A technique to correct for sample thickness variations for use with IDAPS X-ray radiograph analysis

The Image Data Processing System (IDAPS) at the Marshall Space Flight Center is used to analyze radiographs of metal samples to qualitatively and quantitatively map compositional variations across the samples. When the X-ray radiographs are of samples having thickness variations, corrections must be made to accomplish compositional analysis. A correction technique is described for cylindrical samples and is applied to radiographs of SPAR Experiment 74-18. Uncorrected and corrected images are shown

Brahman Genetics Negatively Impact Protein Degradation and Tenderness of Longissimus Lumborum Steaks, but do Not Influence Collagen Cross-Linking

Beef tenderness is an important factor contributing to consumer eating satisfaction of beef products. Tenderness is dependent on several factors including: breed-type, postmortem age time, myofibrillar muscle protein degradation, and collagen content. During the past 30 years, numerous studies have indicated steaks from cattle with a greater percentage of Brahman genetics are tougher than steaks from Bos taurus cattle. The cause of tougher steaks is commonly attributed to Brahman cattle having a greater calpastatin activity which inhibits calpains, the enzymes responsible for myofibrillar protein degradation during the postmortem aging process. Some researchers have reported calpastatin activity was poorly correlated to tenderness of steaks from Brahman cattle. Others have reported sensory panelists indicated steaks from cattle with increasing percentages of Brahman genetics have an increase in the amount of connective tissue or collagen. Additionally, researchers have reported an increase in expression of genes that play a role in cross-linking of collagen which decreases collagen solubility. Due to these findings, we hypothesized steaks from cattle with greater Brahman genetics have more collagen cross-links and therefore a less soluble collagen fraction. The objective of this study was to evaluate the effect of Brahman genetics on protein degradation, collagen cross-linking, and meat tenderness of strip loin steaks

Visual processing in the central bee brain

Visual scenes comprise enormous amounts of information from which nervous systems extract behaviorally relevant cues. In most model systems, little is known about the transformation of visual information as it occurs along visual pathways. We examined how visual information is transformed physiologically as it is communicated from the eye to higher-order brain centers using bumblebees, which are known for their visual capabilities. We recorded intracellularly in vivo from 30 neurons in the central bumblebee brain (the lateral protocerebrum) and compared these neurons to 132 neurons from more distal areas along the visual pathway, namely the medulla and the lobula. In these three brain regions (medulla, lobula, and central brain), we examined correlations between the neurons' branching patterns and their responses primarily to color, but also to motion stimuli. Visual neurons projecting to the anterior central brain were generally color sensitive, while neurons projecting to the posterior central brain were predominantly motion sensitive. The temporal response properties differed significantly between these areas, with an increase in spike time precision across trials and a decrease in average reliable spiking as visual information processing progressed from the periphery to the central brain. These data suggest that neurons along the visual pathway to the central brain not only are segregated with regard to the physical features of the stimuli (e.g., color and motion), but also differ in the way they encode stimuli, possibly to allow for efficient parallel processing to occur

Effects of sorghum particle size on milling characteristics, growth performance, and carcass characteristics in finishing pigs

A total of 200 finishing pigs (PIC TR4 × 1050; average initial BW of 103.2 lb) were used in a 69-d growth assay to determine the effects of sorghum particle size on growth performance. Pigs were sorted by sex and ancestry and balanced by BW, with 5 pigs per pen and 10 pens per treatment. Treatments were a corn-soybean meal-based control with the corn milled to a target mean particle size of 600 μm, and sorghum diets milled to a target mean particle size of 800, 600, or 400 μm. Actual mean particle sizes were 555 μm for corn, and 724, 573, and 319 μm for sorghum, respectively. Feed and water were offered on an ad libitum basis until the pigs were slaughtered (average final BW of 271 lb) at a commercial abattoir. Reducing sorghum particle size improved (linear, P \u3c 0.01) F/G, and we observed a tendency for decreased (P \u3c 0.06) ADFI. Reducing sorghum particle size from 724 to 319 μm had no effects on HCW, backfat thickness, loin depth, or percentage fat-free lean index (FFLI), but tended to increase (P \u3c 0.06) carcass yield. Pigs fed the sorghum-based diets had no difference in growth performance or carcass characteristics compared with those fed the control diet, except carcass yield, which was numerically greater (P \u3c 0.07) for pigs fed the sorghum-based diets. When using a regression equation, we determined that sorghum must be ground to 513 μm to achieve a F/G equal to that of a corn-based diet, with corn ground to 550 μm. In conclusion, linear improvements in F/G and carcass yield were demonstrated with the reduction of sorghum particle size to 319 μm. In this experiment, sorghum should be ground 42 μm finer than corn to achieve a similar feeding value.; Swine Day, Manhattan, KS, November 17, 201

Effect of Pellet Cooling Method, Sample Preparation, Storage Condition, and Storage Time on Phytase Activity of a Swine Diet

Temperature and moisture content have been identified as two factors that influ­ence enzyme inactivation. Phytase may be further degraded in feed samples if there is moisture left in the sample and it is not properly stored prior to analysis. Therefore, the objective of this experiment was to determine the effect of cooling method, sample preparation, storage condition, and storage time on phytase stability. In Exp. 1, treat­ments were arranged in 2 × 2 factorial with main effects of sample preparation (none or freeze-dried) and storage condition (ambient storage or freezer storage). Diets were mixed 3 separate times to provide 3 replicates per treatment. The result of Exp. 1 demonstrated that there was no interaction between drying process and storage condi­tion for mash samples collected from the mixer. The sample drying process and storage condition did not impact the phytase stability. In Exp. 2, treatments were arranged in a 2 × 3 factorial with main effects of cooling method (counterflow cooler or freezer) and sample preparation (non-dried then freezer storage, freeze-dried then freezer storage, freeze-dried then ambient storage). The diet was steam conditioned for approximately 45 s at 185°F using a 5.1- × 35.8-in single shaft conditioner of a pellet mill (California Pellet Mill model Cl-5, Crawfordsville, IN) at a production rate of 2.2 lb/min by holding the feeder at a constant speed setting. The sample was collected at the end of the conditioner and did not pass the pellet die. The conditioner was run 3 separate times to provide 3 replicates for each treatment. The result of Exp. 2 demonstrated that there was no interaction between the cooling method and sample preparation for phytase stability of conditioned mash samples. The cooling method and sample prepara­tion did not affect the phytase stability. In Exp. 3, treatments were arranged in a 5 × 3 × 2 factorial with main effects of cooling method (none, heat diffusion, experimental fan cooler, experimental counterflow cooler, or freezer), storage condition (ziplock/ ambient, ziplock/frozen, and vacuum/frozen), and storage time (1 or 3 wk.). The diet was steam conditioned for approximately 45 s at 185°F and pelleted using a pellet mill (California Pellet Mill model Cl-5, Crawfordsville, IN) equipped with 0.16- × 0.50-in die. The diet was pelleted at a production rate of 2.2 lb/min by holding the feeder at a constant speed setting. The pellet mill was run 3 separate times to provide 3 replicates for each treatment. The result of Exp. 3 demonstrated that there were no three-way and two-way interactions among cooling method, storage condition, and storage time (P \u3e 0.686). The cooling method, storage condition, and storage time did not impact phytase stability (P \u3e 0.348). Therefore, freeze-drying, vacuum sealing, and freezing were not required when the feed samples were analyzed within 3 weeks of production. However, conditioned mash and hot pellet samples should be dried prior to sending the samples to the lab to prevent mold growth

Effect of Added Water, Holding Time, or Phytase Analysis Method on Phytase Stability and Pellet Quality

The addition of water to the mixer prior to pelleting is sometimes necessary to reach the target moisture content at the end of the conditioning process. However, there are limited data to demonstrate the impact of water addition in the mixer on phytase stability during the pelleting process. In addition, the variation of phytase analysis method may lead to incorrect or biased conclusions for research on industrial phytase stability. Therefore, the objective of this experiment was to determine the effect of water added in the mixer, feed holding time, and phytase analysis method on phytase stability and pellet quality. Treatments were arranged in a 2 × 2 × 2 factorial with main effects of added water (0% or 1%), holding time (0 or 2 h), and phytase analysis method (ELISA or EN ISO), respectively. For the 0% added water treatment, a 210-lb basal feed and 0.03-lb phytase were mixed for 5 min. For the 1% added water treatments, a 208-lb basal feed and 0.03-lb phytase were mixed for 120 s followed by the addi­tion of 2-lb water and then the mixture was mixed for 180 s wet mix time. The water was applied to dry feed in the mixer using a hand-held sprayer (Country Tuff model 26329, Sedalia, MO) with a flat spray tip nozzle (TeeJet model TP11006, Glendale Heights, IL). After the diets were mixed, treatments were immediately pelleted or held in a closed container for 2 h before pelleting. Treatments were steam conditioned at 185°F for approximately 30 s and pelleted using a pellet mill (California Pellet Mill Co. model Cl-5, Crawfordsville, IN). The pellet mill was equipped with a 0.16 × 0.87 in die. Samples were collected during discharge of the mixer, after conditioning and after pelleting. The conditioned mash and pelleted samples were cooled for 10 min using an experimental counterflow cooler. There were 3 replicates per treatment. Data were analyzed using the GLIMMIX procedure of SAS. The results demonstrated that there was no evidence of three-way or two-way interactions among added water, holding time, and analysis method on phytase stability for mash samples, conditioned mash samples, and pellets. The added water and holding time did not impact phytase stability for mash samples, conditioned mash samples, and pellets. The ELISA method had greater (P = 0.004) phytase activity than the EN ISO method for the pellet samples. The phytase activity was similar between the two analytical methods for mash samples and conditioned mash samples. For pellet quality, there was no evidence of interaction between added water and holding time. Added water and holding time did not impact pellet durability index. Therefore, the stability of phytase produced by a strain of Trichoderma reesei was not affected when feed was stored in a bin up to 2 h prior to pelleting. The added water in mash feed did not affect the degradation of Trichoderma reesei phytase when the feed moisture did not exceed 13%. Additionally, the ELISA or EN ISO method could be used in the laboratory to determine Trichoderma reesei phytase stability. Increasing moisture content of mash feed by 0.6% did not improve pellet quality

Pelleting and Starch Characteristics of Diets Containing High Amylase Corn

This experiment was designed to evaluate the effects of die thickness and conditioning temperature on pelleting and starch characteristics in diets containing either conventional yellow dent or high amylase corn (Enogen®, Syngenta Seeds, LLC). Treatments were arranged as a 2 × 2 × 3 factorial of corn type (conventional and high amylase), die thickness (L:D 5.6 and 8.0), and conditioning temperature (165, 175, and 185°F). For the high amylase corn treatments, ground high amylase corn replaced conventional ground corn on a lb:lb basis. Diets were pelleted via steam conditioning (10 in × 55 in Wenger twin staff pre-conditioner, Model 150) and using a pellet mill (CPM Model 1012-2) with a 5/32 in × 7/8 in (L:D 5.6) or 5/32 in × 1 1/4 in (L:D 8.0) pellet die. Conditioner retention time was set at 30 sec and production rate was set at 33 lb/min. All treatments were replicated on 3 separate days. Pellets were composited and analyzed for starch and pellet durability index (PDI). Conditioning temperature, hot pellet temperature (HPT), production rate, and pellet mill energy consumption were recorded throughout each processing run. Data were analyzed using the GLIMMIX procedure in SAS (v. 9.4, SAS Institute Inc., Cary, NC), with pelleting run as the experimental unit and day as the blocking factor. The 3-way interaction was not significant (P \u3e 0.15) for any of the pelleting or starch responses analyzed in this study. There was no evidence (P \u3e 0.14) for a corn type × conditioning temperature interaction for HPT, PDI, or energy consumption. There was a tendency (P = 0.08) for a corn type × die thickness interaction for PDI. The PDI for the high amylase and conventional corn treatments were similar when diets were pelleted using the L:D 8.0 die. However, PDI for conventional corn diets was greater than high amylase corn diets when pelleted using the L:D 5.6 die. Pelleting diets with the L:D 8.0 die had improved (P \u3c 0.01) PDI compared to the L:D 5.6. Additionally, PDI increased (linear, P = 0.03) with increasing conditioning temperature. Pellet mill energy consumption was greater for the thicker pellet die (P = 0.02), and tended to decrease (quadratic, P = 0.07) with increasing conditioning temperature. There was a corn type × conditioning temperature interaction (P = 0.01) for gelatinized starch in conditioned mash. High amylase corn diets steam conditioned at 185°F had greater gelatinized starch than all other corn type × conditioning temperature treatments. Cooked starch of conditioned mash was greater for diets containing high amylase corn compared to conventional corn and increased (linear, P \u3c 0.01) with increasing conditioning temperature. There was a corn type × die thickness interaction (P \u3c 0.01) for total starch in pellets. Total starch was greater for high amylase corn diets pelleted using the L:D 8.0 compared to the L:D 5.6 die, but not different from the conventional corn diets pelleted using either the L:D 5.6 or 8.0 die. Starch gelatinization was greatest (P \u3c 0.01) for the high amylase diets and increased (linear, P = 0.05) with increasing conditioning temperature. Lastly, pelleted high amylase corn diets had a greater percentage (P \u3c 0.01) of cooked starch compared to conventional corn diets, and there was a tendency (P = 0.06) for cooked starch to increase with increasing conditioning temperature. In conclusion, increasing die L:D and conditioning temperature improved pellet quality. Starch gelatinization was increased when diets were pelleted at the highest conditioning temperature of 185°F, and high amylase corn diets resulted in greater gelatinized starch than conventional corn diets

Effects of Grinding Corn with Different Moisture Concentrations on Subsequent Particle Size and Flowability Characteristics

The objective of this study was to determine the effects of whole corn moisture and hammermill screen size on subsequent ground corn moisture, particle size, and flow- ability. Whole yellow dent #2 corn was used for this experiment. Treatments were arranged as a 2 × 2 factorial design with two moisture concentrations (as-received and high) each ground using 2 hammermill screen sizes (1/8 and 1/4 in). Corn was ground using a laboratory scale 1.5 HP Bliss Hammermill (Model 6K630B) at 3 separate time points to create 3 replications per treatment. Increasing initial whole corn moisture was accomplished by adding 5% water and heating at 55°C for 3 hours in sealed glass jars using a Fisherbrand Isotemp Oven (Model 15-103-051). Ground corn flowability was calculated using angle of repose (AOR), percent compressibility, and critical orifice diameter (COD) measurements to determine the composite flow index (CFI). There was no evidence for a screen size × corn moisture interaction for moisture content, particle size, standard deviation, or flowability metrics. Grinding corn using a 1/8 in screen resulted in decreased (P \u3c 0.041) moisture content compared to corn ground using the 1/4 in screen. There was a decrease in particle size from the 1/4 in screen to the 1/8 in but no evidence of difference was observed for the standard deviation. There was a decrease (P \u3c 0.03) in percent compressibility as screen size increased from 1/8 to 1/4 in. Angle of repose tended to decrease (P \u3c 0 .056) when corn was ground using a 1/4 in screen compared to a 1/8 in screen. For the main effects of moisture content, high moisture corn had increased (P \u3c 0.0001) ground corn moisture content compared to as-received corn. As-received corn resulted in decreased (P \u3c 0.029) particle size and an increased standard deviation compared to the high moisture corn. Increased moisture content of corn increased (P \u3c 0.038) CFI and tended to decrease (P \u3c 0.056) AOR and COD. In conclusion, decreasing hammermill screen size increased moisture loss by 0.55%, corn particle size by 126 μm, and resulted in poorer flowability as measured by percent compressibility and AOR. High moisture corn increased subsequent particle size by 89 μm, therefore improving flowability as measured by CFI

Effects of Conditioning Temperature on Pellet Quality of Nursery Pig Diets

The objective of this experiment was to determine the effect of conditioning temperature on pellet durability index (PDI) and pellet hardness. A phase 1 swine nursery diet was formulated to contain 25% spray-dried whey. The diet was manufactured and pelleted at the Kansas State University O.H. Kruse Feed Technology and Innovation Center, Manhattan, KS. The treatments consisted of three different conditioning temperatures: 130, 145, and 160°F. Diets were steam conditioned (10 in width × 55 in length Wenger twin staff pre-conditioner, Model 150) for approximately 30 sec on a 1-ton 30-horsepower pellet mill (1012-2 HD Master Model, California Pellet Mill) with a 3/16 in × 1 1/4 in pellet die (L:D 6.7). Treatments were pelleted at 3 separate time points to provide 3 replicates per treatment. Samples were collected directly after discharging from the pellet mill and cooled in an experimental counterflow cooler. Samples were analyzed for PDI using the Holmen NHP 100 (TekPro Ltd, Norfolk, UK) in duplicate for each replicate. Pellet hardness was determined by evaluating the peak amount of force applied before the first signs of fracture. Pellets were crushed perpendicular to their longitudinal axis using a texture analyzer. A total of 30 pellets of similar length were selected at random from each replication to be tested and the force needed to crush each pellet was averaged within replication. Although conditioning temperature was increased in a linear fashion, a quadratic increase (P \u3c 0.002) in hot pellet temperature was observed. Increasing conditioning temperature resulted in increased (linear, P \u3c 0.045) PDI and pellet hardness. There was a tendency for a low correlation (P \u3c 0.076, r = 0.618, r2 = 0.382) between pellet hardness and PDI. Overall, increasing the conditioning temperature increased both pellet hardness and pellet durability; however, these two responses were not strongly correlated. Future research and more data need to be generated to determine the relationship between PDI and pellet hardness at varying levels of pellet quality to determine what factors influence this relationship