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1.
Chemical and fruit skin colour markers for simple quality control of tomato fruits
Vesna Bukovac, Tatjana Unuk, 2015, original scientific article

Abstract: The orientation of this research was to evaluate the classic parameters regarding the external and internal quality of tomato fruits cv. ‘Brilliant‘ at different stages of maturity and to define the dynamics of their changes during the ripening in storage at 18 °C. Principal component analysis (PCA) and multivariate canonical discriminant analysis (DA) were used to classify tomato samples according to quality (internal and external) and nutritional value based on fruit mass, fruit skin colour, contents of soluble solids (SS), total titratable acids (TTA), ascorbic acid (AA), and total antioxidant potential (TAP). Several methods are usedfor determining AA content and TAP in plant samples. A simple routine method, direct redox titration with iodate solution and spectrophotometric determination of TAPSP, as described by Singleton and Rossi, also called total phenols, were used respectively. The results show that the stage of maturity (based on fruit skin colour) strongly determines the quality and nutritional value of the tomato fruit. Tomatoes harvested at table maturity (red colour, index a*/b* ≥ 0.85) have a significantly higher nutritional value (in terms of antioxidants – TAPSP and AA content) and overall quality than those harvested at an earlier maturity stage and then ripened in storage. This brings out the importance of short food supply chains and, from the viewpoint of overall fruit quality, it raises doubt about harvesting before reaching table maturity. On the other hand, it is necessary to be extremely attentive when determining optimal maturity, because when the plant becomes over-ripe or when stored, the nutritional value and overall quality decrease drastically. Besides the colour parameters, AA content is the most important chemical marker for a simple quality control. By using a simple and reliable analytical method for determining AA content, such as direct redox titratiation, the monitoring of tomato fruit quality could also be easily performed in situ.
Keywords: chemical markers, quality control, antioxidant, tomato, discriminant analysis
Published: 24.10.2017; Views: 445; Downloads: 66
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2.
The accuracy of the germination rate of seeds based on image processing and artificial neural networks
Uroš Škrubej, Črtomir Rozman, Denis Stajnko, 2015, original scientific article

Abstract: This paper describes a computer vision system based on image processing and machine learning techniques which was implemented for automatic assessment of the tomato seed germination rate. The entire system was built using open source applications Image J, Weka and their public Java classes and linked by our specially developed code. After object detection, we applied artificial neural networks (ANN), which was able to correctly classify 95.44% of germinated seeds of tomato (Solanum lycopersicum L.).
Keywords: image processing, artificial neural networks, seeds, tomato
Published: 14.11.2017; Views: 535; Downloads: 181
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