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United States Department of Agriculture

Agricultural Research Service

Research Project: OBJECTIVE GRADING AND END-USE PROPERTY ASSESSMENT OF SINGLE KERNELS AND BULK GRAIN SAMPLES

Location: Engineering and Wind Erosion Research Unit

2007 Annual Report


1a.Objectives (from AD-416)
Develop instrumentation and procedures for objective grading, on-line quality measurement, sorting, and correlation of grade and quality measurements of single kernels and bulk samples to end-use properties of cereal grains and their products.


1b.Approach (from AD-416)
Develop rapid sensing and sorting technology for single kernel 'micro' traits such as GMO's, protein quality, starch quality, toxins, potential biosecurity issues, and traits important for evaluating grain for non-food uses (fuel, plastics, etc). Specific projects will include: development of high-speed (>100 kernels/s) sorting techniques for separating corn kernels infested with various molds, including mycotoxin producing molds; and develop methods to detect mutant corn kernels for enhancement of breeding programs. Develop rapid (~1 kernel/s) sensing and sorting technology for single kernel 'macro' traits such as hardness, moisture content, oil, starch, class, internal insects, and protein, especially for grains other than wheat (sorghum, corn, oats, etc). Specific projects will include: development of a single kernel characterization system to help predict milling yield in corn and wheat; and use of advanced signal processing from various sensors to rapidly and automatically detect moldy and insect damaged kernels.

Develop techniques to predict end-use characteristics, and to determine the accuracy and impact of these predictions. This includes studying the synergy of combining multiple measurements, evaluating sampling plans, assessing risk of various methods, conducting epidemiological studies, etc.


4.Accomplishments
Rapid single-kernel NIR measurement of grain and oil-seed attributes. Seed development requires the evaluation of hundreds of seed lines over multiple years to produce only a handful of commercial varieties or hybrids each year. Single-kernel near infrared (SKNIR) measurement has been used to improve and accelerate this process by being able to measure and sort seed for desirable characteristics. A new system was designed and tested that can measure seed characteristics for corn and soybeans at 10 kernels/s, which is a 10-fold throughput increase over previously available technology. Results show the instrument worked well for measuring corn and soybean. The new SKNIR system has excellent potential for reducing the time and costs associated with the development of corn hybrids and soybean lines with specific composition or processing traits. This accomplishment addresses National Program 306 problem areas 1b: Methods to Evaluate Quality.

Detection of Wheat Kernels with hidden insect infestations using an electrically conductive roller mill: Grain kernels infested by insects may show no indication on their exterior, but often contain hidden larvae. Although grain is always inspected for insect infestations upon shipping and receiving, many infested samples go undetected. Many methods for detecting infested wheat have been developed but none has seen widespread use due to expense or inadequate accuracy, or both. In this study, a simple laboratory roller mill system was modified to measure and analyze the electrical conductance of wheat as it was crushed. This facilitated detection of wheat kernels with live insects hidden inside of them. Furthermore, the apparatus is low cost (~1500 for parts) and can inspect a one kg sample in less than two minutes. This technology should help grain handlers and millers detect grain that is infested and take action before the insect population increase and damage more grain. The technology is currently being transferred to General Mills, Inc.

The Relationship of Bread Quality to Kernel, Flour, and Dough Properties: It is difficult to examine wheat kernels, or the flour or dough from those kernels, and determine if they can be used to make a good loaf of bread. However, breeders need to know if their breeding lines will bake well, and millers and bakers need to know if grain or flour they buy will result in good quality bread. We worked with the Federal Grain Inspection Service in order to develop models to predict bread quality including loaf volume, bake mix time, and water absorption. Resulting models showed that these quality indicators could be predicted with accuracies sufficient for screening samples. These results will help breeders develop lines with good bread quality, and help millers and bakers adjust their processes to maximize profits and give domestic and international consumers a consistently high-quality product. This accomplishment addresses National Program problem areas 1a and 1b: Definition and Basis for Quality, and Methods to Evaluate Quality.

An automated near-infrared system for selecting individual kernels based on specific quality characteristics: There is currently no method to select kernels with specific end-use characteristics to assist breeders in developing cultivars for specific grower needs or for specific markets. Current methods of developing new cultivars require many years of repetitive crosses to attempt to develop pure lines with specific traits. We developed a system that can automatically select specific kernels with specific traits from populations. The system utilizes near-infrared spectroscopy that measure attributes such as protein content, starch levels, or kernel hardness in individual kernels, and then removes those kernels from the sample at a rate of about 1 kernel/2 s. These kernels can then be used by breeders to develop cultivars with specific traits that will result in crops with improved agronomic performance and improved end-use quality. Also, the selection of kernels can occur in a few minutes and does not require years of crossing required in current breeding programs. The system can also be used to measure the variability of quality within samples, providing valuable information to grain handlers, storage managers, millers, and grain processors. The system has been applied to wheat and proso millet, and could apply to other grains.

Rapid assessment of insect fragments in flour milled from wheat infested with stored grain insects: The process of milling wheat infested with low densities of insects can result in flour containing insect fragments. We milled small lots of wheat infested with common insects found in stored grain to determine how many fragments would be produced; additionally, we tested near-infrared spectroscopy as a novel method to rapidly estimate the number of fragments in a sample. Immature insects produced 0.4 to 1.5 fragments per insect, but adults produced an average of 27 fragments per insect. Spectroscopy was successfully used to categorize samples containing fragments of immature insects but not fragments resulting from adult insects. These data will enable millers to better predict how many fragments may result in a lot of flour, and rapidly test a finished flour sample to determine if it contains excessive numbers of insect fragments.

In addition, technologies are being transferred to seed breeders in helping them sort early generations, to millers for detecting insects, to other millers for estimating insect fragments in flour, and to GIPSA for methods to estimate end use quality of wheat.

These accomplishments address National Program problem areas 1a and 1b: Definition and Basis for Quality, and Methods to Evaluate Quality.


5.Significant Activities that Support Special Target Populations
None.


6.Technology Transfer

Number of active CRADAs and MTAs3
Number of non-peer reviewed presentations and proceedings20
Number of newspaper articles and other presentations for non-science audiences6

Review Publications
Aldrich, B.T., Maghirang, E.B., Dowell, F.E., Kambhampati, S. 2007. Identification of termite species and subspecies of the genus Zootermopsis using near-infrared reflectance spectroscopy. Journal of Insect Science. 7pp. Journal of Insect Science 7:18, available online: insectscience.org/7/18.

Armstrong, P.R. 2006. Rapid single-kernel nir measurement of grain and oil-seed attributes. Applied Engineering in Agriculture. Vol. 22(5):767-772.

Bramble, T., Dowell, F.E., Herrman, T.J. 2006. Single-kernel near-infrared protein prediction and the role of kernel weight in hard red winter wheat. Applied Engineering in Agriculture. Vol. 22(6):945-949.

Fengyou, J., Maghirang, E.B., Dowell, F.E., Abel, C.A., Sonny, R. 2007. Differentiating Tobacco Budworm and Corn Earworm Using Near-Infrared Spectroscopy. Journal of Economic Entomology. Vol.100(3):759-764.

Dowell, F.E., Maghirang, E.B., Xie, F., Lookhart, G.L., Pierce, R., Seabourn, B.W., Bean, S., Wilson, J.D., Chung, O.K. 2006. Predicting wheat quality characteristics and functionality using near-infrared spectroscopy. Cereal Chemistry. Vol. (83)5:529-536.

Dowell, F.E., Maghirang, E.B., Graybosch, R.A., Baenziger, P.S., Baltensperger, D.D., Hansen, L.E. 2006. An automated near-infrared system for selecting individual kernels based on specific quality characteristics. Cereal Chemistry. Vol. 83(5):537-543.

Maghirang, E.B., Lookhart, G.L., Bean, S., Pierce, R.O., Xie, F., Caley, M.S., Wilson, J.D., Seabourn, B.W., Chung, O.K., Dowell, F.E. 2006. Comparison of quality characteristics and breadmaking functionality of hard red winter and hard red spring wheat. Cereal Chemistry. Vol. 83(5):520-528.

Onaran, I., Pearson, T.C., Yardimici, Y., Cetin, E. 2006. Detection of underdeveloped hazelnuts from fully developed nuts by impact acoustics. Transactions of the ASABE. Vol. 49(6):1971-1976.

Pearson, T.C., Cetin, E.A., Tewfik, A.H., Haff, R.P. 2007. Feasibility of impact-acoustic emissions for detection of damaged wheat kernels. Digital Signal Processing. 17(3):617-633.

Pearson, T.C., Brabec, D.L. 2006. Camera attachment for automatic measurement of single-wheat kernel size on a perten skcs 4100. 2006. Applied Engineering in Agriculture. Volume 22(6):927-933.

Haff, R.P., Pearson, T.C. 2006. Spectral Band Selection for Optical Sorting of Pistachio Nut Defects. Transactions of the ASABE. 49(4): 1105-1113

Pearson, T.C., Wicklow, D.T. 2006. Properties of corn kernels infected by fungi. Transactions of the ASABE. 49(4):1235-1245.

Cheng, E.M., Alavi, S., Pearson, T.C., Agbisit, R. 2007. Mechanical-Acoustic and Sensory Evaluations of Corn Starch-Whey Protein Isolate Extrudates. Journal of Texture Studies. Vol. 38(4):473-498.

Last Modified: 4/23/2014
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