Evan Cole Diepersloot

Dr. Evan Cole Diepersloot


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 June 2021 in Agriculture
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Journal Article
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BSBenjamin A. Saylor
Benjamin A. Saylor
CMCody McCary
Cody McCary
EDEvan Cole Diepersloot
Evan Cole Diepersloot
CHCelso Heinzen
Celso Heinzen
MPMatheus Reboucas Pupo
Matheus Reboucas Pupo
LFLuiz Ferraretto
Luiz Ferraretto
Our objective was to assess the effect of forage processor roll gap width and storage length on fermentation, nutrient composition, kernel processing score (KPS), and ruminal in situ starch disappearance (isSD) of whole-plant maize silage harvested at different maturities. Samples from a single maize silage hybrid at three harvest maturities (1/4, 1/2, and 3/4 kernel milk line (early, intermediate, and late, respectively)) processed with two roll gap widths (1 and 3 mm) were collected and stored in quadruplicate vacuum pouches for 0, 30, 120, or 240 d. Lactic acid concentrations were greater, and pH was reduced in early and intermediate maturity silage compared to late maturity silage. Ruminal isSD was greatest for early maturity silage, intermediate for the intermediate maturity silage, and lowest for the late maturity silage, but differences in isSD due to maturity were diminished after prolonged storage. Kernel processing score was greatest in late maturity silage processed through a 1 mm roll gap and lowest in late maturity silage processed through the 3 mm roll gap. For early and intermediate maturity silages, no differences in KPS were observed between the two roll gap widths. Minimal effects of maturity and roll gap width on fatty acids (FA) and amino acids (AA) were observed. Concentrations of total AA decreased as storage length progressed. Results support the premise that the silo is a dynamic system that undergoes numerous chemical changes throughout the storage period.

11 August 2025 in Animals
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Journal Article
Open access
PDF file
MPMatheus Reboucas Pupo
Matheus Reboucas Pupo
EDEvan Cole Diepersloot
Evan Cole Diepersloot
EPEduardo Marostegan Paula
Eduardo Marostegan Paula
JDJoão Ricardo. R. Dórea
João Ricardo. R. Dórea
LGLucas Ghedin Ghizzi
Lucas Ghedin Ghizzi
LFLuiz Ferraretto
Luiz Ferraretto
Portable near-infrared reflectance spectroscopy (NIRS) offers the opportunity of a rapid measurement of forage dry matter concentration, allowing producers to make faster adjustments in real time. This study compared dry matter (DM) concentration predictions of three units of a portable near-infrared reflectance spectrometer (pNIRS) with conventional forced-air oven drying (48 h at 60 °C) using corn forage and silage samples. Moreover, a common on-farm method (Koster tester) was also compared. The reflectance curve used by pNIRS to predict DM was obtained by scanning WPCS samples and developed by SciO. A total of 113 whole-plant corn forage (WPCF) and 27 whole-plant corn silage (WPCS) samples from 66 corn hybrids were obtained from three separate experiments conducted between 2018 and 2019. These three experiments were completely independent of each other, with sample collections over different periods. In Experiment 1, all treatments were tested in WPCF, and the DM concentration of the forced-air oven differed from Koster testers (35.4 vs. 34.3% DM, on average, respectively) and all three pNIRS units (35.4 vs. 30.7% DM, on average, respectively), with no differences among pNIRS. All treatments were positively correlated with the forced-air oven treatment DM values. Experiment 2 evaluated the Koster tester and pNIRS in WPCF on farms, and the Koster tester differed from pNIRS (37.2 vs. 33.3% DM, on average, respectively) treatments. All pNIRS were positively correlated with Koster tester treatment. In Experiment 3, all treatments were tested in WPCS, and the DM concentration of the forced-air oven was greater than other treatments (35.3 vs. 32.8% DM, on average, respectively). Overall, Koster tester predictions for both Experiments 1 and 3 were better correlated with the forced-air oven than pNIRS. Additionally, pNIRS showed a lower mean bias, although low coefficients of determination and concordance correlation were observed in Experiment 3 compared to Experiments 1 and 2, which might be related to the prediction curve. Further calibrations of the predictive curve with forage samples would be needed to reasonably estimate the DM concentration of WPCF, whereas a greater number of samples could account for the variations in WPCS due to large heterogeneity in particle composition (e.g., leaves, stem, and kernel), size, and distribution.