ABSTRACT
In this study, NIR quantitative prediction model was established for sensory score and physicochemical components of different varieties and quality grades of Yuezhou Longjing tea. Firstly, L, a, b color factors and diffuse reflection spectral data are collected for each sample. Subsequently, the original spectrum is preprocessed. Three techniques for selecting variables, CARS, BOSS, and SPA, were utilized to extract optimal feature bands. Finally, the spectral data extracted from feature bands were fused with L, a and b color factors to build SVR and PLSR prediction models. enabling the rapid non-destructive discrimination of different varieties and grades of Yuezhou Longjing tea. The outcomes demonstrated that BOSS was the best variable selection technique for sensory score and the distinctive caffeine wavelengths, CARS, however, was the best variable selection technique for catechins distinctive wavelengths. Additionally, the middle-level data fusion-based non-linear prediction models greatly outperformed the linear prediction models. For the prediction models of sensory score, catechins, and caffeine, the relative percent deviation (RPD) values were 2.8, 1.6, and 2.6, respectively, suggesting the good predictive ability of the models. In conclusion, evaluating the quality of the five Yuezhou Longjing tea varieties using near-infrared spectroscopy and data fusion have proved as feasible.
Subject(s)
Catechin , Spectroscopy, Near-Infrared , Spectroscopy, Near-Infrared/methods , Tea/chemistry , Caffeine , Linear Models , Algorithms , Least-Squares AnalysisABSTRACT
To investigate soil fertility status and characteristics of typical tea plantations, we selec-ted 372 typical tea plantations of 21 areas across Jiangxi Province and analyzed the soil nutrient, spatial data, and their correlations with topography, soil type, elevation and plantation age. The results showed that soil pH, organic matter, alkaline nitrogen, available phosphorus, available potassium, total nitrogen, total phosphorus and total potassium of tea plantation in Jiangxi reached 53.9%, 60.1%, 56.1%, 22.9%, 38.5%, 43.7%, 11.1% and 95.5% of indices of high fertility, high efficiency and high yield tea plantation, respectively, with the available phosphorus showing a strong variation. Soil available copper, zinc, iron, manganese and boron reached 76.3%, 74.2%, 96.8%, 73.1% and 0.0% of the first-class standards for soil trace elements, respectively. Tea plantations with highest soil fertility located in central Jiangxi, followed by northeastern and northwestern Jiangxi, and lowest in southern Jiangxi. Soil pH was significantly positively correlated with organic matter, alkaline nitrogen, available phosphorus, available potassium, total nitrogen and total phosphorus but not for total potassium. For different topography, soil fertility was highest in the flat land, followed by the high mountains, and lowest in the mountains and hills. Across different soil types, soil fertility was higher in paddy soil, sandy soil and mountain yellow brown soil, followed by yellow soil, red-yellow soil and purple soil, and lowest in red soil. Soil pH, organic matter and total potassium increased while available phosphorus decreased with altitude. The organic matter, alkaline nitrogen, available phosphorus, total nitrogen and total phosphorus increased, but soil pH decreased with time. In summary, soil fertility of tea plantations in Jiangxi Province was generally good, with high organic matter, total potassium, available copper, zinc, iron and manganese. However, soil was acidic, available phosphorus and total phosphorus content was low, available boron was seriously limited. We suggest increase soil pH and potassium supply in central Jiangxi, increase potassium and nitrogen fertilizer supply in northeastern Jiangxi, increase organic matter and phosphorus fertilizer supply in northwestern Jiangxi, and increase nitrogen, phosphorus and potassium supply combined with organic fertilizers in southern Jiangxi. High mountain tea plantations should enhance available phosphorus and potassium supply. Mountain tea plantations should enhance nitrogen and phosphate supply. Tea plantations with red and yellow soil should increase pH and total potassium supply. Tea plantations with red soil should apply nitrogen, phosphorus and potassium fertilizers combined with organic fertilizers. Tea plantations with yellow soil and mountain yellow brown soil required additional phosphorus supply, and tea plantations with purple soil should increase soil organic matter supply. Tea plantations need to increase dolomite powder, physiological alkaline fertilizers and organic fertilizers to prevent soil acidification.
Subject(s)
Fertilizers , Soil , China , Nitrogen , Phosphorus , TeaABSTRACT
BACKGROUND: Camellia sinensis 'Huangjinju' is an albino tea variety developed recently in China. Young leaves of 'Huangjinju' demonstrate bright yellow when cultivated under natural sunlight, but regreens under reduced light intensity. To elucidate the physiological and molecular mechanisms of this light-sensitive albinism, we compared leaf pigmentation, metabolites, cellular ultrastructure and transcriptome between plants cultured under natural sunlight and shade. RESULTS: Shading treatment doubled the chlorophyll concentration and regreened albino leaves; carotenoid also increased by 30%. Electron microscopy analyses showed that chloroplast not only increased in number but also in size with a complete set of components. In addition, regreened leaves also had a significantly higher concentration of polyphenols and catechins than albino leaves. At transcriptomic level, a total of 507 genes were differentially expressed in response to light condition changes. The most enriched pathways include light harvest protein complex, response to stimuli, oxidation-reduction process, generation of precursor metabolites and energy response. CONCLUSION: The integrated strategy in this study allows a mechanistic understanding of leaf albinism in light-sensitive tea plants and suggested the regulation of gene networks involved in pigmentation and protein processing. Results from this study provide valuable information to this area and can benefit the domestication and artificial breeding to develop new albino tea varieties.