Using Machine Learning Methods Combined with Vegetation Indices and Growth Indicators to Predict Seed Yield of

Chengming Ou, Zhicheng Jia, Shoujiang Sun, Jingyu Liu, Wen Ma, Juan Wang, Chunjiao Mi, Peisheng Mao

Abstract read

In one paragraph

Article in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it

0cells of the map it votes in

3citing 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

3 citing papers in PubMed.

Fast Forward the Future: What Are the Key Drivers in Intelligent Sensing for Agriculture?Plants (Basel, Switzerland) · 2026
Article
Reinforcement learning based dynamic vegetation index formulation for rice crop stress detection using satellite and mobile imagery.Scientific reports · 2025
Article
Integrated multi-omics analysis reveals the role of nitrogen application in seed storage protein metabolism and improvement of inferior grains in smooth bromegrass.Frontiers in plant science · 2025
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

8 authors.

Chengming OuForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.

Zhicheng JiaForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.

Shoujiang SunForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.ORCID 0000-0003-0675-7306

Jingyu LiuForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.

Wen MaForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.

Juan WangForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.

Chunjiao MiForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.

Peisheng MaoForage Seed Laboratory, College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China.ORCID 0000-0003-3261-0949

Funding

CARS-34 CARS-34

6 · The paper itself

Abstract

Smooth bromegrass (

Indexed as

leaf nitrogen contentrandom forest modelremote vegetation indexseed yield predictionsmooth bromegrass

Identifiers

PMID38592838

DOI10.3390/plants13060773

PMCPMC10974845

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.