Alamar Priscila D, Caramês Elem T S, Poppi Ronei J, Pallone Juliana A L
Department of Food Science, School of Food Engineering, University of Campinas, Monteiro Lobato Street, 80, 13083-862, Campinas, São Paulo, Brazil.
Department of Food Science, School of Food Engineering, University of Campinas, Monteiro Lobato Street, 80, 13083-862, Campinas, São Paulo, Brazil.
Food Res Int. 2016 Jul;85:209-214. doi: 10.1016/j.foodres.2016.04.027. Epub 2016 Apr 30.
The present study investigated the application of near infrared spectroscopy as a green, quick, and efficient alternative to analytical methods currently used to evaluate the quality (moisture, total sugars, acidity, soluble solids, pH and ascorbic acid) of frozen guava and passion fruit pulps. Fifty samples were analyzed by near infrared spectroscopy (NIR) and reference methods. Partial least square regression (PLSR) was used to develop calibration models to relate the NIR spectra and the reference values. Reference methods indicated adulteration by water addition in 58% of guava pulp samples and 44% of yellow passion fruit pulp samples. The PLS models produced lower values of root mean squares error of calibration (RMSEC), root mean squares error of prediction (RMSEP), and coefficient of determination above 0.7. Moisture and total sugars presented the best calibration models (RMSEP of 0.240 and 0.269, respectively, for guava pulp; RMSEP of 0.401 and 0.413, respectively, for passion fruit pulp) which enables the application of these models to determine adulteration in guava and yellow passion fruit pulp by water or sugar addition. The models constructed for calibration of quality parameters of frozen fruit pulps in this study indicate that NIR spectroscopy coupled with the multivariate calibration technique could be applied to determine the quality of guava and yellow passion fruit pulp.
本研究调查了近红外光谱法作为一种绿色、快速且高效的替代方法，用于评估冷冻番石榴和西番莲果肉质量（水分、总糖、酸度、可溶性固形物、pH值和抗坏血酸）的现有分析方法。通过近红外光谱法（NIR）和参考方法对50个样品进行了分析。使用偏最小二乘回归（PLSR）建立校准模型，以关联近红外光谱和参考值。参考方法表明，58%的番石榴果肉样品和44%的黄色西番莲果肉样品存在加水掺假情况。PLS模型产生的校准均方根误差（RMSEC）、预测均方根误差（RMSEP）值较低，决定系数高于0.7。水分和总糖呈现出最佳校准模型（番石榴果肉的RMSEP分别为0.240和0.269；西番莲果肉的RMSEP分别为0.401和0.413），这使得这些模型能够用于通过加水或加糖来测定番石榴和黄色西番莲果肉中的掺假情况。本研究中构建的用于冷冻水果果肉质量参数校准的模型表明，近红外光谱法与多元校准技术相结合可用于测定番石榴和黄色西番莲果肉的质量。
