We have developed an electronic sensor (“sniffer”) that measures fruit ripeness rapidly and nondestructively by measuring the aromatic volatiles that are naturally emitted by ripening fruit. In this study, we evaluated the potential of using the fruit ripeness sniffer in the quality sorting of blueberries. Blueberries were first visually classified into four distinct ripeness classes: unripe; half-ripe; ripe; and over-ripe and quantitatively measured for color, firmness, TSS, and sugar acid ratio. Ripeness classification accuracy with the sniffer matched or exceeded that of all other ripeness indices. The sniffer differentiated unripe, ripe and over-ripe berries within one second, but could not distinguish between the unripe and half-ripe class. Detection of l-2 damaged or 1-2 soft fruit spiked within a large container of 24-37 high quality ripe fruit was also achieved, but required a response time of 10 seconds. Electronic sensing of aromatic volatiles may be a useful new technique in the grading and sorting of blueberries.
Meny Benady, Amots Hetzroni, James E. Simon, and Bruce Bordelon
Liangli Yu, Denys J. Charles, Amots Hetzroni, and James E. Simon
The volatiles of muskmelon (Cucumis melo L. reticulatis cv. Mission) were sampled by dichloromethane extraction and dynamic headspace methods and analyzed by gas chromatography (GC) and GC–mass spectroscopy (MS). A total of 34 constituents were identified, with esters contributing 8%–92% of the total volatiles. Butyl propionate, ethyl 3-methylpentanoate, hexadecanoic acid, methyl (methylthio)acetate, propyl butyrate, phenylpropyl alcohol, and vanillin, were recovered only by solvent extraction, while hexanal was only detected using dynamic headspace sampling. Methyl butyrate 35.2%, ethyl acetate 17.1%, butyl acetate 11.6%, ethyl propionate 8.3%, and 3-methylbutyl acetate 6.3% were the major constituents by solvent extraction sampling method. Butyl acetate 35.5%, 3-methylbutyl acetate 20.9%, ethyl acetate 7.3%, 2-butyl acetate 5.6%, and hexyl acetate 3.8% were the major constituents recovered by headspace sampling. Fruit tissue was also separated into five layers (exocarp, outer mesocarp, middle mesocarp, inner mesocarp, and seed cavity) and the volatile constituents differed significantly in content and composition by tissue.
Amots Hetzroni, Denys J. Charles, Jules Janick, and James E. Simon
A prototype of a nondestructive electronic sensory system (electronic sniffer) that responds to volatile gases emitted by fruit during ripening was developed. The electronic sniffer is based upon four semiconductor gas sensors designed to react with a range of reductive gases, including aromatic volatiles. In 1994, we examined the potential of using the electronic sniffer as a tool to nondestructively determine ripeness in `Golden Delicious' and `Goldrush' apples. Fruit were harvested weekly from 19 Sept. to 17 Oct. (`Golden Delicious') and 27 Sept. to 18 Nov. (`Goldrush'). Each week, apples of each cultivar were evaluated individually for skin color, weight size, and headspace volatiles. Each fruit was then evaluated by the electronic sniffer, and headspace ethylene was sampled from air within the testing box. Individual fruits were then evaluated for total soluble solids, firmness, pH, total acidity, and starch index value. The electronic sniffer was able to distinguish and accurately classify the apples into three ripeness stages (immature, ripe, and over-ripe). Improved results were obtained when multiple gas sensors were used rather than a single gas sensor.
Denys J. Charles, Amots Hetzroni, and James E. Simon
Recent developments in electronic odor-sensing technology has opened the opportunity for non-destructive, rapid, and objective assessment of food quality. We have developed an electronic sensor (electronic sniffer) that measures aromatic volatiles that are naturally emitted by fruits and fruit products. The ability of our sniffer to detect contamination in fruit juice was tested using tomato juice as a model system. Tomato juice was extracted from cultivar Rutgers and divided into eight glass jars of 300 g juice each. The jars were divided into two treatments: the control jars contained tomato juice mixed with 0.15% sorbic acid to suppress microbial growth, and the experimental jars contained only tomato juice. All the jars were placed open, on a counter top in the laboratory for 8 days. The juice was tested daily with the electronic sniffer and for pH. The total volatiles in the headspace of the juice was extracted on alternating days via dynamic headspace method using charcoal traps, analyzed by gas chromatography, and confirmed by GC/mass spectometry. The results indicate that the sniffer is able to detect differences between the two treatments 4 days after the tomato juice was exposed to ambient atmosphere. The electronic sniffer output for the control juice showed a monotonous decline, while the output for the experimental juice exhibited a sharp incline after day four. This sensor output correlated well with the total volatiles.
Amots Hetzroni, Denys J. Charles, and James E. Simon
A nondestructive electronic sensory system (electronic sniffer) that responds to volatile gases emitted by fruit during ripening was developed. It is based upon a single semi-conductor gas sensor placed within a rigid plastic cup equipped with a gas inlet to flush the head between samples. This gas sensor reacts with the range of reductive gases such as the aromatic volatiles that are naturally emitted by the ripening melon fruit. The sensor cup is placed on the exterior of the fruit and the change in electrical conductivity is recorded. In 1994, we examined the electronic sniffer as a tool to nondestructively determine ripeness in `Superstar', `Mission', and `Makdimon' melons. Fruits were manually classified into five ripeness stages based on external appearance and slip stage. Melons were first sampled nondestructively for color, weight, size, and slip stage, and then subjected to the electronic sniffer. Then, fruit volatiles, flesh firmness, and total soluble solids were measured. The electronic sniffer was able to accurately classify melons into three ripeness classes: unripe, half-ripe, and ripe for `Superstar' and `Mission'. The sniffer was only able to separate ripe from over-ripe in `Makdimon', which is known to become over-ripe and deteriorate rapidly. Using the sniffer as a tool to nondestructively measure ripeness and its potential application in fruit quality will be discussed.