CNN-based object detection and growth estimation of plum fruit (Prunus mume) using RGB and depth imaging techniques.

Modern people who value healthy eating habits have shown increasing interest in plum (Prunus mume) fruits, primarily owing to their nutritiousness and proven efficacy. As consumption increases, it becomes important to monitor work to prevent Prunus mume fruits from falling out. Moreover, determining the growth status of Prunus mume is also crucial and is attracting increasing attention. In this study, convolutional neural network (CNN)-based deep learning object detection was developed using RGBD images collected from Prunus mume farms. These RGBD images consider various environments, including the depth information of objects in the outdoor field. A faster region-based convolutional neural network (R-CNN), EfficientDet, Retinanet, and Single Shot Multibox Detector (SSD) were applied for detection, and the performance of all models was estimated by comparing their respective computing speeds and average precisions (APs). The test results show that the EfficientDet model is the most accurate, and SSD MobileNet is the fastest among the four models. In addition, the algorithm was developed to acquire the growth status of P. mume fruits by applying the coordinates and score values of bounding boxes to the depth map. Compared to the diameters of the artificial Prunus mume fruits used as the experimental group, the calculated diameters were very similar to those of the artificial objects. Collectively, the results demonstrate that the CNN-based deep learning Prunus mume detection and growth estimation method can be applied to real farmlands.

Temperature-Dependent Development of the Post-Diapause Periods of the Apricot Seed Wasp Eurytoma maslovskii (Hymenoptera: Eurytomidae): An Implication for Spring Emergence Prediction Models.

The present study investigates the influence of temperature on the development of Eurytoma maslovskii after a diapause break up until adulthood. The insect development rate was fitted to both linear and nonlinear models to estimate thermal bioparameters, which served as the basis for constructing prediction models. Chilled apricot seeds collected in November were used for the experiments in March. Experiment 1 used intact seeds, while experiment 2 used overwintered larvae obtained by cracking the endocarp cover. Both larvae and intact seeds were subjected to seven constant temperatures (14.5, 18.8, 21.3, 24.0, 27.0, 30.2, and 34.3 °C). The post-diapause larvae of E. maslovskii developed into adults at a temperature range of 14.5-30.2 °C, and no larvae pupated at 34.3 °C. The lower temperature thresholds (LTs) for post-diapause larva and pupa and the total post-diapause period until adult emergence and until adult exit were 8.1, 8.2, 8.2, and 7.3 °C, respectively, whose thermal constants (DD) were 66.2, 180.2, 246.9, and 336.7 degree days, respectively. The distribution of E. maslovskii at all post-diapause stages was described using a two-parameter Weibull function. The data predicted by the model using accumulated degree days starting from January 1 did not differ by more than three days from the observed field emergence of E. maslovskii. Our data provide insights into the development of E. maslovskii after diapause. Temperature-dependent development supports the use of a degree day model to predict field emergence for pest timing control.

Verification of the Functional Antioxidant Activity and Antimelanogenic Properties of Extracts of Poria cocos Mycelium Fermented with Freeze-Dried Plum Powder.

Here we examine the effects of extracts of Poria cocos mycelium fermented with freeze-dried plum powder (PPE) on the α-melanocyte stimulating hormone (α-MSH)-stimulated melanogenesis in cultured murine B16 melanoma cells (B16 cells), relative to the effects of Prunus extract. We found that an extract of Prunus fermentation showed significant inhibition of melanogenesis and tyrosinase activity with no effect on cell proliferation and was more active compared to Prunus extract alone. Furthermore, we confirmed that medium containing 3% Prunus was the optimal culture substrate for fermentation with Poria cocos. These results provide evidence that Prunus fermentation extract affects skin whiting in murine B16 melanoma cells (B16 cells). Prunus contains rutin, oxalic acid, succinic acid, and fumaric acid, which help in digestion and fatigue recovery. The rutin of Prunus mume is reported to have antioxidant and anti-inflammatory effects. Also, Prunus extract has a tyrosinase inhibitory activity for skin whiting through its antioxidant activity. Therefore, we believe the Prunus extract for Poria cocos fermentation can be provided as a potential mediator to induce skin whiting.