Global Mid-Infrared Prediction Models Facilitate Simultaneous Analysis of Juice Composition from Berries of Actinidia ,
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Global Mid-Infrared Prediction Models Facilitate Simultaneous Analysis of Juice Composition from Berries of Actinidia, Ribes, Rubus and Vaccinium Species Christopher J. Clark 1
&
Janine M. Cooney 1 & Wendy A. Hopkins 1 & Alastair Currie 2
Received: 17 February 2018 / Accepted: 17 May 2018 # Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract Introduction of Fourier-transform infrared (FTIR) spectroscopy would enable breeders to screen phenotypic variability in multiple fruit from large numbers of progeny. Thus far, however, there has been no comprehensive attempt to develop chemometric models for determination of quality attributes of small berry species by this approach. FTIR spectra (1800–900 cm−1) of juice from breeding populations of four genera (Actinidia, specifically red kiwifruit, Ribes, Rubus and Vaccinium) were analysed by partial least squares regression to determine the possibility of measuring soluble solids (SS), titratable acidity (TA) and total anthocyanin (ACY) concentration simultaneously using global prediction models. SS, TA and ACY concentrations across all berry juices ranged between 4.1 and 22.4 °Brix, 0.1–5.5% citric acid and 2–4697 ppm, respectively. R2 (coefficient of determination in cross-validation) and SECV (standard error of cross-validation) statistics for global models were 0.996 (0.22 °Brix), 0.996 (0.08% citric acid) and 0.893 (280 ppm). Analysis of data sets for individual berry types separately demonstrated that it was possible to develop models with superior prediction statistics for each attribute. However, these were not necessarily robust when validated against data from different seasons, locations or breeding selections. These global models represent an advance for researchers wishing to screen substantial fruit populations more rapidly. Keywords ATR-FTIR spectroscopy . Chemometrics . Flavonoids . Fruit . Soluble solids . Titratable acidity
Introduction Breeders of fruiting crops frequently need to screen phenotypic variability in multiple fruit from large numbers of progeny. Typically, attributes requiring quantification might include fruit quality traits that affect sensory perception, and the presence of bioactive molecules, if breeding for health-related compounds. Under this scenario, the requirement for highest-possible accuracy, as defined by more time-consuming, expensive and precise ‘gold standard’ methods, is superseded by the need to classify many progeny by less accurate, more pragmatic approaches to identify those with desired characteristics in the shortest time possible. Any unusual
* Christopher J. Clark [email protected] 1
The New Zealand Institute for Plant & Food Research Ltd., Private Bag 3230, Hamilton 3240, New Zealand
2
The New Zealand Institute for Plant & Food Research Ltd., Motueka Research Centre, 55 Old Mill Rd, RD3, Motueka 7198, New Zealand
individuals can subsequently be interrogated by the more detailed classical methodologies later. Vibrational spectroscopic techniques are ideally suited for th
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