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NIR model development and robustness in prediction of melon fruit total soluble solids

journal contribution
posted on 06.12.2017, 00:00 authored by John GuthrieJohn Guthrie, Christoffel LiebenbergChristoffel Liebenberg, Kerry WalshKerry Walsh
Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695–1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The ‘global’ modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the ‘local’ MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Volume

57

Issue

4

Start Page

411

End Page

418

Number of Pages

8

ISSN

0004-9409

Location

Collingwood, Victoria

Publisher

CSIRO Publishing

Language

en-aus

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Department of Primary Industries and Fisheries; Primary Industries Research Centre;

Era Eligible

Yes

Journal

Australian journal of agricultural research.