Search

Early detection of defects and diseases in fruit helps to correctly classify them and make more adequate decisions about the destination of the product: internal market, export or industry. An early fungi infection detection is especially important because a few infected fruits can disseminate the infection to a whole batch, causing great economic loses and affecting to further exports. Ensure products with excellent quality and absolute absence of fungi infections is particularly important in those batches for long conservation or to be exported. The main objective of this work is to detect the fungi infections before they can be visible. Near Infrared (NIR) spectroscopy has been employed in this work, because it is a non-destructive technique and can be easily implemented on line due to the high speed and simplicity of the process. This work is focused in the early detection of Penicilliu sp and Alternaria citri in citrus. Experiments have been conduced to evaluate the evolution of the spectra along the time in fruit inoculated with the selected fungi, trying to estimate the moment in which the infection is not visible but can be detected. Experiments were conducted on navelina oranges. Two spectra of each fruit were acquired, the first one corresponding to the inoculated area and the other from sound skin. The spectra of the inoculated and control oranges were measured in intervals of eight hours until the damage was visually observed. The experiments demonstrated that the best wavelength for early detection of the infection was 1050 nm. The infection was detected between 8 and 16 hours before becoming visible in the conditions of the experiment, which are much more favourable to the growth of the fungi than current, typical storage conditions in the citrus packinghouses. Therefore, this work provides good expectations of further development of automatic inspections systems for invisible defect detection and early warning of fungi infestation in citrus packinghouses.

Consumers demand for natural quality products and concern about the ecological impact of agricultural is growing in all European countries. For the farmers to follow the evolution of the market, new procedures have to be introduced in agriculture to obtain satisfactory production levels, keeping high quality standards, without damaging the environment.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Fruit and vegetables suffer different manipulations from the field to the final consumer. These are basically oriented towards the cleaning and selection of the product in homogeneous categories. For this reason, several research projects, aimed at fast, adequate produce sorting and quality control are currently under development around the world. Moreover, it is possible to find manual and semi- automatic commercial system capable of reasonably performing these tasks.However, in many cases, their accuracy is incompatible with current European market demands, which are constantly increasing. IVIA, the Valencian Research Institute of Agriculture, located in Spain, has been involved in several European projects related with machine vision for real-time inspection of various agricultural produces. This paper will focus on the work related with two products that have different requirements: fruit and olives. In the case of fruit, the Institute has developed a vision system capable of providing assessment of the external quality of single fruit to a robot that also receives information from other senors. The system use four different views of each fruit and has been tested on peaches, apples and citrus. Processing time of each image is under 500 ms using a conventional PC. The system provides information about primary and secondary color, blemishes and their extension, and stem presence and position, which allows further automatic orientation of the fruit in the final box using a robotic manipulator. Work carried out in olives was devoted to fast sorting of olives for consumption at table. A prototype has been developed to demonstrate the feasibility of a machine vision system capable of automatically sorting 2500 kg/h olives using low-cost conventional hardware.