High occurrence of Aspergillus section Aspergillus in corn kernels for feed production.

Size reduction is one of the most important first steps during processing of biofeedstocks for food, feed, fuel or fiber production. Size reduction not only improves conversion processes because of the creation of larger reactive surface areas, but is used to also improve material handling in the process. This study investigated the particle size and size distribution, and the morphological changes of three biofeedstocks, switchgrass, corn kernels and soybean seeds ground by hammermilling through three screen sizes, 6.4 mm, 3.2 mm and 1.6 mm. Particle sizes were significantly different among screen sizes, however significant differences among feedstock type were only found for feedstock passing through 6.4 mm and 3.2 mm hammermill screens. Of the three feedstocks, ground corn exhibited the smallest particle size as expressed by its geometric mean diameter (dwg), while soybean seeds exhibited the largest dwg. The morphological features of all the feedstocks expressed as circularity, roundness and aspect ratio did not change significantly as was initially hypothesized. While ground switchgrass had very high aspect ratios (10 – 12) and low circularity (0.20) and roundness (0.10), the opposite was seen for ground corn and soybean which exhibited more spherical particles. It was concluded that the breakage behavior of biofeedstocks is an inherent material property that changes very little with size reduction by hammermilling.

Size reduction is one of the most important first steps during processing of biofeedstocks for food, feed, fuel, or fiber production. Size reduction improves conversion processes because of the creation of larger reactive surface areas, and it is also used to improve material handling in the process. This study investigated the particle size, particle size distribution, and morphological changes of three biofeedstocks (switchgrass, corn kernels, and soybean seeds) ground by hammermilling through three screen sizes (6.4 mm, 3.2 mm, and 1.6 mm). Feedstock particle size was analyzed based on both screen size and feedstock type. Significant differences were found among screen sizes; however, particle size differences among feedstock types were only significant for material passing through 6.4 mm and 3.2 mm screens. Of the three feedstocks, ground corn exhibited the smallest particle size as expressed by its geometric mean diameter (dwg), while soybean seeds exhibited the largest dwg. The morphological features of all the feedstocks, expressed as circularity, roundness, and aspect ratio, did not change significantly, as was initially hypothesized. While ground switchgrass had very high aspect ratios (10 to 12) and low circularity (0.20) and roundness (0.10), the opposite was seen for ground corn and soybean, which exhibited more spherical particles. It was concluded that the breakage behavior of biofeedstocks is an inherent material property that changes very little with size reduction by hammermilling.

In this study, bacteria residing in the gut of the rice weevils (Sitophilus oryzae L.) (Coleoptera: Curculionidae) feeding on aflatoxin-contaminated corn kernels were isolated and evaluated for their ability to suppress Aspergillus flavus and to remove/degrade aflatoxin B1 (AFB1). Four morphologically distinct S. oryzae gut-associated bacterial isolates were isolated and identified as Bacillus subtilis (RWGB1), Bacillus oceanisediminis (RWGB2), Bacillus firmus (RWGB3), and Pseudomonas aeruginosa (RWGB4) based on 16S rRNA gene sequence analysis. These bacterial isolates inhibited A. flavus growth in the dual culture assay and induced morphological deformities in the fungal hyphae, as confirmed by scanning electron microscopy. All four bacterial isolates were capable of removing AFB1 from the nutrient broth medium. In addition, culture supernatants of these bacterial isolates degraded AFB1, and the degradation of toxin molecules was confirmed by liquid chromatography-mass spectrometry. The bacterial isolates, B. subtilis RWGB1, B. oceanisediminis RWGB2, and P. aeruginosa RWGB4, were capable of producing antifungal volatile organic compounds that inhibited A. flavus growth. These results suggest that the bacterial isolates from S. oryzae gut have the potential to bind and/or degrade AFB1. Further research on their application in the food and feed industries could enhance the safety of food and feed production.

This paper presents the features of corn as raw material for groat industry. Corn is used in many segments of the food andprocessing industry. corn is processed for traditional food products — groats, flakes, flour, extruded foods, and other corn byproductsare widely used for the production of dry breakfast cereals, snacks, cereal bars. In terms of using of the advanced processingtechnologies, the industry produces starch, gluten, and germs. Corn germ is used to produce the high-value vegetable oil, aswell as starch — for both food and non-food purposes. More than half (65%) of corn is used for feed purposes, 25% –technical purposes,and nearly 20% – for various types of food production. corn is processed for traditional food products — groats, flakes, flour,extruded foods, and other corn by-products are widely used for the production of dry breakfast cereals, snacks, cereal bars. For thecolour, corn is divided into white and yellow types. According to the literature data analysis, yellow corn is more used in China,Argentina, Brazil, while white corn — in some countries of Asia, Latin America, and the Balkan countries. Depending on itsmorphological features, the corn kernelis divided into various groups, species and subspecies.In Ukraine corn kernel is classified into 8 types, with separately defined limitations on the content of the major crop in thebatch, grains of other type, etc. Corn of І-VІІІ types with the quality indicators specified in the standard, for the production of foodproducts. Flint and dent corn types are the most applied grain varieties in the industry, they are widely used in the production segmentof food and feed products. Sweet corn is widely used as a vegetable crop in the food canning, food concentrates, starch andbrewing industries due to its flavor properties. Popped corn is not only the most convenient raw material for the production of popcorn,but it also can be used as the raw material for the production of corn curls and dry breakfast cereals By analyzing the weightfraction of fat in kernels of different corn varieties we can note that the lowest number of fat is typical for popped corn (4.0%) andthe largest – for sweet corn (9.1%); dent and flint corn have the same total fat number (4.5-4.9%).Test weight of corn types – poppedcorn ranges within 712-826 g/l, dent corn - 875-893 g/l, and flint corn - 768-786 g/l. The weight of 1000 kernels of corn dependingon the varieties changes within 150-600 g.

As the dry grind ethanol industry has grown, the research and technology surrounding ethanol production and co-product value has also increased. One piece of technology to increase dry grind ethanol co-product value is of fractionation, both front end (before fermentation) and back end oil extraction (after fermentation) Front-end fractionation is prefermentation separation of the corn kernel into 3 fractions. The endosperm fraction is high in starch and is the only stream that enters the ethanol plant. The non-fermentable portion of the endosperm stream is carried into a product called high protein DDGS. The bran, or high fiber, stream is separated out and sold as an animal feed product, particularly to ruminant animals. High value oil is extracted out of the germ stream leaving a high protein co-product, corn germ meal. These 3 co-products have a very different composition than traditional DDGS from a corn ethanol plant. Furthermore, there are several possible fractionation processes; each produces a different set of co-products. Installing this technology allows ethanol plants to increase profitability by tapping into more diverse markets, and ultimately could allow for an increase in profitability. An ethanol plant model was developed to evaluate fractionation technology and predict the change in co-products based on the compositions of the endosperm, bran, and germ streams, of the DDGS alone in the case of back end oil extraction. The model runs in Microsoft Excel and requires inputs of whole corn composition (proximate analysis), amino acid content, and weight to predict the co-product quantity and quality. User inputs include saccharification and fermentation efficiencies, plant capacity, and plant process specifications including frontend fractionation and backend oil extraction, if applicable. This model provides plants a way