scholarly journals Prediction of Drought-Induced Components and Evaluation of Drought Damage of Tea Plants Based on Hyperspectral Imaging

2021 ◽  
Vol 12 ◽  
Author(s):  
Sizhou Chen ◽  
Yuan Gao ◽  
Kai Fan ◽  
Yujie Shi ◽  
Danni Luo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Drought Stress ◽  
Hyperspectral Imaging ◽  
Tea Plant ◽  
Maximum Efficiency ◽  
Tea Leaves ◽  
Physiological And Biochemical Indexes ◽  
Tea Plants ◽  
Physiological And Biochemical ◽  
Drought Damage

Effective evaluation of physiological and biochemical indexes and drought degree of tea plant is an important technology to determine the drought resistance ability of tea plants. At present, the traditional detection method of tea drought stress is mainly based on physiological and biochemical detection, which is not only destructive to tea plants, but also time-consuming and laborious. In this study, through simulating drought treatment of tea plant, hyperspectral camera was used to obtain spectral data of tea leaves, and three machine learning models, namely, support vector machine (SVM), random forest (RF), and partial least-squares (PLS) regression, were used to model malondialdehyde (MDA), electrolyte leakage (EL), maximum efficiency of photosystem II (Fv/Fm), soluble saccharide (SS), and drought damage degree (DDD) of tea leaves. The results showed that the competitive adaptive reweighted sampling (CARS)-PLS model of MDA had the best effect among the four physiological and biochemical indexes (Rcal = 0.96, Rp = 0.92, RPD = 3.51). Uninformative variable elimination (UVE)-SVM model was the best in DDD (Rcal = 0.97, Rp = 0.95, RPD = 4.28). Therefore, through the establishment of machine learning model using hyperspectral imaging technology, we can monitor the drought degree of tea seedlings under drought stress. This method is not only non-destructive, but also fast and accurate, which is expected to be widely used in tea garden water regime monitoring.

scholarly journals Low Caffeine Content in Novel Grafted Tea with Camellia sinensis as Scions and Camellia oleifera as Stocks

2015 ◽  
Vol 10 (5) ◽  
pp. 1934578X1501000 ◽  
Author(s):  
Wei-Wei Deng ◽  
Min Li ◽  
Chen-Chen Gu ◽  
Da-Xiang Li ◽  
Lin-Long Ma ◽  
...  
Keyword(s):  
Camellia Sinensis ◽  
Expression Patterns ◽  
Tea Plant ◽  
Protein Accumulation ◽  
Tea Leaves ◽  
Qrt Pcr ◽  
Caffeine Content ◽  
Caffeine Synthase ◽  
Specificity And Sensitivity ◽  
Tea Plants

Caffeine, a purine alkaloid, is a major secondary metabolite in tea leaves. The demand for low caffeine tea is increasing in recent years, especially for health reasons. We report a novel grafted tea material with low caffeine content. The grafted tea plant had Camellia sinensis as scions and C. oleifera as stocks. The content of purine alkaloids was determined in the leaves of one-year-old grafted tea plants by HPLC. We also characterized caffeine synthase (CS), a key enzyme involved in caffeine biosynthesis in tea plants, at the expression level. The expression patterns of CS were examined in grafted and control leaves by Western blot, using a self-prepared polyclonal antibody with high specificity and sensitivity. The expression of related genes ( TCS1, tea caffeine synthase gene, GenBank accession No. AB031280; sAMS, SAM synthetase gene, AJ277206; TIDH, IMP dehydrogenase gene, EU106658) in the caffeine biosynthetic pathway was investigated by qRT-PCR. HPLC showed that the caffeine content was only 38% as compared with the non-grafted tea leaves. Immunoblotting analysis showed that CS protein decreased by half in the leaves of grafted tea plants. qRT-PCR revealed no significant changes in the expression of two genes in the upstream pathway ( sAMS and TIDH), while the expression of TCS1 was greatly decreased (50%). Taken together, these data revealed that the low caffeine content in the grafted tea leaves is due to low TCS1 expression and CS protein accumulation.

scholarly journals A study of tea leaves drying using dehumidification process and regeneration of liquid desiccant in a closed-cycle dehumidification-humidification

2018 ◽  
Vol 159 ◽  
pp. 02025 ◽  
Author(s):  
Eflita Yohana ◽  
Mohammad Endy Yulianto ◽  
Shofwan Bahar ◽  
Azza Alifa Muhammad ◽  
Novi Laura Indrayani
Keyword(s):  
Absolute Humidity ◽  
Tea Plant ◽  
Regeneration Process ◽  
Drying Process ◽  
Liquid Desiccant ◽  
Tea Leaves ◽  
Saturation Point ◽  
Air Stream ◽  
Tea Plants ◽  
Tea Leaf

Tea plants in Indonesia are derived from Carmelia sinensis var. assamica which contain catechin in quite high amount compared with other countries tea plant. Green tea is made by inactivating the oxidase / phenolase enzyme that presents in the fresh tea leaf buds from tea garden, by using hot steam to prevent the oxidation of the catechins. Drying process to reduce the moisture of tea, one of the method is by utilizing the dry air from dehumidification process. Liquid desiccant made from 50% concentration of CaCl2, the temperature is lowered to 10 °C and sprayed into the air stream which contains water vapor by using a 0.2 mm spraying nozzle so that mass transfer and latent heat occur in the dehumidifier. The result of air dehumidification process used for drying tea leaves. The air is able to dry the tea leaves from the weight of 58 grams to 47 grams. Then the liquid desiccant dehumidification process will be streamed into the humidifier, where the liquid desiccant regeneration process will have change into the initial concentration. The result of air humidification process has an average absolute humidity rise of 0.07 g/kg. The liquid desiccant regeneration process that happened continuously reaching the saturation point at 280 minutes. It can be concluded that the process of dehumidification-humidification is a fairly effective method for drying the tea leaves.

scholarly journals Metabolism of Gallic Acid and Its Distributions in Tea (Camellia sinensis) Plants at the Tissue and Subcellular Levels

2020 ◽  
Vol 21 (16) ◽  
pp. 5684 ◽  
Author(s):  
Xiaochen Zhou ◽  
Lanting Zeng ◽  
Yingjuan Chen ◽  
Xuewen Wang ◽  
Yinyin Liao ◽  
...  
Keyword(s):  
Gallic Acid ◽  
Camellia Sinensis ◽  
Tea Plant ◽  
Plant Diseases ◽  
Tea Leaves ◽  
Specialized Metabolites ◽  
Tea Plants ◽  
Mg Content ◽  
Ga Content

In tea (Camellia sinensis) plants, polyphenols are the representative metabolites and play important roles during their growth. Among tea polyphenols, catechins are extensively studied, while very little attention has been paid to other polyphenols such as gallic acid (GA) that occur in tea leaves with relatively high content. In this study, GA was able to be transformed into methyl gallate (MG), suggesting that GA is not only a precursor of catechins, but also can be transformed into other metabolites in tea plants. GA content in tea leaves was higher than MG content—regardless of the cultivar, plucking month or leaf position. These two metabolites occurred with higher amounts in tender leaves. Using nonaqueous fractionation techniques, it was found that GA and MG were abundantly accumulated in peroxisome. In addition, GA and MG were found to have strong antifungal activity against two main tea plant diseases, Colletotrichum camelliae and Pseudopestalotiopsis camelliae-sinensis. The information will advance our understanding on formation and biologic functions of polyphenols in tea plants and also provide a good reference for studying in vivo occurrence of specialized metabolites in economic plants.

Effects of Simulated Acid Rain and Aluminum Enrichment on Growth and Photosynthesis of Tea Seedlings

2012 ◽  
Vol 610-613 ◽  
pp. 181-185 ◽  
Author(s):  
Xiao Hua Duan ◽  
Xiao Fei Hu ◽  
Fu Sheng Chen ◽  
Ze Yuan Deng
Keyword(s):  
Acid Rain ◽  
Chlorophyll Content ◽  
Combined Treatment ◽  
Tea Plant ◽  
Simulated Acid Rain ◽  
Tea Leaves ◽  
Tea Production ◽  
Al Addition ◽  
Tea Plants ◽  
Photosynthesis Capacity

The effects of simulated acid rain and aluminum (Al) addition on growth and photosynthesis physiology of tea plants (Camellia sinensis L.) were studied with tea seedlings in a hydroculture experiment. Results showed that the growth of tea plant, chlorophyll content, and photosynthesis (Pn) of tea leaves were better in the treatments of suitable Al addition (10 mg/L and/or 20 mg/L) than the treatments without Al addition and higher Al addition (30 mg/L). The growth of tea plant increased with increasing acidity of acid rain, while the leaves of tea plant showed more chlorophyll content and higher Pn at the treatment of pH 4.0 than pH 5.0 and pH 3.0 acid solutions. The growth of tea plant, chlorophyll content and Pn were the best at the combined treatment of suitable Al addition (10~20 mg/L) and moderate acidity of acid rain (pH 4.0), while the slowest at the combined treatment of 30 mg/L Al and pH 3.0 acid rain. These results suggested that suitable Al and moderate acidity of acid rain are helpful to increase tea production by increasing photosynthesis capacity.

scholarly journals Decision Making in the Tea Leaves Diseases Detection Using Mamdani Fuzzy Inference Method

2018 ◽  
Vol 12 (3) ◽  
pp. 1273 ◽  
Author(s):  
Arif Ridho Lubis ◽  
Santi Prayudani ◽  
Muharman Lubis ◽  
Al Khowarizmi
Keyword(s):  
Decision Making ◽  
Fuzzy Inference ◽  
Tea Plant ◽  
Previous Method ◽  
Tea Leaves ◽  
Small Tree ◽  
Tea Production ◽  
Functional Hierarchy ◽  
Tea Plants ◽  
Degree Slope

The tea plants (Camellia Sinensis) are small tree species that use leaves and leaf buds to produce tea harvested through a monoculture system. It is an agriculture practice to cultivate one types of crop or livestock, variety or breed on a farm annually. Moreover, the emergence of pests, pathogens and diseases cause serious damages to tea plants significantly to its productivity and quality to optimum worst. All parts of the tea plant such as leaves, stems, roots, flowers and fruits are exposed to these harm lead to loss of yield 7 until 10% per year. The intensity of these attacks vary greatly on particular climate, the degree slope and the plant material used. Therefore, this study analyzes tea leaves as a common part used in recipes to create unique taste and flavor in tea production, especially in agro-industry. The decision making method used is Fuzzy Mamdani Inference as one of model with functional hierarchy with initial input based on established criteria. Fuzzy logic will provide tolerance to the set of value, so that small changes will not result in significant category differences, only affect the membership level on the variable value. Previous method using probabilities have shown 78% tea leaves have been attacked by category C (Gray Blight) while using Mamdani indicated 86% of tea leaves have been infected. In this case, this result pointed out that Fuzzy Mamdani Inferences have more optimal result compare to the previous method.

scholarly journals Response to the Cold Stress Signaling of the Tea Plant (Camellia sinensis) Elicited by Chitosan Oligosaccharide

Agronomy ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 915 ◽  
Author(s):  
Yingying Li ◽  
Qiuqiu Zhang ◽  
Lina Ou ◽  
Dezhong Ji ◽  
Tao Liu ◽  
...  
Keyword(s):  
Low Temperature ◽  
Cold Stress ◽  
Soluble Sugar ◽  
Tea Plant ◽  
Chitosan Oligosaccharide ◽  
Stress Signaling ◽  
Molecular Response ◽  
Tea Leaves ◽  
Sod Activity ◽  
Tea Plants

Cold stress caused by a low temperature is a significant threat to tea production. The application of chitosan oligosaccharide (COS) can alleviate the effect of low temperature stress on tea plants. However, how COS affects the cold stress signaling in tea plants is still unclear. In this study, we investigated the level of physiological indicators in tea leaves treated with COS, and then the molecular response to the cold stress of tea leaves treated with COS was analyzed by transcriptomics with RNA-Sequencing (RNA-Seq). The results show that the activity of superoxide dismutase (SOD) activity, peroxidase (POD) activity, content of chlorophyll and soluble sugar in tea leaves in COS-treated tea plant were significantly increased and that photosynthesis and carbon metabolism were enriched. Besides, our results suggest that COS may impact to the cold stress signaling via enhancing the photosynthesis and carbon process. Our research provides valuable information for the mechanisms of COS application in tea plants under cold stress.

Chloride and amino acids are associated with K+-alleviated drought stress in tea (Camellia sinesis)

2020 ◽  
Vol 47 (5) ◽  
pp. 398 ◽  
Author(s):  
Xianchen Zhang ◽  
Honghong Wu ◽  
Jingguang Chen ◽  
Linmu Chen ◽  
Xiaochun Wan
Keyword(s):  
Amino Acids ◽  
Drought Stress ◽  
Tea Plant ◽  
Limiting Factors ◽  
Factors Affecting ◽  
Chlorophyll Contents ◽  
Yield And Quality ◽  
Drought Tolerant ◽  
Tea Plants

Drought is one of the main limiting factors affecting tea plant yield and quality. Previous studies have reported that K+ (potassium) application significantly alleviated drought-induced damage in tea plants. However, the intrinsic mechanisms underlying K+-alleviated drought stress are still obscure. In our study, two contrasting varieties, Taicha12 (drought tolerant) and Fuyun6 (drought sensitive), were used to investigate the intrinsic mechanisms behind K+-alleviated drought stress in tea plants. In the present study, we compared with the case of tea plants under drought: higher water and chlorophyll contents were found in drought-stressed tea plants with an external K+ supply, confirming the role of externally supplied K+ in mitigating drought stress. We also found that an adequate K+ supply promoted Cl– accumulation in the mesophyll of Taicha12 (drought tolerant) over that of in Fuyun6 (drought sensitive). Moreover, Gly, Cys, Lys and Arg were not detected in Fuyun6 under ‘Drought’ or ‘Drought + K+’ conditions. Results showed that an exogenous supply of Arg and Val significantly alleviated drought-induced damage in Fuyun6, suggesting their role in K+-alleviated drought stress in tea plants. Collectively, our results show that chloride and amino acids are important components associated with K+-alleviated drought stress in tea plants.

scholarly journals Relationship between the activity of guaiacol peroxidase and the content of photosynthetic pigments in tea leaves

10.5219/1401 ◽  
2020 ◽  
Vol 14 ◽  
pp. 1020-1026
Author(s):  
Nataliia Platonova ◽  
Oksana Belous
Keyword(s):  
Photosynthetic Pigments ◽  
Redox Reactions ◽  
Vegetation Period ◽  
Tea Plant ◽  
Guaiacol Peroxidase ◽  
Tea Leaves ◽  
Low Intensity ◽  
Pigment Complex ◽  
Tea Plants ◽  
Green Pigments

The dynamics of guaiacol peroxidase and photosynthetic pigments in 3-leaf sprouts (flushes) of tea plants were studied. The presence of declines and peaks in the activity of the enzyme associated with the meteorological conditions of each month was noted. It is shown that there is a direct relationship between the increase in enzyme activity and hydrothermal factors. The most significant correlation was found between the activity of GPO in a 3-leaf tea flush and the amount of precipitation (r = 0.86). The highest activity of guaiacol peroxidase during the entire vegetation period is distinguished by the Sochi variety and form 582. The lowest activity was observed in forms 3823 and 2264, which indicates a low intensity of redox reactions in these plants in stressful situations. Determining the dynamics of the pigment complex revealed its dependence on hydrothermal factors. Studies have shown that precipitation is a significant factor affecting the pigment complex of tea plants. It was found that the largest amount of green pigments is synthesized by leaves at the beginning of active vegetation (May). The participation of the pigment apparatus in the adaptation of the tea plant is directly related to carotenoids, the increase in the number of carotenoids coincides with the period of drought. In the content of photosynthetic pigments and the activity of guaiacol peroxidase manifest genotypic features. The revealed patterns are common to all tea plants.

scholarly journals Exogenous abscisic acid induces on lipid and flavonoid metabolism of tea plant under drought stress

2019 ◽  
Author(s):  
Zhongshuai Gai ◽  
Yu Wang ◽  
Yiqian Ding ◽  
Wenjun Qian ◽  
Hui Xie ◽  
...  
Keyword(s):  
Abscisic Acid ◽  
Lipid Metabolism ◽  
Drought Stress ◽  
Tca Cycle ◽  
Chlorophyll Synthesis ◽  
Tea Plant ◽  
Flavonoid Biosynthesis ◽  
Regulation Mechanism ◽  
Tea Leaves ◽  
Exogenous Aba

Abstract Background: Abscisic acid (ABA) is an important phytohormone responsible for activating drought resistance, but the regulation mechanism of exogenous ABA on tea plants under drought stress was rarely reported. Results: The results showed that the exogenous ABA significantly induced the metabolic pathways of tea leaves under drought stress, including the chlorophyll synthesis, photosynthesis, sucrose and starch metabolism, TCA cycle, glycolysis, lipid metabolism and flavonoids biosynthesis. In which, the exogenous ABA could up-regulated the genes related to lipid metabolism and flavonoid biosynthesis, including LPCAT , ALDH, FLS, CHI, DFR, and down-regulated the genes related to lipid metabolism and flavonoid biosynthesis, including FATB, EKI, DGK , PAL, 4CL . The exogenous ABA could also increase the contents of flavone, anthocyanins, flavonol, isoflavone of tea leaves under drought stress, including delphinidin 3-O-glucosidewere, cyanidin 3-O-rutinoside, kaempferitrin, sakuranetin, prunetin, kaempferol, and decrease the contents of glycerophospholipids, glycerolipids and fatty acids of tea leaves under drought stress, including LysoPE 14:0, LysoPE 16:0, LysoPE 18:0, LysoPE 18:1, LysoPC 15:1 and LysoPC 16:0. And there were strong correlations between the genes and metabolites. Conclusions: The results suggested that the exogenous ABA could alleviate the damages of tea leaves under drought stress through inducing the expressions of the genes and altering the contents of metabolites in response to drought stress. The data also provide a good foundation for further research on the roles of the genes and metabolites in response to ABA.

scholarly journals Diseases Classification for Tea Plant Using Concatenated Convolution Neural Network

2019 ◽  
Vol 13 (2) ◽  
Author(s):  
Dikdik Krisnandi ◽  
Hilman F. Pardede ◽  
R. Sandra Yuwana ◽  
Vicky Zilvan ◽  
Ana Heryana ◽  
...  
Keyword(s):  
Neural Network ◽  
Crop Production ◽  
Object Identification ◽  
Tea Plant ◽  
Plant Diseases ◽  
Disease Detection ◽  
Learning Technology ◽  
Tea Leaves ◽  
Early Disease Detection ◽  
Tea Plants

Plant diseases can cause a significant decrease in tea crop production. Early disease detection can help to minimize the loss. For tea plants, experts can identify the diseases by visual inspection on the leaves. However, providing experts to deal with disease identification may be very costly. The machine learning technology can be implemented to provide automatic plant disease detection. Currently, deep learning is state-of-the-art for object identification in computer vision. In this study, the researchers propose the Convolutional Neural Network (CNN) for tea disease detections. The researchers focus on the implementation of concatenated CNN, namely GoogleNet, Xception, and Inception-ResNet-v2, for this task. About 4727 images of tea leaves are collected, comprising of three types of diseases that commonly occur in Indonesia and a healthy class. The experimental results confirm the effectiveness of concatenated CNN for tea disease detections. The accuracy of 89.64% is achieved.

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