Research on plant disease control using fluorescent-type ultraviolet light (UV) lamps is well established; however, UV irradiation conditions using light-emitting diode (LED)-based lamps to control plant diseases remain poorly defined. In this study, we used LED UV lamps of different wavelengths (280, 308, and 330 nm) and investigated the UV irradiation conditions that effectively controlled strawberry anthracnose. The most effective strawberry anthracnose control was achieved with 280 nm irradiation, followed by 308 nm irradiation; 330 nm irradiation had negligible efficiency. The effectiveness of UV irradiation in controlling strawberry anthracnose varied among cultivars. In ‘Tochiotome’ and ‘Sagahonoka’, the incidence of strawberry anthracnose was significantly suppressed by UV irradiation at 280 nm. However, in ‘Benihoppe’, the disease was more severe than that in the other cultivars and did not respond to UV irradiation. Strawberry anthracnose suppression was achieved when UV irradiation was applied before pathogen inoculation, but not when administered solely after pathogen inoculation. Under the specified conditions of lamp height and irradiation duration, namely 110 cm/4.5 h, 110 cm/3 h, 90 cm/3 h, and 80 cm/1.5 h, leaf scorch was minimal, and an anthracnose control effect of more than 30% was observed. Irradiation with 280 nm UV for 2, 4, 7, 10, or 14 days before pathogen inoculation for a duration of 7–14 days was effective at controlling anthracnose. When plants were irradiated with 280 nm UV for 7 days and then infected with pathogen 0–16 days later without UV irradiation, the control effect continued for up to 12 days. This study demonstrated that 280 nm UV LED irradiation effectively controls strawberry anthracnose, affecting the aboveground parts, while also demonstrating irradiation conditions that achieve high control without inducing leaf scorch.

In this study, we compared changes in traits associated with fruit development and ripening in Taiwanese and Japanese cultivars of Japanese apricot (Prunus mume Sieb. et Zucc.). We also analyzed transcriptome profiles to comprehensively examine different fruit development and ripening patterns between the two groups in terms of fruit characteristics and gene expression. Early fruit development in Taiwanese cultivars ‘ST’ and ‘Ellching’ and the Japanese cultivar ‘Hakuo’ was ahead of that in other three Japanese cultivars (P1). From late April to early May, around the stone-hardening stage, the developmental differences decreased to the same level. Thereafter, Japanese cultivars showed rapid growth, whereas Taiwanese cultivars showed slower growth, reversing the developmental differences between these lines (P2). Ethylene production was not detected until the full ripening stage and was detected for the first time at this stage in five cultivars, except for ‘Ellching’ (P3). In contrast, no ethylene production was observed during the entire duration of fruit development in ‘Ellching’. A multidimensional scaling plot showed that the overall transcriptome profile changed according to the three stages (P1–P3) of fruit development and ripening. At P1, gene ontologies (GOs) related to cell division, such as the cell cycle and regulation of cyclin-dependent protein serine/threonine kinase activity, were enriched for differentially expressed genes downregulated in Taiwanese cultivars as compared with their expression in Japanese cultivars. At P2, GOs related to fruit development were not enriched, but some genes related to phytohormones, such as auxin, abscisic acid, and cytokinin, which are associated with fruit development and ripening, were differentially expressed. At P3, the expression of genes such as ACS, ACO, and PG, which are involved in ethylene biosynthesis, increased in response to increased ethylene production, but not in ‘Ellching’, which showed no ethylene production. Expression analysis of 115 NAC (NAM-ATAF1/2-CUC2) family genes, which are related to fruit ripening and ripening date in other fruit species, in the ‘Ellching’ genome revealed changes in expression of NAC056 and NAC073 corresponding to fruit development and ripening in Taiwanese and Japanese cultivars. We discuss the differences in fruit development and ripening behaviors between Taiwanese and Japanese cultivars in terms of physiological and transcriptome changes.

Vernalization is a process in which plants achieve the competence to flower in the upcoming spring through exposure to long-term cold like winter. Unlike cold acclimation (short-term cold stimulus), vernalization is not immediately triggered by exposure to temporary low temperature. It seems likely that vernalization is triggered by low temperatures during winter that set up stable changes that last until the upcoming spring when they trigger floral transition. Over several decades, extensive studies have been conducted to elucidate the molecular mechanisms underlying the vernalization-mediated floral transition process using Arabidopsis thaliana (Arabidopsis) model plants, as well as crop plants. Comprehensive knowledge of the molecular mechanisms underlying vernalization-mediated floral transitions in the model plant Arabidopsis has helped us explore and reveal the molecular mechanisms controlling floral transitions in other plants, especially Brassica crops. This review highlights the current understanding of the molecular characteristics underlying vernalization-mediated flowering in Arabidopsis, as well as in several horticultural Brassica crop plants.

Increasing the contents of γ-aminobutyric acid (GABA), a non-proteinogenic amino acid neurotransmitter known for its beneficial effects on human health, is an important objective in tomato (Solanum lycopersicum) breeding. Improving the nutritional content of fruits remains challenging for breeders, as measuring specific compounds is more labor-intensive than assessing fruit appearance. Therefore, using DNA markers is preferred as an effective, accurate, and simple method for testing nutritional traits. In this study, we identified a tomato line with higher GABA content from progeny derived from a cross with the wild tomato Solanum pennellii. Among S. lycopersicum × S. pennellii introgression lines, we initially obtained one line with higher GABA contents, but smaller fruit. To break the linkage between higher GABA contents and the closely linked small-fruit trait, we designed DNA markers around the genomic region conferring these traits and conducted large-scale genotyping of inbred populations over six generations and backcross populations. Finally, we selected two lines with a recombination event between the loci that regulate GABA production and fruit size, resulting in a tomato line with normal-sized fruits and high GABA levels. These lines and the associated DNA markers could be used in breeding to develop additional varieties with high GABA levels.

Yield prediction models can aid in scheduling harvests based on weather conditions. However, field cultivation introduces spatial variations in crop growth due to pests, disease, uneven fertilizer efficiency, soil conditions, and other factors, reducing prediction accuracy. To better reflect this spatial variability, this study developed a data assimilation method that integrates leaf area index (LAI) (m²·m⁻²) observations into a yield prediction model for spinach (Spinacia oleracea). Specifically, this study created a model to observe spinach LAI using image data obtained from unmanned aerial vehicles, compared observed LAI values based on the LAI observation model and estimated LAI values from an existing LAI estimation model with ground-measured LAI values. Then, the dry yield prediction accuracy using data assimilation of LAI observations and the LAI estimation model was evaluated. The results of the LAI observation model showed that although saturation problems occurred at the high LAI stage, the Red Edge Soil Adjusted Vegetation Index achieved the highest LAI observation accuracy due to its ability to reflect plant biomass changes and mitigate the influence of soil background. The observed LAI values showed higher accuracy than the estimated LAI values based on an existing LAI estimation model, as the developed LAI observation model used spatial growth information obtained from images to capture field LAI differences. This confirms that the LAI observation methodology can accurately monitor growth of processing spinach. The data assimilation method improved dry yield prediction accuracy, achieving higher accuracy (root mean squared error, 119.6 g·m⁻²; mean absolute percentage error, 24.7%) at 26 and 83 days after planting than the conventional method (147.3 g·m⁻² and 29.4%). This higher accuracy was attributed to its ability to reflect spatial variations of LAI through LAI observations. Although the effects of LAI observation frequency were limited, the timings obtained from the images showed critical effects: observation at 83 days, corresponding to LAI stages 3 to 4, was found to be suitable. This study demonstrates the effectiveness of assimilating LAI observations into spinach dry yield prediction models for processing applications, particularly with LAI observations conducted during the middle growth stage under the standard cultivation conditions.

Epigenetics is defined as “the study of changes in gene function that are mitotically and/or meiotically heritable and do not involve a change in DNA sequence”. Epigenetic modifications include post-translational modifications of histones and DNA methylation. Changes in DNA methylation have been observed in response to environmental factors, with some epimutations being heritable across generations. Such epimutations may lead to alterations in plant traits and could be involved in natural selection or domestication. Furthermore, epigenetic transcriptional regulation serves as a crucial strategy for responding to various environmental conditions, including abiotic and biotic stress. In horticultural crops, this regulation is implicated in diverse biological processes, including agronomic traits such as hybrid vigor/heterosis, flowering time, bud dormancy, sex determination, fruit ripening, and anthocyanin accumulation. Recent advances in methods for analyzing epigenetic states, along with advances in sequencing technology, have enabled high-resolution and genome-wide studies in various horticultural crops. This review highlights the critical role of epigenetic transcriptional regulation in biological processes in horticultural crops and discusses the potential for artificially inducing epigenetic variation to enhance phenotypic diversity in horticultural crop breeding.

Drought and global warming affect the photosynthesis and various physiological processes of plants in Asian forest ecosystems. Improving physiological responses is the best way to overcome challenges to survival under drought and higher temperatures. This study was conducted to appraise the role of silicon (Si) in enhancing the drought tolerance and chlorophyll fluorescence response in banyan trees (Ficus annulata) in a pot experiment for 18 days. Three treatments were tested: control (CF), drought (DT), and drought stress sprayed with Si (DS). At the end of the trial, Si foliar spray at a concentration of 15 mM significantly increased (P < 0.05) the leaf relative water content (RWC) by 90%, total chlorophyll by 3.3 mg·g⁻¹ FW, photosynthetic rate by 6.7 μmol CO₂·m⁻²·s⁻¹, stomatal conductance by 0.26 mol H₂O·m⁻²·s⁻¹, and transpiration rate by 2.7 μmol H₂O·m⁻²·s⁻¹. Moreover, ABS/RC, DIo/RC, TRo/RC, and ETo/RC were significantly lower than those under drought stress, while Fv/Fm and Pi were substantially higher than those under drought stress (P < 0.05). The levels of hydrogen peroxide (H₂O₂) production, electrolyte leakage (EL), and malondialdehyde (MDA) were considerably reduced during the drought stress experiment with Si spraying (P < 0.05). Foliar Si spraying did not enhance TSS content, but positively affected proline content (P > 0.05). The findings suggest that Si supplementation effectively improved the physiological responses, photosynthetic pigment content, and photochemical efficiency of F. annulata under drought conditions.

In open-field vegetable cultivation, soil fertility and abiotic stresses substantially affect growth. Therefore, growth diagnostic techniques considerably facilitate accurate yield estimation and stable shipping. Fertilizer application and post-rainfall moisture damage affect lettuce growth in open fields, resulting in frequent fluctuations in supply. Additionally, lettuce is often used as fresh food; however, its short shelf life in cold storage poses challenges for managing shipments. Thus, the aim of the present study was to clarify if growth diagnosis and yield prediction in lettuce can be achieved with a normalized difference vegetation index (NDVI) acquired by a drone equipped with a multispectral camera. In trials with four fertilization levels, the yield, growth parameters, and total nitrogen content differed based on the amount of fertilizer applied. Aerial images of the test plots were captured using a drone equipped with a multispectral camera in the early stage of heading, and NDVI values were calculated from the acquired images by extracting only the lettuce vegetation areas. In a regression analysis between NDVI and yield, the coefficient of determination (R²) was 0.87, while NDVI and total nitrogen was 0.77. The R² values were similar to or higher than those reported previously and were considered practical. Subsequently, a 48-h flood treatment was applied at the base of the lettuce plants to simulate wet damage caused by heavy rainfall. When compared under standard fertilization conditions, the waterlogged treatments produced lower yield and growth parameters than the non-flooded treatments. The values were comparable to those of the non-flooded treatment under no fertilizer conditions. NDVI values were calculated over time from before waterlogging treatment to harvest. Following treatment, there was an immediate decrease in NDVI values that persisted until harvest. Therefore, the NDVI value may serve as a growth indicator in stress conditions. In conclusion, it is feasible to diagnose growth and estimate yield reflecting nitrogen nutritional status by calculating NDVI values obtained from aerial images captured using a drone equipped with a multispectral camera during the early stage of lettuce heading.

Recent climate change has altered the timing of spring phenology (budbreak and flowering) in grapevines. Specific phenological stages serve as key indicators for agricultural production planning in grapevine cultivation, including disease and pest control and gibberellic acid treatment. Therefore, predicting phenology based on its relationship with temperature (the main environmental factor) has become increasingly important. Long-term phenology data can be used to evaluate the climate change impact to date and develop phenology models. Additionally, future climate change impact assessments can be performed by applying future temperature scenarios to phenology models. Furthermore, the use of long-term phenology data is expanding, including the estimation of temperature responses during dormancy using recently developed statistical analytic methods, such as partial least squares regression. This review firstly describes the relationship between spring phenology and temperature in grapevines, then summarizes the current trends in spring phenology affected by climate change using long-term records. Next, the development of temperature-dependent phenology models and future climate change impact assessments using these models are outlined, along with key considerations for their use. Finally, the usefulness of long-term data in developing highly accurate and robust process-based models is emphasized.

Understanding the leaf area index (LAI) dynamics of sweet potatoes grown under different nitrogen conditions is helpful for accurate yield estimation and management of nitrogen stress and fertilization. Therefore, the aim of this study was to clarify: 1) the effects of the nitrogen application rate (NiAR) on the LAI dynamics of sweet potatoes using logistic curves including the effective cumulative temperature and 2) the validity of the developed LAI estimation model considering the effects of NiAR. The results revealed that a higher NiAR resulted in a significantly higher maximum LAI and leaf expansion rate than a lower NiAR. The effects of NiAR on the thermal times of leaf expansion start and leaf senescence start differed among sweet potato cultivars. These differences may be related to the growth characteristics of the sweet potatoes grown under varying NiAR conditions. These results demonstrate that the LAI estimation model should be used separately, depending on the NiAR for each cultivar. Then, the applicability of the developed model was verified. The results showed that the accuracy of the LAI estimation was conditionally improved by using different model parameter configurations for NiAR. The reason for the improved accuracy could be that nitrogen is one of the dominant factors influencing the shoot growth dynamics of sweet potatoes. These results demonstrated the effectiveness of the developed model for LAI estimation using different NiAR configurations; however, further research is required to improve the estimation accuracy, robustness, and its applicability in various situations.