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通过遥感特征定义适应地中海环境的硬粒小麦理想型。

Defining durum wheat ideotypes adapted to Mediterranean environments through remote sensing traits.

作者信息

Gracia-Romero Adrian, Vatter Thomas, Kefauver Shawn C, Rezzouk Fatima Zahra, Segarra Joel, Nieto-Taladriz María Teresa, Aparicio Nieves, Araus José Luis

机构信息

Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Barcelona, Spain and AGROTECNIO (Center for Research in Agrotechnology), Lleida, Spain.

Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain.

出版信息

Front Plant Sci. 2023 Sep 5;14:1254301. doi: 10.3389/fpls.2023.1254301. eCollection 2023.

Abstract

An acceleration of the genetic advances of durum wheat, as a major crop for the Mediterranean region, is required, but phenotyping still represents a bottleneck for breeding. This study aims to define durum wheat ideotypes under Mediterranean conditions by selecting the most suitable phenotypic remote sensing traits among different ones informing on characteristics related with leaf pigments/photosynthetic status, crop water status, and crop growth/green biomass. A set of 24 post-green revolution durum wheat cultivars were assessed in a wide set of 19 environments, accounted as the specific combinations of a range of latitudes in Spain, under different management conditions (water regimes and planting dates), through 3 consecutive years. Thus, red-green-blue and multispectral derived vegetation indices and canopy temperature were evaluated at anthesis and grain filling. The potential of the assessed remote sensing parameters alone and all combined as grain yield (GY) predictors was evaluated through random forest regression models performed for each environment and phenological stage. Biomass and plot greenness indicators consistently proved to be reliable GY predictors in all of the environments tested for both phenological stages. For the lowest-yielding environment, the contribution of water status measurements was higher during anthesis, whereas, for the highest-yielding environments, better predictions were reported during grain filling. Remote sensing traits measured during the grain filling and informing on pigment content and photosynthetic capacity were highlighted under the environments with warmer conditions, as the late-planting treatments. Overall, canopy greenness indicators were reported as the highest correlated traits for most of the environments and regardless of the phenological moment assessed. The addition of carbon isotope composition of mature kernels was attempted to increase the accuracies, but only a few were slightly benefited, as differences in water status among cultivars were already accounted by the measurement of canopy temperature.

摘要

作为地中海地区的主要作物,硬粒小麦的基因改良需要加速,但表型分析仍是育种的一个瓶颈。本研究旨在通过在不同的表型遥感性状中选择最适合的性状来定义地中海条件下的硬粒小麦理想型,这些性状反映了与叶片色素/光合状态、作物水分状况以及作物生长/绿色生物量相关的特征。在连续3年的时间里,对一组24个绿色革命后的硬粒小麦品种在西班牙一系列纬度的特定组合所构成的19种广泛环境中进行了评估,这些环境处于不同的管理条件(水分制度和播种日期)下。因此,在开花期和灌浆期对红-绿-蓝和多光谱衍生植被指数以及冠层温度进行了评估。通过对每个环境和物候阶段建立的随机森林回归模型,评估了单独的以及所有组合的评估遥感参数作为籽粒产量(GY)预测指标的潜力。在两个物候阶段测试的所有环境中,生物量和小区绿度指标一直被证明是可靠的GY预测指标。对于产量最低的环境,花期水分状况测量的贡献更高,而对于产量最高的环境,灌浆期的预测效果更好。在较温暖条件的环境下,如晚播处理,灌浆期测量的、反映色素含量和光合能力的遥感性状更为突出。总体而言,无论评估的物候时刻如何,冠层绿度指标在大多数环境中都被报告为相关性最高的性状。尝试添加成熟籽粒的碳同位素组成以提高准确性,但只有少数略有受益,因为冠层温度的测量已经考虑了品种间的水分状况差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7126/10508639/d0b46aef2604/fpls-14-1254301-g001.jpg

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