate estimations come later Errors from 1 to 3% are expected (field average) Conduct at least one calibration per crop per year Test weights may affect cury recalibrate 6

Moisture Sensing Moisture is necessary for marketable yield Different sensor types: Flow-through Single-sample Electrical resistance of grain measured Indirectly proportional to MC Affected by temperature (measured), lk density and surfe moisture Manual entry not recommended Output from the Monitor Computer Text file (.txt or.csv) format: 7

Output from the Monitor Computer What important data are in those columns: GPS location (latitude and longitude) Mass flow rate (lb/sec) Logging interval (sec) Distance traveled (in or ft) Header cut width (in or ft) Moisture content (%) Estimating our Crop We need a little more information: Adjusting the crop moisture content to a marketable value What is the moisture content for that? We know our mass flow rate (lb/sec) t we want shels we need to estimate the density 8

Estimating our Crop We use the general formula for yield (/): m t d w ρ 100 MC harvest 100 MC market Where: m = mass flow rate (lb/sec) MC harvest = % moisture content at harvest MC market = % marketable moisture content t = logging interval (sec) d = travel distance (ft) w = header cut width (ft) ρ = grain density (lb/) 43,560 = conversion from ft 2 to res Estimating our Crop -Example The yield data output shows a mass flow rate of 15.1 (lb/sec) of corn at a moisture content of 19.3% when traveling 54 inches in a one second logging interval. The header cut width of the combine was 240 inches (8 row header at 30 inches). What is the resulting yield in marketable /? m t d w ρ 100 MC harvest 100 MC market 9

Estimating our Crop -Example Let s start by putting in the MC market & density MC market = 15 % Density = 56 lb/ m t d w 56 100 MC harvest 100 15 Now the mass flow and logging interval Mass flow rate = 15.1 lb/sec Logging interval = 1 sec 15.1 1 d w 56 100 MC harvest 100 15 Estimating our Crop -Example We can input our moisture content while harvesting: MC harvest = 19.3 % 15.1 1 d w 56 100 19.3 100 15 Finally, we can input our travel distance and header cut width can t we? What about the units? Travel distance = 54 inches = 4.5 feet Header cut width = 240 inches = 20 feet 15.1 1 4.5 20 56 100 19.3 100 15 Now we re ready! = 123 / 10

Creating the Map We really only need 3 pieces of information: Latitude Longitude But, we have to have software (GIS) like SMS Summary monitor components and their functions Importance of yield monitor calibration Estimating yield from the yield monitor output Moving forward 11