Evidence map›Paper›PMID 40107352›Full record

ArticleJournal of advanced research2026

Mitigating life-cycle multiple environmental burdens while increasing ecosystem economic benefit and crop productivity with regional universal nitrogen strategy.

Zhi Yao, Xingbang Wang, Wei Zhang, Dunyi Liu, Wushuai Zhang, Xiaopeng Gao, Xinping Chen

Abstract read
In one paragraph

Article in Journal of advanced research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Zhi YaoCollege of Resources and Environment, Yunnan Agricultural University, Kunming 650201, China; Key Laboratory of Low-carbon Green Agriculture, Ministry of Agriculture and Rural Affairs, College of Resources and Environment, Academy of Agricultural Sciences, Interdisciplinary Research Center for Agriculture Green Development in Yangtze River Basin, Southwest University, Chongqing 400715, China.
Xingbang WangKey Laboratory of Low-carbon Green Agriculture, Ministry of Agriculture and Rural Affairs, College of Resources and Environment, Academy of Agricultural Sciences, Interdisciplinary Research Center for Agriculture Green Development in Yangtze River Basin, Southwest University, Chongqing 400715, China.
Wei ZhangKey Laboratory of Low-carbon Green Agriculture, Ministry of Agriculture and Rural Affairs, College of Resources and Environment, Academy of Agricultural Sciences, Interdisciplinary Research Center for Agriculture Green Development in Yangtze River Basin, Southwest University, Chongqing 400715, China.
Dunyi LiuKey Laboratory of Low-carbon Green Agriculture, Ministry of Agriculture and Rural Affairs, College of Resources and Environment, Academy of Agricultural Sciences, Interdisciplinary Research Center for Agriculture Green Development in Yangtze River Basin, Southwest University, Chongqing 400715, China.
Wushuai ZhangKey Laboratory of Low-carbon Green Agriculture, Ministry of Agriculture and Rural Affairs, College of Resources and Environment, Academy of Agricultural Sciences, Interdisciplinary Research Center for Agriculture Green Development in Yangtze River Basin, Southwest University, Chongqing 400715, China. Electronic address: wszhang@swu.edu.cn.
Xiaopeng GaoDepartment of Soil Science, University of Manitoba, Winnipeg MBR3T2N2, Canada.
Xinping ChenKey Laboratory of Low-carbon Green Agriculture, Ministry of Agriculture and Rural Affairs, College of Resources and Environment, Academy of Agricultural Sciences, Interdisciplinary Research Center for Agriculture Green Development in Yangtze River Basin, Southwest University, Chongqing 400715, China. Electronic address: chenxp2017@swu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNitrogen fertiliser is critical for increasing crop yields worldwide, but excessive use causes significant N losses in various forms and subsequent environmental issues, such as greenhouse gas (GHG) emissions. Establishing regional universal nitrogen strategy (RUNs) is indispensable for technology adoption, resource conservation, and pollution mitigation in crop production.

objectivesThis study aims to develop a regional universal nitrogen fertilizer strategy to address variations in N application effectiveness, balancing agricultural productivity with environmental and eco-economic benefits.

methodsWe conducted a total of 48 site-year field experiments including no nitrogen application (Control), farmers' practice (FP), and the implementation of the RUNs with optimized nitrogen recommended formulas and one-off application method.

resultsThe RUNs significantly increased yields by 5.9%, 12%, and 11% for grain, sweet, and silage maize, respectively, compared with FP. Further, RUNs reduced life-cycle potentials of global warming, soil acidification, water eutrophication, and energy depletion by 22-45%, 63-76%, 51-73%, and 46-67%, respectively. The RUNs increased economic benefits by 11%-58.2%, and net ecosystem-economic benefits by 11.3-77.5%, particularly through the reduction of nitrogen fertiliser and labour-associated agricultural and ecological costs.

conclusionWe propose that the RUNs reconciled crop yield, resource efficiency, environmental impacts, and ecosystem economic benefits, demonstrating a regional sustainable N strategy for global food security and resource conservation.

Indexed as

Crop productivityEcosystem economic benefitsEnvironmental impactLife-cycle assessmentRegional universal nitrogen strategy

Identifiers

PMID40107352
PMCPMC12766216

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.