Evidence map›Paper›PMID 39471282›Full record

ArticlePlant biotechnology journal2025

Redefining the accumulated temperature index for accurate prediction of rice flowering time in diverse environments.

Xingbing Xu, Qiong Jia, Sijia Li, Julong Wei, Luchang Ming, Qi Yu, Jing Jiang, Peng Zhang, Honglin Yao, Shibo Wang and 4 more

Abstract read
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In one paragraph

Article in Plant biotechnology journal, 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

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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

14 authors.

Xingbing Xu *National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Qiong Jia *Department of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Sijia Li *National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Julong WeiCenter for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA.
Luchang MingNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Qi YuNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Jing JiangNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Peng ZhangState Key Laboratory of Crop Germplasm Innovation and Molecular Breeding, Life Science and Technology Center, China National Seed Group Co., Ltd, Wuhan, China.
Honglin YaoNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Shibo WangDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Chunjiao XiaNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.
Kai WangState Key Laboratory of Crop Germplasm Innovation and Molecular Breeding, Life Science and Technology Center, China National Seed Group Co., Ltd, Wuhan, China.
Zhenyu JiaDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Weibo XieNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China.ORCID https://orcid.org/0000-0002-2768-3572

Funding

Biological Breeding-Major Project 2023ZD04076Earmarked Fund for the China Agriculture Research System CARS-01Foundation of Hubei Hongshan Laboratory 2021hszd005Fundamental Research Funds for the Central Universities 2662023PY002Hubei Provincial Natural Science Foundation of China 2023AFA043National Key Research and Development Program of China 2016YFD0100803National Key Research and Development Program of China 2023YFF1000100National Natural Science Foundation of China 32261143466National Natural Science Foundation of China U23A20189
6 · The paper itself

Abstract

Accurate prediction of flowering time across diverse environments is crucial for effective crop management and breeding. While the accumulated temperature index (ATI) is widely used as an indicator for estimating flowering time, its traditional definition lacks systematic evaluation and genetic basis understanding. Here, using data from 422 rice hybrids across 47 locations, we identified the optimal ATI calculation window as 1 day after sowing to 26 days before flowering. Based on this redefined ATI, we developed a single-parameter model that outperforms the state-of-the-art reaction norm index model in both accuracy and stability, especially with limited training data. We identified 10 loci significantly associated with ATI variation, including two near known flowering time genes and four linked to ecotype differentiation. To enhance practical utility, we developed an efficient flowering time prediction kit using 28 functionally relevant markers, complemented by a user-friendly online tool (http://xielab.hzau.edu.cn/ATI). Our approach can be easily applied to other crops, as ATI is commonly used across various agricultural systems.

Indexed as

FlowersOryzaTemperatureQuantitative Trait Lociaccumulated temperature indexcross‐environmental predictionGWASrice flowering time

Identifiers

PMID39471282
PMCPMC11672749

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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.