The impacts of climate change on crop yields and fruit quality are projected to accelerate with increased atmospheric carbon dioxide levels; however, few studies have focused on the impacts of climate change on the accumulation pattern and content of soluble sugars in pear (Pyrus pyrifolia) fruit. We compared the soluble sugars content and accumulation patterns during the 2018 and 2019 growing seasons throughout the developmental stages of pear fruit with climate data collected over the same period. Between the two years, we observed differences in the fructose and sucrose contents at the maturation stage of the pear fruit, resulting from differences in sugar accumulation following 132 days after full bloom (DAFB). Differences were also found in the meteorological data measured over the two years. In particular, the daily average temperatures from late-June to mid-August (73 to 132 DAFB) were all higher in 2018 than in 2019, and differences in the cumulative amounts of both fructose and sucrose were observed since 132 DAFB. Notable differences were confirmed in the comparison of the meteorological variables for each time interval. Among the meteorological variables, those related to temperature showed clear differences between the two years. Correlation coefficient matrices showed that sucrose and fructose accumulation responded differently depending on the meteorological variables over the two years. Furthermore, only accumulated temperature and air temperature were correlated with changes in the sucrose and fructose content in 2018, unlike in 2019. Taken together, our results indicate that temperature differences may have contributed to differences in the fructose and sucrose contents and their accumulation patterns over the two years.

Verifying pollen germination using microscopic images is a difficult task. It is usually time-consuming and may entail reduced accuracy and reproducibility. Therefore, in this study, we used random forest (RF) and convolutional neural network (CNN) models to perform image classification on raw data corresponding to pollens with different germination rates; the data were obtained via flow cytometry. A heat map, which was based on the RF analysis results, showed that the variables that significantly influenced the classification decision between NG and 60G categories were mainly located in the center and top-right regions of the 30×30 pixel image. Additionally, a variable importance plot showed that among the 900 input variables, pixel_316 was the variable that contributed the most toward prediction. Gradient-weighted class activation mapping was used to visualize the class activation maps of the CNN model. The bottom-left region of the activation map was activated in the NG image. However, the 60G image showed that not only the bottom-left region but also the top-right region was activated. Both the models classified the input images into NG and 60G categories with high accuracy. However, considering that the RF model does not reflect the characteristics of adjacent variables, the CNN model is more appropriate for classifying pollen germination images corresponding to pollen with various germination rates into distinct classes. Taken together, these results suggest that the CNN model can provide a reliable method for verifying the pollen performance.

Gray mold is a postharvest disease that causes significant economic losses and limits the shelf life of strawberries. This study aimed to assess the effect of a preharvest peracetic acid (PAA) treatment on the natural decay of strawberry fruits under room-temperature storage conditions similar to those during commercial operations in a retail market. The effect of the PAA pretreatment on disease development in strawberries artificially infected with Botrytis cinerea was also assessed. In vitro susceptibility tests revealed that mycelial growth and metabolic activity were inhibited by 50-250 ppm of PAA. A preharvest treatment with 200-800 ppm PAA significantly reduced the initial microbial load in strawberry fruits immediately after harvest by 0.3-0.9 log colony-forming units (CFU)/g. Moreover, 800 ppm PAA significantly reduced the natural decay of strawberry fruits, resulting in approximately 33% less spoilage compared to untreated fruits on day 5. The PAA pretreatment also reduced lesion development in strawberries artificially inoculated with B. cinerea in a dose-dependent manner. Treatment with 800 ppm PAA most effectively reduced microbial populations and delaying the natural decay of strawberry fruits during room-temperature storage. These findings indicate that PAA is feasible as an alternative strategy for maintaining the quality of fresh strawberries and controlling decay in these fruits during room-temperature storage.

This study aimed to compare non-volatile metabolites and antioxidant activities of three purple radish varieties (cv. Sweet Baby, cv. Jungwoonmu, and cv. Boraking) leaves and roots. The total phenolic and flavonoid contents of the leaves were significantly higher than the roots. Glucosinolate content was significantly higher in the leaves than in the roots. In the purple radish roots, Boraking had the highest total anthocyanin content (420.14±16.2 mg cyanidin-3-glucoside/100 g) when compared to Sweet Baby (351.1±27.3 mg C3G/100 g) and Jungwoonmu (367.1±16.6 mg C3G/100 g). Based on the non-volatile metabolite analysis by liquid chromatography-electrospray ionization-quadrupole time-of-flight-mass spectrometry, 40 compounds, including flavonoid glycosides and coumaroyl glycosides in the leaves and 48 compounds, including various cyanidin glycosides and kaempferol glycosides in the roots were identified. Boraking was clearly classified from Sweet Baby and Jungwoonmu. The leaves of three purple radish cultivars had higher ABTS+ radical scavenging activity and ferric-reducing antioxidant power than the roots. The non-volatile metabolites and antioxidative activities of three purple radishes are expected to be used as basic information in food processing. In addition, the purple radish leaves, which are mostly discarded, will be used as a variety of food materials such as salads, wraps, and various vegetable-based dishes.

Typhoons, which are a common natural disaster in Korea, have seen a rapid increase in annual economic losses over the past decade. The objective of this study was to utilize historical crop insurance records to predict fruit drop rates caused by typhoons from 2016 to 2021. A total of 1848 datasets for the fruit drop rate were generated based on the impact of 24 typhoons on 77 cities with typhoon damage histories. Three different types of measures—the average value, the maximum or minimum value, and the value at a specific point during the typhoon—were applied to four meteorological factors, yielding a total of twelve variables used as model inputs. The predictive performance of the proposed models was compared using five evaluation metrics, and SHAP analysis was employed to assess the contribution of predictor variables to the model output. The most significant variable in explaining the vulnerability to typhoons was found to be the maximum wind speed. The categorical boosting model outperformed the other models in all evaluation metrics, except for the mean absolute error. The proposed model will assist in estimating the potential crop loss caused by typhoons, thereby aiding in the establishment of mitigation strategies for the main crop-producing areas.

Black stain is a postharvest disease that occurs on the skin of Niitaka pears (Pyrus pyrifolia Nakai) during cold storage, causing significant economic losses to pear production. We investigated the antifungal effects of peracetic acid (PAA), which is a strong oxidizing agent and an effective disinfectant, on fungi that cause black stain, and we confirmed its preventive effect on black stain after application to pears. Fungal isolates were identified as the type species of Cladosporium porophorum through molecular identification of internal transcribed spacer regions and the large subunit of nuclear ribosomal RNA gene. To assess antifungal effects of PAA and NaOCl on C. porophorum, several susceptibility tests including disc diffusion, mycelial growth tests, and microdilution assays were performed. A comparison of antifungal effects of PAA and NaOCl on C. porophorum showed that the PAA concentrations that inhibit mycelial growth or metabolic activity were twofold lower than those of NaOCl. When conidia were used as a fungal inoculum, PAA completely inhibited fungal growth and metabolic activity at concentrations of 0.02%-0.08% and 0.005%, respectively, whereas PAA concentrations of at least 0.1% were required to achieve sufficient growth inhibition of growing mycelium. After application of PAA to pears, the incidence rate of black stain in fruits treated with 0.1% PAA was approximately half (31.1% ± 1.9%) of that in untreated fruits (58.8% ± 4.5%). Therefore, the antifungal effects of PAA on fungi causing black stain may help reduce postharvest losses of Niitaka pears during cold storage.