Abstract #344
Section: Ruminant Nutrition (orals)
Session: Ruminant Nutrition III: Forages, fiber, and grains
Format: Oral
Day/Time: Tuesday 11:30 AM–11:45 AM
Location: Ballroom E
Session: Ruminant Nutrition III: Forages, fiber, and grains
Format: Oral
Day/Time: Tuesday 11:30 AM–11:45 AM
Location: Ballroom E
# 344
Development of a wet sieving method for measuring corn silage processing score (CSPS).
Ralph Ward*1, David R. Mertens2, 1Cumberland Valley Analytical Services Inc, Waynesboro, PA, 2Mertens Innovation & Research LLC, Belleville, WI.
Key Words: kernel processing
Development of a wet sieving method for measuring corn silage processing score (CSPS).
Ralph Ward*1, David R. Mertens2, 1Cumberland Valley Analytical Services Inc, Waynesboro, PA, 2Mertens Innovation & Research LLC, Belleville, WI.
Current CSPS is the percentage of starch passing through a 4.75-mm sieve with vigorous vertical shaking of a dried corn silage (CS). Starch in immature, extensively processed, or fermented CS may adhere to large particles when drying causing CSPS to be underestimated. Assuming that CS DM is a measure of immaturity, 5500 samples were used to assess the relationship between current CSPS and CS DM. The R2 was < 0.0001 indicating no relationship. The objective was to develop a wet sieving method that could remove soft starch that might stick to large particles. In the wet CSPS (WCSPS) method, a 150 g sample of undried CS is placed in a tall Tyler sieve of 30.5 cm diameter with 4.75-mm openings. At the top of the stroke, the sample is outside of the water in a tub and at the bottom of the stroke the sieve is immersed in water to a depth of about 10 cm. Samples are sieved for 90 s at 60 cycles/min. The residue retained is rinsed with a spray nozzle, dried, and analyzed for starch, and WCSPS was calculated as 100*[(total - retained starch)/total starch]. Dry and wet CSPS was determined on 189 CS. Ordinary least squares (OLS) regression is not appropriate when X and Y variables have similar variation. Geometric regression has the same correlation as OLS; however, the geometric equation fits Y on X and X on Y. Three replicate measures of CSPS and 10 replicates of WCSPS had standard deviations of 2.71 and 2.34, respectively. For the 189 CS, average CSPS and WCSPS was 70.5 and 72.9, respectively. The geometric regression was: CSPS = 21.78 + 0.675*WCSPS; R2 = 0.43. Low R2 suggests that the methods may not measure the same characteristic. Both methods also measure the DM retained (DMR) on the 4.75-mm sieve which obtained the geometric regression: DMR = −6.37 + 0.983*(Wet DMR); R2 = 0.42. When sorted into groups averaging 28, 33, 37, and 44% DM, the WCSPS averages were 76, 74, 72 and 60; and the CSPS were 68, 71, 72 and 69, respectively. WCSPS were higher than CSPS for the wetter silages, but correlations between DM and WCSPS or CSPS were <0.2. The WCSPS may address some of the problems with current CSPS, but low correlations suggest additional study.
Key Words: kernel processing