Peter Schade

Dr. Peter Schade


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

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

Representative Publications

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7 February 2026 in Agriengineering
Verified
Journal Article
Open access
PDF file
KSKevin Shinners
Kevin Shinners
PSPeter Schade
Peter Schade
ATAaron Timm
Aaron Timm
MDMatthew Francis Digman
Matthew Francis Digman
Whole-plant maize (corn) (WPC) is a critical forage in ruminant diets, and rapid, reliable measurement of its nutritional composition is essential for precision feeding. We hypothesized that an on-site near-infrared spectroscopy (OS-NIRS—specifically, HarvestLab™ 3000) sensor would provide within-laboratory repeatability comparable to commercial analytical laboratories (ALs) and inter-laboratory reproducibility similar to conventional laboratory analyses. To test this, WPC samples were collected across three experiments and two countries (USA and Germany) and analyzed by both OS-NIRS and ALs, with precision metrics calculated according to ISO 5725. Results showed that OS-NIRS achieved intra-laboratory repeatability equal to or greater than ALs, particularly for protein and starch. The repeatability performance of the OS-NIRS sensors was similar to that of ALs for moisture and NDF. Inter-laboratory reproducibility varied widely across constituents and experiments. Including OS-NIRS data with AL measurements produced inconsistent effects—sometimes narrowing confidence intervals but more often widening them—while OS-NIRS data alone demonstrated repeatability on par with ALs but mixed reproducibility outcomes. Inclusion of OS-NIRS data did not introduce systematic bias and, in some cases, improved consistency. These findings indicate that OS-NIRS can complement laboratory analyses by providing timely, farm-level measurements that enhance decision-making in feed management.