Selecting Variables for Near Infrared Spectroscopy (NIRS) Evaluation of Mango Fruit Quality

Abstract

Near infrared spectroscopy (NIRS) can be applied to assess the quality of mango. The purpose of this research is to select the appropriate chemical absorption bands to evaluate two cultivars of mango puree, cv. Keitt and cv. Nam Dok Mai Si Thong. Six main chemical substances found in mango fruit, such as glucose, sucrose, citric acid, malic acid, starch and cellulose, were evaluated in this study and there chemical absorption bands were identified. Mango puree was mixed with the six pure substances at various concentrations; glucose, sucrose, citric acid and malic acid were tested with concentrations of 0, 5, 10, 15 and 20%w/w, starch and cellulose were tested with the concentrations 0, 2.5, 5, 7.5 and 10% w/w. The NIRSystem 6500 was used to scan the spectra in the wavelength range from 400 nm to 1100 nm. The partial least square regression (PLSR) was used to develop a model for each component. The result was a wavelength that corresponds to each component. It was found that the second derivative spectra of glucose, sucrose, citric acid, malic acid, starch and cellulose mixtures showed the best PLSR result. The mango cultivar had no effect on wavelength selection by PLSR model. The coefficient of determination (R 2 ) of all models was 0.99. The standard error of calibration (SEC) and the standard error of prediction (SEP) were less than 0.5%w/w. The regression coefficient plot exhibited more sharp peaks than pure substances. The wavelength selection for NIRS evaluation mango fruit quality could not be done by using only measured spectrum of pure substance. However, the cultivars of mango had no effected on wavelength selection by PLSR model. The most effective wavelength for glucose and sucrose were 900-1000 nm, citric acid and malic acid were 800-1000 nm, starch was 900-1000 nm and cellulose was 800-1000 nm.