In apple cultivation, the total nitrogen content is an important indicator of plant growth, fruit quality, and yield. Timely monitoring of growth becomes imperative, since an imbalance, either in deficiency or excess nitrogen, can result in physiological disorders, adversely impacting both the quantity and quality of fruit. Leaf nitrogen content can be determined using simple chlorophyll meters or destructive testing; however, these methods are time-consuming. However, by employing spectral imaging technology, it is possible to swiftly predict leaf nitrogen content. This study estimated the total nitrogen content in apple trees via hyperspectral imaging and machine learning-based regression analysis (partial least-squares regression (PLSR), support vector regression (SVR), and eXtreme gradient boosting regression (XGBoost). Additionally, to reduce computational costs and improve reproducibility, spectral binning was divided into three stages (4, 8, and 16 bins), and models were compared with a 2-binning estimation model. The analysis focused on green, red, red edge, and near-infrared (NIR) spectra, with 5–10 selected wavelengths, and the SVR-based prediction model showed a similar or greater performance to that of the full spectrum. At 4- and 8-binning, the selected wavelengths were similar to those at 2-binning, maintaining similar prediction model performance. However, at 16 bp, the performance of the prediction model decreased owing to spectral data loss, leading to a significant reduction in wavelengths for nitrogen content estimation. These results can support informed nitrogen fertilization decisions, enabling precise, real-time monitoring of nitrogen content for enhanced plant growth, fruit quality, and yield in apple trees. Additionally, the selected wavelengths can be considered in the development of new types of multispectral sensors.

Extensive research has been performed on the in-field nondestructive evaluation (NDE) of the physicochemical properties of ‘Madoka’ peaches, such as chromaticity (a*), soluble solids content (SSC), firmness, and titratable acidity (TA) content. To accomplish this, a snapshot-based hyperspectral imaging (HSI) approach for filed application was conducted in the visible and near-infrared (Vis/NIR) region. The hyperspectral images of ‘Madoka’ samples were captured and combined with commercial HSI analysis software, and then the physicochemical properties of the ‘Madoka’ samples were predicted. To verify the performance of the field-based HSI application, a lab-based HSI application was also conducted, and their coefficient of determination values (R²) were compared. Finally, pixel-based chemical images were produced to interpret the dynamic changes of the physicochemical properties in ‘Madoka’ peach. Consequently, the a* values and SSC content shows statistically significant R² values (0.84). On the other hand, the firmness and TA content shows relatively lower accuracy (R² = 0.6 to 0.7). Then, the resultant chemical images of the a* values and SSC content were created and could represent their different levels using grey scale gradation. This indicates that the HSI system with integrated HSI software used in this work has promising potential as an in-field NDE for analyzing the physicochemical properties in ‘Madoka’ peaches.

We investigated the effects of elevated temperatures on the photosynthetic characteristics and fruit quality of the ‘Mihong’ peach (Prunus persica) under high carbon dioxide concentrations based on climate change scenario RCP 8.5. We simulated three different temperature conditions (control; the average temperature in normal years in Jeonju city, C+3.4 °C, C+5.7 °C) and 700 μmol·mol⁻¹ CO₂ (expected in the mid-21st century). The average photosynthetic rates were 10.64, 10.21, and 8.18 μmol∙m⁻²∙s⁻¹ at C+3.4 °C, control, and C+5.7 °C, respectively. The chlorophyll content in the control and C+3.4 °C increased compared to that at the early stage of growth, but that of C+5.7 °C decreased rapidly. The fruit weight was the highest for C+3.4 °C (158.2 g), followed by C+5.7 °C (129.5 g) and the control (127.3 g). The shoot length increased at C+3.4 °C and C+5.7 °C when compared to the control, and there was no significant difference in the other growth characteristics. The carbohydrate content was the highest at C+3.4 °C, and the nitrogen content increased as the temperature increased. Moreover, the C/N ratio decreased as the temperature increased but there was no significant difference. The rate of floral bud differentiation decreased as temperature increased, and that of C+5.7 °C was the lowest due to the low C/N ratio, vegetative growth dominance, and early defoliation. Furthermore, the floral bud density was low in the C+5.7 °C treatment. These findings indicate that a temperature increase of 5.7 °C under 700 μmol·mol⁻¹ CO₂ conditions will negatively affect the physiological response and fruit quality of the early-maturing peach variety ‘Mihong,’ and yield is expected to decrease in the following year.

Due to recent abnormal weather caused by global warming, peach flowering has gradually accelerated, and spring frost damage caused by premature de-acclimation has increased. In this study, under a simulated spring frost environment using a Soil–Fruit–Daylit–System (SFDS) chamber, we investigated whether treatment with 2% cellulose nanocrystals (CNCs) could enhance the freezing tolerance of the flower buds from 2-year-old whole peach trees. Visual changes in the ice propagation were observed using an infrared camera at the same time. After the peach flower buds in the calyx red stage were placed in the SFDS chamber with a minimum temperature of −4 °C for ~20 h, the percentage of browning in the pistils and stamens was 57.0% in the control group and 14.1% in the group treated with 2% CNCs. During the first pink stage, the percentages of browning in the pistils and stamens in the control group and the group treated with 2% CNCs were 98.2% and 70.3%, respectively. However, when peach flower buds in the group treated with 2% CNCs were exposed to a −6 °C-targeted chamber, they could not mitigate frost injury. Almost all flower buds were damaged. Infrared thermal images showed that the first exotherm in the control group began at 2:33:03 am, whereas that of the group treated with 2% CNCs began at 3:01:33 am. The control started to express exothermic behavior at −4.2 °C, while the group treated with 2% CNCs started expressing exothermic behavior at −5.1 °C. Thus, treatment with 2% CNCs enhanced the freezing tolerance by −0.9 °C and delayed the first instance of exothermic behavior by ~28 min. These results indicate that treatment with 2% CNCs could mitigate the frost damage of peach flower buds in a frost environment of −5 °C.

This study investigated the effects of elevated temperature on the phenology and morphology of the early-maturing peach cultivar ‘Mihong’. The experiment was conducted from 2019 to 2024 in a temperature-gradient chamber at the National Institute of Horticultural and Herbal Science, Wanju, Korea, with four warming treatments (+2.2 °C to +5.0 °C above ambient). Higher temperatures delayed the onset of endodormancy and markedly shortened the period from endodormancy release to full bloom. Elevated temperatures also increased the LD ratio, with the proportion of fruits exceeding an LD ratio of 1.0 rising significantly with temperature. The LD ratio showed strong correlations with November mean temperature (MT11) and March maximum temperature (HT3) (r = 0.81) and was also associated with the average temperature (Temp3, r = 0.51) and duration (P3, r = −0.54) of the endodormancy release to full bloom phase. Stepwise and PLS regression identified temperatures in May, November, and March as key predictors of the LD ratio, while PCA revealed that temperature variables (Temp3, Temp5) and stage durations (P3, P4) were major contributors. These results confirm that climate warming alters the phenology and morphology of ‘Mihong’, reducing fruit quality and marketability, while providing a basis for predictive modeling and highlighting the importance of adaptive strategies such as shading or growth regulator application.