scholarly journals The Distribution of Phosphorus Forms in Wuyi Rock Region and Its Effect on Tea Quality-Related Constituents in Tea Garden Soilil

Author(s):  
Hongmeng Ye ◽  
Guoping Li ◽  
Xuyin Yuan ◽  
Huan He ◽  
Hao Yang ◽  
...  
2014 ◽  
Vol 39 (2) ◽  
pp. 209-212
Author(s):  
Lin LI ◽  
Ming LI ◽  
Dong-cai TAO ◽  
Zhong-hua LIU ◽  
Jian-xiong LIU ◽  
...  

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 619
Author(s):  
Sadeeka Layomi Jayasinghe ◽  
Lalit Kumar

Even though climate change is having an increasing impact on tea plants, systematic reviews on the impact of climate change on the tea system are scarce. This review was undertaken to assess and synthesize the knowledge around the impacts of current and future climate on yield, quality, and climate suitability for tea; the historical roots and the most influential papers on the aforementioned topics; and the key adaptation and mitigation strategies that are practiced in tea fields. Our findings show that a large number of studies have focused on the impact of climate change on tea quality, followed by tea yield, while a smaller number of studies have concentrated on climate suitability. Three pronounced reference peaks found in Reference Publication Year Spectroscopy (RYPS) represent the most significant papers associated with the yield, quality, and climate suitability for tea. Tea yield increases with elevated CO2 levels, but this increment could be substantially affected by an increasing temperature. Other climatic factors are uneven rainfall, extreme weather events, and climate-driven abiotic stressors. An altered climate presents both advantages and disadvantages for tea quality due to the uncertainty of the concentrations of biochemicals in tea leaves. Climate change creates losses, gains, and shifts of climate suitability for tea habitats. Further studies are required in order to fill the knowledge gaps identified through the present review, such as an investigation of the interaction between the tea plant and multiple environmental factors that mimic real-world conditions and then studies on its impact on the tea system, as well as the design of ensemble modeling approaches to predict climate suitability for tea. Finally, we outline multifaceted and evidence-based adaptive and mitigation strategies that can be implemented in tea fields to alleviate the undesirable impacts of climate change.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroto Yamashita ◽  
Rei Sonobe ◽  
Yuhei Hirono ◽  
Akio Morita ◽  
Takashi Ikka

AbstractSpectroscopic 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.


Author(s):  
Shashi Nandar Kumar ◽  
Kumar Vaibhav ◽  
Banajit Bastia ◽  
Vishwajeet Singh ◽  
Meenakshi Ahluwalia ◽  
...  

Author(s):  
Debasish B. Krishnatreya ◽  
Niraj Agarwala ◽  
Sarvajeet Singh Gill ◽  
Tirthankar Bandyopadhyay
Keyword(s):  

2021 ◽  
Vol 43 (4) ◽  
Author(s):  
Liping Zhang ◽  
Menghan Li ◽  
Xin Li ◽  
Peng Yan ◽  
Lan Zhang ◽  
...  

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