D. L. Brabec

Development of a single-kernel wheat characterization system

A single-kernel wheat crushing device was developed to determine crush force, moisture, and size characteristics at a rate of approximately 180 kernels/min. A procedure for determining hardness of single kernels was developed with corrections for the effects of kernel moisture and size on the crush force profile. Single-kernel moisture measurement comparisons with bulk oven moisture measurements were satisfactory. Average kernel size measurements were highly correlated with average kernel weight, although a random machine interaction with single kernel size measurement was noted. Six prototypes of the rotor-crescent system were assembled for further evaluation. Tests to determine the system’s potential for wheat classification and inclusion in the official grain inspection process are under way.

High-speed optical sorting of soft wheat for reduction of deoxynivalenol

Fusarium head blight (FHB) is a fungal disease that affects small cereal grains, such as wheat and barley, and is becoming more prevalent throughout much of the worlds temperate climates. The disease poses a health risk to humans and livestock because of the associated production of the mycotoxin deoxynivalenol (DON or vomitoxin) by the causal organism, Fusarium graminearum. A study was undertaken to examine the efficiency of high-speed, optical sorting of intact wheat (Triticum aestivum) kernels for reduction of DON concentration. Soft red winter (n = 32) and soft white (n = 3) wheat samples, known to have elevated levels of FHB, were obtained from commercial mills throughout the eastern United States. An additional seven samples of wheat from the discard piles of in-mill cleaners were also studied. Fusarium-damaged wheat, cleaned of nonkernels and foreign material ( ~4.5 kg/sample, DON range = 0.6 to 20 mg/kg), was fed into a commercial high-speed bichromatic sorter operating at a throughput of 0.33 kg/(channel-min) and a kernel rejection rate of 10%. A wavelength filter pair combination of 675 and 1,480 nm was selected for sorting, based on prior research. Visual measurements of the proportion of Fusarium-damaged kernels were collected on incoming and sorted seed (separate analyses of accepted and rejected portions), as were measurements of DON concentration. Results indicated that the fraction of DON contaminant level in the sorted wheat to that in the unsorted wheat ranged from 18 to 112%, with an average of 51%. Nine of the 35 regular samples and all seven of the discard pile samples underwent a second sort, with five from this second set undergoing a third sort. Multiple sorting was effective in producing wheat whose DON concentration was between 16 and 69% of its original, unsorted value.

AUTOMATED DETECTION OF INTERNAL INSECT INFESTATIONS IN WHOLE WHEAT KERNELS USING A PERTEN SKCS 4100

The wheat industry is in need of an automated, economical, and rapid means of detecting whole wheat kernels with internal insect infestation. The feasibility of the Perten Single Kernel Characterization System (SKCS) to detect internal insect infestations was studied. The SKCS monitors compression force and electrical conductance as individual kernels are crushed. Samples of hard red winter (HRW) wheat and soft red winter (SRW) wheat infested with rice weevil [Sitophilus oryzae (L.)] and lesser grain borer [Rhyzopertha dominica (F.)] were run through the SKCS and the conductance/force signals saved for post-run processing. Algorithms were developed to detect kernels with live internal insects, kernels with dead internal insects, and kernels from which insects have emerged. The conductance signal was used to detect live infestations and the force signal for dead and emerged infestations. Live insect detection rates were 24.5% for small-sized larvae, 62.2% for medium-sized larvae, 87.5% for large-sized larvae, and 88.4% for pupae. The predicted, and observed, false positive (sound kernels classified as infested) rate was 0.01%. Dead insect detection rates were 60.7% for large-sized larvae, 65.1% for pupae, and 72.6% for kernels where the insect emerged. The false positive rate of the dead insect detection algorithm ranged from 0.2% for SRW to 0.5% for HRW. In all cases, insect detection rates were higher for rice weevil than lesser grain borer. The classification algorithms were robust for a wide range of moisture contents.

DETECTION OF WHEAT KERNELS WITH HIDDEN INSECT INFESTATIONS WITH AN ELECTRICALLY CONDUCTIVE ROLLER MILL

A laboratory roller mill system was modified to measure and analyze the electrical conductance of wheat as it was crushed. The electrical conductance of normal wheat kernels is normally low and fairly constant. In contrast, the electrical conductance of wheat kernels infested with live insects is substantially higher, depending on the size of the larvae and the resulting contact of the crushed larvae between the rolls. This instrument was designed to detect internal insect infestations in wheat that has a moisture content of 13.5% or less. The laboratory mill can test a kilogram (kg) of wheat in less than 2 min and 100 g in less than 10 s. Hard red winter and soft red winter wheat containing larvae of rice weevils and lesser grain borers of a variety of sizes were tested. On average, the instrument detected 8.3 out of 10 infested kernels per 100 g of wheat containing the larger sized insects (fourth instar or pupae). Kernels infested with medium-sized larvae (second or third instar) were detected at an average rate of 7.4 out of 10 infested kernels per 100 g of wheat. Finally, kernels infested with the small-sized larvae (first or second instar) were detected at a rate of 5.9 out of 10 infested kernels per 100 g of wheat. Under reasonable grain moisture contents there were no false positive errors, or noninfested kernels classified as insect infested. The cost of the mill is low and can lead to rapid and automated detection of infested wheat.

CHARACTERISTICS AND SORTING OF WHITE FOOD CORN CONTAMINATED WITH MYCOTOXINS

White corn grown in southern Texas was collected for characterization and evaluation of the feasibility of sorting kernels containing mycotoxins. Kernels were grouped into one of six symptom categories depending on the degree of visible discoloration and bright green-yellow fluorescence (BGYF) or bright orange fluorescence (BOF). Kernels visibly discolored (= 25% of their surface) and having BGYF contained over 57% of the aflatoxin. However, kernels approximately 50% discolored without BGYF contained over 35% of the aflatoxin. Over 33% of the fumonisin was found in kernels that were visibly discolored and had BOF. The remaining fumonisin was in asymptomatic kernels at low levels. Sorting tests for removing mycotoxin-contaminated kernels were performed using a dual wavelength high-speed commercial sorter. In one pass through the sorter, aflatoxin was reduced by an average of 46%, and fumonisin was reduced by 57% while removing 4% to 9% of the corn. Re-sorting accepted kernels a second time resulted in an 88% reduction in aflatoxin while removing approximately 13% of the corn. Approximately half of the aflatoxin missed by the optical sorter was found in larger kernels showing BGYF but no other symptoms, with the remaining aflatoxin in smaller kernels where the germ was damaged by insect feeding.

Camera Attachment for Automatic Measurement of Single-Wheat Kernel Size on a Perten SKCS 4100

A simple camera was attached to a Perten Single-Kernel Characterization System (SKCS) 4100 to measure single kernel morphology as they are fed through the SKCS. The camera and lighting were positioned above the SKCS weigher bucket. Each image of a wheat kernel was captured and processed in 15 to 60 ms. Image measurements included kernel area, length, and width.

Automated detection of hidden internal insect infestations in wheat kernels using electrical conductance

The wheat industry is in need of an automated, economical, and rapid means to detect whole wheat kernels internally infested with insects. The feasibility of the Perten Single-Kernel Characterization System (SKCS) to detect internal insect infestations was studied. The SKCS monitors compression force and electrical conductance as individual kernels are being crushed. Samples of hard red winter wheat (HRW) and soft red winter wheat (SRW) infested with rice weevil and lesser grain borer were run through the SKCS and the conductance/crush signals saved for post-run processing. It was found that a discontinuity is often present in the conductance signal of an insect-infested kernel. An algorithm was developed to classify kernels as infested, based on features of the conductance signal. Average classification accuracies for all wheat samples were 24.5% for small-sized larvae, 62.2% for medium-sized larvae, 87.5% for large-sized larvae, and 88.6% for pupae. There were no false positives (sound kernels classified as infested). The classification algorithm is robust for a wide range of moisture contents. Classification accuracy was somewhat better for kernels infested with rice weevils than for lesser grain borer, and classification accuracy was better for HRW than for SRW.

Detection of Lesser Grain Borer Larvae in Internally Infested Kernels of Brown Rice and Wheat Using an Electrically Conductive Roller Mill1,2

Modifications were made to a small laboratory mill to enable the detection of rice kernels internally infested by immature grain insects. The mill, which was originally designed for wheat, monitors electrical conductance through the grain and detects kernels that are infested with live insects based on abrupt changes in electrical conductance as the insects inside the kernels are crushed between the mill rolls. The mill was adapted to detect rice infested by immature lesser grain borers (LGB) by altering the gearing and reducing the gap between the two mill rolls to produce shear between the rolls. Samples of LGB infested long, medium, and short grain (dehulled) brown rice and hard red winter wheat were tested in both the modified and original mills. The detection rates for long grain brown rice kernels infested with large, medium, and small LGB larvae were 97, 83, and 42%, respectively, with the modified mill and 61, 22, and 4%, respectively, with the original mill. Similar detection rates were observed ...

Detection of Fragments from Internal Insects in Wheat Samples Using a Laboratory Entoleter

ABSTRACT A simple, rapid method that uses a small mechanical rotary device (entoleter) was developed for estimating insect fragment counts in flour caused by hidden, internal-feeding insects in whole grains of hard red winter and soft red winter wheat. Known counts of preemergent adults, pupae, and larvae of lesser grain borers and rice weevils were blended with 500 g samples of uninfested wheat. The entoleter impeller speed was adjusted based on grain hardness and moisture content to obtain about ≈98% intact and ≈2–2.5% broken kernels in an uninfested sample. The entoleter flung the wheat kernels against a surrounding steel ring. Approximately 70–90% of the insect-infested kernels, being weaker, released internal insect pieces upon impact. The broken kernels were sieved with number 10 and number 20 sieves to obtain large-sieved and small-sieved fractions, respectively. Insect pieces in sieved fractions were counted. The insect piece counts were correlated with the estimated flour fragments (R2 = 0.94). T...

EFFECTIVENESS OF A HIGH-PRESSURE WATER-FOGGING SYSTEM IN CONTROLLING DUST EMISSIONS AT GRAIN RECEIVING

Grain dust at the receiving area is a fire hazard, a health concern, and a sanitation problem and should be controlled. The effectiveness of a high-pressure water-fogging system in controlling grain dust emissions was evaluated with corn and wheat while spouting 2.1 m3 (60 bu) of grain into a test chamber. Dust/fog emissions and deposits along with entrained airflows were measured for four fog treatments, a control, and an air-blower treatment at each of two grain flow rates. The uncontrolled dust emissions varied with grain type and grain flow rate. Water-fog sprays, when applied across the top of the test chamber, redirected the airflow downstream of the spray nozzles and reduced dust emissions significantly. Dust reductions ranged from 60% to 84% for corn and from 35% to 73% for wheat. However, the sprays produced significant fog emissions and deposits in proportion to the liquid supply. At the highest spray rate (855 g/min), fog emission was 32 g/min (3.8%), and fog deposits ranged from 1.4 to 7.1 mg/cm2/min.