Prediction of amylose content, protein content, breakdown, and setback viscosity of Kadus rice and its flour by near‐infrared spectroscopy (NIRS) analysis

Abstract

One of the major problems in predicting the quality properties of rice is that conducting experiments can be highly expensive. Therefore, it may be necessary to explore prediction of quality properties through near‐infrared spectroscopy (NIRS). The present research was designed to survey the possibility of using NIRS to predict the Amylose Content (AC), Protein Content (PC), Breakdown Viscosity (BDV), and Setback Viscosity (SBV) of rice and its flour. R2cal to flour samples of AC, PC, BDV, and SBV produced by the Partial Least Squares (PLS) regression, were obtained as R2cal ≥ 0.887 and R2pre ≥ 0.805. Root Mean Square Error of Calibration (RMSEC) was calculated as 0.349, 0.078, 1.868, and 0.68, respectively. Similarly to rice samples, PLS regression was obtained as R2cal ≥ 0.93 and R2pre ≥ 0.75. RMSEC was measured as 0.24, 0.21, 1.87, and 2.58, respectively. The findings showed that, NIRS has the potential to be used as a quick procedure for predicting the quality properties. Practical applications All existing methods for measuring the rice quality indexes are labor‐expensive or time‐consuming. The development of more inexpensive methods can help precipitate the marketing process of the rice. The results of the present research are expected to lead to the development of NIR spectroscopic techniques for determining the quality of rice quickly through focusing on the chemical and physicochemical properties. The results can be used for designing and developing devices to test the quality indices of kernels, similar to those are being used to test the wheat quality according to single kernel characterization (SKCS).

Germplasm variability-assisted near infrared reflectance spectroscopy chemometrics to develop multi-trait robust prediction models in rice

“…RPD value > 3 was observed for protein (3.46) and TDF (3.62) indicating that the model is providing results that are at par with wet chemical analysis. Similar RPD values of 3.76 and 2.42 were observed for PC and AC in Kadus rice from Iran ( 37 ), respectively.…”

Research advance in gas detection of volatile organic compounds released in rice quality deterioration process

“…Near-infrared reflectance spectroscopy (NIRS) is one of the related research focuses currently, identified as a potential method to realize rapid prediction of the content of amylose and protein and other quality characters (Barnaby et al, 2020). Biancolillo et al (2019) and Burestan et al (2020) combined NIRS with soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) for identifying Plodia interpunctella-infested rice. 95.6% of the edible and 97.5% of the contaminated specimens could be accurately identified through PLS-DA, and the prediction of insect erosion in stored rice could be realized by SIMCA.…”

Application of fourier transform infrared photoacoustic spectroscopy for quantification of nutrient contents and their plant availability in manure and digestate

“…For that purpose, traditional laboratory methods (wet chemical analyses) for nutrient quantification are commonly used to quantify nutrient contents. However, these methods are slow and expensive and are, therefore, inadequate for this purpose [ 12 , 13 ] An alternative method for the rapid quantification of nutrient content in bio-based materials (manure and digestate) is spectroscopy in the near-infrared (NIR) wavelength range (780–2500 nm) and mid-infrared (MIR) range (2500–4000 nm) [ [14] , [15] , [16] , [17] , [18] , [19] ]. NIR spectroscopy is known for its weak absorption of overtone and combination bands, broadbands, and lack of distinct characteristics [ 20 , 21 ].…”