کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8845285 1617111 2018 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Algorithmic derivation of CO2 assimilation based on some physiological parameters of tea bushes in North-East India
ترجمه فارسی عنوان
الگوریتم مشتق از جذب دی اکسید کربن بر اساس برخی از پارامترهای فیزیولوژیکی بوته چای در هند شمال شرقی
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی
Tea, an evergreen shrub, is commercially cultivated in dense population as bushes in tea gardens. Periodical pruning of tea bushes makes tea plants distinct from other tree plants. Tea bushes have almost constant height throughout their life-time and have more compact canopy as compared to any forest trees. Hence, established methods of elucidating carbon dioxide (CO2) absorption in forest trees could not be employed for measuring CO2 assimilation in tea bushes. In this study, CO2 assimilation potentials of a high-yielding tea cultivar and a better quality producing tea cultivar had been periodically measured by closed-chamber method under field condition. Such type of experiment was not conducted before. This study revealed that tea bushes had potential to assimilate 1243.8-2526.7 kg CO2 ha−1 year−1 and the high yielding tea cultivar absorbed significantly higher amount of CO2 as compared to better quality producing tea cultivar. Several physiological parameters namely number of branches, plucking point density, leaf area and stomatal index were positively correlated to the annual CO2 assimilation by tea bushes. Higher CO2 assimilation in high yielding tea cultivars can be attributed to their larger and dense canopy structure due to more branching, higher plucking point density and higher leaf area. An algorithm has been derived for computing CO2 assimilation in tea bushes by considering the above-mentioned variable as indicators. This will enable to determine CO2 assimilation by tea plantation over a large area by measuring the physiological indicators without exercising in-situ experiments.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Indicators - Volume 91, August 2018, Pages 77-83
نویسندگان
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