6.8   Comparison Two NIR Monitors for Corn and Wheat

Principal Investigators

Sam G. McNeill, Assistant Extension Professor, Biosystems and Agricultural Engineering
Charles G. Poneleit, Professor, Agronomy
Michael D. Montross, Assistant Professor, Biosystems and Agricultural Engineering

Cooperators

Phil Needham, Crop Consultant and Opti-Crop Program Leader, Miles Inc.
Ross Morgan, Equipment Dealer, Hopkinsville/Owensboro/Russellville

Introduction

Yield monitors have been used in the past six years by many Kentucky farmers to measure the variability of corn, soybeans and wheat yields within given fields as the crop is being harvested.  A current project is aimed at determining the spatial variability of oil and protein content in corn and soybean fields and protein in wheat fields along with yield by collecting grab samples from the combine grain tank during harvest.  This project was funded by the College of Agriculture’s first round of funding for precision agriculture activities.  The authors recently learned of a closely related development that would greatly enhance our goal.

Specialty/value-added grains provide an opportunity for farmers to capture market premiums by recognizing the value of chemical components in seed products.  Premiums currently range between 10 and 50 cents per bushel, based on the amount of a particular component (oil, protein, or starch) in each grain (House, 1999).  In Kentucky, the number of producers growing specialty grains presently outnumbers those generating yield maps or implementing site specific crop management practices.  However, a demonstration of available precision agriculture technologies might enhance the adoption of yield monitors by farmers.

The currently funded project utilizes a near infra-red (NIR) analyzer (NIRsystems, Model 6500 by Infratec®) in the UK Grain Quality Lab on campus to measure the chemical components of corn, soybean and wheat samples that are brought in from the field.  In particular, fiber, moisture, oil, protein and starch are determined for corn and soybean samples, and fiber, moisture and protein in wheat samples.  This project is labor intensive because of the amount of field work required to collect grain samples from the combine and simultaneously record the location of the sample with a DGPS receiver.  A mobile NIR analyzer would greatly facilitate sample collection, enable the investigators to process more grain samples, and allow for the investigation of segregation at harvest.

Case-New Holland (CNH) Advanced Farm Systems (AFS) group has a joint venture with Textron, Inc. to develop a prototype mobile NIR analyzer that has been tested to a limited degree during the last three harvest seasons.  This unit will be purchased and mounted on a CNH combine with an AFS yield monitor and demonstrated during the wheat and corn harvest seasons throughout western Kentucky.  The accuracy of the mobile NIR analyzer will be checked against the stationary NIR analyzer at the UK Grain Quality Lab that is being used in the initial study.

The objective of the proposed work are:

1)                  To collect grain samples, DPGS, and yield data in at least five selected corn and wheat fields as the combine operates from the Russellville area to the Owensboro area during harvest each year in a three-year period;

2)                  To measure the crude fiber, moisture, protein, oil and starch content of corn samples and the moisture and protein content of soft wheat samples using three methods: a) mobile Textron® NIR analyzer on a CNH combine with an AFS® yield monitor, b) the NIRsystems, Model 6500 (Infratec®) analyzer at the UK Grain Quality Lab, c) a commercial “wet chemistry” lab;

3)                  To conduct statistical comparison of grain quality estimates from all methods;

4)                  To provide results of study to farmers, crop consultants, research and extension personnel, manufacturers, and grain buyers at extension workshops, field days, seminars, conferences and meetings; and

5)                  To demonstrate the mobile NIR analyzer at field days during harvest and promote the UK Grain Quality Lab during educational events throughout the year.

Background

The Opti-Crop Program at Miles Farm Supply in Owensboro, Kentucky has been a service provider for precision agriculture since 1986 when they promoted the use of tramlines to control traffic patterns within crop fields (Needham, 1999).  Since then, they have expanded their services to include grid soil sampling, grain yield and boundary map generation, variable rate application of lime and fertilizers and remote sensing.  Consequently, they are recognized as one of the prominent leaders of precision agriculture. They plan to use a new CNH combine with an AFS yield monitor to harvest several thousand acres of wheat and corn in western KY next year.

The University of Kentucky Grain Quality Lab has been in service since 1996, providing free component analysis to corn producers and researchers.  Crude fiber, moisture, oil, protein and starch content levels are measured using a NIRsystems, Model 6500 (Infratec®) analyzer.  Additionally, the Lab provides NIR analysis for soybean and wheat samples with the calibration equations that were purchased with funds from our initial precision agriculture project.

The partnership/collaboration between CNH and Textron, Inc. has led to an interesting development that parallels the efforts of our initial research.  Their preliminary tests indicate that oil levels for regular field corn can range from about 2.5 to 6.0% (Fig. 1) and from 5.5 to 8.5% in high oil corn.  Protein levels can range from 5.0 to 12.0% (Fig. 2).  Moreover, market premiums are often based on small increments of each value-added component.  For example, high-oil corn producers have typically been offered a premium of 1 cent per bushel for each 0.1% of oil above a 6.0% base level (House, 1999).  Hence, precise measurements are essential for both the buyer and seller.  As with yield monitors, it is highly unlikely that market values will be determined by measurements from an instrument on a combine, but this information could help producers determine the variability that exists within each field and allow them to make management decisions that affect profitability.

A reliable mobile grain analyzer would also enable crop managers to segregate their crop into high/low profit yielding lots by placing each type in separate trucks and eventually in separate bins.  They could then market each lot of grain according to market demands to make the most of slim premiums that are offered.  Of course, such premiums would need to cover any additional handling and storage costs otherwise the economic incentive to produce specialty grains would be lost.

Grain buyers have also recently offered premiums for non-GMO soybeans and corn due to consumer demands for food labeling.  As a result of this issue, NIR instrument manufacturers are developing equipment/methods that will segregate GMO and non-GMO grains.  While the future of GMO grain production remains uncertain, NIR technology may play a vital role in assuring grain buyers of certain desirable attributes beyond their current use.

Procedures

A CNH combine with an AFS® yield monitor and Textron NIR analyzer will be purchased, installed, and calibrated prior to the 2000 wheat harvest.  Five corn and wheat fields will be identified prior to corn planting next spring based on anticipated crop rotations and harvest schedules for each year of the three-year study.  Boundary maps for each field will be generated with a DGPS mobile/ backpack receiver.  Samples will be collected from the combine grain tank at random locations in each field during wheat and corn harvest each year.  The location of each collection point will be recorded on the yield monitor log and with the DGPS receiver.

Grain samples will be transported to the UK Grain Quality Lab and processed with the NIRsystems, Model 6500 (Infratec®) analyzer.  Randomly selected samples will be sent to an independent lab for wet chemistry analysis to form a basis of comparison for both instruments. A statistical comparison will be made between the two NIR analyzers and a geo-statistical analysis will be performed with field data.  Results of the statistical analysis will be summarized and written during each year of study and made available on the College of Agriculture’s web page for precision agriculture, pending approval from CNH.  A final report of the three-year study will be written for an extension publication, posted on the College of Agriculture’s web page, and submitted for publication in the Journal for Applied Engineering in Agriculture.

Expected Benefits

This project will encompass both new and existing technology that will provide valuable information to Kentucky grain farmers.  It will introduce them to the technology and help them evaluate it for their operation.  Differences in grain components between stationary and mobile NIR analyzers will be determined and made known to farmers, crop consultants, manufacturers, grain buyers, and university research and extension personnel.  This information will assist all stakeholders in the grain trade by helping them manage the valuable information provided by NIR analyzers.  If significant discrepancies are found between the field and lab instruments, both manufacturers will be notified and attempts will be made to ascertain the accuracy of both devices.

Deliverables

Results from this study will be presented at county, multi-area, and statewide producer meetings, short courses, seminars, conferences and workshops that are sponsored by extension and service providers.  Articles will be prepared for grain trade magazines as appropriate.  One extension publication and a referred journal article will be developed as a result of this field study.