Evidence map›Paper›PMID 38075626›Full record

ArticleData in brief2023

From climate to crop: Unveiling the impact of agro-climate dataset on rice yield in Cotabato Province.

Reymark D Delena, Marivic S Tangkeko, Joseph C Sieras

Abstract read
In one paragraph

Article in Data in brief, 2023. 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

3 authors.

Reymark D DelenaDepartment of Information Sciences, College of Information and Computing Sciences, Mindanao State University, Marawi City, Philippines.
Marivic S TangkekoDepartment of Information Technology, College of Computer Studies, De La Salle University, Manila City, Philippines.
Joseph C SierasDepartment of Information Sciences, College of Information and Computing Sciences, Mindanao State University, Marawi City, Philippines.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This data article presents a dataset that analyzes the trends in climatic factors and rice yield in Cotabato Province, a key contributor to the country's rice output. The dataset was collected from the Office of the Provincial Agriculturist and NASA's POWER Prediction Of Worldwide Energy Resources (POWER) dataset agro-climate dataset from 2007 to 2021. Moreover, the data was processed using Extract, Transform, and Loading (ETL) method, and multivariate linear regression analysis was conducted to identify the agro-climates that significantly influence the production of irrigated and rainfed rice. Further, the explanatory factors that significantly influence the production of rice were determined and presented in an Analytical Dashboard. The dataset has great reuse potential for predictive analytics research at the municipal level, which can provide more detailed insights into the agro-climates of different municipalities in Cotabato Province. Moreover, the dataset can also be used to distribute different varieties of rice that can withstand the effects of climate change to the municipalities of Cotabato. Overall, this dataset provides valuable insights into the relationship between agro-climate and rice production in Cotabato Province and can inform future decision-making and resource allocation in the region.

Indexed as

Analytical dashboardClimate datasetCotabato ProvinceData VisualizationIrrigated and rainfed rice production

Identifiers

PMID38075626
PMCPMC10700579

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.