Multispectral vision for monitoring peach ripeness.

UNLABELLED: The main objective of this research was to develop an automatic procedure able to classify Rich Lady commercial peaches according to their ripeness stage through multispectral imaging techniques. A classification procedure was applied to the ratio images calculated as red (R, 680 nm) divided by infrared (IR, 800 nm), that is, R/IR images. Four image-based ripeness reference classes (A: unripe to D: overripe) were generated from 380 fruit images (season 1: 2006) by a nonsupervised classification method and evaluated according to reference measurements of the ripeness of the same samples: Magness-Taylor penetrometry firmness, low-mass impact firmness, reflectance at 680 nm (R680, and soluble solids content. The assignment of unknown sample images from those season 1 images (internal validation, n = 380) and of 240 images from the 2nd season (season 2: 2007) to the ripeness reference classes (external validation) was carried out by computing the minimum Euclidean distance (classification distance, C(d)) between each unknown image histogram and the average histogram of each ripeness reference class. For both validation phases, firmness values decreased and R680 increased for increasing alphabetical order of image-based class letter, reflecting the ripening process. Moreover, 70% (season 1) and 80% (season 2) of the samples below bruise susceptibility firmness were classified into class D. PRACTICAL APPLICATION: This work proposes and validates a procedure for assessing peach ripeness through spectral imaging. The control of ripeness in this fruit is crucial for ensuring its quality and the measurement of optimum peach ripeness at harvest and postharvest is a controversial issue, which needs to be balanced between a minimum ripeness, acceptable for the consumer, and a maximum ripeness, to minimize fruit losses during the postharvest process. The proposed method is nondestructive and quick, showing thus, a good perspective for its application in fresh fruit packing lines, either for peach ripeness assessment or for other fruits (providing adequate calibration).

Characterization of Fuji apples from different harvest dates and storage conditions from measurements of volatiles by gas chromatography and electronic nose.

Volatile compounds in Fuji apples harvested at two different maturities were measured at harvest and after 5 and 7 months of cold storage (1 degrees C) in four different atmospheres. When the samples were characterized by both chromatographic measurements of volatiles and responses of an electronic nose, the analyses showed a clear separation between fruits from different storage conditions (a normal cold atmosphere and three controlled atmospheres). During poststorage, the apples were left to ripen for 1, 5, and 10 days at 20 degrees C before analytical measurements were done involving headspace-gas chromatography methods and electronic nose type quartz crystal microbalances. Electronic nose responses registered by seven different sensors were used to classify the apples using principal component analysis. It was possible to identify the samples from different storage periods, days of shelf life, and harvest dates, but it was not possible to differentiate the fruits corresponding to different cold storage atmospheres.