Evidence map›Paper›PMID 40551775›Full record

ArticleFrontiers in plant science2025

Spatial patterns and key driving factors of wheat harvest index under irrigation and rainfed conditions in arid regions.

Yongyu Chen, Hengbati Wutanbieke, Dongdong Zhong, Jian Chen, Zhen Huo, Hegan Dong

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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. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Plants (Basel, Switzerland) · 2026
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yongyu Chen *College of Life Sciences, Shihezi University, Shihezi, Xinjiang, China.
Hengbati Wutanbieke *Department of Agriculture and Rural Affairs of Xinjiang, Wulumuqi, Xinjiang, China.
Dongdong ZhongCollege of Life Sciences, Shihezi University, Shihezi, Xinjiang, China.
Jian ChenCollege of Life Sciences, Shihezi University, Shihezi, Xinjiang, China.
Zhen HuoCollege of Life Sciences, Shihezi University, Shihezi, Xinjiang, China.
Hegan DongCollege of Life Sciences, Shihezi University, Shihezi, Xinjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The harvest index (HI), a crucial agronomic trait that measures the ratio of grain yield to aboveground biomass, serves not only as a vital indicator for assessing wheat yield but also as a core parameter for predicting straw resource. It reflects the "source-sink" relationship and biomass allocation strategies in crops. However, the spatial distribution patterns of wheat HI and their key driving factors in arid regions remain unclear. Methods: This study was conducted in Xinjiang, a typical arid region of China, during 2022-2023, involving two years of large-scale systematic sampling. By integrating multidimensional factors such as geographical and climatic conditions, agronomic management practices, and soil nutrient status, methods including correlation analysis, random forest models, structural equation modeling, and linear regression analysis were employed to systematically investigate the spatial distribution characteristics and driving mechanisms of wheat HI under different irrigation regimes in arid regions. Results: The results revealed that: (1) Wheat HI in arid regions exhibited significant spatial heterogeneity (0.43-0.67), with an overall distribution pattern of "central high, peripheral low" and "northern high, southern low." (2) The importance rankings of influencing factors differed between irrigation regimes. For irrigated wheat, the order of importance was: Geographic-climatic factors, soil nutrient factors, agronomic management factors. Comprehensive analysis identified longitude (lon), plant height (H), latitude (lat), and bulk density (BD) as the key drivers of the Harvest Index (HI) in irrigated wheat. In contrast, for rainfed wheat, the order was: soil nutrient factors, Geographic-climatic factors, agronomic management factors, with total nitrogen (TN), available phosphorus(AP), total potassium(TK), and total phosphorus (TP) emerging as critical drivers of HI. Discussion: Irrigation significantly enhanced wheat HI (p < 0.01), and irrigated wheat demonstrated significantly higher HI, yield, and aboveground biomass (AGB) compared to rainfed wheat (p < 0.01). Optimizing phosphorus management could enhance HI in both systems, while irrigation infrastructure development remains vital for yield stability. This study provides a theoretical basis and practical guidance for the synergistic multi-objective approach of "yield increase-irrigation-sustainability" in arid regions wheat production.

Indexed as

arid region wheatdriving factorsharvest index (HI)irrigationspatial heterogeneity

Identifiers

PMID40551775
PMCPMC12183048

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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.