1a. Objectives (from AD-416):
Our overall objective is to maintain and improve grain quality and international competitiveness through the application of engineering principles. Most of our work concentrates on measuring properties of single kernels so that they can be segregated or the distribution of properties in a sample can be ascertained, versus measuring the average quality of a bulk sample. In general, the project will include the development of instruments to improve rapid (up to 500 kernels/s) measurement of grain quality at receiving stations, the development of non-destructive and rapid (up to 500 kernels/s) single-kernel sorting systems to improve post-harvest grain quality and similar systems to help grain breeders rapidly select specific traits for improved lines, and improve grain-storage and handling systems. Specific objectives are: 1. Develop sensors and methods to rapidly and accurately quantify attributes such as protein composition, starch composition, end-use quality, toxins, and micronutrients. 1.A. Develop or apply spectroscopic technologies that offer significant improvements over current technologies used to measure traits of single kernels and other biological materials. 1.B. Adapt a previously developed conductance mill for detection of live-insect infestations in wheat in other grains such as corn, rice, barley, and oats, and to dry beans, such as pinto and navy beans. 1.C. Develop procedures for rapid estimation of insect fragments in milled flour from minimally processed whole wheat. 2. Develop rapid single-kernel sorting systems to accurately remove defects such as fungal or insect-damaged grain and to isolate beneficial traits such as white wheat. 2.A. Develop high-speed, low-cost, image-based sorting systems for a variety of grains and legumes. 2.B. Develop Near-infrared spectroscopy (NIRS) -based, single-seed sorting systems for large grains and legumes. 2.C. Investigate applications of single-kernel NIRS technology to select kernels with specific traits. 3. Develop instrumentation, sensors, and systems to improve monitoring, and management of grain storage. 3.A. Develop traceability and identity-preservation techniques for grain handling. 3.B. Develop new stored-grain packing factors for the common grains in trade with known confidence intervals for a complete range of field conditions. 3.C. Investigate insect-pest densities and commingling of insects in grain that causes the spread of an infestation from bucket elevator boots. 3.D. Develop monitoring systems for grain-storage quality management. 3.E. Develop improved, environmentally-friendly insect-pest control methods for stored grain. While the objectives of this project include pre-harvest (seeds) and post-harvest handling of grain, the work is interconnected in that the overall goal is to improve the quality of grain produced in the United States. Instruments developed to assess grain quality will be used to study how grain quality might change during storage and handling. An instrument previously developed by this group to detect insect-infested grain will be used to study the spread of insect infestations and the storability of grain based on insect population levels.
1b. Approach (from AD-416):
U.S. farmers grow over 15 billion bushels of corn, wheat, soybeans, and other grains annually to supply the nation and world with food, animal feed, and biofuels. A significant amount of this grain may be stored for a year or more before it is used or processed. Our goal is to improve U.S. grain quality and international competitiveness through the application of engineering principles, specifically to the areas of rapid (inspection results from at least 60 individual kernels per minute) quality measurement and in maintaining quality during storage. Much of our research concentrates on measuring the distribution of quality within samples, and on detecting traits that are present at very low levels. We propose to develop instruments to rapidly (up to 500 kernels/s) measure quality traits for inspection at the first point of grain delivery, for breeders in selecting traits for new lines, and for processors prior to grain buying or processing. We also propose to develop chemical-free technology to control insects and maintain quality during handing and storage. This research will lead to higher profits for the agriculture sector, higher-quality foods reaching consumers, and more food available for a growing world population.
3. Progress Report:
Under Objective 1, a method that was previously developed in this project for detection wheat kernels infested with live insect larvae was modified and enhanced to work at higher moisture contents (14 to 15%). Testing of this method is currently underway at a large rice processor, grain handler, and in Europe. Tests were also performed for other grains such as corn, sorghum, barley, and dry beans and the method was shown to be feasible with these commodities. Also, to detect insects that infest grain that were killed during fumigation and encapsulated inside grains, a rotary grain breakage tester was modified so that about 90% of wheat kernels that had been infested by insects break apart while only about 2% of the un-infested kernels are broken. The insect pieces can then be easily counted after sieving the grain. The counts of dead insects are highly correlated with insect fragments found in flour, which is regulated by the Food and Drug Administration. This method could provide a rapid and inexpensive method for estimating insect fragments that would occur when grain is milled. Under Objective 2, a new type of low cost sorting system has been developed and commercialized that is able to separate grain based on multi-spectral near infrared measurements. These measurements enable the system to separate grains based on properties such as protein content, fungal damage, and sprout damage. The system can inspect grains at rates of up to 25 kernels per second so the instrument will find uses in many breeding programs. Work was also performed to develop sorting methods for soybeans so that beans with high oil content could be segregated, leading to crops that will produce more oil. Soybean seeds sorted on the basis of oil and protein were planted in experimental plots and the progeny in some lines were shown to have significantly higher oil content. Under Objective 3, laboratory and field measurements of grain packing in storage bins continue. In laboratory tests, increasing dockage in wheat from 0% to 5% increased both the compressibility and variability in the data. This was because test weight decreased with dockage, as expected, and lower test weights produce greater compressibility. Over 150 upright grain storage bins, ranging from 12 to 105 ft diameter, have been measured so far and their packing factors evaluated. The software package was improved to provide a succinct output mode for showing estimates of packing for corn, hard red winter wheat, soft red winter wheat, soybeans, and grain sorghum. Research was also conducted to develop methods to adapt our research findings to improve food security by reducing storage losses in developing countries.
1. High speed automated multi-spectral sorting of grains. Many grains having desirable chemical constituents such as high protein content, or degraded properties such as fungal damaged or sprouting, cannot currently be segregated at high speeds. ARS researchers in Manhattan, Kansas have successfully developed a new type of electronic sorting machine that measures near infrared light at several different bands. The machine combines these measurements and can then use them to segregate kernels with high protein content or kernels that had started to sprout in the field. The instrument has been commercialized and is used by breeding programs to help produce high quality seed.
2. Automated color image based sorting of grains. Many types of defects found on grains, such as fungal infestation, cannot be detected and removed from food, feed or seed process streams. ARS researchers at Manhattan, KS successfully have developed a new type of electronic sorting machine that can detect and separate many types of weed seeds, discolored seeds, and fungal infected seeds. This new capability has been adopted by producers of grass seed, flax seed, alfalfa seed, pulses, corn seed, soybean seed, and wheat seed. The sorter is able to separate seed on the basis of color, shape, and surface texture. This technology will improve quality of many crops by ensuring better seed that is free from weeds or other contamination, ensuring more uniform seeds, and the technology will help deliver safer foods by reducing fungal contaminated products.
3. Automated sorting to improve breeding lines. Prior to this work wheat breeders had to manually select kernels with specific traits mainly by visual observations. ARS researchers at Manhattan, KS, developed single kernel spectroscopic methods to rapidly and nondestructively select visible traits such as color class, and intrinsic traits such as hardness, protein content, starch content, or disease resistance. As a result, breeders can quickly incorporate improved traits in new breeding lines. Impact is evident through the recent release of new wheat cultivars such as the hard white wheat “Antero” in Colorado, the amylose-free wheat “Mattern” in Nebraska, the hard white wheat “Guymon” and the hard red winter wheat “OK Bullet” in Oklahoma.
Pearson, T.C., Moore, D., Pearson, J. 2012. A machine vision system for high speed sorting of small spots on grains. Journal of Food Measurement & Characterization. 6:27-34. DOI: 10.1007/s11694-012-9130-3.