Prediction performance of portable near infrared reflectance instruments using preprocessed dried, ground forage samples

Abstract

Forage analysis by near infrared reflectance (NIR) spectroscopy has had many advancements since it began in the 1970s. There have been steady improvements in instrumentation, in computers, and chemometric algorithms for developing calibrations. Thus, making NIR the most used technique to routinely analyze samples for forage producers, plant breeders, animal nutritionists, cattle farmers, and feed companies. This study compared the performance of prediction across three different portable instruments compared to a bench top laboratory NIR instrument, using a wide range of alfalfa and grass preprocessed dried, ground forage samples. Laboratory instrument scans were replicated with a reduced spectral range to match the range of each portable instrument. Alfalfa tended to have better calibration and test-set statistics than the grasses in this study. Portable instruments evaluated did not scan the upper portion of the spectral range (1652–2498 mn), which had some negative impact on forage calibration. The SCiO instrument scanned a very narrow range (740–1070 nm); and, although it had comparable results to the laboratory instrument constrained to same wavelength range, most major peaks related to forage quality traits are outside this range. The expensive bench top laboratory instrument had the best performance as expected, while the very inexpensive SCiO portable instrument had much greater error of prediction to the point that, for most traits, the prediction would not be considered reliable. However, the AuroraNir and the NIR-S-G1 digital light processing portable NIR may provide an alternative to expensive bench top laboratory equipment while still providing sufficiently accurate predictions. Therefore, some portable instruments have the potential to be used for on-farm analysis of wet, coarsely chopped forage, and this option must be evaluated in future studies.

Plant phenotyping relevance

乾燥・粉砕したアルファルファおよび草試料の飼料品質特性を推定する携帯型NIR装置を比較・検証しており、植物試料から形質を取得するセンシング手法の性能評価が中心である。

Code and data availability

公開状態または取得可能な本文経路を確認できませんでした。

No evidence-backed public reproduction asset is currently recorded.