| Jujube fruit is an increasingly important fruit in the world for its high nutrients content and medicinal value. The harvest time is crucial for jujube fruit quality. Therefore, information on the degree of fruit ripeness is vitally important to growers to determine the best harvest date associated with best fruit quality. In recently, nondestructive techniques have been applicated in many fields and are becoming more and more popular. At the same time, however, many instruments used in the nondestructive techniques are costly and difficult to carry to the fruit orchards. With the improvement of people’s consumption conception, the classification based on internal nutrients has already become a kind of inevitable trend. Though there are much high nutrients content in jujube fruits, its shelf life is short and it tends to decay and easy to lose nutrient at room temperature. Therefore, the fresh jujube was often processed in industry, such as drying. However, dring may result in different grades of dried jujube because of nonuniform heating. It needs a fast and accurate method to sort them.To solve the above issues, We have carried out some researches. The main contents and results are listed as follows:1. The study was to evaluate the quality changes and the optimum time for harvesting of jujube fruit (Zizyphus jujuba Mill. cv. Changhong) by chlorophyll fluorescence. Our results showed that jujube fruit cv Changhong displayed a double-sigmoid growth curve with a very short lag phase. At the last three ripening stages (72,80and88days after petal fall), Fo, Fm and Fv showed positive and significant correlation with DPPH radical scavenging activity, total phenolic, reducing sugar, ascorbic acid and total flavonoid (0.729≤r<0.920, P<0.05). However, pH, total soluble sugar and carotenoids showed negative and significant correlation with Fo, Fm and Fv (-0.885≤r≤-0.826). The last three ripeness stages in our study were differentiated using the chlorophyll fluorescence parameters.2. Fruit classification is important to improve quality during processing, storage and marketing. The another aim of the study was to determine if a new system combining chlorophyll fluorescence (ChlF) and C-support vector machine (C-SVM) might assist the classification of jujube fruits based on postharvest quality, including ascorbic acid and total phenols contents and2,2’-diphenyl-l-picrylhydrazyl (DPPH) radical-scavenging activity. Our results showed that the best classification accuracy of fruit quality was up to93.33%using the RBF SVM classifier (C=2, y=0.5), and the correct classification rates of86.67%was achieved for the sigmoid (C=2, y=0.5) SVM classifier as well as the polynomial (C=2, y=0.5, d=1) SVM classifier.3. A new method that combines fractal theory and RGB (red, green and blue color) intensity was developed to sort dried jujube fruits by using support vector machine (SVM). Our result shows that the new method is fast and accurate in dried jujube fruits classification. The SVM models based on fractal parameters only achieved85.18%-92.73%total accuracy rate. The total classification accuracy of SVM based on RGB intensity values was94.44%. However, the SVM models based on combining fractal parameters with RGB intensity values achieved94.44%-98.15%total accuracy rate. The best classification accuracy (98.15%) was found when using SVM model based on combining fractal measures with RGB intensity values (C=512, γ=0.0078125).In conclusion, chlorophyll fluorescence is a helpful, non-destructive technique to evaluate the quality changes and the optimum time for harvesting of Changhong jujube. The proposed SVM classifier achieved the best classification accuracy, showing that the SVM-Ch1F system can provide a potential tool for automatically classifying the quality of not only jujube fruits, but also any other chlorophyll-containing fruits in packing lines. In addition, the SVM model based on combining fractal measures with RGB intensity is recommended in dried jujube fruits classification. |
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