Field experiments for evaluating the incorporation of RFID and barcode registration and digital weighing technologies in manual fruit harvesting
In this paper two methods are proposed for automatically matching bins containing harvested fruits with corresponding trees, during harvesting in orchards, where GPS data may be unavailable due to foliage. Both methods use a long-range radio frequency identification (RFID) antenna located on the harvesting platform for tree identification. Bin registration is accomplished in the first method by passive RFID tags attached to the bins, whereas the second method uses a barcode reader located on the platform, and low-cost barcode tags on the bins. Additionally, a digital scale is used with both methods to measure the yield distribution in the field, during the loading of the bins.
An experimental evaluation of these methods was performed during peach and kiwi harvesting in two different fields in Northern Greece. The aim was to estimate the tree and bin detection accuracies of both methods and their effect on the bin loading time. Statistical analysis of the data showed that when compared to the current standard harvesting procedure, RFID bin registration did not affect the amount of time to stack a bin on the platform (loading time), whereas barcode bin registration increased this time by 14%. It was also found that the use of the particular scale increased the loading time by almost 33% in both bin registration methods. Finally, the detection accuracy for the trees was 100% in all experiments and for the bins it was almost 100% for the RFID and 100% for the barcode reader. The results suggest that barcode technology can be used reliably for bin registration, without delaying the harvesting. Tree detection with long-range RFID technology was reliable; however tree growth combined with other factors such as wind, sunlight, etc., might decrease the tree detection accuracy over long periods of time. Finally, the bins had better be weighed at the packinghouse in order to generate the yield map, unless a much faster scale can be used in the field.
Αριστοτέλειο Πανεπιστήμιο Θεσσαλονίκης, Σχολή Γεωπονίας, Δασολογίας και Φυσικού Περιβάλλοντος, Τμήμα Γεωπονίας
Computers and Electronics in Agriculture, vol.66 no.2  p.166-172 [Published Version]
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