2008 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.
A simple imaging system was developed to inspect and sort wheat samples and other grains at moderate feed-rates (30 kernels/s). A single camera captured color images of three sides of each kernel by using mirrors, the images were processed on a personal computer. After classification, the computer could output a signal from the parallel port to activate an air valve to divert (sort) kernels into a secondary container. The sorter is able to separate hard red kernels from hard white kernels (95% to 99%) and is an economical and useful instrument for sorting wheat and other grains with high accuracy. Supports NP306, Component 1, Problem 1b and 1d.
Fusarium head blight of wheat, caused by Fusarium graminearum, results in shriveled, discolored kernels referred to as Fusarium-damaged kernels (FDK). FDK is one of the major grain grading factors and is determined by visual sorting which is laborious and inconsistent. The ability of a single-kernel near-infrared (SKNIR) system to detect FDK was evaluated by comparing FDK sorted by the system to FDK sorted visually. Supports NP306, Component 1, Problem 1b and 1d.
An automated system was developed that nondestructively measured quality traits of individual kernels, sorted the kernels based on user-defined criteria and applied to sorting wheat, Triticum aestivum L, kernels by protein content and hardness. Also used to sort proso millet, Panicum miliaceum L., into amylose-bearing and amylose-free fractions. This technology can be used to enrich the desirable class within segregating populations in breeding programs; increase the purity of heterogeneous advanced or released lines; or measure the distribution of quality within samples during the marketing process. Supports NP306, Component 1, Problem 1b and 1d.
Milling wheat infested with low densities of internal feeding insects can result in flour containing insect fragments. The Food and Drug Admin.(FDA) enforces a standard or defect action level of 75 insect fragments per 50g flour. The relationship between level of infestation and number of resulting fragments is not well documented. We characterized the number of insect fragments produced from milling small lots of wheat spiked with known densities and life stages of Sitophilus oryzae. Fragments were enumerated with near-infrared spectroscopy NIRS. Data suggests NIRS could be adopted for rapid assessment of insect fragments resulting from relatively low levels of infestation with immature life state, but was not accurate enough for enumerating fragments resulting from adults at densities relevant to FDA standards. Supports NP306, Component 1, Problem 1b and 1d.
The relationship between bread quality and 49 hard red spring (HRS) or 48 hard red winter (HRW) grain, flour, and dough quality characteristics was studied. Estimated bread quality attributes included loaf volume, bake mix time, bake water absorption, and crumb grain score. When the data set was divided into calibration and prediction sets, the loaf volume and bake mix time models still looked promising for screening samples. Only loaf volume could be predicted with accuracies adequate for screening samples. Supports NP306, Component 1a.
Grain moisture content (MC) and temperature (T) are the primary factors affecting grain deterioration in storage. If these factors are not properly monitored and controlled, grain quality can deteriorate quickly due to mold growth and insect infestation. This research examined use of relative humidity (RH), T, and carbon dioxide (CO2) sensors for their suitability to determine adverse storage conditions of wheat. Sensors were placed at different depths in the bin. The wet grain produced high amounts of CO2, which, in most cases, was easily detectable during aeration. Lowering grain temperature with aeration diminished the amount of CO2 produced making it more difficult to detect unless the CO2 sensor was located very close to the wet grain. The moisture content of the grain increased downstream of the high-moisture grain during aeration as indicated by the EMC data. Simultaneous monitoring of stored grain with these sensors should improve storage management by detecting problematic conditions quickly so corrective measures could be taken. This accomplishment addresses National Program problem areas 1a and 1b: Definition and Basis for Quality, and Methods to Evaluate Quality.
Fusarium head blight (FHB), or scab, is a destructive disease of wheat. FHB causes yield reductions of up to 50% and crop losses in the US have exceeded $1 billion in some years. In addition, FHB can produce the toxin deoxynivalenol which must be below FDA guidelines. Visible detection of FHB is laborious and subjective and we evaluated the use of automated near-infrared technology to detect FHB. Results showed that visual detection was strongly correlated to NIR detection and that the NIR method was more repeatable. This technology should help the grain industry more consistently detect FHB and thus improve the safety of the US food supply. The technology can also be used to rapidly screen new wheat lines for FHB resistance. This accomplishment addresses National Program problem areas 1a and 1b: Definition and Basis for Quality, and 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. This accomplishment addresses National Program problem areas 1a and 1b: Definition and Basis for Quality, and Methods to Evaluate Quality.
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. This accomplishment addresses National Program problem areas 1a and 1b: Definition and Basis for Quality, and Methods to Evaluate Quality.
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. This accomplishment addresses National Program problem areas 1a and 1b: Definition and Basis for Quality, and Methods to Evaluate Quality.
A low cost sorting device for wheat was built using a standard personal computer and color camera. Special programming techniques were used so that the throughput of the sorter would be high while keeping the sorter cost low. The sorting system was tested on its ability to separate red wheat from white wheat for wheat breeding programs. At a wheat throughput of 30 kernels per second, or 3.5 Kg per hour, the sorter is able to correctly separate 95% to 99% of the wheat. The accuracy is 15 to 20% higher than what can be achieved with traditional sorters. This sorter will help breeding programs isolate desirable kernels so that they can be propagated, which will results in faster releases of new and improved varieties of grain. Four wheat breeders in the United States have already adopted this system as their tool of choice for separating red and white wheat. This accomplishment addresses National Program 306 problem areas 1b: Methods to Evaluate Quality.
5.Significant Activities that Support Special Target Populations
Pearson, T.C., Wilson, J.D., Gwirtz, J., Maghirang, E.B., Dowell, F.E., Mccluskey, P., Bean, S. 2007. The Relationship Between Single Wheat Kernel Particle Size Distribution and the Perten SKCS 4100 Hardness Index. Cereal Chemistry. 84(6):567-575. Online. doi:10.1094/CCHEM-84-6-0567.
Pearson, T.C., Brabec, D.L. 2007. Detection of Wheat Kernels with Hidden Insect Infestations Using an Electrically Conductive Roller Mill. Applied Engineering in Agriculture. 23(5):639-645.
Haff, R.P., Pearson, T.C. 2007. An Automatic Algorithm for detection of Infestations in X-ray Images of Agricultural Products. Sensing and Instrumentation for Food Quality and Safety. 1(3):143-150
Haff, R.P., Pearson, T.C. 2007. Separating in shell pistachio nuts from kernels using impact vibration analysis. Sensing and Instrumentation for Food Quality and Safety. 1(4):188-192
Armstrong, P.R., Lingenfelser, J., Mckinney, L. 2007. The Effect of Moisture Content on Determining Corn Hardness from Grinding Time and Grinding Energy, and Hardness Prediction Using Near-Infrared Spectroscopy. Applied Engineering in Agriculture. Vol. 23(6):793-799.
Abu-Ghoush, M., Herald, T., Dowell, F.E., Xie, F., Aramouni, F.M., Madl, R. 2008. Effect of preservatives addition on the shelf life extensions and quality of flat breat as determined by near infrared spectroscopy and texture analysis. International Journal of Food Science and Technology. 43(2):357-364. Online. doi:10.1111/j.1365-2621.2007.01594.x.
Gwirtz, J., Hosney, C.R., Dowell, F.E., Hubbard, R. 2007. A unique approach to micronization. International Miller. 06/07:60-66.
Abughoush, M., Herald, T., Dowell, F.E., Xie, F., Aramouni, F., Walker, C. 2008. Effect of antimicrobial agents and dough conditioners on the shelf-life extension and quality of flat bread, as determined by near-infrared spectroscopy. International Journal of Food Science and Technology. 43(2):365-372. Online. doi:10.1111/j.1365-2621.2007.01625.x
Dowell, F.E., Maghirang, E.B., Pierce, R.0., Lookhart, G.L., Bean, S., Xie, F., Caley, M.S., Wilson, J.D., Seabourn, B.W., Ram, M.S., Park, S., Chung, O.K. 2008. The Relationship of Bread Quality to Kernel, Flour, and Dough Properties. Cereal Chemistry. 85(1):82-91. Online. doi: 10.1094/CCHEM-85-1-0082. Available http://cerealchemistry.aaccnet.org/toc/cchem/85/1.