Evidence map›Paper›PMID 40234468›Full record

ArticleScientific data2025

China's Well-Facilitated Farmland distribution dataset.

Abdusalam Turup, Jun Zhang, Wenchao Ma, Bingxin Ma, Yue Zhang, Zaeem Hassan Akhter, Longhui Li

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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.

Abdusalam TurupState Key Laboratory of Climate System Prediction and Risk Management, Nanjing Normal University, Nanjing, China.ORCID http://orcid.org/0009-0007-7985-850X
Jun ZhangState Key Laboratory of Climate System Prediction and Risk Management, Nanjing Normal University, Nanjing, China.
Wenchao MaState Key Laboratory of Climate System Prediction and Risk Management, Nanjing Normal University, Nanjing, China.
Bingxin MaState Key Laboratory of Climate System Prediction and Risk Management, Nanjing Normal University, Nanjing, China.
Yue ZhangCollege of Geographical Science and Tourism, Xinjiang Normal University, Urumqi, 830054, China.
Zaeem Hassan AkhterState Key Laboratory of Climate System Prediction and Risk Management, Nanjing Normal University, Nanjing, China.
Longhui LiState Key Laboratory of Climate System Prediction and Risk Management, Nanjing Normal University, Nanjing, China. Longhui.Li@njnu.edu.cn.ORCID http://orcid.org/0000-0001-9983-6681

Funding

National Natural Science Foundation of China (National Science Foundation of China) 42471516National Natural Science Foundation of China (National Science Foundation of China) U2003201
6 · The paper itself

Abstract

China has less than 10% of the world's arable land but must feed more than 20% of the global population. Both climate change and farmland degradation pose significant challenges to China's food security. In 2009, Chinese government launched a nationwide, well-facilitated farmland (WFF) construction strategy to improve food production. The ultimate goal is to create 80 million hectare (1.2 billion mu) of WFF by 2030. Timely monitoring and generation of a public WFF dataset are critical for assessing China's food production and security. However, such data are not currently available for research community or industrial sector. By compiling and synthesizing 377 reports and documents released by local authorities, this study created WFF dataset for 2020, covering both prefecture and provincial levels in China. Additionally, the provincial 2030 WFF targets and the current completion rates are included. This dataset has wide range of applications in food security, as well as agricultural water and nutrition managements for researchers and policymakers.

Indexed as

AgricultureFarmsFood SecurityFood SupplyChinaClimate Change

Identifiers

PMID40234468
PMCPMC12000479

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.