Evidence map›Paper›PMID 40904875›Full record

ArticleFrontiers in plant science2025

Extraction of maize growth stages in the Sanjiang Plain of China from 2003 to 2022 and their spatio-temporal changes in response to meteorological variables.

Huichun Ye, Bingrui Zhang, Shanyu Huang, Chaojia Nie, Peng Wei, Minghao Qin, Hongye Wang

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Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Huichun YeInternational Research Center of Big Data for Sustainable Development Goals, Beijing, China.
Bingrui ZhangInternational Research Center of Big Data for Sustainable Development Goals, Beijing, China.
Shanyu HuangBeijing Keda Tongrui Technology Co., Ltd, Beijing, China.
Chaojia NieInternational Research Center of Big Data for Sustainable Development Goals, Beijing, China.
Peng WeiInternational Research Center of Big Data for Sustainable Development Goals, Beijing, China.
Minghao QinInternational Research Center of Big Data for Sustainable Development Goals, Beijing, China.
Hongye WangCultivated Land Quality Monitoring and Protection Center, Ministry of Agriculture and Rural Affairs, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

How to quickly monitor the growth process of maize on a large scale is crucial for regional maize growth assessment, yield estimation, and farmland management. This article takes the Sanjiang Plain in Northeast China as the research area, which is the main grain production area in China. Using MODIS NDVI time series data and Savitzky Golay and Whittaker filtering techniques, a remote sensing extraction method for key growth stages of maize (i.e., jointing stage, tasseling stage, and maturity stage) was established. The spatiotemporal characteristics of these growth stages from 2003 to 2022 were analyzed, alongside their meteorological influences. Results show the Whittaker filter achieves high accuracy, with errors under 8 days. Jointing stages typically fall between June 9

Indexed as

agricultural remote sensinggrowth stagemaizeSanjiang Plainspatio-temporal variation

Identifiers

PMID40904875
PMCPMC12401967

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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.