Rapid prediction of moisture content of quinoa (Chenopodium quinoa Willd.) flour by Fourier transform infrared (FTIR) spectroscopy
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<p>Moisture content determination on quinoa flour is actually performed by gravimetric analysis, which is time, energy consuming and sample destructive. An emerging technique to measure moisture in an innovative way avoiding those problems is the Fourier transform infrared (FTIR) spectroscopy. The aim of this study is to obtain a trustable and validated model to predict moisture content of quinoa flour using FTIR. To perform the moisture measurements in five quinoa ecotypes, a gravimetric data and area under the curve obtained by FTIR, considering the [sbnd]OH peak associated to water (3200 cm<sup>−1</sup>), were compared at five different relative humidities (0, 33, 58, 75 and 100%). A good correlation between gravimetric measurements and FTIR area were observed (R<sup>2</sup> = 0.8729) and no differences were observed between quinoa ecotypes. A cross validation technique to predict moisture considering experimental and predicted data by area under de curve by FTIR was performed obtaining a general equation (y = 35.73x + 46.04) with a high repetitively and good prediction (100%) of the tested models.</p>
Moisture content determination on quinoa flour is actually performed by gravimetric analysis, which is time, energy consuming and sample destructive. An emerging technique to measure moisture in an innovative way avoiding those problems is the Fourier transform infrared (FTIR) spectroscopy. The aim of this study is to obtain a trustable and validated model to predict moisture content of quinoa flour using FTIR. To perform the moisture measurements in five quinoa ecotypes, a gravimetric data and area under the curve obtained by FTIR, considering the [sbnd]OH peak associated to water (3200 cm−1), were compared at five different relative humidities (0, 33, 58, 75 and 100%). A good correlation between gravimetric measurements and FTIR area were observed (R2 = 0.8729) and no differences were observed between quinoa ecotypes. A cross validation technique to predict moisture considering experimental and predicted data by area under de curve by FTIR was performed obtaining a general equation (y = 35.73x + 46.04) with a high repetitively and good prediction (100%) of the tested models.
Moisture content determination on quinoa flour is actually performed by gravimetric analysis, which is time, energy consuming and sample destructive. An emerging technique to measure moisture in an innovative way avoiding those problems is the Fourier transform infrared (FTIR) spectroscopy. The aim of this study is to obtain a trustable and validated model to predict moisture content of quinoa flour using FTIR. To perform the moisture measurements in five quinoa ecotypes, a gravimetric data and area under the curve obtained by FTIR, considering the [sbnd]OH peak associated to water (3200 cm−1), were compared at five different relative humidities (0, 33, 58, 75 and 100%). A good correlation between gravimetric measurements and FTIR area were observed (R2 = 0.8729) and no differences were observed between quinoa ecotypes. A cross validation technique to predict moisture considering experimental and predicted data by area under de curve by FTIR was performed obtaining a general equation (y = 35.73x + 46.04) with a high repetitively and good prediction (100%) of the tested models.
Keywords
FTIR, Moisture measurement, Prediction, Quinoa ecotypes, FTIR, Moisture measurement, Prediction, Quinoa ecotypes