In contrast to fluorescent lamps and high-power sodium lamps, the use of light-emitting diode (LED) lamps enables the control of not only photosynthetic photon flux density (PPFD) at the plant level, but also the relative spectral photon flux density distribution (RSPD) of light because of the variety, even at different times of day, of producible light emitted by LEDs of different types. Effects of the spectral photon flux density on plant growth and morphology have been investigated using several types of LEDs and plant species. However, few studies on lighting methods with time-varying PPFD or RSPD have been published to date. In this paper, we summarize the effects of time-varying PPFD on the net photosynthetic rate (Pn) and those of time-varying RSPD on plant growth and morphology. Detailed modeling studies have been conducted on the reactions of the photosynthetic pathway under time-varying PPFD at a cycle of milliseconds to seconds. The results of these modeling studies and actual measurements of Pn under pulsed light clearly indicate that pulsed light is not advantageous to improve Pn. Although the integrated PPFD of blue and red light was unchanged, the growth of leaf lettuce was promoted by asynchronous irradiation with blue light and red light compared with growth under simultaneous irradiation. We think that blue-light monochromatic irradiation promotes leaf elongation through leaf expansion as a primary factor in the enhancement of plant growth. In addition, changes in leaf photosynthetic capacity caused by blue-light monochromatic irradiation may be involved in plant growth promotion. An increasing number of studies have investigated the effects of time-varying RSPD on plants. However, the mechanisms underlying these effects remain to be elucidated.
Recently, the number of patients with chronic kidney disease has increased rapidly and kidneys with loss of the K-defecating function have been observed. Thus, providing vegetables with low potassium is an urgent unmet need. In this study, two cultivation methods were used to cultivate lettuce (Lactuca sativa L.) with low K concentrations. One method, dubbed LKEC, was based on electrical conductance management and the K supply was stopped at the end of cultivation. The other method, dubbed LKQM, was based on nutrient quantitative management, and the nutrients required for low-K lettuce were quantitatively supplied. Meanwhile, control lettuce with a normal K concentration, known as CK, were cultivated with electrical conductance management. Compared with CK, both low K treatments reduced the yield by nearly 20% without any visual deficiency symptoms. There was no significant difference between LKEC and LKQM in terms of plant growth. LKQM-treated lettuce contained lower Na and required less fertilizer than LKEC lettuce. Moreover, these plants adapted to K deficiency stress by absorbing more cations to maintain osmotic pressure. N declined with decreasing K. This suggested that the quantitative management method in low-potassium lettuce production reduced the potassium content in the lettuce plants to the same level as the EC management method, and significantly reduced the sodium content compared to EC management.
Low-potassium crops are required for patients with kidney disease, and research on the production of low-potassium vegetables using hydroponics has been conducted. However, there are few studies on low-potassium fruit trees because the soil is generally cultivated. This study focused on blueberries that can be cultivated in a pot, by examining the production of low-potassium blueberry fruits cultured with fertigation in a greenhouse. In a pot culture using peat moss medium, the potassium levels were restricted from the flowering stage and from the fruit coloring stage, causing a decrease in the potassium content of the fruits by 53 and 35%, respectively, when compared with the control. A urethane sponge-based medium with free nutrient leaching was then evaluated to determine whether the potassium content of fruits decreased with short-term potassium restriction. The results showed a reduction in potassium content of 48% when potassium was restricted in the fruit coloring period. In addition, potassium was restricted for five months to determine whether long-term potassium restriction could further reduce the potassium content of fruits. The fruit potassium content did not differ between the second and fifth months after the potassium restriction, although symptoms of potassium deficiency appeared in mature leaves. From these results, it was suggested that the pot culture with fertigation was effective in producing low-potassium blueberry fruits, and the fruit potassium content can be halved by short-term potassium restriction using the urethane sponge-based medium. However, long-term potassium restriction was not effective in producing low-potassium blueberry fruits due to the appearance of symptoms of potassium deficiency.
Noninvasive diagnosis of internal traits in fruit crops is a high unmet need; however it generally requires time, costs, and special methods or facilities. Recent progress in deep neural network (or deep learning) techniques would allow easy, but highly accurate diagnosis with single RGB images, and the latest applications enable visualization of “the reasons for each diagnosis” by backpropagation of neural networks. Here, we propose an application of deep learning for image diagnosis on the classification of internal fruit traits, in this case seedlessness, in persimmon fruit (Diospyros kaki). We examined the classification of seedlessness in persimmon fruit by using four convolutional neural networks (CNN) models with various layer structures. With only 599 pictures of ‘Fuyu’ persimmon fruit from the fruit apex side, the neural networks successfully made a binary classification of seedless and seeded fruits with up to 85% accuracy. Among the four CNN models, the VGG16 model with the simplest layer structure showed the highest classification accuracy of 89%. Prediction values for the binary classification of seeded fruits were significantly increased in proportion to seed numbers in all four CNN models. Furthermore, explainable AI methods, such as Gradient-weighted Class Activation Mapping (Grad-CAM) and Guided Grad-CAM, allowed visualization of the parts and patterns contributing to the diagnosis. The results indicated that finer positions surrounding the apex, which correspond to hypothetical bulges derived from seeds, are an index for seeded fruits. These results suggest the novel potential of deep learning for noninvasive diagnosis of fruit internal traits using simple RGB images and also provide novel insights into previously unrecognized features of seeded/seedless fruits.
The number of leaves in ‘Delaware’ grape is an excellent indicator to determine the optimal timing for gibberellic acid (GA3) application to fruit clusters to induce seedless berries. To predict the optimal timing for GA3 application to ‘Delaware’ grape, we aimed to develop a method to estimate the accumulated leaf number (LN) on the second shoot (which grows from the second dormant bud from the end of the fruiting mother shoot) from the air temperature. This was undertaken using leafing data from a vineyard in Osaka, Japan from 1987 to 2019. Base temperature (Tb, °C), ranging from −2.5 to 12.5°C with step increases of 2.5°C, was estimated using the coefficient of regression determination (R2) between LN and effective accumulative temperature (EAT, °C·day) and two types of root mean square error (RMSE) (RMSE of LN and RMSE of the day when LN reached 10.0 leaves). The LN showed a good fit in linear regression with EAT at every Tb (−2.5 to 12.5°C); in particular, a Tb of 7.5°C yielded the highest R2 and the lowest RMSE. From these results, we determined that the Tb for leaf emergence of ‘Delaware’ grape was 7.5°C. We then compared the estimation accuracy in predicting leaf emergence using EAT (Tb of 7.5°C) (proposed method) and constant leaf emergence rate per day of 0.36 leaves·day−1 (conventional method). As the RMSE when using the proposed method was lower than the RMSE when using the conventional method, the proposed method was more suitable to predict of optimal timing for GA3 application than the conventional method. The findings of this study could be used to predict the optimal timing for GA3 application with high accuracy using LN on the measurement date and forecast values for temperature. Furthermore, the coefficient of the developed equation suggests that the ‘Delaware’ grape develops 4.0 leaves per EAT of 100°C·day with a Tb of 7.5°C.
Spring cabbage (Brassica oleracea var. capitata L.) is a crop type in which sowing is performed in fall and harvesting in spring. The flower bud differentiation, explained as the phase transition from the vegetative phase to reproductive phase, is induced by chilling after a certain plant size, then the risk of premature bolting is triggered by long days and high temperatures. Farmers empirically avoid bolting by selecting suitable varieties and sowing days. However, climate change may increase the risk of premature bolting. The objectives of this study were to evaluate the relationship between the number of head leaves at flower bud differentiation and premature bolting, and to develop a model to predict flower bud differentiation and the number of head leaves using data on the daily cumulative temperature. Firstly, we found that the risk of premature bolting was high for the ‘Kinkei-201’ cabbage variety when the number of head leaves (> 1 g) was less than 6.5 leaves in the flower bud differentiation period. The number of head leaves (> 1 g) (y) was estimated by the daily cumulative temperature (x): y = 0.0248x − 24.485 to 28.613, depending on year. The flower bud differentiation period was estimated based on the concept of the developmental rate (DVR) and the developmental index (DVI), in which the value of DVI at sowing was defined as 0 and that at the flower bud differentiation period as 1. Each parameter’s response to the cold treatment stage (RS) and the response to chilling (C) was estimated based on the daily mean temperature. The DVR model predicted the flower bud differentiation period in 2010–2014 with a root mean squared error = 5.3 days (without outliers). Therefore, the risk of premature bolting is predictable by estimating the number of head leaves (> 1 g) at the flower differentiation period using data on sowing date and mean temperature.
To elucidate the phytohormone profiles associated with various stages of growing and ripening of small watermelon fruits, small watermelon fruits were collected 7 to 35 days after flowering (DAF) and divided into rind, pulp, and seeds. Indole-3-acetic acid (IAA), abscisic acid (ABA), trans-zeatin (tZ), isopentenyl adenine (iP), jasmonic acid (JA), methyl jasmonate (MeJA), gibberellin1 (GA1), and gibberellin4 (GA4) from each tissue were simultaneously quantified by liquid chromatography mass spectrometry (LC-MS). From 7 to 28 DAF, pulp weight increased rapidly due to cellular expansion. The IAA concentration increased up to 21 DAF in seeds, but then decreased up to 35 DAF. Similar changes occurred in the pulp approximately 7 days after the pattern of rising and falling IAA levels in the seeds. The GA concentration was higher in the seeds, and peaked prior to the seed growth peak. The ABA level in the pulp peaked at the time of fruit enlargement (21 DAF). The concentrations of iP, GA1, and GA4 tended to decrease with growth in all tissues. The results revealed the changes in endogenous plant hormones involved in the growth of small watermelon fruit.
‘Micro-Tom’, a dwarf tomato cultivar, has been used as a convenient model system in tomato research. Previous studies have shown that several genes are involved in the phenotype, but to date no study has focused on the fruit weight. In this study, we tried to clarify genetic factors that regulate the fruit weight of ‘Micro-Tom’ using an F2 population derived from ‘Micro-Tom’ and ‘MPK-1’, a mid-size tomato cultivar. The F2 population showed a continuous and transgressive segregation in terms of fruit weight, suggesting that the fruit weight was regulated by multiple loci. To identify these loci, quantitative trait loci (QTL) analysis was performed. Three QTLs located on chromosomes 4, 7, and 9 were found to regulate fruit weight, and were designated as qfw4.1, qfw7.1, and qfw9.1. Of these QTLs, qfw4.1 exhibited the highest logarithm of the odds score. We confirmed the effect of qfw4.1 in the F3 population and showed that it regulates fruit weight without affecting locule number. In addition, being homozygous for the Micro-Tom allele at the marker linked to qfw4.1 reduced vegetative size, suggesting that qfw4.1 regulates not only fruit weight, but also vegetative size in ‘Micro-Tom’.
Fruit Brix is an important indicator in determining the quality of tomatoes (Solanum lycopersicum), and increasing it is an important objective. The production of high Brix tomatoes requires breeding and genetic studies of fruit. During domestication S. lycopersicum lost genetic variation of some wild tomato relative that could be useful for breeding. In this study, we investigated introgression lines (ILs) from a cross between the wild relative Solanum pennellii and the cultivated tomato S. lycopersicum ‘M82’. While there are many genetic and physiological studies that demonstrate the usefulness of tomato S. pennellii ILs, few have investigated the high Brix values of IL fruit. Accordingly, we attempted to detect tomato ILs that resulted in high Brix ripening fruit, in order to obtain valuable genetic and genomic resources for the investigation of phenotypes originating in the S. pennellii genome. IL5-4 may be a line that carries an S. pennellii chromosome segment on chromosome 5 of ‘M82’. Previous research indicated that IL5-4 fruit have higher Brix levels than ‘M82’ fruit. Our results corroborated these findings and revealed Brix changes in fruit during development. We also found that IL5-4 plants showed a higher incidence of blossom-end rot (BER), a major physiological disorder in tomatoes. Therefore, we investigated the physiological mechanism responsible for the higher incidence of BER in IL5-4, by focusing on calcium content, which may be related to BER occurrence. The total and water-soluble Ca contents of fruit tissues were significantly lower in IL5-4 than in ‘M82’ in the proximal part, while no differences were observed in the distal part. Thus, our results suggested that a higher incidence of BER in IL5-4 fruit may not be related to both total and water-soluble Ca contents in the distal fruit tissue, and genetic factors originating in the S. pennellii chromosome may induce high BER incidence in IL5-4. The characterization of IL5-4 in this study showed that it is a valuable genetic and genomic resource for high-Brix breeding stock and for the investigation of novel BER mechanisms.
Evergreen azalea is one of the most important ornamental shrubs and pot plants in temperate zones worldwide. In Japan, hundreds of azalea cultivars have been bred based on the genetic diversity of wild species and various accumulated mutants since the middle of the 17th century. Japanese cultivar groups such as Edo-kirishima, Kurume-tsutsuji, Ryūkyū-tsutsuji, Hirado-tsutsuji, and Satsuki have been developed by selection and crossing, and many cultivars have been exported to Western countries and utilized as breeding materials for pot and garden azalea. Rhododendron ripense Makino, which grows on riverside rocks and is endemic to Japan, is one of the best ornamental species because of its high adaptability to environmental conditions. We have focused on the genetic contribution of this wild species to evergreen azalea cultivars, and developed a PCR-RFLP identification marker of R. ripense cpDNA based on a species-specific sequence of the trn L-F region. The R. ripense cpDNA specific marker has been in Japanese large-flowered groups, all Ryūkyū and Ōkirishima cultivars, and half of all Hirado cultivars have the R. ripense cpDNA type. Most Japanese small flower cultivars, such as Edo-kirishima, Kurume and Satsuki have non-R. ripense type cpDNA. Italian large-flowered cultivars also tend to be the R. ripense cpDNA type. Furthermore, all pot azalea cultivars of the Indian and Simsii groups possess R. ripense type cpDNA. These results clarified the cytoplasmic contribution of R. ripense not only to Japanese large flower cultivars, but also to Western azalea cultivars. Although R. simsii has been considered to be the main ancestral species of pot azalea, R. ripense should be recognized as the cytoplasmic parent of these cultivars. The ornamental value and adaptive environmental trait originating from R. ripense should be reviewed to elucidate the development history of evergreen azalea cultivars.