The objective of this study was to investigate whether prediction of fermentation potential (FP) of dry and high-moisture (HM) corns could be improved by using a concept of effective (e) mean particle size (MPS). A set of FP standards was created by processing a single lot of Reid Yellow Dent (RYD) corn to achieve MPS of 3,778, 2,786, 2,282, 1,808, 1,410, 806, 586, 378, 308, 226, and 105μm. In vitro gas production of RYD standards was measured, and peak absolute rate (PAR) of gas production (mL/0.2g of DM/h) was used to establish a standard relationship between PAR and MPS. To identify factors other than MPS affecting FP, the MPS and nutrient composition of 36 diverse samples of dry (n=18) and HM (n=18) corns were determined. Composition included dry matter (DM), crude protein, soluble crude protein, neutral detergent fiber, starch, NH3-N, prolamin protein, and fat. In vitro gas production of undried, unground dry and HM corns was measured, and PAR, time of peak absolute rate (h), maximum cumulative gas production (mL/0.2g of DM), gas production fractional rate (h−1), and lag (h) were determined. Nonlinear relationships between MPS, defined as the dependent variable, and PAR, as an independent variable, were used to identify FP deviations unexplained by MPS. When no variation in nutritional composition was present (RYD standards), the relationship between PAR and MPS was described by an exponential decay model [RYD_MPS=9,006 × e(−0.452×PAR); R2=0.96]. For diverse dry and HM corn populations, the variation in MPS explained by PAR was diminished (R2=0.50). To investigate factors that diminish the relationship between MPS and PAR in diverse corns, relative residual (rr) MPS was determined [rrMPS = (MPS – RYD_MPS)/MPS], where RYD_MPS was predicted from the PAR of diverse dry and HM corn. The rrMPS was most highly related to prolamin protein [rrMPSdry=0.58 − 0.15 × (prolamin protein, % of DM); R2=0.43] and NH3-N [rrMPSHM=0.21+0.08 × (NH3-N, % of total N); R2=0.46] for dry and HM corns, respectively. An eMPS was calculated as eMPS = MPS – MPS × rrMPS, where rrMPS was predicted from prolamin protein or NH3-N concentration in dry and HM corn, respectively. The natural logarithm of eMPS accounted for 84% of the variability in PAR and 53% of the variability in the fractional rate of gas production. Calculating eMPS by adjusting the MPS of dry corn for prolamin and HM corn for NH3-N concentration improved the assessment of industry corn FP.
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