Evidence map›Paper›PMID 35901077›Full record

ArticlePloS one2022

ARIMA model forecasting analysis of the prices of multiple vegetables under the impact of the COVID-19.

Lisha Mao, Yin Huang, Xiaofan Zhang, Sijin Li, Xiangni Huang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2022. 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
5.2field-weighted citation impact, top 5% of its field
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, 20 citations in OpenAlex.

  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

5 authors at 1 institution in 1 country.

Lisha MaoSchool of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, Hunan, China.
Yin HuangSchool of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, Hunan, China.ORCID 0000-0001-7370-7259
Xiaofan ZhangSchool of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, Hunan, China.
Sijin LiSchool of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, Hunan, China.
Xiangni HuangSchool of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, Hunan, China.
Central South University of Forestry and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a large agricultural country, China's vegetable prices affect the increase in production and income of farmers and the daily life of urban and rural residents and influence the healthy development of Chinese agriculture. 51,567 vegetable price data of 2020 are analyzed to determine the factors that influence vegetable price fluctuations in two dimensions (vertical and horizontal) in the special context of the COVID-19, and an ARIMA model of short-term price prediction is then employed and evaluated. Based on the factors affecting vegetable prices, the results of the model are further examined. Finally, pertinent suggestions are made for the development of the local vegetable industry in the post-epidemic era.

Indexed as

COVID-19VegetablesAgricultureChinaForecastingHumansIncomeModels, Statistical

Identifiers

PMID35901077
PMCPMC9333317
OpenAlexW4288427501

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.