Peer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0022-5142

For breeding rice with improved quality, apparent amylose content (AAC), rapid visco analyser (RVA) pasting viscosities and gel texture properties may be routinely measured. As a direct measurement is time-consuming and expensive, rapid predictive method based on near-infrared spectroscopy (NIRS) is useful for measurement of these quality parameters. In this study, calibration models were developed using modified partial least-squares regression with different mathematical treatments based on the grain and flour spectra of non-waxy rice alone or in combination with waxy rice. The results showed that calibration models built with flour spectra are more robust than those with grain spectra, and with total rice including waxy rice are superior to those with only non-waxy rice. Some starch quality parameters, such as AAC, setback viscosity (SB), pasting temperature (PT), hardness (HD) and cohesiveness (COH) could be predicted with sufficient accuracy by NIRS based on flour spectra, whereas only AAC and PT could be predicted with sufficient accuracy based on grain spectra. All the models reported here are usable for rough sample screening (cold paste viscosity and breakdown viscosity), sample screening (SB, PT and COH) and for most applications (AAC and HD) for routine screening of a large number of samples in the early generation selection in breeding programs. However, for accurate assay of the pasting viscosity and gel textural parameters, direct instrumental measurement should be employed in later generations.

English

John Wiley