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Abstract: sweetpotato starch thermal properties and its noodle quality were analyzed using a rapid predictive method based on near-infrared spectroscopy (NIRS). This method was established based on a total of 93 sweetpotato genotypes with diverse genetic background. Starch samples were scanned by NIRS and analyzed for quality properties by reference methods. Results of statistical modelling indicated that NIRS was reasonably accurate in predicting gelatinization onset temperature (T_o) (standard error of prediction SEP=2.014 °C, coefficient of determination RSQ=0.85), gelatinization peak temperature (T_p) (SEP=1.371 °C, RSQ=0.89), gelatinization temperature range (T_r) (SEP=2.234 °C, RSQ=0.86), and cooling resistance (CR) (SEP=0.528, RSQ=0.89). Gelatinization completion temperature (T_c), enthalpy of gelatinization (ΔH), cooling loss (CL) and swelling degree (SWD), were modelled less well with RSQ between 0.63 and 0.84. The present results suggested that the NIRS based method was sufficiently accurate and practical for routine analysis of sweetpotato starch and its noodle quality.

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