Comparative analysis of the volatile fraction of fruit juice from different Citrus species.

The volatile composition of fruit from four Citrus varieties (Powell Navel orange, Clemenules mandarine, and Fortune mandarine and Chandler pummelo) covering four different species has been studied. Over one hundred compounds were profiled after HS-SPME-GC-MS analysis, including 27 esters, 23 aldehydes, 21 alcohols, 13 monoterpene hydrocarbons, 10 ketones, 5 sesquiterpene hydrocarbons, 4 monoterpene cyclic ethers, 4 furans, and 2 aromatic hydrocarbons, which were all confirmed with standards. The differences in the volatile profile among juices of these varieties were essentially quantitative and only a few compounds were found exclusively in a single variety, mainly in Chandler. The volatile profile however was able to differentiate all four varieties and revealed complex interactions between them including the participation in the same biosynthetic pathway. Some compounds (6 esters, 2 ketones, 1 furan and 2 aromatic hydrocarbons) had never been reported earlier in Citrus juices. This volatile profiling platform for Citrus juice by HS-SPME-GC-MS and the interrelationship detected among the volatiles can be used as a roadmap for future breeding or biotechnological applications.

Automatic sex detection of individuals of Ceratitis capitata by means of computer vision in a biofactory.

BACKGROUND: The sterile insect technique (SIT) is acknowledged around the world as an effective method for biological pest control of Ceratitis capitata (Wiedemann). Sterile insects are produced in biofactories where one key issue is the selection of the progenitors that have to transmit specific genetic characteristics. Recombinant individuals must be removed as this colony is renewed. Nowadays, this task is performed manually, in a process that is extremely slow, painstaking and labour intensive, in which the sex of individuals must be identified. The paper explores the possibility of using vision sensors and pattern recognition algorithms for automated detection of recombinants. RESULTS: An automatic system is proposed and tested to inspect individual specimens of C. capitata using machine vision. It includes a backlighting system and image processing algorithms for determining the sex of live flies in five high-resolution images of each insect. The system is capable of identifying the sex of the flies by means of a program that analyses the contour of the abdomen, using fast Fourier transform features, to detect the presence of the ovipositor. Moreover, it can find the characteristic spatulate setae of males. Simulation tests with 1000 insects (5000 images) had 100% success in identifying male flies, with an error rate of 0.6% for female flies. CONCLUSION: This work establishes the basis for building a machine for the automatic detection and removal of recombinant individuals in the selection of progenitors for biofactories, which would have huge benefits for SIT around the globe.