OBJECTIVE GRADING AND END-USE PROPERTY ASSESSMEENT OF SINGLE KERNELS AND BULK GRAIN SAMPLES

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
404	1510	2020	15%
404	1540	2020	35%
502	1510	1000	15%
502	1540	1000	35%

Progress 02/01/02 to 09/24/04

Outputs
1. What major problem or issue is being resolved and how are you resolving it (summarize project aims and objectives)? How serious is the problem? What does it matter? The U.S. is a major consumer and exporter of cereal grains. However, for the U.S. grain industry to remain competitive internationally and to meet domestic consumer demands for quality, it must continually improve the quality of grain and grain products. We propose to address three important problems that the U.S. grain industry faces in order to improve end-use quality of grain: 1) Grain properties that have the most influence on final or end-use product quality are not well known. For example, we do not know how most wheat kernel properties affect bread quality. This makes selection of grain difficult for buyers, and it is difficult for breeders to know what traits should be propagated; 2) Many instruments to detect quality of whole grains suffer from poor accuracy, high cost, being too slow, requiring toxic chemicals, or do not directly measure what customers need to know: end-use qualities; 3) In many cases, economically viable instruments do not exist to measure and/or sort whole grain defects that occur in small fractions of grain but can have a deleterious effect on quality, such as insect-damaged wheat kernels or mold damaged grain. The proposed research relates to the Quality Characterization, Preservation, and Enhancement Component of NP 306, and in particular, Problem Areas 1a and 1b: Definition and Basis for Quality, and Methods to Evaluate Quality, respectively. This technology will enable grain handlers to detect high-quality specialty grains, GMO's, and food safety concerns such as toxins, biosecurity issues, quarantine issues, etc. for subsequent segregation. The technology will also help handlers improve quality by sorting individual kernels to improve quality and food safety of the grain. Millers and bakers will gain insight into properties of the kernels that correlate to higher quality products, thus enabling them to better select grain for their specific needs. In some cases, technologies will enable sorting of grain to improve low-quality grain to a higher quality, such as by removing fungal-damaged or low-protein kernels from mixed lots. Given knowledge of grain properties that produce premium end-use qualities and non-destructive methods to measure these properties, grain customers will be able to purchase grain that more consistently meets their quality needs and producers will be able to segregate grain lots with higher quality. In addition, breeders will be able to use this technology to identify single kernels with traits that would be desirable to propagate. New technology and information developed through this research will be of use throughout the entire grain industry where quality and/or safety are of a concern. This includes producers, breeders, growers, grain handlers, marketers, millers, bakers, and government agencies such as the Extension Service, FGIS/GIPSA, FSIS, APHIS, and OSHA. 2. List the milestones (indicators of progress) from your Project Plan. The primary goal of our research is to improve the quality and safety of grain and grain products through the development of instrumentation and procedures for objective grading and on-line quality measurement and sorting, and correlation of single-kernel and bulk-sample grain properties to end-use quality measurements. Specific objectives are: 1) Develop automated, rapid-sensing and sorting technology for single kernels. Systems will be developed to a) detect wheat kernel defects using acoustics, and b) detect characteristics of single corn kernels by automating the acquisition of a plurality of measurements including imaging, weight, and near-infrared spectra; 2) Measure characteristics of single kernels and bulk samples that are critical to the success of the grain industry by utilizing experimental or commercial instrumentation. This includes a) detecting and removing kernels with mycotoxin-producing molds, b) detecting mutants for corn breeders, c) measuring oat milling parameters, and d) detecting insect fragments in flour; and 3) Develop techniques, using single and multiple measurements, to predict end-use characteristics such as flour yield, bake absorption, farinograph stability, loaf volume, etc. from whole grain or minimally processed grain, and to determine the accuracy and impact of these predictions. This includes studying the synergy of combining multiple measurements. 3. Milestones: A. Objectives addressed in FY 2004 were: 1) Develop automated, rapid-sensing and sorting technology for single kernels. Systems will be developed to a) detect wheat kernel defects using acoustics, and b) detect characteristics of single corn kernels by automating the acquisition of a plurality of measurements including imaging, weight, and near-infrared spectra; 2) Measure characteristics of single kernels and bulk samples that are critical to the success of the grain industry by utilizing experimental or commercial instrumentation. This includes a) detecting and removing kernels with mycotoxin-producing molds, b) detecting mutants for corn breeders, and c) detecting insect fragments in flour; and 3) Develop techniques, using single and multiple measurements, to predict end-use characteristics such as flour yield, bake absorption, farinograph stability, loaf volume, etc. from whole grain or minimally processed grain, and to determine the accuracy and impact of these predictions. This includes studying the synergy of combining multiple measurements. B. FY 2005 Milestones 1.a. Detect wheat kernel defects using single kernel acoustics from impact emissions - Develop signal processing algorithm using voice recognition technology. 1.b. Detect characteristics of single corn kernels using NIR spectroscopy - Develop corn handling system; integrate spectrometer. 2.a. Detect and remove kernels with mycotoxin-producing molds - Collect spectral data for white corn to select optimal pair of spectral bands for sorting. 2.b. Detect mutants for corn breeders - Develop semi-automated instrumentation to collect data from single corn kernels. 2.c. Detect single-kernel oat milling parameters - Test moisture/size measurement abilities for groats. 2.d. Detect insect fragments in flour - Develop imaging system; collect data with Flouroscan. 3. Predict end-use quality - Literature review, collect samples and analytical data. FY 2006 Milestones 1.a. Detect wheat kernel defects using single kernel acoustics from impact emissions - Develop working prototype that works in real time. 1.b. Detect characteristics of single corn kernels using NIR spectroscopy - Develop sorting system. 2.a. Detect and remove kernels with mycotoxin-producing molds - Test sorter; chemically analyze sorter accepts and rejects for mycotoxins. 2.b. Detect mutants for corn breeders - Analyze data to detect mutants; develop clustering procedure of different mutant classes. 2.c. Detect single-kernel oat milling parameters - Develop SKCS groat- damage prediction. 2.d. Detect insect fragments in flour - Development of fragment- detection algorithms. 3. Predict end-use quality - Develop prediction models for HRW and HRS wheat. FY 2007 Milestones 1.a. Detect wheat kernel defects using single kernel acoustics from impact emissions - Test prototype with field samples, including mold damaged, broken kernels, germinated and kernels damaged by insects that are external feeders. 1.b. Detect characteristics of single corn kernels using NIR spectroscopy - Develop calibrations. 2.a. Detect and remove kernels with mycotoxin-producing molds - Verify sorter performance with more samples. 2.b. Detect mutants for corn breeders - Measure chemical constituents in groups of mutants and normal kernels. 2.c. Detect single-kernel oat milling parameters - Develop SKCS groat size, oat-fill rate measurement. 2.d. Detect insect fragments in flour - Develop a prototype instrument for research/ industrial lab. 3. Predict end-use quality - Verify models with field data. Begin studying other classes. 4. What were the most significant accomplishments this past year? A. Single Most Significant Accomplishment during FY 2003 year: Reducing Toxins in Corn. A high-speed single-kernel sorter was used to remove mycotoxins from corn. It was found that using spectral absorbance at 750nm and 1200nm could distinguish kernels with aflatoxin- contamination greater than 100ppb from kernels with no detectable aflatoxin with over 98% accuracy. When these two spectral bands were applied to sorting corn at high speeds, reductions in aflatoxin averaged 82% for corn samples with an initial level of aflatoxin over 10 ppb. Most of the aflatoxin is removed by rejecting approximately 5% of the grain. Fumonisin is also removed along with aflatoxin during sorting. The sorter reduced fumonisin by an average of 88% for all samples. This technology will help insure the safety of the US food and feed supply. B. Other Significant Accomplishment(s), if any. Automating Grain Grading. Digital imaging technology has found many applications in grain industry. In this study, images of durum wheat kernels acquired under three illumination conditions - reflected, side- transmitted, and transmitted - were used to develop artificial neural network (ANN) models to classify durum wheat kernels by their vitreousness. The results showed that the models trained using transmitted images provided the best classification for the nonvitreousness class - 100% for non-vitreous kernels and 92.6% for mottled kernels. Results of the study also indicated that, using transmitted illumination may greatly reduce the hardware and software requirements for the inspection system, while providing faster and more accurate results, for inspection of vitreousness of durum wheat. Improving Measurement of Grain Traits. We compared two types of NIR instruments for their ability to predict concentrations of protein, moisture, and hardness of whole grain wheat; protein, ash, and amylose of wheat flour; and corn grit fat. The study used a Fourier transform-NIR spectrometer (FT-NIR) from Bruker Optics, Billerica, MA and a Model 6500 NIR from FOSS-NIR Systems, Inc., Silver Spring, MD. The FT-NIR instrument differs from the NIR instrument in the method of light spectra measurement. Wheat flour protein and ash; whole grain wheat protein and moisture were measured with excellent accuracy by both instruments while wheat flour amylose and whole grain wheat hardness measurement were less accurate. Corn grit fat measurement was poor for both instruments. Overall the FT-NIR and NIR instruments were essentially equal in measurement accuracy and there is no apparent advantage of one over the other. Detecting Insects in Flour. Primary pests of stored cereals that develop and feed inside grain kernels are the main source of insect fragments in wheat flour. The Food and Drug Administration (FDA) has set a defect action level of 75 or more insect fragments per 50 gram of flour. The current standard flotation method for detecting insect fragments in flour is very labor intensive and expensive. We investigated the potential of near-infrared spectroscopy (NIRS) to detect insect fragments in wheat flour at the FDA defect action level. Fragments counts with both the NIRS and the standard flotation methods correlated well with the actual number of fragments present in flour samples. However, the flotation method was more sensitive below the FDA defect action level than the NIRS method. Although the flotation method is very sensitive at the FDA action level, this technique is time consuming (almost 2 h/sample) and expensive. Although NIRS currently lacks the sensitivity of the flotation method, it is rapid, does not require sample preparation, and could be easily automated for a more sophisticated sampling protocol for large flour bulks. Therefore, this method should be reexamined in the future because NIRS technology is rapidly improving. Applying Grain Inspection Technology to Eliminating Human and Animal Pests. Tsetse flies are important vectors of African trypanosomes, which cause sleeping sickness in humans and nagana, a fatal disease, in livestock. About 300,000 human deaths are estimated to occur annually. Approximately three million cattle deaths occur annually, causing a direct annual loss of about $1.5 billion. Implementation of the sterile insect technique (SIT) for tsetse requires that only sterile male insects be released; thus, at some stage of the fly production process the females have to be removed. We examined the use of near-infrared spectroscopy technology to sex and sort the fly pupae. This technology was developed for measuring and sorting single grain kernels. Tsetse fly pupae up to 5 days before emergence can be sexed with accuracies that generally range from 80 to 100%. This system will enable effective separation of male and female pupae to be carried out with emerged females being returned to the colony and males being irradiated and released. This will significantly reduce the cost and efficiency of rearing tsetse flies for SIT programs. C. None. D. None. 5. Describe the major accomplishments over the life of the project, including their predicted or actual impact. Wheat hardness is a primary quality trait that relates wheat to its milling properties and end-use quality. The current standard measurement techniques for wheat hardness are destructive, i.e., they require grinding or crushing of wheat samples. There is a need for a measurement technique, such as in breeding programs, that is non-destructive, rapid, accurate, and accommodates small sample sizes. We developed a technique using a single kernel near-infrared instrument developed within the Engineering Research Unit that can measure hardness and sort single kernels automatically at a rate of 1 kernel per second. Wheat breeding programs are expected to benefit from this technique considering its non- destructive feature, small sample size requirement, accuracy, and rapidity. Wheat breeders currently do not have a non-destructive method to rapidly screen single wheat kernels for protein content. High protein content is preferred in wheat products such as pasta while low protein content is desirable for cakes and cookies. Wheat with higher protein commands higher price in export markets. Our Engineering Research Unit conducted cooperative research with Satake using their high-volume color/NIR sorter for sorting single kernels based on protein content. The sorter is now used by breeders to shift early generation wheat populations toward a target protein level, thus reducing the time required to develop varieties with specific quality traits. A high-speed color sorter has the potential to help wheat breeders purify their white wheat breeding lines and to help white wheat exporters meet purity requirements of end users. The Engineering Research Unit evaluated a Satake color sorter in cooperation with the Kansas Wheat Commission for removing red wheat from white wheat. The sorter was able to remove red wheat from white at a potential speed of 300 bu/hr. We currently us this technology to purify white wheat samples for breeders in several states as the US develops white wheat varieties to take advantage of significant export markets. The system significantly reduces the time required to develop new white wheat varieties, and improves the quality of new varieties as they are released. Bread staling is a complex process that occurs during bread storage, and the cause of staling is not understood. Understanding the staling phenomena will help us develop methods to reduce staling. Starch, protein, and temperature effects on bread staling were investigated by the Engineering Research Unit in cooperation with KSU using visible and near-infrared spectroscopy and differential scanning calorimetry. Results show that starch, protein, and moisture all contributed to the bread staling process. However, bread staling was mainly due to amylopectin retrogradation. Protein retarded bread staling, but not as much as temperature. The results of this study could lead to solutions to reduce bread staling that will bring economic benefit to bakers and consumers. The grain industry requested a low cost single kernel quality measurement and sorting system that could be used at field locations and by breeders. Thus, we developed a system in cooperation with KSU Biological and Agricultural Engineering Department that singulates kernels, collects NIR spectra, and sorts kernels. Commercial versions of our system are being built through a CRADA with Perten Instruments, Springfield, IL (CRIS No 5430-44000-009D). This system will allow measurement and sorting of quality factors such as bunted kernels, protein, moisture, scab damage, and color class at grain elevators, thus allowing segregation at the first point of sale and it will also provide breeders with a means to sort kernels with desirable traits from samples when developing new cultivars. Aflatoxin and fumonisin are carcinogens found in corn, and rapid detection means are needed to insure a safe food and feed supply. In cooperation with scientists in Peoria, IL, we studied the use of near infrared spectroscopy to detect whole corn kernels contaminated with these toxins and showed we can detect single kernels contaminated with low levels of toxin using reflectance or transmittance spectroscopy. In 2002, work began to test a high speed sorting machine for removal of contaminated kernels. Results showed that as much as 80% of aflatoxin and fumonisin in commercially grown and harvested corn could be removed by one pass through the sorting machine. This research could result in rapid economical method for segregating all individual kernels before they are used for food or feed purposes, potentially saving the corn industry millions of dollars. At the request of FGIS and in cooperation with KSU and FOSS, we are developing calibrations to detect vitreousness of wheat using machine vision system manufactured by Foss (CRIS No. 5430-44000-014-07T and 08S). We have developed calibrations using samples that represent all vitreous defect classes. In 2002, we began work to calibrate a high-speed inspection system to measure wheat vitreousness. This system will reduce inspector error and labor in detecting vitreousness, allow quality and price to be more accurately accessed, and allow more precise segregation of wheat in order to improve end use quality. The presence of Karnal bunt is a threat to all US wheat production, and could devastate our export wheat markets and US agriculture economy. We showed in 1997 that we could detect bunted kernels using optical sensors. Thus, at APHIS request, we cooperated with APHIS, several state labs, and Satake, USA to apply high speed sorting technology to rapidly screen samples for the presence of bunted kernels. We showed that this technology can remove 100% of bunted kernels from samples, which will reduce inspector error and significantly reduce sample processing time. These results have changed the procedure for inspecting samples for bunted kernels, and the reduction in errors and time will greatly improve our ability to detect and control additional outbreaks, and help insure the quality of our grain and preserve our export markets. At industry request, we developed wheat protein and insect detection calibrations in 2001 for a single kernel quality measurement instrument (SKCS 4170) developed through a CRADA with Perten Instruments in 1998. The calibrations included multiple classes and completed the CRADA work plan. These calibrations are being used by industry laboratories that have purchased the single kernel instrument. The wheat industry uses this information to purchase wheat for mills to optimize flour quality, and to segregate insect infested wheat to minimize insect fragments in flour. The Kansas Wheat Commission requested that ARS develop simple, rapid, safe, and objective procedures for determining red and white wheat color class. We optimized procedures that utilize soaking kernels in sodium hydroxide, resulting in a rapid change in seed color that makes color classification simple and accurate. This color classification test is now commercially marketed and used by the wheat industry and inspectors to determine wheat color class. This simple procedure can help promote the adoption and segregation of white wheat and help expand our white wheat export markets. In response to industry requests, an automated system for measuring single kernel hardness (SKCS 4100) was developed and transferred to industry. Approximately 100 of these units are used throughout the world. This system was recently modified to incorporate NIR measurements on single kernels. This instrument is now commercially produced (SKCS 4170) and can measure attributes such as protein, fungal damage, internal insects, and vitreousness. The NIR spectroscopy procedures developed for determining single kernel attributes were found to apply to determining characteristics of single insects and other commodities. Thus, we applied NIR spectroscopy to detecting insect parasitoids, insect species, insect age grading, and fig quality in cooperation with Drs. Jim Throne and Jim Baker (Biological Research Unit, ARS USDA, Manhattan, KS), Dr. Alberto Broce (Dept. Entomology, KSU), Dr. Bob Wirtz (CDC, Atlanta, GA), and Dr. Chuck Burks (Horticultural Crops Research Laboratory, Fresno, CA). Results showed we could detect parasitized weevils and flies, fly and mosquito age, stored grain insect species, and fig quality using NIR spectroscopy. This information can be used to develop control strategies for various pest insects and to automate fig grading. 6. What science and/or technologies have been transferred and to whom? When is the science and/or technology likely to become available to the end- user (industry, farmer, other scientists)? What are the constraints, if known, to the adoption and durability of the technology products? We continue to reach additional customers with our single kernel sorting technology. Or bench-top automated single NIR system has been used by breeders in several states to study the variability within their cultivars. This information is useful as they develop cultivars with specific end-use traits. Our high-speed sorting technology is being used by breeders in several states in the development of white wheat. Most white wheat grown in this region has been purified through our system. We are also working with millet, sorghum, and corn breeders and processors to remove unwanted kernels from bulk lots. 7. List your most important publications in the popular press and presentations to organizations and articles written about your work. Dowell, F.E. Predicting Wheat Functionality and End-Use Quality. Presented to the GIPSA Advisory Committee. Kansas City, MO. May, 2004. Dowell, F.E. and M.E. Casada. Engineering solutions for insect pest management decision-making in grain, including improved handling of beneficial insects during shipment. Presented to the International Organization for Biological Control of Insects, Montpellier, France. September, 2003. Dowell, F.E., J.E. Throne, and J.E. Baker. Detecting Insect Characteristics Using Near-Infrared Spectroscopy. Presented to the Centers for Disease Control. Atlanta, GA. October, 2004. Dowell, F.E.. Detecting Insect Characteristics Using Near-Infrared Spectroscopy. Presented to the Atomic Energy Commission. Vienna, Austria. January, 2004.

Impacts
(N/A)

Publications

Cole, T.J., Ram, M.S., Dowell, F.E., Omwega, C.O., Overholt, W.A., Ramaswamy, S.B. 2003. Near-infrared spectroscopic method to identify cotesia flavipes and c. sesamiae (hymenoptera: braconidae).. Annals of the Entomological Society of America. 2003. 96(6):865-869.
MAGHIRANG, E.B., DOWELL, F.E., BAKER, J.E., THRONE, J.E. AUTOMATED DETECTION OF SINGLE WHEAT KERNELS CONTAINING LIVE OR DEAD INSECTS USING NEAR-INFRARED REFLECTANCE SPECTROSCOPY. TRANSACTIONS OF THE AMERICAN SOCIETY OF AGRICULTURAL ENGINEERS. 2003. v. 46(4). p. 1277-1282.
Pasikatan, M.C., Dowell, F.E. 2004. High-speed segregation of high-and low- protein single wheat seeds. Cereal Chemistry. 2004. 81(1): 145-150.
Ram, M.S., Seitz, L.M., Dowell, F.E. 2004. Natural fluorescence of red and white wheat kernals. Cereal Chemistry. 2004. 81(2):244-248.
WANG, D., DOWELL, F.E., RAM, M.S., SCHAPAUGH, W.T. CLASSIFICATION OF FUNGAL-DAMAGED SOYBEAN SEEDS USING NEAR-INFRARED SPECTROSCOPY. INTERNATIONAL JOURNAL OF FOOD PROPERTIES. 2003. v. 6(0). p. 1-8.
Wang, N., Dowell, F.E., Zhang, N. 2003. Determining wheat vitreousness using image processing and a neural network. Transactions of the ASAE. 2003. 46(4):1143-1150
Xie, F., Dowell, F.E., Sun, X.S. 2004. Using visible and near-infrared reflectance spectroscopy and differential scanning calorimetry to study starch, protein, and temperature effects on bread staling. Cereal Chemistry. 81(2):249-254
Cetin, A., Pearson, T.C., Tewfik, A.H. 2004. Classification of closed- and open-shell pistachio nuts using voice-recognition technology. Transactions of the ASAE. 2004. 47(2):659-664.
Pearson, T.C., Wicklow, D.T., Pasikatan, M.C. 2004. Reduction of aflatoxin and fumonisin contamination in yellow corn by high-speed bi-chromatic sorting. Cereal Chemistry. 2004. 81(4):490-498.
Pearson, T.C., Brabec, D.L. 2003. Automated detection of internal insect infestations in whole wheat kernels using a perten skcs 4100. Applied Engineering in Agriculture. 2003. 19(6):727-733.
Perez Mendoza, J., Throne, J.E., Dowell, F.E., Baker, J.E. 2004. Chronological age-grading of three species of stored-product beetles using near-infrared spectroscopy. Journal of Economic Entomology. 97(3):1159- 1167.

Progress 10/01/02 to 09/30/03

Outputs
1. What major problem or issue is being resolved and how are you resolving it? The US is a major producer and exporter of wheat and other cereal grains. However, our production and marketing is being threatened by serious food safety and quality issues such as Karnal bunt and vomitoxin in wheat, and aflatoxin and fumonisin in corn. We are also losing export markets to other countries that are producing higher quality grain at lower costs. We must develop rapid detection technologies to insure the quality of our grain. In addition, we need rapid detection methods to address biosecurity concerns such as the introduction of pathogens into our grain supply system. The objective of this research is to develop sensors and instrumentation for objective grading, online measurement, and enduse property assessment of single kernels or bulk grain samples. Specific issues being addressed include: rapid assessment of physical properties such as kernel size and weight; visible and nearinfrared (NIR) measurements of single kernel attributes such as fungal damage or internal insects; machine vision assessment of kernel characteristics; and use of single kernel characterization system (SKCS) data for commercial milling. 2. How serious is the problem? Why does it matter? The production and marketing of grain are major components of the U.S. agricultural economy. Improved utilization and market efficiencies with objective quality, functionality and grain grade assessments will increase food wholesomeness, safety, and market competitiveness. For example, accurate, rapid detection of attributes will assist in: marketing or segregating genetically modified grain; detecting food safety concerns such as aflatoxin or fumonisin in corn; detecting acts of bioterrorism aimed at our food supply; or detecting attributes that can lead to quarantine of commodities such as Karnal bunt in wheat. This information is particularly useful in evaluating grain prior to purchase or trade in market channels. Single kernel assessments are needed to detect defects that may be present in only a small percentage of kernels or to detect mixtures of contrasting quality characteristics. New technology developed through this research will provide FGIS with several options for providing additional objective quality assessments of grain along with official grade services and thereby improve their services and operating efficiencies. The objective assessments of grain quality are useful to producers, breeders, growers, grain handlers, marketers, millers, bakers, and government agencies such as the Extension Service, FGIS, FSIS, APHIS and OSHA. Accurate detection of genetically modified grain and accurate measurement of other grain quality attributes will help preserve our export markets, which contribute over one billion dollars to the US economy. 3. How does it relate to the National Program(s) and National Program Component(s) to which it has been assigned? This research supports the Quality and Utilization of Agricultural Products National Program #306 within the Crop Production, Product Value and Safety research category through development of postharvest engineering technology for grain quality assessment, maintenance and functional utilization. This research will assist buyers and sellers of wheat in developing, marketing and utilizing wheat at its highest functional performance level. The research is expected to advance the application and use of new, rapid and objective assessments of grain quality in the market channel. This research also supports the Food Safety National Program (#108) within the Animal Production, Product Value and Safety research category by addressing such food safety issues as detecting deoxynivalenol (DON) in wheat and aflatoxin and fumonisin in corn. Other programs addressed through cooperative research include: The Crop Protection and Quarantine National Program (#304) by detecting internal insects in wheat, classifying insect species with NIR spectroscopy, and detecting Karnal bunt in wheat; and The Methyl Bromide Alternatives National Program (#308) by developing new and improved pest control technologies by using NIR spectroscopy to detect parasitized weevils and flies. 4. What were the most significant accomplishments this past year? A. Single Most Significant Accomplishment during FY 2003 Internal insect infestation of wheat kernels degrades quality, costs the wheat industry millions of dollars in lost domestic and export markets, and is one of the most difficult defects to detect. We found that the data generated by the Perten SKCS 4100, an instrument developed by our Engineering Research Unit and used by many grain millers and handlers, can be processed for detecting live and dead internal insects in whole wheat kernels. This technology provides the wheat milling and handing industries, as well as FGIS, a rapid and automated method for detecting internal insects in wheat kernels. The software has been transferred to a commercial miller for field testing. Other grain processors throughout the country have expressed interest in this technology. B. Other Significant Accomplishment(s), if any Wheat hardness is a primary quality trait that relates wheat to its milling properties and end-use quality. The current standard measurement techniques for wheat hardness are destructive, i.e., they require grinding or crushing of wheat samples. There is a need for a measurement technique, such as in breeding programs, that is non-destructive, rapid, accurate, and accommodates small sample sizes. We developed a technique using a single kernel near-infrared instrument developed within the Engineering Research Unit that can measure hardness and sort single kernels automatically at a rate of 1 kernel per second. Wheat breeding programs are expected to benefit from this technique considering its non- destructive feature, small sample size requirement, accuracy, and rapidity. Wheat breeders currently do not have a non-destructive method to rapidly screen single wheat kernels for protein content. High protein content is preferred in wheat products such as pasta while low protein content is desirable for cakes and cookies. Wheat with higher protein commands higher price in export markets. Our Engineering Research Unit conducted cooperative research with Satake using their high-volume color/NIR sorter for sorting single kernels based on protein content. The sorter is now used by breeders to shift early generation wheat populations toward a target protein level, thus reducing the time required to develop varieties with specific quality traits. A high-speed color sorter has the potential to help wheat breeders purify their white wheat breeding lines and to help white wheat exporters meet purity requirements of end users. The Engineering Research Unit evaluated a Satake color sorter in cooperation with the Kansas Wheat Commission for removing red wheat from white wheat. The sorter was able to remove red wheat from white at a potential speed of 300 bu/hr. We currently us this technology to purify white wheat samples for breeders in several states as the US develops white wheat varieties to take advantage of significant export markets. The system significantly reduces the time required to develop new white wheat varieties, and improves the quality of new varieties as they are released. Red and white wheat need to be kept segregated because mixtures of these wheats are discounted, and some have different end uses. Identification of wheat color class is not straightforward, and currently, there is interest in characterizing red and white wheat using spectroscopy and chemical tests. The Engineering Research Unit observed that all varieties of red and white wheat exhibited natural fluorescence under ultra-violet light. From a study of 90 cultivars we found that fluorescence emission spectra of red wheat kernels are different from those of white wheat. This information may aid development of a simple, rapid wheat color class identification process easily without the use of chemicals. Bread staling is a complex process that occurs during bread storage, and the cause of staling is not understood. Understanding the staling phenomena will help us develop methods to reduce staling. Starch, protein, and temperature effects on bread staling were investigated by the Engineering Research Unit in cooperation with KSU using visible and near-infrared spectroscopy and differential scanning calorimetry. Results show that starch, protein, and moisture all contributed to the bread staling process. However, bread staling was mainly due to amylopectin retrogradation. Protein retarded bread staling, but not as much as temperature. The results of this study could lead to solutions to reduce bread staling that will bring economic benefit to bakers and consumers. C. Significant accomplishments/activities that support special target populations D. Progress Report 5. Describe the major accomplishments over the life of the project, including their predicted or actual impact. The grain industry requested a low cost single kernel quality measurement and sorting system that could be used at field locations and by breeders. Thus, we developed a system in cooperation with KSU Biological and Agricultural Engineering Department that singulates kernels, collects NIR spectra, and sorts kernels. Commercial versions of our system are being built through a CRADA with Perten Instruments, Springfield, IL (CRIS No 5430-44000-009D). This system will allow measurement and sorting of quality factors such as bunted kernels, protein, moisture, scab damage, and color class at grain elevators, thus allowing segregation at the first point of sale and it will also provide breeders with a means to sort kernels with desirable traits from samples when developing new cultivars. Aflatoxin and fumonisin are carcinogens found in corn, and rapid detection means are needed to insure a safe food and feed supply. In cooperation with scientists in Peoria, IL, we studied the use of nearinfrared spectroscopy to detect whole corn kernels contaminated with these toxins and showed we can detect single kernels contaminated with low levels of toxin using reflectance or transmittance spectroscopy. In 2002, work began to test a high speed sorting machine for removal of contaminated kernels. Results showed that as much as 80% of aflatoxin and fumonisin in commercially grown and harvested corn could be removed by one pass through the sorting machine. This research could result in rapid economical method for segregating all individual kernels before they are used for food or feed purposes, potentially saving the corn industry millions of dollars. At the request of FGIS and in cooperation with KSU and FOSS, we are developing calibrations to detect vitreousness of wheat using machine vision system manufactured by Foss (CRIS No. 5430-44000-014-07T and 08S). We have developed calibrations using samples that represent all vitreous defect classes. In 2002, we began work to calibrate a high-speed inspection system to measure wheat vitreousness. This system will reduce inspector error and labor in detecting vitreousness, allow quality and price to be more accurately accessed, and allow more precise segregation of wheat in order to improve enduse quality. Current methods for measuring bread staling are not very accurate, are destructive, and give no insights to the underlying physical-chemical phenomena that occur during staling. In cooperation with the KSU Grain Science Department, we found that visible and near infrared spectroscopy accurately correlates with bread staling and can provide information about when physical and chemical transformations occur that lead to staling. It was found that NIR spectroscopy can explain more than twice the amount of variation in bread staling than current methods can. This technology will provide the baking industry with new, more accurate, methods for measuring bread staling and help researchers further understand the bread staling process. The presence of Karnal bunt is a threat to all US wheat production, and could devastate our export wheat markets and US agriculture economy. We showed in 1997 that we could detect bunted kernels using optical sensors. Thus, at APHIS request, we cooperated with APHIS, several state labs, and Satake, USA to apply highspeed sorting technology to rapidly screen samples for the presence of bunted kernels. We showed that this technology can remove 100% of bunted kernels from samples, which will reduce inspector error and significantly reduce sample processing time. These results have changed the procedure for inspecting samples for bunted kernels, and the reduction in errors and time will greatly improve our ability to detect and control additional outbreaks, and help insure the quality of our grain and preserve our export markets. At industry request, we developed wheat protein and insect detection calibrations in 2001 for a single kernel quality measurement instrument (SKCS 4170) developed through a CRADA with Perten Instruments in 1998. The calibrations included multiple classes and completed the CRADA work plan. These calibrations are being used by industry laboratories that have purchased the single kernel instrument. The wheat industry uses this information to purchase wheat for mills to optimize flour quality, and to segregate insect infested wheat to minimize insect fragments in flour. The Kansas Wheat Commission requested that ARS develop simple, rapid, safe, and objective procedures for determining red and white wheat color class. We optimized procedures that utilize soaking kernels in sodium hydroxide, resulting in a rapid change in seed color that makes color classification simple and accurate. This color classification test is now commercially marketed and used by the wheat industry and inspectors to determine wheat color class. This simple procedure can help promote the adoption and segregation of white wheat and help expand our white wheat export markets. There is industry interest in increasing sorghum seed size, however, no assessment of increased size on feed components or digestibility has been made. In cooperation with KSU researchers, we investigated the use of nearinfrared spectroscopy (NIRS) to measure these attributes. Crude protein was measurable by NIRS, with ground samples giving better results than whole seeds. These results may provide the sorghum industry with a tool for rapidly screening sorghum for desirable attributes. In response to industry requests, an automated system for measuring single kernel hardness (SKCS 4100) was developed and transferred to industry. Approximately 100 of these units are used throughout the world. This system was recently modified to incorporate NIR measurements on single kernels. This instrument is now commercially produced (SKCS 4170) and can measure attributes such as protein, fungal damage, internal insects, and vitreousness. The NIR spectroscopy procedures developed for determining single kernel attributes were found to apply to determining characteristics of single insects and other commodities. Thus, we applied NIR spectroscopy to detecting insect parasitoids, insect species, insect agegrading, and fig quality in cooperation with Drs. Jim Throne and Jim Baker (Biological Research Unit, ARS USDA, Manhattan, KS), Dr. Alberto Broce (Dept. Entomology, KSU), Dr. Bob Wirtz (CDC, Atlanta, GA), and Dr. Chuck Burks (Horticultural Crops Research Laboratory, Fresno, CA). Results showed we could detect parasitized weevils and flies, fly and mosquito age, stored grain insect species, and fig quality using NIR spectroscopy. This information can be used to develop control strategies for various pest insects and to automate fig grading. 6. What do you expect to accomplish, year by year, over the next 3 years? This project plan has been approved for a new CRIS 5430-44000-014-00D. Here is the plan of work. In FY 2004, we plan to complete development of a low cost NIR system for detecting single kernel attributes and sorting based on these attributes. Investigate other single kernel quality measurements such as protein and starch quality, and detection of transgenic attributes will be continued. Continue our investigation of physical and spectral properties of corn contaminated with aflatoxin and develop rapid methods of sorting contaminated corn. Work with researchers at the University of Florida to develop NIRS methods to rapidly and non-destructively identify mutant kernels. At the request of GIPSA, we will continue image acquisition, calibration and testing of the a high speed image inspection system to determine performance and potential as an aid to grain inspectors which will discriminate dark hard vitreous (DHV) kernels from non DHV wheat kernels. We will also develop the calibrations for the discrimination of hard vitreous and amber colored (HVAC) kernels from non HVAC wheat kernels. Cooperation with industry and other researchers to investigate the potential of the Perten single kernel NIRS and SKCS 4100 to measure insect characteristics and the quality of other commodities will be continued. We plan to integrate a machine vision system into the single kernel system. In FY 2005, we plan to develop a high speed, low cost system for detecting single kernel attributes. We plan to study acoustic properties of wheat for detection of insect damage and other characteristics. We also will investigate technology to detect acts of bio terrorism target at grain crops. In FY 2006, we plan to investigate biosensors and other non spectral sensors for rapidly measuring grain attributes. Sampling, human, and analytical errors associated with measuring grain attributes will be examined. We plan to continue collaborative investigations of the potential of SKCS measurements to predict millability of wheat, investigate variables that influence system physical measurements and expand the application of the system to physical measurements of other grains. 7. What science and/or technologies have been transferred and to whom? When is the science and/or technology likely to become available to the end- user (industry, farmer, other scientists)? What are the constraints, if known, to the adoption and durability of the technology products? A commercial prototype of a lowcost NIRS kernel singulator/sorter system was developed through a CRADA. We transferred software that detects live and dead internal insects using the single kernel characterization system to a commercial miller and to the system manufacturer. We continued with a CRADA with a company that includes breeders and processors to develop a single kernel quality measurement system for corn and soybeans. We initiated a trust agreement to develop imaging applications for wheat using a high speed imaging system. We renewed a memorandum of understanding with a high speed optical sorting machine manufacturer to developed applications for the grain industry. We continued a trust agreement with a wheat commission to investigate technology to purify white wheat. We initiated a MOU with a company to investigate the potential of Fourier Transform spectroscopy for measuring grain attributes. 8. List your most important publications in the popular press and presentations to organizations and articles written about your work. (NOTE: This does not replace your peer-reviewed publications listed below). Cardwell, K, Dowell, F.E., Mitchell, J., Riemenschneider, R., Spaide, R., Vocke, G. Phytosanitary vs regulatory risk of losses due to wheat Karnal bunt in the U.S.A. Proceedings of the International Congress of Plant Pathology, New Zealand. 2002. Paulsen, M.R., Mbuvi, S.W., Haken, A.E., Ye, B., Stewart, R.K. Extractable starch as a quality measurement of dried corn. Applied Engineering in Agriculture. 2003. v. 19(2). P. 211-217. Paulsen, M.R., Pordesimo, L.O., Singh, M., Mbuvi, S.W., Ye, B. Maize starch yield calibrations with near-infrared reflectance. Biosystems Engineering. Available from: www.sciencedirect.com 6 -11-03 [2003] Pearson, T.P., Brabec, D.L. Automated detection of insect infestations in single whole wheat kernels. American Association of Cereal Chemists. 2003. Abstract No. 25. Pearson, T.P., Brabec, D.L. High speed inspection systems for agricultural commodities. American Association of Cereal Chemists. 2002. Abstract No. 17. Pearson, T.C., Wicklow, D., Pasikatan, M.C. Reduction of aflatoxin and fumonisin contamination in yellow corn by high-speed bi-chromatic sorting. North American Dry Millers Association. 2003. Abstract p 22. Singh, M., Paulsen, M.R., Tian, L., Yao, H. Site-specific study of corn protein, oil, and extractable starch variability using NIT spectroscopy. 2002. American Society for Agricultural Engineers. Paper No. 02-1111.

Impacts
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Publications

Bramble, T., Herrman, T.J., Loughin, T. Dowell, F.E. Single kernel protein variance structure in commericial fields in Western Kansas. Crop Science. 2002. v. 42(5). p. 1488-1492.
Delwiche, S.R., Dowell, F.E. NIR-analyise von einzelnen weizenkornern. Getreide Mehl und Brot. 2002. v. 56(3). p. 141-146.
Delwiche, S.R., Dowell, F.E. Single kernel wheat NIR analysis. Proceedings of the 2nd International Wheat Conference, Manhattan, KS. 2001. p. 155-166.
Dowell, F.E., Maghirang, E.B. Accuracy and feasibility of measuring characteristics of single kernels using near-infrared spectroscopy. Proceedings of the ICC Converence 2002 "Novel Raw Materials, Technologies, and Products--New Challenge for Quality Control," Budapest, Hungary. 2002. p. 313-320.
Hicks, C., Tuinstra, M.R., Pedersen, J., Dowell, F.E., Kofoid, K. 2002. Genetic analysis of feed quality and seed weight of sorghum inbred lines and hybrids using analytical methods and nirs. Euphytica. 2002. 127(1):31- 40.
Maghirang, E.B., Dowell, F.E. 2003. Hardness measurement of bulk wheat by single-kernel visible and near-infrared reflectance spectroscopy . Cereal Chemistry. 80(3): 316-322.
Pasikatan, M.C. Development of first-break grinding models and a near- infrared reflectance technique for size estimation of first-break grinding fractions. PhD dissertation. 2000. Kansas State University.
Pasikatan, M.C. Development of first-break grinding models and a near- infrared reflectance technique for size estimation of first-break grinding fractions. PhD dissertation. 2000. Kansas State University.
Pasikatan, M.C., Steele, J. L., Haque E., Spillman, C.K., Milliken, G.A. Evaluation of a near-infrared reflectance spectrometer as a granulation sensor for first-break ground wheat size: Studies with hard red winter wheats. Cereal Chemistry. 2002. v. 79(1). p. 92-97.
Pasikatan, M.C., Haque, E., Steele, J.L., Spillman, C.K., Milliken, G.A. Evaluation of a near-infrared reflectance spectrometer as a granulation sensor for first-break ground wheat: Studies with six wheat classes. Cereal Chemistry. 2001. v. 78(6). p. 730-736.
Wang, D., Dowell, F.E., Ram, M.S., Schapaugh, W.T. Classification of damaged soybean seeds using near-infrared spectroscopy. Transactions of the American Society of Agricultural Engineers. 2003. v. 45. p. 1943-1948.
Wang, N., Dowell, F.E., Zhang, N. Determining wheat vitreousness using image processing and a neural network. Proceedings of the International American Society of Agricultural Engineers meeting in Chicago. 2002. ASAE Paper No. 026089.
Xie, F., Dowell, F.E., Xiuzhi, S.S. 2003. Comparison of near-infrared reflectance spectroscopy and texture analysis for prediting wheat bread staling. Cereal Chemistry. 80(1):25-29
Pasikatan, M.C., Haque, E., Spillman, C.K., Steele, J.A., Milliken, G.A. Granulation sensing of first-break ground wheat using a near-infrared reflectance spectrometer. Proceedings at the 107th Annual Technical Conference and Trade Show for the Association of Operative Millers, Pittsburg, PA. 2003. p. 2-20.
Pasikatan, M.C., Haque, E., Spillman, C.K., Steele, J.L., Milliken, G.A. Granulation sensing of first-break ground wheat using a near-infrared reflectance spectrometer: studies with soft red winter wheats. Journal of the Science of Food and Agriculture. 2003. v. 83(3). p. 151-157.
Pasikatan, M.C., Milliken, G.A., Steele, J. L., Haque E., Spillman, C.K. Modeling the energy requirements of first-break grinding. Transactions of the American Society of Agricultural Engineers. 2001. v. 44(6). p. 1737- 1744.
Pasikatan, M.C., Milliken, G.A., Steele, J.L., Spillman, C.K., Haque, E. Modeling the size properties of first-break ground wheat. Transactions of American Society of Agricultural Engineers. 2001. v. 44(6). p. 1727-1735.
Pasikatan, M.C., Steele, J.L., Spillman, C.K., Haque, E. Near infrared reflectance spectroscopy for online particle size analysis of powders and ground materials. Journal of Near-Infrared Spectroscopy. 2001. v. 9(3). p. 153-164.
Pearson, T.C., Young, R. Automated sorting of almonds with embedded shells by laser transmittance imaging. Applied Engineering in Agriculture. 2002. v. 18(5). p. 637-641.
Pearson, T.C., Edwards, R.H., Mossman, A.P., Wood, D.F., Yu, P.C., Miller, E.L. Insect egg counting on mass rearing oviposition pads by image analysis. Applied Engineering in Agriculture. 2002. v. 18(1). p. 129-135.
Perez-Mendoza, J., Throne, J.E., Dowell, F.E., Baker, J.E. Detection of insect fragments in wheat flour by diffuser reflectance near-infrared spectroscopy. Journal of Stored Product Research. 2003. v. 39. p. 305-312.
Ram, M.S., Dowell, F.E., Seitz, L. FT-Raman spectra of unsoaked and NaOH soaked wheat kernels, bran and ferulic acid. Cereal Chemistry. 2003. v. 80(2). p. 188-192.
Ram. M.S., Dowell, F.E., Seitz, L. Invisible coatings for wheat kernels. Cereal Chemistry. 2002. v. 79(6). p. 857-860.
Throne, J.E., Dowell, F.E., Perez-Mendoza, J., Baker, J.E. Entomological applications of near-infrared spectroscopy. Proceedings of Stored Products Protection International Working Conference, England. 2002.