Zhang Yufan, Zha Yuanyuan, Jin Xiuliang, Wang Yu, Qiao Han
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China.
Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Beijing, China.
Front Plant Sci. 2022 Jul 14;13:942110. doi: 10.3389/fpls.2022.942110. eCollection 2022.
Drought-rehydration irrigation has an enhancing impact on rice yield, but the current research on its yield-increasing effect is mainly experimental and empirical, lacking mechanism theoretical support. Image-based machine vision is rapidly developing and can estimate crop physical and chemical properties. A novel image processing method has been purposefully carried out to detect the real-time response shape of rice drought-rehydration. By application of this method, two new types of morphological descriptors were proposed to characterize and quantify the vertical phenotypic heterogeneity of rice, in which the relative height of the plant centroid () locates the growth focus, while the leaf angle distribution model describes the vertical characteristics of the leaf phenotypic traits. We verified the response of the vertical traits to different water treatments through designed experiments. The results showed that the and leaf angle distribution parameters followed divergent trends under water stress, reflecting the drought characteristics of rice at different growth stages. The newly developed indicators were sensitive to drought response at specific growth stages and also efficient for evaluating rice growth, including determination of radiation interception capacity and assessment of nutrient accumulation. Furthermore, through the measurement and analysis of vertical structural traits, we found that a short-term water deficit and reasonable rehydration during the rice heading period could help to extend the spike-growing time and improve photosynthetic efficiency, thus benefiting yield formation.
干湿交替灌溉对水稻产量有增产作用，但目前对其增产效应的研究主要是试验性和经验性的，缺乏机理理论支撑。基于图像的机器视觉技术发展迅速，能够估算作物的理化性质。本文有针对性地开展了一种新型图像处理方法，以检测水稻干湿交替的实时响应形态。通过应用该方法，提出了两种新型形态学描述符来表征和量化水稻的垂直表型异质性，其中植株质心相对高度（）定位生长重心，而叶角分布模型描述叶片表型性状的垂直特征。我们通过设计实验验证了垂直性状对不同水分处理的响应。结果表明，在水分胁迫下，和叶角分布参数呈现不同趋势，反映了水稻不同生育期的干旱特征。新开发的指标对特定生育期的干旱响应敏感，对评估水稻生长也有效，包括辐射截获能力的测定和养分积累的评估。此外，通过对垂直结构性状的测量和分析，我们发现水稻抽穗期短期水分亏缺和合理复水有助于延长穗生长时间，提高光合效率，从而有利于产量形成。
