Changes in the nitrogen footprint of green tea consumption in Japan from 1965 to 2016.

Heavy application of nitrogen (N) in tea (Camellia sinensis (L.)) plantations causes various environmental problems. To date, studies on N flows have been limited to the tea plantation level, but the crucial drivers of N flows are consumers, not farmers. Therefore, this study aimed to evaluate changes in N flows concerning green tea production and consumption in Japan from 1965 to 2016 using the N footprint concept. Nitrogen use efficiency (NUE), virtual N factor (VNF), and N footprint were calculated using a Monte Carlo method from data for 17 parameters obtained from the literature review. The VNF for green tea in Japan decreased from 54.5 in 1991 to 30.8 in 2016. The major reasons for this decrease were (i) increased NUE in plantations and (ii) increased consumption of ready-to-drink (RTD) tea, matcha, and powdered tea, indicating an increase in the efficiency of N intake from green tea by consumers. The decrease in VNF resulted in a reduction in N footprint from green tea consumption. However, the decline in N footprint since 2004 is not derived from the decrease in VNF but mainly from reduced green tea consumption. A sensitivity analysis revealed that the parameters associated with the extraction efficiency of tea, powdered tea production, and the amount of tea leaves used for RTD production strongly affected VNF estimation.

Potential of spectroscopic analyses for non-destructive estimation of tea quality-related metabolites in fresh new leaves.

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.

Dissection of hyperspectral reflectance to estimate nitrogen and chlorophyll contents in tea leaves based on machine learning algorithms.

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.

Enrichment of Comammox and Nitrite-Oxidizing Nitrospira From Acidic Soils.

In agricultural soils fertilized with a high amount of ammonium nitrogen, the pH decreases because of the oxidation of ammonia by nitrifiers. Molecular-based analyses have revealed that members of the genus Nitrospira dominate over other nitrifiers in some acidic soils. However, terrestrial Nitrospira are rarely cultivated and little is known about their ecophysiology. In addition, recent studies discovered a single microbe with the potential to oxidize both ammonia and nitrite (complete ammonia oxidizer; comammox) within Nitrospira, which had been previously recognized as a nitrite oxidizer. Despite their broad distribution, there are no enrichment samples of comammox from terrestrial or acidic environments. Here, we report the selective enrichment of both comammox and nitrite-oxidizing Nitrospira from the acidic soil of a heavily fertilized tea field. Long-term enrichment was performed with two individual continuous-feeding bioreactors capable of controlling ammonia or nitrite concentration and pH. We found that excessive ammonium supply was a key factor to enhance the growth of comammox Nitrospira under acidic conditions. Additionally, a low concentration of nitrite was fed to prevent the accumulation of free nitrous acid and inhibition of cell growth under low pH, resulting in the selective enrichment of nitrite-oxidizing Nitrospira. Based on 16S rRNA gene analysis, Nitrospira accounting for only 1.2% in an initial soil increased to approximately 80% of the total microorganisms in both ammonia- and nitrite-fed bioreactors. Furthermore, amoA amplicon sequencing revealed that two phylotypes belonging to comammox clade A were enriched in an ammonia-fed bioreactor. One group was closely related to previously cultivated strains, and the other was classified into a different cluster consisting of only uncultivated representatives. These two groups coexisted in the bioreactor controlled at pH 6.0, but the latter became dominant after the pH decreased to 5.5. Additionally, a physiological experiment revealed that the enrichment sample oxidizes ammonia at pH <4, which is in accordance with the strongly acidic tea field soil; this value is lower than the active pH range of isolated acid-adapted nitrifiers. In conclusion, we successfully enriched multiple phylotypes of comammox and nitrite-oxidizing Nitrospira and revealed that the pH and concentrations of protonated N-compounds were potential niche determinants.

Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms.

Tea trees are kept in shaded locations to increase their chlorophyll content, which influences green tea quality. Therefore, monitoring change in chlorophyll content under low light conditions is important for managing tea trees and producing high-quality green tea. Hyperspectral remote sensing is one of the most frequently used methods for estimating chlorophyll content. Numerous studies based on data collected under relatively low-stress conditions and many hyperspectral indices and radiative transfer models show that shade-grown tea performs poorly. The performance of four machine learning algorithms-random forest, support vector machine, deep belief nets, and kernel-based extreme learning machine (KELM)-in evaluating data collected from tea leaves cultivated under different shade treatments was tested. KELM performed best with a root-mean-square error of 8.94 ± 3.05 µg cm-2 and performance to deviation values from 1.70 to 8.04 for the test data. These results suggest that a combination of hyperspectral reflectance and KELM has the potential to trace changes in the chlorophyll content of shaded tea leaves.

Effect of shading intensity on morphological and color traits and on chemical components of new tea (Camellia sinensis L.) shoots under direct covering cultivation.

BACKGROUND: Use of covering cultivation to shade tea (Camellia sinensis L.) trees to produce high-quality, high-priced green tea has recently increased in Japan. Knowledge of shading effects on morphological and color traits and on chemical components of new tea shoots is important for product quality and productivity. We assessed these traits of tea shoots and their relationships under covering cultivation of various radiation intensities. RESULTS: Leaf thickness, leaf mass per area, and leaf density of new tea leaves were smaller under covering culture than under open-field culture. SPAD values and chlorophyll contents were larger under covering culture than under open culture. The derived exponential equation for estimating chlorophyll contents from SPAD values was improved by considering leaf thickness. Covering culture decreased epicatechin and epigallocatechin contents, and increased theanine and caffeine contents. Principal component analysis on shoot and leaf traits indicated that leaf mass per area, chlorophyll, epicatechin, and epigallocatechin contents were strongly associated with shading effects. CONCLUSION: The morphological traits, color traits, and chemical components of new tea shoots and leaves varied depending on radiation intensity, shoot growth, and cropping season. These findings are useful for covering cultivation with high quality and high productivity in tea gardens. © 2018 Society of Chemical Industry.

Effect of dolomite and biochar addition on N2O and CO2 emissions from acidic tea field soil.

A laboratory study was conducted to study the effects of liming and different biochar amendments on N2O and CO2 emissions from acidic tea field soil. The first experiment was done with three different rates of N treatment; N 300 (300 kg N ha-1), N 600 (600 kg N ha-1) and N 900 (900 kg N ha-1) and four different rates of bamboo biochar amendment; 0%, 0.5%, 1% and 2% biochar. The second experiment was done with three different biochars at a rate of 2% (rice husk, sawdust, and bamboo) and a control and lime treatment (dolomite) and control at two moisture levels (50% and 90% water filled pore space (WFPS)). The results showed that dolomite and biochar amendment significantly increased soil pH. However, only biochar amendment showed a significant increase in total carbon (C), C/N (the ratio of total carbon and total nitrogen), and C/IN ratio (the ratio of total carbon and inorganic nitrogen) at the end of incubation. Reduction in soil NO3--N concentration was observed under different biochar amendments. Bamboo biochar with the rates of 0.5, 1 and 2% reduced cumulative N2O emission by 38%, 48% and 61%, respectively, compare to the control soil in experiment 1. Dolomite and biochar, either alone or combined significantly reduced cumulative N2O emission by 4.6% to 32.7% in experiment 2. Reduction in N2O production under biochar amendment was due to increases in soil pH and decreases in the magnitude of mineral-N in soil. Although, both dolomite and biochar increased cumulative CO2 emission, only biochar amendment had a significant effect. The present study suggests that application of dolomite and biochar to acidic tea field soil can mitigate N2O emissions.

An acid-tolerant ammonia-oxidizing γ-proteobacterium from soil.

Nitrification, the microbial oxidation of ammonia to nitrate via nitrite, occurs in a wide range of acidic soils. However, the ammonia-oxidizing bacteria (AOB) that have been isolated from soil to date are acid-sensitive. Here we report the isolation and characterization of an acid-adapted AOB from an acidic agricultural soil. The isolated AOB, strain TAO100, is classified within the Gammaproteobacteria based on phylogenetic characteristics. TAO100 can grow in the pH range of 5-7.5 and survive in highly acidic conditions until pH 2 by forming cell aggregates. Whereas all known gammaproteobacterial AOB (γ-AOB) species, which have been isolated from marine and saline aquatic environments, are halophiles, TAO100 is not phenotypically halophilic. Thus, TAO100 represents the first soil-originated and non-halophilic γ-AOB. The TAO100 genome is considerably smaller than those of other γ-AOB and lacks several genes associated with salt tolerance which are unnecessary for survival in soil. The ammonia monooxygenase subunit A gene of TAO100 and its transcript are higher in abundance than those of ammonia-oxidizing archaea and betaproteobacterial AOB in the strongly acidic soil. These results indicate that TAO100 plays an important role in the nitrification of acidic soils. Based on these results, we propose TAO100 as a novel species of a new genus, Candidatus Nitrosoglobus terrae.

Time series changes in radiocaesium distribution in tea plants (Camellia sinensis (L.)) after the Fukushima Dai-ichi Nuclear Power Plant accident.

Radiocaesium ((134)Cs and (137)Cs) release following the accident at the Fukushima Dai-ichi Nuclear Power Plant, belonging to the Tokyo Electric Power Company caused severe contamination of new tea plant (Camellia sinensis (L.)) shoots by radiocaesium in many prefectures in eastern Japan. Because tea plants are perennial crops, there is the fear that the contamination might last for a long time. The objectives of this study were to reveal time series changes in the distribution of radiocaesium in tea plants after radioactive fallout and to evaluate the effect of pruning on reduction of radiocaesium concentrations in new shoots growing next year. The experimental tea field was located in Shizuoka, Japan, approximately 400 km away from the Fukushima Dai-ichi Nuclear Power Plant in a southwest direction. Time series changes in radiocaesium concentrations in unrefined tea, a tea product primarily produced for making Japanese green tea, from May 2011 to June 2013 and distribution of radiocaesium in tea plants from May 2011 to May 2012 were monitored. The radiocaesium concentrations in unrefined tea exponentially decreased; the effective half-lives for (134)Cs and (137)Cs were 0.30 and 0.36 y during the first 2 y after the accident, respectively. With time, the highest concentrations of (137)Cs moved from the upper to the lower parts of plants. Medium pruning 2-3 months after the accident reduced the concentration of (137)Cs in new shoots harvested in the first crop season of the following year by 56% compared with unpruned tea plants; thus, pruning is an effective measure for reducing radiocaesium concentration in tea.

Rainwater, soil water, and soil nitrate effects on oxygen isotope ratios of nitrous oxide produced in a green tea (Camellia sinensis) field in Japan.

RATIONALE: The oxygen exchange fraction between soil H(2)O and N(2)O precursors differs in soils depending on the responsible N(2)O-producing process: nitrification or denitrification. This study investigated the O-exchange between soil H(2)O and N(2)O precursors in a green tea field with high N(2)O emissions. METHODS: The rainwater δ(18)O value was measured using cavity ring-down spectrometry (CRDS) and compared with that of soil water collected under the tea plant canopy and between tea plant rows. The intramolecular (15)N site preference in (ß) N(α) NO (SP = δ(15)N(α) - δ(15)N(ß)) was determined after measuring the δ(15)N(α) and δ(15)N(bulk) values using gas chromatography/isotope ratio mass spectrometry (GC/IRMS), and the δ(18) O values of N(2)O and NO(3)(-) were also measured using GC/IRMS. RESULTS: The range of δ(18)O values of rainwater (-11.15‰ to -4.91‰) was wider than that of soil water (-7.94‰ to -5.64‰). The δ(18)O value of soil water at 50 cm depth was not immediately affected by rainwater. At 10 cm and 20 cm depths of soil between tea plant rows, linear regression analyses of δ(18)O-N(2)O (relative to δ(18)O-NO(3)(-)) versus δ(18) O-H(2)O (relative to δ(18)O-NO(3)(-)) yielded slopes of 0.76-0.80 and intercepts of 31-35‰. CONCLUSIONS: In soil between tea plant rows, the fraction of O-exchange between H(2)O and N(2)O precursors was approximately 80%. Assuming that denitrification dominated N(2)O production, the net (18)O-isotope effect for denitrification (NO(3)(-) reduction to N(2)O) was approximately 31-35‰, reflecting the upland condition of the tea field.