Variation of winter wheat phenology dataset in Huang Huai Hai Plain of China from 1981 to 2021

This study presents a comprehensive analysis of winter wheat phenological variations in China's Huang-Huai-Hai Plain (HHHP) from 1981 to 2021, leveraging data from 62 national agrometeorological observation stations. As the world’s largest winter wheat production region, the HHHP contributes over 60% of China’s total output, playing a pivotal role in national food security. Using kernel density estimation (KDE) and univariate linear regression, the dataset characterizes interannual trends in key phenological stages—sowing, emergence, tillering, jointing, booting, heading, flowering, milking, and maturity—along with growth period durations. Results reveal significant shifts in phenological timings and growth stages under climate change, such as advanced heading stages and altered phase lengths, which correlate with temperature increases and extreme weather events. The dataset, comprising 1,120 figures generated via Origin Lab, is publicly available on ScienceDB, providing critical insights for climate adaptation strategies, cultivation optimization, and yield stability. Technical validation confirms the reliability of the data, sourced from standardized, long-term manual observations by trained professionals under China Meteorological Administration protocols. This work offers a foundational resource for understanding climate-crop interactions and guiding sustainable agricultural practices in a warming world.

本研究依托62个国家农业气象观测站的观测数据，对1981至2021年中国黄淮海平原（HHHP）冬小麦物候变化开展了全面分析。作为全球规模最大的冬小麦产区，黄淮海平原的冬小麦产量占全国总产量的60%以上，对国家粮食安全具有举足轻重的支撑作用。本数据集借助核密度估计（KDE）与单变量线性回归方法，刻画了冬小麦关键物候期——播种期、出苗期、分蘖期、拔节期、孕穗期、抽穗期、开花期、乳熟期、成熟期——以及各生育阶段时长的年际变化趋势。研究结果表明，气候变化背景下冬小麦物候期与生育阶段均发生了显著偏移，例如抽穗期提前、生育阶段时长改变，上述变化与气温升高及极端天气事件存在显著相关性。本数据集包含通过Origin Lab生成的1120幅图表，已在科学数据库（ScienceDB）公开共享，可为气候适应策略制定、种植模式优化及产量稳定性保障提供关键理论依据。经技术校验，本数据集源自遵循中国气象局规范、由专业受训人员开展的标准化长期人工观测，数据可靠性得到验证。本研究可为理解气候-作物互作机制、指导变暖背景下可持续农业实践提供重要基础支撑资源。

搜集汇总

背景与挑战

背景概述

该数据集记录了中国黄淮海平原1981至2021年间冬小麦的物候变化，包括播种、出苗、抽穗等关键阶段的时间变化及生长周期长度。数据来源于62个国家级农业气象观测站，通过核密度估计和一元线性回归方法分析，揭示了气候变化对冬小麦物候的显著影响，为农业气候适应和产量稳定提供了重要参考。