Development of a non-invasive objective test to measure the eating quality of pineapple and mango fruits

The ability to non-destructively assess fruit or vegetable quality would confer a decided marketing advantage to packing and processing sectors of most horticultural industries. The potential of near infra -red spectroscopy (NIRS) for non-invasive measurement of eating quality of pineapple (Ananas comosus (L.) Merrill, cv. 'Smooth Cayenne') and mango (Magnifera indica L., var. 'Kensington') fruit was assessed. Near infra -red (NIR) reflectance spectra (760-2500 nm) from an area of approximately 16 cm2 were correlated with pineapple juice Brix and with mango flesh dry matter (DM) measured from fruit flesh directly underlying the scanned area. The highest correlations for both fruit were found using the second derivative of the spectra (d2 log 1/R, where R is the amount of light energy emerging from the sample). Calibration using multiple linear regression (MLR) in an additive regression equation has practical application in that absorbance data from only four wavelengths are required. However, modified partial least squares (MPLS) regression analysis, which uses the whole spectrum, gave a better coefficient of determination (R2). Multiple linear regression using d2 log 1/R of pineapple fruit spectra (n = 85) gave a calibration equation with a R2 of 0.75, and a standard error of calibration (SEC) of 1.21° Brix, with a mean Brix of 12.1°. Modified partial least squares regression analysis yielded a calibration equation with a R2 of 0.91 and a SEC of 0.69° Brix. For mango, MLR gave a calibration equation using d2 log 1/R with a R2 of 0.90 and a SEC of 0.85% DM, with a mean of 18.0% DM. Using MPLS analysis, a calibration equation with a R2 of 0.98, a standard error of cross validation (SECV) of 1.19 was obtained.

Pre- and post -dispersive near infra -red spectroscopy were compared for non-invasive measurement of fruit quality of intact pineapple. In the pre -dispersive technique, monochromatic light was delivered via a fibre optic bundle to a probe which contained reflectance detectors. The same fruit were then assessed by the post -dispersive technique, with the fruit illuminated from a distance of 70 mm using white light generated by a tungsten halogen lamp, and reflected light delivered via a fibre optic bundle to a diffraction grating and associated detectors. The post -dispersive technique was comparable to the pre -dispersive technique in terms of accuracy (e.g. R2 0.73, SECV 1.01° Brix).

Near infra -red technology offers the potential to assess fruit sweetness in intact whole pineapple and dry matter in mango fruit, respectively, to within 1° Brix and 1% DM, and could be used for the grading of fruit in fruit packing sheds. Application of post - dispersive NIR technology to in -line assessment of intact fruit in a packing shed environment is discussed.