Optimization of Informative Spectral Regions in FT-NIR Spectroscopy for Measuring the Soluble Solids Content of Apple

Abstract

A novel potential method, linear combination weight PLS (LCW-PLS) model, was suggested for improving the performance of routine PLS model based on selected informative regions. Moving window partial least squares (MWPLS), genetic algorithms interval partial least squares (GAiPLS) and synergy interval partial least squares (SiPLS) were used to optimize informative spectral regions from FT-NIR spectra. A total of 660 apples harvested at 2006, 2007 and 2008, were divided into calibration and prediction sets by Kennard-Stone method. The best calibration model was obtained by LCW-PLS method based on informative spectral regions of 4328–4787, 5323–5512, 5982–7135 and 7159–7463 cm^− 1 selected by MWPLS procedure, and corresponding weights of 0.004, 0.070, 0.066 and 0.860, respectively. The LCW-MWPLS model was applied to predict samples, the prediction results were with R_P of 0.942, RMSEP of 0.649 %Brix and RPD_P of 3.10. In addition, developed LCW-MWPLS model using random two years samples was used to predict one year samples excluded. The predictive results were with R_P of 0.921–0.927, RMSEP of 0.714–0.795 %Brix and RPD_P of 2.44–2.88. The LCW-MWPLS model giving a prediction error equal to 4% of fresh weight was sufficiently accurate to determine the SSC of apple non-destructively.

Keywords::

• FT-NIR spectroscopy
• Non-destructive determination
• Informative region selection
• Linear combination weight PLS
• Soluble solids content
• Apple

Additional information

Notes on contributors

Jiahua Wang

J. Wang received B.Sc. degree in Food Sciences from Henan University of Science and Technology, Luoyang, China in 2004, and Ph.D. degree in Food Sciences from China Agricultural University, Beijing, China in 2010. Associate Prof. Wang joined the College of Food and Biological Engineering of Xuchang University in 2010. His research interests include agricultural products online detection, food information technology, and spectral data analysis.

Jingjing Cheng

J. Cheng received the B.Sc. degree in agronomy from Henan Institute of Science and Technology, Xinxiang, China in 2005, and the Ph.D. degree in agronomy from Northwest A&F University, Yangling, China in 2015, and do research as a visiting scholar in Washington State University, Pullman, USA in 2010. Her research interests include plant disease detection, agricultural products information technology, and spectral data processing.

Haiying Liu

H. Liu received B.Sc. degree in Life science from Shaanxi Normal University, Xi'an, China in 1993, M.Sc. degree in Life Science from Shaanxi Normal University, Xi'an, China in 2004, and Ph.D. degree in Food Science from the Shaanxi Normal University, Xi'an, China in 2009. Associate Prof. Liu joined the College of Food and Biological Engineering of Xuchang University in 2009. Her research interests include separation and detection technology of functional food factors, functional food processing technique.

Zhihui Tang

Z. Tang received B.Sc. degree in Agricultural Mechanization from Shihezi University, Shihezi, China in 1996. Prof. Tang joined the Institute of Machinery and Equipment of Xinjiang Academy of Agriculture and Reclamation Sciences in 2010. His research interests include agricultural harvest machinery, agricultural machinery information technology, and agricultural products processing machinery.

Donghai Han

D. Han is associate chairman of Division of China Near Infrared Spectroscopy. Prof. Han joined the Collage of Food Science and Nutritional Engineering, China Agricultural University in 1999. Dr. HAN received his Ph.D. degree in Agricultural Product Processing from the EHIME University, Japan in 1995. He worked as an Agricultural Engineer at the ISHII industry CO. Ltd from 1995 to 1997. His research topic is NDT (non-destructive testing) on food quality and safety, agricultural products processing technique, and agricultural products online detection.