Papaya: A gifted nutraceutical plant - a critical review of recent human health research

Effects of Ethanol Treatment on Storage Quality and Antioxidant System of Postharvest Papaya

Papaya is the fourth most favored tropical fruit in the global market; it has rich nutrition and can be used for medicine and food processing. However, it will soften and mature in a short time after harvest, resulting in a lot of economic losses. In this study, papaya fruits were soaked in 0, 12.5, 25, 50, and 100 ml/L ethanol solutions for 2 h and stored at 25°C for 14 days, by which we explored the effects of ethanol treatment in papaya after harvest. At an optimal concentration of ethanol treatment, color changing of the papaya fruits was delayed for 6 days, and decay incidence and average firmness of the fruits were shown as 20% and 27.7 N, respectively. Moreover, the effect of ethanol treatment on antioxidant systems in the papaya fruits was explored. It was observed that ethanol treatment contributed to diminish the development of malondialdehyde (MDA), ethylene, and superoxide anions. Furthermore, the activities of superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX) were promoted than those of control group, while the activities of peroxidase (POD), phenylalanine ammonia-lyase (PAL), and polyphenol oxidase (PPO) were brought down. In addition, the principal component analysis (PCA) showed that PAL, ethylene, and superoxide anions were the main contributors for the maturity and senescence of postharvest papaya. In this experiment, ethanol treatment had the potential of delaying the ripening and maintaining the storage quality of papaya fruits.

Multimodal Deep Learning and Visible-Light and Hyperspectral Imaging for Fruit Maturity Estimation

Fruit maturity is a critical factor in the supply chain, consumer preference, and agriculture industry. Most classification methods on fruit maturity identify only two classes: ripe and unripe, but this paper estimates six maturity stages of papaya fruit. Deep learning architectures have gained respect and brought breakthroughs in unimodal processing. This paper suggests a novel non-destructive and multimodal classification using deep convolutional neural networks that estimate fruit maturity by feature concatenation of data acquired from two imaging modes: visible-light and hyperspectral imaging systems. Morphological changes in the sample fruits can be easily measured with RGB images, while spectral signatures that provide high sensitivity and high correlation with the internal properties of fruits can be extracted from hyperspectral images with wavelength range in between 400 nm and 900 nm—factors that must be considered when building a model. This study further modified the architectures: AlexNet, VGG16, VGG19, ResNet50, ResNeXt50, MobileNet, and MobileNetV2 to utilize multimodal data cubes composed of RGB and hyperspectral data for sensitivity analyses. These multimodal variants can achieve up to 0.90 F1 scores and 1.45% top-2 error rate for the classification of six stages. Overall, taking advantage of multimodal input coupled with powerful deep convolutional neural network models can classify fruit maturity even at refined levels of six stages. This indicates that multimodal deep learning architectures and multimodal imaging have great potential for real-time in-field fruit maturity estimation that can help estimate optimal harvest time and other in-field industrial applications.

The Production and Quality of Different Varieties of Papaya Grown under Greenhouse in Short Cycle in Continental Europe

In Europe, papaya consumption is growing due to its nutritional properties. The proximity of consumer markets to Southeast Spain allows fruits to be harvested at a more advanced stage of maturity compared to exporting countries from outside Europe, a timeline which improves the quality of the papaya. Experiments have been carried out to assess the adaptation of papaya to protected cropping systems (under greenhouse) in the region. In this paper, we showed the results obtained in an experiment with five varieties, taking the most cultivated variety as control, which was grafted on its own female rootstock, in addition to another four new varieties that were introduced. Transplanting was made with early sex-identified plants in the nursery. Cultivation was developed in a 446-day cycle, almost 15 months and fruits were always harvested from the soil, due to the height that the plant reached in that period. The best yield parameters and fruit characteristics were obtained from hermaphrodite Intenzza papaya grafted on female papaya rootstock, although there were also other varieties which gave results that made possible its cultivation under this production system.