Evidence map›Paper›PMID 35897068›Full record

ArticlePlant methods2022

Evaluating the productivity of ancient Pu'er tea trees (Camellia sinensis var. assamica): a multivariate modeling approach.

Shuqiao Zhang, Wendou Liu, Xinmeng Cheng, Zizhi Wang, Fengjun Yuan, Wengui Wu, Shengxi Liao

Abstract read
In one paragraph

Article in Plant methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shuqiao ZhangInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650216, Yunnan, China. Shuqiao.zhang@anu.edu.au.
Wendou LiuInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650216, Yunnan, China.
Xinmeng ChengInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650216, Yunnan, China.
Zizhi WangInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650216, Yunnan, China.
Fengjun YuanYunnan Institute of Forest Inventory and Planning, Kunming, Yunnan, China.
Wengui WuInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650216, Yunnan, China.
Shengxi LiaoInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650216, Yunnan, China. cafliao@163.com.

Funding

Chinese Academy of Forestry CAFYBB2019ZC007Science and Technology Development Center of State Forestry and Grassland Administration KJZXSA20203
6 · The paper itself

Abstract

backgroundThe demand for productive economic plant resources is increasing with the continued growth of the human population. Ancient Pu'er tea trees [Camellia sinensis var. assamica (J. W. Mast.) Kitam.] are an important ecological resource with high economic value and large interests. The study intends to explore and evaluate critical drivers affecting the species' productivity, then builds formulas and indexes to make predicting the productivity of such valuable plant resources possible and applicable.

resultsOur analysis identified the ideal values of the seven most important environmental variables and their relative contribution (shown in parentheses) to the distribution of ancient Pu'er tea trees: annual precipitation, ca. 1245 mm (28.73%); min temperature of coldest month, ca. 4.2 °C (18.25%); precipitation of driest quarter, ca. 47.5 mm (14.45%); isothermality, 49.9% to 50.4% (14.11%); precipitation seasonality, ca. 89.2 (6.77%); temperature seasonality, ca. 391 (4.46%); and solar radiation, 12,250 to 13,250 kJ m

conclusionsThis model improves the accuracy of the predictions of ancient Pu'er tea tree productivity and will aid future analyses of distribution shifts under climate change, as well as the identification of areas suitable for Pu'er tea tree plantations. Our modeling framework provides insights that facilitate the interpretation of abstract concepts and could be applied to other economically valuable plant resources.

Indexed as

Economical plant resourcesEvaluation indexMaximum information entropyProductivity predictionStructural equation modelingSustainable development

Identifiers

PMID35897068
PMCPMC9327265

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.