均方误差
化学计量学
偏最小二乘回归
食品科学
数学
巴氏杀菌
抗坏血酸
化学
标准误差
色谱法
统计
作者
Pritty Sushama Babu,K.P. Sudheer,Sarathjith Madathiparambil Chandran,Naveen Kumar Mahanti,R. Pandiselvam,J. Bindu,Anjineyulu Kothakota
摘要
Summary Thermal processing of tender jackfruit is a promising approach to enhance its shelf life and thereby retain the health benefits associated with its inherent antioxidants and phytochemicals. This research looked at the prospective and suitability of near‐infrared reflectance (NIR) spectroscopy (900–1700 nm) to assess the biochemical properties namely ascorbic acid (AA), total flavonoid content (TFC), and total phenolic content (TPC) of thermally treated (pasteurisation and sterilisation) tender jackfruit stored under different preservatives (2% brine, 0.1% KMS, and 0.3% citric acid) for a period of 5 months. The partial least square regression (PLSR) models were developed by using both raw as well as pre‐processed spectra. The pre‐processing of spectral data diminished the prediction accuracy of models. The models developed with raw spectral data reported best prediction accuracies for AA ( = 0.628; RMSE cv = 0.416 and RPD cv = 1.763), TFC ( = 0.915; RMSE cv = 1.909 and RPD cv = 3.719), and TPC ( = 0.882; RMSE cv = 0.032 and RPD cv = 3.013) as compared to models developed with pre‐processed spectral data. However, the lower prediction accuracies were observed in standard normal variate (SNV) pre‐processed data for AA ( = 0.449; RMSE cv = 0.51), TFC ( = 0.500; RMSE cv = 4.628), and TPC ( = 0.396; RMSE cv = 0.072). The standard error (SE P ) values of AA, TPC and TFC were almost 1.5–2 times the standard error of laboratory (SE L ); this implies the developed models have excellent performance. The results obtained in the present study affirmed that NIR spectroscopy in conjunction with appropriate chemometric techniques can be used for the rapid assessment of biochemical properties of thermal processed and canned tender jackfruit during transportation and storage.
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