Development of a predictive model to determine potato flour content in potato-wheat blended powders using near-infrared spectroscopy

Abstract

Potato is a good source of dietary energy and several micronutrients, and the development of staple foods using potato-wheat blended powder has received much attention recently in China. A rapid and accurate method for determining the potato flour content in potato staple foods would be valuable to market regulation efforts. We developed a predictive model for the potato flour content in potato-wheat blended powders based on near-infrared spectroscopy (NIRS) analysis. The correction of the near-infrared optical path was carried out to eliminate optical path differences using multiplicative scatter correction (MSC) and smoothing of the spectra using the Savitzky-Golay smoothing first-orderderivative (S-G-1 st D).The prediction model was developed based on partial least squares (PLS) combined with cross-validation(CV) within the full spectrum(850-1100 nm). The results showed that the optimal main factors of potato flour content in potatowheat blended powder were 9, and the coefficient of determination of calibration (R 2 c) and standard error of cross-validation (SECV) of the prediction model reached 0.9997 and 0.51, respectively, indicating a good correlation. The repeatability standard deviation (SDr) and repeatability coefficient of variation of cross-validation (CVr) in validated samples were 0.246 and 0.967, respectively, which indicated that the prediction model had good repeatability. The bias-corrected standard error of prediction (SEP) and correlation coefficient of validation (R 2 P) were 0.69 and 0.9995, respectively, demonstrating good accuracy and stability. The results of this study demonstrated that this prediction model based on NIRS could determine the potato flour content in potato-wheat blended powders accurately and quickly.

Near‐infrared spectroscopy applications for high‐throughput phenotyping for cassava and yam: A review

“…From this study, it was observed that NIRS as a low‐cost technique could be adapted to quality control schemes for screening many samples with high accuracy. Relatively similar studies have been undertaken for taro (Lebot et al ., 2011a, 2011b), potatoes (Huang et al ., 2018), sweet potato (Lu et al ., 2006) and even for root and tuber crop‐based flour blended with cereal flour (Huang et al ., 2018) or consumptive products such as bread (Wang et al ., 2019). Su & Sun (2017) explored Spectral imaging for quantitative detection of Irish organic wheat flour adulterated with cassava flour and cornflour.…”

Predicting quality, texture and chemical content of yam (Dioscorea alata L.) tubers using near infrared spectroscopy

“…In this regard, near infrared reflectance (NIR) spectroscopy has become a widely used method of quality control in the food processing industry. 28,29 It is a rapid, cost-effective and non-destructive technique allowing the simultaneous determination of major chemical constituents. NIR spectroscopy has been used to predict the content of major constituents in sweet potato, cassava, yam and taro crops.…”

Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)

“…Models of NIRS have been developed for the rapid characterisation of essential quality traits in various Dioscorea spp. [12,14,15] and have been successfully applied in many crops, including potato, cassava, and sweet potato [16][17][18][19]. Quantification of dry matter and protein in yam bean using NIRS was reported with an excellent prediction performance of 0.94 and a SEP of 1.2 [20].…”