Search

Japanese wasabi is traditionally cultivated in terraced fields with running stream water conditions which typically produce a high-quality of yield. Previous studies have explored some of the effects of water nutrient status under such conditions; however, the relationship between water nutrient status in these cultivation conditions and the growth and quality of wasabi is still completely unknown. We evaluated the effects of nutrient strength, inorganic nitrogen sources, and pH of the medium on the growth of wasabi plants. Then, we analyzed the photosynthetic capacity and the ionomes of two major Japanese wasabi cultivars ('Onimidori,' an early-growing green-stem type; and 'Mazuma No.1,' a late-growing red-stem type) grown under a range of pH conditions. These experiments were conducted using a hydroponic system. Wasabi plants showed the best shoot and root growth in 1/10- and 1/2-strength Hoagland's solution with a 50:50 ratio of NH4-N:NO3-N. On the basis of the accumulation patterns of NO3−, amino acids, and chlorophylls, the 1/10-strength nutrient solution provided optimal conditions for wasabi growth. For both wasabi cultivars, the best shoot and root growth was in medium at pH 6.0. The photosynthetic capacity of 'Onimidori' was greater than that of 'Mazuma No.1,' suggesting that this may contribute to the faster growth of 'Onimidori.' Ionome analyses revealed tissue-specific mineral accumulation patterns and their differences among different pH conditions and between the two cultivars. Ionome-based multiple-regression analysis revealed a relationship between element concentration profiles in the wasabi plants, especially those in root, and the shoot growth. Wasabi plants are ammonium-sensitive and nitrate-preferring plants, in addition to relatively low nutrient requirements for optimal growth. The results of this study describe the basic nutritional characteristics of wasabi plants. These findings represent an important step toward optimizing fertilization to control wasabi quality and growth in the traditional flooded cultivation system. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing is frequently used to monitor chlorophyll content, an important characteristic for assessing photosynthetic ability, health and defence against a variety of degenerative diseases. To obtain hyperspectral data, field portable spectroradiometers, such as Ocean Optics Hyperspectral Vis-NIR spectroradiometers and Analytical Spectral Devices FieldSpec series, have been widely used. The development of an affordable hyperspectral remote sensing system would be advantageous. Highly sensitive, affordable and cost-effective finger-tip size spectrometers have recently been released. In this study we investigate the potential of hyperspectral data obtained from such a compact spectrometer (C12880MA-10, Hamamatsu Photonics) for estimating chlorophyll content in Zizania latifolia. We also tested the efficacy of five pre-processing techniques (first derivative reflectance, continuum-removal transformation, de-trending, multiplicative scatter correction and standard normal variate) in conjunction with five machine learning algorithms. [ABSTRACT FROM AUTHOR]

Leaf chlorophyll content is used as a major indicator of plant stress and growth, and hyperspectral remote sensing is frequently used to monitor the chlorophyll content. Hyperspectral reflectance has been used to evaluate vegetation properties such as pigment content, plant structure and physiological features using portable spectroradiometers. However, the prices of these devices have not yet decreased to consumer-affordable levels, which prevents widespread use. In this study, a system based on a cost-effective fingertip-sized spectrometer (Colorcompass-LF, a total price for the proposed solution was approximately 1600 USD) was evaluated for its ability to estimate the chlorophyll contents of radish and wasabi leaves and was compared with the Analytical Spectral Devices FieldSpec4. The chlorophyll contents per leaf area (cm2) of radish were generally higher than those of wasabi and ranged from 42.20 to 94.39 μg/cm2 and 11.39 to 40.40 μg/cm2 for radish and wasabi, respectively. The chlorophyll content was estimated using regression models based on a one-dimensional convolutional neural network (1D-CNN) that was generated after the original reflectance from the spectrometer measurements was de-noised. The results from an independent validation dataset confirmed the good performance of the Colorcompass-LF after spectral correction using a second-degree polynomial, and very similar estimation accuracies were obtained for the measurements from the FieldSpec4. The coefficients of determination of the regression models based on 1D-CNN were almost same (with R2 = 0.94) and the ratios of performance to deviation based on reflectance after spectral correction using a second-degree polynomial for the Colorcompass-LF and the FieldSpec4 were 4.31 and 4.33, respectively. [ABSTRACT FROM AUTHOR]

Phenotypic differences among breeding lines that introduce the same superior gene allele can be a barrier to effective development of cultivars with desirable traits in some crop species. For example, a deficient mutation of the Protein Disulfide Isomerase Like 1–1 (PDIL1-1) gene can cause accumulation of glutelin seed storage protein precursors in rice endosperm, and improves rice flour characteristics and food processing properties. However, the gene must be expressed to be useful. A deficient mutant allele of PDIL1-1 was introduced into two rice cultivars with different genetic backgrounds (Koshihikari and Oonari). The grain components, agronomic traits, and rice flour and food processing properties of the resulting lines were evaluated. The two breeding lines had similar seed storage protein accumulation, amylose content, and low-molecular-weight metabolites. However, only the Koshihikari breeding line had high flour quality and was highly suitable for rice bread, noodles, and sponge cake, evidence of the formation of high-molecular-weight protein complexes in the endosperm. Transcriptome analysis revealed that mRNA levels of fourteen PDI, Ero1, and BiP genes were increased in the Koshihikari breeding line, whereas this change was not observed in the Oonari breeding line. We elucidated part of the molecular basis of the phenotypic differences between two breeding lines possessing the same mutant allele in different genetic backgrounds. The results suggest that certain genetic backgrounds can negate the beneficial effect of the PDIL1-1 mutant allele. Better understanding of the molecular basis for such interactions may accelerate future breeding of novel rice cultivars to meet the strong demand for gluten-free foods. [ABSTRACT FROM AUTHOR]

Spectroscopic sensing provides physical and chemical information in a non-destructive and rapid manner. To develop non-destructive estimation methods of tea quality-related metabolites in fresh leaves, we estimated the contents of free amino acids, catechins, and caffeine in fresh tea leaves using visible to short-wave infrared hyperspectral reflectance data and machine learning algorithms. We acquired these data from approximately 200 new leaves with various status and then constructed the regression model in the combination of six spectral patterns with pre-processing and five algorithms. In most phenotypes, the combination of de-trending pre-processing and Cubist algorithms was robustly selected as the best combination in each round over 100 repetitions that were evaluated based on the ratio of performance to deviation (RPD) values. The mean RPD values were ranged from 1.1 to 2.7 and most of them were above the acceptable or accurate threshold (RPD = 1.4 or 2.0, respectively). Data-based sensitivity analysis identified the important hyperspectral regions around 1500 and 2000 nm. Present spectroscopic approaches indicate that most tea quality-related metabolites can be estimated non-destructively, and pre-processing techniques help to improve its accuracy. [ABSTRACT FROM AUTHOR]

Changes in chlorophyll content can be a good indicator of disease as well as nutritional and environmental stresses on plants. Several pre-processing techniques have been proposed for reducing noise from spectral data to identify vegetation properties such as chlorophyll content. Machine learning algorithms have also been applied to assess biochemical properties; however, an approach integrating pre-processing techniques and machine learning algorithms has not been fully evaluated. Therefore, this study evaluates the effectiveness of five pre-processing techniques used in conjunction with five machine learning algorithms for estimating chlorophyll content in two wasabi cultivars. Overall, incorporating pre-processing techniques was effective for obtaining estimated values with high accuracy. Analyses utilizing both pre-processing and machine learning performed best in 88 of 100 repetitions. The kernel–based extreme learning machine (KELM) and Cubist algorithms yielded the highest performance and achieved the highest accuracies in 54 and 26 of 100 repetitions, respectively. [ABSTRACT FROM AUTHOR]

Plant albinism causes the etiolation of leaves because of factors such as deficiency of chloroplasts or chlorophylls. In general, albino tea leaves accumulate higher free amino acid (FAA) contents than do conventional green tea leaves. To explore the metabolic changes of etiolated leaves (EL) in the light-sensitive Japanese albino tea cultivar "Koganemidori," we performed integrated metabolome and transcriptome analyses by comparing EL with green leaves induced by bud-sport mutation (BM) or shading treatments (S-EL). Comparative omics analyses indicated that etiolation-induced molecular responses were independent of the light environment and were largely influenced by the etiolation itself. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and pathway analyses revealed the downregulation of genes involved in chloroplast development and chlorophyll biosynthesis and upregulation of protein degradation-related pathways, such as the ubiquitin-proteasome system and autophagy in EL. Metabolome analysis showed that most quantified FAAs in EL were highly accumulated compared with those in BM and S-EL. Genes involved in the tricarboxylic acid (TCA) cycle, nitrogen assimilation, and the urea cycle, including the drastically downregulated Arginase-1 homolog, which functions in nitrogen excretion for recycling, showed lower expression levels in EL. The high FAA contents in EL might result from the increased FAA pool and nitrogen source contributed by protein degradation, low N consumption, and stagnation of the urea cycle rather than through enhanced amino acid biosynthesis. [ABSTRACT FROM AUTHOR]

Shade cultivation is a traditional Japanese tea cultivation method in which the shoot buds are shaded for several weeks. This technique is increasingly used for green tea production because it produces tea of high quality (as indicated by umami and nutritional content) and commands high prices. However, given that shaded tea plants are grown under low-light stress, concerns exist regarding damage to tea plants caused by repeated shade cultivation. To understand basic physiological responses and accumulative changes in photosynthetic ability and metabolites of tea plants subjected to repeated shading, we performed a pot experiment on immature tea plants grown in a growth chamber subjected to repeated shading treatments. The results demonstrated that shade cultivation caused a decrease in non-structural carbohydrate content and an increase of several degrees in leaf surface temperature, reflecting transpiration through the leaf stomata, as a result of a reduction in photosynthetic ability. An increase of several degrees in canopy temperature and a reduction in photosynthetic ability in the field in the mid-summer season was also observed in overstressed tea plants subjected to repeated shading. Metabolomic analysis identified several candidate biomarkers, such as citrulline and glycine betaine, that were significantly changed in individuals affected by shade cultivation. These physiological changes may be an indicator of the stress status of tea plants grown under repeated shade cultivation. [ABSTRACT FROM AUTHOR]

The growth of tea plants (Camellia sinensis L.) is promoted by the presence of aluminum (Al), a beneficial element under acidic conditions, but the influence of rhizosphere pH on this interaction is not known. To understand the mechanisms underlying the adaptation to acidic rhizosphere conditions, we evaluated ionome profiles and the effect of pH on tea growth in hydroponic culture. The optimum pH for tea growth was around pH 4.2, and growth was inferior under a pH less than 3.8 or higher than 5.0. Under the optimum pH growth and Al accumulation were markedly stimulated by Al treatment. Al content and accumulation in new and mature leaves and new roots (the predominant tissues that accumulate minerals in tea plants) gradually declined with decrease in pH, especially in new roots. Ionome profiles drastically altered Al treatment, but changes were more pronounced in new roots than in new or mature leaves and did not depend on pH. Although the uptake of most cationic minerals in new roots was decreased by Al treatment, cationic mineral contents in new and mature leaves were not decreased by Al. In contrast to other plant species, the content and accumulation of manganese, despite it being a cationic nutrient, were significantly increased by Al treatment. These results indicated that one role of Al as a beneficial element was to maintain the shoot nutrient status by effectively utilizing Al‐limited elements in the roots. [ABSTRACT FROM AUTHOR]

The improvement of leaf net photosynthetic rate (A n) is a major challenge in enhancing crop productivity. However, the genetic control of A n among natural genetic accessions is still poorly understood. The high-yielding indica cultivar Takanari has the highest A n of all rice cultivars, 20–30% higher than that of the high-quality japonica cultivar Koshihikari. By using reciprocal backcross inbred lines and chromosome segment substitution lines derived from a cross between Takanari and Koshihikari, we identified three quantitative trait loci (QTLs) where the Takanari alleles enhanced A n in plants with a Koshihikari genetic background and five QTLs where the Koshihikari alleles enhanced A n in plants with a Takanari genetic background. Two QTLs were expressed in plants with both backgrounds (type I QTL). The expression of other QTLs depended strongly on genetic background (type II QTL). These beneficial alleles increased stomatal conductance, the initial slope of A n versus intercellular CO2 concentration, or A n at CO2 saturation. Pyramiding of these alleles consistently increased A n. Some alleles positively affected biomass production and grain yield. These alleles associated with photosynthesis and yield can be a valuable tool in rice breeding programs via DNA marker-assisted selection. [ABSTRACT FROM AUTHOR]

To obtain genetic information about the germplasm of tea (Camellia sinensis L.) in Japan, 167 accessions including 138 var. sinensis (96 Japanese var. sinensis and 42 exotic var. sinensis) and 29 Assam hybrids were analyzed using single nucleotide polymorphisms (SNPs) markers identified by double-digest restriction-site-associated DNA sequencing (ddRAD-seq) analysis. Approximately 10,000 SNPs were identified by ddRAD-seq and were mapped across the whole genome. The 167 tea accessions were classified into three genetic subgroups: (1) Japanese var. sinensis; (2) Japanese and exotic var. sinensis; (3) Assam hybrids and exotic var. sinensis. Leaf morphology varied widely within each genetic subgroups. The 96 Japanese var. sinensis were classified into four genetic subgroups as follows; two subgroups of Shizuoka (the largest tea production region) landraces, Uji (most ancient tea production region) landraces, and the pedigree of ‘Yabukita’, the leading green tea cultivar in Japan. These results indicated that the SNP markers obtained from ddRAD-seq are a useful tool to investigate the geographical background and breeding history of Japanese tea. This genetic information revealed the ancestral admixture situation of the ‘Yabukita’ pedigree, and showed that the genome structure of ‘Yabukita’ is clearly different from those of other Japanese accessions. [ABSTRACT FROM AUTHOR]

Endogenous nicotine was confirmed to be present in tea plants (Camellia sinensis L.) by liquid chromatography-tandem mass spectrometry of tea samples from tea-producing regions in six Asian countries. All samples contained nicotine (0.011–0.694 μg g−1 dry weight). Nicotine contents remained constant during manufacturing of green, oolong and black teas, implying that nicotine is stable against heating, drying, enzymatic oxidation and mechanical damage during processing. Flower buds and seeds of cultivar Yabukita also contained nicotine (0.030–0.041 μg g−1 dry weight). A comparison of two cultivars revealed that higher nicotine contents were found in the black tea cultivar Benifuki. All plant parts of hydroponic Yabukita contained nicotine (0.003–0.013 μg g−1 dry weight). Tea cells cultured in B5 medium as well as roots and stems of tea seedlings contained nicotine levels similar to those of new leaves from field-grown plants. Although the levels of endogenous nicotine in tea plants are extremely low and sample contamination cannot be discounted, these levels exceed the maximum acceptable limit in Japan (0.01 μg g−1 dry weight). [ABSTRACT FROM AUTHOR]

Higher sterol content regulated by CYP51 with concomitant lower phospholipid contents in root tips results in higher aluminium tolerance. This strategy is common to different varieties of plant species.Several studies have shown that differences in lipid composition and in the lipid biosynthetic pathway affect the aluminium (Al) tolerance of plants, but little is known about the molecular mechanisms underlying these differences. Phospholipids create a negative charge at the surface of the plasma membrane and enhance Al sensitivity as a result of the accumulation of positively charged Al3+ ions. The phospholipids will be balanced by other electrically neutral lipids, such as sterols. In the present research, Al tolerance was compared among pea (Pisum sativum) genotypes. Compared with Al-tolerant genotypes, the Al-sensitive genotype accumulated more Al in the root tip, had a less intact plasma membrane, and showed a lower expression level of PsCYP51, which encodes obtusifoliol-14α-demethylase (OBT 14DM), a key sterol biosynthetic enzyme. The ratio of phospholipids to sterols was higher in the sensitive genotype than in the tolerant genotypes, suggesting that the sterol biosynthetic pathway plays an important role in Al tolerance. Consistent with this idea, a transgenic Arabidopsis thaliana line with knocked-down AtCYP51 expression showed an Al-sensitive phenotype. Uniconazole-P, an inhibitor of OBT 14DM, suppressed the Al tolerance of Al-tolerant genotypes of maize (Zea mays), sorghum (Sorghum bicolor), rice (Oryza sativa), wheat (Triticum aestivum), and triticale (×Triticosecale Wittmark cv. Currency). These results suggest that increased sterol content, regulated by CYP51, with concomitant lower phospholipid content in the root tip, results in lower negativity of the plasma membrane. This appears to be a common strategy for Al tolerance among several plant species. [ABSTRACT FROM AUTHOR]

The green tea leaf was dipped in the CsCl solution to elucidate the dissolution behavior of Cs. The IP observation showed that Cs was not uniformly adsorbed on the tea leaf, even if the tea leaf was dipped in the homogeneous solution. The activation energy of Cs dissolution was estimated to be 0.045 eV, indicating that most of Cs would exist as the adsorbed state. The dissolution behaviors as a function of cesium and potassium concentrations and pH, were also studied. [ABSTRACT FROM AUTHOR]

Rings or arcs of fungus-stimulated plant growth occur worldwide; these are commonly referred to as 'fairy rings'. In 2010, we discovered 2-azahypoxanthine (AHX), a compound responsible for the fairy-ring phenomenon caused by fungus; AHX stimulated the growth of all the plants tested. Herein, we reveal the isolation and structure determination of a common metabolite of AHX in plants, 2-aza-8-oxohypoxanthine (AOH). AHX is chemically synthesized from 5-aminoimidazole-4-carboxamide (AICA), and AHX can be converted into AOH by xanthine oxidase. AICA is one of the members of the purine metabolic pathway in animals, plants, and microorganisms. However, further metabolism of AICA remains elusive. Based on these results and facts, we hypothesized that plants themselves produce AHX and AOH through a pathway similar to the chemical synthesis. Herein, we demonstrate the existence of endogenous AHX and AOH and a novel purine pathway to produce them in plants. [ABSTRACT FROM AUTHOR]

Rings or arcs of fungus-stimulated plant growth occur worldwide; these are commonly referred to as 'fairy rings'. In 2010, we discovered 2-azahypoxanthine (AHX), a compound responsible for the fairy-ring phenomenon caused by fungus; AHX stimulated the growth of all the plants tested. Herein, we reveal the isolation and structure determination of a common metabolite of AHX in plants, 2-aza-8-oxohypoxanthine (AOH). AHX is chemically synthesized from 5-aminoimidazole-4-carboxamide (AICA), and AHX can be converted into AOH by xanthine oxidase. AICA is one of the members of the purine metabolic pathway in animals, plants, and microorganisms. However, further metabolism of AICA remains elusive. Based on these results and facts, we hypothesized that plants themselves produce AHX and AOH through a pathway similar to the chemical synthesis. Herein, we demonstrate the existence of endogenous AHX and AOH and a novel purine pathway to produce them in plants. [ABSTRACT FROM AUTHOR]

The Arabidopsis (Arabidopsis thaliana) mutant stopT1 (for sensitive to proton rhizotoxicityl) carries a missense mutation at an essential domain of the histidine-2-cysteine-2 zinc finger protein STOP1. Transcriptome analyses revealed that various genes were down-regulated in the mutant, indicating that STOP1 is involved in signal transduction pathways regulating aluminum (Al)- and H+-responsive gene expression. The Al hypersensitivity of the mutant could be caused by down-regulation of AtALMT1 (for Arabidopsis ALUMINUM-ACTIVATED MA LATE TRANSPORTERT1) and ALS3 (ALUMINUM-SENSITIVE3). This hypothesis was supported by comparison of Al tolerance among T-DNA insertion lines and a transgenic stop mutant carrying cauliflower mosaic virus 35S::AtALMT1. All T-DNA insertion lines of STOP1, AtALMT7, and ALS3 were sensitive to Al, but introduction of cauliflower mosaic virus 35S::AtALMT1 did not completely restore the Al tolerance of the stop1 mutant. Down-regulation of various genes involved in ion homeostasis and pH-regulating metabolism in the mutant was also identified by microarray analyses. CBL-!NTERACTING PROTEIN KINASE23, regulating a major K+ transporter, and a sulfate transporter, SULT3;5, were down-regulated in the mutant. In addition, integral profiling of the metabolites and transcripts revealed that pH-regulating metabolic pathways, such as the γ-aminobutyric acid shunt and biochemical pH stat pathways, are down-regulated in the mutant. These changes could explain the H+ hypersensitivity of the mutant and would make the mutant more susceptible in acid soil stress than other Al-hypersensitive T-DNA insertion lines. Finally, we showed that STOP1 is localized to the nucleus, suggesting that the protein regulates the expression of multiple genes that protect Arabidopsis from Al and H+ toxicities, possibly as a transcription factor. [ABSTRACT FROM AUTHOR]

Background: Rhizotoxic ions in problem soils inhibit nutrient and water acquisition by roots, which in turn leads to reduced crop yields. Previous studies on the effects of rhizotoxic ions on root growth and physiological functions suggested that some mechanisms were common to all rhizotoxins, while others were more specific. To understand this complex system, we performed comparative transcriptomic analysis with various rhizotoxic ions, followed by bioinformatics analysis, in the model plant Arabidopsis thaliana. Results: Roots of Arabidopsis were treated with the major rhizotoxic stressors, aluminum (Al) ions, cadmium (Cd) ions, copper (Cu) ions and sodium (NaCl) chloride, and the gene expression responses were analyzed by DNA array technology. The top 2.5% of genes whose expression was most increased by each stressor were compared with identify common and specific gene expression responses induced by these stressors. A number of genes encoding glutathione-S-transferases, peroxidases, Ca-binding proteins and a trehalose-synthesizing enzyme were induced by all stressors. In contrast, gene ontological categorization identified sets of genes uniquely induced by each stressor, with distinct patterns of biological processes and molecular function. These contained known resistance genes for each stressor, such as AtALMT1 (encoding Al-activated malate transporter) in the Al-specific group and DREB (encoding dehydration responsive element binding protein) in the NaCl-specific group. These gene groups are likely to reflect the common and differential cellular responses and the induction of defense systems in response to each ion. We also identified co-expressed gene groups specific to rhizotoxic ions, which might aid further detailed investigation of the response mechanisms. Conclusion: In order to understand the complex responses of roots to rhizotoxic ions, we performed comparative transcriptomic analysis followed by bioinformatics characterization. Our analyses revealed that both general and specific genes were induced in Arabidopsis roots exposed to various rhizotoxic ions. Several defense systems, such as the production of reactive oxygen species and disturbance of Ca homeostasis, were triggered by all stressors, while specific defense genes were also induced by individual stressors. Similar studies in different plant species could help to clarify the resistance mechanisms at the molecular level to provide information that can be utilized for marker-assisted selection. [ABSTRACT FROM AUTHOR]

Root growth of Arabidopsis thaliana is inhibited by proton rhizotoxicity in low ionic strength media when the pH of the medium is lower than 5.0. QTL analysis at pH 4.7 revealed that two major QTLs on chromosome 2 and 5 and an additional six epistatic interacting loci pairs control proton resistance in the L er/Col recombinant inbred population. These genetic factors are independently associated with proton resistance in comparison to the known Al resistant QTL and epistases detected in the same RI population at 4 μM Al at pH 5.0. This indicates that different genetic factors regulate mechanisms of resistance to each stress in this plant species. No correlation was observed between proton resistance and Al resistance among 260 accessions indicating that there is no simple relationship between the genetic factors controlling each trait. Several accessions with different combinations of proton (pH 4.7) and Al (4 μM Al at pH 5.0) resistances were identified by phenotypic cluster analysis. Although this grouping was performed using root growth data, the degree of resistance was correlated with their sensitivity to short-term damage in the root tip, indicating that the same resistance mechanism controls proton resistance at different time scales. Resistant accessions grew better than sensitive ones in acid soil culture. This suggests that proton resistance in hydroponic conditions could be an important index in breeding programs to improve productivity in acid soil, at least in acid sensitive plant species. [ABSTRACT FROM AUTHOR]

Acid soil syndrome causes severe yield losses in various crop plants because of the rhizotoxicities of ions, such as aluminum (Al3+). Although protons (H+) could be also major rhizotoxicants in some soil types, molecular mechanisms of their tolerance have not been identified yet. One mutant that was hypersensitive to H+ rhizotoxicity was isolated from ethyl methanesulfonate mutagenized seeds, and a single recessive mutation was found on chromosome 1. Positional cloning followed by genomic sequence analysis revealed that a missense mutation in the zinc finger domain in a predicted Cys2His2-type zinc finger protein, namely sensitive to proton rhizotoxicity (STOP)1, is the cause of hypersensitivity to H+ rhizotoxicity. The STOP1 protein belongs to a functionally unidentified subfamily of zinc finger proteins, which consists of two members in Arabidopsis based on a Blast search. The stop 1 mutation resulted in no effects on cadmium, copper, lanthanum, man- ganese and sodium chloride sensitivitities, whereas it caused hypersensitivity to Al3+ rhizotoxicity. This stop I mutant lacked the induction of the AtALMT1 gene encoding a malate transporter, which is concomitant with Al-induced malate exudation. There was no induction of AtALMT1 by Al3+ treatment in the stop 1 mutant. These results indicate that STOP1 plays a critical role in Arabidopsis tolerance to major stress factors in acid soils. [ABSTRACT FROM AUTHOR]

Effectively using genomic information greatly accelerates conventional breeding and applying it to long-lived crops promotes the conversion to genomic breeding. Because tea plants are bred using conventional methods, we evaluated the potential of genomic predictions (GPs) and genome-wide association studies (GWASs) for the genetic breeding of tea quality-related metabolites using genome-wide single nucleotide polymorphisms (SNPs) detected from restriction site-associated DNA sequencing of 150 tea accessions. The present GP, based on genome-wide SNPs, and six models produced moderate prediction accuracy values (r) for the levels of most catechins, represented by (−)-epigallocatechin gallate (r = 0.32–0.41) and caffeine (r = 0.44–0.51), but low r values for free amino acids and chlorophylls. Integrated analysis of GWAS and GP detected potential candidate genes for each metabolite using 80–160 top-ranked SNPs that resulted in the maximum cumulative prediction value. Applying GPs and GWASs to tea accession traits will contribute to genomics-assisted tea breeding. [ABSTRACT FROM AUTHOR]

Nondestructive techniques for estimating nitrogen (N) status are essential tools for optimizing N fertilization input and reducing the environmental impact of agricultural N management, especially in green tea cultivation, which is notably problematic. Previously, hyperspectral indices for chlorophyll (Chl) estimation, namely a green peak and red edge in the visible region, have been identified and used for N estimation because leaf N content closely related to Chl content in green leaves. Herein, datasets of N and Chl contents, and visible and near-infrared hyperspectral reflectance, derived from green leaves under various N nutrient conditions and albino yellow leaves were obtained. A regression model was then constructed using several machine learning algorithms and preprocessing techniques. Machine learning algorithms achieved high-performance models for N and Chl content, ensuring an accuracy threshold of 1.4 or 2.0 based on the ratio of performance to deviation values. Data-based sensitivity analysis through integration of the green and yellow leaves datasets identified clear differences in reflectance to estimate N and Chl contents, especially at 1325–1575 nm, suggesting an N content-specific region. These findings will enable the nondestructive estimation of leaf N content in tea plants and contribute advanced indices for nondestructive tracking of N status in crops. [ABSTRACT FROM AUTHOR]

Japanese horseradish (wasabi) grows in very specific conditions, and recent environmental climate changes have damaged wasabi production. In addition, the optimal culture methods are not well known, and it is becoming increasingly difficult for incipient farmers to cultivate it. Chlorophyll a, b and carotenoid contents, as well as their allocation, could be an adequate indicator in evaluating its production and environmental stress; thus, developing an in situ method to monitor photosynthetic pigments based on reflectance could be useful for agricultural management. Besides original reflectance (OR), five pre-processing techniques, namely, first derivative reflectance (FDR), continuum-removed (CR), de-trending (DT), multiplicative scatter correction (MSC), and standard normal variate transformation (SNV), were compared to assess the accuracy of the estimation. Furthermore, five machine learning algorithms—random forest (RF), support vector machine (SVM), kernel-based extreme learning machine (KELM), Cubist, and Stochastic Gradient Boosting (SGB)—were considered. To classify the samples under different pH or sulphur ion concentration conditions, the end of the red edge bands was effective for OR, FDR, DT, MSC, and SNV, while a green-peak band was effective for CR. Overall, KELM and Cubist showed high performance and incorporating pre-processing techniques was effective for obtaining estimated values with high accuracy. The best combinations were found to be DT–KELM for chl a (RPD = 1.511–5.17, RMSE = 1.23–3.62 μg cm−2) and chl a:b (RPD = 0.73–3.17, RMSE = 0.13–0.60); CR–KELM for chl b (RPD = 1.92–5.06, RMSE = 0.41–1.03 μg cm−2) and chl a:car (RPD = 1.31–3.23, RMSE = 0.26–0.50); SNV–Cubist for car (RPD = 1.63–3.32, RMSE = 0.31–1.89 μg cm−2); and DT–Cubist for chl:car (RPD = 1.53–3.96, RMSE = 0.27–0.74). [ABSTRACT FROM AUTHOR]