Evidence map›Paper›PMID 39860919›Full record

ArticleSensors (Basel, Switzerland)2025

Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US.

Sayantan Sarkar, Javier M Osorio Leyton, Efrain Noa-Yarasca, Kabindra Adhikari, Chad B Hajda, Douglas R Smith

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

6 authors.

Sayantan SarkarTexas A&M AgriLife Blackland Research and Extension Center, Temple, TX 76502, USA.ORCID 0000-0003-2680-7200
Javier M Osorio LeytonTexas A&M AgriLife Blackland Research and Extension Center, Temple, TX 76502, USA.ORCID 0000-0003-4573-4932
Efrain Noa-YarascaTexas A&M AgriLife Blackland Research and Extension Center, Temple, TX 76502, USA.ORCID 0000-0002-5228-8486
Kabindra AdhikariUnited States Department of Agriculture-Agriculture Research Service, Grassland Soil and Water Research Laboratory, Temple, TX 76502, USA.ORCID 0000-0002-1365-7015
Chad B HajdaUnited States Department of Agriculture-Agriculture Research Service, Grassland Soil and Water Research Laboratory, Temple, TX 76502, USA.
Douglas R SmithUnited States Department of Agriculture-Agriculture Research Service, Grassland Soil and Water Research Laboratory, Temple, TX 76502, USA.

Funding

United States Department of Agriculture NR213A750023C012
6 · The paper itself

Abstract

Efficient and reliable corn (

Indexed as

Machine LearningRemote Sensing TechnologySoilZea maysAgricultureAlgorithmsUnited StatesSoilcornensemble methodsmachine learningmaizevegetation indicesyield prediction

Identifiers

PMID39860919
PMCPMC11769266

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.