Near-infrared calibration transfer for undried whole maize plant between laboratory and on-site spectrometers. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Marchesini, Giorgio; Serva, Lorenzo; Garbin, Elisabetta; Mirisola, Massimo; Andrighetto, Igino
• Is Part Of: Italian journal of animal science. Volume 17:Issue 1(2018)
• Page Start: 66
• Page End: 72
• Publication Date: 2018-01-02
• Subjects: NIRS -- calibration transfer -- maize silage -- maize plant composition -- on-site spectrometer; Animal culture -- Periodicals; Livestock -- Italy -- Periodicals; Veterinary medicine -- Italy -- Periodicals; Animal culture; Livestock; Veterinary medicine; Italy; Periodicals; Periodicals; 636.005
• DOI: 10.1080/1828051X.2017.1345660
• Languages: English
• ISSNs: 1828-051X

Abstract

Abstract: The analysis of the maize plant immediately after harvest is essential in order to check the composition and maturity of the plant to optimise the quality of silage. NIRS calibrations were carried out on chopped maize using three spectrophotometers: a laboratory instrument (FOSS NIRSystems 5000 scanning monochromator, FOSS, Silver Spring, MD) and two versions of new-generation portable instruments (poliSPEC NIR, PL1 and PL2). The aim was to verify the quality of the transfer of the calibration curves between FOSS, PL1 and PL2 and between PL1 and PL2, obtained by three methods of spectra processing: pre-processing, piecewise direct standardisation (PDS) and direct standardisation (DS). Seventy-six samples of chopped whole maize plant were scanned with the three instruments and were analysed by wet chemistry for dry matter (DM), ash, crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF), starch and total sugars, to develop calibration equations. Two more datasets of 15 samples each were used for the standardisation of equations and validation. The calibration transfer obtained, according to the values of R 2, standard error of prediction and bias, can be considered satisfactory (0.72 > R 2 <0.97) for DM, ash and NDF for both poliSPEC NIR, while CP and ADF have shown a good accuracy of prediction (0.78 > R 2 <0.82) with PL2. Using FOSS as a master instrument, the choice of method of standardisation varies depending on the slave instrument even though the best results are obtained using PDS with PL2. The most accurate predictions are reached using PDS even when PL1 is the master.