Understanding the population dynamics and spatial variability of tea plantation

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Keywords: Geostatistics, Correlation, Tea cultivation, Population, Crop modelling, Land use changes


Abstract


Tea, made from Camellia sinensis leaves, is the most widely consumed beverage after water. Hence, the tea industry, and consequently tea plantation, is rapidly expanding worldwide. Furthermore, since the quality and safety of raw tea leaves are essential parameters for processing tea and related products, mapping the population dynamics of tea plantations has become necessary. Previous studies that analysed tea plantation dynamics in eastern India using satellite imaging reported an expansion in tea plantation area with demographic explosion, deforestation, flood shifting, workforce immigration and urbanisation. However, in China, concentration index modelling and the industry’s barycentre theorem revealed that increase in area, low cost of labour and land and high yield were the main contributors towards enhanced tea productivity. Moreover, spatial distribution of theaflavin and thearubigin affecting black tea quality in different geographical regions of India was investigated using multivariate and geostatistical techniques. Further, Semivariogram and nugget/sill ratio were used to determine the spatial variation of tea quality parameters in different regions. Geostatistical analysis revealed the spatial variability in soil samples of different regions in India, which can be used for best management of tea plantation. Moreover, spatial and quantitative distribution models of different mineral elements in tea plants and edaphic factors were established by multiple linear regression analysis and Kriging interpolation models. Thus, to promote sustainable tea plantations and appropriate land use policies to safeguard economic and social benefits to the people and development of the tea industry, assessment of tea population dynamics in other tea producing regions is required.

Graphical abstract


Geostatistics, Correlation, Tea cultivation, Population, Crop modelling, Land use changes


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Acknowledgements


The authors thank the Director, CSIR-Institute of Himalayan Bioresource Technology, Palampur, India, for infrastructure and support. A.K. thanks to the UGC, GOI (NTA Ref. No.: 191620063807) for providing SRF. The authors acknowledge the financial support provided by CSIR (MLP-201) and DBT (BT/PR45280/NER/95/1918/2022). This manuscript represents CSIR-IHBT communication no. 5234.


Author Information


Kumari Anita
Division of Biotechnology, CSIR-Institute of Himalayan Bioresource Technology, Palampur, India
anitakumarii.som@gmail.com