Using selective NIR wavelengths in portable devices to evaluate the chemical composition of cattle feeds

In modern cattle nutrition, the estimation of chemical composition must be accurate, rapid, andavailable throughout the farm feeding process. This goal can be achieved using portable near infra-red instruments applied at several positions in the feeding chain. Although portable instruments aregenerally more affordable than benchtop equipment, the current costs of purchasing and maintain-ing these tools may still be prohibitive for small and medium-sized animal husbandry businesses.This makes their widespread adoption economically unsustainable for many farms. Reducing thespectral data helps prevent multicollinearity issues, enabling the use of a minimal–optimal problemapproach and supporting the development of a targeted and cost-effective instrument. This wasachieved by evaluating various cattle rations and silages (including rations for cows and bulls andgrass and corn silage), where we selected the most significant wavelengths for fibre characterisationusing the Random Forest (Boruta) algorithm. The number of identified features varied based on thespectral pre-treatments applied or the use of a batch effect reduction algorithm (ComBat function).External validation was accomplished with spectra collected by different instruments, origins andsample types, and the highest adjusted coefficients of determination in validation were 0.95 for drymatter and 0.84 for alpha-amylase and sodium sulphite-treated NDF. Results demonstrated thatusing a few spectral bands is suitable for instrument calibration.